Handbook of Research on Globalization, Investment, and Growth: Implications of Confidence and Governance 9781466682740, 9781466682757

Citation preview

Handbook of Research on Globalization, Investment, and Growth-Implications of Confidence and Governance Ramesh Chandra Das Katwa College, India

A volume in the Advances in Finance, Accounting, and Economics (AFAE) Book Series

Managing Director: Managing Editor: Director of Intellectual Property & Contracts: Acquisitions Editor: Production Editor: Development Editor: Typesetter: Cover Design:

Lindsay Johnston Austin DeMarco Jan Travers Kayla Wolfe Christina Henning Brandon Carbaugh Tucker Knerr Jason Mull

Published in the United States of America by Information Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA, USA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com Copyright © 2015 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Handbook of research on globalization, investment, and growth-implications of confidence and governance / Ramesh Chandra Das, editor. pages cm Includes bibliographical references and index. ISBN 978-1-4666-8274-0 (hardcover) -- ISBN 978-1-4666-8275-7 (ebook) 1. Finance--Developing countries. 2. Investments--Developing countries. 3. Economic development--Developing countries. I. Das, Ramesh Chandra, 1973HG195.H36 2015 337.09172’4--dc23 2015003782 This book is published in the IGI Global book series Advances in Finance, Accounting, and Economics (AFAE) (ISSN: 2327-5677; eISSN: 2327-5685) British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the authors, but not necessarily of the publisher. For electronic access to this publication, please contact: [email protected].

Advances in Finance, Accounting, and Economics (AFAE) Book Series Ahmed Driouchi Al Akhawayn University, Morocco

ISSN: 2327-5677 EISSN: 2327-5685 Mission

In our changing economic and business environment, it is important to consider the financial changes occurring internationally as well as within individual organizations and business environments. Understanding these changes as well as the factors that influence them is crucial in preparing for our financial future and ensuring economic sustainability and growth. The Advances in Finance, Accounting, and Economics (AFAE) book series aims to publish comprehensive and informative titles in all areas of economics and economic theory, finance, and accounting to assist in advancing the available knowledge and providing for further research development in these dynamic fields.

Coverage • • • • • • • • • •

Economics of Risks, Uncertainty, Ambiguity, and Insurance Interest Rates and Annuities Taxes Internet Banking Economic Indices and Quantitative Economic Methods Theoretical Issues in Economics, Finance, and Accounting Applied economics Fiscal Policy Borrowing and Lending Economic Theory

IGI Global is currently accepting manuscripts for publication within this series. To submit a proposal for a volume in this series, please contact our Acquisition Editors at [email protected] or visit: http://www.igi-global.com/publish/.

The Advances in Finance, Accounting, and Economics (AFAE) Book Series (ISSN 2327-5677) is published by IGI Global, 701 E. Chocolate Avenue, Hershey, PA 17033-1240, USA, www.igi-global.com. This series is composed of titles available for purchase individually; each title is edited to be contextually exclusive from any other title within the series. For pricing and ordering information please visit http://www. igi-global.com/book-series/advances-finance-accounting-economics/73685. Postmaster: Send all address changes to above address. Copyright © 2015 IGI Global. All rights, including translation in other languages reserved by the publisher. No part of this series may be reproduced or used in any form or by any means – graphics, electronic, or mechanical, including photocopying, recording, taping, or information and retrieval systems – without written permission from the publisher, except for non commercial, educational use, including classroom teaching purposes. The views expressed in this series are those of the authors, but not necessarily of IGI Global.

Titles in this Series

For a list of additional titles in this series, please visit: www.igi-global.com

Promoting Socio-Economic Development through Business Integration Shalini Kalia (IMT Ghaziabad, India) Bhavna Bhalla (IMT Ghaziabad, India) Lipi Das (IMT Ghaziabad, India) and Neeraj Awasthy (IMT Ghaziabad, India) Business Science Reference • copyright 2015 • 337pp • H/C (ISBN: 9781466682597) • US $210.00 (our price) Handbook of Research on Sustainable Development and Economics Ken D. Thomas (Auburn University, USA) Business Science Reference • copyright 2015 • 462pp • H/C (ISBN: 9781466684331) • US $325.00 (our price) Green Economic Structures in Modern Business and Society Andrei Jean-Vasile (Petroleum-Gas University of Ploiesti, Romania) Ion Raluca Andreea (Bucharest Academy of Economic Studies, Romania) and Turek Rahoveanu Adrian (University of Agronomic Sciences and Veterinary Medicine, Bucharest, Romania) Business Science Reference • copyright 2015 • 325pp • H/C (ISBN: 9781466682191) • US $195.00 (our price) Handbook of Research on Behavioral Finance and Investment Strategies Decision Making in the Financial Industry Zeynep Copur (Hacettepe University, Turkey) Business Science Reference • copyright 2015 • 525pp • H/C (ISBN: 9781466674844) • US $245.00 (our price) Agricultural Management Strategies in a Changing Economy Gabriel Popescu (Bucharest Academy of Economic Studies, Romania) and Andrei Jean-Vasile (Petroleum - Gas University of Ploiesti, Romania) Business Science Reference • copyright 2015 • 439pp • H/C (ISBN: 9781466675216) • US $225.00 (our price) Handbook of Research on In-Country Determinants and Implications of Foreign Land Acquisitions Evans Osabuohien (Covenant University, Nigeria & German Development Institute, Germany) Business Science Reference • copyright 2015 • 430pp • H/C (ISBN: 9781466674059) • US $265.00 (our price) Handbook of Research on Strategic Developments and Regulatory Practice in Global Finance Özlem Olgu (Koç University, Turkey) Hasan Dinçer (Istanbul Medipol University, Turkey) and Ümit Hacıoğlu (Istanbul Medipol University, Turkey) Business Science Reference • copyright 2015 • 433pp • H/C (ISBN: 9781466672888) • US $235.00 (our price) Regional Economic Integration and the Global Financial System Engin Sorhun (Istanbul 29 Mayis University, Turkey) Ümit Hacıoğlu (Istanbul Medipol University, Turkey) and Hasan Dinçer (Istanbul Medipol University, Turkey)

701 E. Chocolate Ave., Hershey, PA 17033 Order online at www.igi-global.com or call 717-533-8845 x100 To place a standing order for titles released in this series, contact: [email protected] Mon-Fri 8:00 am - 5:00 pm (est) or fax 24 hours a day 717-533-8661

Editorial Advisory Board Maniklal Adhikary, The University of Burdwan, India Rajib Bhattacharya, Hooghly Mohsin College, India Amalendu Bhunia, Kalyani University, India Rajagopaldhar Chakrabarti, Calcutta University, India Gagari Chakrabarty, Presidency University, India Saptarshi Chakrabarty, Panchakot Mahavidyalay, WB, India Saumya Chakraborty, Visva Bharati, India Tonmoy Chatterjee, West Bengal, India Amaresh Das, Southern University at New Orleans, USA Hasan Dincer, Beykent University, Turkey Soumyananda Dinda, SKB University, WB, India Jayanta Dwibedi, BKC College, West Bengal, India Umit Hacioglu, Beykent University, Turkey Sebak Jana, Vidyasagar University, WB, India Asim Kumar Karmakar, Jadavpur University, India Adetiloye Kehinde, Covenant University, Nigeria Arindam Laha, The University of Burdwan, India Debabrata Mukhopadhyay, WBSU, India Chironjib Neogi, Indian Statistical Institute, Kolkata, India Olanrewaju Olaoye, Lincoln University, UK Sudhakar Patra, Ravenshaw University, Odisha, India Kamal Ray, Katwa College, WB, India Kiranjit Sett, WB State University, India Mandeep Singh, GNK College, Yamunanagar, Haryana, India Shefali Virkar, University of Oxford, UK



List of Contributors

Adetiloye, Kehinde Adekunle / Covenant University, Nigeria.......................................................... 416 Adhikary, Maniklal / The University of Burdwan, India................................................................... 191 Agu, Chukwuma / University of Nigeria, Nigeria............................................................................... 91 Balasubramaniam, Nagarajan / Bharathiar University, India......................................................... 229 Bhattacharyya, Rajib / Hooghly Mohsin College, India..................................................................... 62 Chakrabarty, Gagari / Presidency University, India......................................................................... 325 Chatterjee, Tonmoy / Sidho-Kanho-Birsha University, India.............................................................. 44 Das, Amaresh / Southern University at New Orleans, USA................................................................... 1 Das, Arindam / The University of Burdwan, India............................................................................. 257 Das, Koushik / Chandias Mahavidyalaya, India................................................................................ 109 Das, Ramesh Chandra / Katwa College, India............................................................................... 1,135 Das, Utpal / Katwa College, India...................................................................................................... 135 Dinda, Soumyananda / Sidho-Kanho-Birsha University, India.................................................... 44,379 Gupta, Anita Chattopadhyay / Muralidhar Girls’ College, India.................................................... 176 Jana, Sebak K. / Vidyasagar University, India................................................................................... 275 Karmakar, Asim K. / Jadavpur University, India............................................................................. 275 Laha, Arindam / The University of Burdwan, India.......................................................................... 399 Mandal, Chhanda / Muralidhar Girls’ College, India....................................................................... 176 Mukhopadhyay, Debabrata / West Bengal State University, India..................................................... 24 Munir, Qaiser / Universiti Malaysia Sabah, Malaysia....................................................................... 155 Nandi, Devanjali / George College, India.......................................................................................... 257 Neogi, Chiranjib / Indian Statistical Institute, Kolkata, India........................................................... 355 Olaoye, Olanrewaju / University of Lincoln, UK............................................................................... 218 Orji, Anthony / University of Nigeria, Nigeria..................................................................................... 91 Patra, Sudhakar / Ravenshaw University, India................................................................................ 437 Raju, A. Subramanyam / Pondicherry University, India.................................................................. 229 Ray, Kamal / Katwa College, India.................................................................................................... 135 Sett, Kiranjit / West Bengal State University, India............................................................................. 24 Sinha, Dyuti / The Bhawanipur Education Society College, India..................................................... 191 Srinivasan, Rajamanickam / Pondicherry University, India............................................................ 229 Vargas-Hernández, José G. / University of Guadalajara, Mexico.................................................... 451 Virkar, Shefali / University of Oxford, UK......................................................................................... 296

 

Table of Contents

Foreword............................................................................................................................................... xx Preface.................................................................................................................................................. xxi Acknowledgment............................................................................................................................... xxix Section 1 Growth and Economic Confidence Chapter 1 Does Consumers’ Confidence Cause Consumption Spending? An Analysis of Selected Countries under the Purview of Global Financial Crisis.......................................................................................... 1 Ramesh Chandra Das, Katwa College, India Amaresh Das, Southern University at New Orleans, USA Chapter 2 The Role of Market Sentiment in Stock Price Movements: An Indian Experience.............................. 24 Kiranjit Sett, West Bengal State University, India Debabrata Mukhopadhyay, West Bengal State University, India Chapter 3 Consumer Sentiment and Confidence during Post-Crisis 2008: A Panel Data Analysis...................... 44 Tonmoy Chatterjee, Sidho-Kanho-Birsha University, India Soumyananda Dinda, Sidho-Kanho-Birsha University, India Chapter 4 Post Crisis Performance and Confidence of the Indian Economy......................................................... 62 Rajib Bhattacharyya, Hooghly Mohsin College, India Chapter 5 Market Fundamentals and Stock Pricing in Nigeria: Further Evidence from Micro and Macro Analysis.................................................................................................................................................. 91 Chukwuma Agu, University of Nigeria, Nigeria Anthony Orji, University of Nigeria, Nigeria





Chapter 6 Globalization, Consumer’s Preference, and Welfare in India: Results from CGE Model................... 109 Koushik Das, Chandias Mahavidyalaya, India Section 2 Governance, Institution, and Growth Chapter 7 Governance and Capital Accumulation under Globalization: A Study on Some  Selected Countries............................................................................................................................... 135 Kamal Ray, Katwa College, India Ramesh Chandra Das, Katwa College, India Utpal Das, Katwa College, India Chapter 8 Corruption, Size of Government, and Economic Growth: Evidence from Global Data..................... 155 Qaiser Munir, Universiti Malaysia Sabah, Malaysia Chapter 9 Dimensions of Good Governance: An Empirical Study...................................................................... 176 Chhanda Mandal, Muralidhar Girls’ College, India Anita Chattopadhyay Gupta, Muralidhar Girls’ College, India Chapter 10 The Inter-Linkage between Governance and Poverty: Evidences from SAARC Countries................ 191 Maniklal Adhikary, The University of Burdwan, India Dyuti Sinha, The Bhawanipur Education Society College, India Chapter 11 Sustaining Governance: The Case for Leadership............................................................................... 218 Olanrewaju Olaoye, University of Lincoln, UK Chapter 12 Governance Evolution and Impact on Economic Growth: A South Asian Perspective...................... 229 A. Subramanyam Raju, Pondicherry University, India Nagarajan Balasubramaniam, Bharathiar University, India Rajamanickam Srinivasan, Pondicherry University, India Chapter 13 Corporate Governance and Firm Performance: A Study of Listed Firms in India.............................. 257 Devanjali Nandi, George College, India Arindam Das, The University of Burdwan, India



Chapter 14 Globalization, Governance, and Food Security: The Case of BRICS................................................. 275 Sebak K. Jana, Vidyasagar University, India Asim K. Karmakar, Jadavpur University, India Section 3 Globalization, Investment, Growth, and Global Financial Crisis Chapter 15 Globalisation, Investment, and Global Economic Growth: Examining the Causes of Recent Banking Crises..................................................................................................................................... 296 Shefali Virkar, University of Oxford, UK Chapter 16 Waves of Financial Crisis: History Repeats Itself?.............................................................................. 325 Gagari Chakrabarty, Presidency University, India Chapter 17 Effect of Recent Global Financial Crisis on South Asian Economy with Special Reference to  India..................................................................................................................................................... 355 Chiranjib Neogi, Indian Statistical Institute, Kolkata, India Chapter 18 Factors Determining Foreign Direct Investment Inflow to Nigeria during Pre-Financial Crisis: An Empirical Investigation........................................................................................................................ 379 Soumyananda Dinda, Sidho-Kanho-Birsha University, India Chapter 19 Impact of Microfinance on Poverty in the Context of Global Financial Crisis: A Cross Country Analysis in South Asia......................................................................................................................... 399 Arindam Laha, The University of Burdwan, India Chapter 20 Business Investment and the Nigerian Investible Capital Haemorrhage in Financial Crises.............. 416 Kehinde Adekunle Adetiloye, Covenant University, Nigeria Chapter 21 FDI, Urbanization, and Economic Growth Linkages in India and China............................................ 437 Sudhakar Patra, Ravenshaw University, India



Chapter 22 Institutional and Cultural Implications of Mexican SMEs Internalization.......................................... 451 José G. Vargas-Hernández, University of Guadalajara, Mexico Compilation of References................................................................................................................ 474 About The Contributors.................................................................................................................... 516 Index.................................................................................................................................................... 523

Detailed Table of Contents

Foreword............................................................................................................................................... xx Preface.................................................................................................................................................. xxi Acknowledgment............................................................................................................................... xxix Section 1 Growth and Economic Confidence Chapter 1 Does Consumers’ Confidence Cause Consumption Spending? An Analysis of Selected Countries under the Purview of Global Financial Crisis.......................................................................................... 1 Ramesh Chandra Das, Katwa College, India Amaresh Das, Southern University at New Orleans, USA The present chapter addresses the financial crisis issue in light of its effect upon the interplay between the consumers’ confidence upon an economy and consumption spending of the households of the same economy. A simple correlation analysis for the quarterly data from January 1996 to October 2012 shows that the occurrence of the crisis has badly affected the consumers’ confidence and consumption spending of the developed countries. Emerging countries have performed well despite the crisis. Also that majority of the developed countries with a few developing ones produce the result of bidirectional causalities whereas in leading emerging countries, consumption spending is making a change in confidence in a ‘causal’ sense for the entire period of study. During pre-crisis phase the result show that the leading developed countries experience unidirectional causal relation from consumption to confidence. But in the post crisis phase seven out of twenty countries produce a line of causation going from consumption to confidence and nine countries fail to show any line of causation.





Chapter 2 The Role of Market Sentiment in Stock Price Movements: An Indian Experience.............................. 24 Kiranjit Sett, West Bengal State University, India Debabrata Mukhopadhyay, West Bengal State University, India In an efficient capital market, the prices of securities always fully reflect all available information implying that prices always reflect the fundamental values. When there is under reaction or over reaction to new information, competition among the arbitrageurs quickly brings the price of an asset back to its fair value. But, if the asymmetry of information about a stock is high and there is a ‘limit to arbitrage’, sentiment of the noise traders is likely to influence the price of that stock. This chapter aims at studying the role of market sentiment, during the period which starts with June 2003 and ends with July 2011, in influencing the return from investment in small capitalization stocks listed on Indian stock exchanges. We have found the presence of ARCH (1) in the time series on returns. Market sentiment, rate of interest and inflation are found to have significant influence on return from investment in small capitalization stocks. The presence of month effects in returns from such stocks has also been detected. Chapter 3 Consumer Sentiment and Confidence during Post-Crisis 2008: A Panel Data Analysis...................... 44 Tonmoy Chatterjee, Sidho-Kanho-Birsha University, India Soumyananda Dinda, Sidho-Kanho-Birsha University, India This chapter attempts to find out the impact of recent recession on the consumption pattern through consumer confidence index (CCI) of selected developed and developing economies. This chapter examines how the macroeconomic variables like growth rate, inflation, unemployment rate and debt-GDP ratio etc. influence the consumer’s confidence during 1996-2012, in which the crisis occurred in 2008. Moreover, in this chapter we have explained the role of consumptions sentiment in terms of consumer confidence regarding future expectation. Apart from that, from the panel data set of 11 countries, we have found that more or less all the economies including the United States have experienced downward movement of consumer’s confidence in the presence of the great recession of 2008-2009. Chapter 4 Post Crisis Performance and Confidence of the Indian Economy......................................................... 62 Rajib Bhattacharyya, Hooghly Mohsin College, India The recent global financial crisis is viewed as a glaring example of limitless pursuit of deregulation of financial markets and failure of global corporate governance. Though the global economic slowdown had its epicenter in the US but its impact is being witnessed in all major economies of the world. The present chapter seeks to analyze the post crisis experience of the Indian economy as compared to the global economic performances, using various macroeconomic indicators as output, employment, inflation, current account balance, movement in real effective exchange rate and inflow of FDI. It is based on a statistical analysis using secondary time-series data and is based on the Exogenous Structural Break Model developed by Perron (1989). Finally it tries to highlight the confidence of the economic agents based on some well recognized confidence indices (for e.g. Business Confidence Index, Consumer Confidence Index, FDI Confidence Index etc.) during the post-crisis period.



Chapter 5 Market Fundamentals and Stock Pricing in Nigeria: Further Evidence from Micro and Macro Analysis.................................................................................................................................................. 91 Chukwuma Agu, University of Nigeria, Nigeria Anthony Orji, University of Nigeria, Nigeria This chapter investigates the relationship between stock pricing and behaviour of the stock market on one hand and micro and macroeconomic fundamentals in the Nigerian economy on the other from 1980-2009 using both primary and secondary data. Results from the primary survey indicate that the key drivers of share prices were neither broad macroeconomic indicators nor key indicators of the health of the firm. Prices were clearly shown to be much above levels that could have been determined by such indicators as posted profits of firms, amounts paid out as dividend and its regularity. Secondary data analysis equally show that the relationship between actual levels of the all share price index for the period of our analysis and during the financial crisis were not driven by “expected” variables. While its fundamental values are driven by monetary and relative price variables, actual values are driven by external sector variables and prices. Chapter 6 Globalization, Consumer’s Preference, and Welfare in India: Results from CGE Model................... 109 Koushik Das, Chandias Mahavidyalaya, India The purpose of the present chapter is to analyse general equilibrium effects of different trade liberalization policies for India under imperfectly competitive market structure. Since present day world trade is much akin towards the increasing returns to scale and market structure oriented industry behaviour, we have considered monopolistically competitive market structure for our analysis. Computable General Equilibrium (CGE) modelling has been applied as it seems to be relevant methodology for policy simulation. Consumer’s love for variety and increasing returns to scale present in the sectors involving large fixed costs, are strong determinants of consumer’s as well as producer’s business confidence. Our study reveals that increased welfare gain due to trade and openness is not much larger as compared to standard perfect competition scenario as the scale economy benefit is predominant only in few sectors like capital goods industries and not prominently visible in large agricultural and informal manufacturing sectors. Section 2 Governance, Institution, and Growth Chapter 7 Governance and Capital Accumulation under Globalization: A Study on Some  Selected Countries............................................................................................................................... 135 Kamal Ray, Katwa College, India Ramesh Chandra Das, Katwa College, India Utpal Das, Katwa College, India Sustaining good governance is necessarily required for all countries in the world after the phase of globalization, especially when almost the entire world is struck by the global financial crisis originated from the USA. The present study tries to concentrate upon establishing an interlinkage among capital accumulation of a sample of countries with principal components of governance for the time period



1996-2012. Correlation analysis along with the Granger Causality test is applied to identify directions of causalities among capital formation and all the governance indicators. The study observes an inverse relation between governance indicators and capital accumulation for majority of the developing countries and in some cases positive relations for developed countries. Besides, it is observed that there are causal relations from capital formation to governance in most of the developed countries whereas in most of the developing countries there are causalities from governance to capital formation. Chapter 8 Corruption, Size of Government, and Economic Growth: Evidence from Global Data..................... 155 Qaiser Munir, Universiti Malaysia Sabah, Malaysia A big size government fosters corruption, which can lead to inefficiencies and resource costs that impede economic progress. In this chapter, it is argued that much of the previous studies have focused only on detecting the linear effects of corruption on growth. This study, therefore adopts the Threshold Autoregression (TAR) approach by using an annual panel data of 100 countries during 1990-2012 to evaluate any existence of a non-linear relationship. This study presents evidence that suggests the existence of a hump shaped (nonlinear) relationship between corruption and long-run economic growth. When the government size is small (11.518%), corruption positively affects economic growth. Whereas, when the government final consumption expenditure (% of GDP) is larger than 19.027%, corruption negatively affects economic growth. Furthermore, the result indicates that a non-linear relationship of the ‘Armey curve’ exists in our panel of countries. Thus, a government should investigate whether government size is over-expanding or not when designing its public finance policy. Chapter 9 Dimensions of Good Governance: An Empirical Study...................................................................... 176 Chhanda Mandal, Muralidhar Girls’ College, India Anita Chattopadhyay Gupta, Muralidhar Girls’ College, India Effectiveness of governance is realised through its responses to any financial crisis. This was put in question as the Great Recession affected the core economies severely. This study empirically investigated the relationship between accountability, corruption, and government effectiveness during the period 2002-2012. Our main purpose was to highlight the sizable gap that exists in the performance literature on cross-country studies especially against the changing economic world scenario. A comparison of the World Bank governance indicators between three countries chosen on the basis of income differentials and hence different adaptive characteristics of each country to the economic recession has been studied. The behavior of the governance indicators in the context of the world has been examined against the background of the shock that the depression had brought and the resilience factors embedded within the indicators in the face of the shocks were studied. Chapter 10 The Inter-Linkage between Governance and Poverty: Evidences from SAARC Countries................ 191 Maniklal Adhikary, The University of Burdwan, India Dyuti Sinha, The Bhawanipur Education Society College, India This chapter aims at assessing the impact of governance on the country’s economic and human well-being in the selected South Asian countries. The study finds that for the countries-India, Pakistan, Bangladesh, Sri Lanka and Nepal, over the years 1990-2012, the growing rate of GDP per capita (PPP) and growing



employment to population ratio has a significant negative impact on the Global Hunger Index as expected. Also the panel regression run for the eight SAARC countries over the period 2007-13 to find out the impact of each of the six governance indicators on the per capita GDP showed that political stability and absence of violence, government effectiveness and regulatory quality have very strong and significant role in augmenting the economic output besides the remaining indicators. The trends for each of the indicators across countries over time show that except Bhutan, none of the countries are exhibiting good performance of the governance indicators. Chapter 11 Sustaining Governance: The Case for Leadership............................................................................... 218 Olanrewaju Olaoye, University of Lincoln, UK This chapter has three core aims. First, to discuss the concepts of governance and leadership while drawing upon key literatures and qualitative data to make sense of the factors that can enable leadership to sustain governance systems. Second, the chapter explores the practice of leadership at the Greater London Authority (GLA) level in the United Kingdom (UK) in order to establish features synonymous with the practice of leadership. Third, the relations between governance and leadership are explored so as to better understand how the latter is employed in sustaining the governance process at the GLA level in the UK. Chapter 12 Governance Evolution and Impact on Economic Growth: A South Asian Perspective...................... 229 A. Subramanyam Raju, Pondicherry University, India Nagarajan Balasubramaniam, Bharathiar University, India Rajamanickam Srinivasan, Pondicherry University, India Governance matters (Kaufman, et al, 1999) for growth is now an accepted dictum. However, there are as many hypotheses as to what constitutes governance as there are researchers in the field. Apart from econometrics, political science provides important insights on factors that influence governance and facilitate growth. This chapter examines the political history and economy of South Asia to determine the features that shaped governance and affected economic growth. It finds that governance in South Asian context evolved through three phases. Using a comparative perspective of GDP growth rates and World Governance Indicators in South Asia and Brazil, it analyzes the relationship between political history and economy in each phase. The findings indicate that political ideologies, stability of regimes and policy continuity hugely influence the institutions of government and economic growth. The chapter also finds that people’s participation in governance would enhance growth and distributive social justice. Chapter 13 Corporate Governance and Firm Performance: A Study of Listed Firms in India.............................. 257 Devanjali Nandi, George College, India Arindam Das, The University of Burdwan, India Ownership structure is considered to be of prime importance in corporate governance of a firm. The ownership structure significantly varies across the nations. The main focus of this chapter is twofold: firstly to see the impact of ownership structure on performance of the firm and secondly to investigate the relationship between stock market performance and ownership structure during the crisis period. Panel data analysis of CNX 200 companies has been done for the time period of 2006-2013.The study



also takes into account the relationship between crisis period stock return and ownership structure. The results of this study reveal a positive relationship of promoter’s shareholding with performance while a negative relationship of performance is found with the non-promoters shareholding. The regression of stock price performance on ownership variable gives a significant negative relationship during the crisis period. Chapter 14 Globalization, Governance, and Food Security: The Case of BRICS................................................. 275 Sebak K. Jana, Vidyasagar University, India Asim K. Karmakar, Jadavpur University, India Food security is a major area of concern for the five nations that constitute BRICS. BRICS countries account for more than 40% of the world population and 25% of world GDP in PPP terms. Besides, these countries have a key role to play in the post-crisis global economy as producer of goods and services, receivers and exporters of capital, and/or consumer market on large potential. More importantly, these ones envisage ways to promote food security and food production in Third World countries by raising agricultural productivity and output via initiatives like the creation of basic agricultural information exchange system of these countries; enhancing investments in the food supply chain; developing a social safety net through conditional income transfer programmes for the poorest of the poor. In this context the present chapter examines the status of food security of BRICS economies in the context of globalization and governance and its implications thereof. Section 3 Globalization, Investment, Growth, and Global Financial Crisis Chapter 15 Globalisation, Investment, and Global Economic Growth: Examining the Causes of Recent Banking Crises..................................................................................................................................... 296 Shefali Virkar, University of Oxford, UK For any economy to be healthy, a strong financial system is required to efficiently move funds from unproductive to productive economic agents. Banks play an important role in this respect as their presence and structure reduces the problems of adverse selection, moral hazard, and asymmetric information. Recent decades have been overshadowed by a series of systemic banking crises that have left many parts of the developing world gasping for breath. In particular, economies like Mexico and the East Asian tigers have been hit hard both during and in the aftermath of such financial misadventures. This chapter thus attempts to examine the causes of banking crises in the light of available evidence. More specifically, the research enumerates and analyses the role of both macroeconomic and microeconomic factors in precipitating such crises through a critical examination of the existing literature, and illustrates each factor with examples from key pan-global financial catastrophes.



Chapter 16 Waves of Financial Crisis: History Repeats Itself?.............................................................................. 325 Gagari Chakrabarty, Presidency University, India Historically, stock-market crashes and the resultant panic have ended in ultimate devastating impact on the real economy. Proper macroeconomic management and accomplishing macroeconomic objectives require, in terms of depth and width, sound health of financial system. Financial fragility is often taken as a prime factor in generating and aggravating crises. Moreover, with extensive economic integration, crises in one market immediately affect others through dynamic interlinkages or “contagion”. Hence, at this juncture, inquiry into market dynamics becomes crucial. This chapter intervenes here focusing on two past significant stock-market crises namely, the dot-com bubble and the melt-down of 2007-08. The chapter found significant volatility transmission channels primarily through past-volatility impacts. In recent era of fluctuation and instability, stock-markets are more integrated through strong and positive innovation and past-volatility impacts. The news-impacts, however, are less intense than past-volatility impacts. Moreover, even with increasing financial integration, there remains a basis for global portfolio diversification. Chapter 17 Effect of Recent Global Financial Crisis on South Asian Economy with Special Reference to  India..................................................................................................................................................... 355 Chiranjib Neogi, Indian Statistical Institute, Kolkata, India Most of the Asian countries were affected adversely for the recent global financial crisis, especially those economies whose growths are largely depended on the external trade. It has been observed over time and again that Indian economy has not been significantly harmed by the waves of global financial and economic crises because of its large domestic market, which can accommodate any external shock. During the phase of shrinking world demand of domestic goods and services, efforts to raise productivity and competitiveness helps countries to protect export market. This chapter investigates the dependence on the external market and the effect of global financial crisis on the trade structure of some Asian countries. Some detail studies will be done for India in respect of compositional changes and productivity and efficiency changes of different industries within manufacturing sector during pre and post crisis period. Efficiency and productivity will be analyzed using frontier model. Chapter 18 Factors Determining Foreign Direct Investment Inflow to Nigeria during Pre-Financial Crisis: An Empirical Investigation........................................................................................................................ 379 Soumyananda Dinda, Sidho-Kanho-Birsha University, India This chapter empirically investigates the determinants of foreign direct investment (FDI) to Nigeria during pre-financial crisis period 1970-2006. This study suggests that the endowment of natural resources, trade intensity, macroeconomic risk factors like inflation and exchange rates are significant determinants of FDI flow to Nigeria. The findings also suggest that in long run market size is not the significant factor for attracting FDI to Nigeria, it contradicts the existing literature. The author’s results indicate that FDI flow to Nigeria is resource-seeking FDI. Results also suggest that trading partner like the UK in NorthSouth (N - S) and China in South-South (S - S) trade relation have strong influence on Nigeria’s natural resource outflow.



Chapter 19 Impact of Microfinance on Poverty in the Context of Global Financial Crisis: A Cross Country Analysis in South Asia......................................................................................................................... 399 Arindam Laha, The University of Burdwan, India The microfinance programme in the South Asia region has proven to be resilient to the shocks of global financial crisis. In fact, cross country experiences in South Asia reveal little impact of the global financial crisis on the penetration of the microfinance programmes to poor households. To explore the impact of microfinance on poverty in the backdrop of global financial crisis, an attempt has been made in this present study to examine the relationship between MFI’s gross portfolio per active borrower and the measures of poverty. Empirical evidences based on Pooled Regression Analysis suggest that gross portfolio per active borrower is negatively and significantly associated with the poverty head count ratio or poverty gap measure, which is consistent with the author’s hypothesis that micro loans reduce poverty. The poverty alleviation role of microfinance in South Asian countries is not changing its dynamics even in post-crisis scenario. Chapter 20 Business Investment and the Nigerian Investible Capital Haemorrhage in Financial Crises.............. 416 Kehinde Adekunle Adetiloye, Covenant University, Nigeria The global financial crises that happened between 2007 and 2010 had deleterious effects on countries across the world including Nigeria with regard to their respective levels of globalisation. This was evidenced with sudden outflows of capital emanating from the capital market that impacted negatively on the banking system. The chapter has adopted a number of variables among which are investment and net portfolio investments and external reserves. The main technique used is the regression (both single and two-stage) the results of which indicate that the investment was not negatively impacted by the portfolio investment but had significantly negative effect on the external reserve and the saving of the country. The chapter recommends a better control of the capital out flows and improvement in the business environment to reduce the capital haemorrhage faced by the Nigerian economy. Chapter 21 FDI, Urbanization, and Economic Growth Linkages in India and China............................................ 437 Sudhakar Patra, Ravenshaw University, India The rapid urbanization and economic growth during new round of globalization is largely due to the flows of Foreign Direct Investment (FDI). In this context the objectives of this chapter is to analyze the causality and linkage among urbanization, GDP and foreign direct investment in China and India with the help of secondary data from 1979 to 2012. It focuses on determinants and pattern of FDI flow in China and India. The study observes a significant positive correlation between urbanization and flow of FDI to a particular region both in China and India. The rate of growth of FDI is significantly influenced by rate of growth of urban population at 10 per cent level of significance and by rate of growth of per capita GDP at 1 percent level of significance. The study also highlights the causality and linkage between urbanization and FDI inflow with evidences from China and India.



Chapter 22 Institutional and Cultural Implications of Mexican SMEs Internalization.......................................... 451 José G. Vargas-Hernández, University of Guadalajara, Mexico The aim of this chapter is to analyze from the perspective of institutionalism if the European Union market is a potential market for the internationalization of Mexican SMEs. This chapter identifies a framework of the current situation of Mexican SMEs, encompassing as the political-economic aspects that govern the cooperative relationship as the normative and cultural factors that impact directly businesses, concluding that the complexity of the European Union resulting from the uniqueness of each of its members is reflected in a set of formal and informal rules that negatively impact on the internationalization of Mexican SMEs to that market. Compilation of References................................................................................................................ 474 About The Contributors.................................................................................................................... 516 Index.................................................................................................................................................... 523

xx

Foreword

I have great pleasure in writing the foreword to this book edited by my former student Ramesh Chandra Das. As a doctoral student he impressed me by his intelligence, the clarity of his logical thinking and very careful attention to detail. All these qualities are adequately reflected in the editorial effort that he has put in for the present volume. The recent global crisis, the worst the capitalist world has ever seen since the Great Depression, has provoked intense rethinking and analysis by economists on nearly every aspect of economic theory and policy. The developing countries, in particular, have realized the need to re-assess and re-orient their position on some major issues of growth and governance in the changed international scenario. There have been significant setbacks in growth for a large number of these economies, including China and India. The worst is over and signs of recovery have appeared, but the need has arisen to take steps to protect oneself against possible recurrence of a catastrophe of similar magnitude in the future. By far the best possible protection is by stimulating growth from within the national economy without over-reliance on external factors. And to achieve that confidence building through long term planning, proper macroeconomic management and good governance is indispensable. This volume brings together between two covers a large number of interesting contributions that address the critical linkages between governance, confidence, investment and growth in the post-crisis global context. The range is truly impressive. Most of the major issues-national as well as international, micro as well as macro- have received probing investigation by authors who hail from a wide diversity of countries. I am confident the volume will enjoy a wide readership. Soumyen Sikdar Indian Institute of Management, India. 3 November, 2014

Soumyen Sikdar is presently holding the post of Professor of Economics in the Indian Institute of Management, Calcutta, India. He has done his graduation and masters respectively from the Presidency College, Kolkata and Calcutta University. He has been awarded Ph. D by University of Minnesota, USA. In early phase of his career he had taught at Presidency College, Burdwan University and Calcutta University. He has been the visiting professor at Indira Gandhi Institute of Development Research, Mumbai, India and Institute of Social and Economic Research at Osaka University, Japan.

 

xxi

Preface

Lured by the contemporary economic and political events both in positive and negative directions and complemented by the publisher, IGI Global, it was in mind to develop such a research outcome in a cooperative manner so that the said economic and political scenarios can be highlighted and their impacts and implications are explained. After a series of screening by the expert teams of the IGI Global the ultimate title of the book was first-rated that would be expected to be capable of covering the original thinking. It was hence, Globalization, Investment and Growth-Implications of Confidence and Governance. The lessons from the recent crisis in the so called developed economies and its aftermath in the rest of the world have compelled the economists, policy makers and governments of different countries to redefine the concept of long run growth states of an economy. The factors that need to be incorporated as crucial elements in analyzing the developmental status of the world economies in the post globalization scenario are the management of good and proper governance as well as to maintain good confidence level of the active economic agents like that of consumers and business houses. Hence the task was to reorient the working of the interlinkages among three prime indicators of developments-Confidence, Governance and Growth/Investment. An economy, to have a stable growth path, should have interlinkages among all three indicators to work in a bidirectional way. That means as the economy grows in quantitative terms the confidence of the economic agents, particularly of the consumers and the business houses, tends to rise. At the same time, if the consumers and business houses have better confidence upon the economy then the growth rate of the overall output will tend to rise. Similarly, if the quality of the governance improves the growth rate of the overall economy will tend to rise and in the reverse way high growth rate of the economy demands active governance by the ruling government of the country. Likewise, as the quality of governance improves the confidence of the economic agents rise and as the level of confidence rises the government should manage to follow active governance. In contrast, if it sounds bad, the impact of such crises travelled throughout the world like an epidemic via trade and service channels. The shares of exports, imports and total trade volumes of USA, France, UK, Germany, Greece, Japan, South Africa, Brazil, etc in world trade have fallen during the phase of 2009-10. There was a remarkable decline in the world trade share of the European Union from 40 per cent in 2008 to 36 per cent in 2010. The same story also is heard for annual growth rates of these countries. There are negative growth rates for USA, UK, France, Germany, Japan, etc for the period 2009-10 but the magnitudes of negative growth rates of Greece aggravates till date. Greece is one of the worst sufferers of the twin crises. But the vibrations of these external shocks could not manage to affect the Asian Giants like China, India; rather they played the role of shock absorber of these crises. China, being front runner in the world trade, has improved, though slightly, in its trade share. India, although possessing a small share in world trade, made itself better off after the crises. The service channels have improved for China 

Preface

and India since there were increasing trends in the remittances of the non-residents of the countries as well as their deposits to the home avenues. The foreign institutional investors (FIIs) moved to India and China as the economies are safe to invest. Hence, the overall outcome is the rising confidence level of the agents of India and China and the agents of foreign nations upon the economies of Asia, particularly upon India and China. At the same time these two economies maintained a sound average growth rate of overall economy amid the crises. It was, thus, necessary to find out empirically the interrelationships among the newly concerned variables-consumer and business confidences, governance, etc. to judge the status of different categories of economies after the crisis and the necessary measures to be taken to save the countries by their own policy makers as per their requirements and available capacities. The issue of trade relations could be justified further and to establish whether bilateral or regional trade was better than open trade all along the countries that might give a signal to the success possibility of the Trade Reform Deal in the Bali WTO summit. After invitation to the potential authors through the official website of the IGI Global and my personal networks for contributions to the said mission through chapter submission on the recommended topics a number of chapters has been shortlisted. All the chapters have attempted to justify their positions in terms of standard quantitative analysis as far as possible. After a double blind peer review system and additional review by me the number of chapters in revised form ultimately turned out to be twenty two with a standard volume. The entire book has been arranged by three different sections in the content to cover the basic themes as addressed in the title. Section 1 highlights the roles of confidence or sentiments of the economic agents upon the economy in general and consumption and investment in particular. It also covers the reverse impact analysis of the positions and performances of economic variables upon the confidence or sentiment of the economic agents. Section 2 throws light upon the inter play between the economic and political indicators and the growth determining factors in different classes of economies in the world. A probable balancing in choosing the classes of countries has been tried by the chapters to convey a message to the academicians and policy makers all round the world. Section 3 covers general issues of global financial crisis and its impacts upon the economic indicators of different countries in the world. Some chapters have tried heavily on the searching the root causes of the crisis and some also analyzed its impacts upon the selected economies. A brief outcome of the chapter contributions are addressed below sequentially. Chapter 1 highlights the issues related to households’ consumptions spending and consumers’ confidence across different countries. It tries to address the financial crisis issue in light of its effect upon the interplay between the consumers’ confidence upon an economy and consumption spending of the households of the same economy. A simple correlation analysis for January 1996 to October 2012 shows that the occurrence of the crisis has badly affected the consumers’ confidence and consumption spending of the developed countries. Emerging countries have performed well despite the crisis. Also that majority of the developed countries with a few developing ones produce the result of bidirectional causalities whereas in leading emerging countries, consumption spending is making a change in confidence in a ‘causal’ sense for the entire period of study. During pre-crisis phase the results show that the leading developed countries experience unidirectional causal relation from consumption to confidence. But in the post crisis phase seven out of twenty countries produce a line of causation going from consumption to confidence and nine countries fail to show any line of causation. xxii

Preface

Chapter 2 throws light upon role of market sentiments on stock price movements in India. To it, in an efficient capital market, the prices of securities always fully reflect all available information implying that prices always reflect the fundamental values. When there is under–reaction or overreaction to new information, competition among the arbitrageurs quickly brings the price of an asset back to its fair value. But, if the asymmetry of information about a stock is high and there is a ‘limit to arbitrage’, sentiment of the noise traders is likely to influence the price of that stock. This paper aims at studying the role of market sentiment, during the period which starts with June 2003 and ends with July 2011, in influencing the return from investment in small capitalization stocks listed on Indian stock exchanges. We have found the presence of ARCH (1) in the time series on returns. Market sentiment, rate of interest and inflation are found to have significant influence on return from investment in small capitalization stocks. The presence of month effects in returns from such stocks has also been detected. Chapter 3 places interests on the relation between consumer sentiments and confidences in light of the effect of the crisis. It specifically attempts to find out the impact of recent recession on the consumption pattern through consumer confidence index (CCI) of selected developed and developing economies. This chapter examines how the macroeconomic variables like growth rate, inflation, unemployment rate and debt-GDP ratio etc influence the consumer’s confidence during 1996-2012, in which the crisis occurred in 2008. Moreover, in this chapter we have explained the role of consumptions sentiment in terms of consumer confidence regarding future expectation. Apart from that, from the panel data set of 11 countries, we have found that more or less all the economies including the United States have experienced downward movement of consumer’s confidence in the presence of the great recession of 2008-2009. Chapter 4 describes post crisis performance and confidence of the Indian economy. According to its view, the recent global financial crisis is widely viewed as a glaring example of limitless pursuit of deregulation of financial markets and failure of global corporate governance at the expense of caution, prudence, due diligence and regulation. Though the global economic slowdown had its epicenter in the US but the contagion is being witnessed in all major economies of the world. The present work seeks to analyze the post crisis experience of the Indian economy as compared to the global economic performances, using various macroeconomic indicators as output, employment, inflation, current account balance, movement in real effective exchange rate and inflow of FDI. It is based on a statistical analysis using secondary time-series data to assess the impact of the global financial crisis on the Indian economy in terms of the Exogenous Structural Break Model developed by Perron (1989). Finally it tries to highlight the confidence of the economic agents based on some well recognized confidence indices (for e.g. Business Confidence Index, Consumer Confidence Index, FDI Confidence Index etc.) during the post-crisis period. Chapter 5 analyzes the role of micro and macro fundamentals on the stock price movements of Nigeria. In reference to it the Nigeria Stock Exchange which has been the toast of investors for nearly a decade started a steep decline in early 2008 even before the rest of the world joined. Market capitalization which peaked at N12.6 trillion as at the first week of March, 2008 quickly nosedived beginning in the second week of March 2008 losing nearly half its value by the end of the same year. Every indicator in the stock market had continued to slide down. As in many other stock markets under the same circumstances, there have been competing arguments as to the cause of the crash. But many of these arguments are not underpinned by strong empirical analyses. Besides, despite its growth and strategic positioning in the African market, the Nigerian capital market has received comparatively little assessment. Consequently, it is not clear that policies for the market are driven by strong understanding of the links between the market and the rest of the economy or more specifically between the market and broad macroeconomic xxiii

Preface

fundamentals as opposed to firm level and institutional variables and/or regulatory loopholes. This work therefore has been set out to systematically study the market with a view to understanding the different roles of market fundamentals and bubbles in the determination of stock pricing and market movements. Using both primary and secondary data, this chapter aims to show the relationship between stock pricing and behaviour of the stock market on one hand and micro and macroeconomic fundamentals in the Nigerian economy on the other from 1980-2009. Results from the primary survey indicate that the key drivers of share prices were neither broad macroeconomic indicators nor key indicators of the health of the firm. Prices were clearly shown to be much above levels that could have been determined by such indicators as posted profits of firms, amounts paid out as dividend and regularity of such dividend payout. Secondary data analysis equally showed that the relationship between actual levels of the all share price index for the period of our analysis and during the financial crisis were not driven by “expected” variables. While its fundamental values are driven by such monetary and relative price variables, actual values are driven by external sector variables and prices. Chapter 6 tries to relate globalization, consumer’s preference and welfare in India by a sophisticated Computable General Equilibrium Model. The purpose of the chapter is to analyze general equilibrium effects of different trade liberalization policies for India under imperfectly competitive market structure and the obtained results are compared with the scenario of perfect competition as an ideal market structure. Since present day world trade is much akin towards to the consumer’s preference for product variety, increasing returns to scale and market structure oriented industry behavior, it has considered monopolistically competitive market structure for the analysis. Computable General Equilibrium (CGE) modeling has been applied for the analysis as it seems to be relevant methodology for the purpose of policy simulation. Consumer’s love for variety and presence of increasing returns to scale benefit inherently present in the sectors which involves large fixed costs, are strong determinants of consumer’s as well as producer’s business confidence. The study reveals that increased welfare gain due to trade and openness is not much larger as compared to standard perfect competition scenario as the scale economy benefit is predominant only in few sectors like capital goods industries and not prominently visible in large agricultural and informal manufacturing sectors. For governance perspectives, policymakers must choose their FDI and liberalization policies very carefully based on sectoral characteristics. Chapter 7 on the issue of governance and institutions highlights the interlinkages among governance indicators and capital accumulation under globalization on some selected counties in a broader way. According to it maintaining good governance is necessarily required for all countries in the world after the phase of globalization, especially when almost the entire world is struck by the global financial crisis originated from the USA. Good governance can lead to positively influence the growth rate of a country besides other important indicators determining overall development of a nation. The present study tries to concentrate upon establishing an interlinkage among capital accumulation of a sample of countries with principal components of governance for the time period 1996-2012. Primarily correlation analysis is done to judge the degree of interdependence among the variables. After that Granger Causality test is carried out to identify directions of causalities among capital formation and all the governance indicators. The study observes an inverse relation between governance indicators and capital accumulation for majority of the developing countries and in some cases positive relations for developed countries. Besides, it is observed that there are causal relations from capital formation to governance in most of the developed countries whereas in most of the developing countries there are causalities from governance to capital formation.

xxiv

Preface

Chapter 8 addresses the issue of corruption, size of government and economic Growth using global data. In line with it a big size government fosters corruption, which can lead to inefficiencies and resource costs that impede economic progress. In this chapter, it is argued that much of the previous studies have focused only on detecting the linear effects of corruption on growth. This study, therefore, adopts the Threshold Autoregression (TAR) Approach by using an annual panel data of 100 countries during 19902012 to evaluate any existence of a non-linear relationship. This study presents evidence that suggests the existence of a hump shaped (nonlinear) relationship between corruption and long-run economic growth. When the government size is small (11.518%), corruption positively affects economic growth. Whereas, when the government final consumption expenditure (% of GDP) is larger than 19.027%, corruption negatively affects economic growth. Furthermore, the result indicates that a non-linear relationship of the ‘Armey curve’ exists in our panel of countries. Thus, it recommends that government should investigate whether government size is over-expanding or not when designing its public finance policy. Chapter 9 unfolds the empirical study on dimensions of good governance. Consistent with this, effectiveness of governance is realized through its responses to any financial crisis. This study empirically investigated the relationship between accountability, corruption, and government effectiveness, focusing on the economic crisis background the world was facing during the period 2002-2012. Its main purpose is to highlight the sizable gap that exists in the performance literature on cross-country studies especially against the changing economic world scenario. A comparison of the World Bank governance indicators between three countries chosen on the basis of income differentials and hence different adaptive characteristics of each country to the economic recession has been studied. The behavior of the governance indicators in the context of the world has been studied against the background of the shock that the depression had brought and the resilience factors embedded within the indicators in the face of the shocks were studied. Political stability and Absence of Violence/Terrorism and Voice & Accountability consistently showed negative impact on a country’s per capita national income. However, Voice & Accountability become significant after 2006. Economic recession in fact has allowed for citizen’s voice to rise in the face of poor governance. Control of corruption is highly significant showing its unaltered importance as an indicator of governance even in the face of economic recession and its impact on change in net national income suggesting policy-implications with respect to development. Chapter 10 throws light on the inter-linkage between governance and poverty for the SAARC countries. According to it a good governance results in higher economic growth, better redistributive policies implying equitable distribution of wealth and resources, increased employment opportunities, rising income, production, consumption, investment and economic growth. In economies with high inequality, the aggregate demand made by the consumers in the society as a whole gets lower which in turn affects production. As production goes down the producers cut short their production expenses, as a result of which, unemployment occurs resulting in loss of earning opportunities. Thus, in an economy with persistent inequality and poverty, there is less equity in all the sectors of the economy. So a welfare state which always aims at good governance reduces poverty, lowers economic inequality and promotes equitable distribution and participation. This chapter aims at assessing the impact of governance on the country’s economic and human well-being in the selected South Asian countries. The study finds that for the countries-India, Pakistan, Bangladesh, Sri Lanka and Nepal, over the years 1990-2012, the growing rate of GDP per capita (PPP) and growing employment to population ratio has a significant negative impact on the Global Hunger Index as expected. Also the panel regression run for the eight SAARC countries over the period 2007-13 to find out the impact of each of the six governance indicators on the per capita GDP showed that political stability and absence of violence, government effectiveness and xxv

Preface

regulatory quality have very strong and significant role in augmenting the economic output besides the remaining indicators. The trends for each of the indicators across countries over time show that except Bhutan, none of the countries are exhibiting good performance of the governance indicators. Chapter 11 illuminates the case for leadership in sustaining governance. The chapter has three core aims. First, to discuss the concepts of governance and leadership while drawing upon key literatures and qualitative data to make sense of the factors that can enable leadership to sustain governance systems. Second, the chapter explores the practice of leadership at the Greater London Authority (GLA) level in the United Kingdom (UK) in order to establish features synonymous with the practice of leadership. Third, the relations between governance and leadership are explored so as to better understand how the latter is employed in sustaining the governance process at the GLA level in the UK. Chapter 12 elucidates the concept of governance and its impact on economic growth in South Asian perspectives. In this attempt, the chapter examines the history and political economy of South Asia to determine the factors that affect growth. It observes that governance in South Asian context evolved through three phases. During each of these phases, dominant factors influenced governance in the region. Using World Governance Indicators (WGI) and GDP growth rates, it analyzes the relationship between political history and economy in each phase. The finding validates its hypothesis that ideologies of political leadership and their economic policies influence the institutions of government. The chapter finds that enhancing people’s participation in governance process would facilitate growth and distributive social justice. It also compares the phases of development of the concept of governance in South Asia with that of Brazil (owing to the BRICS alliance) and discovers the findings reinforced. Chapter 13 sheds light on corporate governance and selected Indian firms’ performances. In line with it, ownership structure is considered to be of prime importance in corporate governance of a firm. The ownership structure significantly varies across the nations. The main focus of this study is twofold; firstly to see the impact of ownership structure on performance of the firms and secondly to investigate the relationship between stock market performance and ownership structure during the crisis period. Panel data analysis of CNX 200 companies has been done for the time period of 2006-2013.The study also takes into account the relationship between crisis period stock return and ownership structure. The results of this study reveal a positive relationship of promoter’s shareholding with performance while a negative relationship of performance is found with the non-promoters shareholding. In addition to that the regression of stock price performance on ownership variable gives a significant negative relationship during the crisis period. Chapter 14 evolves the aspects of globalization, governance and food securities in BRICS countries. According to it food security is a major area of concern for the five nations group. BRICS countries account for more than 40% of the world population and 25% of world GDP in PPP terms. Besides, these countries have a key role to play in the post-crisis global economy as producer of goods and services, receivers and exporters of capital, and/or consumer market on large potential. More importantly, these ones envisage ways to promote food security and food production in Third World countries by raising agricultural productivity and output via initiatives like the creation of basic agricultural information exchange system of these countries; enhancing investments in the food supply chain; developing a social safety net through conditional income transfer programmes for the poorest of the poor. It is in this context the present chapter examines the status of food security of BRICS economies in the context of globalization and governance and its implications thereof. Chapter 15 illuminates basic issues of the global financial crisis and its impacts upon global economic growth and investment through a vast literature survey. Consistent with it, for any economy to be healthy, xxvi

Preface

a strong financial system is required to efficiently move funds from unproductive to productive economic agents. Banks play an important role in this respect. They are also said to play the most important role in the financial system of all existing financial institutions as their presence and structure reduces the problems of adverse economic selection, moral hazard, and asymmetric information; as well as ensuring the success of the overall role of the banking system through aggressive monitoring. This chapter thus attempts to a broad survey of the existing literatures on the issue and examines the causes of banking crises in the light of available evidence. More specifically, the research enumerates and analyses the role of both macroeconomic and microeconomic factors in precipitating such crises through a critical examination of the existing literature, and attempts to illustrate each factor with examples from key pan-global financial catastrophes. Chapter 16 throws light upon waves of financial crisis on the basis of historical perspectives. To it, the global stock market cycles, crashes and the resultant panic over the past years have ended in ultimate devastating impact on the rest of the economy. A poorly performing or a financially fragile financial sector has often been identified as a major factor in creating and aggravating crises. Moreover, in this era of high trade and financial integration, crises in one market sets in motion much turmoil in other markets through long-term and short-term dynamic linkages among different markets or through what is better known as contagion. Hence, at this juncture, some inquiry of the market dynamics is likely to be instigated. This is the area where this study intervenes. Chapter 17 elucidates the effect of global financial crisis on South Asian Economy with special emphasis on Indian economy. In line with it, most of the Asian countries were affected adversely for the recent global financial crisis, especially those economies whose growths are largely depended on the external trade. During the phase of shrinking world demand for domestic goods and services, efforts to raise productivity and competitiveness helps countries to protect export market. This chapter investigates the dependence on the external market and the effect of global financial crisis on the trade structure of some Asian countries. Some detail studies have been done for India in respect of compositional changes and productivity and efficiency changes of different industries within manufacturing sector during pre and post crisis period. Efficiency and productivity have been analyzed using the frontier model. Chapter 18 discusses about the factors determining foreign direct investment inflow to Nigeria during pre economic crisis through empirical investigations for the period 1970-2006. This study suggests that the endowment of natural resources, trade intensity, macroeconomic risk factors like inflation and exchange rates are significant determinants of FDI flow to Nigeria. The findings also suggest that in long run market size is not the significant factor for attracting FDI to Nigeria, contradicting the existing literature. The results indicate that FDI flow to Nigeria is resource-seeking FDI along with the result that trading partner like the UK in North-South (N - S) and China in South-South (S - S) trade relation have strong influence on Nigeria’s natural resource outflow. Chapter 19 analyzes the impact of microfinance on poverty in South Asian countries under the context of global financial crisis. The outreach of microfinance programme is considered as a means to enhance the economic wellbeing among the member households through poverty alleviation. Microfinance programme in the South Asia region has witnessed much more resilient to withstand shocks of global financial crisis compared to other continent in the world. To explore the impact of microfinance on poverty in the backdrop of global financial crisis, the chapter attempts to examine the relationship between microfinance institutions’ gross portfolio per active borrower and the measures of poverty. Empirical evidences based on Pooled Regression Analysis suggest that gross portfolio per active borrower is negatively and significantly associated with the poverty head count ratio or poverty gap measure, xxvii

Preface

which is consistent with the hypothesis that micro loans reduce poverty. The poverty alleviation role of microfinance in South Asian countries is not changing its dynamics even in post-crisis scenario. Chapter 20 illustrates the effect of financial crisis upon investible capital flight from Nigerian economy. The global financial crises that happened between 2007 and 2010 had deleterious effects on countries across the world including Nigeria with regard to their respective levels of globalization. This was evidenced with sudden outflows of capital emanating from the capital market that impacted negatively on the banking system. The chapter has adopted a number of variables among which are investment and net portfolio investments and external reserves. The main technique used is the regression (both single and two-stage) the results of which indicate that the investment is not negatively impacted by the portfolio investment but has significantly negative effect on the external reserve and the saving of the country. The chapter also recommends a better control of the capital out flows and improvement in the business environment to reduce the capital haemorrhage faced by the Nigerian economy. Chapter 21 elucidates the inter connections among urbanization, FDI and growth for India and China. The rapid urbanization and economic growth during new round of globalization is largely due to the inflows and outflows of FDI. The objective of this chapter is to analyze the causality and linkage among urbanization, GDP and foreign direct investment in China and India with the help of secondary data from 1979 to 2012. It focuses on determinants and pattern of FDI flow in China and India. China has historically attracted more FDI than India as a share of GDP, particularly in the early stage of its economic transformation. It achieved a significant growth rate of over 9 percent per year during 1990 to 2010 which was highest in the world during that period. There exist significant positive correlation between urbanization and flow of FDI to a particular region both in China and India. The rate of growth of FDI is significantly influenced by rate of growth of urban population at 10 per cent level of significance and by rate of growth of per capita GDP at 1 percent level of significance. The last one that is Chapter 22 highlights the issues of institutional and cultural implications of Mexican small and medium enterprises’ internalizations into the European Union market. The aim of this chapter is to analyze from the perspective of institutionalism if the European Union market is a potential market for the internationalization of Mexican SMEs. This chapter identifies a framework of the current situation of Mexican SMEs, encompassing as the political-economic aspects that govern the cooperative relationship as the normative and cultural factors that impact directly businesses, concluding that the complexity of the European Union resulting from the uniqueness of each of its members is reflected in a set of formal and informal rules that negatively impact on the internationalization of Mexican SMEs to that market. It is now becomes a news that the proposed project has drawn closer to reality. I expect that the said research outcome will lend a hand to the academicians and policy makers all around the world to have a better understanding of the said economic and political shocks that the book addressed to and making themselves prepared to visualize a safety valve against such shocks that may appear in the future in terms of any economic and political indicators. Ramesh Chandra Das Katwa College, India

xxviii

xxix

Acknowledgment

I would be culpable if I did not acknowledge the contributions of my fellow academicians and others around the world who made this volume possible. Firstly, I must acknowledge the team at IGI Global for approving the book proposal and guiding me throughout all stages of this project through their friendly and helpful suggestions. They have been cooperative and their earnest efforts were always commendable. Secondly, I should be grateful to my research guides Professor Soumyen Sikdar of Indian Institute of Management, Calcutta, India and Professor Sarmila Banerjee of Calcutta University, India for encouraging me to undergo such a project and circulating the call for papers to our fellow academics in the field. Thirdly, I must thank Dr. Amaresh Das at the Southern University at New Orleans, USA, Dr. Soumyananda Dinda, Dr. Maniklal Adhikary and Dr. Arindam Laha of The University of Burdwan, India, Dr. Kamal Ray of Katwa College, India and Dr. Chiranjib Neogi of Indian Statistical Institute, Calcutta, India for their efforts in helping to reviewand edit the submitted manuscripts of the book, in addition to their added encouragements to me. Fourthly, I should acknowledge the efforts of the editorial advisory board members along with the guest editors for revising the chapters and providing me with suggestions despite their busy academic schedules. Fifthly, I should praise all the contributing authors for their valuable chapter contributions and showing their patience for such a long duration project coming into reality; I greatly appreciate the value they’ve provided to this field of research through their contributions to this edited volume. Last, but not the least, I am truly grateful to my parents, wife, daughter, and other family members for their continuous encouragement to me in carrying out this project, as well astheir sacrifice and understanding as book work encroached on our family life. Ramesh Chandra Das Katwa College, India



Section 1

Growth and Economic Confidence

1

Chapter 1

Does Consumers’ Confidence Cause Consumption Spending? An Analysis of Selected Countries under the Purview of Global Financial Crisis Ramesh Chandra Das Katwa College, India Amaresh Das Southern University at New Orleans, USA

ABSTRACT The present chapter addresses the financial crisis issue in light of its effect upon the interplay between the consumers’ confidence upon an economy and consumption spending of the households of the same economy. A simple correlation analysis for the quarterly data from January 1996 to October 2012 shows that the occurrence of the crisis has badly affected the consumers’ confidence and consumption spending of the developed countries. Emerging countries have performed well despite the crisis. Also that majority of the developed countries with a few developing ones produce the result of bidirectional causalities whereas in leading emerging countries, consumption spending is making a change in confidence in a ‘causal’ sense for the entire period of study. During pre-crisis phase the result show that the leading developed countries experience unidirectional causal relation from consumption to confidence. But in the post crisis phase seven out of twenty countries produce a line of causation going from consumption to confidence and nine countries fail to show any line of causation.

INTRODUCTION The lessons from the recent crisis in the so called developed economies, known as Global Financial Crisis (GFC) and its aftermath upon the rest of the world have compelled the economists, policy

makers and governments of different countries to redefine the concept of long run growth states of an economy. Under the framework of dynamic global system, the workings of new economic variables besides the traditional ones have proved their existence. The new factors that need to be

DOI: 10.4018/978-1-4666-8274-0.ch001

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Does Consumers’ Confidence Cause Consumption Spending?

incorporated as crucial elements in analyzing the developmental status of the world economies in the post globalization scenario are, among others, the maintenance of good confidence levels of the active economic agents like that of consumers and business houses as well as management of good and proper governance. Hence it deserves to reorient the working of the interlinkages among the new variables that can explain a possible part of such a crisis. The current mortgage meltdown actually began with the bursting of the U.S. housing “bubble” that began in 2001 and reached its peak in 2005. The housing bubble is defined by rapid increases in the valuations of real property until unsustainable levels are reached in relation to incomes and other indicators of affordability. Following the rapid increases are decreases in home prices and mortgage debt that is higher than the value of the property. Many economists believe that the U.S. housing bubble was caused in part by historically low interest rates (Shiller, 2008; Allen & Carletti, 2009; Carmassi, Gros, & Micossi, 2009; Schneider & Kirchgassner, 2009). After the meltdown in the financial institutions and takeover of larger banks by governments, there became a deficit of credit, which led to local business and international trade. International trade declined by 12 per cent in 2009 and world’s GDP dropped by 5.4 per cent in the same period (Chor & Manova, 2010). In response to the crash of the dot-com bubble in 2000 and the subsequent recession that began in 2001, the Federal Reserve Board cut short-term interest rates from about 6.5 per cent to 1 per cent. Between 2004 and 2006, the Federal Reserve Board raised interest rates 17 times, increasing them from 1 percent to 5.25 per cent. The Fed stopped raising rates because of fears that an accelerating downturn in the housing market could undermine the overall economy. Subprime borrowing was a major factor in the increase in home ownership rates and the demand for housing during the bubble years. The U.S. ownership rate increased from 64 per cent in 1994 to an all-time high peak of 69.2 percent in

2

2004. The demand helped fuel the rise of housing prices and consumer spending, creating an unheard of increase in home values of 124 per cent between 1997 and 2006. Some homeowners took advantage of the increased property values of their home to refinance their homes with lower interest rates and take out second mortgages against the added value to use for consumer spending. In turn, U.S. household debt as a percentage of income rose to 130 per cent in 2007, 30 per cent higher than the average amount earlier in the decade. With the collapse of the housing bubble came high default rates on subprime lending. The share of subprime mortgages to total originations increased from 9 percent in 1996 to 20 per cent in 2006. Subprime mortgages totaled $600 billion in 2006, accounting for approximately one-fifth of the U.S. home loan market. The number of subprime loans rose as rising real estate values led to lenders taking more risks. Some experts believe that Wall Street encouraged this type of behavior by bundling the loans into securities that were sold to pension funds and other institutional investors seeking higher returns. A Federal Reserve study in 2007 reported that the average difference in mortgage interest rates between subprime and prime mortgages declined from 2.8 percentage points in 2001 to 1.3 percentage points in 2007. This implies that the risk premium required by the financial institutions to offer a subprime loan declined. This decline occurred even though subprime borrower and loan characteristics declined overall during the 2001-2006 period, which should have had the opposite effect. The impact of such crises travelled throughout the world like an epidemic via trade and service channels. The shares of exports, imports and total trade volumes of USA, France, UK, Germany, Greece, Japan, South Africa, Brazil, etc in world trade have fallen during the phase of 2009-10. There was a remarkable decline in the world trade share of the European Union from 40 per cent in 2008 to 36 per cent in 2010. The same story also

 Does Consumers’ Confidence Cause Consumption Spending?

is heard for annual growth rates of these countries. There are negative growth rates for USA, UK, France, Germany, Japan, etc for the period 200910 but the magnitudes of negative growth rates of Greece aggravates till date. Greece is one of the worst sufferers of the twin crises. But the calamities could not manage to affect the Asian Giants like China, India; rather they played the role of shock absorber of these crises. China, being front runner in the world trade, has improved, though slightly, in its trade share. India, although possessing a small share in world trade, made itself better off after the crises. The service channels have improved for China and India since there were increasing trends in the remittances of the non-residents of the countries as well as their deposits to the home avenues. The foreign institutional investors (FIIs) moved to India and China as the economies are safe to invest. Hence, the overall outcome is the rising confidence level of the agents of India and China and the agents of foreign nations upon the economies of Asia, particularly upon India and China. At the same time these two economies maintained a sound average growth rate of overall economy amid the crises.

REVIEW OF LITERATURE The lessons of the previous literature related to the present study should not be disregarded. In a working paper Lin and Treichel (2012) cites the root cause of the recent financial crisis starting from the weak monetary policies of the US Government preceded by the dot-com burst. The financial crisis has led to drastic fall in consumers demand, particularly of housing and food items. According to Mielcova (2011) household responses to financial crisis vary from country to country. Whereas German and UK households decreased liabilities (as well as mortgages) as a response to financial crises, French households tends to increase their loans. On the other hand, the ability and willingness to save is in general higher after

the financial crisis than it was in the crisis phase. In their working paper Lee, Rabanal and Sandri (2010) have shown that the US consumption as a share of income has gone down during the crisis period of late 2008 (which had peaked above 95 percent of disposable personal income in 2005) compared to the pre crisis period since 1980 and the savings ratio has increased to 6 per cent from the 5 per cent points making a slowdown in the aggregate demand of the aggregate economy and so growth rates of GDP. The factors responsible for the same, as the report points out, are the falling trend of households wealth because of financial uncertainty, undercutting the growth prospects, tight credit policy of the Federal Reserve, among others. In a study based on American survey data from the period of the great recession, Christelis, Georgarakos and Jappelli (2011) find much smaller marginal propensities to spend out of wealth shocks. Their contribution adds that they have identified households that believe that asset prices are permanent and those who think they are transitory. In another working paper related to England, Banks, Crawford, Crossley and Emmerson (2012) observed that prices of real and financial assets of the country fell substantially during the crisis period and the worst hit by this wave were the older households. The older households, as a result of asset shocks, tried to truncate their spending upon essential items like food, clothing and fuel. In a theoretical modeling, Chai, Maurer, Mitchell and Rogalla (2011) put effort to investigate the short and long-term impacts of a combined financial and economic crisis on households at different stages in their life-cycles by developing a life-cycle model that allowing for optimal consumption, work effort, retirement, asset allocation, and annuitization decisions, incorporating countercyclical labor income and unemployment risk as well as regime shifts in the investment opportunity set. They have shown that for young households, the crisis will have little impact on either work effort or retirement behavior, though

3

 Does Consumers’ Confidence Cause Consumption Spending?

they do suffer from a long-term decline in annual consumption accompanied by lower saving. Young households hit particularly badly by the financial/economic crisis do have more response, reducing their work effort during the crisis by up to 10 percent. But for the older households, the study reveals that they are predicted to boost work effort slightly over the rest of their working lives. The crisis is felt to invite marked declines in annual consumption, both short- and long-term periods. In the related area, the efforts of Hurd and Rohwedder (2011) studied how households of USA adjust their spending in response to the financial crisis. Based on five waves of data from the Consumption and Activities Mail Survey, their panel data analysis on anticipated changes in spending at retirement age tried to quantify the effects of the financial crisis on well-being in retirement via a difference-in-differences approach. It is established that the financial and accordingly the general crisis has directly affected households via losses in the stock market, losses in home equity, and unemployment. Households undoubtedly altered their expectations of their future economic positions, which according to the life-cycle model, would have an additional depressing effect on spending. Indeed, they found that the estimated reductions in spending over the time period 2007 to 2009 were between 3.6 to 7.0 percentage points greater among 50 to 65 year-olds than over earlier two-year time periods. Kumar (2009), in his study report, has cited that the impact of the present crisis has been transmitted to India via financial sector channel, export channel and exchange rate channel. Out of the three the contribution by the former is not significant because of India’s banking sector is not so opened. The significant impact has been revealed by the export/import and exchange rate channels. The study prescribes some policies to make the economy out of danger, like that of removing structural bottlenecks, as the expansionary fiscal policies with further deficit will magnify the damage. In another work by Ghosh (2009) reveals

4

that the crisis has worst hit the agriculture sector in terms of falling employment, total production and non availability of formal sector credit because of food price volatility that led to about 10 per cent hike in food prices. The study demands much more creative and imaginative policy responses, in terms of changing directions of investment and consumption in the home market to emphasize wage-led growth, diversifying exports and making moves designed to turn economic disadvantage to advantage. In a little bit forward study, Thompson (2009) highlights that the effects of the volatile food prices and the financial and economic crisis can impact the most vulnerable section of the society in at least two ways; lowering or disrupting real wages and major sources of income; and, reducing the funds committed by donors to development assistance for social protection and emergency food interventions. Already the severity of the current financial crisis has proved an added burden to an already exceptional difficult situation confronting the institutions responsible for ensuring world food security. In their effort Mourougane and Roma (2002) tried to investigate the usefulness of European Commission’s confidence in forecasting the real GDP growth in the short run for the countries including Belgium, France, Spain, Netherlands, Germany and Italy. They observed significant signs of forecasting by a linear regression of real GDP of these countries upon their confidence indicators. The results for Spain seemed not satisfactory. Bank of Thailand (2004) tried to prepare a report on the relation between the confidence indicators and consumption and investment activities of the Thai people. The report says that growth rates of real private consumption and real private investment seem to move in tandem with consumer confidence and business sentiment indices, respectively. Precisely it has shown that the Overall Consumer Confidence Index appears to be a coincident indicator of real private consumption. In contrast, it shows that Business Sentiment Indices appear to be leading indicators of real private

 Does Consumers’ Confidence Cause Consumption Spending?

investment. Based upon the data available for Turkey Celik, Aslanoglu and Deniz (2010) examined the relationship between consumer confidence and financial markets for an emerging economy, Turkey. They modeled consumer sentiment as a function of high frequency financial market variables such as interest rates, exchange rates and the stock exchange index. They found and established that in emerging economies there might be existence of cointegration between consumer confidence and the financial market variables of interest. Hence, in emerging markets consumer confidence should be viewed as an endogenous variable. In explaining the role of financial crisis upon the households’ consumption behavior the study of Voinea and Filip (2011) deserves a special attention. It states that the new consumer behavior has encountered a series of changes. The recession has led the consumers to look for new landmarks that are they became more economical, more responsible and more demanding. Study Egol, Clyde and Rangan (2010) observes that the US consumers are too much frugal during the recession and that was so strongly rooted among American consumers and it changed their consumption patterns in such a manner that is expected to persist even if the economy recovers. This new frugality, characterized by a strong awareness of the value that dictates compromises in terms of price, brand and comfort, became the dominant mentality among U.S. consumers. Mansoor (2011) points out some of the effects of the crisis upon consumers attitudes. Like that of doing simplified market behavior, maintaining good temperament for buying a particular product, switching over to green products, quickly respond to price changes which is known as smart consumerism, etc. The study of Bram and Ludvigson (1997) on whether consumer confidence forecast household expenditure deserves special emphasis with respect to the present study. The study observes that lagged values of the overall confidence and expectation measures have stronger incremental predictive power for more categories of consumption ex-

penditure growth by the application of vector auto regression technique. Another study specific to Jamaica’s households by Myrie and Robinson (2013) by using data from the Jamaica Survey of Living Conditions, examines how the recession accounts for differences in Jamaican household food consumption before 2007 and during the recession 2009, and compares the impact of micro characteristics such as households’ income, sex of household head, household size and area of residence on food consumption between both periods. The results indicate that income level and area of residence are consistently significant determinants of food consumption in Jamaica. In addition, the findings indicate that food consumption expenditure in all income categories remained basically unchanged between 2007 and 2009. They also found that female-headed households were seemed to spend significantly more on food consumption than male-headed households during the recession, which might be attributable to a combination of factors including the possibility that female-headed households accessed more social welfare and remittances during the recession. The effect of the financial crisis, although it is general, should be viewed from the perspectives of the individual countries. It has been pointed out by Haughton and Khandker (2012), in their working paper, that despite of fall in GDP of Thailand by 2.3 per cent during the recession period and fall in per capita real consumption expenditure, the consumption for durables had been increased along with increased savings. Most of the drop in Thai GDP in 2009 was due to a sharp fall in investment spending. A simulation exercise based on the slowdown in growth of gross domestic product would have missed these effects, as would models based solely on readily-available data series. This points to the importance of country-specific policy analysis, rooted in timely local evidence, including survey data of households. One of the studies specific to China done by Bulman (2010) cites, on the phase of financial crisis that Growth in China’s economy has become

5

 Does Consumers’ Confidence Cause Consumption Spending?

too dependent on investment and exports and the current model for economic growth is unsustainable. This article argues that China should promote the household consumption share and strong adjustments are needed to enable consumption to grow faster than the GDP. As both the investment and trade sides are weak the article further argues strongly for increasing household consumption as a complementary effect upon GDP growth rate to roll back to its pre crisis level as there is large potential for consumption growth vis-à-vis growth rates. In addition to that the article prescribes some possible measures including fiscal and macro policies, price and tax measures, and financial reforms. Besides, strong rising trend of the savings potentiality of the Chinese households, corporate houses and the government on the verge of crisis were dwindling the domestic as well as world demand. This factor, as some research findings prove, worked as a catalyst for the said crisis (Xinhua & Cao, 2007; Bayoumi, Tong & Wei, 2010). One study based on Australia reveals the effect of fiscal stimulus directly to the households for supporting durable and non durable consumption that were following down turn during the crisis phase (Aisbett, Brueckner, Steinhauser & Wilcox, 2013).The study observed that non-durable consumption expenditures did not react significantly to the fiscal stimulus during or after the one-time, pre-announced transfer but there was a small, albeit statistically significant increase in non-durable consumption expenditures at the time of the announcement of the policy. None of the above studies could highlight the role of consumers confidence upon household’s spending in light of such a crisis, although they have highlighted different aspects of the crisis and its impact upon different economic indicators. The present study tries to study the effect of such crisis upon the consumers of different countries. The change of consumption spending can be explained by many economic (both real and financial) indicators, as the above literatures showed, but we

6

have selected the confidence of the consumers as the only relevant dependent variable to influence the consumers spending as our main motto is to track the confidence variable. Hence, we have taken up this venture to investigate the interplay between consumers’ confidence and households’ consumption spending during the crisis phase, keeping the workings of all the other economic and non economic indicators unchanged. An economy, to have a stable growth path, should have interlinkage between the two so far as the crisis effect is concerned. That means as the economy grows in quantitative terms the confidence of the economic agents, particularly of the consumers, tends to rise. At the same time, if the consumers have better confidence upon the economy then the growth rate of the overall output will tend to rise.

OBJECTIVES The present chapter tries to test two hypotheses. Hypothesis I: Whether there is any significant degree of association between the consumers’ confidence index and households’ consumption spending of a country. Hypothesis II: Is there any causal relation between the consumers’ confidence index and households’ consumption spending of a country?

DATA SOURCE We have carried out the entire study for the time period 1996-2012 that covers both pre crisis and crisis and post crisis phases. We have used the quarterly data of consumption spending and consumers’ confidence index (CCI) supplied by different central banks and statistical institutes of the countries and compiled by tradingeconomics. com (visit www.tradingeconomics.com). To have a better view on the span of crisis we have depended upon the quarterly data. We have 68 quarters out of the total 17 years. The entire period of study

 Does Consumers’ Confidence Cause Consumption Spending?

is Jan 1996 - Oct 2012 out of which the pre crisis phase is Jan 1996-Oct 2007, crisis phase Oct 2007-Apr 2009 and post crisis phase Apr 2009-Oct 2012. The sample of countries is twenty nations comprising both highly affected developed nations like USA, UK, France, Germany, Greece, Spain, Italy, Portugal, Ireland, Japan, Russia, and Australia and relatively less affected emerging nations such as China, India, Thailand, South Korea, Brazil, South Africa, Turkey and Argentina. All the consumption spending data are in US Billion Dollar but the CCI are calculated by slightly different methods in different countries which cannot be comparable in strict sense. But we can study their trends and compare their trends across the countries and correlations with the consumption data of the particular country.

METHODOLOGY Our first hypothesis has been tested primarily by a graphical framework by studying the trends of consumers spending and CCI. For some countries we did not find quarterly data for some years in consumption spending like China and CCI for China, India, Greece, Turkey etc. We have interpolated some missing data and substituted all the quarters’ data by the annual data of the particular year of the particular country to have a continuous series data. After graphical analysis we have computed the degrees of associations between both the variables for all the countries by the Spearman’s Coefficient of Correlation and tested their significances by setting t statistics as

(

)

t = r √ (n − 2) / √ 1 − r 2 for the Null Hypothesis H0: ρ = 0 against the Alternative Hypothesis H1: ρ ≠ 0. ‘r’ stands for sample correlation coefficient and ρ as population correlation coefficient and (n-2) is the degrees of freedom.

The testing of the second hypothesis requires rigorous application of the time series econometrics. Since we have a long series of data we need to test their stationarity before going for causality test. If they are found to be non stationary we need to go for whether their first difference is stationary. In other words, we need to diagnose whether the series are integrated of order one i.e. I(1). If so happens then we will go for testing whether there are any sort of long run relation between both the consumption and confidence index series by means of Johansen Cointegration Test and/or the residuals of the long run regression are stationary. If they are found to be cointegrated then the next task is to go for error correction over time by the technique of Engel & Granger (1987). If error correction coefficient is negative and significant then it is stated that the series converge after short run deviation from the long run equilibrium relation. Otherwise, there is no need to go for correcting error (if there is no such significant error). The causality test is then done by the help of Granger (1969) technique after incorporation of the error correction term in cases the error is significant. Hence, there are four steps to go for Granger Causality Test (GCT).

Step 1: Unit Root Test To avoid getting spurious regression results from the application of OLS model in a non stationary bivariate data we need to test for staionarity or unit root test. For a data set (yt, t = 1, 2, ...,T), where t denotes time let us consider the following linear regression set up for unit root test for two versions of the ADF(p) (1979) regression–viz.,  p

∆yt = α + βyt −1 + Σ γ j ∆yt − j + ut j =1

 for the without time trend case and

(1)

7

 Does Consumers’ Confidence Cause Consumption Spending?

∆yt =

α + δ t + β yt −1 +

p

Σγ j∆y j =1

t− j

+ ut

Granger methodology is to model the short run variations of the variables. This is done by estimating the ECM terms by the equation ∆yt = β∆x t + γ∆et −1 + ∈t and γ is error correction term and sign of γ is expected to be negative; e is the error term in yt = α + β xt + et .

(2)

for the with time trend case.

Step 2: Johansen Cointegration Test Cointegration test for two series can be done either by Johansen Test by looking at the Eigen values and likelihood ratio or by estimating the linear regression between y and x and then estimate the residual and test its stationarity. Given a data set on two variables (y, x) the single equation cointegration test proceeds as follows: First, the linear regression equation yt = α + βxt + ut is estimated separately for individual state and the estimated regression residuals given by the following equation et = yt − αˆ − βˆx t

(3)

(where t = 1, 2, …., T) ˆ are obtained, where ‘ βˆ ’s denote the estimated parameters of the regression equation for each country. These estimated linear regression equations may be taken as estimate of the long run equilibrium relationship between y and the x, in case the variables turn out to be cointegrated. Next, for each country the following ADF (p) test like Equation (1) is estimated. If the coefficient of et-1 is found to be unity from our given sample then it is concluded that there is no cointegration and if it is found to be less than one then it is said that y and x series are cointegrated for the said country.

Step 3: Error Correction Modeling (ECM) Once the pair of variables (x, y) has been found to be cointegrated, the next step in the Engle – 8

Step 4: Granger Causality Test For a bivariate model with both the series as non stationary and integrated of order one for all the countries the GCT is done by estimating the following equations in first difference form of the variables including the EC terms for y on x and x on y (Granger, op cit). The equations are: ∆yt = νyx + T11

Σα1 j ∆yt − j + Σβ1 j ∆ x t − j + j =1

(4)

T12

ηyx E CYt −1 + u1t j =1

∆xt = ν xy + Σα 2 j ∆yt − j + T21

T22

Σ β 2 j ∆xt − j + η xy E CYt −1 + u1t j =1

(5)

j =1

Here Δ denotes the first difference operator; T l m, l, m = 1, 2 denotes the number of lagged values of Δy and Δx that affect the current values of these differenced variables; ν, α, β and η denote regression parameters; ult, l = 1, 2 are the equation disturbance terms (that should be white noises when the ECM has been adequately specified). The parameters ηyx and ηxy in Equations (4) and (5) are called the adjustment parameters. They are expected to have negative values. For a bivariate case like the present one, the ECM is complimented by the well known Granger Representation Theorem (Hamilton, 1994). In this present set up as above the nature (or direction) of Granger Causality is determined by the F statistics where the judgments are as follows: 1. If β1j = 0, for all j and ηyx = 0, x may be said not to Granger cause y.2. If α2j= 0 for all j and ηxy=

 Does Consumers’ Confidence Cause Consumption Spending?

Figure 1. Quarterly trend of consumption spending of USA under different phases (in US Bn Dollar)

0, y may be said not to Granger cause x.3. If (1) holds but (2) does not, Granger causality may be said to be unidirectional from y to x.4. Conversely, if (1) does not hold but (2) does, Granger causality may be said to be unidirectional from x to y.5. If both (1) and (2) do not hold Granger causality between x and y may be said to be bi- directional or it is termed as feedback causality. 6. If both (1) and (2) hold, Granger causality between x and y may be said to be absent, or there is no way causality.

GRAPHICAL REPRESENTATION OF THE VARIABLES ACROSS COUNTRIES Before to go for doing quantitative analysis by means of econometric methods we present and analyze the two variable series, namely, consumption spending and consumers’ confidence index (CCI) for the selected 20 countries over the quarterly data from January 1996 to October 2012. The entire data have been presented in Figure 1 to

Figure 5. Figure 1, Figure 2 and Figure 3 present the consumption trends of the countries. USA, making an outstanding figure in the consumption spending, is incomparable to others and hence placed in the top position (Figure 1). It is followed by Japan in the sample but China, being at the lower level in the initial phase, is chasing Japan and USA (Figure 2). Thailand and Ireland are in the bottom line of the group (Figure 3). It is observed from the consumption trends that all the countries felt the punch of the global financial crisis except some highly emerging economies, China, India and Thailand. The shock period has been broken and shown in the figures by discontinuous phases. All the countries have started recovering from the shock except Greece, Italy, Ireland, Portugal and Spain (also known as GIIPS countries) who are still facing falling trends because of their long history of sovereign debt crisis. The scenario of CCI are presented in Figure 4 and Figure 5 that show falling trends of the variable in all the developed countries except Australia, Japan and South Korea and rising trends in most of the emerging countries. Sharp reductions are

9

 Does Consumers’ Confidence Cause Consumption Spending?

Figure 2. Quarterly trends of consumption spending of countries under different phases

Figure 3. Quarterly trends of consumption spending of countries under different phases

10

 Does Consumers’ Confidence Cause Consumption Spending?

Figure 4. Quarterly trends of CCI of countries under different phases

Figure 5. Quarterly trends of CCI of countries under different phases

11

 Does Consumers’ Confidence Cause Consumption Spending?

observed for USA, Greece, Spain, UK, Ireland and Portugal. The appearance of the financial crisis has prominent negative impact upon the all types of economies except India as the rare country. The downturn continues for the developed countries till the last quarter of 2012 in respect of the CCI levels. Most of the emerging economies along with Japan tried surviving after the crisis. The consumers of these countries regained confidences about their own and related economies but the consumers of developed countries still struggling for their economies’ confidence levels to regain. The striking feature of the developed countries of the west is that there is clear difference between two groups of countries in the CCI levels. Five countries, namely, USA, France, Spain, Italy and Ireland maintained CCI at about 100 and above during the pre crisis phase but remaining four, namely Germany, UK, Portugal and Greece maintained CCI at zero or negative levels. After the crisis the first five offer consumers’ the confidence of 50 ≤ CCI ≤ 100 about their economies whereas the last four offer the range -83.8 ≤ CCI ≤ 5.7. The developed countries of the east, Japan, Korea and Australia, maintained a formidable degree of CCI throughout the entire period of study. In the similar way, the developing blocks have three sub blocks- China, Turkey and Brazil in the upper slot during the pre crisis phase with the CCI at around 100, Thailand, India and Argentina in the middle stage with CCI 40 to 90 and South Africa and Russia in the lower slot with CCI around zero. After the crisis phase, India steeply entered into the upper slot even taking the top position from October 2010 on words maintaining CCI around 120-130. India, in this regard, has won the heart of the consumers of its own and of the rest of the world. There is another striking feature for the developing and developed countries as a whole that some countries faced falling (rising) consumption trends with CCI trend falling or rising (rising or falling).

12

Table 1. Results of correlations between C and CCI of countries under different phases Country

Entire Phase (Jan 1996 - Oct 2012)

Pre Crisis Phase (Jan 1996 – Oct 2007)

Crisis Phase (Oct 2007Apr 2009)

Post Crisis Phase (Apr 2009Oct 2012)

USA

-0.70

-0.43

0.62*

0.26

UK

-0.57

-0.38

0.85

-0.20

France

-0.59

-0.20

0.89

-0.09

Germany

-0.34

-0.29

-0.70

0.87

Greece

-0.16

-0.38

-0.31

0.78

Spain

-0.67

-0.72

0.15

0.42

Italy

-0.35

-0.27

-0.22

0.80

Portugal

-0.72

-0.80

0.86

0.78

Ireland

-0.76

-0.60

0.70

0.14

Russia

0.53

0.50

0.37

0.60

China

-0.60

-0.01

-0.87

-0.09

India

0.87

0.43

0.28

0.30

Japan

0.06

0.47

0.86

0.42

Thailand

0.47

0.59

0.76

0.36

S Korea

0.59

0.61

-0.74

-0.52

Brazil

0.85

0.83

-0.66

0.22

S Africa

0.35

0.59

0.24

-0.07

Turkey

-0.89

-0.94

0.56

0.19

Argentina

0.30

0.66

-0.57

0.55

Australia

-0.09

0.41

0.64

-0.57

Note: All bolds are significant. * Marks represent significance at 10% levels.

Hence, the financial shock has long term effects upon the developed nations’ consumption expenditure and consumers’ confidence levels whereas it has short term effects upon that of the developing nations. May be the fact that most of the emerging economies insulated themselves from the shock because of their moderate degrees of cross country integration compared to the developed ones and because of the volume of large demand in the domestic markets the developing countries got the radiation at a lower degree.

 Does Consumers’ Confidence Cause Consumption Spending?

We, thus, need correlation analysis to have some quantitative impact of such an association between consumption and CCI series.

CORRELATION ANALYSIS Since we have quantitative data on country wise consumption expenditure and CCI levels we apply Pearson’s Product Moment Correlation coefficient ‘r’ as explained in the key words’ explanation at the bottom and it has been tested for its statistical significance across the countries as cited in the methodology section. Since we have a long time series data and almost all countries’ bivariate series revealed a common shock in the late 2007 and continued up to early phase of 2009 we have computed the said correlation coefficients in three different time phases- entire phase (Jan, 96 to Oct, 12), pre crisis phase (Jan, 96 to Oct, 07) and post crisis phase (Apr, 09 to Oct, 12). The results are presented in Table 1. There are negative and significant correlations between consumption expenditures and CCI of the so called developed economies of the west except Greece. But all the developing economies except China and Turkey have resulted positive and significant correlations between them. That means consumers buying behavior and their perceptions about the economy is going in reverse way in the developed nations and in direct way for the developing nations. The case for the developed nations is a departure from the standard perceptions of positive relation between the two. The ground for such a reverse result may be the global financial crisis that altered the normal association of the variables. Segregating the entire data into pre crisis, crisis and post crisis phases we get some deviations from the above results. The magnitudes of negative correlations in the developed economies are going down in absolute sense and a few among them are significant. That means developed countries were better positioned before the

crisis. On the other hand, developing countries are losing in terms of correlation values except Turkey. China is moving from high negative to very low negative correlation figure. That means crisis may have somehow benefitted in relative sense to the developing economies compared to the developed ones. The scenario of almost all the developed countries except, Germany, Italy, Greece and S. Korea, get changed during the crisis phase where the degrees of correlations shifted to high positive and significant values. It is not good news as the positive correlations are obtained from two downward moving series. The developed countries are badly hit by the crisis. The case for Germany is that its CCI was moving in upward direction which was opposite to its consumption series. Some developing countries are badly affected by the crisis like China, Turkey, Brazil and Argentina where either one or both the consumption and CCI get affected. But there are the countries like Thailand, India where we observed rising consumption and CCI levels even under crisis condition. But during the post crisis era almost all the countries tried to recover relative to the crisis phase as the correlation figures show. Those who are still suffering like USA are getting benefitted in terms of their magnitudes. Some countries have benefitted by improvements in one or two variables. Germany being the only country who improved its positions in both of the variables after the crisis but Italy becoming the worst country as both of its series got downturn in the post crisis era.

ECONOMETRIC TEST RESULTS AND DISCUSSION The correlation analyses of the above section give some direction of interdependences among the variables but cannot provide any clue about who explains whom. In technical language, whether consumption spending (C) causes CCI or the reverse or both. It can be done by well known

13

 Does Consumers’ Confidence Cause Consumption Spending?

Table 2. Unit root test results of consumption spending for the entire period Consumption at Levels

Consumption at First Differences

Country

ADF

Lag

Prob

Remarks

ADF

Lag

Prob

Remarks

USA

-

-

-

NS

-2.62

1

0.10

S

UK

-2.99

1

0.09

S

-3.63

1

0.01

S

France

-2.75

3

0.06

S

-4.07

1

0.01

S

Germany

-

-

-

NS

-6.98

1

0.009

S

Greece

-

-

-

NS

-6.50

1

0.008

S

Spain

-

-

-

NS

-3.36

1

0.05

S

Italy

-3.09

1

0.05

S

-2.70

1

0.08

S

Portugal

-2.78

1

0.06

S

-3.54

1

0.01

S

Ireland

-2.72

1

0.08

S

-3.32

1

0.05

S

Russia

-

-

-

NS

-7.71

1

0.003

S

China

4.08

2

0.01

S

-7.64

1

0.003

S

India

3.49

3

0.06

S

-6.85

1

0.004

S

Japan

-

-

-

NS

-6.29

1

0.004

S

Thailand

-

-

-

NS

-4.07

1

0.01

S

S Korea

-

-

-

NS

-5.45

1

0.007

S

Brazil

3.06

1

0.05

S

-6.97

1

0.003

S

S Africa

-

-

-

NS

-4.05

1

0.01

S

Turkey

-

-

-

NS

-9.92

1

0.000

S

Argentina

-

-

-

NS

-2.76

1

0.07

S

Australia

-

-

-

NS

-5.2

1

0.005

S

Granger (op cit) Causality Test. Before to do that it is required to test whether both the series are stationary in their levels or not. If not whether they are stationary at their first differences then we need to test whether both the series are cointegrated. If so whether there are any short term deviations from the long run cointegrated relations i.e. whether there is any error in the equilibrium relation. If so, whether they are corrected or not as time go on. After incorporating all these we have to go for causality tests and the equations by which we will do all the exercises are (1) to (5). We have done all the econometric exercises for all the different phases for all individual countries. Table 2 and 3 present the unit root test results of ‘C’ and CCI series at both levels and first differences for the entire period. It is observed that

14

both the series are stationary at their levels for a few country cases but they are all stationary at their first differences irrespective of their status of developments. That means both the series are I (1) and may be cointegrated. Similar kinds of results are obtained for the pre crisis phase. Both consumption series (Table 4) and CCI series (Table 5) in the pre crisis phase are integrated of order one. That means both of the series are stationary at their first differences, not in their levels. We do not require carrying out unit root tests for the crisis and post crisis phases as their time lengths are small and it is meaningless to go for such. Table 6 presents the Johansen cointegration test results incorporating the Eigen and Likelihood Ratio values besides the lag and probability values. We have also tested the same by stationary

 Does Consumers’ Confidence Cause Consumption Spending?

Table 3. Unit root test results of consumers’ confidence indices for the entire period CCI at Levels

CCI at First Differences

Country

ADF

Lag

Prob

Remarks

ADF

Lag

Prob

Remarks

USA

-

-

-

NS

-5.0

1

0.004

S

UK

-

-

-

NS

-4.67

1

0.005

S

France

-

-

-

NS

-5.74

1

0.003

S

Germany

-3.57

1

0.01

S

-5.54

1

0.003

S

Greece

-

-

-

NS

-6.32

1

0.002

S

Spain

-

-

-

NS

-4.83

1

0.005

S

Italy

-

-

-

NS

-4.84

1

0.005

S

Portugal

-

-

-

NS

-6.21

1

0.002

S

Ireland

-

-

-

NS

-5.26

1

0.003

S

Russia

-

-

-

NS

-5.76

1

0.003

S

China

-2.77

3

0.10

S

-8.14

1

0.001

S

India

-

-

-

NS

-5.62

1

0.003

S

Japan

-2.98

2

0.05

S

-5.13

1

0.003

S

Thailand

-

-

-

NS

-4.68

1

0.005

S

S Korea

-3.08

1

0.05

S

-5.94

1

0.002

S

Brazil

-

-

-

NS

-8.28

1

0.001

S

S Africa

-

-

-

NS

-6.57

1

0.002

S

Turkey

-

-

-

NS

-6.14

1

0.002

S

Argentina

-2.69

2

0.08

S

-5.05

1

0.003

S

Australia

-3.20

1

0.05

S

-5.31

1

0.003

S

test of the errors of the linear combinations of the variables in estimated form. We observe that both the series in the entire phase are cointegrated except only Greece (even up to lag 7). May be that the financial shock affected the country. We could not test for any structural break for the countries. Doing the same analysis for the pre crisis phase we observe the existence of long run equilibrium relations for all the countries including Greece. The next exercise is to test whether there is any significant error and whether errors are corrected or not. Then we have done the Granger Causality tests for short run behavior of the series for the countries during the entire period, pre crisis period and post crisis period. Although the post crisis phase carries 15 time points we can get an idea (not robustness) about the directions of causalities.

The error correction terms should be negative and significant so that convergence towards the long run relation occurs. The magnitudes of the coefficients signify the speed of convergence. All the results are summarized in Table 7. For the post crisis phase no error corrections are required and simple Granger Causalities are carried out at the levels of the variables for short run dynamics and the results are presented in Table 8. It is observed (refer to Table 7) that the expected negative signs of error correction terms are observed for most of the developed countries like USA, UK, etc. but significant error corrections are happening for Italy only during the entire period. On the other hand, out of the developing country only Turkey produces the significant error correction. In all other countries there are no

15

 Does Consumers’ Confidence Cause Consumption Spending?

Table 4. Unit root test results of consumption spending for the pre crisis period Consumption at Levels

Consumption at First Differences

Country

ADF

Lag

Prob

Remarks

ADF

Lag

Prob

Remarks

USA

-

-

-

NS

-3.12

1

0.05

S

UK

-

-

-

NS

-5.82

1

0.00

S

France

-

-

-

NS

-4.27

1

0.01

S

Germany

-

-

-

NS

-5.84

1

0.00

S

Greece

-

-

-

NS

-6.10

1

0.00

S

Spain

-

-

-

NS

-2.99

1

0.05

S

Italy

-3.01

1

0.05

S

-3.84

1

0.01

S

Portugal

-

-

-

NS

-3.19

1

0.05

S

Ireland

-

-

-

NS

-5.06

1

0.00

S

Russia

-

-

-

NS

-4.83

1

0.01

S

China

16.46

3

0.000

S

-7.90

1

0.00

S

India

-

-

-

NS

-5.27

1

0.00

S

Japan

-

-

-

NS

-6.38

1

0.00

S

Thailand

-

-

-

NS

-3.15

1

0.05

S

S Korea

-

-

-

NS

-2.81

1

0.06

S

Brazil

-

-

-

NS

-7.14

1

0.00

S

S Africa

3.19

1

0.05

S

-3.42

1

0.05

S

Turkey

-

-

-

NS

-7.44

1

0.00

S

Argentina

-

-

-

NS

-1.91

1

0.06*

S

Australia

-

-

-

NS

-3.87

1

0.01

S

Note: Pre crisis period runs between Jan 1996 and Oct 2007, * for ADF value with no intercept and trend

error corrections. That means both the C and CCI series are in long run equilibrium relation for which causality tests are carried out at levels without incorporating the error correction components. The short run causality results show that in most of the developed countries (namely, USA, UK, France, Italy, Portugal and Ireland) both consumption spending and consumers’ confidence levels are causing each other in a bidirectional way during the entire period. The impact of such causality is that, say for USA, one billion dollar rise in consumption spending leads to fall in CCI by 0.01 units and in the contrary, one unit fall in CCI leads to rise in consumption by 34.2 billion dollar. That means there may be other important indicators beside CCI that help consumption to

16

rise for USA. For all the developed countries the regression coefficients are negative. Also to add that in Thailand, Brazil and Turkey like developing countries consumers sentiment is also playing the role to explain consumption and the reverse causations are also working for them. It is a very notable feature that consumers’ confidence is playing as one of the important roles for determining consumption spending of the countries during entire quarters. Only CCI is the cause for consumption spending for Greece, Spain, Russia, Argentina and South Africa. All the developing countries’ regression results are positive except one way negative result for Turkey and China. Thailand and Brazil are producing higher impact factor compared to all the developing countries of

 Does Consumers’ Confidence Cause Consumption Spending?

Table 5. Unit root test results of consumers’ confidence indices for the pre crisis period CCI at Levels

CCI at First Differences

Country

ADF

Lag

Prob

Remarks

ADF

Lag

Prob

Remarks

USA

-

-

-

NS

-4.20

1

0.01

S

UK

-3.16

2

0.05

S

-5.80

1

0.00

S

France

-

-

-

NS

-4.57

1

0.01

S

Germany

-3.09

1

0.05

S

-4.56

1

0.01

S

Greece

-2.97

2

0.05

S

-4.74

1

0.01

S

Spain

-

-

-

NS

-4.55

1

0.01

S

Italy

-

-

-

NS

-4.46

1

0.01

S

Portugal

-

-

-

NS

-4.20

1

0.01

S

Ireland

-

-

-

NS

-4.19

1

0.01

S

Russia

-

-

-

NS

-5.50

1

0.00

S

China

-3.29

1

0.05

S

-6.12

1

0.00

S

India

-

-

-

NS

-4.58

1

0.00

S

Japan

-

-

-

NS

-5.33

1

0.00

S

Thailand

-

-

-

NS

-3.74

1

0.05

S

S Korea

-

-

-

NS

-5.62

1

0.00

S

Brazil

-

-

-

NS

-6.82

1

0.00

S

S Africa

-

-

-

NS

6.18

1

0.00

S

Turkey

-

-

-

NS

-6.45

1

0.00

S

Argentina

-

-

-

NS

-4.02

1

0.01

S

Australia

-2.86

2

0.06

S

-5.49

1

0.00

S

the sample. Consumption spending is causing CCI for Germany, China and India. No way is causality observed for Japan, South Korea and Australia, known as the developed countries of the east. Whether the presence of the crisis phase affects the directions of causality we need to bifurcate the total period into pre and post crisis phases. During pre crisis period significant error correction (convergence to the long run equilibrium) is observed for five countries, viz. Germany, Greece, Italy, Turkey and Argentina. Also that consumption expenditure in rising form is causing confidence of the consumers to rise for many countries in different status. They are USA, UK, Italy, Ireland, India, Japan and Thailand. Greece remaining in same nature throughout the entire period is still producing causality from CCI to

consumption. Portugal and Brazil remain in the feedback causality status. Australia produces feedback causality during the pre crisis period from the position of no causality in the entire period. Like the entire period’s regression results the developed countries with any sort of causality results produce negative impact of C on CCI or the reverse and the developing countries are with positive regression coefficients. Thailand and Brazil still have high impact factor. But there are eight countries where we do not find any sort of causality between the two which are France, Germany, Spain, Russia, S. Korea, South Africa, Turkey and Argentina. As observed from Table 8 that there are drastic changes in the causality results. In nine out of the sample of countries there is no way causality

17

 Does Consumers’ Confidence Cause Consumption Spending?

Table 6. Johansen cointegration test results Entire Period (Jan 1996 - Oct 2012) Country

Eigen Value

Likelihood Ratio

Lag

Pre Crisis Period (Jan 1996 – Oct 2007) Prob

No. of CEs

Eigen Value

Likelihood Ratio

Lag

Prob

No. of CEs

USA

0.19

19.80

2,2

0.01

2

0.32

18.52

1,1

0.01

1

UK

0.24

25.72

1,1

0.01

2

0.26

15.46

1,1

0.05

1

France

0.21

21.8

1,1

0.01

2

0.29

16.02

2,2

0.05

1

Germany

0.24

20.02

1,1

0.01

1

0.25

16.3

1,1

0.05

1

Greece

0.07

6.01

≤ 7,7

0.20

0*

0.38

25.64

1,1

0.05

1

Spain

0.14

16.55

3,3

0.05

2

0.23

21.75

1,1

0.05

2

Italy

0.19

19.88

2,2

0.05

2

0.27

18.8

2,2

0.05

1

Portugal

0.47

46.2

1,1

0.01

2

0.32

21.9

1,1

0.01

1

Ireland

0.31

31.8

1,1

0.01

2

0.57

39.8

1,1

0.00

1

Russia

0.19

15.5

3,3

0.05

1

0.19

13.85

1,1

0.05

2

China

0.19

20.01

1,1

0.05

2

0.28

16.49

1,1

0.01

1

India

0.21

15.9

2,2

0.05

1

0.19

14.27

3,3

0.05

2

Japan

0.12

14.39

2,2

0.05

2

0.62

47.8

4,4

0.00

1

Thailand

0.24

18.7

1,1

0.04

1

0.26

16.74

1,1

0.05

1

S Korea

0.21

15.8

4,4

0.05

1

0.23

14.61

4,4

0.05

1

Brazil

0.145

15.75

2,2

0.05

2

0.29

15.9

1,1

0.05

1

S Africa

0.34

27.5

2,2

0.01

1

0.19

16.73

1,1

0.05

2

Turkey

0.17

13.1

≤ 5,5

0.10

1

0.32

19.27

1,1

0.05

1

Argentina

0.25

21.09

1,1

0.01

1

0.26

17.2

1,1

0.05

1

Australia

0.29

22.35

2,2

0.01

1

0.40

26.08

2,2

0.01

1

Notes: * mark represents no cointegration result

between the variables during the post crisis era. Again out of the remaining sample, consumption is the cause for CCI for seven countries. CCI is the cause for consumption for Germany, Italy and Thailand. Spain is the only country where both the variables are causing each others. This may imply that regaining consumption expenditure in seven countries leading the consumer sentiments of these countries to rise and in nine ‘no causality countries’ consumption and confidence variables may find other determinants to cause or to be caused by. Only six countries produce significant impact of the directions of causalities. We did not find any country having no causal relation between the two for all the three phases simultaneously.

18

CONCLUDING REMARKS The study so far we have made identifies interplay between consumers’ confidence levels and consumption spending of a sample of twenty countries over the quarterly time period of 1996 to 2012. We observed that both consumption spending and the consumers’ confidence of most of the developed countries were positively correlated during all the three time phases whereas the developing countries in majority of the cases produced negative correlation. The interplay between the two variables have been demonstrated by causality tests which show that majority of the developed countries and a few developing countries produce

 Does Consumers’ Confidence Cause Consumption Spending?

Table 7. Granger causality test results for the entire and pre crisis periods Entire Period (Jan 1996 - Oct 2012)

Pre Crisis Period (Jan 1996 – Oct 2007)

Country

Status of Long Run Relation

Error Correction Terms (Prob)

Status of Error Correction

Directions of Causality

Status of Long Run Relation

Error Correction Terms (Prob)

Status of Error Correction

Directions of Causality

USA

Yes

-0.003(0.67)

No

C↔CCI

Yes

-0.003(0.4)

No

C→CCI

UK

Yes

-0.01(0.28)

No

C↔CCI

Yes

-0.01(0.21)

No

C→CCI

France

Yes

0.01(0.11)

No

C↔CCI

Yes

0.01(0.15)

No

No

Germany

Yes

-0.03(0.16)

No

C→CCI

Yes

-0.05(0.09)

Yes

No

Greece

No

-

-

CCI→C

Yes

-0.17(0.04)

Yes

CCI→C

Spain

Yes

-0.01(0.39)

No

CCI→C

Yes

-0.003(0.8)

No

No

Italy

Yes

-0.03(0.03)

Yes

C↔CCI

Yes

-0.03(0.01)

Yes

C→CCI

Portugal

Yes

0.30(0.000)

No

C↔CCI

Yes

-0.01(0.55)

No

C↔CCI

Ireland

Yes

0.01(0.46)

No

C↔CCI

Yes

0.02(0.12)

No

C→CCI

Russia

Yes

1.00(0.00)

No

CCI→C

Yes

-0.009(0.8)

No

No

China

Yes

1.0(0.00)

No

C→CCI

Yes

0.02(0.35)

No

CCI→C

India

Yes

-0.04(0.51)

No

C→CCI

Yes

-0.000(0.9)

No

C→CCI

Japan

Yes

1.0(0.00)

No

No

Yes

-0.03(0.39)

No

C→CCI

Thailand

Yes

1.0(0.00)

No

C↔CCI

Yes

-0.02(0.33)

No

C→CCI

S Korea

Yes

1.0(0.00)

No

No

Yes

-0.02(0.23)

No

No

Brazil

Yes

0.008(0.74)

No

C↔CCI

Yes

-0.06(0.32)

No

C↔CCI

S Africa

Yes

1.0(0.00)

No

CCI→C

Yes

0.03(0.01)

No

No

Turkey

Yes

-0.14(0.04)

Yes

C↔CCI

Yes

-0.42(0.00)

Yes

No

Argentina

Yes

1.00(0.00)

No

CCI→C

Yes

-0.08(0.05)

Yes

No

Australia

Yes

1.0(0.00)

No

No

Yes

0.01(0.04)

No

C↔CCI

Note: Bold figures in the parentheses of causality directions represent significant results at least at 5% levels. The first result is for C causing to CCI and the reverse is for the second.

the result of bidirectional causalities whereas the leading emerging countries like China and India, it is the volume of consumption spending that is leading to change in consumers’ confidence in a causal way for the entire period of study. However, the global financial crisis has put some impact on the interplay between the variables. The segregation of the result show that the leading developed countries experience unidirectional causal relation from volume of consumption to consumers’ confidence like that of China and India. In the post crisis phase seven out of twenty countries produce a line of causation going from consump-

tion to confidence and nine countries fail to show any line of causation. Hence, it is concluded that consumers’ confidence is an important determining factor of consumption spending in particular and growth in general for all status of countries. The financial crisis has affected the chain of relation and showed the importance of confidence as one of the determining factors. The exploration of other related variables of consumption spending and consumers’ confidence in future should be given importance to modify the above mentioned interplay, particularly when there is no causal link. The variables may be unemployment, inflation,

19

 Does Consumers’ Confidence Cause Consumption Spending?

Table 8. Granger causality test results for the post crisis periods Country

Lags

Directions of Causality

USA

2

No

UK

1

C→CCI

France

2

No

Germany

1

CCI→C

Greece

2

No

Spain

2

C↔CCI

Italy

1

CCI→C

Portugal

2

No

Ireland

2

No

Russia

2

No

China

2

No

India

2

No

Japan

2

No

Thailand

1

CCI→C

S Korea

1

C→CCI

Brazil

2

C→CCI

S Africa

1

C→CCI

Turkey

1

C→CCI

Argentina

2

C→CCI

Australia

1

C→CCI

Note: Bold figures in the parentheses of causality directions represent significant results at least at 5% levels. The first result is for C causing to CCI and the reverse is for the second.

interest rates on consumer credits, growth rates, government debt to GDP ratio, etc. The model will then require a multivariate econometric modeling. It can further be verified whether any pooling of data for all countries, developed or developing separately make any significant change in the above results of the interplay among all possible variables.

20

REFERENCES Aisbett, E, Brueckner, M., Steinhauser, R. & Wilcox, R. (2013). Fiscal stimulus and households’ non-durable consumption expenditures: Evidence from the 2009 Australian Nation Building and Jobs Plan. Australian Research Council Linkage Project, December. Allen, F., & Carletti, E. (2009). The global financial crisis: Causes and Consequences. Retrieved from www.bm.ust.hk Banks, J., Crawford, R., Crossley, T., & Emmerson, C. (2012). The effect of the financial crisis on older households in England, Working Paper. Institute for Fiscal Studies, October. Bayoumi, T., Tong, H., & Wei, S.-J. (2010). The Chinese corporate savings puzzle: A Firm-level cross-country perspective. NBER Working Papers, National Bureau of Economic Research. Bram, J., & Ludvigson, S. (1997). Does consumer confidence forecast household expenditure? A Sentiment Index Horse Race; Federal Reserve Bank of New York, March. Bulman, D. J. (2010). China and the financial crisis: Stimulating and understanding household consumption. Retrieved from www.stanford.edu/ group/sjeaa Carmassi, J., Gros, D., & Micossi, S. (2009). The global financial crisis: Causes and cures. Journal of Common Market Studies, 47(5), 977–996. doi:10.1111/j.1468-5965.2009.02031.x Celik, S., Aslanoglu, E., & Deniz, P. (2010). The relationship between consumer confidence and financial market variables in Turkey during the global crisis, 30th Annual Meeting of The Middle East Economic Association, Allied Social Science Associations, Atlanta, GA, Jan 3-6

 Does Consumers’ Confidence Cause Consumption Spending?

Chai, J., Maurer, R., Mitchell, O., & Rogalla, R. (2011). Lifecycle impacts of the financial and economic crisis on household optimal consumption, Portfolio Choice, and Labor Supply. Netspar Discussion Paper, The Netherlands, June

Hurd, D. M., & Rohwedder, S. (2011). The effects of the financial crisis on actual and anticipated consumption. Michigan Retirement Research Center Working Paper, University of Michigan, October.

Chor, D., & Manova, K. (2010). Off the cliff and back? Credit conditions and international trade during the global financial crisis. NBER Working Paper Series

Kumar, R (2009). Global financial and economic crisis: Impact on India and policy response. UNDP India Report, April.

Christelis, D., Georgarakos, D., & Jappelli, T. (2011). Wealth shocks, unemployment shocks and consumption in the wake of the great recession. Centre for Studies in Economics and Finance (Italy) Working Paper no. 279 Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427–431. doi:10.2307/2286348 Egol, M., Clyde, A. A., & Rangan, K. (2010). The new consumer frugality. Retrieved from www. strategybusiness.com Engle, R. F., & Granger, C. W. (1987). Cointegration and error correction: Representation, estimationand testing. Econometrica, 55(2), 251–276. doi:10.2307/1913236

Lee, J., Rabanal, P., & Sandri, D. (2010). U.S. consumption after the 2008 crisis. Working Paper, Research Department, IMF, January. Lin, Y. J., & Treichel, V. (2012). The unexpected global financial crisis-researching it’s root cause. Policy Research Working Paper, World Bank, January Mansoor, D. (2011). The global business crisis and consumer behavior: Kingdom of Bahrain as a case study. International Journal of Business and Management, 6(1), 104–115. Mielcova, E. (2011). Impact of financial crisis on European households. In Conference Proceedings of 13th International Conference on Finance and Banking, Ostrava, Czech Republic, October

Ghosh, J. (2009). Global Crisis and the Indian Economy, UNDP India Report, April

Myrie, S., & Robinson, O. (2013). Effects of world financial crisis on food consumption spending among households in Jamaica. International Institute for Science Technology and Education, 3(2), 12–23.

Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross spectral methods. Econometrica, 37(3), 424–438. doi:10.2307/1912791

Schneider, F., & Kirchgässner, G. (2009). Financial and world economic crisis: What did economists contribute? Public Choice, 140(3-4), 319–327. doi:10.1007/s11127-009-9479-y

Hamilton, J. D. A. (1994). Time series analysis. Princeton, NJ: Princeton University Press.

Shiller, R. J. (2008). The subprime solution. New Jersey: Princeton University Press.

Haughton, J., & Khandker, S. R. (2012). The surprising effects of the great recession- Losers and winners in Thailand in 2008–2009. The World Bank Policy Research Working Paper, November.

Thompson, B. (2009). Impact of the financial and economic crisis on nutrition: Policy and programme responses. Food and Agriculture Organization of the United Nations (AGN), Nutrition and Consumer Protection Division, Working Paper.

21

 Does Consumers’ Confidence Cause Consumption Spending?

Voinea, L., & Filip, A. (2011). Analyzing the main changes in new consumer buying behavior during economic crisis. International Journal of Economic Practices and Theories, 1(1), 14–19. Xinhua, H., & Cao, Y. (2007). Understanding high saving rate in China. China & World Economy, 15(1), 1–13. doi:10.1111/j.1749124X.2007.00049.x

ADDITIONAL READING Enders, W. (2011). Applied Econometric Time Series. India: Wiley & Sons. Green, W. H. (2011). Econometric Analysis (7th ed.). Prentice Hall. Gujarati, D. (2003). Basic Econometrics. USA: McGraw Hill. Maddala, G. S. (2005). Introduction to Econometrics (3rd ed.). Prentice Hall.

KEY TERMS AND DEFINITIONS Causality Test: In a bivariate or multivariate time series data of variables there may be causal relations among them in the short run. This is usually tested by Granger causality tests. For detail refer to the methodology section. Cointegration Test: It is the method of testing whether there is any sort of long run equilibrium relation between two time series data. If two series are integrated of order one then their linear combination will be stationary. For detail refer to the methodology section. Consumer Confidence: Consumer confidence is an indicator designed to measure the degree of optimism that consumers assess the overall state of the economy and their personal financial and resource situations. How confident people are about stability of their incomes deter-

22

mines their spending and savings activities and therefore serves as one of the key indicators for the overall shape of the economy. If consumer confidence is higher, consumers are making more purchases, boosting the economic expansion. On the other hand, if confidence is lower, consumers tend to save more than they spend, prompting the contraction of the economy. Therefore, growth and consumers sentiments are interdependent. A value of around 100 is called high consumers’ confidence index and below 50 is called poor levels of consumers’ confidence. Consumer Spending: The amount of money/ budget spent by households/consumers in an economy for better livelihoods. The spending includes durables, such as washing machines, and nondurables, such as food. It is also known as consumption. John Maynard Keynes considered consumer spending to be the most important determinant of short-term demand in an economy. When the government wants to stimulate the economy it will attempt to increase consumer spending. This can be done by tax cuts or even through giving out a lump sum or money. The increased income is expected to cause individuals to purchase more goods and services which mean firms/suppliers will experience higher revenues and can potentially hire more factors of production. Correlation: In economics we find many variables which are interdependent or in other words they are associated to each other. It may be the case that both the variables may be related in positive direction or negative direction. The term ‘correlation’ thus, is concerned with the strength or degree of association between a bivariate data set. The degree of such association is measured by Coefficient of Correlation. If X and Y be two variables with combinations of observation (x1, y1), (x2, y2)……. (xn, yn) then the Coefficient of Correlation given by Pearson formula is rxy = Cov (x, y)/S.D (x). S.D(y). If X and Y are positively correlated then rxy is positive and if they are negatively correlated then rxy is negative. If there is linear upward and downward association

 Does Consumers’ Confidence Cause Consumption Spending?

between the two variables then we get perfect or linear correlation with the values of rxy is +1 and -1 respectively. Error Correction: Existence of long run equilibrium relation between two non stationary time series does not necessarily mean that there should not be any deviation or error from the equilibrium relation. How much the deviation or error gets corrected over time is tested by this method. For detail refer to the methodology section.

Financial Crisis: It is defined as the failure in banking and financial system originated from the USA due to housing bubble bursts and slump in the housing as well the entire economy of the country and spread to the other countries via different trade and stock exchange networks. Unit Root Test: It is the method of testing whether a time series of a variable is stationary or not. If it bears the value unity then the series is non stationary. For detail refer to the methodology section.

23

24

Chapter 2

The Role of Market Sentiment in Stock Price Movements: An Indian Experience Kiranjit Sett West Bengal State University, India Debabrata Mukhopadhyay West Bengal State University, India

ABSTRACT In an efficient capital market, the prices of securities always fully reflect all available information implying that prices always reflect the fundamental values. When there is under reaction or over reaction to new information, competition among the arbitrageurs quickly brings the price of an asset back to its fair value. But, if the asymmetry of information about a stock is high and there is a ‘limit to arbitrage’, sentiment of the noise traders is likely to influence the price of that stock. This chapter aims at studying the role of market sentiment, during the period which starts with June 2003 and ends with July 2011, in influencing the return from investment in small capitalization stocks listed on Indian stock exchanges. We have found the presence of ARCH (1) in the time series on returns. Market sentiment, rate of interest and inflation are found to have significant influence on return from investment in small capitalization stocks. The presence of month effects in returns from such stocks has also been detected.

INTRODUCTION In a perfect and frictionless capital market, the competition among profit-seeking arbitrageurs makes the prices of securities equal to their fair values (Modigliani & Miller, 1958; Horne, 2006). In reality, capital markets are far from perfect due to the existence of a number of imperfections and frictions like taxes, floatation costs, cost

of information, cost of trading etc. But capital markets can be efficient in which the prices of securities fully reflect all available information (Fama, 1965a; Fama, 1965b). The efficient market hypothesis (hereinafter called EMH) holds that when a new piece of information (which has the potential of affecting the price of a security) arrives the market, it gets incorporated in the price instantaneously and accurately resulting into an

DOI: 10.4018/978-1-4666-8274-0.ch002

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 The Role of Market Sentiment in Stock Price Movements

immediate reaction to the price and rate of return, but in the absence of any new information, the rate of return is likely to be commensurate with the risk associated with the investment and tenure of such investment (Fama, 1965a; Fama, 1965b; Fama, 1991). Since the expected values of the variables affecting the stock price are likely to have already incorporated in the price at a given point of time, only the shocks (i.e., unpredicted elements) contributing to the changes in the expectations can make abnormal changes in the prices of securities. Since unpredictable shocks occur randomly, abnormal movements in the prices of securities or rates of return on investment in such securities are also likely to be random. So, the abnormal movements in prices or rates of return are likely to be independently and identically distributed (Fama, 1965a; Fama, 1965b; Fama, 1970). Thus, in an efficient capital market, returns will be commensurate with risks (Malkiel, 2003) and time. The uninformed investors who invest in well diversified portfolios are likely to generate returns which would not be significantly different from the rate of returns which smart investors can generate (Malkiel, 2003). Economic reforms and particularly the financial sector reforms introduced in India since 1991 have aimed at unshackling the Indian economy from bureaucratic controls. The financial sector reforms have aimed at making Indian financial system efficient and vibrant and integrating Indian financial markets with other financial markets of the world. Several measures have been taken in order to increase the efficiency of the Indian financial markets with respect to their operations, allocation of resources and incorporation of available information into prices. In an efficient market dominated by rational traders, the role of market sentiment is likely to be less and financial markets are likely to play an important role in mobilizing funds from ultimate savers and allocating funds to ultimate users at market determined rates efficiently whatever may be the size of savings, investment and firm.

But, in reality, the prices of shares of small and new companies which are characterized by high asymmetry of information are influenced by market sentiment. As a result, these small and new companies face greater hurdles in raising capital from the market than the large and diversified companies. Hence, this empirical investigation about the role of market sentiment in influencing the prices of stocks listed on Indian stock exchanges has been undertaken. We have detected the presence of ARCH (1) in returns. We have found that market sentiment has significant influence on returns from investment in small capitalization stocks. Interest rate and inflation also have significant influences on the returns from such stocks. We have also detected the presence of month effects on the returns from such stocks. This paper has nine sections viz., introduction, review of literature, motivation for the study, objective of the study, identification of dependent and independent variables, methodology and model, findings, analysis and interpretations and concluding remarks. The rest of the sections have been laid down hereunder.

REVIEW OF LITERATURE In an efficient capital market, information gets incorporated in the prices of the securities accurately and as soon as it arrives the market. But the possibility of under or over–reaction by the investors to the new piece of information under the condition of uncertainty exists. In case of over–reaction, price increases above the fair value when the new information has the potential to increase the price. Again, when the new information has the potential to reduce the price, price falls below the fair value when there is over–reaction. On the other hand, when good news arrives into the market but there is under–reaction to it, the initial increase in price produces a price that falls below the fair value. When a bad news arrives and

25

 The Role of Market Sentiment in Stock Price Movements

there is under–reaction to it, the initial fall in price produces a price which stops above the fair value. The under– or over–pricing of securities creates arbitrage opportunities for the rational traders and competition among these rational traders brings the prices of securities back to their fair values when such arbitrageurs are not constrained. If the true implication of the information as perceived by the market gets reflected in the price quickly, the pattern in price movements is likely to be short–lived (Fama, 1998). Even when, market over–reacts to some events and under–reacts to some other events and such over–reactions and under–reactions occur randomly and are evenly distributed in the long–run, market is said to be efficient (Fama, 1998). But, after the initial under– or over–reaction to the new piece of information, the market price may move towards the fair value slowly and thereby may generate a persistent pattern in the stock price movements (De Bondt, Werner & Thaler, 1985; Barberis, Shleifer & Vishny, 1998). Longer the time taken by the market to perceive the full implication of the information accurately longer will be the duration of trend in price movements. When there is under–reaction, the ‘relative strength’ strategy of selling past losers and buying past winners generates a rate of return which is higher than the normal rate of return of comparable risk provided arbitrage is not risky and constrained. The normal rate of return is the rate of return generated by a simple buy and hold strategy. On the other hand, in case of over–reaction, the ‘contrarian’ strategy of buying past losers and selling or short–selling past winners generates a rate of return which is superior to the normal rate of return of comparable risk when arbitrage is not risky and constrained. If the under– or over–reactions occur systematically, it is possible for rational traders to beat the market consistently by designing appropriate trading strategies. But arbitrage may become risky and costly when market sentiment becomes a dominant force in determining the price. This happens when one

26

of the important underlying assumptions of an efficient capital market that investors are rational is violated and the market, for some time, is dominated by irrational investors whose trades are driven by feeling rather than an evaluation of the information about fundamental variables on a rational manner. Market psychology or sentiment is the feeling of the market participants about the prices of securities. One of the important attribute of human beings is emotion which is likely to affect the perceptions of such human beings about the reality and consequently affect their decisions. The emotion–loaded perceived world may be quite different from the real world. Since the prices of securities reflect the weighted averages of the beliefs of the rational and irrational investors, when irrational investors dominate, prices move away from their fundamental values as perceived by the rational traders. So, when rational traders dominate, prices are brought to their fair values through arbitrage and wealth flows from irrational traders to rational traders (Daniel, Hirshleifer & Teoh, 2002). On the other hand, when irrational traders are aggressive for quite some time, prices continue to move away from the fair values and wealth flows from rational traders to irrational investors since rational traders are risk-averse (Daniel et. al., 2002), have short investment horizon and sometimes they have leveraged positions. Thus, when investors take time to understand the full implications of the new information, the initial reactions of investors to new information may create a pattern in the stock price movements. Moreover, when good news is followed by good news, investors expect a future better than what it would have been otherwise. Investors extrapolate the past growth rates into the future (La Porta, Lakonishok, Shleifer & Vishny et. al., 1997). On the other hand, when bad news is followed by bad news, investors expect a poorer future (Barberis et. al., 1998). Under these situations the initial patterns are strengthened. Investors who make decisions on the basis of the behaviour of the

 The Role of Market Sentiment in Stock Price Movements

investors, who trade earlier rather than on the basis of the information possessed by them about the stock, are likely to take the stock prices away from their true values by strengthening further the prevailing pattern in the stock price movements. If more investors follow the actions undertaken previously by others, there may be an ‘information cascade’ or ‘snowballing effect’ or ‘feedback effect’ (Bikhchandani & Sharma, 2001; Shiller, 2003; Shiller, 2007) which may result into a situation where stock prices move away further from their true values. But when good news is followed by bad news, investors expect the performance to be ‘mean-reverting’. But eventually, market will realize the extreme situations caused by continuous under– or over– pricing of assets and reversals in the prices of assets will take place. If it is difficult to predict the time when reversals will take place, arbitrage requires longer investment horizon. If arbitrageurs are risk averse and have relatively short time horizon, their ability to bring the prices back to their fair values is likely to be limited in the presence of ‘noise traders’ who drive the prices away from their fundamental values (Baker & Wurgler, 2007). Arbitrage also becomes risky for those rational traders who are leveraged or who manage the money of the people who may want their money back if they get panicked. These fund managers are also not likely to take a stand contrary to the market if they fear to lose their jobs if their performance is found to be poor as compared to the performance of the market. So, arbitrage may be risky and costly under such situations (Baker & Wurgler, 2007). Because of the presence of ‘noise traders’ risk, reversals take longer time to take place. As a result, there will be positive autocorrelation in the stock price movements in the short–run but negative autocorrelation in the long–run (Daniel et. al., 1998). Thus, although markets may not be crazy all the time but sometimes may be significantly influenced by irrational investors whose trades may be

driven by noise or psychological factors (Shiller, 2003). The securities about which information is likely to be less accurate are difficult to value and are likely to be affected more by the investors’ sentiment and the limited ability of the rational traders to arbitrage (Baker & Wurgler, 2007). As a result, the prices of such securities may follow patterns and can be partially predictable (Malkiel, 2003; Shiller, 2003). Thus, market sentiment can explain partially the variability in return from investments in such securities.

MOTIVATION FOR THE STUDY In order to promote ‘equity cult’ among Indian investors, Government of India has taken several measures. Unit Trust of India was established in 1964 with a view to mobilizing household savings and investing such savings in Indian stock markets (Datt & Sundharam, 2007). But until 1992, the primary capital market had been controlled by the Controller of Capital Issues with an excuse of protecting the interests of the investors (Joseph, Nitsure, & Sabnavis, 2002). The Securities and Exchange Board of India (hereinafter called SEBI) was established in 1988. SEBI has been given the regulatory powers in 1992 with the enactment of the Securities and Exchange Board of India Act, 1992 (Datt & Sundharam, 2007). With these changes in the regulatory framework, companies have been allowed to price their issues based on their perception about the market conditions. With the initiation of financial sector reforms in the early nineties, many companies raised equity share capital at hefty premiums by capitalizing the euphoria among the ordinary retail investors about the stock market (Joseph et. al., 2002). Some companies with fake addresses and projects raised capital from the market and then left the scene (Pathak, 2010). Again, the promises made by some promoters could not be materialized (Datt & Sundharam, 2007). But some companies which

27

 The Role of Market Sentiment in Stock Price Movements

also have raised funds from the capital market have been able to create enormous amount of wealth for their investors. Realizing the menace, SEBI has come out with a number of regulations in order to protect the interests of the investors. Despite the measures taken by SEBI, the ordinary retail investors who invest directly in the securities lose money for various reasons (Bhole & Mahakud, 2009; Ghosh, 2003). Since they do not have enormous amount of funds with them, they invest in the shares of small companies when stock market rallies because the stock prices of large companies go beyond their reach. Interestingly, retail investors get attracted to the equity shares when stock prices rise (Joseph et. al., 2002). When stock prices fall, they get panicked and sell the shares. In the process, they end up buying over–priced shares and selling under–priced shares. This is in contrary to the principle of ‘buy under–priced shares and sell over–priced shares’ in order to maximize gain. It is a fact that companies bring public issues of shares when stock market conditions are favourable and avoid going public when stock market conditions are unfavourable. There are instances of over–subscription of issues of shares which are brought to the market by small or medium or relatively new companies when stock market conditions are favourable. In many cases, on the first day of listing, these shares are traded at a price which is significantly higher than the issue price. When the stock market bubble bursts, the prices of some of these shares also fall significantly. And, interestingly the rate of decline in the prices of some of these shares may be higher than the rate of fall in the stock market index. There is no medicine which can cure the ‘herd behaviour’ of the investors unless the investors themselves realize their shortcomings and hold on their nerves. Instead of investing directly into the securities, they may invest through mutual funds. But if they invest through mutual funds, they fail to gain from their superior judgment and have to bear the management fees. In order to achieve

28

consistency in performance, these investors need to be properly educated, informed and need to make decisions as rationally as possible. Table 1 shows that Indian capital markets comprise of nineteen stock exchanges in which shares are transacted in cash and two stock exchanges which provide for dealing in derivative instruments. Around 5,200 scrips are listed on Bombay Stock Exchange (hereinafter referred to as BSE) and 1,665 scrips/companies are listed on National Stock Exchange (hereinafter referred to as NSE). The BSE and NSE are the two leading stock exchanges in India. The total market capitalization of stocks listed on BSE and NSE comes to around Rs 123 lakh crore which is around 139% of the gross domestic product (GDP) of the country. These two exchanges have large turnover too (around 67.75% of GDP). Amount of resources mobilised from the primary capital market have increased significantly over the years indicating the growing importance of the capital market as a source of external finance. A whopping Rs 2.08 lakh crore of funds have been raised from the primary market during the period 1/4/2008 to 31/12/2012. Out of this, around Rs 1.53 lakh crore of funds have been raised by issuing equity shares. This amount is lower than the Rs 1.83 lakh crore of funds raised by issuing equity shares during the period 1/4/2003 to 31/3/2008. Issue of equity shares dominates the fund raising activities in the primary capital market. Interestingly, the average size of issue of equity shares has increased significantly from Rs 10.68 crore of the period 1993–1998 to Rs 547.39 crore of the period 2008–2012. Table 1 also shows that the number of registered Foreign Institutional Investors (FIIs) has increased from 496 as on 31/3/1998 to 1,759 as on 31/12/2012. The number of registered Mutual Funds (MFs) has also increased from 38 to 51 during this period. Foreign portfolio investment has increased tremendously from around Rs 0.51 lakh crore which was invested during the period 1/4/1993 to 31/3/1998 to around Rs 4.27

 The Role of Market Sentiment in Stock Price Movements

Table 1. Salient features of the Indian stock markets Sr. No.

Particulars

1/4/1993 to 31/3/1998

1/4/1998 to 31/3/2003

1/4/2003 to 31/3/2008

1/4/2008 to 31/12/2012

22

23+2

19+2

19+2

     ▪ BSE

6,815

7,363

7,757

5,191

     ▪ NSE

1,357

788

1,236

1,665

     ▪ Sensex

3,893

3,049

15,644

19,427

     ▪ Nifty

1,117

978

4,735

5,905

No. of FIIs registered with SEBI (At the end of the period)

496

502

1,319

1,759

No. of MFs registered with SEBI (At the end of the period)

38

38

40

51

91,663 55,417 5,187 10.68

31,125 11,378 292 38.97

1,99,447 1,83,349 485 378.04

2,07,848 1,52,722 279 547.39

No. of recognized Exchanges at the end of the period (Cash market + Derivative market) No. of scrips listed (BSE) / companies available for trading (NSE):

Indices at the end of the period:

Resources mobilized from primary market (Rs Crore) Out of which, equity share capital mobilized (Rs Crore) Number of issues of equity shares (No.) Average size of issue of equity shares (Rs Crore) Average annual turnover to GDP (%):      ▪ BSE

8.07

22.02

21.46

16.19 ##

     ▪ NSE

14.41 *

32.73

45.36

51.56 ##

      ▪ BSE

5,60,325

5,72,198

51,38,015

62,14,941 #

      ▪ NSE

4,81,503

5,37,133

48,58,133

60,96,518 #

      ▪ BSE

41.4

23.3

103.0

70.2 #

      ▪ NSE

31.6

21.9

97.4

68.8 #

Market capitalization at the end of the period (Rs Crore):

Market capitalization to GDP at the end of the period (%):

Foreign Portfolio Investment during the period (Rs Crore)

50,939

39,841

2,90,894

4,27,059

Asset under the custody of custodians of FIIs/SAs at the end of the period

NA

56,139

7,36,753

13,35,189

Asset of Mutual Funds at the end of the period

NA

1,09,299

5,05,152

5,59,995

BSE stands for Bombay Stock Exchange. NSE stands for National Stock Exchange. NA stands for Not Available. Source: Handbook of Statistics on Indian Securities Market, 2004; SEBI. Handbook of Statistics on Indian Securities Market, 2011; SEBI. Annual Report 2011-12, SEBI. SEBI Bulletin, January, 2013. * Last three years average. # As on 31st March 2012. ## Upto 31st March, 2012.

lakh crore which was invested during the period 1/4/2008 to 31/12/2012. The value of assets under the custody of the custodians of FIIs has increased tremendously from around Rs 0.56 lakh crore as on 31/3/2003 to Rs 13.35 lakh crore as on 31/12/2012. The value of assets under the management of MFs has also increased from Rs 1.09 lakh crore to Rs 5.60 lakh crore during the same period.

The above facts indicate that the presence and influence of the institutional investors in the Indian capital market have increased significantly over the years. The investment managers of these institutions are likely to be more informed and rational than small or retail investors. Thus, a capital market dominated by such institutional investors is likely to have high informational efficiency.

29

 The Role of Market Sentiment in Stock Price Movements

But, these investment managers are also human beings and so they are expected to make mistakes. These managers may not want their performance to fall below the performance of a peer group by adopting a strategy different from the strategy of the peers and taking a position against the market when they are likely to be sacked if they perform poorly in comparison to the peer group (Lackonishok et. al., 1992). Moreover, the proportion of market capitalization held by the foreign portfolio investors, which is around 11% as on 31/12/2012, is still not very significant. Hence, a study of the market efficiency in general and the role of market sentiment in particular, in a market with these characteristics, are assumed to be relevant.

OBJECTIVE OF THE STUDY The objective of this chapter is to examine the influence of the market sentiment on the rate of return from investment in equity shares. The valuations of the shares are likely to be highly subjective and volatile if there is high asymmetry of information about those shares. These shares are also likely to be affected by speculative demands. The shares of the new, small, growth-oriented or unprofitable companies are likely to fall in this category. Arbitrage in the shares of these companies is likely to be riskiest and costliest (Baker & Wurgler, 2006 & 2007). And consequently, the prices of such shares are likely to be significantly influenced by market sentiment. But the market price of shares of a company is also likely to be influenced by the company-specific factors and other common factors. Thus, the rate of return from investment in the shares of a company having small capitalization is affected by market sentiment as well as factors specific to that company and other common factors. The rate of return on a diversified portfolio comprising of small capitalization stocks is likely to be influenced by market sentiment and other common factors.

30

On the other hand, large and diversified companies making profit consistently are followed by a large number of analysts and so asymmetry of information in case of such companies is likely to be low. Any under– or over–pricing of the shares of these companies is likely to be exploited by arbitrageurs and prices revert back to fair values quickly. Due to the aforesaid reasons, the study of the rate of return on an index of small capitalization stocks is likely to reveal the role of market sentiment in influencing the returns on investment in equity shares.

IDENTIFICATION OF DEPENDENT AND INDEPENDENT VARIABLES Exogenous shocks are likely to create a sequence of events and knowledge about such events helps in identifying the proxies for the market sentiment (Baker & Wurgler, 2007). When good news arrives into the market in succession, optimistic investors are likely to over– estimate future returns and under–estimate risks associated with the investment opportunities. As a result, such investors create demand pressures for such shares about which they are optimistic. The prices and trading volumes of such shares increase when arbitrage is risky. It creates opportunities for insiders to make profit by selling or short-selling those over-priced stocks (Jenter, 2005). Companies may raise fresh capital by issuing over-priced shares and repay debt (Baker & Wurgler, 2002; Jenter, 2005). When bad news is followed by bad news and pessimism prevails, investors are likely to under–estimate the returns and over–estimate risks. As a result, such irrational investors are likely to perceive fall in price. Initially, when losses occur, these investors might not sale the shares and book the losses immediately. Thus, trading volume by irrational investors when they are pessimistic is likely to be lower than the trading volume by

 The Role of Market Sentiment in Stock Price Movements

such investors when they are optimistic (Baker & Wurgler, 2007; Shefrin & Statman, 1985). But, due to lack of demand, price may continue to fall when arbitrage is risky and constrained. But insiders are likely to buy the under–priced shares (Jenter, 2005). Companies may raise debt and buyback the under–priced shares (Baker & Wurgler, 2002). But the responses of the investors to the events need to be interpreted cautiously. Insiders may sell/buy over–priced/under–priced shares of their companies for rebalancing their portfolios. Companies may issue over–priced shares for raising capital for financing new projects. When the price of a share increases, the cost of share capital falls and as a result, the projects which were financially unviable earlier may become viable and hence, are needed to be financed. Moreover, by raising equity share capital and repaying debt, companies may create debt capacity which may be used for raising debt when stock market conditions are unfavourable. On the other hand, when a company has accumulated cash reserves but does not have profitable investment opportunities, it can return the funds to the shareholders through buyback of under–priced shares. As pointed out in the objective of the study that the rate of return on investment in Small Cap Index is likely to be affected by the fundamental variables as well as market sentiment so we develop the model based on that assumption. The BSE Small Cap Index at t is taken as the price (denoted by Pt) of a diversified portfolio comprising of shares of small capitalization companies. The rate of return on investment in Small Cap Index is the dependent variable which is likely to be influenced by the following fundamental variables and market sentiment represented by the indicators listed hereunder:

Real Rate of Growth in the Economic Activity When an economy expands and demand from consumers grows, the business of the firms which produce goods and render services also grows. Under such a situation if demand grows at a rate higher than the rate at which supply grows, firms can increase their profitability by increasing the prices of their goods and services. Profitability rises also due to fall in costs per unit due to increase in the volume of activity. Rise in profitability implies more income is available to the equity shareholders resulting into increase in the prices of shares of such firms all other things remaining the same (Chen, Roll & Ross, 1986). Moreover, when the economy expands, firms retain more profit. When profitability is higher than the opportunity cost of the shareholders, higher the retention ratio higher will be the rate of growth in earnings per share and price of share. Thus, the rate of growth of the economy is likely to influence the growth opportunities and profitability of the companies and consequently affect the market prices of the shares of such companies. Rate of change in the index of industrial production is assumed to reflect the rate of change in real economic activity.

Rate of Interest The rate of return required by the investors has two components, the risk-free rate of return and the premium for risk. The premium for risk is the product of two components viz., the amount of risk and the price per unit of risk. If there is an unanticipated change in any of these components, the required rate of return may change resulting into change in price of the security amount of return remaining constant (Chen et. al., 1986).

31

 The Role of Market Sentiment in Stock Price Movements

Thus, an unanticipated increase in the market rate of interest leads to an increase in the investors’ required rate of return resulting into a fall in the prices of securities all other things remaining the same. Since call rates are determined by the market, call rate not only reflects market’s expectation about risk-free rate of interest but also the price of risk. So, call money rate is taken as a proxy for market rate of interest.

Rate of Change in Price Level When an investor decides to save a part of his income, which he would have otherwise spent on consumption, he actually defers his current consumption to a future date. If the price level of the commodities increases, the purchasing power of money falls and as a result, the investor’s future consumption becomes lower than what he would have consumed now had he spent the money saved on current consumption. When there is an unanticipated increase in the price level of commodities, investors ask for a compensation for the loss of purchasing power resulting into an increase in the rate of return required by the investors and as a result, the prices of the securities fall other things remaining the same (Chen et. al., 1986). The rate of change in wholesale price index (i.e., WPI) is assumed to represent the change in price level of the commodities. The following indicators are assumed to represent the market sentiment.

Volume of Trades by Retail Investors The inexperienced retail investors are more likely to act in concert than professionals and experienced traders (Baker & Wurgler, 2007) implying that when one set of retail investors buy stocks, another group of retail investors also tend to buy stocks and vice versa (Kumar, 2006). During the ‘bull run’ retail investors buy stocks more than what they sell and vice versa. Thus, volume of stocks bought to volume of stocks sold by the

32

retail investors can be taken as a proxy for market sentiment. But due to non-availability of data, this proxy is not included in our model.

Market Liquidity When irrational investors are optimistic about a stock, they are likely to demand for that stock. As a result, the price of that stock rises if shortselling is restricted or constrained. Rational traders are likely to sell such over-priced stock. When pessimism prevails, irrational traders expect the price of the stock to fall. But due to restriction on short-selling traders cannot short-sell the stock and the supply of that stock is dried up. Thus, trading volume is likely to increase when optimism persists in the market and vice versa (Baker & Stein, 2004). But, volume of trade is also likely to increase if there is an increase in the number of listed shares. So, turnover per listed scrip is taken as a proxy for investors’ sentiment (Baker & Wurgler, 2007). The number of shares traded out of the listed shares is likely to be more when market sentiment is favourable than when such sentiment is unfavourable. So, number of traded scrips to listed scrips is also taken as an indicator of investors’ sentiment.

Flow of Funds to Equity-Linked Mutual Fund Schemes Mutual fund investors are likely to be naïve and unsophisticated (Baker & Wurgler, 2007). When bullish sentiment prevail, such investors are likely to invest in growth-oriented equity–linked funds and sale units of relatively safe debt funds. The net amount mobilized by equity–linked mutual funds as a proportion to net amount mobilized by ‘safe’ debt or income funds can be taken as a proxy for the investors’ sentiment. Since, in India, equity linked savings schemes have not become very popular investment vehicle for the retail investors, this proxy may not be a true indicator of market sentiment.

 The Role of Market Sentiment in Stock Price Movements

Discount on Units of ClosedEnd Mutual Fund Schemes After the launch of the closed-end mutual fund schemes, the listed units are traded on stock exchanges. Ideally, price should not differ from net asset value per unit (NAV) but price may differ from NAV during the day when NAV is not available. If the retail investors are irrationally optimistic about the future, the demand for such units from these investors is likely to increase resulting into increase in the prices of such units above their NAVs (Lee, Shleifer & Thaler, 1990). On the other hand, if retail investors are irrationally pessimistic, the supply of such units increases resulting into a fall in the prices below their NAVs. But some researchers also argue that the rational investors intending to buy such units have to bear the systematic risk (called ‘noise trader risk’) arising from the irrational actions of the initial owners of such units and so they ask for a compensation for bearing such risk and seek the units at a discount (Lee et. al., 1990; Lee et. al., 1991; Barberis & Thaler, 2002). But the discount is higher when the pessimism in the market is higher. Thus, discount on units of closed-end mutual funds can be taken as a proxy for investors’ sentiment. But due to non-availability of data, we could not include this proxy in our model.

Insider Trading In India, trading by insiders in shares of their companies, on the basis of price sensitive unpublished information, is prohibited until that information is published. But when shares are underpriced, it prompts the insiders to buy those shares and when such shares are over–priced, insiders are likely to sell or short–sell those shares. Thus, trading by insiders can be a good proxy for market sentiment. Since insider trading is prohibited, trades by insiders might have been done through entities which do not show their proximity to the insiders and so those trades are not reported. The

reported data may not be a significant part of the actual volume of insider trading. So, this proxy based on reported data may not truly reflect the market sentiment.

Changes in Promoter’s Holding When the shares are underpriced, promoters are likely to buy the shares of their own companies. It may also be argued that availability of shares at a low price makes a company an easy target for takeover and in order to prevent any hostile takeover promoters increase their shareholding in the company. When shares are over–priced, promoters are likely to sell some shares in order to make personal gains. Since increase in price also make takeover unprofitable, promoters may sell shares of their company and diversify their personal portfolio. Nevertheless, increase in promoters holding implies a bearish sentiment and decrease implies a bullish sentiment. But, again these data are not available on a monthly basis and so it is not included in the model.

Number of Initial Public Offerings (IPOs) When the investors are overly optimistic about the performance of shares, they are likely to demand more shares in comparison to supply and this may result in increase in prices of shares and may result in over–pricing of shares. Companies wishing to go public are likely to enter the market with IPOs when investors’ willingness to buy IPOs are high (Helwege & Liang, 2002) and is reflected by increase in prices of shares (Graham & Harvey, 2001) and over–pricing of shares (Lowry, 2003). Since shares are over–priced, cost of going public is low in such a market (Lowry, 2003). Companies are likely to be reluctant to go to the public with IPOs when managers feel that the shares are under–priced (Graham & Harvey, 2001) in a market characterized by bearish market sentiment (Ritter & Welch, 2002). Since, the willingness of inves-

33

 The Role of Market Sentiment in Stock Price Movements

tors to buy IPOs is an important determinant of IPO cycle (Helwege & Liang, 2002), the number of IPOs is taken as a proxy for market sentiment.

Over-Subscription or UnderSubscription of IPOs Retail investors holding overly optimistic sentiment about the prospect of a particular industry are likely to create demand for the initial public offerings (IPOs) of shares of companies belonging to that industry (Dorn, 2009) as compared to the supply of such shares resulting into oversubscription of such IPOs. Although a part of the successes of such IPOs can be ascribed to the strong fundamentals of the companies which belong to that industry. Moreover, when investors have large investible funds at their disposal but get a few good investment opportunities, the demand for such few opportunities are likely to surpass the supply. But, since IPOs are shrouded with asymmetry of information, rational investors are likely to be cautious about investing in such IPOs. Moreover, in order to evaluate the IPOs, rational investors are likely to collect information which involves cost and so they can be induced to buy such IPOs if shares are offered at a discount. Despite asymmetry of information and cost of information, IPOs are over–subscribed since these IPOs are brought to the market when investors are overly optimistic. Thus, a favourable market sentiment is likely to contribute to the over–subscription of IPOs. Thus, over–subscription or under–subscription of IPOs can be taken as a proxy for investors’ sentiment. But this proxy is not included in the model due to non-availability of such data on a monthly basis.

First Day Returns on IPOs When the market sentiment is bullish, the demand for newly listed stocks is likely to be very high. Under such favourable conditions, companies are

34

expected to sell shares at hefty premiums and at a price which the irrational investors will be ready to pay. But in order to compensate the underwriters and regular investors for bearing the risk arising from the possibility that the favourable sentiment may cease prematurely, shares are offered to them at a discount. When such shares are listed, demand from the irrational investors pushes the price above the offer price (Ljungqvist, Nanda & Singh, 2006). It creates opportunities for the underwriters and regular investors to off-load shares in the market. Thus, the first day’s rate of return on initial public offerings (IPOs) may be taken as a proxy for market sentiment. But due to non-availability of such data on a monthly basis, this indicator is not included in our model.

Amount of Funds Raised Through Issue of Equity Shares as a Percentage of Total Funds Raised Shares are likely to be over–priced in a bull market when market sentiment is favourable and shares are likely to be underpriced in a bear market when market sentiment is unfavourable. Since companies are likely to raise equity share capital when shares are over–priced and raise debt when shares are underpriced, the ratio of funds raised by issue of equity shares to total funds raised is taken as a proxy for investors’ sentiment.

METHODOLOGY AND MODEL The study has used secondary monthly data collected from various sources for the period June 2003 to July 2011. The data relating to BSE Small Cap Index, number of scrips listed, number of scrips traded and turnover (in rupees crore) have been collected from the website of BSE. The data relating to number of initial public offerings, amount of fund raised by issue of equity shares, total amount of fund raised from the capital market, index of industrial production, call rate and

 The Role of Market Sentiment in Stock Price Movements

wholesale price index have been collected from the website of RBI. Since the regression involving non-stationary data series leads to spurious regression results (Granger and Newbold, 1974), it is econometrically appropriate to check the stationary status of the time series data on economic variables and sentiment indicators before running the regression. In view of this, we have checked the stationary status of the data series at their logarithmic values by applying unit root test viz., the Augmented Dickey Fuller test (ADF) (cf. Dickey & Fuller, 1979, 1981; Said & Dickey, 1985). If any series is found to be non-stationary, then the series is made stationary by taking the appropriate difference. Since we have monthly series for all the variables, the data are likely to have seasonal effect, and hence for meaningful data analysis deseasonalization of the data sets is necessary. The nature of seasonality in a given data set can be discerned by plotting returns against month. However, there are two procedures by which deseasonalization of the return series can be carried out. These are seasonal differencing and use of seasonal dummies. We have used seasonal dummies. Assuming pt to be the logarithm of monthly stock price index Pt for the companies having small capitalizations, return rt is defined as rt = pt − pt −1 . We test the stationarity of rt by the aforesaid tests. Rate of return on BSE small cap index can be predicted by a set of macroeconomic variables and behavioural/psychological factors representing the market sentiment. Macro-economic variables viz., real rate of growth in the economic activity (represented by rate of change in the index of industrial production), short term interest rate (represented by call money rate) and inflation (represented by rate of change in wholesale price index) are included in the model. Proxies for the market sentiment viz., turnover per listed scrip, traded scrips to listed scrips, number of initial

public offerings (IPOs) and equity share to total fund raised are also included in the model. The returns on stock indices are found to have time-varying volatilities as understood from the seminal paper of Engle (1982). So, we have used the following model which takes into account the time-varying volatility in returns on BSE Small Cap Index through a GARCH specification for the error term ( ut ).z  m

12

J

i =1

l =1

j =1

rt = ∑ γi rt −i + ∑ wl Dlt + ∑ βj z j ,t + ut

where

ut ψt −1

i s a s s u m e d t o fo l l ow

N (0, ht ) , ht = α0 + α1ut2−1 + δ1ht −1 where

ht

represents conditional variance at time t , as given by the above GARCH specification. Dl ’s

[where l =1, 2,…, 12] denote the monthly dummies to capture month-of-the-year effect in returns. z j,t , s are the seasonally adjusted stationary

macroeconomic variables and proxies for the market sentiment and ψt−1 is the information set  is the appropriate lag value at time t − 1, and m of rt capturing its autocorrelation which is determined by Hall’s (1994) procedure and other diagnostics tests such as Ljung-Box test statistic.

FINDINGS This section presents the findings and their interpretations. To begin with we plot the monthly returns on BSE Small Cap Index (See Figure 1). It is observed from Figure 1 that the movements in the monthly returns on BSE Small Cap Index are not purely random. Figure 2 shows the histogram of the monthly returns on BSE Small Cap Index for the period June 2003 to July 2011. The histogram of the returns shows that the shape of the distribution

35

 The Role of Market Sentiment in Stock Price Movements

Figure 1. Movements in monthly returns on BSE small cap index during the period June 2003 to July 2011

of the monthly returns deviate from the shape of the normal distribution. Figure 3 shows the histogram of the monthly returns on BSE Sensex (which comprises of large capitalization stocks) for the period June 2003 and July 2011. It shows that the histogram of returns

on BSE Sensex is not normally distributed. A comparison of the histograms of monthly returns on BSE Small Cap Index and BSE Sensex reveals that the distribution of returns on BSE Sensex is smoother and consist less outliers than the returns on BSE Small Cap Index.

Figure 2. Histogram of monthly returns on BSE small cap index for the period June 2003 to July 2011

36

 The Role of Market Sentiment in Stock Price Movements

Figure 3. Histogram of monthly returns on BSE Sensex for the period June 2003 to July 2011

Table 2 shows that the distribution of monthly returns on BSE Small Cap Index has negative skewness (i.e., –0.411) and its Kurtosis (i.e., 4.82) is greater than 3. The Jarque-Bera statistic is 16.12 (p-value is 0.000316). Thus, the hypothesis that the distribution of monthly returns on Small Cap Index follows normal distribution is rejected at 1% level of significance. Table 2 shows that the distribution on monthly returns on Sensex also does not follow normal distribution. It has negative Skewness and Kurtosis in excess of 3. Interestingly, the mean, median, minimum, maximum and standard deviations of monthly returns on BSE Small Cap Index are higher than those of the BSE Sensex. We know that Sensex is comprised of the prices of shares of thirty large capitalization and diversified companies. The large capitalization stocks are followed by a large number of analysts and investors. So, asymmetry of information about such stocks is likely to be less. So, in order to examine the effect of market sentiment on return on stocks, return on BSE Small Cap Index has been considered as the dependent variable. Now, we test the stationarity of all the variables used in our analysis covering the period June 2003 to July 2011. We find from Table 3 that for most of the variables the null hypothesis of unit

root is rejected even at 1% level of significance by ADF test. Table 4 gives the results of the regression of the independent variables on the returns from investment in a portfolio represented by BSE Small Cap Index.

Table 2. Summary statistics for monthly returns on BSE small cap index and BSE sensex for the Period June 2003 to July 2011 Sr. No.

Descriptive Statistics

BSE Small Cap Index

BSE Sensex

1

No. of Observations

97

97

2

Mean

0.020560

0.018342

3

Median

0.039038

0.021811

4

Minimum

–0.392958

–0.272992

5

Maximum

0.418151

0.248851

6

Standard Deviation

0.116761

0.079837

7

Skewness

–0.411

–0.725

8

Kurtosis

4.82

4.73

9

Jarque-Bera Statistic

16.12 (0.000316)

20.59 (0.000034)

Figures in parenthesis represent p-values.

37

 The Role of Market Sentiment in Stock Price Movements

Table 3. Results of the Unit Root Tests Variables

Notation

ADF Statistic

P-value

-3.910234

0.0029

Dependent Variable:-

rt

Log of Monthly Return on BSE Small Cap Index

Fundamental Variables:Log of (IIP t / IIPt-1)

z 1t

-6.774226

0.0000

Log of Call Rate (1st diff.)

z 2t

-5.788067

0.0000

Rate of Change in WPI

z 3t

-5.486767

0.0000

Indicators of Market Sentiment:Log of Turnover per Listed Scrip

z 4t

-5.807457

0.0000

Scrips Traded to Scrips Listed

z 5t

-3.882154

0.0164

No. of IPOs

z 6t

-5.730078

0.0000

Funds raised by issuing Equity Shares to Total Fund raised

z 7t

-8.600280

0.0000

Table 4 shows that the adjusted R-squared is 0.178418. The Durbin-Watson d-statistics is 1.9905 which is close to 2 and indicates the absence of autocorrelation in the residuals. Among the indicators of market sentiment, the regression coefficients of funds raised by issuing equity shares to total funds raised and turnover per listed scrip are found to be significant at 5% level of significance. Among the fundamental variables, the regression coefficients of call rate and rate of change in WPI are also found to be statistically significant at 5% level of significance. Interestingly, the regression coefficients of the seasonal dummies representing the months of April, August and November

38

are also found to be statistically significant at 1% level of significance.

ANALYSIS AND INTERPRETATIONS OF THE FINDINGS The statistically significant positive regression coefficients of funds raised by issuing equity shares to total funds raised and turnover per listed scrip indicate that market sentiment is an important determinant of rate of return on BSE small cap index. Increase in the proportion of funds raised through the issue of equity shares to total funds

 The Role of Market Sentiment in Stock Price Movements

Table 4. Results of the Regression R-squared

0.264900

Adjusted R-squared

0.178418

Durbin-Watson statistics

1.990500

Variables

Notation

Coeffi-cient

Std. Error

z-Statistic

p-value

Fundamental Variables:Log of (IIP t / IIPt-1)

z 1t

0.335945

0.249594

1.345968

0.1783

Log of Call Rate (1st diff.)

z 2t

-0.045379

0.020334

-2.231631

0.0256

Rate of change in WPI

z 3t

-0.036061

0.017353

-2.078065

0.0377

Sentiment Indicators:Log of Turnover per Listed Scrip

z 4t

0.124248

0.054813

2.266774

0.0234

Scrips Traded to Scrips Listed

z 5t

-0.114239

0.088830

-1.286034

0.1984

No. of IPOs

z 6t

-0.001804

0.002571

-0.701674

0.4829

Funds raised by issuing Equity Shares to Total Fund raised

z 7t

0.000631

0.000299

2.111599

0.0347

Dummy Variables:April

D4t

0.137915

0.041227

3.345258

0.0008

August

D8t

0.121402

0.028421

4.271505

0.0000

November

D11t

0.055456

0.021480

2.581788

0.0098

0.004190

0.001379

3.038759

0.0024

0.669570

0.305774

2.189759

0.0285

Conditional Variance Equation Constant

GARCH Component

α0

ut−12

Note: Dependent variable: Monthly return on BSE Small Cap Index

39

 The Role of Market Sentiment in Stock Price Movements

raised and increase in turnover per listed scrip reflect favourable market sentiment which contributes to the increase in the demand for small capitalization stocks and supply of such stocks remaining unchanged the prices of such stocks increase. On the other hand, fall in the share of funds raised by issue of equity shares in the total funds raised from the capital market and the fall in the turnover per listed scrip show that market sentiment is unfavourable which increases the supply of small capitalization stocks resulting into the fall in the prices of such stocks. The statistically significant negative regression coefficients of call rate and rate of inflation imply that as these rates increase, investors’ required rate of return also increases resulting into fall in the prices of stocks. Interestingly, the regression coefficient of the index of industrial production is found to be statistically not significant implying that the rate of return on investment in small capitalization stocks depends more on sentiment factors, interest rate and inflation than on the most important macro-economic factor. The statistically significant positive regression coefficients of the dummies for April, August and November indicate that there are significant seasonal influences on the return on investment in small capitalization stocks. Thus, we have found that besides two fundamental variables, market sentiment has significant influence on return from investment in small capitalization stocks. The return on these stocks also increases in the months of April, August and November. Thus, month effects are also present in case of returns on investment in small capitalization stocks.

CONCLUDING REMARKS The efficient market hypothesis says that new information gets incorporated in the stock prices instantaneously. Since shocks arrive randomly, stock prices move randomly. As a result, it is difficult to identify any pattern in the stock price

40

movements and predict future stock prices which can be used for designing a trading strategy for making above–normal returns without commensurate increase in risk. But stock prices may be significantly influenced by the ‘noise traders’ in the presence of ‘limit to arbitrage.’ Thus, market sentiment may have significant influence on return from investment in small capitalization stocks which are shrouded with asymmetry of information, which makes arbitrage in these stocks risky. Based on the returns on investment in BSE Small Cap Index for the period June 2003 to July 2011, we have found that market sentiment, represented by funds raised by issuing equity shares to total funds raised and turnover per listed scrip, has significant influence on return from investment in small capitalization stocks. We have also found that fundamental variables viz., rate of interest and inflation, have significant influence on the return from investment in such stocks. Interestingly, we have also found month effects on such returns. Thus, our findings have important implications for the retail investors in India. Since the return on investment in small capitalization stocks is influenced by market sentiment and there are month effects, retail investors should be cautious while selecting small capitalization stocks and timing their investments. Otherwise, sophisticated traders will be in a position to generate abnormal returns without taking additional risk by designing appropriate trading strategies.

REFERENCES Baker, M., & Stein, J. C. (2004). Market liquidity as a sentiment indicator. Journal of Financial Markets, 7(3), 271–299. doi:10.1016/j. finmar.2003.11.005 Baker, M., & Wurgler, J. (2002). Market timing and capital structure. The Journal of Finance, 57(1), 1–32. doi:10.1111/1540-6261.00414

 The Role of Market Sentiment in Stock Price Movements

Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. The Journal of Finance, LXI(4), 1645–1680. doi:10.1111/j.1540-6261.2006.00885.x Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. The Journal of Economic Perspectives, 21(2), 129–151. doi:10.1257/ jep.21.2.129 Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307–343. doi:10.1016/S0304405X(98)00027-0 Bhole, L. M., & Mahakud, J. (2009). Financial institutions and markets: structure, growth and innovations. New Delhi: Tata Mc-Graw-Hill Education Private Limited. Bikhchandani, S., & Sharma, S. (2001). Herd behavior in financial markets, International Monetary Fund. IMF Staff Papers, 47(3). Chen, N.-F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. The Journal of Business, 59(3), 383–403. doi:10.1086/296344 Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor psychology and security market under- and overreactions. The Journal of Finance, LIII(6), 1839–1885. doi:10.1111/00221082.00077 Daniel, K., Hirshleifer, D., & Teoh, S. H. (2002). Investor psychology in capital market: Evidence and policy implications. Journal of Monetary Economics, 49(1), 139–209. doi:10.1016/S03043932(01)00091-5 Datt, R., & Sundharam, K. P. M. (2007). Indian Economy. S. Chand & Company Ltd, New Delhi. De Bondt, W. F., & Thaler, R. (1985). Does the stock market overreact. The Journal of Finance, XL(3), 793–805. doi:10.1111/j.1540-6261.1985. tb05004.x

Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427–431. doi:10.2307/2286348 Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057–1072. doi:10.2307/1912517 Dorn, D. (2009). Does sentiment drive the retail demand for IPOs. Journal of Financial and Quantitative Analysis, 44(1), 85–108. doi:10.1017/ S0022109009090024 Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of variance of U.K. inflation. Econometrica, 50(3), 987–1008. doi:10.2307/1912773 Fama, E. (1965a). The behaviour of stock-market prices. The Journal of Business, 38(1), 285–299. doi:10.1086/294788 Fama, E. (1965b). Random walks in stock market prices. Financial Analysts Journal, 21(5), 75–80. doi:10.2469/faj.v21.n5.55 Fama, E. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417. doi:10.2307/2325486 Fama, E. (1991). Efficient capital markets: II. The Journal of Finance, 46(5), 1575–1617. doi:10.1111/j.1540-6261.1991.tb04636.x Fama, E. (1998). Market efficiency, long-term returns and behavioural finance. Journal of Financial Economics, 49, 283–306. doi:10.1016/ S0304-405X(98)00026-9 Ghosh, D. N. (2003). Market scandals and regulatory governance. Economic and Political Weekly, 38(20), 17–23.

41

 The Role of Market Sentiment in Stock Price Movements

Graham, J. R., & Harvey, C. R. (2001). The theory and practice of corporate finance: Evidence from the field. Journal of Financial Economics, 60(2-3), 187–243. doi:10.1016/S0304-405X(01)00044-7

Lee, C. M. C., Shleifer, A., & Thaler, R. H. (1991). Investor sentiment and the closed-end fund puzzle. The Journal of Finance, 46(1), 75–109. doi:10.1111/j.1540-6261.1991.tb03746.x

Granger, C. W. J., & Newbold, P. (1974). Spurious regression in econometrics. Journal of Econometrics, 2(2), 111–120. doi:10.1016/03044076(74)90034-7

Ljungqvist, A., Nanda, V., & Singh, R. (2006). Hot markets, investor sentiment and IPO pricing. The Journal of Business, 79(4), 1667–1702. doi:10.1086/503644

Hall, A. (1994). Testing for a unit root in time series with pre-test data based model selection. Journal of Business & Economic Statistics, 12, 461–470.

Lowry, M. (2003). Why does IPO volume fluctuate so much? Journal of Financial Economics, 67(1), 3–40. doi:10.1016/S0304-405X(02)00230-1

Helwege, J., & Liang, N. (2002). Initial public offerings in hot and cold markets. Federal Reserve Board Finance and Economics Discussion Series Working Paper, September.

Malkiel, B. G. (2003). The efficient market hypothesis and its critics. The Journal of Economic Perspectives, 17(1), 59–82. doi:10.1257/089533003321164958

Jenter, D. (2005). Market timing and managerial portfolio decisions. The Journal of Finance, LX(4), 1903–1949. doi:10.1111/j.15406261.2005.00783.x

Miller, M. H., & Modigliani, F. (1958). The cost of capital, corporation finance and theory of investment. The American Economic Review, XLVIII(3), 261–297.

Joseph, M., Nitsure, R. R., & Sabnavis, M. (2002). Financing of Indian firms: Meeting the needs and challenges of the twenty-first century. In J. A. Hanson & S. Kathuria (Eds.), India: A Financial Sector for the Twenty-first Century (pp. 165–201). New Delhi: Oxford University Press.

Pathak, B. V. (2010). The Indian financial system: Markets, Institutions and Services, Dorling Kindersley (India) Pvt. Ltd. licensees of Pearson Education (Singapore). New Delhi: Pte Ltd.

Kumar, A., & Lee, C. M. C. (2006). Retail investor sentiment and return co movements. The Journal of Finance, 61(5), 2451–2486. doi:10.1111/j.15406261.2006.01063.x La, P. R., Lakonishok, J., Shleifer, A., & Vishny, R. (1997). Good news for value stocks: Further evidence on market efficiency. The Journal of Finance, LII(2), 859–874. Lakonishok, J., Shleifer, A., & Vishny, R. (1992). The impact of institutional trading on stock prices. Journal of Financial Economics, 31, 13–43. Lee, C. M. C., Shleifer, A., & Thaler, R. H. (1990). Anomalies: Closed-end mutual funds. The Journal of Economic Perspectives, 4(4), 153–164. doi:10.1257/jep.4.4.153 42

Ritter, J. R., & Welch, I. (2002). A review of IPO activity, pricing and allocations. The Journal of Finance, LVII(4), 1795–1828. doi:10.1111/15406261.00478 Said, S. E., & Dickey, D. A. (1985). Hypothesis testing in ARIMA (p,1,q) models. Journal of the American Statistical Association, 80(390), 369–374. doi:10.1080/01621459.1985.10478125 Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losses too long: Theory and evidence. The Journal of Finance, XL(3), 1–66. Shiller, R. J. (2003). From efficient markets theory to behavioural finance. The Journal of Economic Perspectives, 17(1), 83–104. doi:10.1257/089533003321164967

 The Role of Market Sentiment in Stock Price Movements

Shiller, R. J. (2007). Understanding recent trends in house prices and home ownership. Discussion Paper No. 1630, Cowles Foundation for Research in Economics, Yale University, September. Van, H. J. C. (2006). Financial management and policy. Prentice-Hall of India Private Limited, New Delhi.

KEY TERMS DEFINITIONS ARCH (1): Asset price changes tend to cluster i.e., large changes follow large and small changes small. This phenomenon is called volatility clustering. In a seminal paper in 1982 conditional time varying volatility was first modeled by Engle in the form of autoregressive conditional heteroscedasticity i.e., ARCH. The development of ARCH model has led to a voluminous literature in empirical finance. There have been various extensions and generalizations of this model in the form of generalized ARCH (GARCH), threshold GARCH (TGARCH), exponential GARCH (EGARCH) etc. The ARCH model is symmetric in nature that it treats both negative and positive shocks equally. Efficient Financial Market: An efficient financial market is one in which the prices of securities always fully reflect all available information (Fama, 1965a; Fama, 1965b). GARCH: The generalized ARCH (GARCH) was developed by Bollerslev in 1986 to make the conditional volatility model parsimonious as the higher order ARCH model contain too many parameters. The GARCH model considers both the autoregressive and moving average components of the conditional volatility. Limit to Arbitrage: If arbitrageurs are risk averse and have relatively short time horizon, their ability to bring the prices back to their fair values is likely to be limited in the presence of ‘noise traders’ who drive the prices away from their fundamental values (Baker and Wurgler, 2007; De Long et. al., 1990). Arbitrage also becomes risky for those rational traders who are leveraged

or who manage the money of the people who may want their money back if they get panicked. These fund managers are also not likely to take a stand contrary to the market if they fear to lose their jobs if their performance is found to be poor as compared to the performance of the market. This limited ability of arbitrageurs is known as ‘limit to arbitrage’. Market Sentiment: Market psychology or sentiment is the feeling of the market participants about the prices of securities. Month Effect: Seasonal anomaly is an important phenomenon of financial variables like asset returns where the significant presence of this phenomenon may be important evidence against the efficient market hypothesis. Macro- economic variables at monthly level may follow some systematic pattern in some months of the year. This is called the month of the year effect. This effect can be taken care of by seasonal differencing or using dummy variables at the monthly level. Noise Traders: Investors/traders who make decisions on the basis of the behaviours of the investors/traders who trade earlier rather than on the basis of the information possessed by them about the stock. Noise Traders’ Risk: Noise traders are likely to take the stock prices away from their true values by strengthening the prevailing pattern in the stock price movements. As a result, reversals in price take longer time. The possibility of incurring a loss due to such behavior of the noise traders is called the ‘noise traders’ risk.’ Over-Reaction: In case of over–reaction, price increases above the fair value when the new information has the potential to increase the price. When the new information has the potential to reduce the price, price falls below the fair value. Under-Reaction: When a good news arrives the market but there is under–reaction to it, the initial increase in price produces a price that falls below the fair value. When a bad news arrives and there is under–reaction to it, the initial fall in price produces a price which stops above the fair value.

43

44

Chapter 3

Consumer Sentiment and Confidence during Post-Crisis 2008: A Panel Data Analysis Tonmoy Chatterjee Sidho-Kanho-Birsha University, India Soumyananda Dinda Sidho-Kanho-Birsha University, India

ABSTRACT This chapter attempts to find out the impact of recent recession on the consumption pattern through consumer confidence index (CCI) of selected developed and developing economies. This chapter examines how the macroeconomic variables like growth rate, inflation, unemployment rate and debt-GDP ratio etc. influence the consumer’s confidence during 1996-2012, in which the crisis occurred in 2008. Moreover, in this chapter we have explained the role of consumptions sentiment in terms of consumer confidence regarding future expectation. Apart from that, from the panel data set of 11 countries, we have found that more or less all the economies including the United States have experienced downward movement of consumer’s confidence in the presence of the great recession of 2008-2009.

INTRODUCTION Several authors have rightly pointed out that though economic recession is a part of a business cycle but it make itself an evil of own family. Historically it has been evidenced that economic activities like consumption pattern of households and investment confidence of the producers of an economy have been distorted due to a major

economic slowdown. If we start with the great recession of 1930s as our base instance, we have found that such a recession marked the most severe and persistent decline in aggregate consumption during this period1. In this context the second-worst collapse has been observed in the 1974-5 recession and it sustained for just one year. In contrast to the previous recessions the most current recession 2008-9 has been experienced most severe

DOI: 10.4018/978-1-4666-8274-0.ch003

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Consumer Sentiment and Confidence during Post-Crisis 2008

and persistent decline in aggregate consumption2 since Second World War. All components and subcomponents of consumption declined during this period. Moreover, some of the authors have emphasized that the recovery path of consumption following the recent crisis has been uncharacteristically weak and they have also mentioned that persistence of weaknesses in the recovery path is reflected most in the subcomponents of nondurables and especially in services consumption3. Some of the authors have also claimed that recovery of consumption pattern from its lower trajectory becomes delayed mainly due to lack of consumers’ confidence regarding future. Hence it become essential for us to integrate the issues related with consumers’ confidence and other important macroeconomic variables in the context of recent recession. The motivation behind this work has been generated from the facts that though their exists quite a few works in this line, but none of them have used the panel data of consumers’ confidence of developed and developing countries to discuss the impact of recent economic crisis on consumers’ confidence. In this paper we are trying to fill up the gap of the existing literature using panel data.

BACKGROUND Economic theories recognize the importance of expectations for aggregate economic behaviour. Few influential economic thinkers of the past century attributed explicitly to the volatility of expectations as a crucial factor in explaining the existence and depth of business cycles. Keynes emphasized in the General Theory the importance of changes in expectations that are motivated by “animal spirits”, not by rational probabilistic calculation. In particular, entrepreneurs’ animal spirits related to their investment decisions were theorized of being a major determinant of economic fluctuations. Pigou (1927) also thought of business cycles as being largely driven by

expectations. He stressed entrepreneurs’ errors of optimism and pessimism as key drivers of fluctuations in real activity. Expectations play an important role in modern state-of-the-art general equilibrium models. Expectations are almost universally modelled as formed according to the rational expectations hypothesis. As a result, at least in models with determinate equilibrium, errors (due to expectation) can be solved out as a function of fundamental shocks and they disappear as autonomous sources of dynamics. Hence, there is typically no scope for fluctuations in expectations in the spirit of those emphasized by Keynes, which are driven by animal spirits, market psychology, sentiment, or by any shift in expectation that cannot be reconnected to original structural disturbances. In this study, we focus on sentiment especially on consumer’s sentiment and also consumer confidence that is measured as consumer confidence index (CCI). Now, we discuss on consumer confidence.

CONSUMER CONFIDENCE Consumer confidence is the degree of optimism on the state of the economy that consumers are expressing through their activities of spending and saving. The Consumer Confidence Index (CCI) is an important indicator which measures consumer confidence. Measurement is indicative of consumption component level of gross domestic product (GDP). Naturally CCI affects stock market. The US Federal Reserve looks at the CCI when determining interest rate changes, and it also affects stock market prices. There is huge variation in CCI in the country to country analysis. However, consumer confidence is a lead indicator of economic trends4. In simple terms, increased consumer confidence indicates economic growth in which consumers are spending money, indicating higher consumption. Decreasing consumer confidence implies slowing economic growth, and so consumers are likely

45

 Consumer Sentiment and Confidence during Post-Crisis 2008

to decrease their spending. The idea is that the more confident people feel about the economy and their jobs and incomes, the more likely they are to make purchases. Declining consumer confidence is a sign of slowing economic growth and may indicate that the economy is headed into trouble.

Questionnaire and Index Calculation Each month The Conference Board surveys 5,000 US households. The survey consists of five questions that ask the respondents’ opinions about the following: 1. 2. 3. 4.

Current business conditions. Business conditions for the next six months. Current employment conditions. Employment conditions for the next six months. 5. Total family income for the next six months. Survey participants are asked to answer each question as “positive”, “negative” or “neutral”. The preliminary results from the consumer confidence survey are released on the last Tuesday of each month. After collection of the data, a proportion known as the relative value is calculated for each question separately. Each question’s positive responses are divided by the sum of its positive and negative responses. The relative value for each question is then compared against each relative value from 1985. This comparison of the relative values results in an index value for each question. The index values for all five questions are then averaged together to form the consumer confidence index; the average of index values for questions one and three form the present situation index, and the average of index values for questions two, four and five form the expectations index. Manufacturers, retailers, banks and the government monitor changes in the CCI in order to factor in the data in their decision-making processes. While index changes of less than 5% are often

46

dismissed as inconsequential, moves of 5% or more often indicate a change in the direction of the economy. A month-on-month decreasing trend suggests consumers have a negative outlook on their ability to secure and retain good jobs. Thus, manufacturers may expect consumers to avoid retail purchases, particularly large-ticket items that require financing. Manufacturers may pare down inventories to reduce overhead and/or delay investing in new projects and facilities. Likewise, banks can anticipate a decrease in lending activity, mortgage applications and credit card use. When faced with a down-trending index, the government has a variety of options, such as issuing a tax rebate or taking other fiscal or monetary action to stimulate the economy. Conversely, a rising trend in consumer confidence indicates improvements in consumer buying patterns. Manufacturers can increase production and hiring. Banks can expect increased demand for credit. Builders can prepare for a rise in home construction and government can anticipate improved tax revenues based on the increase in consumer spending.

Consumer-Demand Surveys vs. Consumer-Confidence and -Sentiment Surveys Consumer-demand surveys are interview-based statistical surveys that measure the percentage of households that will buy a car, white goods, PCs, TVs, home furnishings, kitchenware or toys in, for example, the next three-month period. The surveys provide a percentage of those who will purchase more, less or the same amount of food and clothing in the next three months than in the corresponding period the year before. If you ask people about their purchasing behaviour within the coming six or 12 months, there will be more of those who “hope to be able to buy”, than if consumers are asked about what they will purchase in the next three months. The shorter the time spans, the closer to actual behaviour.

 Consumer Sentiment and Confidence during Post-Crisis 2008

Consumer-confidence and sentiment surveys measure how people are doing financially, how they look at the overall economy of the country or business conditions in the country, if they think that the government is doing a good or a poor job and if people think that it is a good or a bad time to buy a car or to buy or sell a house. When the business cycle is fairly stable, consumer demand surveys and consumer confidence and sentiment indices will often correlate closely and indicate the same direction of the economy, but in times with a high degree of economic or political uncertainty or during a prolonged crisis, the two types of consumer surveys might differ significantly. In 2011 the confidence and sentiment surveys went up from March to April, while consumer demand surveys dropped significantly. In August 2011 the confidence and sentiment surveys dropped significantly and stayed low during September and October, while consumer demand surveys showed resilience, a development confirmed later by official statistics.

What Economic Concept Does Consumer Confidence Measure? Consumer confidence definitely corresponds to certain economic concept that would help to explain the modest predictive power of consumer attitudes. This section considers two possible economic interpretations: that the indexes reflect precautionary savings motives or that the indexes capture household expectations of future income or wealth.

Consumer Confidence and Precautionary Saving If higher consumer confidence levels capture reduced uncertainty about the future and therefore diminished the precautionary motive for saving, then higher consumer confidence should be associated with a higher level of consumption today, relative to tomorrow. All else equal, this means

lower consumption growth going forward. Thus, if precautionary motives drive consumer sentiment, consumption growth measured from today to tomorrow should be negatively correlated with consumer sentiment today. This result is not what is found here, nor in previous studies like Carroll, Fuhrer and Wilcox (1994) or Bram and Ludvigson (1998). Instead, the sum of coefficients on the lagged consumer confidence measures in the forecasting regressions reported above is almost always greater than zero, indicating a positive rather than negative correlation between sentiment and future spending growth. Thus, a simple model of precautionary saving cannot explain the sentiment-spending correlation documented above. Interestingly, one empirical study using micro data finds the opposite result. Using the Michigan Survey of Consumer Attitudes and Behaviour (CAB), the household-level data that underlies the Michigan Index of Consumer Sentiment, Souleles (2004) reports that higher confidence is correlated with less saving (lower consumption growth), consistent with precautionary motives. It’s possible that the discrepancy between the micro-level and macro-level results is attributable to some sort of aggregation bias, but without a detailed study of the relation between the individual and aggregate survey responses, the possibility remains speculative.

Confidence and Expectations of Future Income or Wealth Another interpretation of consumer confidence surveys is that they primarily capture household expectations of future income or wealth. Of course, under the general version of the permanent income hypothesis, consumption should change because of unexpected rises in permanent income. However, higher confidence levels could be related to future consumption growth if households are liquidity constrained so that greater income is closely tracked by greater consumption, or if some

47

 Consumer Sentiment and Confidence during Post-Crisis 2008

households follow a “rule-of-thumb” of consuming some fraction of their current income every period (Campbell & Mankiw, 1989). To assess this interpretation, researchers should first investigate the possibility that confidence surveys forecast quarterly income and wealth growth, and reports the results of several forecasting regressions. The dependent variables are labour income growth, the growth of wealth as measured on stock market wealth or non-stock wealth.

LITERATURE REVIEW In this section we will go through the brief discussions among the existing literature on the issues related with consumer confidence and recessions. The existing works are broadly emphasized on two different aspects namely, recession mainly due to lack of consumers’ confidence regarding future expectations and recessions are due to non- consumers’ confidence related components. A long and rich string of literature highlights the critical importance of consumer sentiment measures in economic research and decision making since the pioneering work of Katona (1953). Researchers and policy makers often resort to sentiment measures in their work, and many major popular media outlets constantly monitor and publish news related to consumer sentiment. In the literature, there has been a prolonged interest in the power of consumer sentiment to predict future changes in aggregate consumption growth that is the base source of business cycle. Consumer confidence changes (increases or decreases) with the cyclical position of the economy. In this context business confidence is also important.

Consumer Sentiment and Confidence In the last twenty years, there has been a lot of literature on firm and households confidence indicators and their usefulness in evaluating and

48

forecasting economic outcomes. The sentiment indicators can forecast economic activity and short-term economic developments. Katona (1953) and his colleagues introduced the Index of Consumer Sentiment (ICS) at the University of Michigan, and they have developed a recurring topic in economic and applied statistics research works. In most of the research works carried out in recent time, it proves that both confidence and survey indicators are useful in evaluating the current economic development and also used for short-term forecasting purpose. Many applied statisticians and economists have proposed the use of linear with time-varying coefficients to evaluate the robustness and the performances of forecasting models based on confidence indicators for both in-sample and out-of-sample characteristics. Researchers conducts consumer expectations surveys with the aim of evaluating the relationship between consumer indicators and macroeconomic variables and also examining economic trends and prospects. Confidence indicators derived from business and consumer survey results give crucial information on business and consumer assessments of the economic situation and their intentions and expectations for the future. In earlier stage of development of ICS, Mueller (1963) assess the forecasting performance of the Michigan consumer confidence survey and found that lagged confidence variables were significant predictors of durable and non-durable household expenditures. Furthermore, Friend and Adams (1964) found that the ICS was useful for forecasting motor vehicle expenditures; however, they also found that stock prices were a reliable substitute for the survey measure. Later research studies by (Fair 1971; Juster & Wachtel, 1972a, 1972b) supported Mueller’s claim that sentiment could predict other durables as well. Mishkin (1978) argued that the ICS could be interpreted as measuring consumers’ subjective assessment of the probability of financial distress, and used a significant relationship between the ICS and household assets and liabilities to support this

 Consumer Sentiment and Confidence during Post-Crisis 2008

hypothesis. Mishkin (1978) argued that the ICS should be a significant predictor of consumer durables expenditure, since durables are illiquid and hence less likely to be purchased by consumers facing financial difficulties. This was observed when financial variables were not taken into account, but that when they were the sentiment variable became largely redundant. Again, few researchers are sceptical about the usefulness of the confidence indices in forecasting techniques. Emerson and Hendry (1994) use a Vector Autoregressive technique to state that in general, leading indicators do not have any additional information in forecasting5. Stock and Watson (1993) considered the choice of indicators included in the model as the key source of uncertainty in model specification and forecasting. In contrast, Throop (1992) estimated a fivevariable vector error-correction model (VECM) with the changes in the ICS, durables spending, non-durables and services spending, permanent income, and the 6-month commercial paper rate as endogenous variables. He found that changes in sentiment caused changes in durables spending (but not in non-durables and services); in contrast, durables spending did not cause changes in sentiment. When he replaced the ICS with economic variables that he found predicted sentiment (unemployment and inflation), forecast errors were usually lower than in regressions where the ICS (or its current financial conditions component) were used. Leeper (1992) used a vector auto- regression (VAR) framework to assess the relationship between consumer sentiment and activity. His results echoed Mishkin’s. Sentiment innovations only improved the VAR’s predictions of industrial production and unemployment when financial variables like stock prices and T-bill rates etc were excluded from the analysis. Matsusaka and Sbordone (1995) also used a VAR framework, but found that consumer sentiment explained a large proportion of the innovation variance of GNP, after controlling for the Index of Leading Indicators and a measure of default risk. Es-

trella and Mishkin (1978) used a simple probit analysis including financial variables to assess the usefulness of survey measures for predicting recessions. Literature suggests that sentiment variables become redundant when the researcher controls for financial variables, but this finding is not consistent across the board. The early work of Hymans (1970) and Mishkin (1978) tends to favour the interpretation that sentiment indicators summarize prior (or contemporaneous) economic information, a finding echoed by Throop (1992), Lovell and Tien (2000). Desroches and Gosselin (2002) assess the usefulness of consumer confidence indices in forecasting aggregate consumer spending in the United States. They constructed a simple threshold model that takes into account the magnitude of variation of consumer confidence indexes to forecast consumption expenditures. They concluded that strong variations in confidence matter for consumption, as confidence is a significant predictor of consumption during highvolatility periods. Cotsomitis and Kwanf (2006) examined the ability of consumer confidence to forecast household spending within a multicountry framework. They used two confidence indices, namely the Consumer Confidence Indicator and the Economic Sentiment Indicator. There is much variability in the in-sample incremental forecasting performance of the confidence indices for the countries canvassed. The results of their out-of-sample tests indicate that these confidence indices provide limited information about the future path of household spending. They added that European economic forecasters and government policy makers should, therefore, be careful when using the CCI and ESI to predict consumption growth in EU countries. Gulley and Sultan (1998) established a link between the Consumer Confidence on various stock prices, bond yields and some currency rates using a GARCH model. Similarly, Jansen and Nahuis (2003) study the relationship between stock market developments and consumer confidence in 11 European countries over the years 1986-2001. They argued that the

49

 Consumer Sentiment and Confidence during Post-Crisis 2008

relationship between stock market and consumer sentiment depends on the expectations about economy-wide conditions rather than the conventional wealth effect. In another investigation, Vuchelen (2004) analyzed whether information content of consumer sentiment can be explained by some economic and financial variables such as unemployment, growth rate, interest rates and exchange rates. The study observed that both interest rates and dollar exchange rate have significantly negative effect on consumer sentiment. Lemmon and Portniaguina (2006) explored time series relationship between investor sentiment and the small-stock premium using consumer confidence as a measure of investor optimism. They observed that sentiment does not appear to forecast time series variation in the value and momentum premiums. Yasemin and Sadullah (2010) studied the link between Government Spending, Consumer Confidence and Consumption Expenditures. They attempted to introduce a new variable to this wellknown literature by investigating the existence of a relationship between government expenditure, consumer spending and consumer confidence for a group of emerging market economies. They also demonstrated the important role of consumer confidence on government spending and private consumption expenditures. Previous studies usually focused on the relationship between consumer confidence and other macroeconomic indicators for developed countries. However, there is hardly any study that models consumer confidence as a function of relative price of petrol, unemployment rate, VAT revenue and other macroeconomic indicators. Olowofeso and Olorunsola (2012) discussed and found the link between consumer confidence and other macroeconomic variables on CCI in Nigeria.

Consumer Confidence and Business Recession Let us start with a striking paper of Petev, Pistaferri and Eksten (2011). They have considered the 50

movements of different services subcomponents like health services, transportation and food etc. The authors have shown that the spending on health services increased, but fall significantly for services related to transportation, food. The study documents an unusual decline in spending on food, an important indicator of consumer wellbeing, which raises concerns about the extent and depth of the strains on households during the latest recession. They have also explained the decline in real per capita spending in terms of number of purchases of cars and partly of some durable goods. Recently, using confidence measurements, Bram and Ludvigson (1998) show that consumer confidence has significant predictive power when forecasting household expenditures, particularly consumer durables. Interestingly Aguiar, Hurst and Karabarbounis (2011) have shown that during the latest recession, a major portion of foregone market work hours went to home production. It implies food can be produced at lower cost at recession compared to pre recession era. Hence, home production should gain more importance as non-consumers’ confidence related components. Abderrezak (1997) points out that, household consumption has tended to slow following a dip in consumer sentiment and vice versa for decades. Danthine, Onaldson and Johnsen (1998) take this a step further, linking consumer sentiment to agents’ stochastic expectations concerning long-term labor productivity growth and hence permanent income. Likewise, Matsusaka and Sbordone (1995) have shown that consumer sentiment accounts for approximately 20 percent of the business cycle innovation in post war U.S. GDP. Accordingly, consumer sentiment affects not only the intensity of business cycles, but also their duration. Acemoglu and Scott (1994) have used consumer sentiment in a rational expectations framework and they have examined the validity of permanent income hypothesis in the context of rational expectation. Christelis, Georgarakos and Jappelli (2011)6 that losses on housing and financial wealth, together with the income loss from becoming

 Consumer Sentiment and Confidence during Post-Crisis 2008

unemployed, led households to reduce their spending. The estimated elasticity of consumption to financial wealth implies a marginal propensity to consume with respect to financial wealth equal to three percentage points. The decline in house prices also had an important impact on consumption: The estimated elasticity implies that the marginal propensity to consume out of housing wealth is one percentage point. Put differently, these estimates suggest that every dollar of financial wealth lost reduces consumption three cents per year and every dollar of housing wealth lost reduces consumption one cent per year. Apart from these, households in which at least one of the two adult members (or the single head) became unemployed in 2008 and early 2009 reduced consumption by ten percent in 2009. Hurd and Rohwedder (2010) have also considered similar type of exercise to estimates on the responsiveness of consumption to asset and income shocks. In this regard De has considered a macroeconomic model based on permanent-income hypothesis and from that model they have summarized their findings in the following way: the negative wealth effect and consumers’ decreased income expectations were the most significant determinants in determining the declining path of consumption. Nardi, French and Benson, (2012) has focused on five aspects of consumption during the contemporary slowdown. They are, i) rise in government transfers in the early period of the recession raised the disposable income of low-income individuals, but such transfers weren’t able to overcome the effects of other consumption-reducing forces, ii) the deterioration in consumer expenditures lasted longer than in any of the other recessions since the 1970s, and indeed consumer expenditures still haven’t fully recovered, iii) consumption has also plunged deeper than in the past, leading Americans not only to postpone costly purchases of durables but also to change their leisure habits and cut back even on subsistence spending, iv) an insecurity regarding future expectations are still in evidence, v) all type of consumers have been af-

fected due to such slowdown. Reinhart and Rogoff (2009) have documented the similarities between the current financial crisis and many earlier ones stretching across nations. These crises entailed large declines in real housing prices, equity collapses, and profound falls in output and level of employment. They emphasize the importance of balance sheet repair. Blanchard (1993) has captured the issue of consumer confidence in the presence of recession through a traditional VAR model. In this paper the author has not suspected consumer confidence as the only cause behind the recession of 1990s. It has been rightly pointed out by him that, i) in contrast to earlier recessions, the decline in confidence was largely prior to -and much stronger than would have been predicted by- either the decline of leading indicators or commercial forecasts of the recession, ii) the first large decline in confidence in August 1990, was associated with an important but largely non economic event, the chaos in some Arabian countries and iii) after having dropped, consumer confidence remained very low in the following two years, much lower than would have been predicted on the basis of historical relations with aggregate variables. Again we are taking into account the paper by Petev, Pistaferri and Eksten (2011) to consider the role of state in crisis, in this article they have emphasized that while real per capita consumption declined monotonically until the middle of 2009, real per capita disposable income was relatively stable. It is to be noted that such type of stability in real per capita income is explained entirely by some stimulating packages by the government, for instance a strong increase in government transfers to households. As these transfers are mainly focused to the poorer section of the society, the drop in income expectations for the upcoming year among poor households was smaller than that among all other individuals and it was obvious. Starr (2012) investigates the influence of economic news on consumer sentiment, and examines whether “news shocks” - changes in coverage that

51

 Consumer Sentiment and Confidence during Post-Crisis 2008

would not be expected from incoming data on economic fundamentals - have aggregate effects. Using monthly U.S. data and a structural vector autoregressive, the paper observes that (1) sentiment is affected by news shocks; (2) after filtering out effects of news shocks, shocks to sentiment still have positive effects on consumer spending; and (3) news shocks influence both spending and unemployment in significant, though transitory ways. These results are consistent with other evidence of a role of non-fundamental factors in aggregate fluctuations. From the literature it is clear that consumer sentiment fluctuates with change of macroeconomic conditions. Consumers gain confidence directly linking with economic situations.

DATA AND METHODOLOGY For this study we have collected major macroeconomic variables such as Consumer Confidence Index (CCI), Inflation, Unemployment rate, Debt-GDP ratio, etc from the trading economics organisation (www.tradingeconomics.com). Trading economics organisation actually collects all macroeconomic and financial variables from different countries and provides us the compiled ready data. Taking those macroeconomic variables we compile a panel data set for selected 11 countries for the period of 1996 – 2012. Selected countries are the USA, UK, France, Germany, Greece, China, India, Japan, Brazil, South Africa and Thailand. Our data set is a strong balanced panel data. In this study we mainly analyse data using panel data techniques. Trend analysis is used for individual nation with graphical presentation. So, from basic statistical analysis to panel econometric techniques are adopted in this paper. Our basic equation for panel data analysis is Yit = α + βX it + γt + ηi + εit

52

(1)

Where Yit is the dependable variable (i.e., CCI) of ith individual (country) at tth year; X is the vector of independent variables (like average growth rate, inflation, unemployment, Debt-GDP ratio etc.), and, α is intercept term, β is the vector of coefficients of Xit variables; γt is the time effect, and ηi is the country (individual) effect, and εit is the disturbance term. Assuming unobserved variables are uncorrelated with all observed variables we use random effect model; whereas fixed effect model controls for the effects of time-invariant variables with time–invariant effects.

RESULTS AND ANALYSIS Table 1 and Table 2 provides the summary statistics of major panel variables used in this study. Our data set is a strong balanced panel data of the selected countries (11 countries) over 17 years and total observations are 187. Mean value of consumer confidence index, growth rate, inflation rate, unemployment rate and debt – GDP ratio are 51.74, 3.25, 3.49, 8.4 and 68.17 for the period of 1996 - 2012 respectively. The standard deviations (S.D.s) of CCI, inflation rate, unemployment rate and debt-GDP ratio are higher in between countries than that of in within country. Value of SD (high or low) is crucial for determining significant variable in the study. Figure 1-3 display the trend s of consumer’s confidence index of selected countries for the period of 1996 – 2012. Figure 1 shows a clear downward trend of CCI in the USA, UK, Germany, France and Greece. CCI in the USA and France increase with high confidence and it rises with low confidence in UK and Greece till 2000 but it declines continuously after 2001 in the USA, UK, France and Greece; but Germany is different from others. CCI of Germany fluctuates in the period of 1996 – 2012. Confidence index was the lowest in 2009 in all selected countries in Europe and America (See, Figure 1). Figure 2

 Consumer Sentiment and Confidence during Post-Crisis 2008

Table 1. Summary statistics of major variables of panel data set Variable Consumer Confidence Index

Average growth rate

Inflation rate

Unemployment rate

Mean Overall

Max

Observations

142

N=187

Between

48.84378

-23.406

109.412

n=11

Within

20.1768

-13.556

120.444

T=17

3.6693

-8.9

11.2

N=187

Between

2.5723

0.709

9.34

n=11

Within

2.7233

-8.2836

10.854

T=17

3.424

-1.7

23

N=187

Between

2.5069

-0.1294

7.66

n=11

Within

2.4454

-2.39

18.83

T=17

6.0898

0.4

31.4

N=187

6.088

2.1094

24.8712

n=11

1.7913

2.8484

18.1231

T=17

37.94757

6.1

211.7

N=187

Between

36.5895

16.6353

151.77

n=11

Within

14.71

7.601

128.1

T=17

Overall

Overall

3.24583

3.49267

8.39957

Within Overall

68.1716

shows the CCI of selected four Asian countries for the period of 1996-2012. Consumer’s confidence index in China and Japan are almost constant over Table 2. Average annual incremental change of Consumer’s Confidence Index Country

Min -83

Between Debt- GDP ratio

Std. Dev. 50.8684

Overall

51.7377

Average Annual Incremental Change of CCI

USA

-4.65

UK

-1.79

France

-1.53

Germany

-3.43†

Greece

-4.39

China

-0.803

India

1.747

Japan

-0.128†

Thailand

2.52

Brazil

1.198

South Africa

0.44

Note: † Annual incremental change consumer’s confidence index of Germany and Japan are insignificant because of low variability.

the whole period except 2009. China and Japan show upper and lower boundary of CCI in Asia, respectively. CCI increases in India and Thailand with fluctuations. It should be noted that in 2004 CCI is maximum in Thailand whereas it is minimum in India7. CCI of Thailand starts to decline after 2005 but it rises in India with fluctuations. Figure 3 shows that Consumer’s confidence Index of Brazil is high and rises slowly with low volatility whereas that of South Africa is at low with volatility during 1996 - 2012. Both countries are affected in the crisis period. So, from primary observations it is clear that the global economic crisis influences and dampens the consumer’s confidence index in all countries with certain degree of variations. The global crisis seriously affects developed countries like USA, UK, France, Germany, Greece and Japan; it has least effect on emerging countries. Table 3 provides average annual incremental change of CCI during 1996 -2012. From Table 3, it is clear that declining trend in CCI is very high in the USA and Greece. Next declining rate of CCI is Germany, but CCI falling

53

 Consumer Sentiment and Confidence during Post-Crisis 2008

Figure 1. CCI of USA, UK, France, Germany and Greece during 1996-2012

with high volatility whereas that of the USA and Greece decline with less fluctuation. After 2000, CCI of USA steadily falls, but it reaches at bottom during the economic crisis during the period

of 2007-8. The crisis of 2007-8 affects each and every country in this study (see, fig 1-3). In our study period, the average annual incremental change of CCI is positive only in emerg-

Figure 2. CCI of China, India, Japan and Thailand during 1996-2012

54

 Consumer Sentiment and Confidence during Post-Crisis 2008

Figure 3. CCI of South Africa and Brazil during 1996-2012

ing economies such as India, Thailand, Brazil and South Africa, and only exception is China (see, Figure 2). The average annual incremental change of CCI in Japan is negative but statistically insignificant (with low fluctuation). Similar insignificant result is also observed in Germany but it is due to high fluctuation. It is clear that nature of volatility of CCI in Germany is different from Japan (Figure 1). From Figure 2, it is observed that CCI is nearly constant with sliding trend whereas CCI of Japan fluctuates around a constant mean. Figure 3 shows that CCI in Brazil has rising trend whereas that of South Africa fluctuates around a constant mean CCI value. Now, we investigate the factors affecting consumer confidence index. We consider, here, mainly the macroeconomic variables such as average annual growth rate, inflation, unemployment rate, debt GDP ratio etc. Table 3 displays the pool regression results of 11 countries. The estimated coefficients of average growth rate, unemployment rate and debt-GDP ratio are statistically significant at 1% level. Consumer’s confidence increases directly with growth rate, but consumer’s

confidence declines with unemployment rate and also with debt-GDP ratio. Inflation rate is statistically insignificant and does not affect consumer’s confidence which differs from others – it is may be due to small sample countries in this data set. But inflation should be the determining factor of CCI. Again inflation and unemployment may have

Table 3. OLS (pooled) regression results of CCI Variables

Coefficient

S. E.

t-Statistic

P-Value

Average Growth rate

3.121***

0.955

3.27

0.001

Inflation

1.17

0.967

1.21

0.228

Unemployment

-3.428***

0.544

-6.31

0.000

Debt GDP Ratio

-0.276***

0.092

-3.00

0.003

Constant

85.143***

10.749

7.92

0.000

R2

0.3091

Adj.R2

0.2939

Root MSE

42.745

Observations

187

Note: ***, ** and * denote level of significance at 1%, 5% and 10%, respectively.

55

 Consumer Sentiment and Confidence during Post-Crisis 2008

Figure 4. Average annual incremental change of CCI during 1996 -2012

multicollinearity problem but collinearity and other diagnostic tests do not reveal such problem. It is clear from Table 3 that debt and unemployment dampen consumer’s confidence. Marginally 3.43 point of CCI declines due to one percent increase in unemployment, whereas 0.276 of CCI falls due to one percent rise in debt. One percent rise in growth rate increases 3.12 point of CCI (See, Table 3). These results support our intuitive ideas but do not reflect the change of the variables over time and country specific characteristics. Hence, we apply panel data analysis techniques, especially Random Effect and Fixed Effect models. Table 4 and Table 5 present panel regression results of CCI for random effect and fixed effect, respectively. Basic results in terms of sign of the estimated coefficients are exactly same but vary in level of significance. Inflation rate and unemployment rate are statistically insignificant in both random effect and fixed effect models.

56

Table 4. Panel regression results of CCI: random effect model Variables

Coefficient

S. E.

t-Statistic

P-Value

Average Growth rate

2.7849***

0.5178

5.38

0.000

Inflation

-0.4273

0.5566

-0.77

0.443

Unemployment

-0.5989

0.7724

-0.78

0.438

Debt GDP Ratio

-0.2145**

.0972

-2.21

0.027

Constant

68.8426***

17.44

3.66

0.000

Sigma_u

49.9946

Sigma_e

18.6571

Rho

0.8778

R2 within

0.2088

R between

0.2385

Over all R2

0.2199

No. of Countries

11

Observations

187

2

Note: ***, ** and * denote level of significance at 1%, 5% and 10%, respectively.

 Consumer Sentiment and Confidence during Post-Crisis 2008

Table 5. Panel regression results of CCI: fixed effect model Variables

Coefficient

S. E.

P-Value

5.33

0.000

Average Growth rate

2.7868***

Inflation

-0.43548

0.5622

-0.77

0.44

Unemployment

-0.33

0.8189

-0.4

0.687

Debt GDP Ratio

-0.2224**

0.1009

-2.2

0.029

Constant

62.146***

9.14

6.8

0.000

Sigma_u

44.5548

Sigma_e

18.6571

Rho

0.8508

R2 within

0.2093

R between

0.1982

Over all R2

0.1911

No. of Countries

11

Observations

187

2

0.5225

t-Statistic

Note: ***, ** and * denote level of significance at 1%, 5% and 10%, respectively.

There is not much significant difference in the results in both models [random effect GLS regression and fixed effect (within) regression]. The estimated results are very much similar in terms of quality but not in terms of quantity in both random effect and fixed effect models. In Table 4 and Table 5, the estimated significant coefficients of growth rate are 2.7849 and 2.7868, respectively. The significant debt-GDP ratio coefficients are -0.214 and -0.2224 in random effect and fixed effect models (Table 4 & Table 5), respectively. The intercept terms are highly significant in both random effect and fixed effect models, it suggests that there are other variables which affect consumer’s confidence. Next our research agenda is to find out other variables that influence consumer’s sentiment and should be incorporated in appropriate models. Now we discuss the impact of the 2008 crisis on the consumer’s confidence. After the year 2008 crisis period is different from the pre-crisis period.

Table 6. Impact of the economic crisis on the consumer’s confidence index in the post crisis period of 2009 -2012 Random Effect Variable

Coefficient

t

Fixed Effect Coefficient

T

Growth rate

2.62

4.86

2.576

4.76

D912

-9.15

-2.64

-9.26

-2.67

Constant

45.386

3.16

45.56

17.6

This paper attempts to separate the crisis effect on consumer’s confidence from pre-crisis period and estimates the approximate lose of consumer’s confidence. For this purpose we use a dummy variable d912 for the period of 2009-2012. Table 6 shows the effect of the economic crisis on the consumer’s confidence index (CCI). From Table 6 it is clear that consumer’s confidence decreases more than 9 points during post-crisis period 2009 – 2012. It is a significant shift in downward direction. Few developed nations have failed to improve the confidence while developing countries have recovered marginally during post crisis.

CONCLUDING REMARKS This paper deals with a very crucial aspect of consumer’s sentiment during economic crisis in major developed and developing economies. Moreover, here we have incorporated the phenomenon of consumer sentiment or consumer confidence in terms of movement of consumption pattern of consumers of the corresponding countries. Here we have used a data set of 11 countries regarding aggregate consumption pattern through CCI and from that we have found that the trend of consumption pattern has been curved towards negative direction after 2008 and hence consumers of the developed and developing countries have lost their confidence for future expectation. We have observed that due to lack of consumers’ confidence in the market, some of the economies

57

 Consumer Sentiment and Confidence during Post-Crisis 2008

have experienced either upward trend with lower trajectory or upward movement for very short period and declined after that. The global financial crisis affects each and every country but degree of volatility varies from country to country and absorbs the shock accordingly. It is different in developed countries compared to developing countries. CCI declines continuously in developed countries after 2000 and major steep falls during crisis period of 2008 - 2009. In developing countries (except China) consumer’s confidence improves gradually over the period of 1996 - 2012 and only a temporal small dip in the crisis time 2008 -9. Overall growth rate directly affects CCI and debt influences CCI indirectly. Inflation and unemployment rate are also affect consumer’s confidence inversely. This study has some limitations, especially limited data. Need more countries covering highly developed, developed, middle income group countries, emerging economies with high and low growth rates, and less developed countries etc. These will help to identify level of CCI in different group of countries and their rate of change during economic crisis, pre and post crisis. Using the additional information this paper can be improved by identifying proper impulse response functions. This is our next research agenda.

REFERENCES Abderrezak, A. (1997). Consumer expectations and cyclical durations. The Quarterly Review of Economics and Finance, 37(4), 843–857. doi:10.1016/S1062-9769(97)90007-7 Acemoglu, D., & Scott, A. (1994). Consumer confidence and rational expectations: Are agents beliefs consistent with the theory? The Economic Journal, 104(422), 1–19. doi:10.2307/2234671

58

Aguiar, M. A., Hurst, E., & Karabarbounis, L. (2011). Time use during recessions. Working Paper, No. 17259, National Bureau of Economic Research, July. Barsky, R. B., & Sims, E. R. (2009). Information, animal spirits, and the meaning of innovations in consumer confidence. Working Paper, No. 15049, National Bureau of Economic Research, June. Blanchard, O. (1993). Consumption and the Recession of 1990-1991. MIT and NBER, No. 93-5. Bram, J., & Ludvigson, S. (1998). Does consumer confidence forecast household expenditure? a sentiment index horse race. FRBNY Economic Policy Review, 4(2), 59–78. Campbell, J. Y., & Mankiw, N. G. (1989). Consumption, income and interest rates: reinterpreting the time series evidence. Nber Chapters, in: Nber Macroeconomics Annual 1989, 4, 185-246 National Bureau Of Economic Research, Inc. Carroll, C. D., Fuhrer, J. C., & Wilcox, D. W. (1994). Does consumer sentiment forecast household spending? If so, why? The American Economic Review, 84(5), 1397–1408. Christelis, D., Georgarakos, D., & Jappelli, T. (2011). Wealth shocks, unemployment shocks and consumption in the wake of the great recession. Working Paper, No. 279, University of Naples, Italy, Centre for Studies in Economics and Finance, October. Cotsomitis, J. A. A., & Kwanf, A. C. C. (2006). Exogenous shocks and consumer sentiment: The 2003 SARS epidemic in Hong Kong. Working Paper, Chinese University of Hong Kong, Department of Economics. Danthine, J. P., Donaldson, J., & Johnsen, T. (1998). Productivity growth, consumer confidence, and the business cycle. European Economic Review, 42(6), 1113–1140. doi:10.1016/S00142921(98)00025-7

 Consumer Sentiment and Confidence during Post-Crisis 2008

De, N., French, M. E., & Benson, D. (2012). Consumption and the great recession, Economic Perspectives. Federal Reserve Bank of Chicago. Desroches, B., & Gosselin, M. (2002). The usefulness of consumer confidence indexes in the United States. Bank of Canada, 2002. Emerson, R. A., & Hendry, D. F. (1994). An evaluation of forecasting using leading indicators. Economics Papers 5, Economics Group, Nuffield College, University of Oxford. 26. Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. The Review of Economics and Statistics, 80(1), 45–61. doi:10.1162/003465398557320 Fair, R. C. (1971). The optimal distribution of income. The Quarterly Journal of Economics, 85(4), 551–579. doi:10.2307/1882268 Friend, I., & Adams, F. G. (1964). The predictive ability of consumer attitudes, stock prices, and non-attitudinal variables. Journal of the American Statistical Association, 59(308), 987–1005. doi: 10.1080/01621459.1964.10480745 Gulley, O. D., & Sultan, J. (1998). Consumer confidence announcements: Do they matter? Applied Financial Economics. Taylor & Francis Journals, 8(2), 155–166. Hendry, D. F. (1994). Hus revisited. Oxford Review of Economic Policy, 10(2), 86-106. Hurd, M. D., & Rohwedder, S. (2010). Effects of the financial crisis and great recession on American households. Working Paper, No. 16407, National Bureau of Economic Research, September. Hymans, S. H., Ackley, G., & Juster, F. T. (1970). Consumer durable spending: Explanation and prediction. Brookings Papers on Economic Activity, 2(2), 173–206. doi:10.2307/2534239

Jansen, W. J., & Nahuis, J. N. (2003). The stock market and consumer confidence: European evidence. Economics Letters, 79(1), 89–98. doi:10.1016/S0165-1765(02)00292-6 Juster, F. T. & Wachtel, P, (1972a). Inflation and the consumer. Brookings Papers on Economic Activity, 3(1), 71-122. Juster, F. T. & Wachtel, P, (1972b). A note on inflation and the saving rate. Brookings Papers on Economic Activity, 3(3), 765-778. Katona, G. (1953). Rational behaviour and economic behaviour. Psychological Review, 60(5), 307–318. doi:10.1037/h0060640 PMID:13100536 Keynes, J. M. (1936). The general theory of employment, interest and money. London: Macmillan. Leeper, E. M. (1992). Consumer attitudes: King for a day. Economic Review (Federal Reserve Bank of Atlanta), (July), 1–15. Lemmon, M. & Portniaguina, E, (2006). Consumer confidence and asset prices: some empirical evidence. The Review of Financial Studies, 19(4), 1499-1529. Lovell, M. C., & Tien, P. (2000). Economic discomfort and consumer sentiment. Eastern Economic Journal, 26(1), 1–8. Ludvigson, S. C. (2004). Consumer confidence and consumer spending. The Journal of Economic Perspectives, 18(2), 29–50. doi:10.1257/0895330041371222 Matsusaka, J. G., & Sbordone, A. M. (1995). Consumer confidence and economic fluctuations. Economic Inquiry, 33(2), 296–318. doi:10.1111/j.1465-7295.1995.tb01864.x McIntyre, K. H. (1999). Asset returns, consumer sentiment, and economic fluctuations, Working Paper.

59

 Consumer Sentiment and Confidence during Post-Crisis 2008

Mishkin, F. S. (1978). Consumer sentiment and spending on consumer durables. Brookings Papers on Economic Activity, 9(1), 217–232.

Throop, A. W. (1992). Consumer sentiment: Its causes and effects. Federal Reserve Bank of San Francisco Economic Review, 1, 35–59.

Mueller, E. (1963). Ten years of consumer attitude surveys: Their forecasting record. Journal of the American Statistical Association, 58(304), 899–917. doi:10.1080/01621459.1963.10480677

Vuchelen, J. (2004). Consumer sentiment and macroeconomic forecasts. Journal of Economic Psychology, Elsevier, 25(4), 493–506. doi:10.1016/ S0167-4870(03)00031-X

Olorunsola E. Olowofeso, T. & Olorunsola, S. (2012). Consumer sentiment and confidence indices in Nigeria: A panel data analysis. mimeo.

Yasemin, Ö., & Sadullah, C. (2010). The link between government spending, consumer confidence and consumption expenditures in emerging market countries, panoeconomicus, saves ekonomista vojvodine, novi sad. Serbia, 57(4), 471–485.

Petev, I.; Pistaferri, L., & Eksten, I. S. (2011). Consumption and the great recession: An analysis of trends, perceptions, and distributional effects. Stanford University, mimeo, August. Petev, L. D., Crest, L. & Pistaferri, L. (2012). Consumption in the great recession. The Russell Sage Foundation and the Stanford Centre on Poverty and Inequality. Pigou, A. C. (1927). The law of diminishing and increasing cost. The Economic Journal, 37(146), 1887–1897. doi:10.2307/2224353 Reinhart, C. M., & Rogoff, K. S. (2009). This time is different: eight centuries of financial folly, Princeton: Princeton University Press. Souleles, N. S. (2004). Expectations, heterogeneous forecast errors, and consumption: Micro evidence from the Michigan consumer sentiment surveys. Journal of Money, Credit and Banking, 36(1), 39–72. Starr, M. (2012). Consumption, sentiment and economic news. Economic Inquiry, 50(4), 1097–1111. doi:10.1111/j.1465-7295.2010.00346.x Stock, J. H. & Watson, M. W. (1993). A simple estimator of co integrating vectors in higher order integrated systems. Econometrical, 61(4), 783-820.

60

ENDNOTES

1



2

J.M. Keynes (1929) has also mentioned the role of consumption pattern and absolute income in the context of economic crisis. From the data set of Euro stat 29/2009, OECD and OECD Economic Outlook No. 94 (database) on consumption pattern of the following 21 OECD countries: Austria, Belgium, Czech Republic, Denmark, Finland, Germany, Hungary, Ireland, Italy, Netherlands, Norway, Poland, Slovak Republic, Slovenia, Sweden, Switzerland, United States, France, Portugal, Spain and United Kingdom, and we can infer that all of the above mentioned economies have suffered from the great depression of 2008-2009. From the data we can also explain the down ward trend of the aggregate consumption of all of these 21 economies at that period. The data has shown that from the beginning of 2000 -2001 consumers of these nations have gained more confidence regarding their corresponding economies and hence, due to such type of positive sentiment in consumption, these economies have faced a positive trend in the consumption pattern. It is to be noted from the data that such trend has been curved

 Consumer Sentiment and Confidence during Post-Crisis 2008



3



4

towards negative direction after 2008 and again consumers of the OECD countries have lost their confidence for future expectation and as a consequence of that they have found a downward movement of consumption pattern till 2012. If we go through the data of consumption pattern of United States, we see that there exist a definite downward shift of aggregate consumption at 2008-09, but after that it is increasing sharply at a lower trajectory. Note, such type of positive trend of consumption pattern may compatible with the above mentioned literature. Interestingly, countries like Switzerland, Sweden and Poland have experienced a sharp increase in the period of 2009-2010 and 2010-2011 but after that it has been declined. It implies lower consumers’ confidence effect dominates over states’ stimulating packages effect. For details see the paper by Petev et al. (2011), Bram and Ludvigson (1998) and Aguiar et al. (2011) etc. The consumer confidence index was started in 1967 and is benchmarked to 1985=100. This year was chosen because it was neither a peak nor a trough. The Index is calculated each month on the basis of a household survey of consumers’ opinions on current conditions and future expectations of the



5



6



7

economy. Monthly report reveals the detailing consumer attitudes and buying intentions, with data available by age, income and region. Opinions on current conditions make up forty percent of the index, with expectations of future conditions comprising the remaining sixty percent. In addition, they further strength that leading indicators are frequently revised and open to certain degree of subjectivity in the selection process of the component variables. The discovery is in line with the findings of Weale (1996), in which the initial transformation and refinement of the data is considered as additional sources of ambiguity when dealing with leading indicators. In past recessionary periods, nominal income expectations of the elderly population had hovered around or just above zero. However, these expectations have been markedly negative since the NBER peak in 2007:Q4. In this paper they have used the above mentioned types of population data. There was general election in India in 2004. Consumer’s confidence was low because of uncertainty related to nuclear programme and withdrawal of the Left part from support and also about formation of the new Government at centre.

61

62

Chapter 4

Post Crisis Performance and Confidence of the Indian Economy Rajib Bhattacharyya Hooghly Mohsin College, India

ABSTRACT The recent global financial crisis is viewed as a glaring example of limitless pursuit of deregulation of financial markets and failure of global corporate governance. Though the global economic slowdown had its epicenter in the US but its impact is being witnessed in all major economies of the world. The present chapter seeks to analyze the post crisis experience of the Indian economy as compared to the global economic performances, using various macroeconomic indicators as output, employment, inflation, current account balance, movement in real effective exchange rate and inflow of FDI. It is based on a statistical analysis using secondary time-series data and is based on the Exogenous Structural Break Model developed by Perron (1989). Finally it tries to highlight the confidence of the economic agents based on some well recognized confidence indices (for e.g. Business Confidence Index, Consumer Confidence Index, FDI Confidence Index etc.) during the post-crisis period.

INTRODUCTION Financial crises and accompanying economic recessions have occurred throughout history and it is a form of the normal business cycle. The crisis may be a traumatic or stressful change in, political, social, economic, military affairs and large-scale environmental event. The origin may be different but the tremors are being felt in different parts of the world. Globalization, which, has contributed

to the extraordinary accumulation of wealth and finance overtime, is usually the leading force in the growth of globalization. Financial globalization contributed to the unprecedented growth and prosperity on the one hand but has also resulted in greater instability through excessive use of credit, lowering of credit standards, and heavy reliance on leverage due to poor governance. The recent economic crisis is widely viewed as a glaring example of limitless pursuit of deregulation of

DOI: 10.4018/978-1-4666-8274-0.ch004

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Post Crisis Performance and Confidence of the Indian Economy

financial markets and failure of global corporate governance at the expense of caution, prudence, due diligence and regulation. After the collapse of the Bretton Woods Order, finance capital was increasingly operating under freely floating exchange rate. In developed capitalist world, all restrictions on movement of capital were gradually withdrawn. With full capital account convertibility of international currencies, there was a perceptible change in the functioning of the financial institutions. By early 1990s the new feature of “Sucking in Finance from all over the Globe and investing in all over the Globe” (Patnaik, 2009) became the order of the day. The origin of current economic crisis can be traced back to mid 2007, when three things became surfaced: (a) low income or sub-prime US households had borrowed heavily from banks and financial companies to buy homes; (b) the size of this sub-prime housing loan market was huge at about $ 1.4 trillion and (c) these loans had been packaged by the Wall Street financial engineers to really complicated financial instruments. In U.S.A., between 2001 and 2006, the interest rate prevailing in various sectors were low. Prices of houses showed an increasing trend because of lower rate of interest and banking sector was incurring lower profit. Therefore the banks and financial institutions in USA revised their lending rates, in which high rates of interests were charged and loans were given to the sub-prime lenders for purchasing the houses. They were fully aware about the risk involved in sub-prime lending for housing but they have taken such risk on the belief that housing prices would never fall. Investment in housing sector was found to be profitable to the speculators as well as banks, due to the continuously rising prices of houses. Americans have made huge speculative investment in housing sector. It caused a rise in demand for houses and housing loans in US. In order to fulfill the demand for huge loans for housing, the funds available with banks and financial institutions were found insufficient. Therefore, American

banks and financial institutions introduced a new credit weapon called Mortgage Bonds. The basis of these mortgage bonds was the houses already mortgaged by the people for borrowing housing loans were again mortgaged by artificially increasing the price of houses more than their actual prices. These mortgage bonds were sold in international market. Large amounts of funds were collected by American banks by selling these mortgage bonds. These funds were utilized for financing the housing loans in US. This housing bubble based on sub-prime loans burst in 2006-07. In the same year housing prices had declined after 15-16 years. It adversely affected the speculative investment made in housing sector. Those who had invested in houses to earn more profit, have to face losses. Therefore, they started to sell the houses but due to lack of demand, houses could not be sold. Huge over dues of housing loans were not repaid by the borrowers. Banks and financial institutions did not succeed in the recovery of these loans. The price of mortgage bonds started a steep fall resulting in loss for those who invested in mortgage bonds. Hence, the liquidity problem in America became very serious. Meltdown set in the third quarter of the year 2007. The large banks like Lehman Brothers, Merrill Synch had declared bankrupt. In USA, 19 large banks and 100 private financial institutions were declared bankrupt. Thus, the default in mortgage loans for housing is the primary reason for the financial crisis sweeping the world. In spite of the massive bailout packages declared by various governments, countries like Britain, Russia and Canada are facing recession, while China, India, Brazil, South Korea has experienced a slowing down in the pace of growth. The IMF did not admit the case of a global recession at the initial period, but finally had to accept it when it became more pronounced in November 2008. Economists like Paul Krugman and Joseph Stiglitz who were quite skeptical about the functioning of the financial market did not anticipate the speedy collapse. For more than a year since

63

 Post Crisis Performance and Confidence of the Indian Economy

the outbreak of the crisis, it was thought that the two fastest growing Asian economies, viz. China and India, would not only insulated but will also play a key role in resisting and moderating global downturn leading to world-wide recovery in a year or so. But the “decoupling hypothesis” proved this proposition to be seriously wrong as both advanced and emerging economies experienced a marked deterioration in their condition since September 2008 (Rakshit, 2009).

OBJECTIVE OF THE STUDY AND METHODOLOGY The present work seeks to analyze the post crisis experience of the Indian economy as compared to the global economic performances, using various macroeconomic indicators. It tries to explore the major explanations for the cause of the crisis and its impact on some major macroeconomic variables- output, employment, inflation, current account balance, movement in real effective exchange rate and inflow of FDI. The impact of the global financial crisis on the Indian economy has been assessed in terms of the Exogenous Structural Break Model developed by Perron (1989) using secondary time series annual data for the period 1981- 2013. The effect of the crisis has been assessed on five macroeconomic variables: annual growth rate of GDP at factor cost, annual growth rate of Gross Domestic Capital Formation or Investment, Gross Fiscal Deficit as percentage of GDP, foreign exchange (US $ million) and Current Account Balance as a percentage of GDP. It also focuses on certain global confidence indices (for e.g. Business Confidence Index, Consumer Confidence Index, FDI Confidence Index etc.) to estimate the confidence of the economic agents, particularly of the consumers and the business houses, during the post-crisis period. The entire analysis is based on time-series data, comparative studies and analytical logic developed through the understandings from various research papers,

64

reports, books, journals, and online data bases. The Statistical Package Eviews- 7 has been used for the empirical analysis of the data.

LITERATURE REVIEW One of the most vital parts of any research work is literature survey. It is generally done for the judgment of the relevancy of the research work under consideration. There has been an enormous body of literature, both theoretical and empirical, in the area of global financial crisis. The following are the instances of some notable works in this area. Rakshit (2009) was of the opinion that the world economic crisis first surfaced with the collapse of the US sub-prime mortgage market in August 2007 as the housing bubble lost steam. Soon it spread to markets for other securities in both the US and other countries having strong linkages with the US. This finally led to huge financial meltdown, a string of bankruptcies and a sharp economic slowdown in practically all industrialized countries. Stiglitz and Krugman (2009) believed that it is merely a temporary financial crisis which can be tackled by the governments. While Stiglitz believes that a better designed package is necessary, Krugman argues it needs to be large enough to have an effect. Patnaik (2009) stated that by early 1990s the new feature of “Sucking in Finance from all over the Globe and investing in all over the Globe” became the order of the day and there was a perceptible change in the functioning of the financial institutions. Vasudevan (2009) pointed out that the seeds of the current crisis lies in the process of financialisation in a model where profit accrues through proliferation of finance in different channels rather than through trade and commodity production. Kumar (2009) is of the opinion that the crisis is a fundamental one because restoration of trust and confidence in a flawed financial system is difficult and a sound financial system is the basic requirement of a capitalist system. Crotty (2008) pointed out

 Post Crisis Performance and Confidence of the Indian Economy

the key structural flaws in the US New Financial Architecture (NFA) which according to him is the prime cause of the crisis. Subbarao (2009) opined that the subprime crisis originating in US rapidly spread to other countries and permeated from the financial sector into the real economy through different channels. Mohanty (2009, 2010, 2013) in his speech as executive director, RBI pointed out that the Indian economy like other Emerging Market Economies (EMEs) was affected both by the global financial crisis and the announcement of likely exit by the US Fed in May 2013. So the government has resorted to both conventional and unconventional measures to mitigate the crisis. Green, King and Dawkins (2010) explain the main reason of global economic crisis is excessive sub-prime mortgages. Sinha (2012), in his speech as deputy Governor of RBI, opined that the crisis which started off as a localized sub-prime crisis has morphed into a financial crisis leading to a full-blown global economic crisis and has now taken the shape of a sovereign debt crisis. Shinde and More (2010) discussed in detail the impact of global economic recession and changes in macroeconomic variables in world economy. Walia (2012) explained the impact of the crisis on the Indian economy in terms various macroeconomic variables, such as output, export, import, BOP and stock market indicators. Perron (1989) explained the relation between the Great Crash, the Oil Price Shock and Unit Root Hypothesis in terms of the Exogenous Structural Break Model. Hemen, Williams and Olaniyi (2014) analyze the impact of the global financial crisis on economic growth on the Nigerian economy using Instrumental variable regression approach. Srivastava and Shanmugam (2012) also studied stationarity tests for aggregate outputs in the presence of structural breaks (GDP at factor costs) for the Indian economy during 1950-51 to 2011-12.

CAUSES OF ECONOMIC CRISIS Various explanations were advanced for the global financial crisis (2008). The major among them are as follows.

Process of Financialisation and Failure in Sub-Prime Asset Market First, it is generally argued that the crisis originating in the US financial market is due to the failure of sub-prime assets, especially in the housing mortgage market. Vasudevan (2009) pointed out that the seeds of the current crisis lies in the process of financialisation in a model where profit accrues through proliferation of finance in different channels rather than through trade and commodity production. After the collapse of the Bretton Woods arrangements in 1973, this process of vulnerable financial system with growing US debt and excessive private financial flows globally helped US sustain the privileged role of dollar as an international currency. Banks went out of their way to lend to sub-prime borrowers who had no collateral assets. Low income individuals who took out risky sub-prime mortgages were often unaware of the known risks inherent in such mortgages. While on the one hand, they were ever keen to become house-owners, on the other, they were offered easy loans without having any regard to the fact that they were not in a position to refinance their mortgages in the event of the crisis. All this was fine as long as housing prices were rising. But the housing bubble burst in 2007. Home prices fell between 20 per cent and 35 per cent from their peak and in some areas more than 40 per cent; mortgage rates also rose. Sub-prime borrowers started defaulting in large numbers. The banks had to report huge losses. Acharya (2009), Green, King and Dawkins (2010) also explain the main reason of global economic crisis is excessive sub-prime mortgages.

65

 Post Crisis Performance and Confidence of the Indian Economy

The crisis spread through the ‘Shadow Banking System’ that was based on unstructured sub-prime loans and assets which was motivated by investment banks, hedge funds, private equity groups, broker-dealers, money market funds and non-bank mortgage lenders- whose purpose was to generate huge incomes by securitization of loans. Credit markets became “dis-intermediated” i.e. capital markets became the intermediaries, instead of banks, between the savers and the borrowers. The investors driving this process took massive amount of debt. When the market for asset backed securities crashed it created a huge gap in the balance sheet of the financial institutions. As these institutions began selling of “toxic” assets to restore their balance sheet, they set off a downward spiral in prices and a drying up of credit- better known as “Minsky Moment” (Minsky, 2008).

Securitization and Repackaging of Loans The mortgage market crisis that originated in the US was a complex matter involving a whole range of instruments of the financial market that transcended the boundaries of sub-prime mortgage. An interesting aspect of the crisis emanated from the fact that the banks/ lenders or the mortgage originators that sold sub-prime housing loans did not hold onto them. They sold them to other banks and investors through a process called securitization. Securitization, as a financial process, has gained wide currency in the US in the last couple of decades. In the context of the boom in the housing sector, the lenders enticed the naive, with poor credit histories, to borrow in the swelling sub-prime mortgage market. They originated and sold poorly underwritten loans without demanding appropriate documentation or performing adequate due diligence and passed the risks along to investors and securitizes without accepting responsibility for subsequent defaults. These sub-prime mortgages were securitized and re-packaged, sold and resold to investors around

66

the world, as products that were rated as profitable investments. They had a strong incentive to lend to risky borrowers as investors, seeking high returns and were eager to purchase securities backed by sub-prime mortgages. The booming housing sector brought to the fore a system of repackaging of loans. It thrived on the back of flourishing mortgage credit market. The system was such that big investment banks such as Merrill Lynch, Morgan Stanley, Goldman Sachs, Lehman Brothers or Bears Stearns would encourage the mortgage banks countrywide to make home loans, often providing the capital and then the Huge Investment Banks (HIBs), would purchase these loans and package them into large securities called the Residential Mortgage Backed Securities (RMBS).

Worldwide Macroeconomic Imbalance It is argued that while the subprime problem was the trigger, the root cause of the crisis lies in the persistence of the global imbalances since the start of the current decade. Large current account deficits in the advanced countries mirrored by large current account surpluses in the emerging market economies (EMEs) implied that excess saving flowed uphill from developing countries to developed countries (Table 1). Bernanke (2005) considered this ‘saving glut’ as one of the factors leading to the crisis. Among the advanced countries, it is the US which has a large savinginvestment gap. Among the EMEs, it is China, which has the largest saving surplus. Differences in the consumption and investment patterns among countries (a saving glut in Asia and oil exporting countries and a spending binge in the United States) have resulted in emergence of global imbalances which led to large capital flows from surplus countries into deficit countries which were mostly the advanced countries (table- 2). Apart from the saving-investment imbalances, there has been concurrent accumulation of large foreign exchange reserves by the EMEs,

 Post Crisis Performance and Confidence of the Indian Economy

Table 1. Saving and investment [as a percentage of GDP] Countries

2001 Savings

Advanced Economies of which

2008

Investment

Gap

Savings

Investment

Gap

20.4

20.9

-0.5

19.5

21

-1.5

16.5

19.3

-2.8

12.6

18.2

-5.6

United States

26.9

24.8

2.1

26.6

23.5

3.1

Japan

19.5

19.5

0

25.6

19.2

6.4

Germany

15.4

17.4

-2

15.3

17

-1.7

United Kingdom

21.2

21.1

0.1

21.4

22.2

-0.8

25

24.4

0.6

34.8

30.9

3.9

Emerging and Developing Economies Of which

31.5

30.1

1.4

47.7

41.9

5.8

Developing Asia

38.4

36.3

2.1

49.2

42.6

6.6

China

23.5

22.8

0.7

32.5

34.9

-2.4

India

29.7

23.4

6.3

41.9

22.8

19.1

Middle East

28.8

21.8

7

30.9

26.2

4.7

Euro area

[Note: Data for China is from the World Development Indicators Online Database, World Bank; data for India is from the national source (CSO).] [Source: Compiled from World Economic Outlook (WEO), October 2009, IMF.]

particularly China, also as self insurance against sudden reversal of capital flows (Table 3). It is argued that accumulation of reserves, particularly from trade surplus, resulted in misalignment of exchange rates. This prevented the global imbalances to adjust. Moreover, the burden of adjustment was borne disproportionately by countries with flexible currencies. While there is merit in this argument, it is not clear whether movement in exchange rates by itself could have prevented

global imbalances without an adjustment in aggregate demand – lower consumption in the US and higher consumption in China.

Profound Structural Flaw in the US Financial System On the financial side the flawed institutions, often referred to as New Financial Architecture (NFA), which implies the integration of modern finan-

Table 2. Current account balance (as percentage of Global GDP) Countries

2006

2007

2008

2009

2010

2011

2012

2013

Advanced Economies

-1.2

-0.8

-1.2

-0.1

0.0

-0.1

-0.1

0.4

United States

-5.8

-4.9

-4.6

-2.6

-3

-2.9

-2.7

-2.3

Emerging and Developing Asia

5.7

6.6

5.9

3.5

2.5

0.9

0.8

1.1

Emerging and Developing Europe

-6.5

-8.1

-8.2

-3.2

-4.9

-6.4

-4.5

-3.9

Latin America and the Caribbean

1.5

0.2

-0.9

-0.7

-1.3

-1.4

-1.9

-2.7

Middle East, North Africa, Afghanistan, and Pakistan

15.5

12.2

12.8

1.7

6.5

13.1

12.6

9.5

Sub-Saharan Africa

4.1

1.4

-0.2

-3.2

-1.0

-1.0

-2.7

-3.6

[Source: Compiled from World Economic Outlook, 2014]

67

 Post Crisis Performance and Confidence of the Indian Economy

Table 3. Foreign Exchange Reserves in Emerging Economies & Developing Countries (US $ billions) Countries

2001

2008

Emerging and Developing Economies Of which

857

4,963

Developing Asia

380

2,538

China

216

1,950

India

46

248

135

826

Commonwealth of Independent States

44

504

Russia

33

413

159

498

Brazil

36

193

Mexico

45

95

Middle East

Western Hemisphere

[Source: World Economic Outlook, October 2009]

cial markets with a regime of light government regulation that originated in US and UK in the late 1970s is one of main causes of the financial crisis (Kumar, 2009). Deregulation accompanied by rapid financial innovation stimulated powerful financial booms ended in the crisis. The key structural flaws in the NFA (Crotty, 2008) were 1. The NFA was based on light regulation on commercial banks, even lighter regulations on Investment Banks, and little, if any regulation of the shadow banking system- hedge and private equity funds and the bank-created Special Investment Vehicles (SIVs). 2. The NFA incorporates perverse incentives which induce all important financial institutions to take excessive risks, exacerbate boom and generate crisis. 3. Complex and opaque financial products created by innovations lacked proper pricing this result in loss of liquidity when boom ended. 4. The statement that commercial banks distributed almost all risky assets to capital markets and hedged the remaining risk was

68

incorrect and this was not considered in the NFA narrative about efficient capital market. 5. In the NFA banks are allowed to hold risky securities of their balance sheets in special investment vehicles (SIVs), with no capital required to support them .

Excessive Leverage A comparison of the current crisis with various episodes of past crises reveals considerable similarity with regard to the underlying causes – excessive use of credit, lowering of credit standards, and heavy reliance on leverage. Reinhart and Rogoff (2009) found that the global dimension of the current crisis is neither new nor unique to this episode. Apart from perpetuating global imbalances, the easy monetary policy pursued in advanced economies encouraged excessive leveraging on the part of investors as well as banks and financial institutions. The sharp rise in the leverage of financial institutions in the first decade of this century has been particularly striking. In 2004 the Securities and Exchange Commission (SEC) allowed the five largest investment banks – Merrill Lynch, Bear Stearns, Lehman Brothers, Goldman Sachs and Morgan Stanley – to more than double the leverage they were allowed to keep on their balance sheets, i.e. to lower their capital adequacy requirements. The institutions that have reported huge losses are those which are highly leveraged.

Lack of Good Global Corporate Governance Critics have pointed out that failure of global corporate governance is one of the major reasons for the crisis. The financial system of USA has changed dramatically since the 1930s. Many of America’s big banks moved out of the “lending” business and into the “moving business”. They focused on buying assets, repackaging them, and selling them, while establishing a record of

 Post Crisis Performance and Confidence of the Indian Economy

Table 4. Real GDP growth of different regions of the world during pre and post crisis period Countries

Pre-crisis Period 2005

2006

2007

Post-crisis Period 2008

2009

2010

2011

2012

2013

2014c

World

4.7

5.2

5.3

2.7

-0.4

5.2

3.9

3.2

2.9

3.6

Developed Economies

2.6

2.8

2.5

0

-3.7

2.6

1.5

1.3

1

1.9

European Union

2.2

3.4

3.2

0.4

-4.5

2

1.7

-0.4

-0.1

1.4

Economies in Transition

6.6

8.5

8.7

5.3

-6.5

4.7

4.6

3.2

2

3.3

Developing Countries

6.8

7.6

7.9

5.4

2.7

7.7

5.9

4.7

4.6

5.1

[Source: World Economic Situation and Prospect, 2014.]

incompetence in assessing risk and screening for credit-worthiness. Nothing has been done even to address their perverse incentive structures, which encourage short-sighted behaviour and excessive risk taking. Prudential oversight was lax, allowing poor lending standards, the proliferation of non-transparent securitization structures, poor risk management throughout the securitization chain, and the build-up of excessive leverage by financial institutions. The weak-nesses in prudential oversight were partly due to particular characteristics of the US financial system, such as the existence of different regulatory regimes for investment banks, commercial banks and government-sponsored enterprises.

IMPACT OF THE GLOBAL FINANCIAL CRISIS Following the collapse of Lehman Brothers in September 2008, the global inter-bank financial markets froze in view of large losses suffered by the major financial institutions and the extreme uncertainty over the health of the counterparty balance sheets. This had a knock-on effect on various segments of financial markets, including inter-bank markets. Interbank markets in advanced economies were the first to be affected by severe liquidity crisis as banks became reluctant to lend to each other on fear of counterparty risks. This was manifested in abnormal level of spreads,

shortening of maturities, and contraction, or even closure, of some market segments. These effects were quickly transmitted to real sector. With money markets witnessing a squeeze, equity prices plummeting and credit spreads rising, banks and other financial institutions experienced erosion in their access to funding and capital. The crisis spread to the Emerging Market Economies (EMEs) through all the three broad channels – confidence, finance and trade – reflecting increased global integration (Sinha, 2012). The confidence channel worked in two ways. First, although the epicenter of crisis was in advanced markets, exposures to emerging markets were reduced sharply with the return of risk aversion. Second, with increase in deleveraging, there was a widespread shortage of US dollar (Shankar, 2009).

IMPACT ON REAL SECTOR Impact on Real GDP Growth Real GDP growth in advanced economies turned negative in 2009 (- 3.7 per cent) from the strong pace of 2.9 per cent during 2004-07. Growth recovered modestly in 2010, but again turned anemic in 2011 (1.6 per cent). Growth in advanced economies averaged a mere 0.3 per cent during 2008-11 and output still remains well below potential. The IMF expected the growth in advanced economies to decelerate further to 1.2 per cent in

69

 Post Crisis Performance and Confidence of the Indian Economy

Figure 1. Real GDP of various regions of the world during 2005 to 2014

[Note: ‘c’ denotes Baseline scenario forecasts, based on data available from World Economic Situation and Prospect, 2014] [Source: Table- 4]

2012. Underperformance in the world economy was observed across almost all regions and major economic groups. Though most developed economies continued to struggle, there have been some signs of improvements for the euro area which has finally come out of a protracted recession, with gross domestic product (GDP) for the region as a whole returning to growth. The region of “Economies in transition” was the block which suffered a steep decline in their real GDP growth (from 5.3 per cent in 2008 to – 6.5 per cent in 2009. Amongst these countries the worst affected were the Common Wealth of Independent States and Georgia. Their growth decelerated due to weak exports and external financing constraints, supply-side bottlenecks, and weak consumer and business confidence. Among all the regions, developing countries were

70

the sole exception where the real GDP growth, though declined, did not turn negative after the crisis (Figure 1). After a notable slowdown in 2011-2012, economic growth in East Asia stabilized at a moderate level in 2013. The region continues to be adversely affected by relatively weak external demand from developed economies, as well as an adjustment to slower growth in China. In most East Asian economies, private consumption and investment will continue to expand at a solid pace, supported by stable labour market conditions, low inflation and fairly accommodative monetary policies. Fiscal policies will remain moderately expansionary and continue to provide support for growth. Growth in South Asia remains subdued due to a combination of both internal and external factors.

 Post Crisis Performance and Confidence of the Indian Economy

Table 5. Comparison of real GDP growth rate in selected countries during the pre and post crisis period Countries

Pre-crisis Period 2005

2006

Post-crisis Period

2007

2008

2009

2010

2011

2012

2013

2.7

1.8

-0.3

-2.8

2.5

1.8

2.8

1.6

1.7

2.2

-1

-5.5

4.7

-0.6

1.9

1.9

Developed US

3.4

Japan

1.3

EU UK

3.2

2.8

3.4

-0.8

-5.2

1.7

1.1

0.1

1.4

France

1.8

2.5

2.3

-0.1

-3.1

1.7

2

0

0.1

Developing Economies China

11.3

12.7

14.2

9.6

9.2

10.4

9.3

7.7

7.7

India

9.1

9.3

9.7

5.3

7.4

10.1

7.3

5.1

4.8

Argentina

9.2

8.5

8.7

6.8

0.8

9.2

8.9

1.9

5

Brazil

3.2

4

6.1

5.2

-0.3

7.5

2.7

0.9

2.5

Philippines

4.8

5.2

6.6

4.2

1.1

7.6

3.6

6.8

6.7

[Source: World Economic Situation and Prospect, 2014, United Nations]

In order to assess the differential impact of the crisis on different sets of countries the world has been divided into three major groups: Developed, European Union (EU) and Developing countries. From the first two groups each two countries were chosen which are assumed to be the most important ones and a set of five countries were taken in the last category to make the comparison more meaningful relative to the Indian economy. It is quite clear from Table 5 that among the few selected countries of the world only China, India, Argentina and Philippines could maintain a positive real GDP growth in 2009, but the growth rates of all the others turned negative. Among developed countries the United States of America is estimated to grow at a meager pace of 1.6 per cent in 2013, significantly lower than the 2.8 per cent growth of the previous year. Fiscal tightening and a series of political gridlocks over budgetary issues during the year have weighed heavily on growth. Monetary policy has been extremely accommodative, but it has had greater effect on boosting equity prices than on stimulating the

real economy [Global Economic Prospects (June 2014)]. Japan is estimated to grow by 1.9 per cent in 2013, boosted by a set of expansionary policy packages, including fiscal stimulus and large-scale purchases of assets by the central bank. But the condition for UK and France is not quite encouraging. Within the developing economies China is trying to maintain a stable growth of almost 7.7 per cent followed by Philippines, Argentina and India. One of the most interesting features is that since 2010 there has been a steady decline of real GDP growth in India from 10.1 per cent in 2010 to almost 4.8 per cent in 2013 (Figure 2).

Impact on Employment The global unemployment rate remained at 6.0 per cent of the global labour force, unchanged from 2012. The number of unemployed around the world is estimated to have reached 201.8 million in 2013, an increase of 4.9 million from a revised 196.9 million in the previous year. There were

71

 Post Crisis Performance and Confidence of the Indian Economy

Figure 2. Comparison of real GDP growth in selected countries during 2005-2013. [Source: Table- 5]

31.8 million more unemployed persons around the world in 2013 than in 2007, prior to the onset of the global economic crisis (figure- 3). On the basis of current macroeconomic projections, the ILO expects little improvement in the global labour market in 2014, with the global unemployment rate ticking up to 6.1 per cent and the number of unemployed rising by a further 4.2 million [Global Employment Trends, ILO (2013, 2014)] . When we compare the unemployment rates of the above selected countries, presented in Table 6, during the pre and post crisis years we see that US and France are the worst affected by the crisis. But the countries of the developing world are not that much affected by the crisis (though the countries which had strong trade relationship with the US were indirectly affected by the job loss).

72

Impact on Inflation During the period of crisis inflation increased at a rapid pace throughout the world, both in advanced economies as well as in emerging market and developing economies. The differing growth dynamics between the major economies are projected to come with subdued inflation pressure, for two reasons. First, the pickup in activity in the advanced economies will not lead to a major reduction in output gaps, which remain large. Second, commodity prices have fallen amid improved supply and lower demand growth from key emerging market economies, notably China. The latest projections for both fuel and nonfuel prices indicate modest declines in both 2013 and 2014. In advanced economies, inflation is cur-

 Post Crisis Performance and Confidence of the Indian Economy

Figure 3. Trends in global unemployment

[Note: * 2013 are preliminary estimates; 2014–18 are projections. The graph displays past trends and projections for global unemployment]. [Source: Global Employment Trends (2014), ILO]

rently running below target, at about 1½ per cent on average. Inflation is expected to move broadly sideways at around 5-6 per cent in emerging market and developing economies (figure-4). In the US the consumer price inflation fell steeply from 4.3 per cent in 2008 to -0.8 per cent

in 2009, but thereafter it again started to increase slowly. Almost same picture is seen in case of Japan. In China also it fell from 5.9 to -0.7 during the same period. In 2009, it was the highest in case of India among all these countries (it in fact increased from 8.3 to 10.9).

Table 6. Comparison of unemployment rates of selected countries during 2006- 2013 Unemployment Rates (As Percentage Of Labour Force) Pre-Crisis Period 2006

Post-crisis Period

2007

2008

2009

2010

2011

2012

2013

US

4.6

4.6

5.8

9.3

9.6

8.9

8.1

7.5

Japan

4.1

3.8

4

5.1

5.1

4.6

4.4

3.9

UK

5.4

5.3

5.7

7.6

7.8

8

7.9

7.5

France

9.2

8.4

7.8

9.5

9.7

9.6

10.3

10.9

China

4.1

4

4.2

4.3

4.1

4.1

4.1

4.1

India

N.A

N.A

N.A

9.4

N.A

3.8

4.7

N.A

Argentina

10.2

8.5

7.9

8.7

7.7

7.2

7.3

7.6

Brazil

10

9.3

7.9

8.1

6.7

6

5.5

5.6

Philippines

7.9

7.3

7.4

7.5

7.4

7

7

7.3

[Source: Author’s Compilation is based on World Economic Situation and Prospects, 2014]

73

 Post Crisis Performance and Confidence of the Indian Economy

Figure 4. Global Inflation (Year-on Year percentage change) [Source: World Economic Outlook 2013]

Figure 5. Consumer price inflation

[Source: Author’s Construction is based on the data of World Economic Situation and Prospects, 2014]

74

 Post Crisis Performance and Confidence of the Indian Economy

Figure 6. Current account as percentage of GDP

[Source: Author’s Construction is based on World Economic Outlook, 2014]

Impact on Balance of Payments (BOP) The major impact of the global financial crisis is on the BOP which comprises of both current account as well as capital account.

Impact on Current Account Deficit Large current account deficits in the advanced countries mirrored by large current account surpluses in the emerging market economies (EMEs) implied that excess saving flowed uphill from developing countries to developed countries. Bernanke (2005) considered this ‘saving glut’ as one of the factors leading to the crisis. Among the advanced countries, it is the US which has a large saving-investment gap. Among the EMEs, it is China, which has the largest saving surplus. As seen from figure- 6, the current account balance (CAB) as percentage of GDP improved

in US in the post crisis period compared to the pre-crisis period, but the situation is opposite in case of countries which had trade relations with US. In Japan, except in 2010, CAB deteriorated continually. Same is the trend in UK, France, China, India, Argentina and Brazil. The only exception is Philippines.

Movement in Real Effective Exchange Rate (REER) The real effective exchange rate, which adjusts the nominal index for relative price changes, gauges the effect on international price competitiveness of the country’s manufactures owing to currency changes and inflation differentials. A rise in the index implies a fall in competitiveness and vice versa. From figure- 7 it shows that compared to 2008 there has been some rise in the REER of US and Japan, which signifies a loss of competitive strength. This has been more pronounced for

75

 Post Crisis Performance and Confidence of the Indian Economy

Figure 7. Movement in real effective exchange rate (REER)

[Source: Costructed from the data World Economic Situation and Prospects, 2014] [Note: a Year 2000=100.b Indices based on a “broad” measure currency basket of 46 currencies (including the euro). The relative price changes are based on indices most closely measuring the prices of domestically produced finished manufactured goods, excluding food and energy, at the first stage of manufacturing. The weights for currency indices are derived from 2000 bilateral trade patterns of the corresponding countries.]

Brazil and China. But in case of India, Argentina and Philippines the situation is just the reverse.

Impact on FDI Inflows The recent database available clearly indicates that almost all countries in the world suffered a

setback respect to the inflow of FDI following the global financial crisis in 2008 including the US. FDI inflows halved in US; Russia, Brazil, Argentina were severely hit by the outbreak of the crisis. India and China, also experienced a fall in FDI inflows, but the extent of decline has been less sharp as shown in Table 7.

Table 7. FDI Inflows in India and few selected economies (USD billion) Pre-Crisis Period 2004

2005

2006

Post-Crisis Period

2007

2008

2009

2010

2011

2012

2013

USA

146

112.6

243.2

221.2

310.1

150.4

205.9

230.2

166.4

193.4

Argentina

4.1

5.3

5.5

6.5

9.7

4

7.8

9.9

12.1

9.1

Brazil

18.1

15.1

18.8

34.6

45.1

25.9

48.5

65.3

64

66,7

China

62.1

104.1

124.1

156.2

171.5

131.1

243.7

280

253.4

258.2

India

5.8

7.6

20.3

25.5

43.4

35.6

27.4

36.5

24

28.2

Russia

15.4

14.4

37.4

54.5

75.9

27.8

31.7

36.9

30.2

54.5

0.8

6.6

-0.5

5.7

9

5.7

1.2

4.3

4.6

8.2

South Africa

[Source: OECD International direct investment database, IMF.]

76

 Post Crisis Performance and Confidence of the Indian Economy

STATISTICAL ANALYSIS Empirical Literature In general, the time series models employ the stationary series as they are mean reverting, ensuring the constancy of parameters (mean, variance etc.) and having limited memory of past behavior (i.e., shocks are only transitory). For non-stationary series such as random walk, the parameters are time dependant (or varying). The presence of either unit root (s) or deterministic trend (or both) will lead to the non-stationarity. If the former is present, the series will reduce to stationary by differencing and the series is known as “difference stationary”. If the latter exists, the series will reduce to stationary by de-trending and the series in this case is called as “trend stationary”. According to Nelson and Plosser (1982) the nature of macroeconomic data follows two types of process, such as Difference Stationary (DS) rather than Trend Stationary (TS). A TS process implies that the effect of random shock is temporary around a trend. On the other hand, DS process implies that this random shock has a permanent effect. Further, in case of DS process the variance of the Yt is not constant. It is depend on time. A large number of studies following Nelson and Plosser (1982) also suggested that DS process is the most appropriate one. The test for detecting whether a series is DS or TS is called the unit root test, as introduced by Dickey and Fuller (1979, 1981). To understand this process considers the following regression equation:

∆Yt = δ 0 + δ1t + γ Yt −1 + U t where U t = αU t −1 + εt

A test of null hypothesis H0: γ = 0 is required. If the null hypothesis is fail to reject then the underlying series is DS. Rejection of the null hypothesis implies the underlying series is TS. The coefficient of Yt-1 does not follow the standard t distribution. The problem was solved by Fuller, who obtained limiting distribution of this coefficient. These distributions were approximated empirically by Dickey (1976). McKinnon (1990) has derived critical values from a much larger set of replications. If the underlying process is TS and the coefficient of time is statistically significant then it implies that there exists a trend in the series. And if constant term is statistically significant then there exists a drift in the model. Now if ∆Yt depends on the ∆Yt-j (where j=1, 2, K, K Tλ, 0 otherwise; DTt(λ) = t - Tλ if t < Tλ, 0 otherwise.DUt(λ) is the intercept dummy or change in levelsDTt(λ) is the slope dummy or change in the slope.Yt is the time series variable to be tested in each case.λ corresponds to estimated values of the break fraction.FDi denotes the first difference for the ith variable (i = 1……5)

Results and Analysis For GDPFC the model is statistically significant at 10% level and for GDPFC Model-C is the

 Post Crisis Performance and Confidence of the Indian Economy

best Fitted Model. In this model the coefficient of GDPFC (-1) is -1.036084 and its t-statistic is -3.729988. The coefficient of DT (slope Dummy) is -1.354275 and its t-statistic is -2.028675. This implies that after the structural break or crisis of 2008, there has been a significant negative impact on the growth of GDPFC. So the effect of the crisis on Real GDP of India is quite significant. Moreover, the coefficient of DU (intercept Dummy or change in level) is 2.669985 with t-statistic 1.161577, which is less than the critical value 1.64. The coefficient of T is 0.122820 with t-statistic 1.908340 which shows that after 2008 there has been fluctuation in real GDP growth of India. In Case of GFD Model A is the best Fitted Model and the model is significant at 10% level. In this model the coefficient of GFD (-1) is -0.627516 and its t-statistic is -3.543853. The coefficient of T is -0.026001 with t-statistic -0.801213 which shows that after 2008 there has been no fluctuation in GFD of India. Moreover, the coefficient of DU (intercept Dummy or change in level) is 0.082149 with t-statistic 0.096951, which is less than the critical value 1.64. This implies there has been no significant change in GFD after the crisis in 2008. For rest of the variables (i.e. INV, FOREX and CAB) the model is DS (Difference Stationary) type. No clear assessment can be made about the impact of the crisis on these variables; only we can state their variability overtime. In case of INV the t-statistic has been the minimum for model A (-1.566923). The coefficient of T is 0.205902 with t-statistic 1.933717 which is more than the critical value 1.64. This shows that after 2008 there has been positive variability in investment of India. In the case of FOREX the t-statistic has been the minimum for model B (t-value is -0.190054. In this model the coefficient of T is 1959.279 (i.e. positive) and it is significant (t-value is 1.953049). So there has been significant variability of foreign exchange in India after the crisis period in 2008. In the case of the variable CAB the t-value has been the minimum for model A (t-value is -2.718347).

In this model the coefficient of T is 0.035899 (i.e. positive) but it is not significant (t-value is 1.124837). So there has been no significant variability of current account balance in India after the crisis period in 2008. [For Details refer to the tables in the Appendix]

CONFIDENCE OF ECONOMIC AGENTS Business Confidence The latest Business Confidence Survey conducted by FICCI in September, 2013. The survey drew responses from about 200 companies with a turnover ranging from 90 lakh to 1.35 lakh crore. The participating companies belonged to a varied array of sectors such as textiles, cement, financial services, hospitality, chemicals, metal and metal products, automobiles, FMCG, electrical equipment and machinery, paper and paper products. The survey was conducted during July 2013 and August 2013 and brings out expectations of the corporate members for the period July 2013 to December 2013. It points out position of business confidence in the economy in recent times. The survey highlights the following features: 1. With regard to the current overall economic situation relative to last six months, a majority 65% of the respondents cited a ‘moderately to substantially’ worse performance. 2. Expectation of the participants with regard to near term outlook was not buoyant. 3. The performance of the operational parameters (such as sales, profits and investments were disappointing too. 4. The value of Overall Business Confidence Index declined to 49.0 in the current survey round. The corresponding figure in last survey was 57.4 and 51.8 a year back.

79

 Post Crisis Performance and Confidence of the Indian Economy

Figure 8. Overall business confidence index

[Source: Business Confidence Survey (FICCI), Sept. 2013]

5. Weak demand, availability of credit, high cost of credit was identified as the basic constraints. The current condition index dropped to 43.6 in Q1 FY14 from 50.7 in Q4 FY13. A year back the corresponding figure was 45.7. The fall in the value of current condition index, which captures the performance at the economy, industry and firm level, clearly indicates that situation has deteriorated noticeably. The Expectation Index stood at 51.7 in Q1 FY14, vis-a-vis 60.8 in Q4 FY13 and 54.8 in Q1 FY13. As a result, the value of Overall Business Confidence Index declined to 49.0 in Q1 FY14. The corresponding figure in Q4 FY13 was 57.4 and 51.8 a year back. This is the lowest in about 18 quarters and is somewhat reminiscent of the situation in 2008-09 (Figure 8).

viz., Bengaluru, Chennai, Hyderabad, Kolkata, Mumbai and New Delhi. The survey captures qualitative information on a 3 point scale viz. improve, remain same or worsen. The assessments are analyzed in two parts, viz., current situation as compared with a year ago and expectations for a year ahead. There are four blocks in the survey schedule broadly covering around 4,000 respondents’ perceptions on general economic conditions and own financial situation. The major highlights of the survey are-

Consumer Confidence

1. There has been a significant improvement in both Current Situation Index (CSI) and Future Expectations Index (FEI) in March 2014 (shown in table- 9) largely due to increase in the net response on household circumstances and due to increase in the positive perceptions on all selected parameters except spending.

RBI, Consumer confidence survey, March 2014 (Round 16) provides an assessment of respondents’ perception spread across six metropolitan cities

2. The net responses on current economic condition and economic outlook witnessed sharp

80

 Post Crisis Performance and Confidence of the Indian Economy

Table 9. Current and future expectations index Indices

June 2013

Sept 2013

Dec 2013

Mar 2014

Current Situation Index (CSI)

101.7

88.0

90.7

99.9

Future Expectation Index (FEI)

109.8

90.5

100.3

114.9

prices to increase during the next year which is lower than the previous round of surveys. Here, perceptions of increase in prices are considered to be negative sentiments and decrease in prices is considered to be positive sentiments.

FDI Confidence Index

[Source: RBI, Consumer confidence survey, March 2014 (Round 16)]

rise during this round of survey as compared to December 2013 survey (as seen from Table 10). This is largely due to decline in the negative sentiments along with a rise in positive perceptions. However, net response on current economic conditions remains in the negative zone since September 2012 (Table 10). In this round of the survey significant improvement in income expectations is observed This coupled with reduction in negative perceptions has pushed the net responses on income outlook to above 50 levels. Lower confidence on spending has been reported on this round of the consumer survey. Only about one fourth of respondents reported intentions for increase in future spending. However, the net response on future spending remained negative during the latest three rounds of survey. With regard to the perceptions on employment outlook there has been overall improvement. Around 73 per cent of respondents expect the

The A.T. Kearney’s FDI Confidence Index which was established in 1998 has been published for 2014. It examines how changes in a country’s political, economic and regulatory system are likely to affect FDI inflows in the coming years. The top ten countries of 2014 are shown below and their corresponding positions in the previous year and the change in each of their ranks are also depicted [+ denote improvement; and – denote deterioration]. Table 11 clearly shows that the attractiveness according to FDI ranking has either remained same or improved in case of most of the developed countries like US, Canada, UK, Germany, and France and also in case of China and Singapore. But it has deteriorated in case of India, Brazil and Australia.

CONCLUSION The global financial crisis which initially started off with the sub-prime crisis has diffused into a financial crisis leading to a full-blown global

Table 10. Perceptions on economic conditions (percentage responses) Compared with 1 year ago

1 year ahead

June 2013

Sept 2013

Dec 2013

Mar 2014

June 2013

Sept 2013

Dec 2013

Mar 2014

Improve

28.2

22.4

22.7

29.5

35.2

29.9

34.8

47.6

Remain same

20.2

18.4

23.3

31.3

27.0

31.5

35.1

31.2

Worsen

51.6

59.3

54.0

39.1

37.8

38.6

30.1

21.1

Net Response

     -23.3

-36.9

-31.2

-9.6

-2.6

-8.8

4.7

26.5

[Source: RBI, Consumer confidence survey, March 2014 (Round 16)]

81

 Post Crisis Performance and Confidence of the Indian Economy

Table 11. FDI confidence index rankings of top ten nations in 2014 Country Name

FDI ranking in 2014

FDI ranking in 2013

Change in Rank from previous year

US

1

1

0

China

2

2

0

Canada

3

4

+1

UK

4

8

+4

Brazil

5

3

-2

Germany

6

7

+1

India

7

5

-2

Australia

8

6

-2

Singapore

9

10

+1

France

10

12

+2

[Source: A. T. Kearney FDI Confidence Index, 2013, 2014]

economic crisis has now taken the shape of a sovereign debt crisis. Following the emergence of the crisis, India, initially remained somewhat insulated to the global developments, but eventually was impacted significantly through all the channels – financial, real and more importantly, the confidence channel. This could be attributed to the global nature of the crisis on the one hand and accelerated trade and financial integration of the Indian economy with the world on the other. Initially it was apprehended that India would remain insulated from global financial meltdown on the back of the significant buffers they have built over the years, which included substantial foreign exchange reserves, improved policy frameworks and generally robust banking sector. Due to the tightening of credit conditions in international markets Indian companies found it difficult to raise money from the international market. This shortage of dollar liquidity put significant pressures on the domestic foreign exchange market, which was reflected in downward pressures on the Indian rupee along with its increased volatility. Statistical analysis suggest the exogenous structural break which occurred in the form of global

82

financial crisis resulted in significant fluctuations in both the growth of real GDP and gross fiscal deficit of India during the post crisis period. For rest of the variables (i.e. investment, foreign exchange reserves and current account balance as a percentage of GDP) the model is DS (Difference Stationary) type. No clear assessment can be made about the impact of the crisis on these variables. RBI has taken both conventional as well as unconventional measures [such as Quantitative Easing (QE) and Credit easing (CE)] to mitigate the negative impact of the crisis. Along with this the RBI has also resorted to regulatory policies to stabilize the market. But the greatest challenges to the policy makers seems to be the revival of the growth rate of GDP, creation of employment opportunity and maintain a stable price situation. Though with regard to the confidence of the business near term outlook was not buoyant but from the point of view of the consumers, significant improvement was observed in income expectations coupled with reduction in negative perceptions. In terms of FDI attractiveness India’s positions declined in 2014 compared to 2013.

REFERENCES Bernanke, B. S. (2005). The global saving glut and the U.S. current account deficit. Remarks at the Sandridge Lecture. Richmond, Virginia: Virginia Association of Economics. Bhagwati, J. (2004). In Defense of Globalization. New York: Oxford University Press. Crotty, J. (2008). Structural causes of the global financial crisis: A critical assessment of the “New Financial Architecture”. Economics Department Working Paper Series, Paper 16. University of Massachusetts – Amherst. Economic Survey (2009-10) & (2010-11), Government of India, New Delhi.

 Post Crisis Performance and Confidence of the Indian Economy

FICCI. (September, 2013). Business Confidence Survey. Global Economic Prospects, World Bank Group, June 2014. Global Employment Trends (2013, 2014), ILO. Green, D., King, R., & Dawkins, M. M. (2010). The global economic crisis and developing countries: Impact and response. Working Draft, Oxfam Research Report. Oxfam Australia. Hemen, A., Williams, H. T., & Olaniyi, A. (2014). The impact of the global financial crisis on economic growth on a developing economy. (An Instrumental Variable Regression Approach). Global Advanced Research Journal of Management and Business Studies, 3(1), 23–31. India Development Update, World Bank Group, October 2013.

Mohanty, D. (2010). Global financial crisis and the Indian economy. Speech by Deepak Mohanty, Executive Director, Reserve Bank of India, delivered at GEM Investor Conference, Washington DC on October 10, 2010. Mohanty, D. (2013). Unconventional monetary policy – the Indian experience with crisis response and policy exit. Speech by Mr. Deepak Mohanty, Executive Director of the Reserve Bank of India, at the Reserve Bank Staff College (RBSC), Chennai, 26 December 2013. Nelson, C. R., & Plosser, C. I. (1982). Trends and random walks in macroeconomic time series. Journal of Monetary Economics, 10(2), 139–162. Patnaik, P. (2009). The economic crisis and contemporary capitalism. Economic and Political Weekly, 44(13), 28.

Kearney, A.T. (2014). FDI Confidence Index, 2013.

Perron, P. (1989). The great crash, the oil price shock, and the Unit Root Hypothesis. Econometrica, 57(6), 1361–1401. doi:10.2307/1913712

Krugman, P. (2009). How Did Economists Get It So Wrong? The New York Times, September 2.

Rakshit, M. (2009). India amidst the global crisis. Economic and Political Weekly, 28(13), 94–105.

Kumar, A. (2009). Tackling the current global and financial crisis: Beyond demand management. Economic and Political Weekly, 44(13), 28.

RBI, Consumer Confidence Survey: March 2014 (Round 16).

Minsky, H. P. (2008). Stabilizing an Unstable Economy. McGraw-Hill Publications. Mohan, R. (2009). Global financial crisis: Causes, impact, policy responses and lessons. Working Paper 407, Stanford University, Stanford, CA, USA. Mohanty, D. (2009). The global financial crisis: Genesis, impact and lessons. Speech by Deepak Mohanty, Executive Director, Reserve Bank of India in Hyderabad on December 30, 2009 at the International Conference on Frontiers of Interface between Statistics and Science.

RBI, Hand Book of Statistics on Indian Economy 2013-14. RBI Quarterly Review (2013-14), (April- June). Reddy, Y. V. (2009). India and the Global Financial Crisis Managing Money and Finance. New Delhi: Orient Blackswan Private Limited. Reinhart, C. M., & Kenneth, S. R. (2009). This Time is Different: Eight Centuries of Financial Folly. Princeton University Press. Shankar, A. (2009). India-After the Global Crisis. New Delhi: Academic Foundation.

83

 Post Crisis Performance and Confidence of the Indian Economy

Shinde, M. N. & More, D. K. (2010). Global economic recession and changes in macroeconomic variables in world economy. Southern Economist, 49(9). Sinha. A. (2012). Changing contours of global crisis: Impact on Indian economy. RBI Monthly Bulletin, April. Srivastava, D. K., & Shanmugam, K. R. (2012). Stationarity test for aggregate outputs in the presence of structural breaks, Working paper 72/2012, Madras School of Economics. Stiglitz, J. (2009). The global crisis, socil protection and jobs. International Labour Review, 148(12), 1–13. doi:10.1111/j.1564-913X.2009.00046.x

Subbarao, D. (2009). Financial Stability: Issues and Challenges. Valedictory address at the FICCIIBA Annual Conference on ‘Global Banking: Paradigm Shift’ organized jointly by FICCI and IBA on September 10. Vasudevan, R. (2009). The global melt-down: Financialisation, dollar hegemony and sub-prime market collapse. Economic and Political Weekly, 44(13), 28. Walia, S. (2012). Impact of global economic crisis on Indian economy. International Journal of Latest Trends in Engineering and Technology, 1(2), 31–36. World Economic Outlook Database, 2009- 2014, International Monetary Fund. World Economic Situation and Prospects (WESP) 2013.

84

Post Crisis Performance and Confidence of the Indian Economy

APPENDIX For Variable- GDPFC Table 12. Model-A Dependent Variable: D(GDPFC) Method: Least Squares Date: 10/14/14 Time: 18:32 Sample (adjusted): 1983 2013 Included observations: 31 after adjustments Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

4.135573

1.510339

2.738175

0.0110

DU

-1.164309

1.384291

-0.841087

0.4080

T

0.095680

0.066619

1.436236

0.1629

GDPFC(-1)

-0.897311

0.284890

-3.149674

0.0041

FD1

-0.016265

0.206739

-0.078674

0.9379

Table 13. Model-B Dependent Variable: D(GDPFC) Method: Least Squares Date: 10/14/14 Time: 18:41 Sample (adjusted): 1983 2013 Included observations: 31 after adjustments Variable C

Coefficient

Std. Error

4.152042

1.409350

t-Statistic

Prob.

2.946069

0.0067

T

0.134158

0.064041

2.094896

0.0461

DT

-0.716665

0.382457

-1.873843

0.0722

GDPFC(-1)

-0.985143

0.276124

-3.567759

0.0014

FD1

0.004155

0.196545

0.021143

0.9833

85

Post Crisis Performance and Confidence of the Indian Economy

Table 14. Model-C Dependent Variable: D(GDPFC) Method: Least Squares Date: 10/14/14 Time: 18:44 Sample (adjusted): 1983 2013 Included observations: 31 after adjustments Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

4.553714

1.442052

3.157801

0.0041

DU

2.669985

2.298586

1.161577

0.2564

T

0.122820

0.064359

1.908340

0.0679

DT

-1.354275

0.667566

-2.028675

0.0533

GDPFC(-1)

-1.036084

0.277771

-3.729988

0.0010

FD1

0.034174

0.196941

0.173525

0.8636

For Variable INV Table 15. Model- A Dependent Variable: D(INV) Method: Least Squares Date: 10/14/14 Time: 19:09 Sample (adjusted): 1983 2012 Included observations: 30 after adjustments Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

4.289932

2.939803

1.459259

0.1569

DU

0.549771

1.674290

0.328361

0.7454

T

0.205902

0.106480

1.933717

0.0645

INV(-1)

-0.270017

0.172323

-1.566923

0.1297

FD2

-0.128891

0.225729

-0.570998

0.5731

Table 16. Model-B Dependent Variable: D(INV) Method: Least Squares Date: 10/14/14 Time: 19:10 Sample (adjusted): 1983 2012 Included observations: 30 after adjustments Variable

86

Coefficient

Std. Error

t-Statistic

Prob.

C

3.081821

2.736676

1.126118

0.2708

T

0.189517

0.105429

1.797571

0.0843

DT

-0.192972

0.539013

-0.358010

0.7233

INV(-1)

-0.207519

0.162734

-1.275207

0.2140

FD2

-0.195582

0.210355

-0.929772

0.3614

Post Crisis Performance and Confidence of the Indian Economy

Table 17. Model-C Dependent Variable: D(INV) Method: Least Squares Date: 10/14/14 Time: 19:12 Sample (adjusted): 1983 2012 Included observations: 30 after adjustments Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

4.165143

2.940524

1.416463

0.1695

DU

2.762095

2.746804

1.005567

0.3247

T

0.204291

0.106425

1.919578

0.0669

DT

-0.898449

0.884651

-1.015597

0.3200

INV(-1)

-0.264550

0.172299

-1.535410

0.1378

FD2

-0.111789

0.226215

-0.494169

0.6257

For Variable GFD Table 18. Model- A Dependent Variable: D(GFD) Method: Least Squares Date: 10/14/14 Time: 19:17 Sample (adjusted): 1983 2012 Included observations: 30 after adjustments Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

5.302913

1.510007

3.511846

0.0017

DU

0.082149

0.847326

0.096951

0.9235

T

-0.026001

0.032452

-0.801213

0.4306

GFD(-1)

-0.627516

0.176990

-3.545490

0.0016

FD3

0.243106

0.191619

1.268696

0.2162

Table 19. Model-B Dependent Variable: D(GFD) Method: Least Squares Date: 10/14/14 Time: 19:19 Sample (adjusted): 1983 2012 Included observations: 30 after adjustments Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

5.311486

1.509666

3.518320

0.0017

T

-0.026134

0.030421

-0.859072

0.3985

DT

0.034455

0.277600

0.124117

0.9022

GFD(-1)

-0.628433

0.177330

-3.543853

0.0016

FD3

0.247788

0.182548

1.357387

0.1868

87

Post Crisis Performance and Confidence of the Indian Economy

Table 20. Model-C Dependent Variable: D(GFD) Method: Least Squares Date: 10/14/14 Time: 19:21 Sample (adjusted): 1983 2012 Included observations: 30 after adjustments Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

5.309257

1.542942

3.440995

0.0021

DU

-0.050668

1.859926

-0.027242

0.9785

T

-0.025814

0.033198

-0.777560

0.4444

DT

0.049153

0.609420

0.080656

0.9364

GFD(-1)

-0.628652

0.181163

-3.470086

0.0020

FD3

0.250868

0.217942

1.151080

0.2610

For Variable Forex Table 21. Model- A Dependent Variable: D(FOREX) Method: Least Squares Date: 10/14/14 Time: 19:28 Sample (adjusted): 1983 2013 Included observations: 31 after adjustments Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

-14023.53

12786.20

-1.096771

0.2828

DU

-59475.11

35546.11

-1.673182

0.1063

T

1605.478

1035.217

1.550862

0.1330

FOREX(-1)

0.112527

0.162165

0.693903

0.4939

FD4

-0.612936

0.333734

-1.836599

0.0777

Table 22. Model- B Dependent Variable: D(FOREX) Method: Least Squares Date: 10/14/14 Time: 19:31 Sample (adjusted): 1983 2013 Included observations: 31 after adjustments Variable

88

Coefficient

Std. Error

t-Statistic

Prob.

C

-16510.85

12827.63

-1.287131

0.2094

T

1959.279

1003.190

1.953049

0.0617

DT

-8868.362

6129.308

-1.446878

0.1599

FOREX(-1)

-0.020620

0.108496

-0.190054

0.8507

FD4

-0.319606

0.219350

-1.457059

0.1571

Post Crisis Performance and Confidence of the Indian Economy

Table 23. Model- C Dependent Variable: D(FOREX) Method: Least Squares Date: 10/14/14 Time: 19:32 Sample (adjusted): 1983 2013 Included observations: 31 after adjustments Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

-14568.54

13006.28

-1.120116

0.2733

DU

-44181.29

46077.39

-0.958850

0.3468

T

1654.565

1053.808

1.570082

0.1290

DT

-4181.364

7847.244

-0.532845

0.5988

FOREX(-1)

0.099892

0.166146

0.601233

0.5531

FD4

-0.575478

0.345651

-1.664911

0.1084

CAB Table 24. Model- A Dependent Variable: D(CAB) Method: Least Squares Date: 10/14/14 Time: 19:36 Sample (adjusted): 1983 2013 Included observations: 31 after adjustments Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

-1.192865

0.677241

-1.761362

0.0899

DU

-1.852563

1.011840

-1.830885

0.0786

T

0.035899

0.031914

1.124837

0.2709

CAB(-1)

-0.573738

0.211061

-2.718347

0.0115

FD5

0.137070

0.229875

0.596281

0.5561

Table 25. Model- B Dependent Variable: D(CAB) Method: Least Squares Date: 10/14/14 Time: 19:38 Sample (adjusted): 1983 2013 Included observations: 31 after adjustments Variable

Coefficient

Std. Error

t-Statistic

Prob.

C

-0.125666

0.790381

-0.158995

0.8749

T

-0.014268

0.034893

-0.408900

0.6860

DT

0.083403

0.353010

0.236264

0.8151

CAB(-1)

-0.229820

0.262805

-0.874488

0.3899

FD5

0.019242

0.265630

0.072438

0.9428

89

Post Crisis Performance and Confidence of the Indian Economy

Table 26. Model- C Dependent Variable: D(CAB) Method: Least Squares Date: 10/14/14 Time: 19:39 Sample (adjusted): 1983 2013 Included observations: 31 after adjustments Variable

90

Coefficient

Std. Error

t-Statistic

Prob.

C

-0.634493

0.757361

-0.837769

0.4101

DU

-2.812242

1.174276

-2.394872

0.0244

T

0.014393

0.034251

0.420210

0.6779

DT

0.583313

0.385991

1.511207

0.1433

CAB(-1)

-0.364644

0.248183

-1.469253

0.1542

FD5

-0.010084

0.244619

-0.041224

0.9674

91

Chapter 5

Market Fundamentals and Stock Pricing in Nigeria: Further Evidence from Micro and Macro Analysis Chukwuma Agu University of Nigeria, Nigeria Anthony Orji University of Nigeria, Nigeria

ABSTRACT This chapter investigates the relationship between stock pricing and behaviour of the stock market on one hand and micro and macroeconomic fundamentals in the Nigerian economy on the other from 19802009 using both primary and secondary data. Results from the primary survey indicate that the key drivers of share prices were neither broad macroeconomic indicators nor key indicators of the health of the firm. Prices were clearly shown to be much above levels that could have been determined by such indicators as posted profits of firms, amounts paid out as dividend and its regularity. Secondary data analysis equally show that the relationship between actual levels of the all share price index for the period of our analysis and during the financial crisis were not driven by “expected” variables. While its fundamental values are driven by monetary and relative price variables, actual values are driven by external sector variables and prices.

INTRODUCTION The role of financial markets in economic development has received considerable attention in the literature starting from Schumpeter’s work in 1911. There is no gainsaying the fact that without the capital market, the financial system

of any country will be grossly incomplete. The primary role of a capital market is the provision of medium to long term finance for development. Stock markets help to allocate and reallocate the ownership of the economy’s capital resources. In this way it plays an important role in distributing the economy’s wealth (Owolabi & Ajayi, 2013;

DOI: 10.4018/978-1-4666-8274-0.ch005

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Market Fundamentals and Stock Pricing in Nigeria

Ulici, 2012; Ndako, 2010; Agu & ChukwumaAgu (2010), Ajadi, 1984). According to Olarotimi (2008) absence of an effective and efficient capital market that mobilises and allocates the surplus funds to the deficit units of the economy could mean that such funds would remain idle and thus unproductive. However, in the past few years, developments in our national and global finance and economics have led to renewed interest in stock market outcomes. For example, when on March 10, 2000, the technology-heavy NASDAQ composite peaked at 5, 048.62, very few expected what was to follow the next couple of months. Even though such high movements were quite contrary to the trends in the rest of the US economy (particularly given that the Federal Reserve had raised interest rates six times over the same period and that the rest of the economy was already beginning to slow down), the fall still caught many analysts and stakeholders unprepared. The bubble burst that followed (generally known as the dot-com bubble crash) wiped out about $5 trillion in market value of technology companies between March 2000 and October 2002. Many other (non-technology) stocks followed in the wave of weak confidence in the market and lost values. A number of reasons have been given for that particular market crash, but as in many other times, such reasons often relate to market-specific occurrences and are weakly related to the overall question of what causes stock market crash and how these can be prevented. Consequently, the question of what causes a particular market crash remains a context-specific one that must be answered for all dips in the market. Investors sometimes, albeit temporarily, show excessive optimisms and pessimism which end in pulling stock prices away from their long term trend levels to extreme points. Just before a major burst, experience has shown, the market will always look so promising and attract some late comers who are also somewhat new and inexperienced in the business. Unfortunately, they are the most vulnerable in crisis times. However, even for the

92

more mature investors, there is evidence that following the market is a very demanding job and no one actually ever does a perfect job of correctly predicting its direction. In particular, the cause of bubbles remains a challenge to most analysts, particularly those who are convinced that asset prices ought not to deviate strongly from intrinsic values. While many explanations have been suggested, it has been recently shown that bubbles appear even without uncertainty, speculation, or bounded rationality. For instance, in their work, Froot and Obstfeld (1992) explained several puzzling aspects of the behavior of the United States stock prices by the presence of a specific type of bubble that they termed “intrinsic bubbles”. Bubbles are often identified only in retrospect, when a sudden drop in prices appears. Such drop is known as a crash or a bubble burst. To date, there is no widely accepted theory to explain the occurrence of bubbles or their bursts. Interestingly, bubbles occur even in highly predictable experimental markets, where uncertainty is eliminated and market participants should be able to calculate the intrinsic value of the assets simply by examining the expected stream of dividends. Clearly, the existence of stock market bubbles is at odds with the assumptions of Efficient Market Theory (EMT) which assumes rational investor behaviour. Often, when the phenomenon appears, pundits try to find a rationale. Literatures show that sometimes, people will dismiss concerns about overpriced markets by citing a new economy where the old stock valuation rules may no longer apply. This type of thinking helps to further propagate the bubble whereby everyone is investing. The growth in stock markets in the emerging economies has reflected the increased demand for such transactions and the lower costs of investing in international markets. According to International Finance Corporation (1999), from 1989-1998 the number of developing countries with actively trading stock markets increased from 31 to 78, the number of domestic companies listed on emerging market stock indices rose

 Market Fundamentals and Stock Pricing in Nigeria

over 300% from 8,709 to 26,354, and market capitalization in the emerging markets increased by 256% to US$1.91 trillion (Magnusson, Westjohn, & Zdravkovic, 2011). Also, in line with the argument above, Massa (2009), opined that stock markets in several African countries are at risk as a result of the global financial crisis, and the implications for economic growth are worrying. Market capitalization as a share of GDP– a better measure of the development of stock markets than changes in the share price index – has fallen more than 40% in some African economies. Also, Masseti (2013) argues that equity markets in Africa are said to lack size and liquidity because: First, Portfolio equity investment in Sub-Saharan Africa (SSA), which forms a very large chunk of Africa, is focused on the most active and liquid stock markets: South Africa, Nigeria, Kenya, Mauritius and Zimbabwe. The Johannesburg Stock Exchange (JSE) continues to dominate the region, representing 38% of all listed companies and 83% of total market capitalization in SSA in 2012. Second, 68 of Sub-Saharan Africa’s 100 largest companies in terms of market capitalization are listed on the JSE, including the 5 largest companies in Africa. Third, most of the major companies listed on the JSE are, however, large multinational companies that are listed on several stock exchanges world-wide. Apart from being the most advanced stock exchange in SSA, the JSE is also among the global top 20 of exchanges in terms of market capitalization and turnover. There are over 400 firms listed therein, with full electronic trading where clearing and settlement is operated. With a market capitalization of 159% of GDP in 2012, South Africa also has one of the largest equity markets relative to the size of its economy in the world. After South Africa, Nigeria has the second largest equity market in Sub-Saharan Africa. The Nigeria Stock Exchange accounted for 7.7% of total market capitalization in SSA in 2012. 15 Nigerian companies are among the 100 largest in SSA and two Nigerian firms already rank among the top 25.

The Nigeria Stock Exchange which has been the toast of investors for nearly a decade started a steep decline in early 2008 even before the rest of the world joined. Market capitalization which peaked at N12.6 trillion as at the first week of March, 2008 quickly nosedived beginning in the second week of March 2008 losing nearly half its value by the end of the same year. Every indicator in the stock market has continued to slide down. As in many other stock markets under the same circumstances, there have been competing arguments as to the cause of the crash. But many of these arguments are not underpinned by strong empirical analyses. Besides, despite its growth and strategic positioning in the African market, the Nigerian capital market has received comparatively little assessment. Consequently, it is not clear that policies for the market are driven by strong understanding of the links between the market and the rest of the economy or more specifically between the market and broad macroeconomic fundamentals as opposed to firm level and institutional variables and/or regulatory loopholes. This research work therefore sets out to systematically study the market with a view to understanding the different roles of market fundamentals and bubbles in the determination of stock pricing and market movements. The critical measure of market activity used in the study is the all share price index. In terms of the standard indicators for measuring the stock market (market capitalization, turnover, value and volume of traded shares, size (value) and number of primary market issues, new securities being listed on the exchange, among others), the Nigeria stock exchange has grown in leaps over the last two decades. The operational highlights, trends and performance of the Nigerian Stock Market from 1995-2011 are shown in table 1 below using the key indicators. The table above shows that there was significant growth in the various market indicators before the recent decline which was occasioned by global financial meltdown. From the table, value

93

 Market Fundamentals and Stock Pricing in Nigeria

Table 1. Major indices of the Nigerian stock market (1995-2011) Year

Volume Traded (Billion Shares)

Value Traded (N’Billion)

Market Capitaliza-tion (N’Billion)

The NSE All Share Index

New Issues (N’Million)

No of Listed Companies

Total Stock value traded / GDP

1995

0.397

1.838

171.1

5092.15

-

181

0.0

1996

0.882

7.06

285.6

6890.9

21.45

183

0.2

1997

1.3

11.07

282.0

6400.4

9.11

182

0.4

1998

2.1

13.57

263.3

5690.96

17.28

186

0.5

1999

3.95

14.08

300.06

5179.17

44.44

196

0.4

2000

5.0

28.15

472.9

8111.01

35.5

195

0.6

2001

5.9

57.6

662.6

10963.43

44.17

194

1.0

2002

6.6

60.3

763.9

12137.72

67.32

195

0.8

2003

13.3

120.7

1350

20128.94

164.84

200

1.7

2004

19.21

225.82

2112

23844.45

235.53

207

1.9

2005

26.7

262.94

2900

24085.76

730.54

214

1.7

2006

36.7

470.25

4227.1

33189.30

690

202

2.4

2007

138.1

2100

10180.3

57990.22

650

212

10.1

2008

193.1

2400

6957.5

31450.78

-

213

9.6

2009

33.32

399.84

3332

20827.17

279.25

214

2.7

2010

50.88

610.56

5088

24770.52

244

215

2.3

2011

39.37

472.44

4066

27770.52

-

216

1.7

Source: Nigerian Stock Exchange (NSE), Annual Reports (various issues)

of shares traded increased from NGN1.8 billion (US$13.85 million) in year 1995 to NGN28.2 billion (US $ 0.22 billion) in 2000 and shooting up to NGN2.4 trillion (US $ 18.5 billion) in 2008. However, there was a decline to NGN 399 Billion as a result of the crisis in 2009 and subsequent fluctuation between 2010 and 2011. The volume of shares traded during the same period also increased from 0.397 billion units in 1995 to 5 billion units in 2000 and on to 193.1, 33.32, 50.88, and 39.37 billion units in year 2008, 2009, 2010 and 2011 respectively. This shows a growth rate of 3.76 percent between 2000 and 2008, with serious decline and fluctuation in the growth rate between 2009 and 2011. Market capitalization also increased from NGN171.1 billion (US $ 1.3 billion) in 1995 to NGN472.9 billion (US $ 3.64

94

billion) in 2000 and reached a peak of NGN10.18 trillion (US $ 78.3 billion) in 2007.The years 20082011 witnessed some declines and fluctuations in market capitalization, as shown by the table above. New issues and total stock value traded generally reflect the size of funds mobilized by the stock market in relation to GDP. Both the absolute number of new issues and the ratio of total stock value traded to GDP have fluctuated significantly over the period peaking at approximately NGN 700b and 10.1 percent of GDP respectively around 2005 and 2007 respectively. The years 2008-2011 showed some level of decline in both indicators as a result of the financial crisis. A critical examination of the statistics regarding Africa’s equity market and Nigeria’s capital market, thus, shows that, even though there has

 Market Fundamentals and Stock Pricing in Nigeria

been a significantly positive change in these markets within the last two decades, much is still left to be desired. Akuoma (2014) posits that within the last five years, so many European investors have found Africa very attractive and conducive for investment and, hence, have channelled a lot of funds in form of Foreign Direct Investment. However, one could still argue that the financial crisis and the sensitivity of the capital market to external shock resulting from the global financial meltdown have affected the performance of the macroeconomic fundamentals in the economy. Hence, there is a need to understand the different roles of market fundamentals and bubbles in the determination of stock pricing and market movements in Nigeria. The primary objective of the paper is to provide empirical evidence on the causes of the stock market crisis in Nigeria. In doing so, it tries to find out whether movements in stock prices over the last couple of years (particularly since from 2004) follows fundamentals in the economy or merely reflect speculative (and other) bubbles. It aims to add to the body of knowledge on the Nigerian stock market (which presently is relatively small) and point the way for more enquiries into the subject for future studies. The rest of the paper is organized as follows: section II reviews some works in related areas and provides basis for this study; section III outlines the methodology; section IV discusses the findings while section V concludes.

REVIEW OF RELATED LITERATURE Theoretical and Empirical studies on the relevance of the capital market to the development of any economy abound in the literature. The capital market is actually created to make provisions for easy access to long-term funds which are used for developmental and other purposes. In fact, for a nation to develop there is a dire need for that nation to have a functional and efficient capital market,

of which, the stock exchange is the hub (Nneji 2013; Ozurumba & Chigbu; 2013). There are various ways in which stock market and the macro economy have been related in the literature. One way of considering the effect of macroeconomic events on the stock prices is through the assetpricing perspective in which Arbitrage Pricing Theory (APT) developed by Ross (1976) was used as a framework to address the question of whether risk associated with particular macro variables is reflected in the expected stock returns. A closelyrelated analysis is the one based on the Capital Asset Pricing Model (CAPM) which concentrates on a single macro influence, the growth of aggregate consumption (Breeden, 1979). An alternative to this direction of influence from the economy to the stock market is to analyze the effects of stock prices on the macro economy or selected macroeconomic variables. A relationship of this nature is between stock prices and investment (in the case of capital formation). Studies of this type start with the Tobin’s q-theory of investment (Tobin, 1969). The question usually addressed by this strand of literature is whether firms, in making investment decisions, should pay any heed to stock prices or whether stock prices are simply a veil over the real part of the economy and should be dispensed with when making decisions about real variables such as investment. Theoretically, stock market performance is usually analyzed within the Efficient Market Hypothesis (EMH) attributed to Fama (1970) and used in Nwosu, Orji and Anagwu (2013). An efficient market under the concept is one in which security prices adjust rapidly to the arrival of new information and therefore, the current prices of securities reflect all relevant information about the security. In extreme case of an efficient market, it is argued that stock prices should reflect expectations about future corporate performance. Corporate profits on the other hand generally may reflect the level of country’s economic activities. Thus, if stock prices accurately reflect the underlying fundamentals, then the stock prices should be

95

 Market Fundamentals and Stock Pricing in Nigeria

employed as leading indicators of future economic activity. However, economic activities could lead instead of lag stock prices, in which case opposite results might obtain. Unfortunately though, the question of the dynamic causal relationships between macroeconomic factors and stock prices remain largely unresolved in the literature. To examine the behavior of the stock market, one must first distinguish between what drives market valuation levels (such as market-valueto-capital ratios) and what drives total return to shareholders (TRS), which are primarily the market fundamentals (Koller, Goedhart, Wessels, Thomas, Copeland, McKinsey & Company, 2005). According to the Koller team, market valuation levels are determined by the company’s absolute level of long-term performance and growth, that is, expected revenue and earnings growth and return on invested capital (ROIC). TRS is measured by changes in the market valuation of a company over some specific time period and is driven by changes in investor expectations for long-term future returns on capital and growth. Their work showed that the relative market value of a company as measured by the market-value-to-capital ratio is determined by the company’s growth and its spread of ROIC over the weighted average cost of capital (WACC). These discussions are generally captured under three approaches to stock valuation given as Fundamental, Technical and Efficient Market Approaches (Okafor, 1983). Two major theories dominate thinking on investor behaviour. These are the bandwagon theory and contrary opinion hypothesis. While the former asserts that errors of judgement in stock market transactions will be minimised by an investor who follows the lead market-makers, the latter is based on the assumption that small investors are usually wrong. Okafor (1983) asserts that “market-leads” which originate from odd-lot pressures are more likely to mislead than help the investor. There is an argument that in a discrete-time-finite horizon setting, stock prices cannot deviate from fundamentals unless traders are irrational or myopic.

96

However, Allen and Gorton (1993) differed. They based their study on the assumption that investors hire portfolio managers to invest their wealth for them; the agency problem that arises between investors and managers because of asymmetric information between them means that asset prices can deviate from their fundamentals and bubbles can exist. Koller, et al. (2005) assert that significant deviations from intrinsic value are rare, and markets revert to the economic fundamentals rapidly enough that managers should continue to base their decisions on such fundamental Discounted Cash Flow (DCF) analyses. But they also discovered three key conditions for market deviations from economic fundamentals which include irrational investor behavior, systematic patterns of behavior across different investors, and limits to arbitrage in financial markets the latter occurring where there are no barriers to arbitrage leading to the exploitation of systematic patterns of irrational behavior When these conditions all apply, behavioral finance predicts that pricing biases in financial markets can be both significant and persistent. But besides the behaviors of micro private agents in the market, the broad macroeconomic conditions under which a market operates is definitely expected to impact on trends in that market. A number of key macroeconomic fundamentals like overall economic growth, inflation rates, exchange rates, monetary policy and interest rates, government fiscal policy, public indebtedness, taxation policies among others have significant influence on stock movements. Analysts and investors closely watch these variables and they impact on the pricing decisions of stocks. In this section, we review some of the issues in the relationship between such macroeconomic fundamentals and the stock market. Several works have examined the relationship between stock market and economic growth and there are evidences that stock markets can give a boost to economic development and vice versa. The fact that capital, as generated from the stock

 Market Fundamentals and Stock Pricing in Nigeria

market is needed for economic growth is not disputable (Soyode, 1990; Alajekwu, Ezeabasili & Nzotta,, 2013; Ndako, 2010). The stock market is widely described as a leading indicator of any nation’s economic direction. More generally, stock markets are seen as enhancing the operations of the domestic financial system in general and the capital market in particular (Kenny & Moss, 1998). When a nation’s economy is doing well, its stock market usually mirrors this economic growth. An active stock market may be relied upon to measure changes in the general economic activities using the stock market index (Obadan, 1998). Savings mobilization and liquidity creation, foreign inflows, and risk diversification, are some of the contributions of stock markets to economic growth. In principle, the stock market is expected to accelerate economic growth by providing a boost to domestic savings and increasing the quantity and the quality of investment (Singh, 1997). To achieve this, the stock market provides investors with facilities that may better meet their liquidity needs and risk preferences. Better savings mobilization may increase the savings rate (Levine & Zervos, 1998). Stock markets also provide an avenue for growing companies to raise capital at lower cost. In addition, companies in countries with developed stock markets are less dependent on bank financing, which can reduce the risk of a credit crunch. Stock markets therefore are able to positively influence economic growth through encouraging savings amongst individuals and providing avenues for firm financing. Costs of information are also reduced in an efficient stock market. Reducing the costs of acquiring information is expected to facilitate and improve the acquisition of information about investment opportunities and thereby improves resource allocation. Stock prices determined in exchanges and other publicly available information may help investor make better investment decisions

and thereby ensure better allocation of funds among corporations and as a result a higher rate of economic growth. Empirical research into the relationship between firm fundamentals, macroeconomic indicators and stock pricing is a long one and several works have made significant inroads into trying to understand these links. Tripathi (2008) examined the relationship between four company fundamental variables (viz. market capitalization, book equity to market equity ratio, price earnings ratio and debt equity ratio) and equity returns in the Indian stock market using monthly price data of a sample of 455 companies forming part of S&P CNX 500 Index over the period June 1997 to June 2007. The results was that market capitalization and price earnings ratio have statistically significant negative relationship with equity returns while book equity to market equity ratio and debt equity ratio have statistically significant positive relationship with equity returns in India. A number of other studies have also worked on other macro indicators with mixed findings. For example, Das (2005) shows there are evidence that stock prices and interest rates possess a common trend in many of the countries he studied with the exception of India. However, there is strong evidence of common cycles for the other countries. These findings provide support to the view that although bond markets and stock markets in these countries are linked, this may not be through a common trend, but through a common cyclical pattern. From the policy point of view, being linked through a common cyclical pattern provides the advantage of better forecasting or decomposition of stock price change affected by bank interest rate change. Haastrecht and Pelsser (2009) analyze the pricing of stock, foreign exchange and inflation options under stochastic interest rates and volatility. They considered a generic foreign exchange framework for the pricing of foreign exchange (FX), inflation and stock options. Moreover

97

 Market Fundamentals and Stock Pricing in Nigeria

they allowed for a general correlation structure between the drivers of the volatility, the inflation index, the domestic (nominal) and the foreign (real) rates. Having the flexibility to correlate the underlying FX/Inflation/Stock index with both stochastic volatility and stochastic interest rates yields a realistic model, which is of practical importance for the pricing and hedging of options with a long-term exposure. They derive explicit option pricing formulas for various securities, like vanilla call/put options, forward starting options, inflation-indexed swaps and inflation caps/floors. Finally, they test the numerical quality of this approximation and consider a calibration example to FX market data. Some interesting works in this area has also been done among developing countries. Mookerjee and Yu (1997) investigate the effect of macroeconomic variable on Singapore stock market. Results suggest that stock prices are cointegrated with both measures of the money supply (M1 and M2) and aggregate foreign exchange reserves. However stock prices and exchange rates do not have a long-term relationship. This was followed by the work by Know and Shin (1999) who examine the role of macroeconomic variables in estimating Korean stock prices. They find that stock indices seem to be cointegrated with the combination of the four macroeconomic variables namely trade balance, foreign exchange rate, industrial production and money supply. Ibrahim and Aziz (2003) investigate the relationship between stock prices and industrial production, money supply, consumer price index, and exchange rate in Malayasia. Stock prices are found to share positive long term relationships with industrial production and CPI. On the contrary, stock prices have a negative association with money supply and exchange rate. Serkan (2008) investigates the role of macroeconomic factors in explaining Turkish stock returns, employing macroeconomic factor model from the period of July 1997 to June 2005. He found that exchange rate, interest rate and world

98

market return seem to affect all of the portfolio returns, while inflation rate is significant for only three of the twelve portfolios. Also, industrial production, money supply and oil prices do not appear to have significant effect on stock returns in Turkey. Adam and Tweneboah (2008) examine the impact of macroeconomic variables on stock prices in Ghana using quarterly data from 1991 to 2007, looking at both long-run and short-run dynamic relationships and using Vector Error Correction Model (VECM). They found the existence of co-integration indicating long run relationship between stock prices and major macro variables. From these reviewed works, it is obvious that there is some relationship between the stock market and both firm-level and macroeconomic fundamentals. There is need therefore for some empirical estimates in this respect in order to see how various indicators in the economy contribute its growth or to the shock, and analyze their implication for national policy formulation.

METHODOLOGY Following Agu and Chukwuma-Agu (2010) this work employs both econometric analysis of both time series and survey data. The methodology is therefore a mix of primary and secondary data. A survey instrument which aims at eliciting information on the causes and impacts of the fall in key market indices was designed and administered on a select number of market operators, regulators, employees of quoted firms, investors and other stakeholders. For the secondary data, the publications of the Nigeria Stock Exchange, the Central Bank of Nigeria and other major institutions in the country will be used. For the time series estimation, using quarterly data from 1990-2007, a single equation regression model of the relationship between the all-share price index and related macro and micro indicators is specified and estimated.

 Market Fundamentals and Stock Pricing in Nigeria

SURVEY DATA ANALYSIS Analytical Techniques for the Survey Data A questionnaire has been designed and information elicited from stakeholders, particularly those working in stock-broking houses, the Nigerian stock exchange, investors, managers of quoted firms and other stakeholders. Most of the variables in the time series model are broad macroeconomic indicators. However, there are microeconomic issues relating to regulation and management of firms in the stock market that would doubtless have been important in affecting the recent trends in the market. The time series analysis is not able to fully capture these micro concerns. To therefore have a fuller picture, this study develops a survey instrument (structured questionnaire) to elicit the relevant information from stakeholders in the stock exchange. Responses obtained from the instrument are separately analyzed and the results compared to the ones obtained from the time series analysis to give a fuller picture of the factors affecting the stock exchange. To effectively capture causality, a dichotomous binary estimator shall be used. Four variants of such dichotomous binary estimators generally come in handy in modelling vector qualitative variables – the Linear Probability Model [LPM], the Logit model, the Probit (Normit) model and the Tobit model. Among all four, the Logit model is known to be superior to the other three as an analytical technique. The LPM has structural deficiencies while the Tobit and Probit models are computationally unattractive (Gujarati, 1995; Holly & Weale, 2000). Therefore, analysis in this work shall be limited to the use of the Logit model. The probability function of a causality for price movements under the Logit model by any of the factors listed by respondents (represented here with an omnibus term (Pr) could be obtained as:

P (Pr) = E (Pr = 1 / {Xi} = 1 / 1 + e

−(a 1′ )



Where p is probability of causality, Pr is the dependent variable (in this case price movement), E is expected value, Xi is a vector of explanatory variables and e is a binary operator. To ease interpretation and ensure consistency in the estimation, the original data obtained via likert scale responses will be converted to two groups of variables i.e. positive and negative. For responses where there are two sets of possible responses, they will be grouped as related. For example ‘strong’ and ‘very strong’ will be grouped as positive with a value of 1 while ‘weak’ and ‘very weak’ will be grouped as negative with a value of 0 and classified as not being strong enough to merit policy attention. A linear regression will then be used to estimate the relative impact of the different variables on stock prices (Agu & Chukwuma-Agu, 2010).

The Time Series Model: Specification and Analytical Techniques Again following Agu and Chukwuma-Agu (2010) a time series analysis of the determinants of stock prices employing selected macroeconomic fundamentals like exchange rate, interest rate, non-oil output growth, money supply, etc is specified and estimated. Activities in the Nigerian stock exchange shall be proxied by the all-share price index (ASPI). The choice of the all-share price index as a proxy is based on two major considerations. First, it is a ratio and is therefore already in standard measurement that needs no further conversion. Secondly, more than any other variable, it has the capacity of capturing trends in all stock prices simultaneously. Given that each price movement that reflects in the ASPI is in ratio of the original price, the ASPI equally gives a weighted average of the prices and of other economic activities relating to trading in the market.

99

 Market Fundamentals and Stock Pricing in Nigeria

The relationship between output and stock market indices is well documented in the literature, both theoretical and empirical. This relationship is obviously bidirectional. For example, growth translates to increased savings which makes resources available for investment in the stock market. It also leads to economic diversification and therefore a deepening of the stock market. However, stock market deepening leads to more efficient resource mobilization which in turn makes available long term funds for increased investment and growth. The relationship is therefore proposed to be positive. Interest rate is the principal return on capital. In capital investment, there are short run (money market) and long run (capital market) options. These options imply potential trade off in the decisions to invest in either of the two. In Nigeria, high, assured interest rates on money market instruments have often meant less attention to the more unstable returns from investment in the capital market. Therefore increases in rewards to money market investment may reduce investment in the stock market and therefore depress the share price index. However, given that both are prices; there is the possibility of co-trending as well between stock prices and interest rates. Therefore, the relationship between interest rates and stock prices shall be assumed to either be positive or negative in this model. Nigeria operates a fairly open capital account. Over the period 2004 through 2007, the consolidation of the banking sector came with a surge in public offers. It is believed in many quarters that a substantial part of the investments in these public offers came from remittances and portfolio flows from abroad. This proposition is yet to be empirically tested. However, it signals the possible impact of the external sector on the movements in stock prices over the period. As such, it will be helpful to bring in selected indicators of the external sector. The impact of remittances will therefore be tested here. Generally, higher remittances should lead to increases in the all-share price index as demand exceeds supply in the stock exchange. 100

In the light of the above discussion, the final model can be functionally represented as follows: ASPI = f (MLR, M 2, GEXP, CPS, RER, NOS, YN , TBR, REM ) where: ASPI: Is the all share price index. MLR: Is maximum lending rate. M2: Is money supply. GEXP: Is government expenditure. CPS: Is credit to the private sector. RER: Is real exchange rate. NOS: Is number of listed securities. YN: Is non-oil output. TBR: Is treasury bills rate. REM: Is remittances. Mathematically, the model is given as: ASPI = C + αMLR ± βM 2 ± χGEXP + δCPS + ηRER + γNOS + ςYN + ψTBR + ξREM + µ All variables are as earlier defined; α, β, χ, δ, η, γ, ς, ψ, ξ are coefficients while µ is a randomly distributed error term. The study shall use an error correction model to evaluate the nature and size of the long run relationship between the all-share price index and the selected fundamentals. The introduction of the error correction factor (ECF) is expected to show the rate of adjustment back to equilibrium given a shock to the relationship among the variables. ASPI = C + αMLR ± βM 2 ± χGEXP + δCPS + ηRER + γNOS + ςYN + ψTBR + ξREM − ECF + µ

 Market Fundamentals and Stock Pricing in Nigeria

All variables are as earlier defined. ECF is the error correction factor. The result from this second model will be compared with the one specified above. This will help in making judgments about the relationship between the market and the rest of the economy and in determining what really drives prices and therefore the fall in prices in the market. Equilibrium levels of the fundamentals shall be determined using Williamson (1994) exante methodology which uses a single equation to decompose times series data into permanent and transitory components (Agu & ChukwumaAgu, 2010).

FINDINGS Findings from Primary Survey A censored logit model was used to analyze the responses from the field. However, given that there was no independent question asked on stock pricing in the questionnaire, the dependent variable had to be slightly adjusted and availability of safeguards in the system, on which responses largely mirrored the reality of stock price fall was used. For this first equation, dependent variables were deliberately chosen to include only the critical firm level and stock market regulatory factors. These include existence or otherwise of price setting behaviour, extent to which such price setting affected the market, management standards and practices, size of posted profits of the firms,, regularity of dividend payment and amounts paid out as dividend, balance sheet of the quoted companies and extent to which regulation capacity of both the Nigeria Stock Exchange and the Securities and Exchange Commission meet minimum standards. As shown in Table 2, four factors more than others were critically associated with the view on lack of safeguards in the market. These include price setting behaviour of firms, poor management standards and practices in the quoted firms, irregularity of dividend payment

and weakness in the regulatory capacity of both the Nigeria Stock Exchange and Securities and Exchange Commission. Other factors like amount shared as dividend, posted profits and balance sheet of the firms were less important, again confirming the trends observed in the statistical analyses. A similar regression on macroeconomic indicators (not displayed here) identifies macroeconomic instability, policies on margin facility, growth and the change in government as significant determinants. In effect, these latter macroeconomic variables provided the environment for specific regulatory weaknesses of key regulators (NSE and SEC) to be exploited by price setting tendencies and weak management standards of the quoted firms to provide overall weakness in the safeguard system and lead to market instability and general overvaluation of prices on the market which collapsed when it could bear no more. Interestingly, similar equations run on factors that could contribute to a rebound in the market seem to indicate little faith by stakeholders in the resolution of these micro challenges and direct market regulation issues within the short period in which they expect the market to at least moderately rebound. Two of such equations were again estimated, the first using predominantly the same micro variables used in the equation in table 2 and the second using predominantly macro variables, including growth, macroeconomic instability, and change in government. The factors identified by respondents in both equations as potential redemptive measures to be taken include more effective management of inflation and macroeconomic instability measures, effective policies on the use of margin facilities for stock purchase and upturn in the global economic condition. Changes in government once again showed up as not being of any importance one way or another. Stakeholders are obviously not concerned about the impact of government in power, probably indicating that they are not expecting any major shift in policies on account of the change. Economic growth is also not expected to have much impact (maybe

101

 Market Fundamentals and Stock Pricing in Nigeria

Table 2. A censored logit model of availability of safeguard in the market Dependent Variable: SAFGUAD Method: ML - Censored Logistic (Quadratic hill climbing) Sample: 1 71 Included observations: 55 Left censoring (value) at zero Convergence achieved after 5 iterations Covariance matrix computed using second derivatives Variable

Coefficient

Std. Error

z-Statistic

Prob.

PRICESET

-0.278458

0.154629

-1.800817

0.0717

PRICING

0.325267

0.105670

3.078152

0.0021

MGTSP

0.238693

0.076329

3.127153

0.0018

POSPRFIT

-0.055053

0.078129

-0.704649

0.4810

REGDIV

0.255620

0.077805

3.285374

0.0010

DIVAMT

0.082132

0.060035

1.368073

0.1713

BSHT

-0.027629

0.062402

-0.442763

0.6579

NSEREQ

0.188753

0.056225

3.357127

0.0008

8.593357

0.0000

Error Distribution SCALE:C(9)

0.193212

0.022484

Mean dependent var

1.890909

S.D. dependent var

0.314627

S.E. of regression

0.425980

Akaike info criterion

1.115112

Sum squared resid

8.528582

Schwarz criterion

1.443585

Log likelihood

-21.66559

Hannan-Quinn criter.

1.242135

Avg. log likelihood

-0.393920

Left censored obs

0

Right censored obs

0

Uncensored obs

55

Total obs

55

not much change in the growth rate is expected over the time horizon for which a rebound is possible by respondents either). Firm profitability, management, and improved regulation are also not expected very soon as to lead to market rebound. Nor do stakeholders expect that changes in broad credit policy and other governance indicators were going to make significant impacts in terms of leading to a turnaround in the market. where

POSPRFIT: Is the size of posted profits of the firms. REGDIV: Is regularity of dividend payment. DIVAMT: Is the amount paid out as dividend. BSHT: Is the balance sheet of the quoted companies. NSEREQ: Is extent to which regulation capacity of both the Nigeria Stock Exchange and the Securities and Exchange Commission meet minimum standards.

SAFGUAD: Is availability of safeguard in the market. This is the dependent variable. PRICESET: Is price setting behaviour. PRICING: Is the pricing of equities. MGTSP: Is management standards and practices.

Evidence from Secondary Data

102

Here, the relationship between stock pricing (proxied by the all share price index) and broad macroeconomic indicators is analysed to comple-

 Market Fundamentals and Stock Pricing in Nigeria

Table 3. Modeling fundamental and actual values of the all share price index Model

Actual ASPI

Fundamental ASPI

MLR

-1.95373 (-3.27)

M2

2.127017 (4.74)

GEXP

0.839622 (1.03)

CPS

0.242951 (1.85)

RER

1.498225 (2.48) -1.11737 (-1.84)

NOS

1.553487 (1.43)

9.148427 (1.86)

YN

1.04379 (1.28)

1.1270 (1.74)

TBR

-0.08642 (-1.14)

2.154 (2.74)

REM

0.173315 (2.06)

0.130422 (1.68)

ECF

-0.80 (-3.77)

-0.00088 (-4.21)

R2

0.314

0.607

DW

2.6

2.3

ment the views from the survey. Chosen indicators include interest rate which is expected to serve either of two purposes – indicate alternative investment opportunities in the money market as well as show access to funds from the money market which agents can invest to make short term gains in the capital market. Others are income, money supply, government expenditure, credit to the private sector, nominal exchange rate, number of listed securities, on-oil output, treasury bills rate and remittances. Two equations were estimated. The first equation uses a derived value of the all share price index obtained by estimating a single equation of the relationship of the index with broad macroeconomic fundamentals of the economy, indicated as ASPIGEN. The value of the all share price index that is consistent with the long term value of these determinants is taken as

its fundamental value. Deviations from this value were thereafter regarded as bubbles or irregular movements in the real value of the all share price index. Identified fundamentals include output, money supply, and interest rates. The fundamental value of the all share price index (ASPIGEN) were then ploughed back into an equation of a broader set of determinants and the results compared to a regular error correction function of the deflated all share price index using identified indicators. Factors that affect the “normal all share price index” but do not affected the fundamental all share price index are considered to have temporary impacts and so may not matter in the long run determination of ASPI. For both equations, the estimation technique is general-to-specific in order to capture economy-specific relevant factors that may ordinarily not appear in a theory-constrained model. The results are shown in Table 3. The results from the two are compared. Unit root and cointegration tests were conducted on both the derived and actual all share price indices. The unit root test results interestingly indicated that while the actual all share price index (in real terms) is stationary at order 2, the derived variable is stationary at order 1 indicating more stability in the real value of the derived (fundamental) value. Both sets of variables were cointegrated with the specified determinants. The estimation results for the equations are shown in the table 3 below. And here, we have very interesting results. The long-run, real value of the all-share price index (shown by the results of the ASPIGEN equation (row 2 in the table) are determined by almost a different set of variables from the actual values. For the long run values (ASPIGEN), key determinants include the lending rate, money supply and credit to the private sector. The real exchange rate and number of listed securities were marginally significant at 7 percent each. This implies that key determinants of the long run value of the all share price index are mainly absolute price and monetary variables with the

103

 Market Fundamentals and Stock Pricing in Nigeria

exception of the real exchange rate, which are a relative price and the number of listed securities. However, moving one step further and analyzing the factors that determine actual values of the dependent variable shows up such indicators as remittances and nominal exchange rate. Most of the variables identified in the long run equation disappear in significance with many of them not even able to enter the model at more than 20 percent probability. Credit to the private sector is the only variable that remained fairly significant, though not as important as remittances and nominal exchange rate. In effect, uncertain flows in remittances and changes in the nominal exchange rate have been part of the factors causing shifts of the market prices of stocks away from their fundamentals. Most of the other major variables in the economy are very weakly related to the ASPI. These findings fairly corroborate the view obtained from stakeholders in the survey about the weak relationship between stock pricing and macroeconomic fundamentals. Because however the micro variables could not be picked up in the macro estimate, it becomes difficult to directly compare the coefficients for the more micro factors. But at least the message from the macro factors seems to be fairly consistent.

SUMMARY OF FINDINGS AND POLICY IMPLICATIONS OF RESULTS This work has shown the relationship between stock pricing and behaviour of the stock market on one hand and micro and macroeconomic fundamentals in the Nigerian economy on the other. Primary data was analyzed using a censored logistic model while secondary data was modeled using an error correction approach. The long run value of the all share price index in the time series model was obtained using a single equation approach that relates the dependent variable to fundamental values of its core explanatory variables. two equations were thereafter estimated, the first showing

104

the relationship of this long run all share price index with major indicators in the economy and the second showing the relationship of the actual value of the all share price index with same set (or augmented values) of indicators. The results from both the primary and secondary analyses were fairly consistent and largely corroborate the other. Data from the primary survey largely indicate that the key drivers of share prices, particularly for the boom period were neither broad macroeconomic indicators (though such factors as inflation rate and macro instability are noted to affect it) nor key indicators of the health of the firm. Prices were clearly shown to be much above levels that could have been determined by such indicators as posted profits of firms, amounts paid out as dividend and regularity of such dividend payout. In contrast, stakeholders see price setting behaviour as dominant in the market and largely driving stock prices for the boom period. Such price setting behaviour seems to be strongly aided by weak regulatory capacity of key institutions in charge of the market. Reframed as censored logit equations, these same results obtained. Secondary data analysis equally showed that the relationship between actual levels of the all share price index for the period 1990 through 2007 were not driven by “expected” variables. While its fundamental values are driven by such monetary and relative price variables as the real exchange rate, money supply and credit to the private sector, its actual values are driven by nominal exchange rate, remittances and credit to the private sector. Such long term important variables as output did not seem to be significant in dictating trends in the market. These findings have profound implications for potential trends in the Nigerian Stock Exchange. First, being out of sync with the real sector does not portend good for the long term relationship between the market and growth of the other sectors. It seems that the same factors that have made the money market largely non-responsive and non-responsible to the real sector equally impact the capital market currently. Being driven by

 Market Fundamentals and Stock Pricing in Nigeria

financial indicators and players in the financial sector seems to show that regulation and policies to relate growth in these monetary sectors with the real sector are still weak where they exist. It portends even bleaker future for the already weak real sector over the short to medium term at least. But equally, the implications of stock prices not necessarily being driven by firm level fundamentals are not miniscule. That stock prices cannot be related to such basic indicators as profitability and dividend policy imply that sick firms can hide behind bloated stock prices to wreck havoc on corporate Nigeria. But more importantly, such trends remove the most important leverage available to genuine investors for evaluating alternative investments in quoted firms. Besides raising the stakes for genuine investors, it creates room for arbitrageurs and other rent-seekers to manipulate prices and reap bumper benefits that end up hurting all genuine participants in the market. It is interesting and in a way comforting that changes in government do not seem to affect the stock market. But this equally implies that government actions or inactions become nearly irrelevant in the stock market. This is a measure of insulation from activities in the rest of the economy that could be considered unhealthy. This might also be no more than an indicator that the market is not expecting much from the government of the day – a possibility that itself does not give much reason for cheer. A vital message that is clear from the work is that regulation of the market falls short of the ‘desirable’. Key regulators (particularly the Nigeria Stock Exchange and the Securities and Exchange Commission) were clearly depicted as lacking the capacity (or maybe the will) to effectively run the market. Such weaknesses, the sources of which could not be obtained in the course of the

survey, seem to be so obvious that key players in the market exploit them. They equally interact with macroeconomic instability factors and other regulatory loopholes to create room for market manipulation by key players. Obviously then, instituting additional measures to boost the capacity of the regulators to moderate activities will be an important step towards restoring confidence in the market. But it might equally be important to research further into what specifically may be wrong with the ‘safeguard mechanisms’ in the market and how such can be corrected. Whether it is money market or capital market, the overall aim of the financial sector is to provide funds for real sector growth. The financial sector in a country does not exist for its own sake. But it seems this is consistently the trend in both money and capital markets in Nigeria. Relationship of the capital market with such important indicators as output is so weak that both at the long run fundamental or short run actual determination, the impact of output on the stock market is nearly non-existent. One implication of this is that one grows without the other. Plainly, this is not healthy for long term growth as the real sector is likely to remain stunted for far longer than is warranted given the boom in the financial sectors. The situation is equally not the best even for investors in the stock market as the probability of market crashes continues to soar given increased differences between the performance of the real sector and the financial sector. When price increases are not supported by real activities, the market is driven by bubbles which ultimately will disappear. So it is incumbent on Nigeria’s monetary authorities and policy makers to constantly formulate and implement policies that will help sustain the stock market and make it remain internationally competitive.

105

 Market Fundamentals and Stock Pricing in Nigeria

REFERENCES Adam, A. M., & Tweneboah, G. (2008). Do Macroeconomic Variables Play any Role in the Stock Market Movement in Ghana? (MPRA Working Paper, No.9368). Agu, C., & Chukwuma-Agu, C. (2010). Shaky pillars: Are micro and macroeconomic fundamentals enough to explain the strength of the Nigeria Stock Exchange? International Research Journal of Finance and Economics, 40, 74–86. Akinnifesi, O.E. (1987). The role and performance of the capital market, Journal of Nigeria Institute of Social and Economic Research, Ibadan. Alajekwu, U. B., Ezeabasili, V. N., & Nzotta, S. M. (2013). Trade openness, stock market development and economic growth of Nigeria: Empirical evidence. Research Journal of Finance and Accounting, 4(3), 120–127. Allen, F., & Gorton, G. (1993). Churning bubbles. The Review of Economic Studies, 60(4), 813–836. doi:10.2307/2298101 Amadi, S. N., Oneyema, J. I., & Odubo, T. D. (2000). Macroeconomic variables and stock prices: A multivariate analysis. African Journal of Development Studies, 9(1), 478–496. Black, A., Fraser, P., & Groenewold, N. (2001). US Stock Prices and Macroeconomic Fundamentals. University of Aberdeen Working Paper. Chen, N. F., Roll, R., & Ross, S. (1986). Economic forces and the stock market. The Journal of Business, 59(3), 383–403. doi:10.1086/296344 Cochrane, J. H. (1994). Permanent and transitory components of gnp and stock prices. The Quarterly Journal of Economics, 107(2), 241–265. doi:10.2307/2118434

106

Das, A. (2005). Do stock prices and interest rates possess a common trend? Louvain Economic Review 71(4). Washington, D.C.: Public Policy Institute Georgetown University. Fama, E., & Schwert, G. (1977). Asset returns and inflation. Journal of Financial Economics, 5(2), 115–146. doi:10.1016/0304-405X(77)90014-9 Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417. doi:10.2307/2325486 Flannery, M., & Protopapadakis, A. A. (2002). Macroeconomic factors do increase aggregate stock returns. Review of Financial Studies, 15(3), 751–789. doi:10.1093/rfs/15.3.751 Froot, K., & Obstfeld, M. (1992). Intrinsic Bubbles: The Case of Stock Prices. (NBER Working Paper Series, w3091) Retrieved from http://ssrn. com/abstract=304858 Gonzalo, J., Lee, T., & Yang, W. (2007). Permanent and transitory components of GDP and stock prices: further analysis. Macroeconomics and Finance in Emerging Market Economies, 1(1), 155-120, Available at www.informaworld. com/smpp/content Ibrahim, M. H., & Aziz, H. (2003). Macroeconomic variables and the Malaysian equity market: A view through rolling subsamples. Journal of Economic Studies (Glasgow, Scotland), 30(1), 6–27. doi:10.1108/01443580310455241 Kenny, C., & Todd, D. M. (1998). Stock markets in Africa: Emerging lions or white elephants? World Development, 26(5), 829–843. doi:10.1016/ S0305-750X(98)00019-9 King, R. G., Plosser, C. I., Stock, J. H., & Watson, M. W. (1991). Stochastic trends and economic fluctuations. The American Economic Review, 81(4), 819–840.

 Market Fundamentals and Stock Pricing in Nigeria

Koller, T. Goedhart, M., Wessels, D., Thomas, E., & Copeland. 2005). Valuation: Measuring and Managing the Value of Companies, 4th edition. John Willey and Sons Inc. Kwon, C. S., & Shin, T. S. (1999). Cointegration vectors of economic variables and stock market returns. Global Finance Journal, 10(1), 71–81. doi:10.1016/S1044-0283(99)00006-X Levine, R., & Zervos, S. (1998). Stock markets, banks and economic growth. The American Economic Review, 88(3), 537–557. Magnusson, P., Westjohn, S. A., & Zdravkovic, S. (2011b). Further clarification on how perceived brand origin affects brand attitude: A reply to Samiee and Usunier. International Marketing Review, 28(5), 497–507. doi:10.1108/02651331111167615 Mookerjee, R., & Yu, Q. (1997). Macroeconomic variables and stock prices in a small open economy: The case of Singapore. Pacific-Basin Finance Journal, 5(3), 377–388. doi:10.1016/ S0927-538X(96)00029-7 Mukherjee, T. K., & Naka, A. (1995). Dynamic relations between macroeconomic variables and the japanese stock market: An application of a vector error correction model. Journal of Financial Research, 18(2), 223–237. doi:10.1111/j.1475-6803.1995.tb00563.x Ndako, U. B. (2010). Financial Development, Economic Growth and Stock Market Volatility: Evidence from Nigeria and South Africa. Unpublished Ph.D Thesis, Department Of Economics, University of Leicester. Nelson, C. R. (1976). Inflation and rates of return on common stocks. The Journal of Finance, 31(2), 471–483. doi:10.1111/j.1540-6261.1976. tb01900.x

Nneji, I. (2013). Efficiency of the Nigerian capital market; an empirical analysis. Research Journal of Finance and Accounting, 4(4), 69–77. Nwokoma, N. I. (2002). Stock market performance and macroeconomic indicators nexus in nigeria: An empirical investigation. The Journal of Economic and Social Studies, 44(2), 231–251. Nwosu, E., Orji, A., & Anagwu, O. (2013). African emerging equity markets re‐examined: Testing the weak form efficiency theory. African Development Review, 25(4), 485–498. doi:10.1111/14678268.12044 Obadan, M. I. (1998). Presidential Address presented on the “Capital Market and Nigeria’s Economic Development” at one day seminar organized by Nigeria Economic Society at the Institute of International Affairs, Lagos 21st January. Okafor, F. O. (1983). Investment Decisions: Evaluation of projects and securities. London: Cassell. Olarotimi, A. K. (2008). Exploiting the investment opportunities in the capital markets, ICAN student Journal, 12(3), 1-20. Ologunde, A.O., Elumilade, D.O. & Asaolu, T.O. (2006). Stock market capitalization and interest rate in Nigeria: a time series analysis, International Research Journal of Finance and Economics, Issue 4. Owolabi, A., & Ajayi, N. O. (2013). Econometrics analysis of impact of capital market on economic growth in Nigeria (1971-2010). Asian Economic and Financial Review, 3(1), 99–110. Ozurumba, B. A., & Chigbu, E. E. (2013). An Econometric analysis of capital market performance and economic growth of Nigeria. Interdisciplinary Journal of Contemporary Research in Business, 4(10), 165–176. Ross, S. A. (1976). The arbitrage theory of capital asset pricing. Journal of Economic Theory, 13(3), 341–360. doi:10.1016/0022-0531(76)90046-6

107

 Market Fundamentals and Stock Pricing in Nigeria

Sekan, Y. (2008). Macroeconomic variables, firm characteristics and stock returns: evidence from Turkey, International Research Journal of Finance and Economics, 16. Singh, A. (1997). Financial liberalization, stock markets, and economic development. The Economic Journal, 107(442), 771–782. doi:10.1111/j.1468-0297.1997.tb00042.x Soyode, A. (1990). The role of capital in economic development, Security Market Journal Nigeria, 6 Soyode, A. (1993). Structural adjustment programme and its impact on the Nigerian stock market. Research in Third World Accounting, 2, 335–352. Tobin, J. (1969). A general equilibrium approach to monetary theory. Journal of Money, Credit and Banking, 1(1), 15–29. doi:10.2307/1991374 Tripathi, V. (2008). Company fundamentals and Equity returns in India. 21st Australasian Finance and Banking Conference 2008 Paper Available at SSRN: http://ssrn.com/abstract=1247717 Ulici, M. (2012). Financial Liberalization and the Impact on Financial Market. Unpublished Ph.D Thesis Babes-Bolyai University, Faculty of Economics and Business Administration, Finance Department. van Haastrecht, A., & Pelsser, A. (2009). Generic pricing of FX, inflation and stock options under stochastic interest rates and stochastic volatility. Journal of Property Research, 17, 93–108.

ADDITIONAL READING Abugri, B. A. (2008). Empirical relationship between macroeconomic volatility and stock return: Evidence from Latin American markets. International Review of Financial Analysis, 17(2), 396–410. doi:10.1016/j.irfa.2006.09.002

108

Akbar, M., Ali, S., & Khan, M. F. (2012). The relationship of stock prices and macroeconomic variables revisited: Evidence from Karachi stock exchange. African Journal of Business Management, 6(4), 1315–1322. Asaolu, T. O., & Ogunmuyiwa, M. S. (2011). An Econometric Analysis of the Impact of Macroecomomic Variables on Stock Market Movement in Nigeria. Asian Journal of Business Management, 3(1), 72–78. Brooks, C. (2002). Introductory Econometrics for Finance (2nd ed.). Cambridge University Press. Gujarati, D. (2004). Basic Econometrics. Mc Grawhill. Izedonmi, P. F., & Abdullahi, I. B. (2011). The effects of macroeconomic factors on the nigerian stock returns: A sectoral approach. Global Journal of Management and Business Research, 11(7), 1–7. Kalra, R. (2012). Impact of Macroeconomic Variables on Indian Stock Market. The IUP Journal of Financial Risk Management, IX(1), 43-54. Pal, K., & Mittal, R. (2011). Impact of Macroeconomic Indicators on Indian Capital Markets. The Journal of Risk Finance, 12(2), 84–97. doi:10.1108/15265941111112811 Ray, P., & Vani, V. (2003). What moves Indian Stock Market: A study on a linkage with Real Economy in the post reform era (pp. 1-19). Working Paper, National Institute of Management, Kolkata. Zubair, A. (2013). Causal relationship between stock market index and exchange rate: Evidence from Nigeria. CBN Journal of Applied Statistics, 4(2), 87–109.

109

Chapter 6

Globalization, Consumer’s Preference, and Welfare in India: Results from CGE Model Koushik Das Chandias Mahavidyalaya, India

ABSTRACT The purpose of the present chapter is to analyse general equilibrium effects of different trade liberalization policies for India under imperfectly competitive market structure. Since present day world trade is much akin towards the increasing returns to scale and market structure oriented industry behaviour, we have considered monopolistically competitive market structure for our analysis. Computable General Equilibrium (CGE) modelling has been applied as it seems to be relevant methodology for policy simulation. Consumer’s love for variety and increasing returns to scale present in the sectors involving large fixed costs, are strong determinants of consumer’s as well as producer’s business confidence. Our study reveals that increased welfare gain due to trade and openness is not much larger as compared to standard perfect competition scenario as the scale economy benefit is predominant only in few sectors like capital goods industries and not prominently visible in large agricultural and informal manufacturing sectors.

INTRODUCTION The present chapter has been devoted to study the consequences of India’s foreign trade policy and expanding globalization under market imperfection and diverse consumer preferences. In the present day globalized scenario emergence of scale economy, diverse consumer preference and market structure oriented industry behaviour give rise to the rethinking of international trade especially in the direction of intra industry trade.

Firms with bigger capital stock usually reap scale economy benefit from producing greater volume of output and selling them in more than one country. Product differentiation, diverse consumer preference and returns to scale benefit reaped by the firms, eventually affect welfare of the consumers through offering them wide range of varieties and opportunities in reduced and competitive prices. On the other side, market structure oriented industry behaviour and competition among firms to retain market share, significantly affect business

DOI: 10.4018/978-1-4666-8274-0.ch006

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Globalization, Consumer’s Preference, and Welfare in India

confidence of the big multinational firms operating in the open economy globalized scenarios. As those firms generally reap sufficient scale economy benefits and invest in R&D for inventing new varieties, it is very much relevant to study the implication of expanding globalization on firm’s business confidence and welfare of the consumers. The purpose of the present chapter in this context is to comprehend general equilibrium implications of trade liberalization on India’s macroeconomic aspects under alternative market structures, giving emphasis on consumer’s preference for product variety and presence of increasing returns to scale. We applied Computable General Equilibrium (CGE) modelling as our relevant methodology following Shoven, J.B. and Whalley, J (1984). CGE based simulation models are commonly used for economic analysis while choosing right policy option among different alternatives. For example, to reduce budget deficit three different policy options are available to the policy maker: a) To increase direct tax b) To increase indirect tax c) Borrowing from the central bank and raise money supply. Now each policy option has its own pros and cons pertaining to macroeconomic effects. Simulation of each policy option provides the knowledge of macroeconomic and welfare effects associated with the execution of such policies. It helps the policy makers as they can choose the right policy option whose effects suits with their goals and objectives. Constructing a four sector Social Accounting Matrix (SAM) for India paper attempts to purport the effects of liberalized trade over different macroeconomic aspects under monopolistic competition and compared the results with the same obtained under benchmark perfect competition scenario. Three basic research questions will be emphasised through our simulation experiment, a) what are the macroeconomic and welfare effects of trade liberalization under diverse consumer preference? b) Effects of technological progress on social welfare and macroeconomic indicators under

110

imperfect competition and c) Impacts of foreign capital inflow on welfare and macroeconomic indicators under monopolistically competitive market structure. Our study reveals that trade under imperfect competition could not produce any greater domestic output, expansion of trade in terms of volume of export & import and gains from trade as compared to standard perfect competition scenario.

BACKGROUND This chapter delineates empirical implementation of a real trade general equilibrium model using computable general equilibrium methodology for a small open economy that includes some features related to “industrial organization” approach to trade. Theoretical study in this area has been developed rapidly by the works of Helpman (1981, 1982), Krugman (1979, 1980, 1981) and many others dealing with imperfect competition, economies of scale, entry barriers, product differentiation and few other aspects of industry structure while judging costs and benefits of trade liberalization. Very early works of Balassa (1966), Corden (1972, 1974), Eastman and Stykolt (1966), and Wonnacott (1967) studied the role of scale economies and its impact on international trade and structure of the industry. Balassa (1966) and Grubel and Loyed (1975) reported that much trade takes place on intra-industry basis which provides solid foundation for inter industry and intra-industry adjustment along with HecksherOhlin argument of comparative cost advantage. Argument from Industrial Organisation (IO) standpoint predicts that imposition of trade barriers restrict market size and foreign competition promoting too many home firms to operate in an industry exploiting too low scale of production (Krugman 1994, ch. 14). Conventional analysis under perfect competition and constant return to scale predicts the cost of protection to be very small in the order of 0.5 to 2% of the GDP. This

 Globalization, Consumer’s Preference, and Welfare in India

empirical result is confirmed by Boardway and Treddnick (1978), Brown and Whalley (1980), Deardorff and Stern (1981), Dixon (1981), Williams (1976) etc. based on the assumption of perfect competition. Contrary to that analysis Balassa (1966) and Wonnacott (1975) reported much higher gains from trade liberalization, obtained under the presence of scale economies and market imperfection than under conventional perfect competition based analysis. Trade theory and industrial policies are such kind of economic policy which highly depends on general equilibrium structure of the economy. While conventional trade theory highly depends upon Heckswer/Ohlin framework, I/O approach is highly predominant towards partial equilibrium framework. Theoretical works of Brander (1981), Helpman (1981), Krugman (1980) and Lancaster (1980) have been most important in this direction. Dealing with I/O approach to trade with empirical general equilibrium framework is likely to provide insightful implications. Important thing in the general equilibrium set up of the open economy trade structure including I/O features is the assumption of inter sectoral circular flows of commodities and basic factor services which is supposed to capture additional source of comparative cost advantage due to the presence of scale economy benefit along with other conventional sources like geographical factor endowment difference and technology difference. Haris and Cox (1984) first constructed an empirical general equilibrium model of small open economy that incorporates many I/O features, seems to be important for an industry in a real economy such as Semiconductor industry in U.S.A. and Japan (Baldwin & Krugman 1988). Their empirical general equilibrium model followed the methodology used by Shoven and Whalley (1983). Many such works in this direction established the fact that empirical results of a general equilibrium analysis incorporating I/O features differs significantly from the analysis that

does not incorporate I/O features1. Perfectly competitive structure assumed in many CGE models usually understates gains from trade originated from the reduction of trade barriers. Empirical study of Cox and Harris (1992), Brown and Stern (1989) have shown that incorporation of imperfectly competitive sectors within CGE framework leads to substantial increase of welfare gains for Canada from US-Canada free trade agreement. In Indian context, noteworthy works on CGE modelling, like Panda and Quizon (2001), Panda and Sarkar (1990), Parikh, Narayana, Panda and Ganesh (1997) did not consider market imperfection explicitly in their empirical general equilibrium analysis. Several strategic aspects like, economies of scale and scope, competition among firms, product differentiation due to consumer’s preference for varieties may give rise to different trade policy implications in a general equilibrium framework. In this paper our intention is to introduce market imperfection explicitly in a benchmark perfect competition model and study the consequent trade policy implications.

SOME THEORETICAL ASPECTS OF INTERNATIONAL TRADE AND MARKET STRUCTURE According to Krugman and Helpman (1984) there are four alternative approaches of modelling international trade in the presence of increasing returns: a) External effects b) Contestable market C) Cournot oligopoly and D) Monopolistic competition. Among the four different approaches we shall apply the last one to formulate our CGE trade model under increasing returns and diverse consumer preference .We find that this approach turns out to be very much useful for realistic modelling on its strategic simplification that allows us to avoid many complexities despite formulating a robust structure of the international economy under market imperfection. The key assumption

111

 Globalization, Consumer’s Preference, and Welfare in India

of this approach is that, there are a limited number of products each of which can be divided into many differentiated varieties.

THE GENERAL FORMULATION We may assume an economy with identifiable sectoral structure of commodities. Each of these commodities is a differentiated product in the sense that, large number of varieties of each product could be obtained in the market and also, a completely different set of varieties could be potentially produced to meet the demand for the consumers2. Since products can be differentiated in many dimensions, standard utility function cannot effectively represent such type of user’s preference. For this special type of preferences in relation to differentiated products, we may conceptualize a two level utility function from which a manageable demand curve can be generated. Our utility function is having following shapes: U = U u1 (⋅), u2 (⋅),.........., u 3 (⋅)  

(1)

Where the sub utility u1 (⋅) is derived from

the consumption of product i and .U (⋅) .is upper tier utility function that converts all sectoral sub utilities into an overall welfare level. We further assume is increasing and homothetic in its arguments. If a product ‘i’ is a homogenous product sub utilityU (⋅) dependsU (⋅) on quantity of the ith product being consumed Di . We also choose particular form of sub utility function in such casesU (⋅) ≡ Di . Whenever the product is a differentiated product we assume sub utility level depends upon quantity of each variety being consumed. Normally two alternative approaches are put forwarded for modelling consumer’s preferences in the context of differentiated products. A) Love

112

of variety approach and B) Ideal variety approach. In our present analysis we shall follow ‘love of variety’ approach as it is convenient to fit it with computable general equilibrium trade structure without affecting essential characteristics as done by Harris (1994), Horidge (1996) and many others.

Love of Variety Approach Preferences for differentiated products can be introduced by assuming commodities are being consumed by the individuals with different varieties. Following the works of Spence (1976), Dixit and Stiglitz (1977) individual preference for varieties can be modelled by specifying concave shaped and symmetrical sub utility functions for e a c h c o m m o d i t i e s i n t h e fo r m o f ui = u (Di 1, Di 2 ,.........) where D iω is the quantity of ith good being consumed with variety. There can be an infinite number of potential varieties which can be produced. But assuming certain amount of fixed costs present in the industry, only finite numbers of varieties are supplied to the consumers in equilibrium3.

The CES Sub Utility Function A workable form of sub utility function can be specified as symmetrical constant elasticity of substitution function which can be represented as follows: 1 βi

  U i = (Di 1, Di 2 ,.........) ≡ ∑ Diβωi   ω 



 1  βi ≡ 1 −  ,  σi  σi ≥ 1,

(2)

ω Equation-2 is a Dixit-Stiglitz type utility

functions where, σi is the elasticity of substitution between two varieties of the same product i. The

 Globalization, Consumer’s Preference, and Welfare in India

need of elasticity of substitution greater than one stems from the requirement that elasticity of demand is larger than one. If we have ni number of variety for the good i, then all varieties will be priced almost equally at pi . Demand function can be obtained following Dixit and Stiglitz (1977)4 as follows: pi ω i

∑p

ϖ ∈Ωi

1−σi iϖ

(6)

Subject to ∑ i ∈i pi Di ≤ E , where (3)

Here piω is the price of variety ω and Ωi is the set of all available varieties and Ei is the expenditure on ith product. Price elasticity of demand faced by the firm that produces variety ω can be represented by the following expression:5 1−σi

∑

U (D1, D2 ,...........DI )

Ei

ω ∈ Ωi

E p = σi +

Max

 1,D  2,...........DI  D

−σ

Di ω =

try to optimize the following welfare function which is constructed by the transformation of variables i.e. consumption demand and prices in each sector are adjusted by number of variety and elasticity of substitution between varieties8. Reformulated problem can be represented as follows:

pi ω

ω ∈Ω

1−σi iϖ

p

(1 − σ ) i

(4)

When all varieties of the ith product are equally priced second term of the expression becomes (1 − σi ) ni . This simplifies the expression for price elasticity as follows: 1 − σ  i  E P = σi +    ni 

(5)

Above expression shows that if we assume n is very large, almost close to infinity, the second term becomes zero and price elasticity of demand for the ith product becomes σi .

Welfare Function for S-D-S6 Preference Assuming all individuals are identical with same preferences and endowments, the utility function serves as the social welfare function7. Society will

σi (σi −1) Di = ni Di

is an index of consumption services derived from sector i. −1 (σi −1)

pi = pi ni



is the effective price of the product of sector i. Particular form of social welfare functions for two industry model can be represented by following Krugman (1981)9 as follows: 1β

 N1  W = ln ∑ D1β,ω    ω =1

0 < β < 1,

1β

 N2  + ln ∑ D2β,ω    ω =1

(7)

 1  βi ≡ 1 −   σi 

and σi > 1

Here Di,ω is the consumption level of the ω th product of industry i. (i=1, 2).N1, N2 are the numbers of potential products in each industry. Not all products will necessarily be produced, actually n1, n2 numbers of products will be pro-

113

 Globalization, Consumer’s Preference, and Welfare in India

duced domestically. The numbers which will fall short be imported from rest of the world.

STRUCTURE OF BENCHMARK CGE MODEL UNDER PERFECT COMPETITION

SOCIAL ACCOUNTING MATRIX

Our benchmark CGE model is based on Perfect Competition and constant returns to scale assumption both in commodity market and factor market. Model is based on following assumptions.

CGE models are traditionally based on SAM which is matrix representation of all transactions and transfers that takes place between different production activities, various factors of production and different institutions like households, corporate and government within the country and with respect to rest of the world in a particular financial year. SAM therefore defines a comprehensive framework that can depict full circular flow of income from production activities to factor service providers like households. Each row of a SAM represents total receipts of any account and column represents expenditure of that account. Therefore row total is supposed to be equal with corresponding column total. An entry in the ith row and jth column represents receipts of ith account from the jth account. A SAM is a database and extension over input/output matrix (I/O). Use of I/O matrix is widely accepted with the pioneering work of Wassily Leontief. I/O matrix however, does not represent interrelationship between factor value added and agent’s final expenditure. Extension of an I/O table with the introduction agent’s behaviour and institutional characteristics one can get essential features of a SAM. This can depict entire circular flow of income much more effectively. For the schematic structure of a SAM see Table-1 .Our environmental CGE model is based on schematic structure of SAM and for calibration of the model we constructed SAM for India for the year 2003-04 following Saluja and Yadav (2006)10 . Table 1. presents schematic structure of a standard SAM across different activities, factors, economic agents, etc.

114

Sectors and Agents Following SAM for India of the year 2004 produced by Saluja and Yadav (2006) we grouped all sectors of the economy into four aggregated sectors i.e. 1) Primary sector consists of all agricultural products, minerals, primary products such as iron ores, crude petroleum and agro process activities 2)Secondary sector is comprised mainly of all manufacturing activities like, cotton & textile, plastic, rubber and lather products, cement, different chemical products etc. 3) Infrastructural service consists infrastructural service activities like Water supply, Travel and Transport, Railway, Hotel and Restaurant and Construction. 4) Other service sectors like education, health care services, public administration, bank and insurance, postal services etc .We considered four types of agents in the economy i.e. a) Household b) Firm c) Government and d) Rest Of the World (ROW).There are four types of households i.e. i) RHH-1(Rural agricultural and other labourers) ii) RHH-2(Agricultural self employed and other households)iii) UHH-1(Urban salaried class) and iv) UHH-2(Urban casual labour and others).All other countries and regions are clubbed together into ROW.

Production and Factor Inputs We have considered two basic factors of production i.e. labour and capital that take part in the production process within which substitution is possible through Cobb-Dauglus production technology. Each production unit requires intermediate

Operating Surplus Income from entrepr.

Imports

Aggregate Supply

Household

PVT corp.

Pub. Ent.

Govt.

Ind. Tax

Capital A/C

ROW

Total

4

5

6

7

8

9

10

Total cost of production

Total factor endowments

Depreciation

Operating Profits

Value added

Factors

3

Taxes on intermediate

Endowment Of HH

Purchase of raw material

Commodities

2

Gross output

(3)

Activities

(2)

(1)

Factors

1

Commodities

Activities

Table 1. Schematic Structure of SAM

Total use of HH income

Household savings

Taxes on purchases

Income tax by households

Household consumption

(4)

Households

PVT CORP income

Corporate savings

Corporate taxes

(5)

PVT Corp.

Income of PSU

Public sector Savings

(6)

Pub.Ent

Aggregate govt. exp.

Govt. savings

Taxes on purchases

Interest on debt

Govt. transfer,

Govt. consumption

(7)

Govt.

Total ind. tax

Total indirect taxes

(8)

Ind. taxes

Aggregate investment

Taxes on investment

Gross Fixed Capital Formation

(9)

Capital A/C

Foreign Ex. Recpt.

Foreign savings

Tax on exports

Net capital transfer

Net current transfer

Net factor income

Exports

(10)

ROW

Foreign exchange payments

Gross savings of Economy

Total Indirect Taxes

Total govt. Earnings

Income of Public Departmental

Income of Private Corporate

Total Household income

Factor Income

Aggregate demand

Output

Total

 Globalization, Consumer’s Preference, and Welfare in India

115

 Globalization, Consumer’s Preference, and Welfare in India

inputs following fixed coefficient type Leontief technology.

Prices Product prices are determined from the equality of price and average cost. Average cost is comprised of basic factor cost, cost of intermediate inputs that includes cost of energy inputs. Increasing returns to scale is assumed through the presence of fixed cost in the production units.  β  Yj = bj ⋅ ∏ Fh , jj ,h   h 

(8)

X i, j = ax i, j ⋅ Z j

(9)

Yj = ay j ⋅ Z j

(10)

Fh , j = βh , j ⋅ py j ⋅Yj pfh pz j = ay j ⋅ py j + ∑ ax i, j ⋅ pqi +

(11)

FC j

i

(12)

Zj

where: Yj = Combined input used in jth activity. Fh , j = Demand for basic input h in jth activity. Z j = Output of j activity th

py j = Price of combined input in jth activity. pfh = Price of basic input h.

bj = Production function shift parameter. β j ,h = Share of hth input within combined input

in j activity. ax i, j = Per unit requirement of ith commodity in jth activity as intermediate input. ay j = Per unit requirement of combined input in jth activity. pqi = Price of the ith commodity. th

116

FC j = Fixed cost in the jth sector.

Government Income and Expenditure Source of income of the Government is a) Direct, indirect and corporate taxes b) Import tariff11 c) Income from entrepreneurial activity. In the expenditure front we assumed government’s expenditure in any sector is exogenously determined i.e. determined in the government’s budget and adjusted to benchmark SAM. Difference between government’s income and expenditure is government’s savings12. GINC = Td + Tdc + TInd + NCAT + ENT + TARR − Ts

(13)

 ∑ pf ⋅ FF ⋅ r + h h h ,b   Td = ∑ taudb ⋅  h  GTb + NCUTb  b  

(14)

Tdc = tcorp ⋅ (OPR + IND )

(15)

OPR =   sop ⋅  ∑ pfh ⋅ FFh + NF1 + NF2   h  

(16)

TInd = ∑ tauz j ⋅ pz j ⋅ Z j

(17)

TARR = ∑ taumi ⋅ pmi ⋅ M i

(18)

Ts = taus ⋅ ∑ pei ⋅ Ei

(19)

Xgi = mu ×GDP pqi

(20)

GTb = gtb ⋅ GINC

(21)

b

i

i

 Globalization, Consumer’s Preference, and Welfare in India

GEXP = ∑ Xgi + ∑ GTb + Ts

(22)

SG = GINC − GEXP

(23)

i

b

Where: GINC = Total Government income. Td = Household income tax. Tdc = Corporate tax.

TInd = Indirect tax FFh =Factor demand of the hth factor GTb = Government transfer to the bth household. gtb = Government income share transferred to b

th

household. Xgi = Government consumption of the ith good. rh ,b = hth factor income share of bth household. ENT = Income of the government from entrepreneurial activity. taudb = Share of total household income paid as income tax by bth household. mui = Share of government expenditure on ith commodity. NCAT = Net transfer to government. Sf = Foreign savings at world prices. Dep = Depreciation of capital. FFh = Total factor demand of the hth factor. tind = Indirect tax rate. taumi = Import tariff rate. taus = Export subsidy rate. NCUTb = Net current transfer to bth household. tcorp = Share of corporate income to tax. OPR = Operating profit. IND = Interest on debt. sop = Share of operating profit to total factor income. NF1 = Net labor income earned abroad. NF2 = Net capital income earned abroad. Tpurhh = bth household purchase tax. Tpurg = Government purchase tax. Ting = Taxes on intermediate. Tinv = Taxes on investment good.

Ts = Taxes on export. tpurhhb = Share of household purchase paid as

purchase tax by bth household. tpurg = Share of government purchase paid as purchase tax. ting = Share of intermediate good purchase to tax. tinv = Share of investment to tax. taus = Share of export paid as tax.

Household Income and Expenditure Households are rendering factor services in terms of labour and capital while in return they are receiving factor payments in the form of wages and rentals. We have considered four types of household, two of them are rural type and other two are urban type. Household spends his income for consumption purposes. We have assumed linier expenditure system type demand function for household.

Investment and Savings We considered Neo-classical type closure rule where investment is guided by saving. Total saving is composed of i) Household saving ii) Government saving iii) Corporate saving and iv) Foreign savings. Total saving is converted into total investment. Alternative closure rules are depicted in Table 4. Xvi =

  Dep + ∑ Spb + Sg + b lamdai ⋅   pqi Sc + Sf ⋅ epsilon   

(24)

Savings: HHIN b =  FF ⋅ pf + h  ⋅r + ∑ ∑ NFh + NF  hb h  h 1 2   NCUTb + GTb

(25)

117

 Globalization, Consumer’s Preference, and Welfare in India

HHIN b =  FF ⋅ pf + (25.a) h h    ∑ NF + NF  ⋅ rb + NCUTb + GTb 1 2   h

variety are combined together following a Constant Elasticity of Substitution type preference function.

Production of Output and Transformation

where rb = ∑ rh ,b h

Spb = sspb ⋅ HHIN b

(26)

Sc = ssc ⋅ (OPR + IND )

(27)

Household consumption: Xpi,b =

alphai,b ⋅ HHIN b − Tdb − Spb  pqi

(28)

Xpi,b = bth household consumption of the ith good.

Xvi = i commodity used as investment good. th

pqi = Price of the i commodity. pei = Price of export. th

Spb = Private savings of the bth household. Sg = Government savings. Sc = Corporate savings. epsilon = Exchange rate. HHIN b = Income of the bth household. FFh = Total factor demand of the hth factor. lamdai = Proportion of savings converted into investment.

Armington Function and Trade International trade in our model is guided by Armington function. Total availability of composite commodity in the domestic economy is composed of domestically produced variety of the good demanded by the domestic people and foreign variety of the same good. Both types of

118

Total supply of each domestic good produced using labour, capital and intermediate input is used up by export of that good and to meet up domestic demand of domestic variety. Both export and domestic demand of the produced good is combined together following CES type transformation function. International trade: pmi = epsilon ∗ pWmi ∗ (1 + taumi )

(29)

pei = epsilon ∗ pWei ∗ (1 + taus )

(30)

∑ pWe ∗ E + Sf + ∑ NCUT + NF + NF ∑ pWm ∗ M i

i

i

b

b

i

i

1

2

+ NCAT + Ts =



i

(31) Armington function: 1

deltam ⋅ M etaI + eta  i i Qi = gammai   eta deltadi ⋅ Di i  i

Mi Qi

(32)

= 1

  1−etai gamma etai ⋅ deltam ⋅ pqi  i i⋅  pmi  



(33)

1

 pq  1−etai eta = gammai i ⋅ deltadi ⋅ ⋅ i  . pdi  Qi  Di

(34)

 Globalization, Consumer’s Preference, and Welfare in India

Transformation function:

xiei = Share parameter of export in Transforma-

tion function.

Zi = 1

phi phi thetai ⋅ xiei ⋅ Ei i + xidi ⋅ Di i  phii  

Ei Zi

Zi

(35)



(36)

=

  theta phii ⋅ xie ⋅ (1 + tind ) pz i  i i  ⋅pei  

Di



1 1−phii

= 1

  1−phii theta phii ⋅ xid ⋅ (1 + tind ) ⋅ pz i  i i  pdi  



(37)

pei = Export price of good i. in domestic currency. pmi = Imports price of good i in domestic currency. pdi = Price of domestic good. pz i = Supply price of the ith good. pWei = World export price. pWmi = World import price. Ei = Export of good i. M i = Import of good i. epsilon = Exchange rate. Qi = Output composite good. Di = Output domestic good. gammai = Scale parameter in Armington function. deltadi = Share coefficient of domestic good in Armington function. deltami = Share coefficient of import good in Armington function. etai = Constant determining elasticity of substitution in Armington function. thetai = Scale parameter transformation function.

xidi = Share parameter of domestic good in trans-

formation function. phii = Constant determining elasticity of substitution in Transformation function.

Factor Prices and Equilibrium We consider two basic factors of production i.e. labour and capital. Total supply of basic factor is fixed in value terms and factor prices are flexible. Physical quantity of labour or capital may change in different simulation experiments following demand and supply equilibrium mechanism in the factor market. Demand for factor is originated from the production of goods and services.

Equilibrium in Commodity Market In the commodity market total supply of the composite commodity is constituted by domestic variety as well as imported foreign variety corresponds to each good. Demand for the composite commodity is generated from household consumption, government consumption expenditure, total investment demand and demand for intermediate input. Composite commodity price is determined from the demand and supply of composite commodity.

GDP and Welfare Under perfect competition GDP has been computed adding all sectoral outputs. Social welfare has been of Cobb-Douglas type and depends on private household consumption. Market clearing condition: Qi = ∑ Xpi,b + Xgi + Xvi + ∑ Xi, j b

(38)

j

119

 Globalization, Consumer’s Preference, and Welfare in India

FFh = ∑ Fh , j

(39)

j

Fictitious Objective function: UU = ∑ ∏ Xpi,bi ,b α

b

(40)

i

Inclusion of Fixed Costs

UU = Social welfare function. pz(j) = ay(j) py(j) × 



+

Basic Factor Cost

∑ ax(i,j) × pq(i) i  

(41)

+ FC(j)/Z(j)  ; Average Fixed Cost

Intermediate Input Cost

INCLUSION OF MARKET IMPERFECTIONS INTO CGE MODEL In our analysis we assumed presence of fixed cost in the production sector which gives rise to economics of scale at the firm level enabling the firms to have sufficient market power in respect of price setting. Firms may act cooperatively or non-cooperatively. In this point we have been restricted to non-cooperative behaviour of firms only as we followed Krugman and Helpman (1985)13 essentially. The outcome of non-cooperative behavior of firms in an industry depends on two factors: a) Strategic aspects of non-cooperation b) Condition of entry and exit in the industry. Most of the theoretical works on trade models incorporating oligopoly14 considered either output decision or price decision as strategic variables. In our analysis we followed Monopolistic Competition approach based on the assumption of Bertrand-type Competition where each firm takes rival’s price as given while taking decision over his own price. We also assume, firms are able to differentiate their products such that products are not perfect substitute for those products of existing competi-

120

tors as well as potential entrants. Here each firm is acting as monopolist facing downward sloping demand curve. Regarding entry we assumed no barriers to entry or free entry that drives profit to zero. This is known as Chamberlin’s “large group” case which is quite consistent with Bertrand model.

We modelled fixed cost as the part of total cost which is invariant to output. In actual practice it is not the ‘sunk’ cost but a recurrent expenditure must be incurred by the firms in each year to carry on production process. For example: maintenance cost of building & construction, machinery, various equipments15 etc. We further assume certain part of the total capital cost is fixed cost which is independent of output. Presence of fixed cost implies, higher output production reduces per unit capital cost. This gives sufficient market power to the existing farms. According to our assumption scale economy is external to the firms but internal to the industry16. Falling average fixed cost is depicted in Figure-1. From equation (41) it is evident that average total cost is the sum of a) Unit basic factor cost b) Unit intermediate input cost and c) average fixed cost. Unit basic factor cost includes both labour and capital cost while capital cost excludes fixed cost.

Inclusion of Consumer’s Preference for Varieties Welfare of the consumer can be treated as the proxy measure of Consumer’s confidence. Whenever any economic policy enhances welfare, it indicates that confidence of the consumer and businessmen have also increased. Consumer’s welfare is essentially related with consumer’s preference for variety in the sense that as the number of variety increases consumer’s welfare also enhances. Theoretically there are two important factors that could comprehensively represent consumers’ preference for different varieties. They are A) Elasticity of

 Globalization, Consumer’s Preference, and Welfare in India

Figure 1. Falling average fixed cost

substitution between varieties and B) Number of varieties. Their inclusion into our CGE framework is as follows.

Elasticity of substitution We considered an indirect measure of Elasticity of Substitution parameter in terms of price elasticity of demand faced by the firms. We borrowed our social welfare function from Krugman (1979) that takes price elasticities as different across industries as we find below: W= 1 1  N1 β β  N2 β β log ∑ D1 1  1 + log ∑ D2 2  2 +     i= 1

i= 1

1 1  N4 β β  N3 β β log ∑ D3 3  3 + log ∑ D4 4  4    i=1  i=1  1  βi ≡ 1 −   θi 

(42)

Here βi is elasticity of substitution parameter for ith industry. N i and Di are the number of variety and domestic consumption of the ith product. W is consumer’s welfare. Krugman (1979) also pointed out that social welfare function (2) has nice property that with large N each firm will face demand elasticity =

1 = θi . 1 − βi

When number of variety is large firms do not consider second term and so elasticity value becomes θi . When all varieties are equally priced second term becomes

(1 − θ ) i

Ni

.

As number of variety is large second term vanishes. In our analysis price elasticity of demand for ith commodity is EpHere

121

 Globalization, Consumer’s Preference, and Welfare in India

1 − θ  i E P = θi +   17 .  N i  Now Ep value can be computed from our model and setting N=1018, we can compute θi which determines elasticity of substitution parameter in each sector. From our model we calculated price elasticity of demand for a) Primary sector b) Secondary sector c) Infrastructure and d) Other service sec or as -0.35215, -.2642, -0.289,0.3107 respectively19.

DATABASE AND CALIBRATION The parameters of the constructed model are then estimated in conjunction with the benchmark dataset. In few instances, econometric estimates obtained from other sources have been applied for the purpose of parameter estimation. For example, number of varieties in the industry has been considered as 10 based on certain assumption. Remaining parameters are chosen, such that, they are consistent with the benchmark data. Here we have manipulated the equations of the model, so that parameters can be represented as the function of the data and solved the equations to obtain parameter values. This process is known as calibration, a deterministic procedure, in which we get point estimates of the parameters without having any standard errors. Calibrated CGE model will be solved to check whether it can reproduce a replica of the benchmark data. If benchmark Social Accounting Matrix (SAM) is not regenerated during solve of the model, we have to re-specify our model and re-estimate the parameters until the model generates a replica of the benchmark SAM. For the calibration of our model parameters we used SAM of India for the year 2003-04 with four sectors, two basic factors and four types of households20. SAM of India has been presented in Table 2 and Table 3. For the estimate of fixed cost; we assumed 10% of the capital employed in

122

the production process21 is invariant to output in each year. It indicates that, as output increases by 10%, average capital cost will fall by 1%. For the social welfare function under imperfect competition, we have two determinants. First one is the number of product variety in different sectors and second one is elasticity of substitution between varieties corresponding to different sectors. For the first one we assumed, benchmark number of variety is 1022. For the substitution elasticity, we consider the relationship with elasticity of demand and using sectoral price elasticity computed from our model we calculated elasticity of substitution between varieties23. We have solved the model using GAMS package for benchmark equilibrium. SAM is regenerated during the process of calibration. Calibrated values of the parameters are presented in Table 5. Figure 2 depicts flow chart of calibration process.

SIMULATION EXPERIMENTS After estimating the model parameters through benchmark equilibrium, we performed simulation experiments to obtain the impacts of policy change. We have changed the policy parameters appropriately and solved the model once again to obtain counterfactual equilibrium data values. We made three simulation experiments related to trade liberalization a) 50% reduction of import tariff b) Technological up gradation and c) Greater foreign capital inflow. In order to obtain the impacts of policy changes, counter factual equilibrium values are compared with benchmark equilibrium values of the macroeconomic variables. Experiment-1: Import liberalization in the presence of increasing returns to scale and “Consumers preference for variety.” We liberalized trade by 50% tariff reduction in the presence of increasing returns to scale in production sector and consumers preference for

 Globalization, Consumer’s Preference, and Welfare in India

Table 2. SAM of India for 2003-04(Rs. In Lakhs) Sectors

Primary sector

Secondary sector

Infrastructure

Other service

Labour

Capital

Primary sector

7813229

35487406

2764682

148968

0

0

Secondary sector

6791879

72102447

15722644

6844878

0

0

Infrastructure

3310796

25253708

6639444

3069054

0

0

0

0

32279505

12834674

Other service

771827

13603244

8167558

8196396

Labour

34310321

33292466

24461809

38969523

Capital

29878150

27090185

33397891

31081063

RHH1

0

0

0

0

RHH2

0

0

0

0

29243484

29319601

UHH1

0

0

0

0

61509848

16734549

UHH2

0

0

0

0

8661430

5406382

PVT

9557281

PSE

4626200

GOV

3618000

Indirect taxes

-1306585

9471626

3514423

1145516

Capital A/C

0

0

0

0

Rest of the world

12756258

28730550

3326565

4213424

variety in the demand side and compared the result with trade liberalization under perfect competition. We find import increases by 5.62% as opposed to 6.81% increase of import in case of perfect competition. Exchange rate depreciates by 1.748% as opposed to 1.9% in case of perfect competition. This led to reduced expansion of export by 4.94% as opposed to 5.9% in perfect competition. Reduced trade expansion is attributed due to the presence of ‘excess capacity’ in production that outweighs benefit from additional basis of comparative cost advantage namely “variety driven trade” apart from factor endowment difference and technology difference. GDP in this process increases by .097 as opposed to .296% in perfect competition case due to the presence of ‘excess capacity’ in production process that outweighs benefit from increasing return to scale. Sectoral output increases in secondary sector, infrastructure and service sector where benefits of market imperfection like, increasing returns to scale and horizontal product differentiation owing to comer’s preference for

25363700

product variety could have been reaped due to the presence of ‘excess unutilized capacity’ in those sectors . On the contrary, agricultural output could not be expanded due to capacity constraints like, inadequate supply of arable land, lack of technology adoption possibility etc. Composite commodity price has been reduced with lower percentage than under perfect competition. Sectoral changes of import remains similar while sectoral changes of export have been lower than that of under perfect competition. Number of product variety and consumer’s choice rises in all sectors except little reduction in infrastructural sector. Social welfare increases by 0.03% as compared to 0.146% in case of perfect competition. Even if consumers are gaining from increased product variety, there is some excess capacity loss in monopolistically competitive product market24. This causes welfare to increase by lesser percentage than in perfect competition case. Major interactions due to import liberalization are depicted in Figure 3.

123

 Globalization, Consumer’s Preference, and Welfare in India

Table 3. SAM of India for 2003-04(Continued) Activities

RHH1

RHH2

UHH1

UHH2

PVT.

PSE

GOV

Ind. Taxes

Primary sector

12294143

11910716

10703541

2211793

0

0

241670

0

Secondary Sector

12389764

15568374

14754899

818775

0

0

5157523

0

Infrastructure

5571019

5753069

6855314

1209437

0

0

1871435

Other service

13238946

17029747

25392996

5250963

0

0

24837174

Labour

0

0

0

Capital

0

0

0

RHH1

0

0

0

0

0

0

52075667

0

RHH2

0

0

0

0

0

0

9824402

0

UHH1

0

0

0

0

0

0

9113270

UHH2

0

0

0

0

0

0

1190924

Rest of the world

T otal

1803896

2978019

93480335

55622644

25376947

231376699

0

3260561

10605075

100069843

0

693607

4824222

106094471

0

-312600

130721521

0

-1095200

120352089

0

993035

53666294

0

2157927

80904465

0

0

6175802

93533470

0

0

2562618

17821354

PSE

0

0

0

0

GOV

224068

3506373

1500237

2906519

Indirect taxes

1517569

2035126

13333662

440247

Capital a/c

10308227

20323643

21205637

2945766

Rest of the world wWorld

0

0

0

0

Total

53666294

80904465

93533470

17821354

PVT

Capital a/c

1216819

10774100 4626200

6099400

24616465 685090

4674700

4626200

5094808

-16661127

-248200

40437165

-157127

24616465

-3426241

67692335 49026796

10774100

4626200

40437165

24616465

67692335

49026796

Table 4. Alternative closure rules Gov-1 Flexible government savings, fixed Direct tax rates.

ROW-1 Fixed foreign saving., Flexible exchange rate.

S-1 Fixed capital formation, Uniform MPS point change for selected institution.

Gov-2 Fixed government savings Uniform direct tax rates

ROW-2 Flexible foreign saving, fixed real exchange rate.

S-2 Fixed capital formation, scaled MPS for selected institution.

Gov-3 Fixed government savings Scaled direct tax for selected institution.

S-3 Flexible capital formation, Fixed MPS for all non governmental institutions. S-4 Fixed investment and government consumption absorption shares(flexible quantities) Uniform MPS, point change for selected institution. S-5 Fixed investment and government consumption absorption shares. (flexible quantities) Scaled MPS for selected institution.

124

 Globalization, Consumer’s Preference, and Welfare in India

Table 5. Calibrated values of the parameters Parameter

Description

Primary

Secondary

Infra.

Service

βi (Labour)

Share parameter in production function Produc

.561

0.577

0.449

0.582

βi (Capital)

Share parameter in production function Produc

0.439

0.423

.551

.418

bj

Production function shift parameter.

1.98

1.97

1.98

1.97

ayi

Composite factor requirement

0.766

0.283

0.621

0.786

Government consumption share

0.01

0.207

0.075

0.996

taumi

Import tariff rate.

.4

.14

.14

.14

tindi

Indirect tax rate

-0.004

0.012

0.010

0.003

gammai

Scale parameter in Armington function

1.624

1.655

1.077

1.98

deltami

Share parameter of imported good.

0.29

0.285

0.171

0.186

deltadi

Share parameter of domestic good.

0.710

0.715

0.829

0.814

etai

Elasticity of substitution in Armington.

0.5

0.5

0.5

0.5

thetai

Scale parameter in transformation func.

54980

138610

78534

63972

xiei

Share parameter of export.

4.020E-7

5.41E-8

1.29E-7

2.5E-7

xidi

Share param. Of domestic good(Trans)

7.9559E-8

2.034E-8

4.77E-8

6.33E-8

phii

Substitution elasticity in transformation.

1.5

1.5

1.5

1.5

mui

Parameter

Description

RHH1

RHH2

UHH1

UHH2

taudb

Direct tax rate.

0.018

0.41

0.017

0.190

gtb

Parameter for govt. transfer.

0.189

0.413

0.365

0.048

sspb

Propensity to save for households.

0.14

0.344

0.243

0.029

rb (Labour)

Labour income share for households.

0.246

0.223

0.128

0.041

rb (Capital)

Capital income share for households.

0.117

0.268

0.563

0.078

125

 Globalization, Consumer’s Preference, and Welfare in India

Figure 2. Flow chart of calibration

Under perfect competition long run equilibrium takes place at the minimum point of the long run average cost (LAC) curve and satisfies the condition P=AC=MR=MC while under monopolistic competition equilibrium takes place at the point of tangency of the demand curve to the LAC curve. At this point MC=MR and AC=P, but P> MC. As the consequence, equilibrium price is higher and output is lower under monopolistic competition than under perfect competition. Price and output under Monopolistic competition is depicted in Figure-4. 126

Under monopolistic competition too many firms in the industry and each are producing an output less than optimal at a cost which is higher than minimum. In Figure-4 (QIMP-QPER) depicts excess capacity present in the industry under imperfect competition25. Above fact explains, starting from same benchmark scenario, lower increase of GDP, sectoral output, trade expansion and sectoral composite commodity price reduction under imperfect completion than under perfect competition in response to tariff reduction. In addition to, increased social

 Globalization, Consumer’s Preference, and Welfare in India

Figure 3. Major Interactions due to import liberalization

Figure 4. Price and output under monopolistic competition

127

 Globalization, Consumer’s Preference, and Welfare in India

welfare is lower under monopolistic competition than under perfect competition as equilibrium takes place in case of the former at an output below the socially optimal level. Simulation experiment results are depicted in Table-6. Experiment-2: Technological progress in the presence of increasing returns to scale and “Consumers preference for variety.” We simulated the impact of 5% technological progress and compared the results with perfect competition. We find in most of the cases, imperfect competition results map with perfect competition results with little dissimilarities in magnitude. Under monopolistically competitive market structure with increasing returns to scale and consumer’s preference for variety, a 5% technical progress leads to an expansion of GDP, gross investment, household consumption, sectoral export and import and sectoral real output roughly by 5%. As the case of perfect competition, composite commodity prices in the domestic market lowered down by more than 4.5% and domestic exchange rate is appreciated by 4.86%.Number of firms has been increased in almost all sectors. Domestic policy towards skill formation and R&D promotion for ensuring technical progress may lead to growth of the economy in the long run. A continuous improvement of technology over time will increase output and gross investment that could expand existing capital stock in the next period. With higher per capita capital stock economy could achieve sustainable development in the long run. Experiment-3: Greater foreign capital inflow in the presence of increasing returns to scale and “Consumers preference for variety” International capital mobility and integration of global financial markets have been emerged as many developed countries removed capital controls after 1970s. Developing country like

128

India too adopted liberalization policies towards greater inflow of foreign capital in order to augment domestic savings. As in the case of perfect competition we simulate a 25% increase of foreign capital under increasing returns to scale and consumers’ preference for variety. Under monopolistic competition also, foreign capital inflow appreciates exchange rate, increases imports and reduces export without much differences in magnitudes as compared to perfect competition case. Household consumption increases from increased real income as composite commodity prices are lowered down due to the competition among firms and higher capacity utilization. There is a small increase of number of firms in almost every sector.

SOLUTIONS AND RECOMMENDATIONS In this chapter we studied trade policy consequences under market imperfection. In the present day globalized scenario emergence of scale economy, diverse consumer preference and market structure oriented industry behaviour give rise to the rethinking of international trade especially in the direction of intra industry trade .Our study reveals that under imperfect competition, reduction of import tariff follows standard trade theory results i.e. export and import expand, exchange rate deteriorates, domestic sectoral output increases and composite commodity price falls. However, variety driven trade could not produce any greater domestic output, trade expansion (Higher volume of export and import) and gains from trade as compared to standard perfect competition case. This is probably because, increased gains from trade owing to the presence of third source of comparative cost advantage namely ‘Variety driven trade’ or gains from specialization is completely offset by excess capacity loss naturally present in imperfectly competitive market structures. Comprehensively, it could be stated that the presence of

 Globalization, Consumer’s Preference, and Welfare in India

Table 6. Simulation experiment results Economic Variable

Base run

Exp-1

Exp-2

Exp-3

Macro Indicators

In Rs. Lakhs

Imperfect Competition

Perfect Comp.

Imp. Comp.

Perfect Comp.

Imp. Comp.

Perfect Comp.

GDP

4.75E+08

0.097

.332

5.033

5.056

.056

0.033

Gross investment

67692335

0.547

0.642

5.35

6.02

1.6

1.77

Gross consumption

462304387

-0.028

0.123

5.82

5.69

.027

.139

Welfare

3061.817

0.03

0.256

0.193

5.7

.002

0.143

Import

4.97E+07

5.62

9.24

5.39

5.53

1.324

1.4

Export

45206080

4.94

7.99

4.77

4.78

-0.92

-1.049

Exchange rate

1

1.748

2.623

-4.86

-4.88

-0.524

-0.556

Govt. Income

23776038

-10

-13.4

.151

0.138

0.17

0.260

Govt. Expenditure

40437165

-4.1

-5.377

.061

0.054

0.067

0.101

Govt. savings

-16661127

-0.007

-0.093

-9.46308 E-4

1.45E04

-0.006

-0.004

External Account

Government Account

HH Consumption RHH1

40413419

0.123

0.279

5.86

5.01

0.019

0.028

RHH2

5.44E+07

-0.3

-0.417

5.76

5.2

0.042

0.038

UHH1

3.58E+08

.09

0.306

5.85

6.45

0.021

0.26

UHH2

9490968

.8

0.143

5.74

5.011

0.024

0.012

Sectoral Output Primary sector

7.85E+07

-2.5

-1.8

4.956

5.33

0.114

-0.013

Secondary sector

1.91E+08

.345

1.189

4.9

5.2

0.330

0.144

Infrastructural services

9.86E+07

0.343

1.23

5.5

5.07

-0.091

-0.078

Other Services

8.47E+07

.099

-0.078

2.9

4.622

-0.070

-0.027

Primary sector

1

-1.523

-1.92

-4.7

-4.761

-0.082

-0.047

Secondary sector

1

-1.41

-2.08

-4.7

-4.76

-0.084

-0.025

Infrastructural services

1

-0.74

-0.88

-4.6

-4.74

0.006

0.051

Other Services

1

-0.39

-0.448

-4.57

-4.752

-0.012

0.011

Composite prices

Sectoral Import Primary sector

1.28E+07

19.8

19.917

5.33

5.655

1.161

1.17

Secondary sector

2.87E+07

3.38

3.101

5.33

5.568

1.454

1.5

Infrastructural services

3.33E+06

4.464

4.26

6

5.46

1.132

1.34

Other Services

4.21E+06

5.33

4.54

3.58

4.95

1.064

1.24

Sectoral Export Primary sector

2978019

1.169

2.955

4.59

5.04

-0.868

-1.1

Secondary sector

25376947

5.81

7.073

4.53

4.91

-0.613

-0.94

Infrastructural services

10605075

4.73

5.838

5.14

4.78

-1.080

-1.179

Continued on fllowing page. 129

 Globalization, Consumer’s Preference, and Welfare in India

Table 6. Continued Economic Variable

Base run

Exp-1 3.98

Exp-2

Other Services

4824222

4.154

2.28

Primary sector

10

1.23

----

5

Secondary sector

10

1.12

----

Infrastructural services

10

-0.175

Other sector

10

.09

Exp-3

4.32

-1.09

-1.131

----

0.079

---

4.99

----

0.082

---

----

-0.75

----

-0.033

---

----

4.85

-----

0.009

---

Number of firms

increasing returns to scale and imperfect competition although puts some insights into the basis of international trade; it could not alter standard trade theory results based on perfect competition. This striking result for the Indian economy might be due to fact that, intra-industry trade and consumers’ preference for variety, particularly horizontal product differentiation is not truly visible in large agricultural sector and informal manufacturing sectors where globalization and foreign investment have not been promoted much. However, the practical relevance of introducing market imperfection, increasing returns and monopolistic competition, into the framework of trade and globalization seems to be noteworthy. Despite less emergence of variety driven trade in agrarian sectors of the Indian economy, it is very prominently visible in globalized service sectors and capital goods industries. People can freely opt for their chosen varieties from large number of alternatives in mobile computing sector, laptop, and television or in the market of service sectors like, insurance, banking, education and healthcare services. Certainly this would provide extra welfare gain to the consumers. From the policy makers perspectives it is thus worthwhile to allow higher FDI in the sectors like insurance, pension funds, education and other service sectors. Risk and vulnerability associated with higher exposure to the global capital market can be surpassed by the higher welfare gain achieved by the consumers

130

belonging in a world of wide range of varieties and opportunities.

CONCLUSION AND FUTURE RESEARCH DIRECTIONS This chapter examines effects of trade on macro economy under market imperfection. Applying CGE modelling methodology it is found that trade and globalization under imperfect competition expands trade and consumer’s confidence by providing them with the opportunity of making choice from greater number of product varieties of the same product. This would certainly increase consumer’s welfare and thereby confidence of the households as well as businessmen. From policy maker’s perspective, thus we should promote globalization and foreign capital movement in those sectors where returns to scale benefit and welfare gain from horizontal product differentiation can be achieved, such as in durable capital goods sector and service sectors. However, there are also some ill effects of globalization and FDI flow in some sectors like agricultural food crops and retail business sectors where various kinds of sectoral imperfections are present in addition to very little scope of reaping increasing returns to scale benefit and consumers welfare gain from product differentiation. In this connection, the present debate centred on

 Globalization, Consumer’s Preference, and Welfare in India

promoting FDI in retail business sectors should certainly be discouraged as it would eventually generate substantial loss of jobs of the people associated with distribution, marketing and selling of the products. Despite the consumers may enjoy higher welfare from increased varieties available in the departmental stores of the multinationals like, Walmart, Spencers etc., there will be an overall social welfare loss as the gain in welfare is simply outweighed by reduced welfare owing to considerable loss of jobs. Social planners, thus have to select government policies very carefully. The scope of the chapter is static in nature in the sense that, it does not incorporate intertemporal movements of the macroeconomic variables which arises naturally if one consider growth aspects of the economy. Accumulation of capital stock, population growth over time and technological progress give rise to the need for considering dynamic behaviour of an economy. The impacts of trade liberalization policies on the long run growth path of the economy in an applied general equilibrium framework, seems to be an interesting direction for future research work.

Eastman, H., & Stykolt, S. (1960). A model for the study of protected oligopolies. The Economic Journal, 70(2), 336–347.

REFERENCES

Krugman, P. R. (1980). Scale economies, product differentiation, and the pattern of trade. The American Economic Review, 70(5), 950–959.

Balassa, B. (1966). Tariff reductions and trade in manufacturers. The American Economic Review, 56(3), 466–473. Brander, J. A., & Spencer, B. J. (1985). Export subsidies and international market share rivalry. Journal of International Economics, 18(1-2), 83–100. doi:10.1016/0022-1996(85)90006-6 Corden, W. M. (1974). Trade Policy and Economic Welfare. Oxford: Clarendon.

Harris, R. (1984). Applied general equilibrium analysis of small open economies with scale economies and imperfect competition. The American Economic Review, 74, 1016–1033. Harris, R., & Cox, D. (1984). Trade, Industrial Policy, and Canadian Manufacturing. Toronto: University of Toronto Press. Helpman, E. (1981). International trade in the Presence of Product Differentiation, Economies of Scale and Monopolistic Competition: A Chamberlinian-Heckscher-Ohlin Approach. Journal of International Economics, 11(3), 305–340. doi:10.1016/0022-1996(81)90001-5 Helpman, E. (1982). Increasing Returns, Imperfect Markets, and Trade Theory. Discussion Paper. Tel Aviv University. Krugman, P. R. (1979). Increasing returns monopolistic competition, and international trade. Journal of International Economics, 9(4), 469–479. doi:10.1016/0022-1996(79)90017-5

Krugman, P. R. (1981). Intra industry specialization and the gains from trade. Journal of Political Economy, 89(5), 959–973. doi:10.1086/261015 Narayana, N. S. S., Parikh, K. S., & Srinivasan, T. N. (1991). Agriculture, Growth and Redistribution of Income: Policy Analysis with a General Equilibrium Model of India. Amsterdam: North Holland.

Das, K., & Das, R. C. (2012). International trade, energy consumption and environment: A computable general equilibrium analysis for India. Asian Journal of Research in Business Economics and Management, 4(2), 1–25.

131

 Globalization, Consumer’s Preference, and Welfare in India

Panda, M., & Quizon, J. (2001). Growth and Distribution under trade liberalization in India, Chapter-8. In A. Guha, K. L. Krishna, & A. K. Lahiri (Eds.), Trade and Industry: Essays by NIPFP-Ford Foundation Fellows. New Delhi: National Institute of Public Finance and Policy. Panda, M., & Sarkar, H. (1990). Resource Mobilisation through Administered Prices in an Indian CGE. In T. Lance (Ed.), Socially Relevant Policy Analysis. Cambridge, MA: MIT Press. Parikh, K. S., Narayana, N. S. S., Panda, M., & Ganesh, A. K. (1997). Agricultural trade liberalization: Growth, welfare and large county effects. Agricultural Economics, 17(1), 53–78. doi:10.1016/S0169-5150(97)00017-0

END NOTES

For an example, estimated long run gains from Canadian trade liberalization ranges 8-12% larger than gains suggested by conventional method, Cox, D. and Harris, R(1983). There can be pencil with different colors, refrigerator with different colors and shapes, laptop computers with different configurations, haircuts of different styles, list is endless. Indeed, it is not the actual number of establishments that actually matters to both producers and the consumers. Consumer’s preference for product varieties remain usually confined around 10 to 15 varieties in a particular point of time and geographical location. For the producers, it is also a finite set of rival firms within which strategic competition as well as gains from specialization belongs. Here the Maximization problem is: Max

1



2



3

Robinson, S. (1989). Multisectoral Models. In H. B. Chenery & T. N. Srinivasan (Eds.), Handbook of Development Economics. Amsterdam: Northholland. doi:10.1016/S1573-4471(89)02005-X Saluja, M. R., & Yadav, B. (2006). Social Accounting matrix for India 2003-04. Retrieved from http://planningcommission.nic.in/reports/ sereport/ser/ser_sam Sarkar, H., & Panda, M. (1990). Short term Forecasting and Policy Analysis through a Structural Macroeconomic Model for India. UN-ESCAP seminar on inter-linked country model system, Bangkok. Shoven, J. B., & Whally, J. (1984). Applied general equilibrium models of taxation and international trade. Journal of Economic Literature, 22(3), 1007–1051. Suryanarayana, M. H. (1996). Economic reforms, nature and poverty. Economic and Political Weekly, 31(10), 617–624.

132



4

{u (⋅) | ∑ i



5



6



7



8



9



10

ω ∈Ωi

pi ω Di ω ≤ Ei

}

For derivation of this expression and more elaborate discussion please see Helpman and Krugman (1985), Page-118. S-D-S preference indicates that each consumer loves variety. In CGE models, there are several categories of households. However, for a particular category of household, taste & Preference, endowments are assumed to be identical. n is the number of variety and σ is the elasticity of substitution between varieties. Please see Rethinking International Trade, Written by P. Krugman Page-40. In Indian context I/O table is published by Central Statistical Office (CSO) in every five tears gap. Saluja et al (2006) constructed SAM for India using I/O matrix for the year 1999.

 Globalization, Consumer’s Preference, and Welfare in India



11



12



13 14



15



16



17 18



19

Net indirect tax mentioned in the SAM has been classified into domestic indirect tax and import tariff. In the Indian context government savings in most of the cases is negative that constitute large part of country’s fiscal deficit. Expenditure of the government is usually determined in annual budget. Market structure and foreign trade. See Brander and Spencer (1985) and Brander and Krugman(1983) in this connection. Purchase cost of them is called ‘sunk’ cost as the benefit from them may be accrued in the subsequent years. Gross domestic capital formation provides an addition to the stock of fixed capital like building, machinery, equipments etc. This implies total industry fixed cost is constant and does not depend on entry or exit of new firms. Considering each variety is equally priced. We took same number of firms in each sector as 10. On an average competition among sellers lye within 10 varieties while consumer’s preferences are usually confined within, on an average, 10 varieties of the same product. We get few empirical support of our price elasticity computed value. In case of elec-



20



21



22



23



24



25

tricity in services obtained value is -0.3, in case of bus transport calculated value lies between -0.232 to -0.523.For the tobacco product price elasticity lies between -.4 to -.9. Since the SAM of 2003-04 is a balanced SAM and our intention is to empirically examine the directional movement of different macroeconomic variables in response to trade policy change, results will not be much affected only because of calibrating model parameters using 2003-04 SAM instead of using some recent SAM. This value can directly be obtained from SAM. For the necessary underlying assumptions, consider immediately preceding section. For more elaborate discussion, see the preceding section. Price elasticities are considered for a) Primary sector b) Secondary sector c) Infrastructure and d) Other service sector as -0.35215,-.2642,-0.289,-0.3107 respectively. We obtained these values from various economic literatures on Indian economy. In the presence of fixed cost, equilibrium does not take place at the minimum point of LAC. See E. Chamberlin, ‘Monopolistic Competition Revisited ‘Economic Journal (1952).

133

Section 2

Governance, Institution, and Growth

135

Chapter 7

Governance and Capital Accumulation under Globalization:

A Study on Some Selected Countries Kamal Ray Katwa College, India Ramesh Chandra Das Katwa College, India Utpal Das Katwa College, India

ABSTRACT Sustaining good governance is necessarily required for all countries in the world after the phase of globalization, especially when almost the entire world is struck by the global financial crisis originated from the USA. The present study tries to concentrate upon establishing an interlinkage among capital accumulation of a sample of countries with principal components of governance for the time period 1996-2012. Correlation analysis along with the Granger Causality test is applied to identify directions of causalities among capital formation and all the governance indicators. The study observes an inverse relation between governance indicators and capital accumulation for majority of the developing countries and in some cases positive relations for developed countries. Besides, it is observed that there are causal relations from capital formation to governance in most of the developed countries whereas in most of the developing countries there are causalities from governance to capital formation.

INTRODUCTION The occurrence of the global financial crisis during 2007-09, originated from the USA because of the housing sector bubble bursts and spread to other

countries via different channels, has affected the chain of actions between growth and its determinants of different status of countries of the world. Failure of governance, among other factors, may have caused the disturbance that affected growth

DOI: 10.4018/978-1-4666-8274-0.ch007

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Governance and Capital Accumulation under Globalization

rates of output along with other related variables like capital formation/investment, consumption spending, etc. Governance refers to all process of governing, whether undertaken by government, market or network, whether through laws, norms or powers. Governance occurs in three broadways: a) through top-down methods that particularly involve governments and state machineries b) through the use of market mechanism where market principles of competition serve to allocate resources operating under government regulations in optimal way c) through networks involving public-private partnerships. It is obvious that some of the countries inherited British colonial state of affairs and pro-people massive reformation in governmental activities is not noticed as they, developing nations in particular, kept much of the governance structure intact. Lack of transparency, accountability undermines pro-people development since public servants become their own masters with little responsibility. Many inflicted countries are facing man made crisis of governance during the last two or three decades, the administrative system is now largely non-functional and unresponsive to the social and economic priorities of the developing countries in particular. Nobody cares about urgently needed structural reformation in the component parts of the governance. Recommendations of several commissions have become unimplemented when simplifications of procedures, reduction of administrative layers are complementary to today’s growth and development. Commission and omission work well traditionally signifying zero or negative output to the nation since salaries to the members of commission and establishment cost of executing commission matter much to a nation. The decay in the county’s administrative and public distribution systems has affected the wellbeing of the poor people generated black money. New institutional and constitutional initiatives are required to hold individual ministers accountable for efficient services to the public. The scenario of the governance-structure in some

136

developing countries after globalization has changed, but not up to the desired level that enables in pulling sizeable domestic investment and FDI too. Market-enhancing governance (Khan, 2007) might be underlined as the developed countries are able to reduce the transaction cost as well as today’s massive level of corruption. In contrast, less developed countries usually follow growthenhancing governance that focuses on effective institutional systems for accelerating the process of transfer of assets and resources to more productive sectors with the help of updated technologies. Broadly speaking, it has two broad approaches: market-enhancing as well as growth-enhancing governance. Private investors would be comfortably in driver’s seat if the government can ensure efficient market with desired market incentives and adequate security. It is, no doubt, a dominant paradigm in the face of today’s international development. The sizeable market incentives for the provocation of investors is directly related to rule of law, regulatory quality, protection of property rights, effective machineries for reduction or control of corruption, commitment to the non-expropriation. Markets mediating resource allocation in any country become more efficient to speak of. The supply of public goods is to be done by the state, not by the private sector. The credibility of the government is reflected through watertight and compact legal system. In contrast, non-orthodox approaches to governance have argued that markets are inherently inefficient in developing countries despite the political will. Given the structural limitations of markets in developing countries, required development needs critical governance capacities of the nation for ensuring productivity growth both in private and public sectors. The example of East Asian countries’ growth with lax governance during last two decades may be underlined in this context. East Asian countries have effective institutions that accelerate growth when technological backwardness and high transaction cost matter much in their countries, which is described

 Governance and Capital Accumulation under Globalization

as growth-enhancing governance. It focuses on effectiveness of institutions and accelerating the process of transfer of assets and resources to more productive sectors; updated technologies are also being applied. Control of corruption, achievement of stable property rights as well as compact or stringent rule of law corresponds to significant amount of government expenditure when the country is poor. So it is a serious problem to the less developed countries to make governance sound and hence developing countries do not satisfy the market-enhancing governance criteria at early stage of development even with its high growth era. In this context we might refer to the postulates of Knack and Keefer (1995), where they include the indices for a number of key variables that measures the performance of the states in providing market-enhancing governance. The indices are corruption in government, rule of law, bureaucratic quality, and repudiation of government contracts and expropriation of risk. These indices reflect the extent of reduction of transaction cost as well as measure the degree of efficiency of markets. Kaufmann, Kraay and Massimo (2005) applied second set of data for testing role of the market-enhancing governance; data on six broad governance indicators are available on World Bank’s website (www.data.worldbank. org) since 1996. The governance indicators are Voice and Accountability (measuring political, civil and human rights), Political Stability and Absence of Violence (measuring likelihood of violent threats to, or charges in, government including terrorism), Government Effectiveness (competence of bureaucracy and the quality of public service delivery), Regulatory Quality (market-friendly policies),Rule of Law (quality of contract enforcement, the police, and the courts as well as likelihood of crime and violence) and Control of Corruption (exercise of public power for private gain, including both petty and grand corruption and state capture). The argument for market-enhancing governance that we mentioned is that if the efficient markets can be constructed,

they will attract most efficient technologies even to a developing nation. On the other hand, inefficient transferring of assets and resources to the growth sectors under growth-enhancing governance in a developing nation is pronounced. In addition, use of low graded technologies and low-value-added activities become proactive in the less developed countries construing benefits in the short run period only under growth-enhancing governance. Old theoretical background supports that a proportion of the output, which is not consumed instantly, is saved for the future and the reward of painful abstinence from present consumption is being compensated by the market rate of interest in the future period. The color of saving is changed to investment demand via financial intermediaries subject to the market incentive, and finally the flow of investment is being funneled into ultimate capital stock, the engine of growth to speak of. So capital formation can be differentiated from savings because accumulation deals with the increase in stock of real investment flow and all savings are not invested. Some confusion may arise in view of investment with capital formation since investment can be in financial assets that might be unproductive. Usually construction of new factories along with machineries, equipments and all productive capital goods are taken as newly formed capital. Gross fixed capital formation can be classified into gross private domestic investment and gross public investment. The gross public investment includes investment by the government and public enterprises. It is suggested that robust growth rates can be sustained over a long period since countries are able to maintain sizeable proportion of capital to GDP. No doubt, higher and higher the growth rate of capital formation, higher would be the productive capacity of the economy, although high productive capacity of the economy might not be properly utilized by the nation because of the lack of conducive macro economic factors at both domestic as well as international level, good governance, whereas its paucity matters much in the era of sustainable globalization. Here responsibility

137

 Governance and Capital Accumulation under Globalization

of the respective government cannot be denied so far as creation of market incentive for investment in different fields is concerned. Bureaucrats are likely to be proactive in inviting industrialists with some required facilities so that industrial initiatives cannot be ravaged in the concerned country, which is absent in most of the developing nations. Besides some quantitative explanatory variables, the quality of governance comprised of control of corruption, regulatory quality and rule of law, state machineries or instruments plays key role in the present day economy. Minimum government, maximum governance emerged as a new slogan today for reduction of social cost per unit of social benefit. Question is how to measure quantitatively the quality of governance that directly affects capital formation? As per World Bank method, the principal components of different aspects of governance like political stability, government effectiveness, voice of accountability, control of corruption, rule of law and regulatory quality are the different indices by which we might percept the quality of governance of any government under globalization. The Worldwide Governance Indicators (WGI) are a research data set summarizing the views on the quality of governance provided by a large number of enterprise, citizen and expert survey respondents in industrial and developing countries. These data are gathered from a number of survey institutes, think tanks, non-governmental organizations, international organizations, and private sector firms. The WGI do not reflect the official views of the World Bank, its Executive Directors, or the countries they represent. The WGI are not used by the World Bank Group to allocate resources. For simplicity, indices of control of corruption, rule of law, regulatory quality and governance effectiveness are taken as principal components of governance in the present study as explanatory variables.

138

LITERATURE REVIEW The crisis of East Asian countries reveals that corruption is inimical to development. Evidence clearly shows that phenomenal rates of growth have been achieved, despite the tangible rates of corruption. Leff (2002) proposed that corruption could be good business with an emphasis on connections works as well, if not better for development than a system based on openness, accountability and competitive bidding. Others suggest that the Asian Miracle can be explained because systemic corruption was not actually as bad as it is made out to be. The logic for this fits modern analysis of corruption; systemic corruption is harmful to development and so development within this environment is impossible. By examining the causes and costs of corruption it will become apparent to what extent these perspectives on the impact of corruption are true. Over the last twenty years, the Philippines are estimated to have lost $48 billion due to corruption, surpassing its entire foreign debt of $40 billion (Reuter Newswire, 1997). Over the last decade in Indonesia, assets have fallen by more than $50 billion, primarily because corrupt officials trading state assets have deliberately undervalued their worth in exchange for substantial kickbacks (Business Week, 1993). Nakata (1979) reveals that governments have paid between twenty and one hundred percent more for goods than they should have otherwise been paid. According to Mauro (2002) corrupt government officials may be more likely to choose to undertake types of government expenditure that allow them to collect bribes and to maintain them a secret. Good corporate governance is essentially required to create field for sound investment that helps firms to prosper in domestic as well as in global markets since Kajola (2008) defines corporate governance as the system by which

 Governance and Capital Accumulation under Globalization

business corporations are directed and controlled to proceed ahead. Claessens (2006) believes that good corporate governance practices contribute to firm-level growth and increases returns on equity, promote efficiency of firms in favour of stakeholders. Bohren, Cooper and Priestley (2006) opined from the data of US manufacturing firms and they observed: i) good governance improves the efficiency of capital allocation within firms ii) lax or low quality of governance produces under or over investment. Chang, Chang and Wei (2008) collected data from Taiwan for their study and found that corporate governance mechanisms affect investment decisions of the firms. Aldrighi, Kalatzisand Pellicani (2011) collected data from Brazil and observed that ownership and control structures significantly affect the firm’s investment decisions. None of the above set of literatures put emphasis upon the inter play between capital formation and governance and hence the present study bears a good rationale for taking up it as a venture.

of governances or governance indicators of the respective governments in the era of globalization; the selected countries are eleven in number comprising of both developed and developing nations which are selected non-randomly. The impact of governance indicators like voice and accountability, political instability and violence on capital formation are not taken into account to make our study less cumbersome. Secondary data set on different indicators of governance and capital formation of the respective countries are obtained from the World Bank database; which are gathered from a number of survey institutes, think tanks, non-governmental organizations, international organizations, and private sector firms covering 230 nations in the world. Therefore, we collected time series data on gross capital formation and principal components of governance indicators of the selected eleven countries from the year of 1996 to 2012. The countries are USA, UK, France, Germany, Greece, China, India, Japan, Thailand, Brazil, and South Africa.

OBJECTIVE OF THE STUDY

METHODOLOGY

The present study tries to concentrate upon establishing an interrelation among capital accumulation of a country with principal components of governance, namely, control of corruption (CC), regulatory quality (RQ), rule of law(RL) and governance effectiveness (GE) for the time period 1996-2012. Finding the relation in the phase of the global financial crisis with respect to the selected countries is also included in the present study. Market-enhancing as well as growth-enhancing governance have come into force automatically as we try to find any relation between capital formation and governance in the age of globalization.

The graphical method of simple line diagram against the time series data is applied for quick understanding the relative positions of different trend lines. It is not the straight way to find interrelationship between the qualitative characters of governance of different countries and their gross capital formation unless we have the cardinal figures of the indices of principal components of governance. The estimate of governance indicators, as framed by World Bank, ranges from -2.5 (weak) to 2.5 (strong performer) that would help us for quantifications. The correlation coefficient is enough to assess primarily the degree and direction of association between the variables as we get the numerical data on governance indicators of the selected countries. The tool of Granger Causality Test is taken into account for investigating causal relationships between the variables, cause and effect to speak of. We have done the causality

SOURCES OF DATA How capital accumulation in developing and developed nations are being influenced by the quality

139

 Governance and Capital Accumulation under Globalization

tests in line with the Granger (1969). As the data length is 17, so we do not need to check whether all the time series are stationary or not. The test procedure can be done by estimating the following two equations where variables X and Y stand for the GCF (in US BN Dollar) and Governance Indicators (CC, RQ, RL and GE) at their levels. The equations are: n

n

i =1

j =1

Yt = Σ αi Xt −i + Σ βjYt − j + u1t n

n

i =1

j =1

X t = Σ λi X t −i + Σ δ jYt − j + u2t 

(1)

(2)

where Yt = time series values of the variable Y at period tYt-j = lag t-jXt = time series values of the variable X at period tXt-i = lag t-iu1t, u2t = normally distributed error terms that are serially independentαi = responsiveness of Yt with respect to Xt for ith stateδj = Xt with respect to Yt for the ith state X variable causes Y if ∑αi = 0 is rejected or ∑αi ≠ 0 is accepted in equation (1) and ∑δj = 0 is rejected by equation (2). On the other hand, Y causes X when the null hypothesis of ∑αi = 0 in equation (1) is accepted and ∑δj = 0 in equation (2) is rejected. There will be bidirectional or feedback causality between X and Y if the null hypothesis of ∑αi ≠ 0 is accepted in equation (1) and ∑δj ≠ 0 is accepted in equation (2). Linear regression is taken as a tool for quantification of a change in explained variables due to change in explanatory variables.

GRAPHICAL ANALYSIS The trend of gross capital formation in USA could be noted quickly by the line diagram during the period 1996 to 2012 (Figure 1); growth process of gross capital stock during pre-crisis period 1996 to 2007 continued to rise and financial shocks of

140

2007 force gross capital stock to fall till 2009 and finally failed to reach the level of 2007 even in the year of 2012. Japan occupied the second highest position in terms of gross capital formation after USA and its trend line is insignificantly downward throughout the study period evolving absence of effect of financial crisis of 2007. Germany may demand third position out of the sample as far as gross capital stock is concerned and it has meager upward trend line over the selected time horizon. Capital stocks at the disposal of France and UK are very close to Germany and they gave rising trend lines. In Germany, there is a slight downward turn at the juncture of beginning of crisis. Greece has got uptrend line with very low growth rate. Trends of gross capital formation in the developing nations are somewhat different compared to developed nations (Figure 2). In China, gross capital stock exponentially increases from 342.43 US billion dollars in 1996 to 4031.28 US billion dollars in 2012 and even it surpasses the level of gross capital stock of USA in 2012. No external shock of the financial crisis of 2007 is found to be observed in China. India stood second position among the selected developing countries and it has very scanty uptrend over the study period. The gap between China and India increases rapidly as China’s stock increases exponentially. Brazil has almost similar trend like India except the time period from 2008 to 2012. Brazil has got the downtrend after 2008, after the financial crisis of 2007. Thailand and South Africa are very close to each other, and uptrend with little growth rate are found to be noticed for both the countries. In Figure 3, the trends of control of corruption indices are depicted for all the selected countries where United Kingdom becomes topper in terms of controlling corruption till 2007, and then Germany is regarded as a leader in controlling corruption up to 2012. The condition of USA is relatively better at least up to 2002 and then it has got sharp downtrend. It could be due the effect of financial crisis of 2007. Despite the lurid scenario of France

 Governance and Capital Accumulation under Globalization

Figure 1. GCF of developed countries over years

Figure 2. GCF of developing countries over years

141

 Governance and Capital Accumulation under Globalization

Figure 3. Control of corruption indices of countries

relative to UK, Germany and USA, it shows better result as it has a continuous rising effort to check the corruption over the period. Japan improved its state machineries radically in controlling of corruption as it has a relatively greater gradient of its upward trend line. Corruption controlling machineries for Greece and South Africa are not at all good from the beginning of the study period; even they got downward trends during 1996 to 2012. Brazil’s trend is quite similar to the trend of Thailand where corruptions are proactively pronounced; almost touch the line that lies below zero line. Similarly, India is reputed in terms of corruption, and China becomes champion in this regard out of the present sample whereas its gross capital stock increases exponentially. Most of the trends of all status of countries show downward trend over time implying bad governance in terms of CC. In Figure 4, the trends of regulatory quality of the selected countries are shown. Despite the downward trends of UK and USA, they take a leading role among the selected nations. Accord-

142

ingly, Germany is also supposed to be a good performer in terms of regulatory quality as it has uptrend from relatively better regulatory quality level. France occupied fourth position and it has also a sharp upward trend throughout the study period. Japan improved its quality very slowly with the progress of time. The value of RQ falls from 0.64 to 0.49 – a downward trend is observed for Greece. South Africa has almost similar trend like Greece when it sounds bad as compared to above nations. Thailand shows relatively better trend among the developing nations in spite of falling tendency after 2005 in particular. In Brazil, regulatory quality sharply falls up to 2006, and then it has got uptrend. India and China as twin brothers have been executing regulatory measures at the bottom level out of the selected nations. In Figure 5, the trends of the indices of rule of law of selected courtiers are being depicted as values of the indices for the selected countries are moving between the upper limit (1.76) and lower limit (-0.55). Here Germany, UK and USA are very close to each other in terms of implementing rule

 Governance and Capital Accumulation under Globalization

Figure 4. Regulatory quality indices of countries

Figure 5. Rule of law indices of countries

143

 Governance and Capital Accumulation under Globalization

Figure 6. Government’s effectiveness indices of countries

of law; though they are far below the value of upper limit 2.5. France occupied fourth position and it has slightly rising trend in the indicator like that of Germany and USA. Japan’s rule of law trend over the study period is supposed to be downward with insignificant gradient. Greece is seating in the last bench among the six developed nations, but its rule of law is better as compared to all other developing nations. The performance of Thailand was better relatively in the initial stage among the developing nations, despite the downward trend during 1996 to 2012. India has also faced falling trend from low initial stage like Thailand but it is well placed compared to China and Brazil. There is an almost oscillatory movement around the value 0.1 for South Africa. Overall trend of Brazil is observed to be slightly upward as she gets a turn at the juncture of 2005; it badly ranges from -0.33 to 0.00. The scenario of rule of law of China is said to be worse like above mentioned two governance indicators, moving around -0.5. The annual movement of government’s effectiveness indices of the selected countries is

144

graphically shown in the Figure 6. UK and USA have acquired leading position with almost similar trends when both of them have got downward trends. Germany has got downtrend up to 2003 and then it improved its quality of GE. France has started from very worse condition (0.23) in 1996 and then its government tightened this measure within two years; finally it has got uptrend. Japan improved its quality gradually as far as its uptrend is concerned. Greece has acquired sixth position in the present sample and it has also downtrend. South Africa lies next to Japan and it has also downtrend like most of the countries. Thailand started from very weak GE, but it has negligible uptrend. Brazil’s trend has fallen sharply from very worse condition; it has fallen dramatically after 2008. GE index of India has always been lying below the zero line except year 2007. China earned uptrend with significant effect for the entire period; but its indices have fallen continuously after 2007.

 Governance and Capital Accumulation under Globalization

Table 1. Correlation between GCF and governance indicators of countries Country

Total Period (1996-2012)

Pre Crisis Period (19962008)

Post Crisis Period (20092012)

CC

RQ

RL

GE

CC

RQ

RL

GE

CC

RQ

RL

GE

USA

-0.41

-0.40

0.52

-0.57

-0.40

-0.32

0.49

-0.59

0.98

-0.74

0.23

-0.19

UK

-0.95

-0.58

0.25

-0.52

-0.97

-0.28

-0.31

-0.86

0.62

0.34

-0.65

0.59

France

0.69

0.49

0.60

0.16

0.58

0.51

0.61

0.26

0.98

-0.66

-0.46

-0.59

Germany

-0.79

0.53

0.23

-0.34

-0.88

0.57

0.88

-0.23

0.05

0.27

-0.71

-0.90

China

-0.45

0.45

0.032

0.62

-0.51

0.50

0.18

0.86

0.30

-0.80

-0.94

-0.85

India

-0.42

-0.24

-0.61

0.38

-0.17

0.01

-0.38

0.68

-0.99

-0.57

-0.92

-0.39

Japan

0.69

0.62

0.63

-0.15

0.60

0.58

0.64

-0.32

0.92

0.59

0.38

-0.57

Thailand

-0.68

-0.14

-0.69

0.08

-0.67

-0.07

-0.55

0.41

0.33

-0.41

0.87

-0.80

S. Africa

-0.84

-0.21

0.17

-0.50

-0.65

0.19

0.11

-0.18

0.54

-0.56

0.37

-0.72

Brazil

-0.27

-0.71

-0.23

-0.86

-0.34

-0.76

-0.68

-0.59

0.89

0.03

0.93

0.42

Greece

-0.46

0.15

-0.02

-0.23

-0.60

0.40

0.17

-0.62

0.95

0.90

0.94

0.97

Note: The bold figures represent significant correlation result at least at 5% level of significance

EMPIRICAL INVESTIGATION Perhaps it may not be the myth that good governance, as explained by principal components of governance indicators defined by World Bank, leads to a high rate of gross capital formation (GCF) in developed nations in particular whereas rate of GCF in the developing nations always sounds bad because of bad or lax governance. To have a primary view on the interdependence between GCF and governance indicators, we have computed the correlation coefficients (or product moment correlation coefficient of Spearman) for all the countries over the entire period, pre crisis and post crisis phases. The results are presented in Table 1.The degrees of associations measured by correlation coefficients between GCF and all the four governance indicators are of negative values in most of the countries except France, Japan and China for the entire period. This means with rising values of GCF for all the countries, most of the governance indicators are of falling values. For France, all the governance indicators are of rising trends like the GCF, whereas for Japan, CC, RQ and RL are of rising values over time. China’s GE

and RQ have significantly improved and have a link with rising GCF. Brazil has also performed well in its GE as it showed a rising trend, reaching a peak in the year 2003 whereas all other governance indicators are going down in values over time. After segregation of the entire phase we observe a near similar correlation results for the countries. A slight change is observed for UK where all the governance factors are of negative trends including the RL. Brazil remains in the same position like before. The occurrence of the crisis has somehow affected the countries’ governance scenarios in a better way. In most cases corruption has been controlled by the respective governments. Governance in China and India has deteriorated but Brazil has improved much in this area. Greece has continued to be the only country where GCF and all the governance indicators still going in downward direction during the post crisis period. No sign of improvement is observed for Greece even after the crisis when most of the countries have made improvements at least in their GCF. Any sign and magnitude of correlation of a country among the selected variables do not justify which one is making influence upon the

145

 Governance and Capital Accumulation under Globalization

Table 2. Granger causality test results Country

Hypothesis

F

P

Remarks

United States

CC does not cause GCF GCF does not cause CC

0.00055 2.38669

0.98170 0.9817

No No

RQ does not cause GCF GCF does not cause RQ

0.30955 3.60442

0.58741 0.08005

No →

RL does not cause GCF GCF does not cause RL

0.08663 7.42511

0.77315 0.01735

No →

GE does not cause GCF GCF does not cause GE

0.79990 5.49256

0.38738 0.03565

No →

CC does not cause GCF GCF does not cause CC

0.08663 7.42511

0.77315 0.01735

No →

RQ does not cause GCF GCF does not cause RQ

0.23846 1.06400

0.63345 0.32111

No No

RL does not cause GCF GCF does not cause RL

0.98988 0.01143

0.33793 0.91651

No No

GE does not cause GCF GCF does not cause GE

0.00011 8.97682

0.99171 0.01032

No →

CC does not Cause GCF GCF does not Cause CC

1.57219 1.75295

0.23197 0.20832

No No

RQ does not cause GCF GCF does not cause RQ

10.7334 0.19363

0.00602 0.66714

→ No

RL does not cause GCF GCF does not cause RL

0.00888 3.86504

0.92636 0.07103

No →

GE does not cause GCF GCF does not cause GE

1.06236 8.30761

0.32147 0.01282

No →

CC does not Cause GCF GCF does not Cause CC

8.34557 0.12472

0.01268 0.72963

→ No

RQ does not cause GCF GCF does not cause RQ

10.7334 0.1936

0.00602 0.66714

→ No

RL does not cause GCF GCF does not cause RL

4.34783 1.46950

0.05734 0.24700

→ No

GE does not cause GCF GCF does not cause GE

1.52629 0.15243

0.23853 0.70254

No No

United Kingdom

France

Germany

others. This can be demonstrated by causality tests. Our Granger Causality Tests over 17 years’ time series data for selected eleven countries speaks for cause and effect in the movements of respective variables. The qualities of principal components of variables are measured by cardinal figures and hence any change in governance indicators may have effect on GCF of the respective countries or change in GCF of any nation may have impact on country’s governance indicators which depends on causal relationships between GCF and governance indicators as we already derived results by Granger-Causality test.

146

In our present study, derived empirical results (Table 2, 3, and 4) for USA show that there are causal relations from GCF to three governance indicators, viz. RQ, RL and GE, but no way reverse causalities are observed. This means governance indicators work as end, not as means, of explaining economic variables like GCF. As observed from Figure 1 that trend of GCF is positive for the study period like the RL but reverse to RQ and GE. Hence, the quantification of how much of GCF increase leads to increase in RL and decrease of RQ and GE is the matter of concern now. We have presented the regression results in Table 5

 Governance and Capital Accumulation under Globalization

Table 3. Granger causality test results Country

Hypothesis

F

P

Remarks

China

CC does not cause GCF GCF does not cause CC

3.81329 0.10138

0.07272 0.75524

→ No

RQ does not cause GCF GCF does not cause RQ

0.36384 0.17060

0.55676 0.68631

No No

RL does not cause GCF GCF does not cause RL

0.90476 0.09297

0.35886 0.76526

No No

GE does not cause GCF GCF does not cause GE

9.25172 0.05926

0.00945 0.81147

→ No

CC does not cause GCF GCF does not cause CC

2.59156 4.26197

0.13144 0.05952

No →

RQ does not cause GCF GCF does not cause RQ

0.01458 2.25439

0.90573 0.15713

No No

RL does not cause GCF GCF does not cause RL

0.05955 2.34301

0.81102 0.14981

No No

GE does not cause GCF GCF does not cause GE

2.12015 0.18536

0.16910 0.67386

No No

CC does not cause GCF GCF does not cause CC

2.96359 3.91979

0.10885 0.06929

↔ ↔

RQ does not cause GCF GCF does not cause RQ

0.50530 6.78813

0.48974 0.02178

No →

RL does not cause GCF GCF does not cause RL

1.59566 0.18248

0.22871 0.67624

No No

GE does not cause GCF GCF does not cause GE

1.50833 5.5111

0.24117 0.03539

No →

CC does not cause GCF GCF does not cause CC

0.70384 0.00930

0.41666 0.92465

No No

RQ does not cause GCF GCF does not cause RQ

0.22769 1.68532

0.64116 0.21678

No No

RL does not cause GCF GCF does not cause RL

20.4626 0.67638

0.00057 0.42566

→ No

GE does not cause GCF GCF does not cause GE

1.51029 3.36905

0.24088 0.08941

No →

CC does not cause GCF GCF does not cause CC

1.38074 3.37387

0.26105 0.08920

No →

RQ does not cause GCF GCF does not cause RQ

4.79446 4.77731

0.04739 0.04773

↔ ↔

RL does not cause GCF GCF does not cause RL

0.00988 0.04010

0.92234 0.84438

No No

GE does not cause GCF GCF does not cause GE

0.45616 24.8899

0.51126 0.00025

No →

India

Japan

Thailand

South Africa

and Table 6. It is observed that, if the value of GCF is increased by one unit in United States, the value of RQ gets reduced by 0.001 units. In a similar way, as value of GCF is increased by one unit, value of GE is reduced by 0.00015 units; but RL is increased by 0.000062 units when there is an in increase in GCF by one unit. It is indica-

tive that enhancement of GCF is at least in one way complementary to the governance in United States as far as betterment of RL is concerned. How do we explain the meager or scanty negative association between GCF and GE in USA? Enhancement of gross capital stock in USA does not mean enhancement of GCF at the disposal of

147

 Governance and Capital Accumulation under Globalization

Table 4 Granger causality test results Country Brazil

Greece

Hypothesis

F

P

Remarks

CC does not cause GCF GCF does not cause CC

6.39757 0.02049

0.02516 0.88838

→ No

RQ does not cause GCF GCF does not cause RQ

2.85543 0.02134

0.11489 0.88609

No No

RL does not cause GCF GCF does not cause RL

0.57594 3.35523

0.46145 0.09000

No →

GE does not cause GCF GCF does not cause GE

4.58159 12.4961

0.05185 0.00366

↔ ↔

CC does not cause GCF GCF does not cause CC

0.96053 2.84585

0.34494 0.11544

No No

RQ does not cause GCF GCF does not cause RQ

6.02995 2.13700

0.02891 0.16753

→ No

RL does not cause GCF GCF does not cause RL

0.69682 0.26386

0.41893 0.61610

No No

GE does not cause GCF GCF does not cause GE

2.51918 0.04766

0.13648 0.83058

No No

state when there is an immense chance of private capital accumulation. Private capital accumulation is not all is conducive to tighten GE index as GE includes quality public services, civil services, independent role of politicians, policy formulation and implementations. So scanty inverse association between GCF and GE might be explained by the fact that rising trend of GCF in the hands of corporate sector does not cause falling tendency of GE, perhaps GE has been falling in natural way due to lax governance over the time in USA. In addition to that the occurrence of financial crisis may have forced the state to attract more investment even with a poor GE. In a similar way any change in GCF negatively affects both control of corruption (CC) and GE in the United Kingdom. The values of the coefficients of causal effects are very small, 0.0019 and 0.0009 respectively, but they are highly statistically significant. The quantitative linear relationship between GCF and CC reveals the fact that the value of index of CC is reduced by 0.0019 units as GCF rises by one unit. It signifies that UK government is not capable to control corruption even in the face of rising trend of GCF or rising trend of GCF does not work as check valve to make stringent

148

corruption controlling machineries, despite the fact that robust corruption controlling machineries needs additional capital-based technology, capitalbased institutional network etc in addition to better human quality. It is also to be noted that growth rate of GCF might largely be explained by the private capital stock enhancement that should not be under consideration in controlling corruption at the national level. The relation between GCF and GE in UK is almost similar to the same relationship in USA; as GCF rises, GE falls by the rate of 0.0009. The index of governance effectiveness is supposed to be enhanced in the face of rising trend of GCF if major part of the incremental GCF is appropriated by the government itself. But it might not be the reality. The result may be explained which is quite similar to USA. In France, the index of RL is increasing at the rate of 0.0003 with the increase in GCF by one unit, not vice versa. It is quite natural that government is capable to allot additional fund to reform the machineries of RL when GCF rises via growth rate of GDP, provided major part of the additional gross capital should be under the control of the state. One important result is found which is absent in both USA and UK; RQ strongly

 Governance and Capital Accumulation under Globalization

Table 5. Quantifications of impact of explanatory variables on explained variables Country

Nature of the Variables

Name of the Variables

Intercept

USA

Dependent Variable

RQ RL GE

UK

France

Germany

China

India

Japan

Thailand

Slope

R2

1.82 (11.31)

-0.001 (-1.68)

0.15

1.37 (18.59)

0.000062 (2.36)

0.27

2.05 (14.01)

-0.00015 (-2.72)

0.33

Independent Variable

GCF

Dependent Variable

CC

2.57 (11.91)

-0.0019 (-3.15)

0.39

GE

2.05 (15.48)

-0.0009 (-2.39)

0.27

Independent Variable

GCF

Dependent Variable

GCF

RQ → -287.25 (-2.18)

625.91 (5.26)

0.64

RL

GCF → 1.27 (26.77)

0.0003 (2.90)

0.35

GE

GCF → 1.27 (4.3)

0.0004 0.66)

0.02

CC→ 1393.55 (7.07)

-468.85 (- 4.51)

0.57

Independent Variable

RQ, GCF

Dependent Variable

GCF GCF

RQ → 95.02 (0.30)

278.85 (1.31)

0.10

GCF

RL → -942.47 (-1.61)

-1332.24 (2.83)

0.34

Independent Variable

CC, RQ, RL

Dependent Variable

GCF

CC → -283.41 (-0.32)

-3606.16 (-1.96)

0.34

GCF

GE → 375.35 (5.66)

1165.75 (1.60)

0.14

Independent Variable

CC, GE

Dependent Variable

CC

-0.33 (-9.48)

-0.0005 (-2.83)

0.34

Independent Variable

GCF

Dependent Variable

CC

GCF→ 0.63 (1.2)

0.0005 (1.13)

0.07

GCF

CC→ 902.39 (5.51)

151.74 (1.13)

0.28

RQ

GCF→ 0.93 (1.53)

-0.000027 (-0.48)

0.0001

GE

GCF → 0.29 (3.80)

0.0003 (0.30)

0.006

Independent Variable

GCF, CC

Dependent Variable

GCF

RL → 64.90 (12.22)

-59.26 (-3.80)

0.49

GE

GCF→ 0.24 (3.80)

-0.0003 (0.30)

0.006

Independent Variable

RL,GCF

Note: t for significance at 5% level of d.f

influences GCF. It is justified that growth rate of GCF of a nation would sound good as government’s ability to formulate market-friendly policy regulations for the development of private sector is being noticed. Causal relationships between GCF and governance indicators are absolutely different in Germany as compared to USA, UK and France; almost opposite picture is noticed to speak of. Here the variations of CC and RL

are causing the variation of GCF in the negative direction. Paradoxically it is observed that GCF is reduced by 468.85 billion US dollar as CC index is enhanced by one unit, similarly, GCF is reduced by 1332.24 billion US dollar as RL index is enhanced one unit. Perhaps ongoing network or state machineries for controlling degree of corruption in the field of investment discourages investors, and at the same time investors perhaps

149

 Governance and Capital Accumulation under Globalization

Table 6. Quantifications of impact of explanatory variables on explained variables Country South Africa

Brazil

Nature of the Variables Dependent Variable

Intercept

Slope

R2

CC

GCF→ 0.82 (10.08)

-0.10 (-6.02)

0.70

RQ

GCF→ 0.55 (7.6)

-.0013 (-0.81)

0.40

GCF

RQ→ 58.71 (2.77)

-33.59 (-0.81)

0.04

GE

GCF→ 0.47 (3.17)

-0.0047 (-6.70)

0.01

Independent Variable

GCF, RQ

Dependent Variable

GCF

CC→ 212.90 (6.26)

187.86 (0.47)

0.01

RL

GCF→ -0.45 (-10.28)

0.00076 (4.29)

0.55

GCF

GE→ 139.96 (7.08)

-185.18 (-6.70)

0.75

GE

GCF→ 0.47 (3.17)

-0.004 (-6.70)

0.75

RQ→ 0.64 (6.19)

0.0029 (1.39)

0.11

Independent Variable Greece

Name of the Variables

CC, GCF, GE

Dependent Variable

GCF

Independent Variable

RQ

Note: t for significance at 5% level of d.f

feel uncomfortable for investment because of stringent policy formulation. The scenario of cause-effect in Japan is almost similar to the USA and UK except the magnitude of variations of explained variables. Despite the strong by-directional relationships between explained and explanatory variables, further discussion is not required as the coefficients are statistically insignificant. Our empirical results for Greece show that there is a causal relation from RQ to GCF, but insignificant coefficient does not provide any scope for discussion. So, quality of governance is not important factor so far as gross capital formation is concerned in Greece. In China, our empirical results show that there are causal relations from CC to GCF and GE to GCF, governance quality matters so far as GCF is concerned. Gross capital stock is increased by 3606.16 billion US dollar when CC index is decreased by one unit. So, would China exempt corruption for the sake of investment? In contrast, GCF is enhanced by 1165.75 billion US dollar as GE is increased by one unit. It signifies that as state corruption controlling machineries become

150

compact or stringent, GCF of the state is proved to be reduced. The result is partially similar to the result of Germany. The positive association between GCF and GE is justifiable even in the developing country like China because private investors become proactive for investment as investors face market-friendly atmosphere with the tight policy of GE. GCF negatively causes CC at the rate of 0.0005 in India. It means higher and higher the value of GCF, lower would be the value of index of corruption controlling machineries. Perhaps it could be justified by the fact that private corporate sector may illegally provokes policy makers at the government level to relax rules and regulations so that investors could enjoy the benefits or there may be a hidden trade-off between policy makers and investors that forces CC index to move downward direction in the face of rising trend of GCF. In Thailand, causal relations from RL to GCF and GCF to GE are observed. But negative association between GCF and RL reveals the fact that GCF is increased by 59.26 billion US dollar when RL index decreases by one unit. Rule of

 Governance and Capital Accumulation under Globalization

Law may not be conducive to the investors in the age of globalization. Besides this, the relationship between GE and GCF is insignificant. The negative causal relation from GCF to CC is noticed, rise in GCF makes the state level corruption controlling system more lurid, and bilateral causal relations between GCF and RQ have no importance since they are insignificant in South Africa. Again a negative causal relation from GCF to GE is empirically established in South Africa construing urgency of relaxations of GE policies for the sake of investment. In Brazil, there prevails an insignificant causal relation from CC to GCF whereas we observe a significant positive causal relation from GCF to RL. It implies government tightens the machineries of RL as GCF of the country increase. Again there are bilateral causal relations between GCF and GE in negative direction; GE falls as GCF rises and GCF rises as GE falls. May be other factors of determining GCF matter much compared to GE.

CONCLUDING REMARKS The study so far we have made is now in a position to conclude. Good governance does not always mean better growth rate of GCF even in developing nation. In USA, in reverse way, some indicators negatively influence GCF and enhancement of GCF is at least in one way complementary to the governance in United States as far as betterment of RL is concerned. UK government is not capable to control corruption as well as it also fails to introduce time-relevant GE policies even in the face of rising trend of GCF. In France, it sounds good that RQ positively influence to the growth rate of GCF whereas RL improves slightly with the rise in GCF. In contrast, all governance components except GE in Germany either positively or negatively determine GCF; tight polices of CC and RL force GCF to fall. The scenario of developing nations is quite different. GCF increases

phenomenally as China pampers corruption by relaxing corruption controlling machineries. The positive causal relation from GE to GCF is justifiable even in the developing country like China because private investors become proactive for investment as investors face market-friendly atmosphere with the tight or time-relevant policy of GE. Rising trend of GCF forces corruption level to be rampant in India. Tightening of RL induces investors not to invest in Thailand and a relaxation of GE policies for the sake of investment is only an option. Rise in GCF makes the state level corruption controlling system more lurid, and urgency of relaxation of GE policies is pronounced for the sake of investment in South Africa. It is observed that Brazil government tightens the machineries of RL as GCF increases. A bilateral causal relation between GCF and GE in negative direction signifies relaxation of GE as an aftermath for future investment. The overall finding is that there is an inverse relation between governance indicators and capital accumulation for majority of the developing countries and in some cases positive relations for developed countries. It is observed that there are causal relations from capital formation to governance in most of the developed countries whereas in most of the developing countries there are causalities from governance to capital formation. The deviations from the natural outcome of the interdependence between governance and capital formation may have been by the occurrence of the global financial crisis.

REFERENCES Aldrighi, D., Kalatzis, A. E., & Pellicani, A. (2011). The impact of corporate governance and financial constraints on firm’s investment decisions: Evidence from Brazil. Retrieved from www. scienpress.com/Upload/JFIA/Vol%201_2_2.pdf

151

 Governance and Capital Accumulation under Globalization

Amighini, A., Rebellotti, R., & Sanfilippo, M. (2011). China’s outward FDI: An industry-level analysis of host country determinants. Economic proceedings of the CESifo Conference, china and global Economy Post Crisis, 18-19 July Venice International University. Batra, G., Kaufmann, D., & Stone, A. H. W. (2001). Voice of Firma 2000: Investment Climate And Governance Finding of the World Business environment Survey. World Bank. Bohren, O., Cooper, I., & Priestley, R. (2006). Corporate governance and real investment decisions, 1-29. Retrieved from http:finance.bi.no./~bemt/ governance/wp_Investment.pdf

Emery, J. J. (2003). Global forum on International Investment. Johannesburg, South Africa, Government of South Africa, Encouraging Modern Governance and Transparency for Investment: Why and How? 17-18 November Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross spectral methods. Econometrica, 37(3), 424–438. doi:10.2307/1912791 Jalilian, H., Krikpatrick, C. & Parker, D. (2006). The Impact of regulation on Economic Growth in Developing Countries: A Cross-Country Analysis. Final Revised version 20 March 2006

Businessweek. (1993). The Destructive Costs of Greasing Palms. Retrieved from http://www. bloomberg.com/bw/stories/1993-12-05/thedestructive-costs-of-greasing-palms

Julia, D., Desborders, R., & Wooten, I. (2010). Does public governance always matter? How experience of poor institutional quality influences FDI to the South. Dissuasion paper 7533. London: Center for Economic Policy Research.

Chang, Y.W., Chang, R, D. & Wei, J.T. (2008). The effects of corporate governance mechanisms on investment decisions, 1-16. Retrieved from http:scholar.googleusercontent

Kajola, S. O. (2008). Corporate governance and firm performance: The Case Nigerian listed firms; European Journal of Economics. Finance and Administrative Sciences, 14, 16–22.

Claessens, S. (2006). Corporate governance and development. The World Bank Research Observer, 21(1), 91–122. doi:10.1093/wbro/lkj004

Kauffman, D., & Kraay, A. & Zoido-Lobaton. (1999). Governance matters. World Bank policy working paper no. 2196, World Bank, Washington DC.

Cuervo-Cazurra, A., & Genc, M. (2008). Transforming to disadvantages into advantages: Developing-country MNEs in the least developed countries. Journal of International Business Studies, 39(6), 957–979. doi:10.1057/palgrave. jibs.8400390 Das, R. C. (2013). Is Governance a Precondition to Growth? A Study of Selected Countries in the Globalized World. In Martinez, ... (Eds.), Managing Scarcity: Participation, Territories and Welfare State. Madrid, Spain: GOGEP Complutence. Dixit, A. (2012). Governance, Development, and Foreign Direct Investment. Max Weber Lecture No.2012/01

152

Kaufmann, D., Kraay, A., & Massimo, M. (2005). Governance Matters IV: Governance Indicators for 1996-2004. Retrieved from http://www. worldbank.org Keynes, J.M. (1960). General Theory of Employment, Interest and Money, Volume III of the collected writings of J.M. Keynes. London, McMillan Khan, M. H. (2007). Governance, Economic Growth and Development since 1960s. DESA Working Paper No. 54 Krueger, A. O. (1990). Government failure in development. The Journal of Economic Perspectives, 4(3), 9–23. doi:10.1257/jep.4.3.9

 Governance and Capital Accumulation under Globalization

Leff, N. (2002). Economic Development through Bureaucratic Corruption. In A. Heidenheimer & M. Johnson (Eds.), Political Corruption: Concepts and Contexts (p. 312). Transaction Publishers.

Steven, G., & Shapiro, D. (2002). Global foreign direct investment flows: Role of the governance infrastructure. World Development, 30(11), 1899– 1919. doi:10.1016/S0305-750X(02)00110-9

Mauro, P. (2002). The Effects of Corruption on Growth and Public Expenditure. In A. Heidenheimer & M. Johnson (Eds.), Political Corruption: Concepts and Contexts (p. 343). Transaction Publishers.

Stiglitz, J. (1998). Private uses of public interest: Incentives and institutions. The Journal of Economic Perspectives, 12(2), 3–22. doi:10.1257/ jep.12.2.3

Nakata, T. (1979). Corruption in the Thai bureaucracy, who gets what, how and why in its public expenditures. Thai Journal of Public Administration, 18, 102–128. Parker, D. (1999). Regulation of privatized public utilities in the UK: Performance and governance. International Journal of Public Sector Management, 12(3), 213–235. doi:10.1108/09513559910267387 Philippine Government Reuter Newswire. (1997). Philippine Corruption a Nightmare. 11 January, visit www.benaston.com Ruiz-Porras, A., & Lopez-Meteo, C. (2011). Corporate governance, market competition and investment decisions in Mexican manufacturing firms. Middle Eastern Finance and Economics, 10. Sachs, J., McArthur, J. W., Schmidt-Traub, G., Kruk, M., Bahadur, C., Faye, M., & McCord, G. (2004). Ending Africa’s poverty trap. Brookings Papers on Economic Activity, 1(1), 117–240. doi:10.1353/eca.2004.0018 Stephen, K., & Philip, K. (1995). Institutions and economic performance: Cross-country tests using alternative institutional measures. Economics and Politics, 7(3), 207–227. doi:10.1111/j.1468-0343.1995.tb00111.x

KEY TERMS AND DEFINITIONS Correlation Coefficient: It is concerned with the strength or degree of association between a bivariate data set. The degree of such association is measured by Coefficient of Correlation. If X and Y be two variables with combinations of observation (x1, y1), (x2, y2)……. (xn, yn) then the Coefficient of Correlation given by Pearson formula is rxy = Cov (x, y)/S.D (x). S.D(y). If X and Y are positively correlated then rxy is positive and if they are negatively correlated then rxy is negative. If there is linear upward and down ward association between the two variables then we get perfect or linear correlation with the values of rxy is +1 and -1 respectively. Financial Crisis: The financial crisis happened in United States in 2007-08 because banks were able to create too much money, too quickly, and used it to push up house prices and speculate on financial markets. Housing bubble and lending crunch that proceeded. Americans wooed by collapsed lending standards, a situation magnified many times over the years around the world. Globalization: Intensification of cross-border movement of goods, services, technologies and capital. It is a process of international integration

153

 Governance and Capital Accumulation under Globalization

as a result of unprecedented acceleration in the flow of trade, assets, technology, information and ideas across the national boundaries. Governance Indicators: It is the measure of governments’ performance. According to World Bank, there are six components of governance of a country. They are Voice and Accountability, Political Stability, Regulatory Quality, Rule of Law, Governments’ Effectiveness and Control of Corruption. Granger Causality: See methodology section for brief definition of the term. Gross Capital Formation: It is the addition to stock of capital generated from private as well as public savings. In Keynesian economics capital

154

formation or investment is a driving force in economic growth. It can affect the output by means of Acceleration Principle. It has two parts-real and financial. Out of the real or physical investment there are again two parts-gross and net investments. Regression: It is a method of projection of a dependent variable for a specific value of an independent variable. If y is dependent and x is independent variables with y* and x* as their mean values then the equation (y-y*) = byx (x-x*) is called Regression Equation of y on x, where byx is known as regression coefficient determined by variances of y and x and correlation coefficient.

155

Chapter 8

Corruption, Size of Government, and Economic Growth:

Evidence from Global Data Qaiser Munir Universiti Malaysia Sabah, Malaysia

ABSTRACT A big size government fosters corruption, which can lead to inefficiencies and resource costs that impede economic progress. In this chapter, it is argued that much of the previous studies have focused only on detecting the linear effects of corruption on growth. This study, therefore adopts the Threshold Autoregression (TAR) approach by using an annual panel data of 100 countries during 1990-2012 to evaluate any existence of a non-linear relationship. This study presents evidence that suggests the existence of a hump shaped (nonlinear) relationship between corruption and long-run economic growth. When the government size is small (11.518%), corruption positively affects economic growth. Whereas, when the government final consumption expenditure (% of GDP) is larger than 19.027%, corruption negatively affects economic growth. Furthermore, the result indicates that a non-linear relationship of the ‘Armey curve’ exists in our panel of countries. Thus, a government should investigate whether government size is over-expanding or not when designing its public finance policy.

INTRODUCTION The growing concerns that high levels of corruption might reflect detrimental effects on economies have motivated a large amount of academic and policy-oriented research.Corruption happens and it happens across the countries. A lingering debate that still provides a powerful research motivation

is whether corruption greases or sands the wheels of economic growth (Bardhan 1997; Pande 2008; Aidt 2009). Recent research has moved beyond simplyanalysing the direct effects and has tried to evaluate how corruption affects the relationship between size of government and economic growth. Government’s role in the economy is extremely crucial, as it is reflecting the responsibility in

DOI: 10.4018/978-1-4666-8274-0.ch008

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Corruption, Size of Government, and Economic Growth

policy making aimed at achieving economic stability and growth. Precisely, the presence of a government is essential to provide policy guidance and enforce regulation in ensuring the wellfunctioning of the entire economic system. Good governance will strengthen the whole system of an economy, and in turn supports a country’s sustainable economic growth. This point is consistent with Blackburn, Bose, and Emranul (2006: 2448) who claim that, “good quality governance is essential for sustained economic development”. Nevertheless, it is a fact that the role of government which is vital to an economy can be jeopardized by the arising problems of corruptions, as well as the size of a government which is considered too large. These obstacles appear to be serious policy concerns and challenges in both developed and developing countries, especially in countries that exhibit large government expenditures incompatible to the economic growth, and also in nations that their economies are harmed by the critical state of corruptions involving a large number of civil servants. In its simplest form, public sector corruption is a concept uniquely signifies the abuse of public power for private benefit (Tanzi, 1998). This concept is broadly defined as the abuse of authority by bureaucratic officials who exploit their powers of discretion delegated to them by the government, to further their own interests by engaging in illegal or unauthorized rent-seeking activities (Blackburn, Bose & Emranul, 2006). Public sector corruption refers to any unlawful arrangements or practices which feature the manipulation of public authorization power motivated by illicit incentives to both public and private agents. Some common forms of public sector corruption are such as bribery, patronage, trading in influence, kickbacks, coalition for hidden gain, electoral fraud, and others. Public sector corruption is detrimental to a nation’s governance quality, as the involvement of civil servants in corrupt practice directly leads to bureaucratic malpractice in various aspects, including the official duties of high-level policy

156

making, regulation enforcement, immigration affairs, the provision of public goods, tax collection, government expenditure, the granting of new infrastructure projects, as well as licensing. Obviously, public sector corruption put a nation and its economy to risk. What are the causes of public sector corruption? Perhaps the causes are due to various factors. Public sector corruption occurs because of the motivation of the parties involved in obtaining illicit incentives. Blackburn, Bose and Emranul, (2006) mention that corruption appears from the incentives of both private and public agents in conspiring to conceal information from the government. There are other specific dimensions of the causes of public sector corruption. Tanzi (1998) suggests two main groups of factors. First, the factors that affect the demand by public, including regulations and authorizations, particular characteristic of the tax systems, particular spending decisions, and the provision of public goods below their market prices. Second, the factors that influence the supply by government officials, which include bureaucratic tradition, wage levels in the public sector, the penalty systems, institutional controls, transparency of laws and procedures, and also the examples reflected from leadership. Furthermore, economists reveal that institutional features can stimulate public sector corruption. A country which has good quality of democratic political institutions will allow its citizens to elect a right party, which is able to deter corruption and bring sustainable growth to the country’s economy (Aidt, Dutta & Sena, 2008). As this point is concerned, press freedom is addressed as a complement to democratic election in the effect on corruption determent (Kalenborn & Lessmann, 2013). Moreover, Goel and Nelson (2010) have postulated the factors of history, geography, and government in relation with public sector corruption. Historical influence is based on the view that history is essential in shaping the culture norms, which in turn determines the undertaking of corruption. The consideration of geography factor reflects

 Corruption, Size of Government, and Economic Growth

the opinion that, more spread out of nations will possibly leads to increase corruption, due to the difficulty in monitoring government officials in dispersed locations, and also because of the problem arising from the situation featuring prisoner’s dilemma (Goel & Nelson, 2010: 434). There are several logics that explain about government factor. As government size is concerned, most importantly it is predicted that when the size of a government is bigger, it is likely to cause increase corruption due to greater extent of bureaucracy and corrupt opportunities (Goel & Nelson, 2010: 436). Indeed, many angles of consideration can be further studied on this topic. Above all, the foreseeable adverse effects on economic growth given by public sector corruption, and government size which is incommensurate with the size of an economy shall not be disregarded. The present study reflects strong belief in the potential negative effect of larger government size on the level of public sector corruption. This will be addressed in the present study in a way that government size is treated as a threshold indicator in the correlation between corruption and economic growth. The purpose of this study is twofold: First, to revisit the impact of corruption with a focus on global data using a nonlinear panel modeling framework to investigate empirically the existence of a threshold effect in the size of government on economic growth. Specifically, this study attempts to determine if an optimum size of government exists under which corruption produces growth or above which corruption become ineffective or even growth-limiting. The second issue deals with the possibility of empirically verifying the existence of the so-called ‘Armey curve’ in the context of global data. The Armey curve, as defined in the literature, claims an inverted U-shaped relationship between government size, i.e., government expenditure as a percentage of GDP, and economic growth. Over the last decade the phenomenon of the Armey curve has been empirically established for the single countries, such as United States and

many other countries, but it has hardly been investigated in the context of developed and developing countries. The Armey curve provides the possibility of calculating optimal government expenditure percentages, and therefore may well be used as a policy tool in determining the efficient levels of government expenditure. Rather than merely supplying yet another evidence of the existence of the Armey curve for an additional country or period, it is interesting to know if the result from this study is consistent with the related empirical literature. The aim is actually to understand, in the light of our finding, the diversity of sometimes contradictory results of the studies on the relationship between corruption, government size and economic growth.A threshold could allow the effect of corruptionon GDP growth based on the size of government. Hansen (1999) argues that the threshold model is an interesting alternative when there are no theoretical models predicting a clear threshold. Our intention here is not to build a theoretical model with a threshold effect of size of government, but to simply investigate empirically whether such a possibility exists and, if so, to produce estimates of the thresholds. Following the literature, a natural threshold variable: government final consumption expenditure (% of GDP) is considered.

THEORETICAL BACKGROUND The linkages of corruption, government size, and economic growth, or other associations with any two of them, are plausibly explained by a number of economists. These theories have been applied in forming the central hypothesis of a research in this area of study. Firstly, literature shows the feasible growthreduction effect of corruption. According to Aidt, et al. (2008), the two variables are related and the correlation is subject to the variation in different governance regimes. Generally, it can be differentiated between the regimes with

157

 Corruption, Size of Government, and Economic Growth

high and low qualities of political institutions. The author mentions two specific features of the regime with high quality political institutions. In that regime, it is possible for citizens to use threat of replacement to reduce corruption. As far as when economic growth is considered giving the incentives of rulers, economic growth can reduce corruption. Besides that, in that regime, it is also possible that corruption reduces economic growth. Thereby, the model proposed by the author allows for corruption and economic growth to be self-reinforcing and endogenous. There is also theory developed to reflect the idea of a corruption threshold, which it features the levels of corruption that are most damaging and causing much disadvantage to a nation’s economy. When the impact of corruption on public goods provision is concerned, it is most appropriate to apply the theory of corruption threshold proposed by Bose, Capasso and Murshid (2008). The theory describes that the process of public goods provision involves the supply from private vendors to a government. Information asymmetries enable private vendors to earn profits, which the profits can be redistributed to government bureaucrats. Corruption has the likelihood to inversely affect the provision of public goods when the threshold is crossed. As such, corruption threshold would indicate the state of corruption which is considerable harmful to a country, and hence it signals immediate policy attention. Secondly, there are theories that assert the predicted links between government size and economic growth. Liu et al. (2008) apply the ideas of the Wagner’s Law and Keynesian’s theory to show two distinct causal relations between government expenditure and economic growth. In accordance with the Wagner’s Law proposed by Adolf Wagner, economic growth and government activity growth are positively related. It is interpreted in a way that higher economic growth leads to higher government activities, causing government expenditure to increase. The Keynesian’s view is apparently different from the underlying idea of

158

Wagner’s Law. In which, it affirms that government expenditure is likely to stimulate economic growth. Meanwhile, Vedder and Gallaway (1998) present the idea with regards to the Armey Curve developed by Richard Armey which is very much similar to the threshold approach. The Armey Curve depicts that the expansions in government size tend to enhance output when a government is small. As the size of a government grows larger, it can lead to output expansion. However, when reaching certain point, further expansions in government size will tend to result in declining output (see figure 1). Government contributions for regulation and up-keep of law and order further contribute to the growth of the economy by creating a safe economic atmosphere. Any expansion of government spending in the economy initially is associated with an expansion in output. Nevertheless, as spending rises, additional projects financed by the government become increasingly less productive. The excess infrastructure lowers benefits per dollar spent while higher tariffs de-motivate imports and exports. In addition, the taxes and borrowings levied to finance these disproportionate ventures impose increasing burdens, thus creating disincentives to workers. At some point, the marginal benefits from increased government spending reach zero. Theconstructive features of government begin to diminish when the adverse effects of big government result in a reduction of output growth. Further expansions of government contribute to a decline in output. Thus, policy makers need to ensure the outputenhancing feature of government size is always well-maintained. Thirdly, economists view there exist potential associations of corruption and the size of a government. On one hand, there is a belief that, as a government grows larger it can possibly lead to corruption through excessive bureaucracy or red tape (Goel & Nelson, 1998, 2010). Thus, larger size of a government is likely to induce higher corruption. On the other hand, some other economists believe corruption might be reducing government

 Corruption, Size of Government, and Economic Growth

Figure 1. Illustration of an Armey Curve

expenditure and thus government size. As Dzhumashev (2014) notes, government expenditure gives rise to public sector corruption, which in turn corruption distorts the size and structure of government expenditure. Following the activities of corruption, some productive resources of a country is exploited as incentives to corrupted public and private agents. For example, Mauro (1998) shows that corruption tends to reduce government spending in education and health. In addition, Bergh, Fink, and Öhrvall, (2012) seems to suggest corruption pressures might be high when there are limited government resources. Fourth, some economists explain how the concepts of corruption, government size, and economic growth can be linked together. As corruption might distort the size and structure of government expenditure, thus in low-income economies, higher government spending will likely to increase rent seeking activities and corruption, which in turn leads to government inefficiency and the decline in economic growth. Hence, the feedback associations between corruption and government size are plausible (Dzhumashev, 2014). Tanzi and Davoodi (1997) have offered specific arguments on how corruption can reduce economic growth through the channel of public sector investment

in a few different ways. Corruption can slower growth by enlarging public sector investment while decreasing the productivity of public investment, specifically by increasing public sector investment when it does not go along with its recurrent current expenditure, for example, operations and maintenance expenditure, by reducing the existing infrastructure, and also by decreasing the revenue received by government.

EMPIRICAL LITERATURE SURVEY At least four camps of empirical literature are considered important to the present study. These include the correlations of i) corruption and economic growth, ii) government size and economic growth, iii) corruption, government size and scope, and iv) corruption, government size, and economic growth. The following is the brief discussion of each category of the literature:

Corruption and Economic Growth Mostly previous studies aim to verify empirically whether corruption negatively affects economic growth. Furthermore, some researchers attempt to 159

 Corruption, Size of Government, and Economic Growth

offer reasonable explanations of such causality by postulating any feasible transmission mechanisms through which corruption might impact on growth. Moreover, it is also the interest of researchers to compare the causal relations between corruption and economic growth on cross-country basis by assessing the variations in different governance regimes. Mo (2001) demonstrates several transmission channels through which corruption renders negative impact on economic growth. His study applies a cross-country analysis and adopts the sample period from 1970-1985. In a comparison, finding indicates that political instability channel is most vital via which corruption can affect economic growth. By looking at the rate of productivity reduction, political instability channel accounts for about 64 percent, while approximately 28 percent is due to the channel of investment, and human capital channel results in about 9.7 percent. Mauro (1995) argue that corruption reduces investment across developing countries, thereby negatively affecting growth. Reinikka and Svensson (2004, 2005) find that corruption has detrimental effects on human capital accumulation. Aidt, Dutta, and Sena (2008) highlight the variations emerge from two distinct governance regimes when studying the negative impact of corruption on economic growth. This study considers separately the regime with high quality political institutions, and the regime with low quality political institutions, which the measure used to indicate the different regimes, is the voice and accountability index. As mentioned by the author, this index combines the measures of numerous aspects of political process, political rights, civil liberties, and the independence of media. Moreover, the index is utilized as the threshold indicator in the relationship between corruption and economic growth. Finding shows that corruption has a great negative impact on economic growth in the regime with high quality political institutions. While in the regime with low quality political institutions, there is no evidence of cor-

160

ruption impacts on economic growth. As such, this study suggests the existence of a regime specific impact of corruption on economic growth, and that is most detrimental to the regime with good quality political institutions. A later study by Kalenborn and Lessmann (2013) has extended the literature on the role of democracy in controlling corruption by implying press freedom as an important complement to the democracy role. The study provides the evidences for the period of 1996 to 2010, from using regression analysis applied to a cross-section of 170 countries, and also panel data analysis for 175 countries. Finding shows that the Vanhanen Index used to measure democracy has a negative impact on corruption reduction in countries exhibiting a low level of press freedom, while, in countries with high level of press freedom, democracy probably reduces corruption.

Government Size and Economic Growth The issue of government size in transition economies has been addressed by Gupta, Leruth, Mello and Chakravarti (2001). In which, the changes of government size in twenty-four transition economies are studied. The common indicators used, such as public expenditure in relation to GDP, and public employment as a share of population, consistently show the sign of a reduced size of government. However, some other indicators signal the opposite situation. Government size is considered still large indicated by the enlarging national indebtedness, noncash transactions, accumulation of arrears, and also heavy regulatory burden. Thus, when government size is concerned, it is unavoidable to take into account different dimensions of measurement. Past studies have provided evidences of the relationship between the size of a government and economic growth. Vedder and Gallaway (1998) find evidence for emerging countries to support the perception that the growth of government

 Corruption, Size of Government, and Economic Growth

increases the country’s output. The positive effect of government size on economic growth might be due to transaction costs reduction, and the upgrade of investment environment in terms of property rights and improved rule of law. Ram (1986) and Kormendi and Meguire (1986) also found a positive relationship between government size and economic growth. They write that expanding government size provides an insurance function to private property, and public expenditure can encourage private investment which will cause economic growth. Government expenditure provides the investment for public goods that will improve, in general, the investment environment. However, other study seems to suggest larger government size leads to reduce economic growth. Fu, Taylor and Yücel (2003) assess the relationship between fiscal policy and economic growth for the United States by using pair-wise combinations of fiscal indicators. Finding indicates that over the period of 1983-2002, the size or the expenditure of the country’s Federal government significantly slower economic growth. Dar and Amirkhalkhali (2002) found a negative relationship between government size and economic growth. They believe that expanding government size (government expenditure) has the effect of diminishing returns, and over-expanding government size will cause a crowded-out effect to private investment. In addition, government expenditure often turns into inefficient expenditure which will cause a distorted allocation of the resources as well as corruption. While expanding government expenditure, a government needs more taxes to support the expenditure, but expanding taxes will gradually damage the economy. Chen and Lee (2005) empirically found the nonlinear relationship between the government size and economic growth. For instance Chen and Lee (2005) used a threshold regression approach for testing a nonlinear relationship between government size and economic growth in Taiwan. They found different threshold value for different government size in Taiwan. Chen, Chen and Kim (2011) employ the

quantile regression methodology to investigate the relationship between government size and economic growth using a panel data set for 24 OECD countries. They found that the magnitude of the effect of government size on economic growth varies through the quantiles. When the economic growth is low, increasing the size of the government may have a positive effect and stimulate economic growth. However, as the economic growth rate increases, such an effect declines and has a negative effect on economic growth. Precisely, it is possible that the individual components of government expenditure have a different influence on economic growth. Liu, Hsu and Younis (2008) apply time series analysis and utilize Granger causality test to study the link between the United States Federal government expenditure and its economic growth, over a longer time span from 1947 to 2002. At the aggregate level, it is found that total Federal outlays cause gross domestic product (GDP) to grow. At the disaggregated level, findings show more insights of the causality. Among others, the main findings are: the association between GDP and national defence expenditure does not exist; a bilateral causality exists between GDP with physical resource expenditure, and also net interest payment; and a growing GDP is led by human resource investment.

Corruption, Government Size, and Scope This section emphasizes on the potential linkages between corruption and government size, as well as government scope. It is often previous studies use government expenditure to reflect the size of a government. Meantime, the degree of government intervention can represent government scope. Literature shows evidence of higher corruption is associated with larger size of governments. Goel and Nelson (2010) include a broad scope of study. It examines the impact on corruption with regards to government size using the proxy

161

 Corruption, Size of Government, and Economic Growth

of general government final consumption expenditure in percentage of GDP, government scope applying the indices of government intervention in the economy as indicators, government decentralization measured by Subnational Government/ population and Subnational Government/area, and also other history and geography factors. It applies data of about hundred countries and covers the sample period spanning 1995-2003. However, only main findings related to government factor are reported here. First, when government size enlarges, it is associated with less corruption, which it is probably caused by the effect of stronger institutions. This finding is very much consistent with Aidt, Dutta, and Sena, (2008), for the theoretical description that, the governance regime with high quality political institutions can be having less corruption, because its citizens are allowed to use threat for replacement to reduce corruption. Second, greater decentralization tends to reduce corruption, thus, government intervention particularly in the regulatory area is likely to increase corruption. Third, it is possible that any reduction in corruption brought about by larger government size is cancelled out by the corruption-enhancing effect of government intervention. Meanwhile, Bergh, Fink and Öhrvall, (2012) find that the idea of larger government size leads to greater bureaucracy and thus higher corruption is not supported empirically. Instead of that, this study gives weak evidence showing government size negatively causes corruption. This study suggests corruption pressures may increase due to limited government resources. In investigating the effect of government size on public sector corruption, this study applies the data obtained from a survey conducted in 2007 with participants of high-level politicians and government officials in 290 Swedish municipalities. Finding indicates a robust negative association between corruption and government expenditure. Furthermore, it is compatible with greater budget causality decreasing corruption.

162

Different from foregoing that shows how government size impacts on corruption, the correlation can also runs from corruption to government size. Literature also provides evidence of public sector corruption reduces government expenditure. The study of Mauro (1998) covers the time span 1970-1985 and assesses the relationship that links together corruption and the composition of government expenditure. The components of government expenditure studied include the main aspects of capital, education, health, defence, and also transportation. By applying a cross-country analysis, strong and robust finding is obtained indicating corruption lowers government spending on education. As education appears to be a key determinant of economic growth, this finding is considerable significant to the economic growth concern. Public goods provision appears as an important component of government expenditure. As such, it is considered affecting government size. The particular corruption threshold of public goods provision is empirically verified by Bose, Capasso and Murshid (2008). This study finds strong evidence of the corruption threshold in terms of public goods provision from a sample of 125 countries, over the period 1990-2000. The aspect of public goods provision studied is the quality of the stock of public infrastructure, including the measures of the quality of electricity distribution, the quality of roads, and the quality of water supply. Public goods include the basic infrastructures collectively needed to support the well-function of an economy. This justifies the use of the corruption threshold in policy making.

Corruption, Government Size, and Economic Growth Tanzi and Davoodi (1997) find evidence showing corruption has a negative impact on economic growth by reducing the productivity of public sector investment. Since public sector investment

 Corruption, Size of Government, and Economic Growth

appears as a component of government expenditure, the extent of its allocation affects the size of a government. This study applies regression analysis to examine the relationship between corruption with several variables, including public sector investment, government revenue, operations and maintenance expenditure, and quality of infrastructure, using cross-country data for the period of 1980-1995. It is found that higher corruption is associated with larger public sector investments, but smaller government revenues, operations and maintenance expenditures, and also quantity of public infrastructure. In addition, finding indicates corruption increases public sector investment, but decreases its productivity. In that sense, the negative impact on economic growth is justified. Hence, this study implies high corruption countries shall limit the spending on public sector investment. While the growth-reduction effect of corruption is well-maintained, Monte and Papagni (2001) study whether corruption is a potential factor causing the limited policy success for Southern Italy development. This study covers the period of 1963-1991 and applies time series data of twenty Italian regions. Panel data approach is employed to estimate the effect of corruption on the productivity of public investment expenditure. From the finding, two different negative effects on economic growth caused by corruption are evident, namely the effect on private investment, and also the effect on the efficiency of public investment expenditure. This study points to the need of policies aimed at deterring corruption, and also improving the efficiency of public institutions. A study by d’ Agostino, Dunne and Pieroni, (2012) emphasizes on how the effect of individual components of government expenditure on economic growth is influenced by the quality of governance. In which, military spending and government investment spending are two components considered. For analysis, this study includes twenty-two African countries and covers the period of 1996-2007. The important finding arisen from

the study is that, economic growth is strongly affected by the interaction between military burden and corruption. Meantime, the interaction between government investment spending and corruption is giving a weaker effect. In sum, corruption can increase the negative effect given by military spending on economic growth. As for policy recommendation, this study proposes for the use of combined policies directed at deterring corruption and lowering military burdens. The latter might be possible through regional security agreements.

RESEARCH METHODOLOGY In this section, the general econometric framework developed by Hansen (1999) that supports our empirical work is described. Hansen’s (1999) panel threshold regression model is an extension of the traditional least squared estimation method. Threshold regression models allow individual observations to be divided into regimes based on the value of an observed variable. Firstly introduced into univariate time series context (Tong, 1983), the seminal paper of Hansen (1999) introduced the econometric techniques appropriate for threshold regression with panel data. Allowing for fixed individual-effects the PTR model divides the observations into two or more regimes depending on whether a threshold variable is smaller or larger than a threshold value, and these regimes are distinguished by differing regression slopes.

Estimation This chapter hypothesizes that there exists threshold effect between the size of government and economic growth. It is important to determine whether there is threshold effect or not.From panel data of a dependent variable yit, (in our case economic growth, GDPGR) a vector of regressors xit, a threshold variable qit, (size of government) and a threshold valueof γ , the structural equation of interest is specified in the following eq. (1):

163

 Corruption, Size of Government, and Economic Growth

yit = αi + β1' X it I (qit ≤ γ )β2' X it I (qit > γ ) + εit



(1)

In this expression, the sample is divided into two regimes distinguished by different regression slopes β1 and β2. I(.) is the indicator function that defines the sample splitting, and εitis independent and identically distributed (i.i.d.) error term with mean zero and finite variance .The term αiis a permanent but unobserved fixed effect. It captures cross-sectional unobserved heterogeneity due to differences in technology between countries and also all other determinants of the variability in yit not already controlled in Xit. It is easy to see that the point estimates for the slope coefficients β’s are dependent of the given threshold value γ . Since the threshold value is not previously known and it is supposed to be endogenously determined, Hansen (1999) recommends a grid search selection of γ that minimizes the sum of squared errors (SSE) obtained by least squares estimates of equation, i.e. γˆ = arg min s1 (ˆ) γ = εˆit (ˆ) γ ’ ∗ εˆit (ˆ) γ

(2)

Moreover, it is undesirable for a threshold γ to be selected which sorts too few observations into one or the other regime, and so, it is also suggested that the search for the SSE minimizing threshold value to be restricted by eliminating the smallest and largest η%values of the threshold variable qitfor some η>0. For convenience, Hansen (1999) suggests that it might be desirable to impose some restrictions on the threshold variable in order to obtain a minimum percentage of observation (5%) in each regime.

Testing for a Threshold After the estimation of the endogenous threshold γˆ ,it is necessary to test whether or not thethreshold effect is significant. The null hypothesis of this test is written as H0 = β1= β2. However, as

164

the threshold γ is not identified under the H0, classical tests have non-standard distributions. At this point, Hansen (1996) suggested a bootstrap procedure to simulate the asymptotic distribution of the likelihood ratio test of eq. (3). Details about this procedure can be found at Hansen (1999, 350-1). The null of no threshold effect is rejected if the p-value obtained by the bootstrap procedure is smaller than the desired critical value. F1 =

S 0 − S1 (ˆ) γ δ2



(3)

where S0 is the SSE obtained from the estimative of (1) under the null hypothesis of no threshold, S1 is the SSE obtained from the panel threshold regression (PTR) estimative of (1), and δ2 is the residual variance of the PTR regression. Once the threshold effect is found to be significant, one would ask if the estimated γˆ is consistent for the true value of the threshold (γ0). To form confidence intervals for γˆ , Hansen (1999, p. 351) proposes the likelihood ratio (LR)statistic reproduced in equation (4), which under some technical assumptions has the critical values of 5.94, 7.35, and 10.59, at the significance levels of 10%, 5%, and 1%, respectively. Hansen (1999) argued that the best way to form confidence intervals for γ is to form the ‘no-rejection region’ using the likelihood ratio statistic for tests on γ . To test the hypothesis H0 = γ =γ0, we construct the testing model: LR1 (γ ) =

S1 − S1 (ˆ) γ δ2



(4)

Hansen (1999) pointed out that when

LR1 (γ 0 ) is too large and the p-value exceeds the

confidence interval, the null hypothesis is rejected. Besides, Hansen (1999) indicated that under some specific assumptions and H 0 : γ = γ 0 , LR1 (γ ) = d ζ , as n → ∞ , where ζ

 Corruption, Size of Government, and Economic Growth

is a random variable with distribution function,

(

)

2

P (ζ ≤ x ) = 1 − exp (−x / 2) .

The associated no rejection region can be graphically represented by drawing a flat line at

c (α) = −2 log(1 − 1 − α the desired confi-

dence level. It corresponds to the values of the likelihood that lie beneath the flat line. The slopes β1 and β2 have asymptotic normal distribution provided that the errors are normally i.i.d. This can be used for inference. The other regression slopes are unaffected and the usual normal asymptotic distribution can be applied for inference. Hansen (1999, 353) also extends the Panel Threshold Regression (PTR) model to test for multiple thresholds. The general approach is quite the same for the case of only two regimes, with just a few differences. The first one refers to the estimation procedure, which may be done by a three-stage (when there is only three regimes) sequential estimation of the two threshold parameters. The first stage refers to the same estimation procedure as presented for the single threshold model, which yields the first estimate γˆ1 . Fixing this threshold parameter, the second stage estimates the second threshold parameter γˆ2 minimizing the SSE of eq. (5). In the last stage, the first threshold parameter is re-estimated holding fixed the second threshold parameter. From this threestage sequential estimation results the asymptotically efficient estimator of the threshold parameters, γˆ1 and γˆ2 . Note that these estimators have the same asymptotic distributions as the threshold estimate in a single threshold model, which means that we can construct confidence intervals in the same way as we did before. yit = αi + β1' x it I (qit ≤ γ1 )β2' x it I (γ1 < qit ≤ γ ) + β3' x it I (γ2 < qit ) + εit

(5)

The second difference refe––rs to the inference over the thresholds estimates. When the null of no threshold is rejected with the F1 statistic, one needs a further test to discriminate between one and two thresholds. This test is done with a similar bootstrap procedure, but now simulating the distribution of the F2 statistic (Eq. 6). F2 =

S1 (γˆ1 ) − Sˆ2 (ˆ γ2 ) 2 δˆ

(6)

where S1 is the SSE obtained from the first-stage estimative, Sˆ2 is the SSE obtained from the secondstage estimative, and δˆ2 is the residual variance of the second-stage estimate.

DESCRIPTION AND SOURCE OF DATASET The study is based on a balanced panel data set over the period 1990-2012 for 100 developed and developing countries. High-income countries are categorized as developed countries and the countries that fall into the low-income, lower-middle-income, and upper-middle income categories are developing countries. The countries included are Albania, Algeria, Australia, Austria, Bahamas, Bahrain, Bangladesh, Belgium, Bolivia, Botswana, Brazil, Brunei Darussalam, Bulgaria, Burkina Faso, Cameroon, Canada, Chile, China, Colombia, Congo Rep, Costa Rica, Cote d’Ivoire, Cuba, Cyprus, Denmark, Dominican Republic, Ecuador, Egypt, El Salvador, Ethiopia, Finland, France, Gabon, Gambia, Ghana, Greece, Guatemala, Guinea, Guyana, Honduras, Hong Kong, Hungary, Iceland, India, Indonesia, Ireland, Israel, Italy, Japan, Jordan, Kenya, South Korea, Lebanon, Luxembourg, Madagascar, Malawi, Malaysia, Mali, Malta, Mexico, Mongolia, Morocco, Mozambique, Netherlands, New Zealand,

165

 Corruption, Size of Government, and Economic Growth

Nicaragua, Niger, Nigeria, Norway, Pakistan, Panama, Paraguay, Peru, Philippines, Poland, Portugal, Romania, Saudi Arabia, Senegal, Sierra Leone, Singapore, South Africa, Spain, Sri Lanka, Sudan, Sweden, Switzerland, Tanzania, Thailand, Togo, Tunisia, Turkey, Uganda, United Kingdom, United States, Uruguay, Venezuela, Vietnam, Zambia and Zimbabwe. Below is the discussion of the variable used to measure corruption and as well as other control variables. Except for the corruption index, democracy and Bureaucratic quality, all data are obtained from World Bank’s World Development Indicators (WDI CD-ROM, 2014). The corruption (Corr) data extracted from the International Country Risk Guide (ICRG) database1. The ICRG Index measuring corruption in government, based on subjective ratings by experts. Low ratings indicate that “high government officials are likely to demand special payments” and “illegal payments are generally expected at lower levels of government” in the form of “bribes connected with import and export licenses, exchange controls, tax assessment, policy protection, or loans”. Scale is from0 to 6. Data come in the form of monthly ratings; annual figure is the average of monthly ratings.The ICRG index is the most widely used indicator of corruption worldwide (ICRG, 2013). Government size (Gov) is measured as government final consumption expenditure (% of GDP). Its anticipated effect on growth is negative. Any rise in government spending means the use of sources in line with the interests of pressure and interest groups, rather than efficient use of sources. Government final consumption expenditure includes all expenditure by general government on individual consumption goods and services (e.g. in-kind transfers: schools, health care), and collective consumption goods and services (e.g. national defense). The economic growth measure (GDPGR) is calculated as the annual average growth rate of per capita GDP between two years. To strengthen our results, we also include different controlling vari-

166

ables in our standard cross-country growth equation to mitigate the specification error problem. The control variables are selected in accordance with the empirical growth literature, see e.g. Barro (1991) and Islam (1995). In particular, we use seven controlling variables. The conditioning set of variables consists of the (logarithm of) initial real per capita GDP (gdp0) to control for convergence hypothesis. The other variables included are gross fixed capital formation (invest) to capture the effect of investment share. It is expected that investments have a positive effect on growth. The population growth rates (popgr), it is expected that population growth have a negative effect on growth. The variable life expectancy (lifexp) is also includedto control for the impact of human capital accumulation. Human capital accumulation is one of fundamental determinants of economic development. Life Expectancy symbolizes average life duration. The measure of life expectancy is treated as an indicator of a healthy life and rising productivity of individuals. In this sense, it makes a positive effect on growth. The scale of openness of the economies is also one of the factors influencing economic growth. Trade openness (open) is an index derived from the division of foreign trade volume to GDP [(export + import)/ GDP]. It shows outward openness of countries. Its expected effect on growth is positive. According to comparative advantages theory of Ricardo, free trade will result in more outputs thanks to efficient use of sources There is a lively debate on the relation between democracy and economic growth. One group of studies presents empirical evidence that democracy stimulates economic growth (Chong & Calderon, 2000; Kaufmann & Kraay, 2002). Other studies, however, provide evidence for a negative relationship between governance, democracy and economic development (Quibria, 2006)2. Furthermore, Democratic countries might face lower degrees of corruption as corrupt officials/politicians face the threat of losing public office. In contrast, there might be some unique rent-seeking oppor-

 Corruption, Size of Government, and Economic Growth

tunities in less democratic countries (Kunicová, 2006). Keeping in mind this, we added “democ” variable in the growth regression. The variable “democ” signifies the democracy index that is used for comparing countries with each other, and coding and rating administrative characteristics of the countries. Index values are extracted from The Center for Systemic Peace (CSP) within the scope of Polity IV Project. Countries are coded with 21 scores ranging from “-10” to “+10” in terms of their political system and administrative type in polity data set. It is expected that it will make a positive and/or negative or no effect on growth. Lastly, the bureaucratic quality variable (bureau) is included in the growth regression. Bureaucracy quality index measuring institutional strength and quality of the bureaucracy, based on subjective ratings by experts. High ratings are given to countries where “the bureaucracy has the strength and expertise to govern without drastic changes in policy or interruptions in government services”, and where “the bureaucracy tends to be somewhat autonomous from political pressure and to have an established mechanism for recruitment and training”. Scale is from 0 to 4.The data are extracted from the International Country Risk Guide (ICRG) database.

EMPIRICAL RESULTS The Number of Size of Government Thresholds In a first step, the Hansen’s (1999) sequential testing procedure for determining the number of thresholds based on the size of the government (GOV) is applied. The teststatistics F1, F2 and F3, along with their bootstrap p-values, are shown inTable 1.The results indicatethat the test for a single threshold F1 is highly significant witha bootstrap p-value of 0.000, and the test for a double threshold F2 is alsostrongly significant, with a bootstrap p-value of 0.049. On the other

Table 1. Tests for threshold effects based on size of government Test for No Threshold(H0: K = 0) F1

42.68

p-value

0.000

(10%, 5%, 1% critical values)

(22.38, 25.09, 29.59)

Test for One Threshold(H0: K = 1) F2

22.56

p-value

0.049

(10%, 5%, 1% critical values)

(19.72, 22.31, 30.63)

Test for Double Threshold(H0: K = 2) F3

11.67

p-value

0.876

(10%, 5%, 1% critical values)

(18.16, 20.45, 28.33)

Note: One thousand bootstrap replications were used to obtain the p-values. Following Hansen (1999), each regime is required to contain at least 5% of all observations.

hand, thetest for a third threshold F3 is not close to being statistically significant, witha bootstrap p-value of 0.876. It can be concluded that there is strong evidence that there are two thresholds in the regression relationship, and therefore the data can be classified into threedifferent regimes to analyze the dynamics of corruption if the government size is large, government size is mediumor the government size is small. The remainder of theanalysis is dealing with this double threshold model. The point estimates of the two thresholds and their asymptotic 95% confidence intervals are reported in Table 2. The threshold estimates are 11.518 and 19.027, which are small and large values in the empirical distribution of the (Gov) threshold variable. Thus the three different size of government indicated by the point estimates are those with ‘Government size is small, ‘Government size is large’ and ‘other (intermediate)’. The asymptotic confidence intervals for the

167

 Corruption, Size of Government, and Economic Growth

Table 2. Threshold estimates and confidence intervals Estimate

95% Confidence Interval

γˆ1

11.518 (%)

[11.110,11.760]

γˆ2

19.027 (%)

[18.440, 20.300]

threshold are very tight indicating little uncertainty about the nature of this division.The estimated optimal government size in this study is quite similar to the previous studies. For instance, Vedder and Gallaway (1998) find the optimal total government expenditure size of the United States as 17.5 percent of real GDP. They also infer the optimal government size of other OECD countries: 21.4 percent in Canada, and 21.0 percent in the United Kingdom. Chen and Lee (2005), on the other hand, using the quarterly data of Taiwan from 1979 Q1 to 2003 Q3 and confirm that all three classifications of government expenditure as a ratio to GDP: total government expenditure, government investment spending,

and government consumption expenditure, have threshold effects. The optimal government size found for these expenditures is 22.8, 7.3, and 15.0 percent, respectively. More information can be found about the threshold estimates from plots of the concentrated likelihood ratio function. Figure2 displays a graph of the normalised likelihood ratio sequence LR( γ ) when estimating a single threshold model. The point estimates are the value of γ at which the likelihood ratio hits the zero axis. The 95% confidence intervals for γˆ2 and γˆ1 can be found from LR2( γ ) and LR1( γ ) by the values of γ for which the likelihood ratio lies beneath the dotted line.Furthermore, Fig. 1 indicates that there may be a second dip in the likelihood ratio. Thus the single threshold likelihood conveys information that suggests that there may be a second threshold ( γˆ2 =19.027) in the regression. The graph for this second threshold is displayed in Figure 3. In view of the evidence in favour of two thresholds based on the size of the government, we estimated the following double-threshold model:

Figure 2. Threshold effect and confidence interval construction in double threshold model

168

 Corruption, Size of Government, and Economic Growth

Figure 3. Threshold effect and confidence interval construction in double threshold model

GDPGRit = αi + (δ1 + β1πit )I (πit ≤ γ1 ) + (δ2 + β2 πit )I (γ1 < πit ≤ γ2 ) + β3 πit I (γ2 < πit ) + εit

(22)

The estimates ( βˆ1 , βˆ2 , βˆ3 ) for the marginal impact of corruption (Corr) in the three government size regimes are shown in the Table 3. The threshold model reveals that corruption has a significant impact on economic growth (GDPGR). However, both magnitude and sign of the corruption coefficient depend on the size of government. When the size of government is low—i.e., government final consumption expenditure (% of GDP) is below 11.518 percent—the marginal impact of corruption on economic growth is significantly positive ( βˆ1 = 0.431) at the 5% level of significance. In fact, in the intermediate regime, when size of government is (11.518 19.027), the marginal impact of corruption is negative and statistically significant at less than 1% level.This finding is consistent with the results reported by Mauro (1995) and Barro (1997). The finding that corruption is negatively and significantly associated with economic growth is consistent with the view that corruption lowers the marginal product of capital (for example, by acting as a tax on investment proceeds). A sense of the economic importance of the coefficients can be obtained by predicting the change in long-run economic growth resulting from a decrease (worsening) in the corruption index. For countries with low levels of corruption, such as The Netherlands, Norwayand Sweden (corruption index near 6), such a worsening up to the growth-maximizing level of corruption implies an increase in long-run growth of 0.40 percentage points per year. For countries with average levels of corruption, such as Nigeria (corruption index of 3.1) and Pakistan

169

 Corruption, Size of Government, and Economic Growth

(4.4), an improvement (increase) in the corruption index would raise long-run economic growth by 1.66 and 0.85 percentage points per year respectively.Coming to the second objective of the study, whether Armey (1995) theoryholds or not in countries included in this study.The estimates ( βˆ4 , βˆ5 , βˆ6 ) of this exercise show very interesting results depending on the threshold levels. For instant, when the government size is small (the threshold value is less than 11.518%), total government consumption expenditure and economic growth (GDPGR) have a significantly (p-value = 0.037) positive relationship, but when the government size is large (the threshold value is larger than 19.027%), total government consumption expenditure and economic growth have a statistically significant (p-value = 0.040) negative relationship. However, this negative relationship is not statistically significant in the intermediate regime even at the 10% levels with positive sign. Thus, we can also say that the non-linear theory of the Armey curve exists in the selected countries of this study. All the other variables in the baseline model have the expected signs and are statistically significant at conventional levels. In particular, gdp0, invest, popgr, lifexp, and open are significant at less than 1% level and with correct signs. The democracy variable is estimated positive and significant at the level of 5%. In other words, democratic activities make a positive effect on growth in selected countries of this study. In contrast to this, the bureaucratic quality is estimated positive however, it is statistically insignificant. More democratic countries (Democracy) also experience lower levels of corruption.

CONCLUDING REMARKS There are two main issues examined in this chapter. First this study examines the role of government size in explaining the differences in economic growth rates. Second, issue addressed 170

Table 3. Regression estimates: double threshold model Coefficient

Std. Error

p-value

Regime-dependent regressors

βˆ1 (Gov ≤ 11.518)

0.431

0.183

0.018

βˆ2 (11.518 19.027)

-0.894

0.208

0.000

βˆ4 (Gov ≤ 11.518)

0.812

0.389

0.037

βˆ5 (11.518 19.027)

-0.736

0.358

0.040

Regime-independent regressors gdp0

-6.230

0.183

0.000

Invest

2.559

0.347

0.000

Popgr

-0.882

0.144

0.000

Lifexp

0.297

0.045

0.000

open democ bureau

3.413 0.312 0.047

0.475 0.157 0.124

0.000 0.047 0.704

Notes: Each regime contains at least 5% of all observations.

in this study pertained to the effects of the size of government on the incidence of corruption across 100 countries over the period of 1990–2012 using a panel threshold regression approach suggested by Hansen (1999) and Bick (2010). Overall, the answer to the first issue is that the optimal size of government gives significant influence on economic growth. Previous studies which test the relationship between government size and economic growth mainly use linear models and achieve inconsistent results. In a different way, this paper adopts the non-linear theory of Armey (1995) and Vedder and Gallaway (1998) to test whether a non-linear Armey curve exists in a panel of countries or not. This study uses a threshold

 Corruption, Size of Government, and Economic Growth

regression model and applies Hansen (1999) and Bick (2010) method to test the threshold effect in the size of the government. The empirical results indicate that threshold effects exist between government size and economic growth in the panel of countries when government sizeis adopted as the threshold variable. The two estimated threshold regimes are 11.518% and 19.027, classified as lowgovernment final consumption expenditure (% of GDP) is below 11.518% and large-government final consumption expenditure (% of GDP) is more than 19.027%.This indicates that there is a non-linear relationship of the Armey curve. When the government size is smaller than the regime, economic growth is promoted under expanding government expenditure, but if the government size is larger than the regime, then the economic growth decreases. There is important policy implication from the above results.Through this chapter’s analysis it is found that beyond the optimum government size, over-expanding on government expenditure will result in a negative effect on the economy. The optimum total government size in this study is found to be 19.027%, but actual total government consumption expenditure size in the global data were above than 19.027% (568 observations) during 1990-2012 period, which means that the expanding government size will actually damage the economy. For instance, in 2004 the total government consumption expenditure in Belgium, Botswana, Brazil, Cuba, Guyana and Sweden were 22.539, 20.532, 19.226, 35.479, 27.244 and 26.491 respectively. In order to deal with the debate of the relationship between government size and economic growth, this chapter secondly provides a threshold regression model to identify the threshold regime of government size in an objective way. This study also provides an empirical explanation of why this panel of countries continues to expand its government size to promote economic growth, but in the end achieves the opposite result. According to the theoretical explanation, Barro (1989) considers

that when government size is small, the summation effect of expanding government expenditure and increasing taxes has a positive impact to economic growth. However, when government size is large enough to exceed a standard, the summation effect of over-expanding government expenditure will cause damage to the economy. Barro (1989) also provides the concept of optimum government size which can be found objectively in this chapter. Therefore, trying to find the optimum government size and implementing the most effective allocation of government expenditure are actions that the government should pay attention to doing well. The government should be able to adjust its function to raise expenditure efficiency and save money from the budget by finding reasons that cause the difference between actual government size and the estimated government size. Abizadeh and Yousefi (1998) point out that “in many developing economies, the public sector absorbs a relatively large share of society’s economic resources and, therefore, affects economic growth”. They also indicate that government expenditures involve economic benefits and costs, and this means that while the costs exceed the benefits, expanding government size will damage an economic system. Ram (1986) also shows that a large government size is detrimental to efficiency and economic growth, because of (1) government operations are often inefficient, (2) the regulatory process imposes excessive burden and costs on the economic system, and (3) many of a government’s fiscal and monetary policies tend to distort economic incentives and lower the productivity of the system. Therefore, how to adjust the government to be at its optimum is important to the economy. While the government size is over-expanding, the economy will be damaged with inefficient use of limited resources as Ram (1986) indicates, but the government should actually cut the budget to the optimum government size as we provide. One must make sure that the benefits of expanding government size actually

171

 Corruption, Size of Government, and Economic Growth

exceed the costs, and this paper really provides an indicator of Taiwan’s optimum government size. Turning to the answer to the second question is that the size of government matters impact corruption. The past studies that have reported a linear relationship between corruption and economic development failed to differentiate between growth-enhancing and growth-reducing levels of corruption depending on the size of government. This study presents evidence that suggests the existence of a hump shaped (nonlinear) relationship between corruption and long-run economic growth. When the government size is small, corruption positively affects economic growth. Whereas, when the government final consumption expenditure (% of GDP) is larger than 19.027%, corruption negatively affects economic growth. The results of this study suggest that over-expanding government expenditure does not promote economic growth, but may cause damage to an economy, because of crowding effects or the increasing of taxes. Thus, a government should investigate whether government size is over-expanding or not when designing its public finance policy. If the government size is over-expanding, then a country should shrink its government size to increase the efficiency of government expenditures and promote economic growth.Theargument is that, although government consumption has no direct effect on private productivity (or private property rights), it lowers saving and growth through the distortion effects from taxation or government expenditure programs (Barro, 1991). Lambsdorff (2006) notes that the role of government can come into play in ways that can make corruption “hard to find” (Rose-Ackerman, 1999). For example, a large government might contribute to corruption by increasing red tape (Goel & Nelson, 1998) or promulgating regulations that induce individuals to seek illegal means to circumvent those rules (Graeff & Mehlkop, 2003). Biggovernment spawns corruption via bureaucrats manipulating spending in order to collect more

172

bribes (Li, Colin., & Zou, 2000). Furthermore, Corruption can increase the ability of agents to get resources from central and local governments. Therefore, public resources reward the more ‘able’ people, not the best entrepreneurs. Corruption can distort the composition of government expenditure as corrupt politicians may be expected to invest in large, non-productive projects from which it is easier than in productive activities to exact large bribes (Mauro, 1998). In fact, recently a number of studies (Fisman & Gatti, 2002; Goel & Nelson, 2005) point out that larger government size in fact leads to lower corruption. These results of the these studies suggest that it is not a large public sector, per se, that contributes to corrupt activity; larger governments may well be involved in greater spending on law enforcement and on implementing checks and balances to deter such activity(La Porta, Lopezde-Silanes, Shleifer & Vishny, 1999). However, greater regulatory activity in the public arena may foster more corruption by increasing the opportunities to engage in corrupt behaviour.Thus, the results of this study suggest that macroeconomic policy is also important as large government tendsto hurt economic growth.

REFERENCES Abizadeh, S., & Yousefi, M. (1998). An empirical analysis of South Korea’s economic development and public expenditures growth. Journal of Socio-Economics, 27(6), 687–700. doi:10.1016/ S1053-5357(99)80003-1 Aidt, T. (2009). Corruption, institutions, and economic development. Oxford Review of Economic Policy, 25(2), 271–291. doi:10.1093/oxrep/grp012 Aidt, T., Dutta, J., & Sena, V. (2008). Governance regimes, corruption and growth: Theory and evidence. Journal of Comparative Economics, 36(2), 195–220. doi:10.1016/j.jce.2007.11.004

 Corruption, Size of Government, and Economic Growth

Armey, R. (1995). The Freedom Revolution. Washington, DC: Rognery Publishing Co. Bardhan, P. (1997). Corruption and development: A review of issues. Journal of Economic Literature, 35(3), 1320–1346. Barro, R. J. (1989). A cross-country study of growth, saving, and government. Working Paper. No. 2855. National Bureau of Economic Research. Barro, R. J. (1991). Economic growth in a cross section of countries. The Quarterly Journal of Economics, 106(2), 407–443. doi:10.2307/2937943 Barro, R. J. (1997). Determinants of economic growth: a cross-country empirical study (2nd ed.). Cambridge: MIT Press. Bergh, A., Fink, G., & Öhrvall, R. (2012). Public sector size and corruption: Evidence from 290 Swedish Municipalities. IFN Working Paper. No. 938. Research Institute of Industrial Economics. Bick, A. (2010). Threshold effects of inflation on economic growth in developing countries. Economics Letters, 108(2), 126–129. doi:10.1016/j. econlet.2010.04.040 Blackburn, K., Bose, N., & Emranul, H. M. (2006). The incidence and persistence of corruption in economic development. Journal of Economic Dynamics & Control, 30(12), 2447–2467. doi:10.1016/j.jedc.2005.07.007 Bose, N., Capasso, S., & Murshid, A. P. (2008). Threshold effects of corruption: Theory and evidence. World Development, 36(7), 1173–1191. doi:10.1016/j.worlddev.2007.06.022 Chen, S. T., Chen, C. C., & Kim, Y. (2011). Economic growth and government size in OECD countries: New evidence from the quantile regression approach. Economic Bulletin, 31(1), 416–425. Chen, S.-T., & Lee, C.-C. (2005). Government size and economic growth in Taiwan: A threshold regression approach. Journal of Policy Modeling, 27(9), 1051–1066. doi:10.1016/j.jpolmod.2005.06.006

Chi-Hung, L. L., Hsu, C. E., & Younis, M. Z. (2008). The association between government expenditure and economic growth: Granger causality test of US data, 1947-2002. Journal of Public Budgeting, Accounting, and Financial Management, 20(4), 439–452. Chih-HL, L., Hsu, C., & Younis, M. Z. (2008). The association between government expenditure and economic growth: The Granger causality test of the US data, 1974-2002. Journal of Public Budgeting. Accounting and Financial Management, 20(4), 439–452. Chong, A., & Calderon, C. (2000). Causality and feedback between institutional measures and economic growth. Economics and Politics, 12(1), 69–82. doi:10.1111/1468-0343.00069 d’ Agostino, G., Dunne, P.J., & Pieroni, L. (2012). Government spending, corruption and economic growth. MPRA Paper, No. 38109. Dar, A., & Amirkhalkhali, S. (2002). Government size, factor accumulation, and economic growth: Evidence from OECD countries. Journal of Policy Modeling, 24(7-8), 679–692. doi:10.1016/S01618938(02)00163-1 Dzhumashev, R. (2014). The two-way relationship between government spending and corruption and its effects on economic growth. Contemporary Economic Policy, 32(2), 403–419. doi:10.1111/ coep.12025 Fisman, R., & Gatti, R. (2002). Decentralization and corruption: Evidence across countries. Journal of Public Economics, 83(3), 325–345. doi:10.1016/S0047-2727(00)00158-4 Fu, D., Taylor, L. L., & Yücel, M. K. (2003). Fiscal policy and growth. Federal Reserve Bank of Dallas Research Department Working Paper, No. 0301. Goel, R. K., & Nelson, M. A. (1998). Corruption and government size: A disaggregated analysis. Public Choice, 97(1-2), 107–120. doi:10.1023/A:1004900603583 173

 Corruption, Size of Government, and Economic Growth

Goel, R. K., & Nelson, M. A. (2005). Economic freedom versus political freedom: Cross-country influences on corruption. Australian Economic Papers, 44(2), 121–133. doi:10.1111/j.14678454.2005.00253.x Goel, R. K., & Nelson, M. A. (2010). Causes of corruption: History, geography and government. Journal of Policy Modeling, 32(4), 433–447. doi:10.1016/j.jpolmod.2010.05.004 Graeff, P., & Mehlkop, G. (2003). The impact of economic freedom on corruption: Different patterns for rich and poor countries. European Journal of Political Economy, 19(3), 605–620. doi:10.1016/S0176-2680(03)00015-6 Gupta, S., Leruth, L., Mello, L., & Chakravarti, S. (2001). Transition economies: How appropriate is the size and scope of government? IMF Working Paper, No. WP/01/55. Hansen, B. E. (1996). Inference when a nuisance parameter is not identified under the null hypothesis. Econometrica, 64(2), 413–430. doi:10.2307/2171789 Hansen, B. E. (1999). Threshold effects in nondynamic panels: Estimation, testing and inference. Journal of Econometrics, 93(2), 345–368. doi:10.1016/S0304-4076(99)00025-1 Hansen, B. E. (2000). Sample splitting and threshold estimation. Econometrica, 68(3), 575–603. doi:10.1111/1468-0262.00124 Islam, N. (1995). Growth empirics: A panel data approach. The Quarterly Journal of Economics, 110(4), 1127–1170. doi:10.2307/2946651 Kalenborn, C., & Lessmann, C. (2013). The impact of democracy and press freedom on corruption: Conditionality matters. Journal of Policy Modeling, 35(6), 857–886. doi:10.1016/j. jpolmod.2013.02.009 Kaufmann, D., & Kraay, A. (2002). Growth without governance. Economia, 3(1), 169–215.

174

Kormendi, R. C., & Meguire, P. (1986). Government debt, government spending, and private sector behaviour [Reply]. The American Economic Review, 76(1), 191–203. Kunicová, J. (2006). Democratic institutions and corruption: incentives and constraints in politics. In S. Rose-Ackerman (Ed.), International handbook on the economics of corruption (pp. 140–160). Cheltenham, UK: Edward Elgar. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. (1999). The quality of government. Journal of Law Economics and Organization, 15(1), 222–279. doi:10.1093/jleo/15.1.222 Lambsdorff, J. G. (2006). Causes and consequences of corruption: what do we know from a cross-section of countries? In S. Rose-Ackerman (Ed.), International Handbook on the Economics of Corruption (pp. 3–51). Cheltenham, UK: Edward Elgar. doi:10.4337/9781847203106.00007 Li, H., Colin, L., & Zou, H.-F. (2000). Corruption, income distribution and growth. Economics and Politics, 12(2), 155–181. doi:10.1111/14680343.00073 Marshall, M. G., & Jaggers, K. (2013). Polity IV project: Political regime characteristics and transitions, 1800-2012. Dataset user’s manual. University of Maryland, College Park, M. A. Retrieved from http://www.systemicpeace.org/ inscr/p4manualv2012.pdf Mauro, P. (1995). Corruption and growth. The Quarterly Journal of Economics, 110(3), 681–712. doi:10.2307/2946696 Mauro, P. (1998). Corruption and the composition of government expenditure. Journal of Public Economics, 69(2), 263–279. doi:10.1016/S00472727(98)00025-5 Mo, P. H. (2001). Corruption and economic growth. Journal of Comparative Economics, 29(1), 66–79. doi:10.1006/jcec.2000.1703

 Corruption, Size of Government, and Economic Growth

Monte, A. D., & Papagni, E. (2001). Public expenditure, corruption, and economic growth: The case of Italy. European Journal of Political Economy, 17(1), 1–16. doi:10.1016/S01762680(00)00025-2 Pande, R. (2008). Understanding political corruption in low income countries. In T. Schultz & J. Strauss (Eds.), Handbook of Development Economics (4). Elsevier. Pritchett, L. (2003). A toy collection, a socialist star and a democratic dud: growth theory, Vietnam, and the Philippines’ in Search of Prosperity: Analytical Narratives on Economic Growth. Dani Rodrick (ed.), Princeton University Press: 123-151. Qian, Y. (2003). How reform worked in China. In D. Rodrik (Ed.), in search of prosperity: analytic narratives of economic growth. Princeton, NJ: Princeton University Press. Ram, R. (1986). Government size and economic growth: A new framework and some evidence from cross-sectionand time-series data. The American Economic Review, 76(1), 191–203. Reinikka, R., & Svensson, J. (2004). Local capture. The Quarterly Journal of Economics, 119(2), 679–705. doi:10.1162/0033553041382120 Reinikka, R., & Svensson, J. (2005). Fighting corruption to improve schooling: Evidence from a newspaper campaign in Uganda. Journal of the European Economic Association, 3(2), 259–267. doi:10.1162/1542476054472883

Rose-Ackerman, S. (1999). Corruption and government. Cambridge: Cambridge University Press. doi:10.1017/CBO9781139175098 Tanzi, V. (1998). Corruption around the world: causes, consequences, scope and cures. IMF Working Paper, No. 63. Tanzi, V., & Davoodi, H. (1997). Corruption, public investment, and growth. IMF Working Paper, No. WP/97/139. Tong, H. (1983). Threshold models in non-linear time series analysis. New York: Springer-Verlag. doi:10.1007/978-1-4684-7888-4 Vedder, R.K., & Gallaway, L.E. (1998). Government size and economic growth. Paper prepared for the Joint Economic Committee of the US Congress, 1-15.

ENDNOTES

1 2

Drawn from http://www.icrgonline.com/ A good example is China.Even though its governance is below the world average, it has above-average rates of growth (Qian, 2003). Likewise, the Philippines and Vietnam have more or less the same quality of governance, but Vietnam is booming out of a poverty trap, while the economy of the Philippines stagnates (Pritchett, 2003).

175

176

Chapter 9

Dimensions of Good Governance: An Empirical Study Chhanda Mandal Muralidhar Girls’ College, India Anita Chattopadhyay Gupta Muralidhar Girls’ College, India

ABSTRACT Effectiveness of governance is realised through its responses to any financial crisis. This was put in question as the Great Recession affected the core economies severely. This study empirically investigated the relationship between accountability, corruption, and government effectiveness during the period 2002-2012. Our main purpose was to highlight the sizable gap that exists in the performance literature on cross-country studies especially against the changing economic world scenario. A comparison of the World Bank governance indicators between three countries chosen on the basis of income differentials and hence different adaptive characteristics of each country to the economic recession has been studied. The behavior of the governance indicators in the context of the world has been examined against the background of the shock that the depression had brought and the resilience factors embedded within the indicators in the face of the shocks were studied.

INTRODUCTION “Governance” is the process of decision-making and involves the process by which decisions are implemented (or not implemented). Governance can be used in several contexts such as corporate governance, international governance, national governance and local governance. Since governance is the process of decision-making and

involves structural and legal framework through which such decisions are implemented, an analysis of governance focuses on the formal and informal actors involved in decision-making and implementation of such decisions. Government is one such actor in the governance process. Other actors involved in governance process vary depending on the level of governance that is under discussion. In rural areas, for example, other actors

DOI: 10.4018/978-1-4666-8274-0.ch009

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Dimensions of Good Governance

may include influential landlords, associations of peasant farmers, cooperatives, NGOs, research institutes, religious leaders, financial institutions, political parties, the military etc. The situation in urban areas is much more complex. At the national level, in addition to the above actors, media, lobbyists, international donors, multinational corporations, etc. may play a role in the decision-making or in influencing the decisionmaking process. All actors other than government and the military are grouped together as part of the “civil society.” In some countries, in addition to the civil society, organized crime syndicates also influencedecision-making, particularly in urban areas and at the national level. Similarly formal government structures are the means by which decisions are arrived at and implemented. At the national level, informal decision-making structures, or informal advisors may exist. In some rural areas, locally powerful families may indulge in decision-making and/or influence the decision making process. Such, informal decision-making is often the result of corrupt practices or leads to corrupt practices. Good governance implies that the authority should work based on a broad purpose – the good of the people being governed. Good governance has 8 major characteristics. It is participatory, consensus oriented, accountable, transparent, responsive, effective and efficient, equitable and inclusive and follows the rule of law. It ensures that corruption is minimized and takes cognizance of the views of minorities in decision-making to ensure peace, security and prosperity of the people. It is also responsive to the present and future needs of society. Equitable participation by both men and women is a key corner stone of good governance. It could be either through direct or legitimate intermediate institutions or through elected authorized representatives. It is important to note that representative democracy does not necessarily imply that the concerns of the most vulnerable in society would be taken into consideration in decision making. But it needs to

be informed and organized. This means freedom of association and expression on the one hand and an organized civil society on the other hand. Good governance requires fair legal frameworks that are enforced impartially. It also requires full protection of human rights, particularly those of minorities. Impartial enforcement of laws requires an independency within the judiciary and an impartial and incorruptible police force. Transparency presupposes the fact that decisions are taken based on consensus and within the boundaries of established and accepted legal and structural frameworks in vogue. It also implies that information is freely available and directly accessible to those who will be benefitted/affected by such decisions and their enforcement. It also implies dissemination of information in intelligible forms through media. Good governance requires that institutions and processes try to serve all stakeholders within a reasonable time framework There are several actors and as many viewpoints in a given society. Good governance encompasses the process of mediation of conflicting/diverse interest groups prevailing in society leading to a broad consensus, keeping in perspective society’s best interests. It also requires a broad and longterm perspective on what is needed for sustainable human development and how to achieve the goals of such development. This can only result from an understanding of the historical, cultural and social contexts of a given society or community. Society’s well-being depends on the inclusiveness that is followed and fostered among the members to make them feel as stakeholders in the mainstream of society. This requires all groups, but particularly the most vulnerable, have opportunities to improve or maintain their well-being. Good governance means that processes and institutions produce results that meet the needs of society while making the best use of resources at their disposal. The concept of efficiency in the context of good governance also covers the sustainable use of natural resources and the protection of the environment. Accountability is a key require-

177

 Dimensions of Good Governance

ment of good governance. Not only governmental institutions but also the private sector and civil society organizations must be accountable to the public and to their institutional stakeholders. Who is accountable to whom varies depending on whether decisions or actions taken are internal or external to an organization or institution. In general an organization or an institution is accountable to those who will be affected by its decisions or actions. Accountability cannot be enforced without proper delegation, transparency and the rule of law. Control of corruption is one of the pillars that the fundamentals of good governance is based on. The concept of social (or collaborative) learning refers to learning processes among a group of people who seek to improve a common situation and take action collectively. This understanding effectively extends experiential learning into collective learning. This is a form of governance, in the sense that governance relates to how society manages to allocate resources and coordinate or control activity in society or the economy. It is also adaptive management or ‘learning-by-doing’. Worldwide there is an increasing recognition that citizen involvement is critical for enhancing democratic governance, improving service delivery, and fostering empowerment. “Demand for Good Governance” (DFGG) refers to the ability of citizens, civil society organizations and other non-state actors to hold the state accountable and make it responsive to their needs. It encompasses initiatives that focus on citizens as the ultimate stakeholders and include activities relating to - information disclosure, demystification and dissemination; beneficiary/user participation and consultation; complaints handling; and independent and/or participatory monitoring. This demand aims to strengthen the capacity of NGOs, the media, local communities, and the private sector to hold authorities accountable for better development results. The concept of accountability has gained increasing importance in the World Bank’s discourse in the past two decades. Analytical studies and frameworks that have been developed since

178

have contributed greatly to advancing the agenda. For example, the 2001 World Development Report and the World Bank’s empowerment framework report very often they are demand-driven and operate from the bottom-up.

LITERATURE SURVEY Governance refers to the formal and informal processes through which a society’s rules are established, operate and evolve. The formal institutional framework of the state is important in determining how a society is governed, but governance is about more than this. In reality, governance is messy and context dependent, and entails the interaction between formal and informal rules, processes and relationships (UNDP, 2007). The foundation of governance is therefore politics. Politics is a process and constitutes all activities involved in the “use, production and distribution of resources”. It involves both the “rules of the game” and the “games within the rules” – the ongoing processes of social and political bargaining that results from individual and group interests (Leftwich, 2006). Governance is therefore also about power, because this determines who has the power to set and oversee society’s rules. According to the World Bank’s notion of governance, it has five goals of legal foundation, maintaining macroeconomic stability through non-distortionary policy intervention, investment in core services, protecting the vulnerable groups as well as the environment. Governance should include democracy, transparency, accountability, active participation and responsiveness, protection of human rights and strong enforcement of rule of law (Guhan, 1998). Voice and accountability are important dimensions of governance. Voice refers both to the capacity to express views and interests and to the exercise of this, usually in an attempt to influence government priorities or governance processes. Accountability exists when those who set and implement the rules (politicians and public

 Dimensions of Good Governance

officials) are answerable to those whose lives are shaped by those rules and can be sanctioned if their performance is unsatisfactory.Goetz and Jenkins (2005), in their work on the “new accountability agenda”, suggest that to understand accountability one needs to ask a series of questions: who is demanding accountability; from whom is accountability being sought; where – in what forum – are they being held to account; how is accountability being delivered; and, for what are people/institutions being held accountable? In recent years, the range of answers to these questions has expanded, due, in part, to challenges from participatory governance initiatives. Voice and accountability are therefore important indicators of the nature of the relationship between a state and its citizens. Improved governance requires an integrated, long-term strategy built upon co-operation between government and citizens. It involves both participation and institutions. The Rule of Law, accountability, and transparency are technical and legal issues at some levels, but also interactive to produce government that is legitimate, effective, and widely supported by citizens, as well as a civil society that is strong, open, and capable of playing a positive role in politics and government. This paper (Johnston, 1993) considers goals for better governance, key challenges confronting efforts at reform, examples of successful goodgovernance efforts, and action steps for improving both participation and institutions. The question is how to bring those levels of strategy together in such a way that they draw impetus from each other, become sustainable and effective, and produce visible results in real societies. Another study (Brewer, Choi & Richard, 2007) utilizes World Bank Governance indicators to investigate government effectiveness in Asia, both regionally and across sub-regions. Several factors seem to influence the level of government effectiveness, accountability and voice, control of corruption, and wealth and income. The presence of a democratic form of government does not seem to be an important factor, but we note that more

sensitive measures of democracy might produce more positive results.Citizens’ capacity to express and exercise their views is a vital part of poverty reduction. States that can be held accountable for their actions are more likely to respond to the different needs and demands of the public (Holland & Dani, 2005). Enhancing voice and accountability can therefore have an impact on poverty in two ways. Firstly, increasing voice and accountability can directly reduce poverty because powerlessness is a constitutive aspect of poverty. Secondly, voice and accountability can indirectly contribute to poverty reduction through its contribution to other objectives, for instance by supporting a governance environment in which poor people are able to voice their interests and participate in public discussions, leading to more pro-poor policies (O’Neil, Foresti & Hudson, 2007). Kaufmann, Kraay & Mastruzzi, (2004) have done a detail analysis of the link between governance quality and income level of an economy and direction of that link-up. Better governance results in an improvement in the per capita income. On the other hand, a rich government is able to provide corruption-free competitive service to the public. But they found a negative impact of per capita income on governance. Effectiveness of governance is once again realised through its responses to the financial crisis. Multilateral economic institutions come up with quick implementation of open economic policies where formal and informal government structures lag behind in proper policy formulating. But the role of global economic governance is put in question as the Great Recession affected the core economies more severely. There is a lack of confidence on governance system among the public, holding it responsible for the loss of job, income and wealth, during the economic crisis. That, in turn, makes it difficult for the existing government to tackle the challenges. From past experiences it has been noticed that this shift in public attitude is offset by a contrasting move through the period of economic health. As a result,

179

 Dimensions of Good Governance

Figure 1. ‘Control of corruption (CC)’ and ‘government effectiveness (GV)’in USA, India and Uganda

demand for government regulation, government intervention in poverty reduction along with other social issues rises allowing the policymakers to work on it. People rely on government assuming it will arrest the declining growth rate and will revive the economy. A crisis, in that way, defines a new growth trajectory and also assigns revised role to the government.

PLAN OF THE CHAPTER The 2007-2009 recession was long and deep, and according to several indicators was the most severe economic contraction since the 1930s (but still much less severe than the Great Depression). When the fall of economic activity finally bottomed out in the second half of 2009, real gross domestic product (GDP) had contracted by approximately 5.1%, or by about $680 billion. At this point the output gap—the difference between what an economy could produce and what it actually

180

produced—widened to an estimated 8.1%. The decline in economic activity was much sharper than in the 10 previous post-war recessions, in which the fall of real GDP averaged about 2.0% and the output gap increased to near 4.0% (see Figure 1). However, the decline falls well short of the experience during the Great Depression, when real GDP decreased by 30% and the output gap probably exceeded 40%. The slowdown of economic activity was moderate through the first half of 2008, but at that point the weakening economy was overtaken by a major financial crisis that would exacerbate the economic weakness and accelerate the decline. There is a need to redefine the role of good governance and the new challenges it is facing in the aftermath of Great Recession that the world has gone through. To cope with its ill-effects as well as for sustained economic development, the current climate demands for radical changes in the dynamics of how governance addresses the issues arising from this global crisis. With lower amount of revenue to

 Dimensions of Good Governance

spend as a result of declining rate of growth and development and on the other hand rising demand for public services – these two create an environment for better and effective governance system that will deliver the core services with a higher level of efficacy. Also, this crisis presents an opportunity for re-structuring the existing system of policy formulation and implementation which in turn again calls for a new, strong leadership, not driven by any populism, to accompany this transformation. It is evident from the above discussion that good governance and society’s development are inter-related as they deal with same set of goals. From an economic point of view, both of them are determined by same set of independent variables. Therefore, it is very natural to explore the extent of inter-dependency between these two concepts in this changing scenario.Our objective is in trying to judge the relative importance of these factors in the context of governance and see whether the importance of these indicators have changed in importance before and after the world-wide economic crisis. The plan of the paper is as follows: we have compared the governance indicators between three countries chosen on the basis of income differentials and hence different adaptive characteristics of each country to the economic recession that hit the world, then we looked at the behavior of the governance indicators in the context of the world against the background of the shock that the depression had brought and study the resilience factors embedded within the governance indicators in the face of the shocks, the corresponding methodology has been traced out in the next section and results and discussions in the following section.

AN ANALYSIS ACROSS INCOMEGROUPS: COMPARISON BETWEEN USA, INDIAAND UGANDA There are few cross-country studies of government performance, and most of these studies have

focused on developed nations. Few studies have examined regional differences, and even fewer have focused on sub-regional trends. The studies mounted thus far have identified some promising variables, but their findings are not wholly consistent. More studies are needed to fill in these gaps and sort out conflicting findings from prior research. Cross-country studies of countries having income differential is extremely rare in this line of research. There is an urgent need for scholars to attempt more empirical research on government performance between countries at different stages of development. To ascertain if there were variations in these measures of governance, comparisons between different countries by region, sub-region, democracy and wealth of nations were undertaken. Countries were categorized into regions based upon United Nations groupings (www.un.org). This includes: Asia, Africa, North America, South America, the Caribbean and Central America, Europe, and Oceania. We use income level as a measure of the wealth of nations. To classify the countries used in this study, we used the World Bank List of Economics (2006) which includes 2005 data for gross national income per capita. Four groups are identified: low income, $875 or less; lower middle income $876-$3,465; upper middle income $3,466-$10,725; and high income $10,726 or more. Countries have been classified into three groups, namely, high income group, middle income group and low income group, by the World Bank. We have chosen USA from the high income group countries where economic recession showed its worst form, India from middle income group countries as it is among the fastest growing economic powers in the world and Uganda from low income group of countries having its own characteristic features. Six dimensions of governance are taken in the set of indicators: • • •

Voice and accountability, Political stability and absence of violence, Government effectiveness,

181

 Dimensions of Good Governance

• • •

Rule of law, Regulatory quality, and Control of corruption.

In this chapter we use the World Bank’s Governance Indicators to explore accountability, performance and corruption in countries of the world. The Indicators provide data on 214 countries and territories for the period 1996-2012 (the data are biannual, 1996-2002 and annual thereafter). We have considered the time period 2003-2012, covering the period of building up the financial crisis that hit the world severely and also the recovery period. The construction of the indices is complex, drawing upon data from a huge numbers of sources. Further details of the Worldwide Governance Indicators can be found in the papers by Kaufmann, Kraay & Mastruzzi (2006) at the World Bank ten-year time period, beginning from 2003 and continuing up to 2012 covers the crucial period of the great recession that had a worldwide impact. This time period is studied on yearly basis to capture how the effect of governance, ‘good’ or ‘bad’ whatever it may be, on country’s per capita net national income, changes over time. Due to unavailability of data on governance indicator, it cannot be expanded over a longer period of time. However, this period is of great significance as the major countries of the world economy have gone through crucial policy changes faced with problems of new millennium. In this section we consider the countries USA, India and Uganda in studying the change, if any, in the relative impact of each of the governance indicators. In India we have strictly regulated market by active participation of financial regulators like Reserve Bank of India, Securities and Exchange Board of India, Ministry of Finance, Ministry of Corporate Affairs. These regulators ensure that although Indian Markets have exposure to for foreign players but at the same time have lesser vulnerability to global risks. Participatory Notes (P Notes) is one of the measures taken by Government of India (GOI) to control the Foreign

182

Institutional Investment (FII). During recession stock markets gets plummeted if foreign players pull out their investments, P Notes is the key to check that. There are many such policies which had enabled GOI to run Indian Market as a tight ship. Some of the major Indian Banks were nationalized in 1969; it facilitated GOI in forcing certain policies like high Cash to Reserve Ratio (CRR), stringent credit policy and regulation of lending rate. This control over banks has proven to be a boon to India as recession started in U.S. due to the burst of Sub Prime Bubble; during this phase, to increase their profits, financial institutions started lending to the borrowers having lesser credibility at higher rates. In India above policies prevented Indian Banks from falling into this pitfall. Apart from these, as compared to countries like USA, people in India are traditionally less spend thrifty. In India people use their savings in accumulating wealth and making provisions for rainy day. As per the study published in Global Journal of Finance and Management, it has been found that Indians have higher risk aversion as compared to their European and American counterparts. They are less prone to speculative and risky investments. In India people also tend to put their savings in form of gold which further reduces the risk of losing investment. Gold is considered to be the best investment during recession times. US economy is having high level of consumerism which led to the avalanche effect of meltdown. India is still far behind USA in this aspect. Indian economy is still focusing more on its local markets, which makes it lesser susceptible to the risk posed by global markets. India is one of the largest economies in Purchasing Power Parity Terms. It has made India a preferred location for Foreign Direct Investment (FDI). Large amount of FDIs make the economy of India robust and hence more resistant to the global fluctuations. Indian markets are still untapped at large and hence provide a much greater opportunity. Bigger local markets of India insulate her from global turmoil up to an extent.

 Dimensions of Good Governance

In India we still don’t have full Capital Account Convertibility (CAC). CAC is a nation’s feature to conduct various local financial transactions at market driven exchange rate. It has again protected India from various market forces and hence made India immune towards the global turmoil. Indian has broad government policies targeting the long term growth by facilitating growth in sectors like energy, infrastructure and manufacturing. Another aspect of why India survived recession is the poverty prevailing in India. As per the World Bank Report, 80% of India’s population survives on less than $2 a day. These people mostly earn their livelihood on daily wages. They are least impacted by any crises, as poor people will eat pulses and chapatti but if finds pulses are expensive he will switch to other cheaper alternatives like potato or sometime will have chapatti with just salt. In this way a large portion of Indian Population is completely immune to any financial turmoil. India has not only shown greater resistance during financial crises but it was one of the countries showing the fastest recovery too. This financial crisis displayed the robustness of Indian economy. The United States’ effectiveness in acting alone is diminished, particularly in non-defense-related areas such as economic and environmental challenges, where the rising powers have not yet been prepared to invest in global leadership. The result is a leadership deficit on the defining challenges of our age: building a more resilient economic system, productive employment for the world’s young people, stable markets for food, energy and other natural resources, and climate stabilization. It has huge potential for technological and social innovation. Its economy has global reach, and its policies and actions shape markets. Favorable demographics, a strengthening economy, growing energy reserves, and a robust and durable geopolitical position all provide the basis for it to take a more confident and assertive stance. However, American global leadership needs to be underpinned by a robust economy that delivers outcomesfor a wider range of its population

and at an acceptable environmental cost. Policies that address the key economic, environmental and social challenges outlined in this paper will ultimately be the main drivers and determinants. The most severe impact of the global economic crisis on Uganda has been a decline in the real wages of the most vulnerable workers.One of the most serious consequences of this fall might prove to be an increase in female dropout rates in rural schools, aggravating a long-term problem of low labor force education and productivity and rapid population growth. Other consequences include an increase in the severity of poverty. Many more poor households are unable to acquire sufficient basic food and are falling even further below the national poverty line.The assessment has also shown that despite the relatively moderate macroeconomic shock, low-wage workers have been affected severely and have born adisproportionate share of the crisis impact. The vulnerability of the work-force is a cause for concern as it implies that future shocks could immediately translate into large increases in poverty in Uganda. The boom in informal exports seems to be driven mainly by ad-hoc trading by individuals in consumer goods following the depreciation in the Ugandan shilling. While it demonstrates the large demand potential for exports to regional markets, and especially into Southern Sudan, it has not yet been associated with increases in output and employment in Uganda and its sustainability is questionable. Also a substantial decline of earnings in tourism has led to immediate layoffsin the sector. Import values have declined during the crisis, which is partially a price effect due to lower world market prices for oil. This has also led to a substantial improvement in the terms of trade since the beginning of the crisis. The first figure compares the “Control of Corruption (CC)”and “Government Effectiveness (GV)” indicators over years for the three countries under our consideration.The figure reveals that as expected because of strong government administration the general level of control of corruption

183

 Dimensions of Good Governance

Figure 2. ‘Political stability and absence of violence and terrorism (PV)’and ‘regulatory quality (RQ)’in USA, India and Uganda

is much higher in USA than in India and worst in Uganda where political instability plays a very important role. The figure also shows that control of corruption level fell in USA during 2004 to 2006 which can be said to be one of the causes of the economic crisis that emerged post 2006-07. In India, control of corruption remained at a certain stable level though we have a drop during 2007 which can be interpreted as a reaction to the aftermath of the shock of the economic crisis. Uganda, at a low level of development faced a decline in the control of corruption during the period post 2006. Further, this figure traces out the pictorial trend in the level of Government Effectiveness over the period 2002-2012. The sharp fall after 2004 in the level of Government Effectiveness in USA speaks of the shocks of the economic crisis and that the government machinery couldn’t com-

184

pletely recover from the aftermath is seen in the low level it set in after 2005. The shock was felt in India around 2008 as the government policy effectiveness fell and turned negative after 2012. It shows the impact of the shock after a gestation period of shock absorption through the government policies. Uganda, already in the negative bracket with regard to government policies further fell in 2005 gradually recovered and again fell after 2007 post economic crisis. Figure 2 traces out the pathway for the governance indicator “Political Stability and Absence of Violence and Terrorism (PV)” and “Regulatory Quality (RQ)” for the three countries. Very interestingly, the trend for Political Stability and Absence of Violence and Terrorism in India and Uganda reversed post 2006 with Uganda gaining strength through political stability while India losing out as terrorism started to show its

 Dimensions of Good Governance

Figure 3. ‘Voice and accountability (VA)’ and ‘rule of law (RL)’ in USA, India and Uganda

claws post economic crisis. USA has retained its political stability even post-recession and actually improved on it. Economic recession failed to have any impact on this indicator of governance in higher stage of development and very low of development. Those in the middle stages felt its heat.Considering the level of Regulatory Quality for the three countries during 2003-2012, like the earlier indicators, in this case also USA enjoys better position compared to India and Uganda. USA experienced a fall in in 2009. Due to recession, the government may lack the confidence to formulate and implement new policies. India, already with negative value, did not get affected much and Uganda had small fall and rise in regulatory quality after the recession. Figure 3 depicts the trend lines for “Voice and Accountability (VA)” and “Rule of Law (RL)” for the three countries within the given time period. It demonstrates that Voice and Accountability fell

in USA in 2006 and can be identified as a major reason for the global crisis in 2008. If the public’s voice is restricted then government’s policies could go against the people and the economy as well. USA continued at the reduced level even after the recession. India has kept a steady and positive value over the years. Uganda surprisingly experienced a significant rise in 2006and remained at the same level during or after the recession period. This figure also reveals that when India has gone through a sharp decline in Rule of Law after the financial crisis, even it became negative, USA and Uganda both remained at their respective levels. USA with an improved ruling system can bear the shock of the crisis and Uganda, having lower quality of ruling mechanism, did not have much impact. The recession has increased unemployment in India which was already at quite a high level and due to this crime rate rises with less effective judiciary system.

185

 Dimensions of Good Governance

DATA AND METHODOLOGY

RESULTS AND DISCUSSION

The regression analysis has been done separately for each of the ten years. The data used is secondary data sourced from World Bank data base. Study of the governance system of a particular country or region cannot be generalized over world as the nature of governance depends on social, political and economic framework specific to that country being studied. A cross-country analysis may provide a better picture of performance of governance. We use cross-section data for 214 countries in the world for the above mentioned time points. We consider linear model and express our equation as:

From Table 1, it is cleared that Political stability and Absence of Violence/Terrorism and Voice & Accountability consistently showed negative impact on a country’s per capita national income although the estimations are not significant for most of the years and the magnitude of impact is negligible. However, Voice & Accountability become significant after 2006. Economic recession in fact has allowed for citizen’s voice to rise in the face of poor governance. This shows that voice and accountability have become important dimensions of governance. Voice refers both to the capacity to express views and interests and to the exercise of this, usually in an attempt to influence government priorities or governance processes. Accountability exists when those who set and implement the rules (politicians and public officials) are answerable to those whose lives are shaped by those rules and can be sanctioned if their performance is unsatisfactory. The “new accountability agenda” suggest that to understand accountability one needs to ask a series of questions: who is demanding accountability; from whom is accountability being sought; where – in what forum – are they being held to account; how is accountability being delivered; and, for what are people/institutions being held accountable? In recent years, the range of answers to these questions has expanded, due, in part, to challenges from participatory governance initiatives in the face of economic recession. Voice and Accountability are therefore important indicators of the nature of the relationship between a state and its citizens. Our results in fact show the robustness of these two parameters as indicators of governance (Table 2). The negative impact of ‘Voice and Accountability’ on a country’s income level can be explained as increase in government’s answerability to its citizens makes it difficult for the government to formulate and implement various public policies readily. That may affect the development process in turn, slowing down the

NNI = α0 t + α1 tCC + α2 tGE + α3 t PV + α4 t RQ + α5 t RL + α6 tVA + ut where NNI => adjusted Net National Income per capita in current US$. CC=> Control of Corruption. GE=>Government Effectiveness. PV=>Political Stability and Absence of Violence/ Terrorism. RQ=>Regulatory Quality. RL=> Rule of Law. VA=>Voice and Accountability. u t=>Stochastic disturbance term. Assuming a standard linear econometric model, we apply Ordinary Least square Method estimation. Now for year 2003, t = 1; for year 2004, t = 2; and so on, and lastly for year 2012, t = 10. The total number of observations, n = 214 but it varies for each year due to the problem of missing data.

186

 Dimensions of Good Governance

Table 1. Coefficients of the variables Constant

GE. EST

PV. EST

RQ. EST

RL. EST

VA. EST

5476.995 (3.535)

4427.418 (2.340)

-690.671 (-0.984)

-1708.871 (-1.175)

380.343 (0.214)

-281.982 (-0.379)

7331.735(15.074)

5227.594(2.875)

7644.929(3.619)

-605.206 (-0.713)

-1345.454 (-0.848)

-1442.511 (-0.668)

-595.253 (-0.615)

2005

8144.713 (15.045)

5357.901 (2.945)

7010.290 (2.677)

-1963.932 (-2.094)

-2740.574 (-1.390)

1848.646 (0.836)

-453.106 (-0.436)

2006

8641.582 (15.133)

7999.067 (4.304)

3157.065 (1.228)

-714.292 (-0.774)

327.519 (0.165)

529.498 (0.233)

-1420.633 (-1.389)

2007

9867.717 (15.189)

9826.021 (4.542)

-306.593 (-0.113)

-265.072 (-0.252)

3926.434 (1.904)

710.688 (0.271)

-2529.217 (-2.206)

2008

10318.574 (14.913)

8533.731 (3.693)

-802.923 (-0.271)

-785.331 (-0.708)

4337.133 (2.017)

2433.555 (0.834)

-2054.945 (-1.718)

2009

9307.278 (16.939)

6182.392 (3.377)

3584.366 (1.592)

-1052.127 (-1.231)

1100.901 (0.677)

1532.102 (0.612)

-962.579 (-1.016)

2010

9891.189 (16.799)

7025.550 (3.606)

3040.559 (1.277)

-1539.280 (-1.571)

1329.095 (0.775)

2505.584 (0.897)

-1510.910 (-1.469)

2011

10948.539 (16.439)

7879.498 (3.495)

1130.025 (0.418)

-1661.007 (-1.418)

2364.858 (1.188)

5060.146 (1.660)

-2807.300 (-2.314)

2012

10801.053 (16.380)

8133.193 (3.636)

1772.100 (0.652)

-1502.495 (-1.358)

2161.608 (1.122)

3876.851 (1.273)

-2812.084 (-2.306)

2003

6395.344 (14.619)

2004

CC. EST

Notes: Dependent Variable: Adjusted net national income per capita (current US$). The t-value for each coefficient is given in the parentheses.

Table 2. Summary output for regression analysis Year

R-square

Adjusted R-square

F

df

2003

0.664

0.653

56.097

176

2004

0.682

0.671

61.178

177

2005

0.652

0.640

53.479

177

2006

0.656

0.644

54.026

176

2007

0.650

0.638

53.308

178

2008

0.638

0.626

49.731

175

2009

0.696

0.685

64.868

176

2010

0.694

0.683

64.195

176

2011

0.684

0.673

61.455

176

2012

0.677

0.666

59.077

175

Notes: a. Predictors: (Constant), VA.EST, PV.EST, GE.EST, RQ.EST, CC.EST, RL.EST b. Dependent Variable: Adjusted net national income per capita (current US$)

growth rate. One possible reason behind inverse influence of ‘Political Stability’ on an economy’s growth may be that the ruling party is more concerned to ensure its own stability rather than society’s welfare and so higher stability reduces the incentive to undertake developmental strategies. Coefficients of other four indicators bear positive sign in general. Among the six indicators, coefficient of control of corruption is only highly significant for each of the year’s regression analysis showing its unaltered importance as an indicator of governance even in the face of economic recession. Also, it has maximum impact on change in net national income suggesting policyimplications with respect to development. Lesser occurrence of corruption raises the credibility of the existing government and transparency of the system makes people confident about the administrations. These conditions create a favourable situation for economic growth. All the variables

187

 Dimensions of Good Governance

are significant jointly as suggested by the Wald F-statistic, ensuring the validity of the regression model used in this paper. For each year, the model exhibits quite a high value of adjusted R-square – around 65% of the variability in the value of net national income can be explained by these six economic indicators.

CONCLUDING REMARKS AND FUTURE RESEARCH DIRECTIONS The past years research agenda questions about governance capacities worldwide. Currently many public institutions in the world are implementing various reforms to measure and improve their performances. Although growing attention has been given to the question of improving government effectiveness, surprisingly little crosscountry research has been carried out using an evidence-based approach. Our main purpose was to highlight the sizable gap that exists in the performance literature on cross-country studies especially against the changing economic world scenario. This study empirically investigated the relationship between accountability, corruption, and government effectiveness, focusing on the economic crisis background the world was facing during the period 2002-2012. The first part summarized previous cross-country literature regarding government effectiveness. We then introduce the dataset and research method used in this study. The data used are the of the World Bank’s worldwide government indicators. This dataset is particularly robust, for it incorporates various data sources constructed by different organizations. The next section delved into the descriptive statistics and used six background variables to explore variations in the accountability, corruption, and government effectiveness indicators. The negative shocks the world received in 2008 and 2009 were, arguably, more severe than what occurred in 1929. The severe negative impulses turned the

188

economy into a recession as timely and sizable policy responses by the government did not occur. India braved the recession better than many other countries. India had some higher immunity to resist the global meltdown which started in USA in 2007. This financial crisis impacted various economies across the world; including USA, UK, Japan, China, France and India. During this turmoil the countries had varying impacts; countries like India had a lesser share of the worldwide despair. There are many reasons which it has led the world to believe that India survived the global problem. Financial policies implemented in India after liberalization in 1991 played an important role in this perspective. But in case of United States, its resilience has been weakened. The United States’ response to this era of crisis was an important factor influencing how other countries reacted, given the size of its economy, its position as a “necessary but not sufficient” actor on most global issues and its potential for innovation. It was necessary to gain an understanding of the drivers of and obstacles to change in American society to draw the millennial decade was one of profound crisis, with serious consequences for the United States’ security and prosperity, and for the sustainability of the American dream. The dotcom market crashed in March 2000, the latest in a chain of asset price bubbles that burst in Japan in 1991 and South East Asia in 1997. The attacks of 9/11 drew the United States into expensive and inconclusive wars that caused significant damage to its international reputation. In 2007, the property market collapsed, triggering near-meltdown in the financial sector, and then a brutal recession saw the median American family lose 40 percent. America is not alone in its lack of direction, of course. India faced significant headwinds over the coming years. India by a combination of political gridlock and economic slowdown absorbed some of the shock.The resilience of the economy has been challenged by a series of financial shocks, some starting in the United States (the dot-com

 Dimensions of Good Governance

crash and the subprime/housing crisis) and some originating internationally (the East Asian financial crisis and euro crisis), but with an impact on growth in the United States. Uganda’s economy has experienced one of the highest growth rates in sub-Saharan Africa during this decade, and growth has been relatively resilient to the initial impact of the crisis. However, growth has not sufficiently translated into gains in jobs, productivity, or real wages, and neither has the relative resilience of growth during the crisis shielded workers against its impact. The global economic crisis has led to substantial changes within the economy of Uganda with negative consequences for workers and especially the poor. The most important finding is that there is an ongoing steep decline in real wages caused by food price inflation combined with stagnation in nominal wages. Our study argues that the global economic crisis contributed to this in two ways: first, rapid outflows of portfolio investment led to a steep depreciation of the Ugandan shilling in late 2008 that continued throughout the first half of 2009. As a result food exports to neighbouring countries remained very profitable and continued to grow despite increasing domestic food prices. Second, in the context of the crisis most employers refused to pay an inflation adjustment to workers even in sectors that clearly have not been affected. Both effects were particularly strong for low-wage casual workers who spend a higher share of their income on food and are much less likely to receive wage inflation adjustments given their low bargaining power. The crisis has also led to a substantial reshuffling of Uganda’s export portfolio. Total exports actually increased, but this was driven entirely by informal crossborder trade. Some of Uganda’s traditional export crops, most notably coffee but also tobacco and cocoa, suffered a decline in export value caused by lower world market demand. In other cases, such as fish and flowers, declines in exports seem to be attributable to supply side constraints rather than world market conditions. Some export com-

modities such as tea and maize even benefited from higher market prices. We live in an era of rapid change and great uncertainty. This crisis of globalization can best be understood as a crisis of unsustainability as the world struggles to provide a decent standard of living to more than billion people at a time when resources are constrained, natural systems are under threat, and international and national institutions are ill equipped to manage contemporary risks. This is not an easy world in which to lead. Trust is low within and between countries. Levels of uncertainty are high, complicating geopolitical calculations and hampering investment decisions. Governments spend much of their time firefighting and have little time to actively shape new policies, approaches and solutions. That simulative economic policies would have this beneficial effect on a collapsing economy is consistent with standard macroeconomic theory, but without the counterfactual of the economy’s path in the absence of these policies, it is difficult to establish with precision how effective these policies were. Government effectiveness becomes important here which we find in study. Post 2006 we find Government effectiveness on a decline as an attribute to governance. Control of corruption remained important as an important determinant of governance even with world-wide economic recession taking place. More systematic work needs to be undertaken using these indicators to test their robustness over time and also to explore their true explanatory capacity. Researchers should consider unpacking the measures to increase measurement validity. Some sub-indicators may be more useful than others depending on the research questions. Researchers can refine complex, broad concepts by thinning out less useful sub-indicators for their own studies. Furthermore, the variables used in the present study are not all of the factors that affect government effectiveness. For example, the extent of managerial reforms related to accountability, corruption, and government effectiveness were not included in this study. Though this study is pre-

189

 Dimensions of Good Governance

liminary and suffers from a number of limitations, we hope that the results will foster discussion and research on government effectiveness, globally.

REFERENCES Brewer, G. A., Choi, Y., & Richard, W. M. (2007). Accountability, corruption and government effectiveness in Asia: AnexplorationofWorld Bank governance indicators. International Public Management Network, 8(2), 200–219. Goetz, A. M., & Jenkins, R. (2005). Re-inventingaccountability: Making democracy work for human development. International Political Economy Series. Basingstoke: Palgrave Macmillan. Guhan, S. (1998). World Bank on governance: A critique. Economic and Political Weekly, 33(4), 185–190. Holland, J., & Dani, A. (2005). Tools for institutional, political and social analysis (TIPS) of policyreform: A sourcebook poverty and social impact analysis (PSIA) (Vol. 1). Washington, D.C.: World Bank. Johnston, M. (1993). Political corruption: Historical conflict and the rise of standards. In L. Diamond & M. F. Plattner (Eds.), The Global Resurgence of Democracy (pp. 193–205). Baltimore: Johns Hopkins University Press.

190

Kaufmann, D., Kraay, A., & Mastruzzi, M. (2004). Governance matters III: Governance indicators for 1996, 1998 2000 and 2002. The World Bank Economic Review, 18(2), 253–287. doi:10.1093/ wber/lhh041 Kaufmann, D., Kraay, A., & Mastruzzi, M. (2006). Governance matters V: Aggregate and individual governance indicators for 1996-2005. TheWorld Bank. doi:10.1596/1813-9450-4012 Leftwich, A. (2006). Drivers of change: Refining the analytical framework. Part 1: Conceptual and theoretical issues, Paper prepared for DFID. York and University of York. O’Neil, T., Foresti, M., & Hudson, A. (2007). Evaluation of citizens’ voice and accountability: Review of the literature and donor approaches. London: DFID. UNDP. (2007). Governance indicators: A users’ guide (2nd ed.). Oslo: UNDP.

ADDITIONAL READING Kaufmann, D. (2003). Governance redux: The empirical challenge. Paper no.8210, Munich Personal RePec Archive, MPRA Paper no 8210. Kaufmann, D., Kraay, A., & Mastruzzi, M. (2010). The worldwide governance indicators: Methodology and analytical issues. Global Economy and Development, Brookings Institution.

191

Chapter 10

The Inter-Linkage between Governance and Poverty: Evidences from SAARC Countries Maniklal Adhikary The University of Burdwan, India Dyuti Sinha The Bhawanipur Education Society College, India

ABSTRACT This chapter aims at assessing the impact of governance on the country’s economic and human well-being in the selected South Asian countries. The study finds that for the countries-India, Pakistan, Bangladesh, Sri Lanka and Nepal, over the years 1990-2012, the growing rate of GDP per capita (PPP) and growing employment to population ratio has a significant negative impact on the Global Hunger Index as expected. Also the panel regression run for the eight SAARC countries over the period 2007-13 to find out the impact of each of the six governance indicators on the per capita GDP showed that political stability and absence of violence, government effectiveness and regulatory quality have very strong and significant role in augmenting the economic output besides the remaining indicators. The trends for each of the indicators across countries over time show that except Bhutan, none of the countries are exhibiting good performance of the governance indicators.

INTRODUCTION It is undeniable that governance is an indispensible regulatory parameter in upbringing the health of an economy. The public expenditures made in the past periods have a positive correlation with the human development index in the current period (UNDP, 2013). Likewise, efficient governance is a pre-condition for any nation to benefit from

the various development programs taken up for the mass human development. Over the past few decades, policy measures have been taken up in the developing and underdeveloped countries all over the world through provision of certain basic entitlements necessary for a decent living like providing food, education, health services, safe drinking water, besides several other entitlements which in turn enables the people to work and

DOI: 10.4018/978-1-4666-8274-0.ch010

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 The Inter-Linkage between Governance and Poverty

earn their living thereby promoting human and economic development. The target of a state is to maximize the welfare. This act of maximizing the welfare is successful if the welfare is inclusive: that which involves all the sections of the society irrespective of economic class, topography, age, gender, caste, creed, political affiliation, education etc. and the public services that the state provides should percolate equally to all the targeted beneficiaries. The public welfare entwined with the welfare of the state thus depends on how efficiently the state runs its administration for implementing the various schemes taken for the well-being of its stake-holders (public). It also depends on the level and extent of participation of the public in the decision making process and in policy framework for those specific beneficiaries. The Government should be maintaining a transparent system which would involve an active participation of the stakeholders (both providers and beneficiaries) thereby promoting public confidence on the Government. The stronger the public confidence on the Government, the larger is the scope for the state to receive foreign and domestic investment, which, if sustains, would further promote production. Several outcomes act as parameters for a sustained growth and development. Higher investment occurs due to sustained increased consumption which augments labor employment and hence better job prospects. Thus proper resource allocation, distribution and utilization are very important aspects for a sustained development. When public resources are privately used up by the public servants for their personal gain, there appears the failure of strong governance, resulting in corruption. International confidence on the concerned domestic countries is very much dependent on the perception of corruption. If the beneficiaries and stakeholders of the public services perceive and express satisfaction about good functioning of the government thereby facilitating all the stakeholders equally and justly, there is said to exist

192

good governance. Thus growing and sustained international confidence in an economy invites more of foreign investment and aid which promote development. So, a good governance results in higher economic growth, better redistributive policies implying equitable distribution of wealth and resources, increased employment opportunities, rising income, production, consumption, investment and economic growth. In economies where the inequality is high, the differences between the rich and the poor are demarcated well; there exists poverty among the lower sections of the society. If inequality is high, the aggregate demand made by the consumers in the society as a whole lowers which in turn affects production. As production goes down due to reduced demand, the producers cut short their production expenses, as a result of which, unemployment occurs resulting in loss of earning opportunities. Thus, in an economy with persistent inequality and poverty, there is less equity in all the sectors of the economy. The sectors may be economic, social or political. So a welfare oriented state which always aims at good governance reduces poverty, lowers economic inequality and promotes equitable distribution and participation. The international organizations and regulatory bodies like the World Bank and the IMF are concerned with the issues of governance and institutions in the developing economies, particularly with corruption. Evidences are there which say that good governance and institutions help in accelerating development and in reducing poverty in the developing countries. Thus good governance impedes corruption and poverty in developing economies.

DEFINING GOVERNANCE AND GOOD GOVERNANCE Governance is the exercise of economic, political and administrative authority to manage a

 The Inter-Linkage between Governance and Poverty

country’s affairs at all levels. The dimensions of good governance as proposed by the World Bank Institute’s Kauffmann, Kray and Mastruzzi (2010) are as follows •

•

•

•

Political Stability and the Absence of Violence: Capturing perceptions of the likelihood that the government will be destabilized or overthrown by unconstitutional or violent means, including politically motivated violence and terrorism. Economic and social integrity is very much necessary for efficient execution of the various development programs. The Rule of Law: capturing perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. Maintenance of proper law and order in the state augments smooth functioning of the administration for implementing its policies is necessary. Voice and Accountability: Capturing perceptions of the extent to which a country’s citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media. Participation of the beneficiaries and their ability to contribute in the policy making process, giving feedback and standing against the motion. The government should make every possible attempt to maintain a transparency in their policy implementation process. There should not be ethnic, gender and class bias and all citizens can equally raise their voice against any sort of corruption. Regulatory Quality: Capturing perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. The govern-

•

•

ment should act as a facilitator for encouraging private sector development in certain basic sectors like health, education, etc. in developing nations. Government Effectiveness: Capturing perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies. Control of Corruption: Capturing perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as “capture” of the state by elites and private interests.

Thus, to be precise, these parameters are very much decisive in determining the effectiveness of various policies that are implemented for reducing poverty and inequality across nations for promoting growth with economic development. Although good governance focuses on the interactions of the state and society, its origin lies in economic concerns. Aid donors believe that development depends on the issues of governance. The purpose of good governance is commonly seen as a promoter of development. ‘Bad’ governance is identified with corruption, wastefulness, incompetence, and unresponsiveness, all of which impede economic development and perpetuate poverty. The World Bank’s view of good governance is seen as a strategy for development, or a principle to guide donors and investors when they make decisions. The Bank’s economic liberalism ensures that its wish-list includes the promotion not only of liberal democratic political institutions, but also of a market economy, free trade, and reduced public sectors. The term ‘good governance’ became popular in the 1990s when it was used in relation to economic and social development by the World Bank as a part

193

 The Inter-Linkage between Governance and Poverty

Table 1. Regional profile of the governance indicators across SAARC countries 2012 GDPPC (current US$)*

GE

RQ

RL

CC

VA

PSAV

Afghanistan

Country

678.3479

-1.4

-1.21

-1.72

-1.41

-1.32

-2.42

Bangladesh

829.2515

-0.83

-0.96

-0.91

-0.87

-0.42

-1.35

Bhutan

2498.391

0.48

-1.12

0.19

0.82

-0.32

0.81

India

1498.872

-0.18

-0.47

-0.1

-0.57

0.35

-1.25

Maldives

6665.768

-0.16

-0.35

-0.5

-0.44

-0.52

-0.28

Nepal

694.1048

-0.99

-0.81

-0.79

-0.83

-0.7

-1.38

Pakistan

1299.119

-0.79

-0.73

-0.91

-1.06

-0.87

-2.68

Sri Lanka

3279.891

-0.24

-0.12

-0.11

-0.24

-0.6

-0.71

* implies data for GDP per capita corresponds to the year 2013 The six governance indicators are government effectiveness, regulatory quality, rule of law, control of corruption, voice accountability, and political stability & absence of violence.

of its lending requirements. A better governance results in improved functioning of the social and economic development policies which tends to reduce persistent inequality and poverty. Failure of political governance results in corruption.

Governance in South Asia The lack of effective governance has emerged as one of the foremost challenges in South Asia. South Asia is amongst the most vulnerable regions of the world after Africa to hunger due to high levels of poverty and deprivation. Heavy reliance of the region on climate sensitive sectors such as crops, livestock, forestry and fisheries also place it in a vulnerable position. Despite the developed economies’ recession in the recent years, South Asia has experienced the fastest growth in the world in the recent years. The South Asian region has achieved an economic growth averaging 6.5 percent annually during 2000-12, however, this is not enough to reduce poverty and ensure food security1. South Asia is a region rich in culture and tradition, but poor in governance for human development. It has three-fifths of the world’s population and positive growth rates, which managed to sustain in the face of the global financial crisis since 2009. Though South Asia has shown much potential towards sustained economic growth, poverty alleviation

194

and human development, poor governance has deterred the improvement. Social, economic and political factors are equally responsible for human deprivation in the region. South Asia is unable to cope up with the problems of poverty, deprivation of the masses, social exclusion, rapid urbanization and environmental degradation caused by the forces of development. The region reports highest incidence of child malnourishment. The maternal mortality rates in some countries are very high and majority of the births take place unattended by the skilled medical professionals. Women are forced to work in the informal sector where wages are very low and minimum standards are even not maintained. Rapid urbanization is putting more strain on urban water and sanitation systems. Table 1 provides a highlight on different magnitudes of the six governance indicators across the countries of the list.

Corruption and Poverty Following Chetwynd and Spector (2003) report on corruption and poverty which concludes that corruption has direct consequences on economic and governance factors, intermediaries that in turn produce poverty, this study proceeds with the structural framework as has been given by the said authors. Corruption in the public sector

 The Inter-Linkage between Governance and Poverty

-- the misuse of public office for private gain -- is often viewed as stimulating conditions of poverty (low income, poor health and education status, vulnerability to shocks and other characteristics) in countries already struggling with the strains of economic growth and democratic transition. Alternatively, countries experiencing chronic poverty are seen as natural breeding grounds for systemic corruption due to social and income inequalities and perverse economic incentives. They discuss two major models explaining the moderated linkage between corruption and poverty: an economic model and a governance model. The Economic Model postulates that corruption affects poverty by first impacting economic growth factors, which, in turn, affect poverty levels. Economic theory and empirical evidence both demonstrate that there is a direct causal link between corruption and economic growth. Corruption hampers economic growth by discouraging foreign and domestic investment, taxing and dampening entrepreneurship, lowering the quality of public infrastructure, decreasing tax revenues, diverting public talent into rent-seeking, and distorting the composition of public expenditure. Besides limiting economic growth, corruption also aggravates income inequality. Corruption distorts the economy and the legal and policy frameworks allowing some to benefit more than others; there is unfair distribution of government resources and services; corruption reduces the progressivity of the tax system; corruption increases the inequality of factor ownership; and lower income households (and businesses) pay a higher proportion of their income in bribes than do middle or upper-income households. Thus corruption impedes economic growth thereby resulting in income inequality which aggravates poverty. On the other hand, there are evidences that an increase in GDP produces an increase in the income of the poor. However, income distribution is an important mediating factor because economic growth may not always benefit the poor.

The Governance Model asserts that corruption affects poverty by influencing governance factors, which, in turn, impact poverty levels. •

•

•

Corruption reduces governance capacity, i.e. it weakens political institutions and citizen participation and leads to lower quality government services and infrastructure. The poor suffer disproportionately from reduced public services. When health and basic education expenditures are given lower priority, for example, in favor of capital intensive programs that offer more opportunities for high-level rent taking, lower income groups lose services on which they depend. Corruption is consistently correlated with higher school dropout rates and high levels of infant mortality. Secondly, impaired governance increases poverty by restricting economic growth and, coming full circle, by its inability to control corruption. Thirdly, corruption that reduces governance capacity also may inflict critical collateral damage: reduced public trust in government institutions. As trust -- an important element of social capital -- declines, research has shown that vulnerability of the poor increases as their economic productivity is affected. When people perceive that the social system is untrustworthy and inequitable, their incentive to engage in productive economic activities declines.

Thus, anti-corruption programs that are crafted to address issues of economic growth, income distribution, and governance capacity, government services in health and education, and public trust in government are likely to not only reduce corruption, but reduce poverty as well.

195

 The Inter-Linkage between Governance and Poverty

RATIONALE, BACKGROUND AND MOTIVATION OF THE STUDY In developing countries, characterized by high growth rate of population and large volumes of underutilized resources, inequality is an outcome of unequal distribution and utilization of resources. Inequality in access to public services, contribution to the country’s GDP etc. makes weaker section of the people vulnerable to situations of poverty. The concept of class differentiation between the ‘have’s and the ‘have-not’s hence comes into play which gradually creates inequality which widens over time if no sudden big-push pulls them out of the well. Education, health services, housing, sanitation and communication are the chief areas which create the gap between the rich and the poor. Those suffering from lack of access to these basic amenities hence become weak in terms of their physical, mental and economic ability to get them employed. Thus unemployment results in widening the persistent gap resulting in poverty, which when worsens, results to situations of hunger and malnutrition. Thus inequality leads to violence and corruption which are causal factors for weak governance. The first decade of the 21st century experienced the global financial crisis and worldwide recession which made the policy makers in South Asian countries re-evaluate their planning and budgeting priorities thereby making major cuts in development spending. Besides experiencing frequent natural calamities, the region also suffers from increased military, extremist activities which make governance vulnerable. Despite all these negative forces which tend to deter human development in South Asia, the economies of South Asia- India, being the largest of its kind among the SAARC countries, has experienced a sustained economic upsurge led by the rapid emergence of the information and communication technology (ICT) sector. In the face of the recent crisis, where developed economies had run bankrupt, India and China managed to grow with

196

a positive growth rate. This phenomenal success has earned these countries the confidence of the foreign investors and has henceforth started being the favorite destinations of foreign investment and aid which will promote economic and social development. On the other hand, the crisis has taught the economies to cut short their expenses by means of better governance. Evidences say that when an economy curbs its public expenses on any public program it is the poor who suffer the most. Thus the austerity measures of the government should be such that it does not affect the masses, or even if it affects, the intensity should be minimum. In this context, it is relevant to discuss the various dimensions of governance as developed and practiced in the South Asian region. It is the state’s responsibility to provide basic amenities that enable its citizens to enjoy their ‘right to life with dignity’2.

RESEARCH GAP This work is very elementary in its approach to the linkage between governance and the country’s economic output and poverty The poverty measures were not available for all the SAARC countries over the common time frame. Data for Afghanistan, Nepal etc. are not available preceding 2002 and for all the years following it for aggregate national income. Due to the irregularities in the household surveys and variations in the methodologies for calculating the poverty estimates, the popularly used poverty indices could not be used. Thus another important dimension of poverty, viz. the per capita gross domestic product is being used which would also signify the economic growth pattern of the concerned countries. Data on poverty head count ratio, Gini coefficient measure of inequality is not available for all the years for all the countries, hence we cannot use the data for comparison.

 The Inter-Linkage between Governance and Poverty

REVIEW OF LITERATURE Mahbub ul Haq Human Development Centre’s (2012, 2013) approach to Governance is from the stand point of economic, human and social development which has been described in the following section. Good governance from the standpoint of human development is redefined as humane governance. This definition is based on the fact that the costs of poor governance, whether in terms of un-enforceable property rights and contracts, deteriorating law and order, or widespread absenteeism by teachers and doctors are largely borne by the poor people. Hence human development takes the centre-stage of any governance agenda where humane governance is simply defined as good governance dedicated to securing human development. Good governance requires participation of people in the state, civil society and the private sector to build the capacity of all people including deprived and marginalized. Humane governance is conceptualized in three interlocking dimensions: good political governance, good economic governance and good civic governance. Chetwynd and Spector (2003) in a report containing a vast review of literature on corruption and poverty explore the linkages between corrupt free governance and an economy’s well being, both socially and economically.

ECONOMIC MODELS OF CORRUPTION A vast literature is available showing an inverse correlation between aggregate economic growth and corruption; in general, countries with higher corruption experience less economic growth. Corruption affects economic growth, through deterring investment and entrepreneurship, distorting markets, and undermining productivity.

Corruption Impedes Economic Growth The relationship between corruption and economic growth is complex. Economic theory supports the notion that corruption hinders economic growth in the following ways: •

•

•

•

•

•

•

•

Corruption discourages foreign and domestic investment: Rent seeking behavior increases costs and creates uncertainty, reducing incentives to both foreign and domestic investors. Corruption taxes entrepreneurship: Entrepreneurs and innovators require licenses and permits and paying bribes for these services cuts into profit margins. Corruption lowers the quality of public infrastructure: Public resources are diverted to private uses, standards are waived; funds for operations and maintenance are diverted in favor of more rent seeking activity. Corruption decreases tax revenue: Firms and activities are driven into the informal or gray sector by excessive rent taking and taxes are reduced in exchange for payoffs to tax officials. Corruption diverts talent into rent seeking: Officials who otherwise would be engaged in productive activity become pre-occupied with rent taking, in which increasing returns encourage more rent taking. Corruption distorts the composition of public expenditure: Rent seekers execute those projects for which rent seeking is easiest and best disguised, diverting funds from other key social sectors like education and health. Corruption discourages domestic investment: In countries like Bulgaria and Latvia, planned investments were dropped due to corruption. Corruption hurts entrepreneurship especially among small businesses: Several

197

 The Inter-Linkage between Governance and Poverty

• •

studies reported that small businesses tend to pay the most bribes as a percentage of total revenue. Corruption decreases revenue from taxes and fees Corruption invigorates income inequality

Several studies have demonstrated a relationship between corruption and income inequality. The theoretical foundations for this relationship are derived from rent theory and draw on the ideas of Rose-Ackerman (1978) and Krueger (1974), among others. Propositions include: • •

Corruption may create permanent distortions from which some groups or individuals can benefit more than others. The distributional consequences of corruption are likely to be more severe the more persistent the corruption.

Gupta, Davoodi, and Alonso-Terme (1998) studied the impact of corruption on income distribution When Gini coefficients for income per capita (measures of income inequality) were graphed against the Transparency International (TI) Corruption Perceptions Index (CPI), lower levels of corruption were seen to be statistically associated with lower levels of income inequality (simple correlation was +0.72). In another study of 35 countries (mostly OECD countries), Karstedt hypothesized that corruption supports, stabilizes and deepens inequality. In conclusion, the literature establishes clearly that corruption impedes economic growth and augments income inequalities. Since inefficient governance results in corruption, corruption has been taken as a major indicator of governance in the following literature.

Impeded Economic Growth Rates Aggravates Poverty There is evidence that the absence of economic growth (or negative growth) increases poverty. 198

Quibria’s study (2002) suggests that the burden of rapid economic retrenchment, such as was seen in Thailand and Indonesia, hurts the poor most heavily. Dollar and Kraay (2002) of the World Bank Development Research Group studied a sample of 80 countries over four decades and showed that income of the lowest 20 percent of the population increases one for one with increases in per capita GDP. Moreover, using tests for directionality, they concluded that a 1 per cent increase in GDP actually causes a 1 per cent increase in the incomes of the poor. Similarly, Ravallion and Chen (in Easterly, 2001: 13-14) examined 65 developing countries between 1981 and 1999. They found that the number of people below the poverty line of $1 per day was reduced in countries with positive economic growth. However, they concluded that “measures of inequality show no tendency to get either better or worse with economic growth.” In conclusion, these studies show conclusively that income rises with economic growth and vice versa. It should be noted that economic growth does not necessarily lead to more equal income distribution; an increase in income may benefit the better-off rather than bringing the poor out of poverty. Income distribution seems to be an important moderating factor in the relationship between economic growth and poverty reduction.

GOVERNANCE MODELS OF CORRUPTION The governance model postulates that increased corruption reduces governance capacity, which, in turn, increases poverty conditions. Kaufmann, Kraay and Pablo Zoido- Lobaton (1999) define governance as, “the traditions and institutions by which authority in a country is exercised. This includes (1) the process by which governments are selected, monitored and replaced, (2) the capacity of the government to effectively formulate and implement sound policies, and (3)

 The Inter-Linkage between Governance and Poverty

the respect of citizens and the state for the institutions that govern economic and social interactions among them.”

Corruption Degrades Governance Johnston (2000) suggests that serious corruption threatens democracy and governance by weakening political institutions and mass participation, and by delaying and distorting the economic development needed to sustain democracy. As government revenues decline through leakage brought on by corruption, public funds for poverty programs and programs to stimulate growth also become scarcer. Gupta, Davoodi and Tiongson (2000) used regression analysis across a large sample of countries to assess an aggregate measure of education outcome and health status in a model that includes several corruption indices, per capita income, public spending on health care and education, and average years of education completed. The results supported the proposition that better health care and education outcomes are positively correlated with lower corruption. In particular, corruption is consistently correlated with higher school dropout rates and corruption is significantly correlated with higher levels of infant mortality and lower-birth weights of babies. Gupta, Davoodi and Terme (1998) also found that corruption can lead to reduced social spending on health and education. Countries with higher corruption tend to have lower levels of social spending, regardless of level of development. Corruption lowers tax revenues, increases government operating costs, increases government spending for wages and reduces spending on operations and maintenance, and often biases government toward spending on higher education and tertiary health care (rather than basic education and primary health care).

Impaired Governance Increases Poverty Pioneering research on the relationship among corruption, governance and poverty has been conducted at the World Bank by the team of Kaufmann, Kraay and Zoido-Lobaton. Their studies suggest an association between good governance (with control of corruption as an important component) and poverty alleviation. Kaufmann and Kraay (2002) found (i) better governance tends to yield higher per capita incomes, but (ii) higher per capita incomes tend to produce reduced governance capacity. The effect of governance on corruption and poverty is illuminated by another World Bank study (2000a). The deterioration in governance discussed in this study was accompanied by an increase in both corruption and poverty. Thus, as seen earlier, increases in corruption tend to deteriorate governance practices, but the reverse holds true as well – reduction in governance capacity increases the opportunities for corruption.

Reduced Public Trust in Government Increases Vulnerability of the Poor Corruption that reduces governance capacity also may inflict critical collateral damage: reduced public trust in government institutions. As trust, an important element of social capital, declines, research has shown that vulnerability of the poor increases as their economic productivity is affected. Zak and Knack (1998) found that trust is higher in nations with stronger formal institutions for enforcing contracts and reducing corruption, and in nations with less polarized populations (as measured by income or land inequality, ethnic heterogeneity, and a subjective measure of the intensity of economic discrimination). They also

199

 The Inter-Linkage between Governance and Poverty

showed that formal institutions and polarization appear to influence growth rates in part through their impacts on trust. For example, income inequality, land inequality, discrimination and corruption are associated with significantly lower growth rates, but the association of these variables with growth dramatically weakens when trust is controlled for. Knack (1999) also looked at the effect of social capital on income inequality. His study has made regression of various indicators of social capital and trust against income data by quintile and found that higher scores on property rights measures were associated with declines in income inequality. Knack concludes that “social capital reduces poverty rates and improves – or at a minimum does not exacerbate – income inequality.” With the vast literature describing the causal relationships between the elements of good governance, corruption, economic growth, and poverty the study now delves into the empirical evidences from the eight SAARC countries over the past seven years.

2. To analyze the impact of GDP per capita (PPP) and employment to population ratio on the country’s hunger index over the period 1990-2012. 3. To study the impact of the six dimensions of governance on the country’s GDP per capita (PPP).

DATA AND METHODOLOGY

This paper concentrates on three major objectives to establish the various causes and effects of corruption (which is a result of weak governance) with respect to the country’s economic output and state of poverty, which results in hunger. The employment to population ratio also has an important role to play in determining a country’s social and economic well being. The principal objectives are

The study is based completely on the World Bank data available on the gross domestic product (current US$) and the six dimensions of governance as given by the Worldwide Governance Indicators for the selected South Asian countries. The study covers eight SAARC countries namely Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka. Data on the governance indicators are available since 1996 biennially to 2002 after which annual data is available. In order to test the degree of causality of the governance indicators on the nation’s GDP, a regression analysis is proposed. The model assumes that the governance indicators have a long term effect in determining the current value of GDP. Thus for the governance indicators one period lag has been taken. For example the governance indicators corresponding to the year 2012 are decisive in determining the GDP for the next year viz. 2013. We have assumed a linear relationship between the variables with general Classical Linear Regression Model following the standard assumptions and Ordinary Least Squares technique is applied. The six governance indicators on which the quantitative data is available are:

1. To explore the trend in poverty, hunger, and inequality across the SAARC countries and to map the trend in GDP growth and governance indicators across countries over time as per the availability of data.

• • • • •

OBJECTIVE OF THE STUDY

200

Government Effectiveness (ge) Regulatory Quality (rq) Rule of Law (rl) Control of Corruption (cc) Voice and Accountability (va)

 The Inter-Linkage between Governance and Poverty

•

Political Stability and Absence of Violence (psav)

These estimates of governance range from approximately minus 2.5 (weak) to plus 2.5 (strong) for the concerned governance indicator. Since the estimates of governance are measured on a scale which has got such a narrow range, the dependent variable here which is the GDP per capita is normalized by taking the log of the actual GDP per capita (loggdppc) for the ease of parity. Hence the huge gap between the GDP per capita expressed in US $, and the dimensions of governance are minimized and are hence comparable. The hunch is, if the country’s GDP increases, the global hunger score should decline as increased income of the individuals is used to meet the expenses of food. Similarly, if people find more jobs, which results in increased income, the hunger score should be on a decline for all countries in general. In the first place, we measure the impact of employment growth rate and growing output on the growth rate of hunger index of the country. It is expected that if country’s employment to population ratio (EMP_POP) goes up, the hunger score (GHI) is suppose to go down as fewer cases of hunger and inequality should be reported. The regression equation is log (GHI ) =

β0 + β1 .log (GDPPCPPP ) + β2 .log (EMP _ POP ) + ut

The study aims at testing the significance and depth of association between GDP, employment and global hunger index. It is expected, that for developing countries, as the employed population ratio increases thereby resulting in greater money at dispose, the incidence of poverty, hunger and malnutrition should go down. The test statistic is H0: β1 = 0, against the alternative hypothesis H1: β1< 0

Similarly, H0: β2 = 0 against H1: β2< 0. The coefficients are expected to be significant and having a negative sign denoting inverse relation with the explained variable (GHI) Coming down to the governance indicators, we assume a linear relationship between the governance parameters and GDP growth as follows: log (gdppcn +1 ) = α0 + α1 * gen + α2 * rqn + α3 * rln + α4 * ccn + α5 * van + α6 * psavn +ut This model is used to measure the impact of each of the governance parameters in determining the national product in the next period. The recent rankings by the Transparency International on the Corruption Perception Index (CPI) in 2013 finds Bhutan (rank 31) as the least corrupt country among the other SAARC countries, followed by Sri Lanka (91), India (94), Nepal (116), Pakistan (127), Bangladesh(136) and Afghanistan (175) among 177 countries. Thus among the SAARC countries, Bhutan has the lowest incidence of poor governance in terms of control of corruption, political stability and absence of violence and government effectiveness. Although one may argue, that Bhutan is a very small country, landlocked on all sides and runs entirely on its strategic relationships with its neighboring countries, especially India; Sri Lanka among the major SAARC countries has the second lowest CPI rank3.

SUMMARY STATISTICS The summary statistics for the variables under study has been depicted in Table 2. Figure 1 depicts the box plot diagram showing the lower quartile (Q1), median (Q2) and upper quartile (Q3) for each of the six governance indicators. The lower and upper fences are shown by the lines bounding each of the box plots for each variable. The variable control of corruption 201

 The Inter-Linkage between Governance and Poverty

Table 2. Descriptive statistics for the variables under study Summary Statistics of the Variables Under Study for All SAARC Countries,2006-12 Variable

No. of obs.

Mean

S.D.

Min.

Max

GDPPC(PPP$)

56

1870.75

1803.29

373.59

6665.76

Government Effectiveness

56

-0.46

0.55

-1.49

0.616

Regulatory Quality

56

-0.68

0.45

-1.68

0.29

Rule of Law

56

-0.54

0.66

-1.95

0.372

Voice Accountability

56

-0.53

0.49

-1.48

0.45

Control of Corruption

56

-0.6

0.64

-1.63

0.82

Political stability & absence of violence

56

-1.22

1.12

-2.81

1.3

Source:Calculations based on World Bank Data on Governance, 2006-12

has three outliers during the years under study for different countries. This does not signify any abnormality in the value of the index but shows that Bhutan has the best control of corruption and the index is highly positive implying good governance. The position of the median (Q2) signifies the nature of the distribution.

EMPIRICAL RESULTS AND ESTIMATES The South Asian countries have emerged to be one of the largest information communication technology (ICT) hubs, India being the most popular destination among SAARC countries besides Malaysia, China, Singapore, and Thailand in the region. The gradual dependence in the ICT Figure 1. Pattern of the data on governance measured over the time period 2006- 12

202

sector on these countries is due to abundance of cheap skilled labor which makes the production cost effective besides several other infrastructural factors. Several researchers have emphasized on the growing importance of the various non-income measures of poverty which are very significant indicators of human well being. If a person earns enough to keep him above the respective poverty line, but is denied access to or is deprived of certain basic entitlements like proper healthcare facilities and education, then he is said to be suffer from poverty of opportunity. If there are not enough income-earning opportunities, then even if the state is well equipped with improved medical and better teaching facilities, the state would suffer from unemployment problem. So the availability of opportunities for earning a healthy living is significant parameter for determining the well being of the people. Thus the poverty of opportunity index has been tabulated for the major four SAARC countries (Table 3). The table compares income poverty measured by the percentage of population living below the PPP $1.25 per day, with the measure of poverty estimated using POPI value for four South Asian countries. It shows that income poverty tells only a part f the story. The incidence of poverty for Pakistan as measured by POPI at 29.2 per cent is much higher than income poverty (US $1.25 per day) at 22.6 per cent. This implies that individu-

 The Inter-Linkage between Governance and Poverty

Table 3. Non-income measure of poverty in selected SAARC countries: Poverty of Opportunity Index (POPI)

Asian countries over the recent past (Table 4). The data on sub-components of the GHI were not available for all the SAARC countries; hence, we have taken few other South Asian countries. On the scale of 0 to 100, where 0 indicates no reported cases of undernourishment, underweight children and underweight child mortality under five, the countries are ranked according to their hunger scores. So the lower the index, the better it is. From the statistics, it is evident that among the selected South Asian countries, which were chosen based on data availability, Bangladesh, India and Nepal had their GHI score nearing to 30, which was quite high, compared to their neighboring counterparts. China, which also has a huge population as India scored strikingly, just 13 on the GHI scale in 1990 when India and Bangladesh had a GHI more than twice as that of China. Economies of Malaysia and Mauritius which are not as large as that of India or China scored the lowest among all the countries on GHI in 1990. The pace of reduction in the GHI parameters has been fastest in Thailand followed by China. Among the booming developing economies China records the fastest reduction in hunger index. India has been one of the struggling economies in the region to

Poverty of Opportunity in South Asia,2010 Bangladesh

India

Pakistan

Sri Lanka

Poverty of health opportunities (%)

16.3

13.4

11.6

7.8

Poverty of education opportunities (%)

39.6

32.7

41.3

9

Poverty of income opportunities (%)

43.3

32.7

22.6

7

Poverty of opportunity index (POPI) value (%)

35.2

27.8

29.2

7.8

Sources: UIS 2012, UNDP 2010c, UNDP 2012, World Bank 2012b,e and i and MHHDC staff computations

als living above the income poverty line may still suffer from deprivations in education, health and other living conditions. Countries like India that perform better with respect to poverty of education opportunities, have a lower incidence of poverty as measured by POPI, despite suffering from a greater incidence of income poverty compared to Pakistan. The next section discusses the decadal trend in the Global Hunger Index for selected South

Table 4. Performance of selected South Asian countries in terms of Global Hunger Index since 1990 2013 Global Hunger Index of selected South Asian Countries 1990 (with data from 1988-92)

1995 (with data from 1993-97)

2000 (with data from 1998-2002)

2005 (with data from 20032007)

2013 (with data from 2008-12)

Improvement Index Ratio of GHI1990 to GHI2013

Bangladesh

36.7

35.1

24.0

20.2

19.4

1.89

China

13.0

10.4

8.4

6.7

5.5

2.36

India

32.6

27.1

24.8

24.0

21.3

1.53

Malaysia

9.5

7.1

6.9

5.8

5.5

1.72

Country

Mauritius

8.5

7.6

6.5

5.9

5.2

1.63

Nepal

28.0

27.3

25.3

22.3

17.3

1.61

Pakistan

25.9

22.8

21.6

21.2

19.3

1.34

Sri Lanka

22.3

20.7

17.8

16.9

15.6

1.42

Thailand

21.3

17.1

10.2

6.6

5.8

3.67

Source: IFPRI 2013, author’s calculation

203

 The Inter-Linkage between Governance and Poverty

Table 5. Various consumption measures of poverty for SAARC countries except Afghanistan Country

Pov.line (PPP$/mon.)

Mean C ($)

Headcount (%)

Pov. Gap (%)

Squared pov. gap

Population (mil.)

Survey Year

Bangladesh

38

51.67

43.25

11.17

3.84

148.69

Bhutan

38

137.82

4.42

0.66

0.16

0.73

India*

38

60.39

32.67

7.49

2.5

1,224.62

India--Rural

38

54.96

34.28

7.53

2.46

856.01

2009.5

India--Urban

38

73.01

28.93

7.39

2.61

368.61

2009.5

2010 interpolated weighted

Maldives

38

213.14

0.23

0.02

0

0.32

2004

Nepal

38

68.06

24.82

5.55

1.76

29.96

2010.2

Pakistan

38

73.39

13.47

1.9

0.43

173.59

2007.5

Sri Lanka

38

117.66

4.11

0.65

0.18

20.86

2009.5

Source: PovcalNet: the on-line tool for poverty measurement developed by the Development Research Group of the World Bank

reduce hunger and undernourishment given its huge territorial extent and population pressure. In the next section (Table 5), based on the most recently available data on consumption expenditure, various income measures of poverty have been tabulated. The reference poverty line is the international poverty line of US$38 PPP per month. From the table, we find that of all the SAARC countries except Myanmar (data unavailable), Bangladesh tops the list of poverty measured in terms poverty head count ratio, poverty gap ratio and squared poverty gap ratio. Poverty head count ratio simply gives the proportion of the population living below the reference poverty line. Poverty gap ratio gives the extent of inequality in consumption expenditure or income. The squared poverty gap ratio gives the strength or intensity of the poverty measured in terms of inequality. Thus in terms of income poverty, Bangladesh has the highest amount of consumption (income) deprivations followed by India and Nepal. The population proportion living below the international poverty line is highest in Bangladesh. The following figure (Figure 2) shows the average annual change in poverty for the major SAARC countries on which the data is available. It is seen that all the selected South Asian countries have undergone a significant decrease in the

204

poverty head count ratio over the past decade. The highest rate of decline in poverty head count ratio has been recorded by Sri Lanka and Bangladesh followed by India. The following chart (Figure 3) shows the quintile distribution of the total consumption expenditure which is taken as a proxy of income. The bottom(poorest) 20 per cent of the population contribute just about 8 per cent to the total national income while the top(richest) 20 per cent of the population contribute about 40 per cent to the total national income in general across all the SAARC countries. This shows that there is a wide gap between the rich and the poor in terms of the distribution of the income generated. In the following figure (Figure 4), the poverty head count ratios for the selected South Asian countries measured at the international poverty lines have been estimated for the year 2010 at PPP. When measured with respect to the $2 a day (PPP) as the international poverty line, about 70 per cent of the population lies below the poverty line for the countries like India and Bangladesh. Bhutan and Maldives report the lowest incidence of income or consumption poverty at both the $2 and $1.25 daily poverty line (PPP).Pakistan fares better than India and Bangladesh in terms of the number of people living below the poverty line.

 The Inter-Linkage between Governance and Poverty

Figure 2. Average annual change in poverty ratios for the selected SAARC countries

Nonetheless, the various non-income parameters of poverty measurement are very significant indicators of human development and well being. Such parameters like nutrition status of the children, their access to the basic entitlements

like primary education, shelter, food, income earning opportunities etc. are important as well. Hence we look at the recent trend in the human development index for the selected South Asian countries (Table 6). The Human Development

Figure 3. Quintile distribution of the total income generated: Evidence on persistent Inequality

205

 The Inter-Linkage between Governance and Poverty

Figure 4. Poverty head count ratio for the south Asian countries Source: Poverty & Equity Databank and PovcalNet

Table 6. Human development index over the past two consecutive years in the south Asian countries Human Development Index (HDI) for South Asia,2011-12 2011 HDI_2011

2012 Rank

HDI_2012

% Change in HDI Rank

India

0.547

134

0.554

136

1.28

Pakistan

0.504

145

0.515

146

2.18

Bangladesh

0.5

146

0.515

146

3.00

Afghanistan

0.398

172

0.374

175

-6.03

Nepal

0.458

157

0.463

157

1.09

Sri Lanka

0.691

97

0.715

92

3.47

Bhutan

0.522

141

0.538

140

3.07

Maldives

0.661

109

0.668

104

1.06

South Asia

0.535

-

0.543

-

1.50

Source: UNDP 2011, 2012

206

 The Inter-Linkage between Governance and Poverty

Figure 5. Trend in GDP per capita across the SAARC countries Source: World Bank Data,2001-13

indices for the countries have been tabulated and the changes in the ranks indicate whether there has been any improvement in the human development indicators. Except Afghanistan, which scores abysmally low in the human development index, all other selected South Asian countries which are members of the SAARC fare moderately in terms of human development index. In the latest two years as available with the UNDP, we find that Sri Lanka and Maldives have improved their ranks whereas India and Afghanistan have gone down in the international ranking although all the countries have got a better HDI in 2012 than in 2011. The annual rate of change clearly shows that the quality of life in Afghanistan has degraded remarkably and thus the HDI has gone down by about 6 per cent in a year. Among other SAARC countries, Sri Lanka, Bangladesh and Bhutan have improved on the HDI by about 3 per cent over the previous year. India, Nepal and Maldives are the strugglers

in improving the HDI with a marginal 1 per cent improvement in HDI. From the chart (Figure 5), it is evident that among all the SAARC countries, Maldives stands alone as the topmost generator of GDP per capita over the past 13 years. The country’s high GDP per capita is mainly attributed to the growing popularity of the country over the recent years as a popular holiday destination from all over the world. The tourism industry generates the major revenue for the country with small territorial bound and less dense population compared to its other SAARC counterparts. The GDP per capita of Maldives is about five times as that of India. Among the other SAARC countries, Sri Lankan economy is the second highest generator of GDP followed by Bhutan, India and Pakistan. Over the past six years, the growth rate of GDP seems to have accelerated in nearly all the countries but the progress is shooting in Maldives.

207

 The Inter-Linkage between Governance and Poverty

Figure 6. Voice and accountability in SAARC countries, 2000-2012

Source: World Bank Data,2000-12

In this section, we show the trend in the six indicators of governance as listed by the World Bank across the eight SAARC countries since 2000. The estimates of Governance are measured on a scale ranging from - 2.5 for the worst performance to + 2.5 for the best performance in terms of the concerned governance indicator. Among the SAARC countries, except India all other member countries exhibit a negative estimate of the indicator of voice and accountability which implies that Indians irrespective of their caste, gender and ethnic background exercise the freedom of expression, freedom of speech, the right to participate in the selection of the government and standing against the motion. Among the other countries, Afghanistan fares worst where the people don’t exercise their freedom to express and to participate in the country’s decision making process. Countries like Bhutan and Pakistan has shown an improvement in terms of the said indicator (Figure 6). In terms of the government’s effectiveness, it can be seen that countries like Bhutan and Mal-

208

dives, where the index of government effectiveness was high during 2000 gradually decreased and converged in 2004 with that of India which maintained a steady index of about -0.15 over the past 12 years. Afghanistan over years has managed to fare slightly better than in terms of the index from -2.4 in 2000 showing ineffective government which improved gradually and stabilized around -1.5 from 2006 and onwards. This can be well related to the crisis that Afghanistan has been facing after the war (Figure 7). The regulatory quality of a Government captures the perception of the ability of the government to implement and promote policies featuring private sector development. Maldives, besides Sri Lanka, was the only country among the SAARC countries to have positive index of regulatory quality (Figure 8) in early 2000s which later deteriorated and signifies a weak state of governance in terms of the said indicator. As usual, war in Afghanistan has left the country devastated which has resulted in weak governance catered by poor execution of rule of

 The Inter-Linkage between Governance and Poverty

Figure 7. Government effectiveness in SAARC countries, 2000-2012 Source: World Bank Data,2000-12

law thereby resulting in awful regulatory quality of the government (Figure 9). The trend in control of corruption has been plotted in the following figure (Figure 10) which shows that only Bhutan among the SAARC

countries has a positive estimate of corruption over the years of study and the index has been improving moderately over years. All other countries managed to remain below the benchmark of fair governance.

Figure 8. Regulatory quality in SAARC countries, 2000-2012 Source: World Bank Data,2001-12

209

 The Inter-Linkage between Governance and Poverty

Figure 9. Rule of law in SAARC countries, 2000-2012

Source: World Bank Data,2000-12

In terms of political stability and absence of violence (Figure 11), only Maldives and Bhutan reported to be politically stable since 2001 which has declined in 2007 but has stabilized since then. But other SAARC countries have consistently

been politically unstable and violent featuring the instances of weak governance in these countries which are dense in population with varied ethnic and religious backgrounds.

Figure 10. Control of corruption in SAARC countries, 2000-2012 Source: World Bank Data,2000-12

210

 The Inter-Linkage between Governance and Poverty

Figure 11. Political stability and absence of violence in SAARC countries, 2000-2012 Source: World Bank Data,2001-12

Summary of Results In this section, which simply analyses the trend in GDP per capita across countries over the last twelve years shows that all SAARC countries have experienced a rise in GDP per capita but Maldives has been doing exceptionally well among all its counterparts with a GDP per capita which is more than five times as that of India. In terms of the governance indicators, we find that Afghanistan reports very weak state of governance as measured by all six indicators, whereas Bhutan reports positive index of governance like control of corruption, rule of law, government effectiveness, and political stability. To our surprise, the regulatory quality and the freedom of people to raise their voices against the motion is quite poor in the said country. Maldives continues to be one of the popular holiday destinations in the South East Asia due to its consistent political stability and absence of violence and terrorism. This has a huge positive impact on the GDP of the country at large. All other countries like India, Nepal,

Bangladesh, Sri Lanka and Pakistan have weak indices of governance with India as the only country among its counterparts which has a good estimate of voice and accountability pertaining to the freedom of speech, freedom to move against the motion and freedom of media. This section illustrates impact of GDP per capita and the employment population ratio on the global hunger index (Table 7). The coefficient of log(GDPPCPPP) being -0.514 implies that Global Hunger Index is inelastic with rising GDP per capita measured at purchasing power parity. If GDP per capita rises by 1 per cent, GHI decreases by 0.51 per cent which is very obvious. Hunger and undernourishment ought to decline with rising income or GDP per capita. Again, the coefficient of log (EMP_POP) is -0.723 implies that GHI is highly inelastic with rising employmentpopulation ratio. If employment to population ratio increases by 1 per cent, GHI decreases by 0.72 per cent which makes sense. As employment increases, income goes up; hence households get the required food for their survival and also the

211

 The Inter-Linkage between Governance and Poverty

Table 7. Panel regression analysis: Measuring the impact of GDP per capita (PPP) and employment to population ratio on the global hunger index for selected SAARC countries Dependent Variable: LOG(GHI) Method: Panel Least Squares Sample: 1990 1995 2000 2005 2012 Periods included: 5 Cross-sections included: 5 (India Pakistan Bangladesh Sri Lanka Nepal) Total panel (balanced) observations: 25

log (GHI) = β0 + β1 .log (GDPPCPPP) + β2 .log (EMP _ POP) + ut Coefficient

Std. Error

t-Statistic

Prob.

log(GDPPCPPP)

β1 = -0.514

0.141

-3.629

0.001

log(EMP_POP)

β2 = -0.723

0.343

-2.105

0.046

Constant

β0=7.0333

1.637

4.295

0.000

R-squared

0.448

Mean dependent var[log(GHI)]

3.136

Adjusted R-squared

0.397

S.D. dependent var[log(GHI)]

0.218

S.E. of regression

0.169

AIC

-0.600

Sum squared residual

0.631

SBC

-0.453

Log likelihood

10.501

HQ criterion

-0.559

F-statistic

8.930

DW statistics

0.726

Prob(F-statistic)

0.001

Source: Calculated from secondary data available from IFPRI, World Bank and ADB, 1990-2012

basic health services. Thus the incidence of child mortality due to undernourishment and prevalence of underweight children become very rare with increasing employment opportunities. Thus we can arrive at a conclusion that over the years from 1990, for the five SAARC countries viz. Bangladesh, Nepal, Pakistan, India and Sri Lanka, data for which were available for all the parameters under our consideration, the incidence of hunger and hence poverty has been declining over years from 1990 to 2012 with rising GDP per capita (PPP) and employment. The other three SAARC countries could not be included in the analysis due to unavailability of data for the specified years and the variables of concern.

212

Table 8 tabulates the results of the panel regression which has been based on data pertaining to the per capita GDP of the selected South Asian countries and the worldwide governance indicators. A balanced panel is prepared consisting of 8 cross-sections over the years 2007-13. Thus we have 56 observations in all. The dependent variable is the log of GDP per capita and the six dimensions of governance are the independent variables respectively. Besides these, there are certain other explanatory variables which are important determinants of the national output. From the analysis, it is found that good government effectiveness, regulatory quality and a stable political situation with absence of violence

 The Inter-Linkage between Governance and Poverty

Table 8. Panel regression for eight SAARC countries, 2007-13 log (gdppcn +1 ) = α 0 + α 1 * ge n + α 2 * rq n + α 3 * rl n + α 4 * ccn + α 5 * va n + α 6 * psav n Independent Variable

Coefficient

Standard Error

t statistic

P>t

ge

1.273

0.446

2.85

0.006

rq

0.936

0.309

3.03

0.004

rl

-0.664

0.487

-1.36

0.179

cc

-0.481

0.311

-1.55

0.128

va

-0.285

0.201

-1.42

0.161

psav

0.440

0.108

4.08

0.000

constant

8.128

0.230

35.39

0.000

Number of observations

56 F(6, 49)

18.23

Prob > F

0

R-squared

0.6907

Adj R-squared

0.6528

Root MSE

0.48632

Source: Calculations based on World Bank Data, 2006-13

stimulate the GDP per capita to a large extent. On the other hand, the ability of the people to raise their voice, the government’s action to control corruption and the rule of law are seen to be having a detrimental effect on the per capita GDP of the SAARC countries. The most significant variable affecting the growth rate of GDP in the next period is government effectiveness with a coefficient of 1.27, a high‘t’ value at 94 per cent level of significance. Similarly, regulatory quality and political stability and absence of violence were also found to be positively affecting the GDP growth at 96 per cent and 100 per cent level of significance respectively. The model fits well as the R2 is moderately high for 56 observations only. The rest of the indicators were moderately significant in augmenting the SAARC countries’ economic output. However, the dynamics may vary from country to country depending on the country’s internal situations, the economic and political situation of the country.

Thus, from the analysis, it is clear, that counties with poor state of governance have low income. In terms of the indicator of government effectiveness, only Bhutan has a positive estimate of governance and a higher income (2013). On the other hand, exceptions are also there in countries like Maldives and Sri Lanka where in spite of having a poor state of government effectiveness, the GDP per capita is even higher than that of Bhutan which showed moderately good government effectiveness in 2013. Thus certain indicators act as important dimension of governance for certain countries and they cannot be generalized for all the countries across the entire time period of study.

CONCLUSION To sum up, the growing rate of GDP per capita measured at purchasing power parity is found to have a significant negative impact on the Global

213

 The Inter-Linkage between Governance and Poverty

Hunger Index of the SAARC countries of concern. As the GDP improves, the instances of poverty, hunger and malnourishment reported keeps on declining. The employment to population ratio was found to be having significant impact on the GDP per capita. As the country’s employment to population ratio goes up, citizens are empowered with income, the instances of poverty, hunger and malnutrition show significant reduction. To conclude, the developing nations with huge prospects for development must focus on administering the policy measures efficiently by effective and strict execution of the rule of law thereby acting as a facilitator for market transactions and social development. The respective governments must keep strict vigilance to check the rent seeking behavior among the public servants in developing nations who are very susceptible to taking bribes from the vulnerable low income vendors and beneficiaries which when exercised, plunge them into darker dens of poverty.

REFERENCES

Dollar, D., & Kraay, A. (2002). Growth is good for the poor. Journal of Economic Growth, 7(3), 195–225. doi:10.1023/A:1020139631000 Easterly, W. (2001). The Elusive Quest for Growth: Economists’ Adventures and Misadventures in the Tropics. Cambridge, Mass: MIT Press. Feldman, T., & Rossing, S. A. (1999). Social Capital: Conceptual Frameworks and Empirical Evidence: An Annotated Bibliography. World Bank Social Capital Initiative, Working Paper No. 5. Gray, C. W., & Kaufmann, D. (1998). Corruption and development. Finance & Development, 35(1), 6–10. Gupta, S., Davoodi, H., & Terme, R. A. (1998). Does Corruption Affect Income Equality and Poverty? IMF Working Paper 98/76, International Monetary Fund, Washington, DC. Heidenheimer, A. J., & Johnston, M. (Eds.). (2002). Political Corruption: Concepts and Contexts (3rd ed.). New Brunswick, NJ: Transaction Publishers.

ADB. (2013). Framework of Inclusive Growth indicators 2013: Key indicators for Asia and the Pacific. Retrieved from http://www.adb.org/publications/framework-inclusive-growth-indicators2013-key-indicators-asia-and-pacific

Hellman, J., Jones, G., & Kaufmann, D. (2000). Seize the state; seize the day—state capture, corruption, and influence in transition. Policy Research Paper no. 2444, The World Bank, Washington, DC.

Barro, R. J. (1996). Determinants of Economic Growth: A Cross-Country Empirical Study. National Bureau of Economic Research Working Paper no. 5698.

IFPRI. (2013) Global Hunger Index. Retrieved from http://www.ifpri.org/ghi/2013 last accessed on 07/06/2014

Bread for The World Institute. (2012). Within Reach Global Development Goals 2013 Hunger Report. Cartier-Bresson, J. (n.d.). Economics of Corruption. In Spotlight Corruption. Chetwynd, E., Chetwynd, F., & Spector, B. (2003). Corruption And Poverty: A Review of Recent Literature. Management Systems International.

214

Johnston, M. (2000a). The New Corruption Rankings: Implications for Analysis and Reform. Paper presented at the International Political Science Association, World Congress, Quebec City, Canada. Johnston, M. (2000b). Corruption and Democracy: Threats to Development, Opportunities for Reform. Paper prepared for Department of Political Science, Colgate University.

 The Inter-Linkage between Governance and Poverty

Johnston, M. & Kpundeh S. (2002). The Measurement Problem: A Focus on Governance. Unpublished, January 2002. Karstedt, S. (2001). The Culture of Inequality and Corruption: A Cross-National Study of Corruption. Department of Criminology, Keele University. Kaufmann, D. (2002). Governance Empirics. Presentation at State Department, April 19, 2002. Kaufmann, D., & Kraay, A., & Zoido-Lobaton, P. (1999). Governance Matters. World Bank Policy Research Working Paper No. 2196. Kaufmann, D., & Kraay, A., & Zoido- Lobaton, P. (2000). Governance matters: From measurement to action. Finance & Development, 37(2), 101–113. Kaufmann, D., & Kraay, A. (2002). Growth without governance. Economia, 3(1), 169–229. Kaufmann, D., & Kraay, A. & Pablo Zoido- Lobaton. (2002). Governance Matters II, Updated Indicators for 2000/01. World Bank Policy Research Working Paper 2772. Kaufmann, D., Mehrez, G., & Gurgur, T. (2003). Voice or Public Sector Management: An Empirical Investigation of Determinants of Public Sector Performance Based on a Survey of Public Officials. Washington, DC: World Bank, June. Knack, S. (2002). Social Capital, Growth and Poverty: A Survey of Cross-Country Evidence. In C. Grootaert & T. van Bastelaer (Eds.), The Role Of Social Capital In Development: An Empirical Assessment. Cambridge, UK: Cambridge University Press. doi:10.1017/CBO9780511492600.004 Lambsdorff, G. J. (1999). Corruption in Empirical Research: A Review. Transparency International Working Paper.

Lambsdorff, G. J. (2001). How Corruption in Government Affects Public Welfare: A Review of Theories. Paper prepared for the Center for Globalization and Europeanization of the Economy, Gottingen, Germany. Mahbub ul Haq Centre (2012). Human Development in South Asia: Governance for People’s Empowerment. Mahbub ul Haq Centre (2013). Human Development in South Asia: Water for Human Development. Mauro, P. (1998). Corruption: Causes, Consequences, and Agenda for Further Research. Finance & Development, (March), 11–14. Mauro, P. (2002). The Effects of Corruption on Growth and Public Expenditure. In Heidenheimer and Johnston (Eds.), Political and Bureaucratic Corruption (pp. 312-313). Transaction Publishers. Murphy, K., Shleifer, M., Robert, A., & Vishny, W. (1993). Why is Rent-Seeking So Costly to Growth? The American Economic Review, 83(2), 409–414. North, D. C. (1990). Institutions, Institutional Change and Economic Performance. Cambridge University Press. Quibria, M. G. (2002). Growth and Poverty: Lessons from the East Asian Miracle Revisited. Asia Development Bank Research Paper 33. Rose-Ackerman, S. (1978). Corruption: A Study in Political Economy. NY: Academic Press. Rose-Ackerman, S. (1999). Corruption and Government: Causes, Consequences and Reform. Cambridge, UK: Cambridge University Press. doi:10.1017/CBO9781139175098 Rose-Ackerman, S. (2001). Trust, honesty and corruption: Reflections on the state building process. European Journal of Sociology, 42(3), 27–71. doi:10.1017/S0003975601001084

215

 The Inter-Linkage between Governance and Poverty

Rose-Ackerman, S. (2002). When is Corruption Harmful? In Heidenheimer and Johnston (Eds.), Political and Bureaucratic Corruption. Transaction Publishers. Tanzi, V. (1998). Corruption Around the World: Causes, Consequences, Scope and Cures. IMF Staff Papers, 45, 4. Tanzi, V., & Davoodi, H. (1997). Corruption, Public Investment and Growth. IMF Working Paper 97/139. UNDP. (2013) https://data.undp.org/dataset/Table-1-Human-Development-Index-and-its-components/wxub-qc5k last accessed on 03/06/2014 UNDP (United Nations Development Programme). (2002). Human Development Report 2002. New York: Oxford Univ. Press. USAID. (1999). A Handbook on Fighting Corruption. Technical Publication Series. Center for Democracy and Governance. World Bank. (2000a). Anti-Corruption in Transition: A Contribution to the Policy Debate. World Bank. (2000b). Helping Countries Combat Corruption: Progress at the World Bank Since 1977. World Bank. (2000c). Making Transition Work For Everyone: Poverty and Inequality in Europe and Central Asia. Washington D.C. World Bank. (2001). World Development Report 2000/2001: Attacking Poverty. Oxford University Press. World Bank. (2002). World Development Report 2003: Sustainable Development in a Dynamic World: Transforming Institutions, Growth and Quality of Life. World Bank and Oxford University Press. Zak, P., & Knack, P. (1998). Trust and Growth. IRIS Center Working Paper No. 219.

216

KEY WORDS AND DEFINITIONS Corruption: Corruption is the misuse of entrusted power (by heritage, education, marriage, election, appointment or whatever else) for private gain. Developing countries: Developing country is a term generally used to describe a nation with a low level of material well-being (not to be confused with third world countries). Since no single definition of the term developed country is recognized internationally, the levels of development may vary widely within so-called developing countries. Some developing countries have high average standards of living. Countries with more advanced economies than other developing nations, but which have not yet fully demonstrated the signs of a developed country, are categorized under the term newly industrialized countries. Economic Development: The act or process of growing or causing something to grow or become larger or more advanced. Economic Inequality: Economic inequality (also described as the gap between rich and poor, income inequality, wealth disparity, wealth and income differences or wealth gap) is the state of affairs in which assets, wealth, or income are distributed unequally among individuals in a group, among groups in a population, or among countries. The issue of economic inequality can implicate notions of equity, equality of outcome, and equality of opportunity. Governance: The way that a city, company, etc. is controlled by the people who run it. Hunger: It is a craving, desire, or urgent need for food and an uneasy sensation occasioned normally by the lack of food and resulting directly from stimulation of the sensory nerves of the stomach by the contraction and churning movement of the empty stomach. SAARC Countries: The South Asian Association for Regional Cooperation (SAARC) is an economic and geopolitical organization of eight countries that are primarily located in South Asia.

 The Inter-Linkage between Governance and Poverty

ENDNOTES

1



2

A Report titled “ SAARC Regional Poverty Profile”, 2013. Report titled ‘Human Development in South Asia 2012: Governance for People’s



3

Empowerment, pp.36 (http://mhhdc.org/wpcontent/themes/mhdc/reports/HDSA-2012. pdf) http://cpi.transparency.org/cpi2013/ results/#myAnchor1

217

218

Chapter 11

Sustaining Governance: The Case for Leadership Olanrewaju Olaoye University of Lincoln, UK

ABSTRACT This chapter has three core aims. First, to discuss the concepts of governance and leadership while drawing upon key literatures and qualitative data to make sense of the factors that can enable leadership to sustain governance systems. Second, the chapter explores the practice of leadership at the Greater London Authority (GLA) level in the United Kingdom (UK) in order to establish features synonymous with the practice of leadership. Third, the relations between governance and leadership are explored so as to better understand how the latter is employed in sustaining the governance process at the GLA level in the UK.

INTRODUCTION Leadership is important across various institutional settings due mainly to its role in steering, coordinating and enabling the creation of the necessary environment needed to allow for the functioning of any organization, institution or society. The governance of a place or an organization is also significant for planning and implementation purposes and for ensuring the making and enforcement of rules. This chapter explores the concept of leadership due to its relevance in sustaining the practice of governance across different levels. While governance is arguably a complex concept as reflected in its contrasting definitions, leadership is better understood.

In politics, leadership occurs on many different levels, from the Mayor of London (Boris Johnson) whose jurisdiction is London, to the UK Prime Minister (David Cameron) who ultimately is responsible for the protection and services of the entire country he preside over, and regional president such as the President of the European Commission (Jean-Claude Junker), who ensures members of the EC engages with one another in a fair manner. Thus, it is clear that leadership occurs across different levels. To better understand the concept of governance and leadership, this chapter is structured as follow: The first section discusses the concept of governance. Stoker’s (2004) definition of governance as referring to the rules and forms that guide col-

DOI: 10.4018/978-1-4666-8274-0.ch011

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Sustaining Governance

lective decision-making is employed. This then makes it clear that governance is not just about one individual making a decision but rather about groups of individuals or organizations or systems making decisions. Thereafter, the definitions of political leadership are considered. In defining leadership, here the view of Northouse (2013) who defines leadership as a process whereby an individual influences a group of individuals to achieve a common goal, is employed (see also Western (2008)). Subsequently, the case of leadership at the Greater London Authority (GLA) is examined drawing on qualitative data. The fourth section seeks to understand the relationship between leadership and governance, especially on how the latter inform the former. To conclude, the fifth section argues for the relevance of good leadership in sustaining governance across levels in the society in order to sustain socio-economic developments.

THE CONCEPT OF GOVERNANCE The concept of governance has existed for quite a long time and its formal use can be traced to the work of Plato where he referred to governance as a way of designing a system of rule (Kjær, 2004). Governance as a concept witnessed a renaissance in the 1980s and 1990s as several authors (March & Olsen, 1995; Kooiman, 2003; Kjær, 2004; Leftwich, 1993, 1994; Rhodes, 1997; Stoker, 1998) defined the concept based on their interpretation and emerging trends. However, despite the definitional problem suffered by the term especially due to its use in different contexts, it shall be defined here according to Stoker (1999) as rules guiding collective decision among interconnected stakeholders.

LITERATURE SURVEY Although governance literatures (Sullivan & Skelcher, 2002; Stoker, 1997; Kooiman, 2003;

Healey, 2006) suggest that there are multi-level institutions and organizations involved in the governing process, thereby witnessing a reduction in the role of the state (the power of the state becoming de-centered as argued by Newman et al., 2004), the reality based on some case studies is that the state, especially in the UK has developed more means (use of commissions such as the National Audit Office and Ofsted) to regulate the powers it hitherto devolved in the governing process. Elsewhere, Bovens, T’Hart and Peters (2001) also critiqued governance based on the failure of the new governance structure to adapt to the new conditions of co-dependence identified by Newman, Barnes, Sullivan and Knops (2004) to include citizens depending on interactions with the state, state actors depending on citizens to participate in government policies and service users dependence on feedback mechanism in order to influence the policy process that delivers public goods and services. Furthermore, democratic channels have also partly failed to address increasing citizen differentiation and reflexivity as central government policies sometimes conflict with local and other spheres of government priorities and developmental needs. Notwithstanding the challenges inherent in governance, it has fundamentally changed the structure of governing from government use of hierarchies to networks, and from the state use of direct control to approaches devised to engage a number of stakeholders. However, despite the aforesaid change in the structure of governing, it is pertinent to note that the state in particular its leadership still plays key roles (regulator and producer (Evans, 1995)) by using the tools of government for example, law and regulation, public spending and taxation, bureaucracy, institutions, information and networks especially to protect citizens while delivering relevant public goods and services (John, 2011). While commenting on governance in the UK, Newman et al. (2004) suggests that intricate social issues, for example, social exclusion, community regeneration and inequalities cannot be addressed by using the 219

 Sustaining Governance

traditional approach of governing in which the state is responsible for the delivery of most public goods and services because contemporary public needs and demands are multifaceted, consequently demanding multi-dimensional solutions. Thus, it is understandable that the state for example in the UK, redefined its role by making different governance permutations (use of hierarchical governance and use of network governance) as regard the ways it delivers public goods and services. In furthering the understanding of the concept of governance, Stoker’s (1997) interpretation of the concept as focusing on the interdependence of governmental and non-governmental bodies in meeting challenges because governance is about the former and latter bodies working together will suffice. Similarly, Kooiman (2003) emphasized that governance represents a shift from the state as the central governing actor to state-society relations (society mix) as central governing actors. This shift in the practice of governance is attributed to the increasing diversity, complexity and socio-political issues which emerge from various factors, and which make governing objectives difficult to define. Thus, governance is important because it is a societal mix operating in different modes (self-governing, co-governing and hierarchical governing) in order to address prevalent and emerging societal challenges. In addition, governance is significant because it reflects the reality of government not being the sole actor that addresses the challenges of public service delivery (Kooiman, 2003). Akin to the definitional stance of Kooiman (2003) and Stoker (1997), Rhodes (1997) comments that governance is a process of governing, especially through self-organising, interorganisational networks which are characterised by interdependence, exchange of resources, adherence to the rules of the game and considerable autonomy from the state. In explaining the concept, Rhodes (1997) suggest that governance could be construed as the minimal state in terms of its extent and form in intervening in public

220

affairs; as the New Public Management (NPM) which introduced private sector management tools and methods to the public sector, and as ‘good governance’ which was conceptualized based on Leftwich’s (1993) three strands of good governance which include systemic (efficient public service), political (respect for the rule of law) and administrative (accountable administration). Thus, it is clear that the concept of governance is fluid and flexible as it takes different forms while ensuring public services are delivered by any permutation of government and the private and voluntary sectors in collaboration with other stakeholders such as citizens. A fact that can be emphasized is that Rhodes’ (1997) argument is premised on government working through relevant established networks. However, it can be argued that since government steers the process, it may exercise some bias, especially while making decisions to work with certain networks that may be of more importance to the achievement of government policy goals. A typical example is while the previous Labour central government (1997-2010) in the UK criticised banks for paying huge bonuses to top executives despite their role in the world economic recession (2008-2010), the same government still rescued these banks by not allowing them to fail (collapse), probably due to the role of the big banks and other financial institutions in British capitalism. In commenting on governance, Osborne and Gaebler (1992) emphasized that, even though government is the instrument used by the society in solving its problems, there is a need for further reforms; hence as a result of existing conditions in their context (United States), they argued for what they termed ‘American perestroika’. This explains Osborne and Gaebler’s (1992) argument for the use of a reform process in addressing the challenges of governance in the United States. Despite the aforementioned stance of Osborne and Gaebler, especially as pertaining to the use of government and self-organized networks in making necessary reforms to address the challenges

 Sustaining Governance

of service delivery, it can be noted that Rhodes (1997) and Osborne and Gaebler (1992) share a common ground especially on the use of collectives and networks embedded in the society to be crucial components of governance. However, Rhodes (1997) and Kooiman (2003) established that governance is different from government because of its multi-level and spheres of operation as it occurs outside and across various tiers of government. Due to the need to better understand the role of governance vis-a-vis institutions, the suggestion of March and Olsen (1995) was explored. March and Olsen argued that, using an institutional lens, a democratic polity is formed by its fundamental practices and rules while politics is organized through the interdependent responsibilities of political identities (1995). Thus, they argued that governance involves the structures within which citizens and officials act, and where politics occurs in order to shape the institutions of the society. Leftwich (1994) sought to classify governance by identifying three definitional strands. Firstly, he defined governance according to most Western politicians as a legitimate and democratically elected government fashioned along liberal democracy. On a second note, he defined governance according to the World Bank, which links good governance to good administration, and efficient and accountable public services. Thirdly, he conceives governance from a systemic point of view as a further looser and wider distribution of both internal and external political and economic power. Through this definition of governance, more emphasis is placed on structures of political and economic relationships and rules that determine in the long term the process by which public goods are delivered and how a society is governed. In essence, the classification of Leftwich (1994) further demonstrates some of the diversity and similarities characterising the definition of governance. In another attempt to understand the definition and use of the term governance, Healey (2006)

has commented that the system of governance of a society refers to the methods by which the collective affairs of the society are managed. Hence, “governance involves the articulation of rules of behaviour with respect to the collective affairs of a political community; and of principles for allocating resources among community members”. Healey further argued that government is the apparatus that legitimises programmes and policies taken on behalf of any given political community (associations of people with a common interest) and speaks for the collective concerns of such community using collective interests and values which are symbolized in terms such as the ‘common good’ or the ‘public interest’. It is imperative to note that such political communities may have no basic territorial definition, or they may also be territorial communities identified by cultural associations with place or by the boundaries of political jurisdictions, such as all those living in a particular local government area. Hence, as governments operate across territorial communities, they may engage stakeholders from outside or inside any given territorial area in order to tackle the provision of public goods and manage any externality effects.

CHARACTERISTICS OF GOVERNANCE Having discussed the propositions of some authors about the concept of governance, this section examines some common and different features which traverse previous discussion. First, it is clear that governance is a ‘process’ hence, it is not static. Stoker (1997), Rhodes (1997), Osborne and Gaebler (1992), Leftwich (1994) and Kooiman (2003) all established this fact in their definitions of governance as discussed earlier. This has influenced the working definition of governance employed here which interpret governance as a ‘process’ where rules guide collective decision making among actors interconnected. Furthermore, it was clear

221

 Sustaining Governance

from the discussion of governance that authors including Stoker (1997), Osborne and Gaebler (1992), Kooiman (2003), March and Olsen (1995) share common perspective that governance has features such as the interdependence of government and NGOs, inter-organisational networks, collectives, partnerships, interplay of interests and coalition building. The discussion of governance according to Stoker (1997), Kooiman (2003), and March and Olsen (1995) also show that the concept could be seen as a means to an end as it uses different frameworks to mitigate problems while the government steers (creates the enabling environment and means for achieving set goals) the process in which policies are made for relevant targets. Another feature of governance observed by Healey (2006) suggests that the concept has capabilities which enables it to be used as an apparatus which legitimises any given policy or programme taken on behalf of a political community or association of people while occurring in or outside or across any given territory. Notwithstanding the alleged capability of governance as argued by Healey (2006), some of the literature on the concept shows that the processes of governance have been construed by different authors to be marred by various factors such as conflicts and the challenge of how to determine who participates in the governance process. Furthermore, it is surprising to note that even though some literatures have argued for the existence of the change from ‘government to governance’, it must be emphasized that ‘government’ still plays a leadership role in the governance process. Nonetheless, evidence from some governments, for instance the UK and US governments in the 1990s demonstrate the use of reform programmes as a means to transfer hitherto government functions to other sectors such as the private and third sectors, and institutions operating at different government levels thereby partly validating the claim of the change from government to governance.

222

In summarizing the discussion focused on governance, it can be established from the various definitional stances discussed that at the core of governance are political processes (inclusive or exclusive), participating institutions, networks, and collaborations including a mix of actors from the public, private, voluntary sectors and civil society. Hence, governance materializes when there is a shared task (overt or covert) among the various actors involved in the processes mentioned (political processes, participating institutions, networks), and which also shape the nature of collaboration. It is also important to note that leadership through governments was observed in the governance process as suggested in literature. This therefore suggests that leadership is imperative for establishing a governance framework. However, this is counter Rhode’s (1997) argument which proposes that governance may operate through self-organizing networks. The literature examined shows that it makes sense having a broad view of how governance occurs in order to understand its inherent intricacies and possible solutions. Hence, a deep understanding about the process, participating stakeholders, and networks that determine and shape governance, will further our understanding of the concept. Kooiman’s (2003) three modes of governance (‘self-governing’ capacities of social systems; ‘co-governing’ arrangements; and ‘hierarchical’ governing) confirm that governance is a fluid but also complex concept. To enable the understanding of the roles of leadership in the governance process, leadership is discussed in the next section.

LEADERSHIP Leaders can be found in many institutional settings, whether it be a school classroom where the teacher must educate their students, religious settings for instance the pope, or executives at a multi-national

 Sustaining Governance

corporation, and of course; politics. In politics, leadership occurs on different levels, from the local mayor whose jurisdiction is the city they live in, to the regional president and the head of state who ultimately becomes responsible for the protection and services of the entire country they preside over. This section examines the historical and contemporary definitions of political leadership. In this context Gourevitch (1979) states, political leadership ‘constructs and maintains strong central institutions common to the whole country and formulates common policies’. But what makes a good political leader? Machiavelli (2009) prescribed a set of criteria outlining the qualities a prince (leader) should possess in order to have effective control over his territory. Political leaders come from both democratic and non-democratic institutions. In terms of non-democratic leaders, their ascension to power may have come from war, becoming ‘legal’ when establishing new law in the reformed state. Even in democratic states, widespread corruption or intimidation can create an atmosphere where processes are unfairly carried out. Furthermore, it is clear that political leaders are allowed to exert their influence on everyone in their territory even if those people do not have voting rights. Take for instance illegal immigrants who have no voting right but who are still under the authority of the political leader in the state where they are resident. Political leadership then does not need democracy for it to be established as it can be created when a man or woman becomes a leader, regardless of the means to this end. Whether or not it is considered legitimate by outsiders has no bearing if the ruling body has constructed those central institutions and policies within its borders. In response to Weber’s three pillars of leadership (traditional, legal and charismatic), Elcock (2001) seeks to outline a logical description as to why a person or group of people (a body) comes to have authority, power and influence, he states:

1. A man has authority if it follows from his saying ‘let X happen’, that X ought to happen. 2. A man has power if the result of his saying ‘let X happen, is that X does happen. 3. A man has influence if the result of his saying ‘let X happen’ is that other people will say (perhaps only to themselves), let ‘let X happen’. How leaders then use their authority varies. For instance, there are some leaders who feel that there has been some kind of divine call to duty as was once described by Weber. This divine duty may unite followers of the particular leader because of a shared common belief (Wildavsky, 1989). What follows can often be described as a quixotic relationship between leader and follower, which may or may not consider the future consequences of the leader’s actions. In democratic societies, voters are allowed to oust a person who they see as abusing their authority, power and influence. In non-democratic societies or democratic societies where the situation has created a non-democratic environment, removing a political leader may be more difficult due to established structures.

LEADERSHIP AS PRACTISED IN THE GOVERNANCE SYSTEM IN LONDON The leadership definition by Northouse (2013) was adopted for analysis here because the study of the governance system in London shows that the Mayor of London, as political leader, influences actors through his powers and capacity within a group context in order to achieve goals such as delivering effective integrated mass transportation while making London the destination for business. The Mayor, as the political leader, employs some elements of strategic leadership, which can be defined as the creation of an overall sense of purpose and direction which guide integrated strategy

223

 Sustaining Governance

formulation and implementation. For instance, evidence from the study of the governance system in London reveals that in sustaining the delivery of the key priorities of the GLA, the Mayor works with non-governmental actors, committees and some politicians in the London Assembly including those serving as Deputy Mayors,1. Furthermore, the Mayor uses his leadership position to engage with business and London boroughs by working in partnership with them on relevant aspects of their Local Implementation Plans in order to ensure the implementation of London-wide initiatives, such as Cross rail 1, the Barclays Cycle Hire scheme and Barclays Cycle Superhighways2. Thus, due to the powers of the Mayor it was not surprising to observe that he played different leadership roles (political and strategic) in order to coordinate the system and sustain the delivery of public services. While it is clear the Mayor provides leadership for the making and implementation of relevant policies and for governing the system in London, the London Plan stresses that his policies would be delivered through partnership working among some actors for projects such as the Upgrade of the Underground, Cross rail 1, and the Barclays cycle scheme. Nonetheless, it can be argued that these partnerships are not immune to problems, such as the exclusion of certain actors or interests, thereby serving as additional potential source of conflicts. For instance, the Borough Partnership, which consists of 33 London boroughs, works closely with Transport for London (TfL) to provide a range of local transport initiatives while excluding actors from the private sector. While the operation of this partnership could result in some degree of conflict as the excluded actors may withhold their supports, there was no evidence of such an occurrence to support this argument. The discussion of the leadership functions of the Mayor thus enable an understanding of the Mayor’s role in London in order to gain further insight on how such roles enable or restrict the governance process in London. Notwithstanding the powers possessed by the Mayor as conferred

224

under the GLA Act 1999, which enable him to employ and deploy resources for the planning and implementation of relevant policies, some actors in the governance system were of the opinion that central government should lead the system in London due to its resource capacity (grants), which they see as key for the sustainability of service delivery in London. Other actors believed that the Mayor and a strategic body such as Transport for London (TfL) which is responsible for planning and implementing inter-modal schemes were most suited to lead the system in London due to the strategic expertise on integrated mass transport of TfL, and the powers of the office of Mayor. Another interviewee was of the view that the leader of the governance system should have strategic and resource capacity, and also should be allowed by central government to retain a significant proportion of the tax revenue London generates. The interviewee goes on to argue that central government control over revenues generated from London limits the funding power of the Mayor. Some other actors were also supportive of the Mayor’s leadership, as they presented the view that the existence of a powerful Mayor is in the interest of London especially for the purpose of enabling socio-economic development and sustaining the delivery of public services such as mass transportation. Lastly, another interviewee from TfL supported the leadership of TfL and the Mayor as he was of the view that both actors play significant roles relating to strategy, planning and the coordination of the system. It is thus clear that the majority of actors in the governance system in London wanted the Mayor and TfL to lead the system due to the funding capacity of the former and the strategic competence (the capacity to plan and implement transport projects) of the latter. Thus, actors made the argument for a leadership structure which employs official powers in influencing and coordinating actors in the system. Most interviewees supported the leadership of the Mayor due to the powers of the office in relation to the making

 Sustaining Governance

and implementation of policies aimed at Londonwide development. The actors that provided data indicated that they were in support of the various London-wide policies and projects implemented by the Mayor, irrespective of the inconveniences associated with some of the projects, as evidenced by the closure of some Underground lines due to engineering/maintenance work thereby causing more hardship to users. This therefore shows that regardless of the differences existing among organizations and in the Mayor’s role, key actors from different organizations indicate their support for the Mayor’s leadership including his programmes. From the study of leadership, the four governments (Metropolitan Board of Works, London County Council, Greater London Council and Greater London Authority) that have administered London since the emergence of its governmental institutions shows that regardless of the form of government adopted in governing in London, there are some responsibilities which the political leader performs. Heywood (2007) outlines the five most important of these responsibilities to include ceremonial duties, control of policymaking, popular political leadership, crisis response and bureaucratic management.

RELATIONSHIP BETWEEN LEADERSHIP AND GOVERNANCE From the discussion of leadership and governance, the data gathered from the case of London has shown that a leader is particularly important for coordinating and sustaining the governance process in any milieu similar to London. Hence, it is argued here that leadership enables the governance process as the case of London shows how the Mayor through his leadership enables and sustains the delivery of public goods and services. The study however shows that the practice of leadership has been affected by the fluidity of the concept of governance which has witnessed an increase in the numbers of actors engaged in

the governing process. For instance, although it is clear the Mayor is powerful as illustrated with his political and strategic powers (the power to levy three transport-related charges: a congestion charge, emissions charge, and workplace parking levy; the power to raise funds through the Business Rate Supplement and Community Infrastructure Levy (CIL) which is being employed for funding Cross rail 1; and the power to direct boroughs to change their local plans to ensure conformity with the London Plan (Sandford, 2013)) thereby influencing actors in the governance process in London, nonetheless, the study shows that central government employs its superior powers relating to grants and statutes to influence GLA policies. Furthermore, it was clear that other actors in the governance process especially those from the private sector also partly influence the decisions of the Mayor relating to the provision of infrastructures to make London one of the best cities to do business. It is thus clear that there is a causal relationship between governance and leadership as found in the case of the governance system in London where the Mayor employs his powers in coordinating actors in the governance process. Furthermore, the three previous governments which had existed in London demonstrate the existence of relations between leadership and actors across sectors as previous political leaders of London and the incumbent have engaged with different actors for the purpose of service delivery. Hence, it is argued that leadership is key for enabling the governance process. However, there is the debate on what constitute ‘good leadership’. For instance, the findings from the study of the governance system in London show that majority interviewees view the Mayor’s leadership as ‘good leadership’. The study also shows that actors in London relate ‘good leadership’ with a leader who is able to coordinate actors and organizations in the system while also enabling the sustenance of the delivery of public goods and services. To further define what constitute good leadership, different factors

225

 Sustaining Governance

could be considered including the personalities of leaders, as people want to identify with a strong leader who has a good reputation, a history of success whether it be in politics or business; and charisma, as Friedrich (1961) suggests that ‘charismatic leadership is important’.

CONCLUSION Leadership is no doubt an important concept not only for sustaining the governance process of a state, society or institution but more importantly for coordinating and steering actors in any given system. The investigation of the case of London shows that not only is the Mayor’s leadership important for sustaining the delivery of public goods and services but that it enables the joining-up of all the actors in the system while also establishing the framework by which actors are held to account for their use of resources. This then shows that leadership also plays a strategic role in joining-up the components making up a system or society. One of the key findings from the study shows that actors in the governance system in London do not agree on the actor that should constitute the leadership of the governance system in London as different actors argued for diverse factors to be considered in choosing a leader for the governance system. In conclusion, the study of the case of London shows that the Mayor has delivered on some of his vision and plans relating to regeneration and the sustenance of inter-modal transportation for instance, through the implementation of Barclay’s cycles, the upgrade of London Underground and implementation of Cross rail 1, to aid capacity as set out in the Mayor’s Transport Strategy (2010) and The London Plan (2011). During the process by which the Mayor exercises his leadership roles and implement policies, both collaboration and imperative coordination3 were

226

identified. Furthermore, an illustration of how the Mayor coordinates the governance system is exemplified in the London Plan which statutorily requires all 33 London boroughs and the City of London Corporation to work jointly with TfL for the purpose of the collection of the Community Infrastructure Levy (CIL). Thus, through the Mayor’s leadership and policies in the London Plan and Mayor’s Transport Strategy (MTS), in particular the CIL, which must be implemented by both London boroughs and the Corporation, a structure was observed to be in place as directed by the Mayor. This chapter has discussed the concepts of governance and leadership while also showing evidence of their existence in the political system in London. While contradictory views exist among actors in the system in London on the preferred actor to lead, the evidence gathered shows that all interviewees believe there is need for strategic leadership to coordinate the governance system in London. However, it was also clear that these actors have different opinions on the criteria (funding capacity and the possession of power) that should be used in selecting the leader. Nonetheless, most of the interviewees in the study indicated their desire for a strategic leader who would play different (strategic and political roles) leadership roles in the system through influence towards advancing the delivery of public goods and services in London. Also, it was the view of all interviewees that the leadership of the governance system should be able to hold other actors to account for their functions. Nevertheless, in instances where actors support schemes that further their individual organisational goals, as witnessed with London First and operators of mass transportation, it is the opinion of the researcher that the leader of the system has a role to play in terms of coordinating the behaviours of actors.

 Sustaining Governance

REFERENCES Bovens, M., T’Hart, P., & Peters, G. (2001). Success and Failure in Government Policy. Cheltenham: Edward Elgar. Elcock, H. (2001). Political Leadership. Northampton: Edward Elgar. doi:10.4337/9781843762881 Evans, P. (1995). Embedded Autonomy: States and industrial transformation. Princeton: Princeton University Press. Friedrich, C. (1961). Political leadership and the problem of the charismatic power. The Journal of Politics, 23(1), 3–24. Gourevitch, P. (1979). The reemergence of ‘peripheral nationalisms’: Some comparative speculations on the spatial distribution of political leadership and economic growth. Comparative Studies in Society and History, 21(3), 303–322. doi:10.1017/ S0010417500012986 Healey, P. (2006). Collaborative Planning: Shaping Places in Fragmented Societies (2nd ed.). Basingstoke: Palgrave Macmillan. Heywood, A. (2007). Politics. Basingstoke: Palgrave Macmillan. John, P. (2011). Making Policy Work. Oxon: Routledge. Kjær, A. (2004). Governance. Cambridge: Polity Press. Kooiman, J. (2003). Governing as Governance. London: Sage Publications Ltd. Leftwich, A. (1993). Governance, democracy and development in the third world. Third World Quarterly, 14(3), 605–624. doi:10.1080/01436599308420345 Leftwich, A. (1994). Governance, the state and politics of development. Development and Change, 25(2), 363–386. doi:10.1111/j.1467-7660.1994. tb00519.x

Machiavelli, N. (2009). The Prince. Vancouver: Engage Publishing. March, J., & Olsen, J. (1995). Democratic Governance. New York: Free Press. Newman, J., Barnes, M., Sullivan, H., & Knops, A. (2004). Public participation and collaborative governance. Journal of Social Policy, 33(2), 203–223. doi:10.1017/S0047279403007499 Northouse, P. (2013). Leadership: Theory and practice (6th ed.). London: Sage. Osborne, D., & Gaebler, T. (1992). Reinventing Government: How the Entrepreneurial Spirit is Transforming the Public Sector. USA: Penguin Group. Rhodes, R. A. W. (1997). Understanding Governance: Policy Networks; Governance, Reflexivity and Accountability. Berkshire: Open University Press. Sandford, M. (2013). Directly elected Mayor’s. London, House of Commons Library Stoker, G. (1997). Public-private Partnerships and Urban Governance. In J. Pierre (ed.), PublicPrivate Partnerships in Europe and the United State. London: Macmillan. Stoker, G. (1998). Governance as theory: Five propositions. International Social Science Journal, 50(155), 17–28. doi:10.1111/14682451.00106 Sullivan, H., & Skelcher, C. (2002). Working Across Boundaries: Collaboration in Public Services. New York: Palgrave Macmillan. Wildavsky, A. (1989). A Cultural Theory of Leadership. In B. D. Jones (Ed.), Leadership and Politics: New Perspectives in Political Science (pp. 87–113). Lawrence: University of Kansas Press.

227

 Sustaining Governance

ENDNOTES

1



2

228

The Mayor employs several politicians and non politicians to work in the Mayoral team which is responsible for running London (This is available at http://www.london.gov. uk/who-runs-london/mayor/mayoral-team). These schemes are sponsored by Barclays which is a major global financial services provider. TfL claims that both schemes make



3

a positive contribution to London by offering sustainable environmentally friendly means of transport and helping Londoners and visitors to the Capital lead more active lives . Imperative coordination is the process whereby the Mayor employs his powers in mandating actors to implement his policies or collaborate with him on certain schemes.

229

Chapter 12

Governance Evolution and Impact on Economic Growth: A South Asian Perspective A. Subramanyam Raju Pondicherry University, India Nagarajan Balasubramaniam Bharathiar University, India Rajamanickam Srinivasan Pondicherry University, India

ABSTRACT Governance matters (Kaufman, et al, 1999) for growth is now an accepted dictum. However, there are as many hypotheses as to what constitutes governance ‘as there are researchers in the field’ (Bressers, J.T.A. & Kuks, S.M.M., 2003). Apart from econometrics, political science provides important insights on factors that influence governance and facilitate growth. This chapter examines the political history and economy of South Asia to determine the features that shaped governance and affected economic growth. It finds that governance in South Asian context evolved through three phases. Using a comparative perspective of GDP growth rates and World Governance Indicators in South Asia and Brazil, it analyzes the relationship between political history and economy in each phase. The findings indicate that political ideologies, stability of regimes and policy continuity hugely influence the institutions of government and economic growth. The chapter also finds that people’s participation in governance would enhance growth and distributive social justice.

INTRODUCTION The term ‘government’ has usually included formal institutions of the state, and its monopoly of legitimate violence. Formal and institutional

processes formulated centrally are used to maintain common order and to facilitate collective actions (Stocker, 1998). As a contrast to these traditional views of government, political systems and processes are increasingly discussed in terms

DOI: 10.4018/978-1-4666-8274-0.ch012

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Governance Evolution and Impact on Economic Growth

of ‘governance’, and sometimes even in terms of ‘modern governance’ (Rhodes, 1996, 1997; Kooiman, 1994). One of the biggest challenges of these theoretical frameworks is that ‘there are as many ideas of governance as there are researchers in the field’ (Bressers, J.T.A. & Kuks, S.M.M, 2003). Notwithstanding the apparent diversity of expressions, it is necessary to appreciate that governance is not a science or field by itself. As Dixit (2009) stated, “governance is an organizing concept for many fields in all social sciences; it is not a field per se, and certainly not a field within economics. Case studies in law, political science, sociology, and anthropology, and game-theoretic modeling in economics, have all contributed to the advancement of our knowledge concerning governance institutions. This offers a unique opportunity for the social sciences to have a meeting point, if not for reunification, after their separation over a century ago”. This chapter aims to understand the relationship between political governance and economic growth by examining the history of political economy of South Asia, in particular India. In such an examination, whether political stability, policy continuity, institutional framework and stakeholder (citizen) participation contribute to economic growth is looked into by use of a comparative study. The French Revolution of 1787 – 1799 changed the way people looked at their kings and countries. Nation or State came to be regarded as the guarantor of three principles: Liberty, Equality and Fraternity. In due course of time, people across the world have come to regard their countries not merely as guarantors of the fundamental principles but as promoters of institutions and practices through which opportunities to fulfill their political, economic and social aspirations will be provided. In short, governance is measured in “the manner in which government uses its power in the management of the institutional environment, hence affecting the accumulation of the factors of economic growth” (Badun, 2005, p. 280).

230

Three major events in the Western hemisphere influenced South Asian thinkers and practitioners in developing the concept of state as well as governance: French Revolution, American Independence and the two World Wars. While the West industrialized and developed, the East, particularly South Asia, became the laboratory where the colonial rulers practiced the art of governance from the colonizer’s perspective (Iyer, 2004). However, by the end of 19th century, a strong movement for independence emerged in the subcontinent. Western education and the remarkable struggle for Indian Independence, combined with the emergence of USSR played a huge role in laying the ideological foundations to South Asian concept of governance(Bayly, 2008;Chandra, Mukherjee, Mukherjee, Panikkar, & Mahajan, 2013)1. To a large extent the over-awing impact of the Empire left political leaders and thinkers in South Asian region adopting, rather than experimenting, the concept of governance that had evolved in the West by the end of World War II (Roy, 2002).

DEFINING GOVERNANCE In order to appreciate the lessons from South Asian experiences, it is important to commence with a survey of different ways the term governance is defined. Richards and Smith (2002), suggest that governance is a descriptive label that is used to highlight the changing nature of the policy process in recent decades. In particular, it “sensitizes us to the ever-increasing variety of terrains and actors involved in the making of public policy”. It thus demands that we consider all the actors and locations beyond the ‘core executive’ involved in the policy-making processes(p. 2). Rhodes (1997) argues that governance refers to a ‘new process of governing’. He then proposes that, in the British case, governance “refers to self-organizing, interorganizational networks characterized by interdependence, resource exchange, rules of the game

 Governance Evolution and Impact on Economic Growth

and significant autonomy from the state”(p. 15). Kooiman(1993) has concentrated on the relationship between government and society. He suggests that the governance of modern societies is a blend of all kinds of governing levels, modes, and orders. He argues that social-political governance implies “arrangements in which public as well as private actors aim at solving problems or create societal opportunities, and aim at the care for the societal institutions within which these governing activities take place”(p. 139). Rosenau (1992) focuses on what he refers to as global governance, and adopts a perspective that allows for governance occurring apart from what governments do. He contends that “governance is conceived as systems of rules, as the purposive activities of any collectivity that sustain mechanisms designed to insure its safety, prosperity, coherence, stability, and continuance”. Building further on the Kooiman’s approach to governance, Cheema and Mcguire (2002) emphasize that “governance is a neutral concept comprising the complex mechanisms, processes, relationships and institutions through which citizens and groups articulate their interests, exercise their rights and obligations and mediate their differences. Good governance addresses the allocation and management of resources to respond to collective problems; it is characterized by the principles of participation, transparency, accountability, rule of law, effectiveness, equity and strategic vision”(p. 8). For the international organizations, the focus appears different. Their definitions reflect the interest on strengthening domestic institutions for policy development and implementation. The World Bank (World Bank [WB], 1992) expressly defines the term as “the manner in which power is exercised in the management of a country’s social and economic resources for development”(p. 3). While the Asian Development Bank (Asian Development Bank [ADB], 1999) has linked governance to capacity building and defines that “it encompasses the functioning and capability of

the public sector, as well as the rules and institutions that create the framework for the conduct of both public and private business, including accountability for economic and financial performance, and regulatory frameworks relating to companies, corporations, and partnerships”(p. 3). Both of them seem different from the United Nations Development Programme (United Nations Development Programme [UNDP], 1997) that links governance to sustainable human development and defines it as “the exercise of political, economic and administrative authority in the management of a nation’s affairs at all levels. It comprises the complex mechanisms, processes, relationships and institutions, through which citizens and groups articulate their interests, exercise their legal rights, meet their obligations and mediate their differences”. Weiss shows that the definitions of governance used by international organizations vary substantially. While comparing the definitions adopted by various agencies, Weiss (2000) says “For the OECD, governance denotes ‘the use of political authority and exercise of control in a society in relation to the management of its resources for social and economic development’. In the same line, the UN Secretary-General claims that good governance is ‘ensuring respect for human rights and the rule of law; strengthening democracy; promoting transparency and capacity in public administration’. The WBI assumes that governance is the exercise of authority through formal and informal traditions and institutions for the common good, thus encompassing: (1) the process of selecting, monitoring, and replacing governments; (2) the capacity to formulate and implement sound policies and deliver public services; and (3) the respect of citizens and the state for the institutions that govern economic and social interactions among them”. The above definitions underline the fact that the use is vast and range from specific problems of institutional development to broader questions relating to the manner in which power is exercised within society.

231

 Governance Evolution and Impact on Economic Growth

As the nations of South Asia are contemporary entities whose birth coincides with United Nations (UN), the definition adopted by UN would also be of relevance: In the community of nations, governance is considered “good” and “democratic” to the degree in which a country’s institutions and processes are transparent. Its institutions refer to such bodies as parliament and its various ministries. Its processes include such key activities as elections and legal procedures, which must be seen to be free of corruption and accountable to the people. A country’s success in achieving this standard has become a key measure of its credibility and respect in the world2. A review of various definitions used indicates that governance involves not only improvement of public sector capacity but also a transformation in the scope, role, power and activities of the state in economy and society. It identifies the optimal role of the government in public life and a space for the involvement of society in public sphere. The definitions also promote the role of non-state actors, widening their roles and responsibilities outside the ambit of State. Instead of holding the state singularly responsible for providing all the services necessary for growth, development and public good, the definitions cumulatively vest it on the state to foster conditions and provide mechanisms for public, private and civil society participation to achieve the same.

THEORETICAL PREMISE AND OBJECTIVE Economists the world over have evolved various models to study the relationship between governance and growth. However, Badun (2005) laments, “Although governance did exist in

232

descriptive studies of economic growth and in particular in the domain of economic history, it has been neglected in the standard growth models. The Solow model, for example, is grounded on numerous assumptions, one of them being that property rights are secure. Thus the main deficiency of this model from the standpoint of governance is that it does not take into account any shortcomings in the quality of governance assuming that they do not exist”(p. 281). With the path breaking contribution of Kaufmann, et al., in evolving the World Governance Indicators (WGI) in 1996, and the adoption of WGIs as benchmarks for good governance the world over since then, economists have paid considerable attention to quality of governance and its impact on growth. However, Acemoglu, Johnson and Robinson (2004) note that (although) “neoclassical models of growth are still current in economics and granting that they have explained a great deal in the mechanism of growth, they still do not give a fundamental explanation of the foundations of such growth” (p.1) . Notwithstanding the deficiencies in these approaches, that “governance matters” has come to be accepted as fundamental to any study of economic growth. The governance-matters approach to development is not without problems. Cross-national studies showing that good governance is a key determinant of economic performance can be challenged on the grounds of “causality problems”, “measurement errors”, “missing-variable considerations” and “conceptual vagueness” (Chong & Calderon, 2000; Glaeser, La Porta, & Shleifer, 2004; Bardhan, 2005; Weiss, 2000). Importantly, the study of political economy does not as yet appear to have grasped the relationship between political sources of good institutions and how they affect growth. As the Director of Global Governance and Regional Capacity of the World Bank Institute (WBI) (Kaufmann, 2003) recognizes, “one of the most difficult issues in the field

 Governance Evolution and Impact on Economic Growth

of governance is the imperfect understanding of how politics shapes governance and development outcomes”. The first attempt to combine economic and political analyses to account for the determinants of economic growth studied the effect of political regimes on economic performance. Feng (Feng, 2003) explains that, “Research looking at whether democracy promotes or hinders economic growth has produced three schools of thought: the conflict school that argues that democracy hinders economic growth, mainly in less developed countries, by creating consumption pressures, fuelling distributional conflicts and inhibiting capital accumulation; the compatibility school contends that democracy enhances economic growth, because the existence of fundamental civil liberties and political rights generate the social conditions most conducive to economic development; and the skeptical school that claims that there is no systematic relationship between democracy and economic development. That there may be no systematic relationship between democracy and economic development, as claimed by the skeptical school, may have credence considering that every country that has embarked on a growth path is not necessarily democratic, for example China”. However, even ardent advocates of Skeptical school will concede that the vision, commitment and policies of political leadership have considerable impact on the economic destiny of a country. The quality of political leadership influences and shapes the structures, institutions and environment in a country which in turn either facilitates or limits growth. The actions of the polity and factors that influence them are therefore of relevance to the growth of any society. Feng shows that factors such as political stability, political polarization and government repression were the political conditions influencing economic growth in the region (Southeast Asia and China). Feng also finds that “political institutions (operationalized in terms of political repression, political instability and policy uncertainty) do matter for economic

growth by constraining individuals decisions in their marketplace” (p. 296). Kaufmann, Kraay and Lobaton (Kaufmann, Kraay & Lobaton, 1999) endorse this view by asserting that “the environment of political polarization that hinders growth in many developing countries could be more associated with deeply rooted distributional and ideological struggles than with the institutional structure per se”. These studies indicate that the relationship between governance and polity cannot be ignored in any attempt to study economic growth, though the exact manner in which this relationship can be defined or evaluated remains as yet unclear. The factors that influence political governance are mostly the products of history and therefore the authors believe that examining contemporary history, particularly history of political economy, would yield lessons that are important to the realization of economic, social and developmental objectives of governance.

POLITICAL ECONOMY PERSPECTIVE OF GOVERNANCE IN SOUTH ASIA The progression of the concept of governance is closely linked to the progression of contemporary history of South Asia in the past five hundred years. This phase can be represented in the form of a flow diagram (Figure 1).

GOVERNANCE BY DOMINATION This is the phase commencing with the era of Christopher Columbus, Magellan and Vasco da Gama when European powers set out to find new sea routes to the East. The need to find new sea routes was necessitated by commercial interest [to find spice, cotton textiles, saltpeter, etc.,] since Europe faced a dominant Islamic Empire that controlled all the land routes and sea routes leading

233

 Governance Evolution and Impact on Economic Growth

Figure 1. Progression of governance in South Asia

to the East then known to man. Interestingly, the western explorers found, when they reached India eventually, that India needed nothing from the West whereas the West needed not merely the spice but was dazzled by the wealth that the sub-continent sported. There have been arguments that the spread of colonialism was actually ‘civilization on the march’. However, Panikkar (1967) said “It was, …., an attempt to get around the overwhelming land power of Islam in the Middle East, supplemented by an urge to break through the ‘prison of the Mediterranean’ to which European energies were confined……It challenged the basis of Asian societies; it imposed its will on them and brought about social and political changes in Asia which are of fundamental importance”(p. 17)3. Governance in the context of the four and half centuries after Vasco da Gama arrived in India on May 27th, 1498, was primarily aimed at exploiting the native lands to procure raw materials for

234

the European industries and to create markets for western products. A quote from the Dutch Historian Bernard HM Vlekke (as cited in Panikkar, 1967, p. 48) adequately describes the purpose and method adopted by European rulers: The Company made them (the cultivators) change their clove gardens into rice fields and sago tree plantations. The small mountainous islands could not produce food enough and the inhabitants were obliged to buy a supplement of rice from the company. It sold this commodity to them at too high a price which made the situation still more desperate. Thus the economic situation of the Moluccas was ruined and the population reduced to poverty. In the context of the subcontinent for example, Iyer (2004) finds evidence that colonial annexation policy (annexation of territories for direct

 Governance Evolution and Impact on Economic Growth

rule by East India Company) was highly selective and concentrated on areas with high agricultural potential. Governance in the context of colonial rule was essentially aimed at procuring resources and labor for consumption in Britain for industrial production. Colonialism therefore was primarily driven by economic considerations of European powers and India was effectively converted from that of a producer to consumer, becoming a huge market or staging house for further exports to the South and Far East Asia. Amongst others, Dutt (1901), Maddison (2005), Van der Eng (2007), Bayly (2008) and Ziltener and Kunzler (2013) provide evidence and arguments to support the views expressed.

GOVERNANCE BY IDEOLOGY The end of World War II (WW II) brought an era of de-colonization, both on account of unsustainability of huge empires after the war as well as due to the birth of strong movements for independence in the colonies. Leaders like Mahatma Gandhi, Nehru, MA Jinnah, Ho Chi Minh, Sukarno, Khan Abdul Gaffar Khan and Don Senanayake, who lead the movements for independence in their countries in South Asia, were equally influenced by ideals of western democracy and the Soviet model of socialism. They adapted them as governing philosophies in varying degrees as suited to local perceptions. The ideologies set by political leaders served their purpose well – that is to say they propelled countries, institutions and people in South Asia to experiment with various forms of governments. However, it must be remembered that the nations of South Asia have a common contemporary history. They were all under colonial rule which replaced the traditional forms of governance that prevailed before they were colonized. They all had an invasion that was from beyond their physical geographical dimension – their system of education, society, judiciary, administration, economy

and military - that is, every dimension of their life as a society was colonized. The four hundred fifty years of rule and the impact that the West had on native society and culture is so much so that one may say there is a crisis of identity in the post-independence era. Wignaraja and Hussain (Wignaraja & Hussain, 1989) put it concisely: South Asian societies, having been incorporated after World War II along with other Third World countries (sic) into a global system over which they had little control, have not made a meaningful historical transition in conventional terms either to capitalism or socialism, nor have they been able to integrate their dualistic economies or eradicate the worst forms of poverty and hunger or find a cultural identity. There is a heightening sense of alienation, a waste of resources, and a failure to deploy effectively the available knowledge system rooted in the culture of the people for a sustainable development. The emerging contradictions are leading to political and social unrest and heightened violence, which could lead in many cases not so much to revolutionary changes but to complete social collapse. These factors then lead to growing militarization, external dependence and possibilities for further destabilizing interventions from outside the region (p.9)4. (Emphasis added) Three features marked the South Asian countries at the time of their independence from colonial rule. One, there was a palpable feeling of nationalism prevailing in the atmosphere. It was heady, infectious and affected the way the society behaved. Freedom from colonizers, liberation of the oppressed, nationhood, and self-rule were catch-words. Two, the saga of Communist struggles of the early 20th Century and the emergence of the Soviet Union as a world power in the post WW II era held an immense appeal. Three, the resounding success of the Allies in World War II and the stature of Churchill and Roosevelt, claiming their moral superiority over Hitler in the name of democracy and freedom, had an abiding

235

 Governance Evolution and Impact on Economic Growth

impact on the psyche of the newly independent colonies. The struggles of Chinese Communists initially against Japan and subsequently to establish their self-rule had a huge impact on the Indian leaders, particularly Nehru. Idealism, patriotism and a free society where poverty had no place emerged as the theme songs of the South Asian countries. In order to find their national identity, the South Asian countries initially did what was normal to do – they adopted one or the other ‘ism’ or ideology as the foundation of their new political edifice. India particularly adopted a mixture of ‘Democratic-Socialism’. The socialistic model adopted by Nehru, of state control over means of production and distribution, essentially of Soviet origin modified by Indian planners to suit local needs, became popular amongst South Asian leaders. However, the notion of the government that control of bigger means of production by the state will propel economic prosperity downward proved incorrect. While the vast majority in the parliament gave Nehru the stability to translate his socialistic dreams into institutions and programs, seventeen years of his rule later, the economic and social objectives with which he set out to govern remained unrealized (Nayar, 2012). A primary reason for the shortfall was that the policies and programs of the government were made by elitist upper class that had very little appreciation of market realities or actual needs of people.

GOVERNANCE BY INCLUSION The successive conflicts in the post-World War eras, repressive regimes in Eastern Europe, Africa and the Americas, combined with enlightened international intervention into domestic governance (although some would say avoidable, in the form that it took in some instances) saw the emergence of new themes or bench marks for governance: respect for law (Rule of Law), human rights, and sustainable development. The prime mover in this direction can be said to be the UN for it enabled

236

the shift in the focal point of all the discourses on governance from the rulers to the ruled. The UN came into being for a single purpose – peace. The death, destruction and man-made devastation that followed the two world wars affected people everywhere, irrespective of the ideologies and affiliations. The leaders of the world of 51 countries then, in 1945, put together the UN to help countries resolve their differences in a peaceful manner. The Charter of the UN was drafted with great passion, one may say. Roosevelt, the person credited with the vision, was instrumental in incorporating the four freedoms into the body of the Charter. In due course of the time, UN adopted various instruments like UDHR5, ICCPR6, and ICESCR7. These instruments combined with the International Court of Justice (ICJ) initially and later the International Criminal Court (ICC) brought in a realization across the world that the flip side of political power in any country is not the enjoyment of those powers but the protection of the lives and liberties its people. The adjudications of ICTY, ICTR and the currently on going Sudan, Congo and other trials by Special Chambers are not to be seen merely as interventionism of the West, though that criticism may hold water in one perspective. These cases have brought to fore a fundamental question in front of people and governments alike – the quality of governance. The Millennium Declaration8 of the UN positively gives the UN the mandate to promote global governance and to help member States realize their aspirations through mutual interaction and assistance. In fact the Millennium Declaration states: Success in meeting these objectives depends, inter alia, on good governance within each country. It also depends on good governance at the international level and on transparency in the financial, monetary and trading systems. We are committed to an open, equitable, rule-based, predictable and non-discriminatory multilateral trading and financial system.9

 Governance Evolution and Impact on Economic Growth

The UN Charter, UDHR and the Millennium Declaration together with the Millennium Development Goals (MDG) have set a new foundation for the edifice that we call governance now. Growth, development, human rights, security, poverty alleviation, access to education, gender rights, rule of law, accountability, transparency, et al, have become the mantras that define the form and quality of governance than the ideology on which the body politic is based. These are universal goals, being reflective of the aspirations of humans in all countries. Economic prosperity can be achieved only when these universal aspirations are parallelly fulfilled. This phase evinces a distinctive departure from the 19th century notion that private enterprise, protection of property rights and entrepreneurial intent are at the heart of economic growth; instead, economists have come to realize that economic growth is intricately meshed with social progress (McMichael, 2011). South Asian countries, particularly India, have been hugely influenced by the socio-economic goals as outlined in the UN instruments. The lessons of the initial phase of independence when emphasis was laid on huge projects to lift up the economy, but the failure to produce the ‘trickledown effect’ and the persistence of poverty (as the single most challenge) in India produced two important effects: economically, opening of the markets to private and foreign investment and politically, the growth and consolidation of democracy. Both these factors have set India on an un-assailable path to global predominance. The Indian growth story has propelled the growth of democratic institutions in the neighborhood and the opening of their economies.

The State of Political Ideology in South Asia The political ideals originate from historical legacy, socio-economic conditions at the time of independence and aspirations of the people. From the ideals enshrined in their constitutions, it is

seen that countries in South Asia have expressly committed themselves to democracy; socialism (India, Sri Lanka and Bangladesh); Islam (Pakistan and Maldives, where Islamic ideals of social justice and Islamic Law will prevail respectively); secularism (India and Bangladesh); and monarchy (Bhutan, while wanting to be a democracy). The political leadership in these countries therefore has to construct their policies and programs according to the interpretations of these ideals as accepted by (or as acceptable to) majority of their electoral constituencies. South Asian region also saw the rise of border disputes, communal violence, and terrorism in the period after their independence. While these challenges to stability may be seen as the birth pangs of new nations, the persistence of these challenges implies the lack of connection between high ideals and poor institutional execution. Bruce King (King, 1995) highlights this aspect in the following terms: Where the end of the second World War brought a demand for national political independence to the forefront as a solution to the problems of the colonies, this was soon found to be an unrealistic hope as many new nations became divided by civil war and micro nationalisms….or failed to develop economically or to offer social justice to those outside the government and its supporters (p.3). Further, as Partha Chatterjee (as cited in McLeod, 2011, pp. 9-10) pertinently highlights in his book Nationalist Thought and The Colonial World: Nationalism sought to demonstrate the falsity of the colonial claim that the backward peoples were culturally incapable of ruling themselves in the conditions of the modern world. Nationalism denied the alleged inferiority of the colonized people; it also asserted that a backward nation could ‘modernize’ itself while retaining its cultural identity. It thus produced a discourse in

237

 Governance Evolution and Impact on Economic Growth

which, even as it challenged the colonial claim to political domination, it also accepted the very intellectual premises of ‘modernity’ on which colonial domination was based.

growth (Acemoglu, Naidu, Restrepo & Robinson, 2004; Lisboa & Latif, 2013; Rivera-Batiz, 2002; Przeworski, 2004).

The countries of South Asia present a picture that perhaps fits the rationale in Chatterjee’s argument. Having founded them on the institutional framework set by their colonial masters, South Asian countries today have everything that defies normal logic –Pakistan and India have nuclear arsenal on one side and on the flip side, there are millions of children in these countries who have no access to basic education. Sri Lanka, Nepal and Bangladesh are aspiring to enter the economic growth wagon as emerging potential markets on one side and on the other side, their edifice stands on such unacceptable records of human rights violations by State and instruments of State that defy all parameters of probity. These instances reveal a dichotomy between ideology and delivery. The dichotomy in their being is not obviously due to the lack of understanding of the concept of governance but it is due to the lack of understanding of the tenets of good governance. While the concept of sovereignty, nationhood, and governance have continued to evolve owing to the political pressures and realities of the times, the institutional framework of the yester years appears to be the single most challenge for achieving good governance in South Asia. As Kaufmann Kraay and Lobaton (Kaufmann, Kraay, & Lobaton, 1999) summarize, “Good governance requires time and resources to develop, suggesting that rich countries are likely to enjoy good governance. Governance also depends on a country’s political and social history, especially in those countries that inherited a set of institutions from the former colonial powers”. However, to the credit of South Asian countries, it must be said that democracy (implying greater people’s participation) has increasingly become evident in all these countries. Evidence from across the world also suggests that democracy provides better environment for facilitating

IMPACT OF GOVERNANCE ON ECONOMIC GROWTH

238

The testimony of any concept rests on its ability to deliver. Concepts of governance or ideologies like democracy and communism continue to remain the subject of interest and analysis since they hugely impact the lives of people. They have evolved as governance models through application and synthesis in due course of time. The proponents of democracy in West had always predicted that communism will fail. Their predictions actually appeared true when USSR collapsed. But to impartial political analysts, story of the fall of USSR is not the story of unsustainability of communism. Otherwise, explaining the phenomenal growth of China, the socialist republics in South America, Caribbean, and the most recent victory of Leftist Party in Greek elections would be extremely difficult. These instances of political history demonstrate a simple lesson: those concepts fail which do not connect the system of governance to aspirations of people. Roskin (as cited in Himanen, 2014, p. 196) “turned this question on its head”. He analyzed governance in nine countries, and then claimed that in order to assess governing regimes, it is best to study their results. In India, the political history of which has a huge impact on the lives of the people of the subcontinent, the transition from governance by domination to governance by inclusion has had its own impact on the lives of the people. From Adam Smith’s Wealth of Nations onwards, there have been debates on the role of state (government) in the economic growth of the society. Property and private enterprise have been agreed upon as the foundations of economic growth. Economists and thinkers after Smith had astutely resisted state intervention in economic

 Governance Evolution and Impact on Economic Growth

activity. In the initial stages of the industrial revolution and growth of private enterprise in Europe, it was advocated that state actually must refrain from intervening into the private initiatives for industry and growth. Clay (1916) claimed that “Adam Smith had shown that the organization of industry and commerce was a spontaneous thing, owing little or nothing to the direct action of the State, and that it had in it a sort of self-regulating principle, which made it unnecessary for the State to interfere in the public interest” (p.392). However, this stand underwent a huge change as the Industrial Revolution progressed. Mass production led to exploitation of labor under inhuman conditions, gross discrimination on account of gender, employment of minor children and denial of basic amenities for safety and welfare at the work place. These instances resulted in the State assuming a regulatory role. Industrial revolution facilitated mass production and therefore compelled the search for markets abroad. The terms of trade thus came to be revised from that of rent-seekingprotectionist to one of contracts and tariff. State became an important instrument in the process since sovereign authority was essential to enforce conditions on all parties. The social dimension to economics was propelled by the massive destruction and human suffering during both the World Wars. State became the instrument to ensure social justice and rights of the people. Economic development therefore became part of the overall social development and justice. Political organization that till then was seen as largely independent of economic organization had now to be accepted as the controller of engines for economic growth in order to achieve social justice. The relevance of any political organization or regime in a democracy is proportional to its ability to translate people’s aspiration to reality. In order to do so it must rely on an institutional framework whose behavior is controlled by a set of rules and whose outcome is predictable. The political philosophy of ruling regimes therefore becomes a key factor contributing to growth. Governance

to this extent, Rapley (2005) says, becomes not just “an institutional framework but to a prevailing way of doing things based on implicit and explicit norms” (p. 6). Viewed from this perspective, it is possible to understand the success of Chinese communism in propelling growth. The alternative evidence from Africa reinforces the view that political regimes and their policies could result in underdevelopment owing to their failure in building strong institutional framework (Fosu, Bates & Hoeffler, 2006; Fayissa & Nsiah, 2010). As defined by North (1991), “the humanly devised constraints that structure political, economic and social interaction (institutions) consist of both informal constraints (sanctions, taboos, customs, traditions and codes of conduct), and formal rules (constitutions, laws, property rights)” (p.97).Institutions act as the interface between society and the state and play a crucial role in determining the room to maneuver for elites. In addition to their importance in creating order and reducing uncertainty in exchange, institutions are ‘carriers of history’ which implies that historical precedent can influence the shaping of a whole institutional cluster (Schottli, 2009). The political, social and economic philosophy of the ruling regimes therefore plays a vital role in shaping the policy and institutional framework which in turn affects growth. The authors’ hypothesis that this is a crucial determinant for economic growth was tested through a comparative case study and two-way test.

CASE STUDY A combination of factors like geographical location, population, colonial legacy, democratic credentials and liberalization of economy have put India among those nations that are poised to be robust economies in the coming decades. Amongst developing nations, Brazil in South America shares such similarities with India. Both are estimated to belong to the exclusive

239

 Governance Evolution and Impact on Economic Growth

club of economic super powers in the foreseeable future. The G20 and BRICS partnerships of these countries suggest a convergence of efforts in this direction. Accordingly, by examining factors like political stability, consistency in policy, institutional framework (bureaucratic efficiency) and participative governance in these countries, an attempt is made to understand the influence of these factors on economic and social growth.

Brazil Brazil was under military rule from 1964 to 1989. Codato divides this period into 17 stages through which the military regime gave way to liberal democratic regimes (Codato, 2006). Codato also notes that high inflation and other economic compulsions influenced the military decision to initiate reforms from 1979. Elections were introduced in its political life in 1980. The military which held sway till then chose to step aside and let elected representatives rule the country. Studying the process, Stuenkel (2014) observed: “For Brazilians, one of the greatest achievements of their country’s democratization process was the fact that incumbent leaders were able to finish their terms and hand over power to their successors in an orderly way, without protracted violence or mass upheaval”. The GDP growth between 1971-1980 averaged at 7.4 percent. Post 1980, the GDP averaged over 8.5 percent. “Brazil experience suggests that democracy might have contributed to the construction of more solid institutions, contrasting to those undertaken during the dictatorship, albeit the pace of adjustments looks slower. Reforms in democratic regimes may be more difficult to negotiate, but they have proved to be more resilient”(Lisboa & Latif, 2013, p. 49)10. The Brazilian story merits a little analysis. From the end of colonial rule in late 19thcentury, the political history of Brazil was punctuated by huge upheavals. The most notable are the two really long periods of military dictatorships, first between 1930 -1945 and then later from 1964 to

240

1985. The political upheavals and military rule would normally have resulted in economic stagnation and under-development. However, even during the dictatorships, the leadership remained focused on economic development to the extent that the GDP growth consistently remained around seven percent or more. As Lisboa (2013) points out, government played a central role in the country’s economic development, financing public and private investment, coordinating production decisions, providing protection to selected sectors and setting prices (p. 1). The consistency, with which the successive democratic governments opened up the economy to foreign investment in a calibrated manner parallelly protecting domestic business interests, contributed to the steady growth in GDP and generally was responsible to economic development. There have been keen debates as to the models – market enhancing governance vis-a-vis growth enhancing governance – particularly with reference to the Latin American countries. While economists remain divided in their opinion, that governance and good governance play a vital role in growth has received universal consensus. The Brazilian story also highlights the role that institutions and processes of governance play towards economic growth irrespective of their ideology.

India The economy of India under British rule was exploitative in nature. Huge outflow in the form of salaries and pensions were granted. The remaining exactingly collected revenue was used by the government to maintain its 200000 strong Army and for developmental works required for its commercial interests. The failure of cotton crop in America in 1839, for example, was hugely responsible for development of railways in India to transport cotton from various parts to Bombay, Kolkata and Madras for further dispatch to factories in Manchester. The consequent advantage to Britain resulted in textile imports that broke the native textile industry (Clingingsmith

 Governance Evolution and Impact on Economic Growth

& Williamson, 2005). This had two way impacts on economy. First, it rendered the most profitable sector of native economy redundant and second, it pushed more hands into agriculture. India also witnessed ten famines between the years 1860 and 1900, which were hugely due to the exploitative taxation on agriculture by the British, thus making agriculture unsustainable. In a report submitted to the English parliament, Dutt (1901)indicated that “there was a net loss of Rs 57734761 up to the end of 1898-99 on account of expenditure for the railways, since the operation of railways (for imperial interests) was guaranteed out of the proceeds of the taxes (thus) sacrificing the interests of the people of India to the interests of speculators and capitalists”. Further, “far above the financial considerations should be reckoned the duty of the state to protect agriculture and to save the lives of the people in a country as dependent on water as in India” (p.8). In the year’s between1900 to 1947, India was the key financial supporter for British war efforts, both in WW I & II. Public sources estimate that India contributed USD 730 million for WW I and USD 1.9 billion for WW II, apart from 2.5 million Indian troops who fought for the Allies all over the world. The Bengal famine and other natural disasters also took a huge toll on the economic lives of people. The colonial rule ended in 1947, with agriculture in India nearly crippled and native industry practically undeveloped. During the period of colonial rule, it may therefore be stated, the institutional framework created by Britain was more focused at facilitating the economic interests of the empire rather than creating opportunities for native components of economic activities to seed and grow. The governance actors (the Viceroy, the India office at London, British parliament and the administrative machinery) remained aloof from the lives and aspirations of the people of the sub-continent. In the years after independence, the tasks in front of Nehru’s government were complex. The first among the government’s tasks was to orient

the institutional framework towards the social and economic upliftment of the people (Schottli, 2009). India had achieved certain level of industrialization, particularly during the World War period, essentially to contribute to the war efforts. The state of industry was not good enough to generate employment and instigate growth in agriculture and other microeconomic spheres. The growth story of USSR and China were hugely appealing to Nehru since they appear to be aimed at social equality. The exploitative capitalism practiced by British colonial rulers also made Nehru look towards state control of economy rather than private sector autonomy. The levels of poverty in India and social inequalities had to be balanced against aspirations for economic growth. The huge majority support that Nehru enjoyed and the resultant political consensus was conducive to the top-down approach to economic development. There is abundant criticism and differences in view of the Nehru concept of state control and emphasis on large projects. However apart from stability of Nehru’s government for 17 years and consistency in its policy, his largest contribution to economic growth was the concept of ‘Planned Growth” (Dantwala, 1964) through Five Year Plan and the establishment of Planning Commission for the purpose. When Nehru passed away, the underlying political consensus that held the Congress Party together began to fall away and natural fissures in Indian politics – representing the diversity of social classes, ethnicities, and nations – began to influence the political order. The political compulsions of her time, and the unabated rise in levels of poverty urged Indira Gandhi in the second phase of her government to enforce state control by nationalizing banks, regulating foreign exchange, and licensing industrial production (essentially falling back on socialistic ideals propounded by Nehru). Government control was viewed as a conduit through which a postmodern Indian state could be facilitated (Sibal, 2012). In the later years of her rule, she began to realize that state control

241

 Governance Evolution and Impact on Economic Growth

had actually stymied the economy and a certain amount of privatization was essential to generate wealth as well as employment. As observed by Sibal (2013), “Public sector corporations could enable cooperation between and amongst different ethnic groups and castes, much better than could the private sector. Focusing on national unity, at the expense of economic development, cost India dearly. India’s economy had anemic growth and extreme volatility between 1965 and 1981” (pp.19-20).These lessons went home to policy makers under Rajiv Gandhi, after Indira Gandhi, who was instrumental in opening of economy to private enterprises and foreign investment. This phase of ‘transition’ in governance was also hugely influenced by economists like Manmohan Singh and Montek Singh who steered government policy under Rajiv Gandhi. The most important lesson of this period of Indian history is the role political leadership played in the governance process. The transition from state control to liberalization (albeit selective) revitalized the economy providing necessary fillip to growth. In Indian political-economic history, the period between 1991 and 2004 is vital to understand the connection between governance and economic growth. In this period India saw seven Prime Ministers, whose term in office varied from 16 days to 6 years and 64 days. India’s experiments with coalition politics during this period had mixed results on the economy. At times the country experienced total policy paralysis because of the fast turn out of governments and at others, like the PVN Rao tenure between1991 to 1996 and AB Vajpayee tenure between1998 to 2004, it witnessed graduated opening of the economy which facilitated investment and growth11. It is pertinent to remember that governance process that aims to bring means of better livelihood closer to people becomes mired in rent-seeking behavior when the actors are concerned only about

242

securing their positions in government. The most important casualties in times of unstable governments are the institutions of government. They become weakened through inaction and confusion. Rapley (Rapley, 2005) emphasizes this aspect in these words: Regimes may change within a static institutional framework, and alternatively the institutional framework may be changed without a regime being altered. Stable regimes, moreover, do not relate merely to material distribution, but have a cultural or spiritual component as well. Hence regime stability tends to correspond to cultural stability, and regime crisis tends to correspond to cultural ferment and what Gramsci called hegemonic dissolution. When a regime breaks down – when, put simply, a party (usually the dominant one) is perceived to have broken its end of the bargain – political instability results and the regime enters into crisis (p.7).

The Two-Way Test The four factors that were primarily considered for an examination by the authors are: political stability, policy continuity, institutional framework and stakeholder (citizen) participation and their relationship to economic growth. For the purpose of this study, these terms are defined as below: •

•

Political stability is defined as the stability of a particular regime (either by a single political party or by a party in majority) with a defined political, social, economic agenda. This would include the electoral manifesto as well as ideological orientation of the majority party. Policy continuity refers to the consistency with which successive regimes pursue a political or social or economic agenda.

 Governance Evolution and Impact on Economic Growth

•

•

•

Institutional framework is defined as the creation, existence and functioning of institutions of government like parliament, state legislatures, central bank, police, judiciary, etc. Citizen participation is defined as the institutional as well as informal space provided to citizenry for influencing government policy as well as the channels for participating in government decision making. Economic growth, as is accepted across the world, has been taken as the GDP growth rate.

In order to test our hypothesis, a two-way test was carried out in the following manner: World Governance Indicators (WGI) developed by World Bank uses six parameters to rank the nations of the world. Political Stability and Absence of Violence (PV), Regulatory Quality (RQ), Government Effectiveness (GE), Voice and Accountability (VA), Rule of Law (ROL) and Control of Corruption (CC). Under each of these categories, country rankings are available as a data set with World Bank from the year 1996. The rankings in respect of Brazil and India were segregated and tabulated in the first phase. The United States Department of Agriculture (USDA) maintains exhaustive data on all countries of the world on a variety of issues concerning their economy. One of the data sets available with USDA is the historical real GDP for countries from 1969. From this data bank, the GDP for Brazil and India for the period 1996-2012 were compiled. Both the above data were compared and the charts are given under as Figure 2 and 3: In the case of Brazil and India, the following observations result from the charts: •

Political stability (indicated by PV) coincides with the periods marked by shortlived ruling regimes/volatility resulting in policy stagnation in both the countries. In the case of India 1996-2004, is the period

•

•

when successive coalition governments stayed in power for varying durations. The stability and progressive policies of the government in the 2004-2007 period resulted in the GDP touching its highest growth. In the case of Brazil, for example, lower GDP of pre-1998 years coincides with three successive regime changes between 1990 and 1995. The Cordoso government that took over in 1995 specifically embarked upon privatizing public companies and opening the economy for foreign investment. While vested political interest was alleged, the GDP rose markedly during 1998-2003. Variations in GE, RQ and VA coincide with the trough/peak of PV. The regime volatility appears to be a key factor influencing this trend. Interestingly CC, a key indicator in good governance, is seen parallel to the GDP. For example in the case of India, this coincided with serious corruption scams like 2G in 2009-10, resulting eventually in the fall of the government. The routing of the ruling regime in the general elections of 2014 was mostly due to perceived high levels of corruption and policy paralysis. Similarly in Brazil, the period 2003-2006, when the GDP plunged to its lowest, was marked by “mensalao’ or the ‘big monthly allowance’ scandal that nearly threatened President Lula’s government.

The above trends supplement the studies conducted by World Bank, ADB and various scholars on good governance. They suggest that political stability, policy continuity and institutional framework are conducive to economic growth. Such an environment facilitates rent seeking alliances in promoting trade and commerce, and also attempts to draw a balance between the demand for distributive justice and the exploitative energy of the market forces. The trends reinforce the

243

 Governance Evolution and Impact on Economic Growth

Figure 2. WGI v. GDP Brazil 1996-2012

(Source: Compiled by author, from data collected from World Bank and United States Department of Agriculture websites at www. governanceindicators.wb.organd http://ers.usda.gov/data-products/international-macroeconomic-data-set.aspx#.U5rpx7F6uZQ)

authors’ hypothesis that the policies of successive governments to control instability, provide long term institutional framework for enhancing bureaucratic efficiency and an environment of confidence for economic investments are necessary for economic growth. While studying the economic growth of East Asian countries, Feng (2003) found that “factors such as political stability, political polarization and government repression were the political conditions influencing economic growth in the region”. He also further found “that political institution (operationalized in terms of political repression, political instability and policy uncertainty) do matter for economic growth by constraining individuals decisions in their marketplace”(p. 296).

244

Apart from balancing the market forces with the needs of people, good governance attempts to promote those sectors that are outside the purview of profit seeking market forces - like education, public health, social and physical security. Economists like Sen (2000) believe that these factors have a profound impact on economic environment. An important feature that emerges while tracing the relationship of voice & accountability to GDP is the empowerment to people in public decision making. As Lyakurwa(2009) finds, “empowerment gives people dignity, a sense of inclusion and the moral strength to help themselves economically”. Block (1991) posits that social empowerment increases a sense of responsibility and ownership and takes governance to the masses. Some of the prominent examples of empowerment in

 Governance Evolution and Impact on Economic Growth

Figure 3. WGI v. GDP: India 1996-2012

(Source: Compiled by author, from data collected from World Bank and United States Department of Agriculture websites at www.governanceindicators.wb.organd [UNKNOWN ENTITY &!CommentStart20;]http://ers.usda.gov/data-products/ international-macroeconomic-data-set.aspx#.[UNKNOWN ENTITY &!CommentStart21;]U5rpx7F6uZQ)

developing countries are: The Grameen Bank of (rural) Bangladesh is renowned for its microenterprise development initiative: small loans to poor women to encourage individual businesses, which in turn generate new employment opportunities. The Government of Botswana has been fighting to reduce poverty and improve the welfare of the poor through programs and policies such as the Financial Assistance Policy (FAP). The government also embarked on providing social services like maternal and child health programs with a view to addressing extreme poverty in the country (World Bank, 1997). Further, the acceleration in the penetration of LPG in Kenya demonstrates the facilitating role governments can play, providing a policy and regulatory framework attractive to

prospective energy and financial investors, and to users. Public infrastructure, communications, mines and minerals, coal, forests, national water bodies, etc., where government only can exercise control for sustainable exploitation are important contributors for economic growth. Unless responsible and responsive governance structure prevails in a country, these resources would be exploited ruthlessly for short term private profit. In its report submitted to the European Symposium on Space Environmental Control Systems, ADB (ADB, 2011) summarized this challenge in these words: “At the Pittsburgh Summit, the global leaders clearly mandated the G20 to address development issues, recognizing that reducing poverty and narrowing

245

 Governance Evolution and Impact on Economic Growth

the development gap are essential to the broader G20 framework of achieving strong, sustained, and balanced global growth. The recent crisis has likely resulted in an additional 50 million people living in extreme poverty (on less than $1.25 a day) in 2009 and approximately 64 million more people by end-2010 (G20, 2010). While strong growth has been exhibited in developing parts of the world; income inequality and pervasive poverty also remain a real threat to economic, social, and political stability in many emerging market economies”. It is important to understand that a governance mechanism exercises the judicial, legislative and executive controls which are indispensible tools to produce the ‘trickle down’ effect of the benefits of economic growth across all segments of the society. The historical development of governance in South Asia has profound lessons to be learnt in this regard.

LESSONS FROM THE HISTORY OF INDIAN POLITICAL ECONOMY Tracing the growth of political history of South Asia, particularly of India, enormous lessons on the relationship between governance, growth and development emerge. As Kishor and Singh (1969) observe, “even the most ardent believers in the laissez faire philosophy agree today that the development process must be initiated and directed by appropriate government participation in the economic and social spheres of activity. For, in a stagnant economy, only the government has the requisite power and resources to break through the obstacles to development in a big way” (p. 65). In his study of the growth of 143 countries across the world, Himanen (2014) found that there is a direct relationship between quality of governance and social/economic development12. While we concur with the role of governance in facilitating growth, we observe five major lessons from the history of political economy in India:

246

Lesson 1: From the experiences of India’s transition from Mughal to British governance to Nehru’s socialistic model for economy to the subsequent tumultuous era between 1965 and 1991, the first fundamental lesson that we draw is that political stability and policy continuity are fundamental to governance and growth. The Indian experimentation of coalition politics of 1996 to 1998 that resulted in stagnation of economy reinforces this lesson. Lesson 2: The second lesson that becomes evident is the role played by indecisive bureaucracy resulting in stagnation. As Debroy (2014) explains, “a cause that is frequently overlooked, however, is the administrative deficit in the central government. There has been a collapse of both bureaucratic and ministerial decision-making and implementation in the executive branch”. This was particularly pronounced in the years between 2009 and 2014 when UPA II government was in power. The results of the recent elections in India and overwhelming majority given to one party by the people are testimony to the perception of people on governance. Acemoglu, Johnson and Robinson (Acemoglu, Johnson, & Robinson, 2005)provide empirical evidence favoring the idea “that current institutions (administrative and institutional machinery of the government) have a strong influence on current economic performance of countries with a colonial past”. North, Acemoglu, Fukuyama and Rodrik (2008) as also Aubuyn (2007) assert that the “institutions of a country may create incentives for investment and technology adoption, for its businesses to invest, and the opportunity to accumulate human capital for its workers, thus engendering economic growth. Or they may discourage such activities, leading to stagnation. They may create incentives for politicians to work towards creating a growth-enhancing environment. Or they

 Governance Evolution and Impact on Economic Growth

may encourage rent seeking activities, corruption, and the unfettered pursuance of personal gain at great cost for the rest of the society. … There is relatively strong evidence showing that the broad cluster of institutions—comprising economic, political, and legal aspects—are essential for long-run economic development”. Reinforcing this lesson, Rapley (Rapley, 2005)finds that weaker regimes prompt institutions to seek either self-serving autonomy or indulge in rent seeking behavior. In their study, Rajkumar and Swaroop (2002) witnessed that child mortality rates and primary school attainment improved in response to increased public health and education spending only in countries with low corruption and high bureaucratic quality. Their finding seems to acknowledge World Bank stance (World Bank, 2008) that “if government is not the proximate cause of growth (that role falls to the private sector, to investment and entrepreneurship responding to price signals and market forces), stable, honest, and effective government is critical in the long run, that is to say for sustained growth”. Lesson 3: Going a little back in history to the period of Colonial Rule evidences an important lesson in economy and development. In his report to English parliament, Dutt (1901) made a plea for improving the irrigation and water resources of India. He pleaded that “it was the duty of the state to protect agriculture and to save the lives of the people in a country as dependent on water as in India” (p.8). He also made an important point when talking of railways vis-a-vis irrigation. He argued against the disproportionate importance in government spending for railways than agriculture. His arguments have a vital lesson – that development should not exact an undue price over sustenance. Extensive exploitation of environment and natural resources has propelled serious debates over

another crisis, much more serious than mere monetary ones – food. Brown (Brown, 2011, 2012)argues powerfully against the stress that states and citizens exert on environment engendering the food crisis to alarming levels. He also marks the challenges to growth by highlighting the issues of falling water tables, shrinking harvests, eroding soils, expanding deserts, and the snowballing challenge of environmental refugees. The most outstanding example for this argument is the devastation caused by floods in the state of Uttarakhand (India) in 2014. The price paid for unregulated development in the ecosensitive river valley purely for commercial considerations highlights this lesson. From East Asia, substantial evidence and argument has been presented by Mori (Mori, 2013) in this regard. The third important lesson therefore is that civil society, private sector and government agencies have an important and complementary role towards sustainable development. Lesson 4: The fourth lesson pertains to government control on engines of growth. The excessive control experienced during the ‘License Raj’13 of the 1970’s and 80’s resulted in ‘anemic growth’ as well as wide spread poverty. Even in the case of Brazil during the military regimes when state control was absolute, the GDP remained constant. In the Indian context, the failure to propel growth after three decades of state control demonstrated that governance should strike a fair balance between macro-economic growth and micro-economies that sustain bulk of the population. Globalization has particularly accentuated this aspect since unregulated privatization has the potential to make the rich richer and the poor substantially poorer. Seven decades before, Lehfeldt (1940) made a pertinent remark on the role of the state: “practical problem is therefore to devise methods of exercising

247

 Governance Evolution and Impact on Economic Growth

the necessary state control that will not waste the energy, fertility, and inventiveness of individual effort” (p. 98). The Brazilian experience also has a notable lesson reiterated by Lisboa and Latif (2013): “the presence of political actors with veto power might not be the only threat to democratic institutions. The lack of transparency of government policies contributes significantly to weaken democracy, not only due to risks of higher corruption and low government alternation, but also because widespread and opaque rent-seeking policies mean undemocratic economic decisions. Society does not effectively participate on economic decisions and does not count with full accountability of policies’ costs and impacts, though they pressure the government for benefits. By their own nature, rent seeking policies lack adequate governance and does not lead to transparent social costs, weakening public policy effectiveness” (p. 33). Lesson 5: The fifth and most important lesson is the role of people in governance. It is important to note that people are the reason why governments exist and it is precisely for them that governance must occur. People’s participation in government decision making process or in other words, participative democracy thereby gains importance. Chekki (1979) defines Participatory Democracy as “a process which refers to all acts of citizens that are intended to influence the behavior of those empowered to make decisions” (p. xiii). Participative models elsewhere in the world have had mixed results. As Aleshire (1970) observes “citizen participation… does make the process (of governance) more complex and more difficult, perhaps more costly and time consuming. It involves some conflicts and dilemmas which are not easily solved and with which few planners have sufficient insight or background to deal effectively”. In India, the Constitution

248

envisaged citizen participation through Panchayati Raj (Local Governance Committee at village level with elected people’s representatives). Even though Constitutional mandate was available, perhaps due to the hesitation of the bureaucracy owing to the limitations expressed by Aleshire, the Panchayati Raj languished on paper for over three decades. Three Commissions had been instituted by the government to study the issue of implementation. It is to the credit of Rajiv Gandhi, the government decided to vigorously implement Panchayati Raj14. A separate ministry was commissioned to oversee the process. It was also recognized that common citizens who become elected representatives in Panchayati Raj Institutions (PRI) across the country would be unfamiliar with government processes which would hugely impede their grass root participation. Accordingly, the government allocated funds for training the PRI members to enable meaningful participation, based on LM Singhvi Committee recommendations. While in theory, this was a huge initiative, the actual allocations and infrastructural support to PRIs has remained insufficient. However, the recognition that grass roots involvement of people contributes to good governance has come to stay as a reality. Grass roots democracy is not merely a form of governance through participation. In countries like India and its neighbors in South Asia, two thirds of the population still depends on agriculture and allied micro-economic activities for their sustenance. It needs no emphasis to appreciate that sustaining micro-economic activities through appropriate policy protection against undue competition therefore is important in South Asian context. Involving the rural populations through participative governance provides the villagers an opportunity to set developmental agendas that are in sync with their actual needs and support facilities

 Governance Evolution and Impact on Economic Growth

for agriculture and other avenues to fulfill their sustenance needs. Lyakurwa (2009) notes that, “empowerment gives people dignity, a sense of inclusion and the moral strength to help themselves economically”. Kannabiran (2014) takes this point further by emphasizing that (At a time) “when we are attempting to bring about change through participatory planning, we must exercise caution against reducing it to a bureaucratic exercise by involving the widest range of citizen groups, researchers, professionals, occupational groups and intellectuals in thinking the process through and carrying it forward”.

economic growth in both the contexts could take the following paths: •

THE WAY FORWARD Are lessons from history relevant to other spheres of social/business activity? Our answer to this question is in the affirmative. We have already seen that economic growth is not the exclusive prerogative of the private entrepreneur. It is a rail engine whose twin tracks – growth and sustainability – always run parallel. While the government institutions are vested with the authority to control the environment to facilitate growth, private sector has the responsibility to abide by sustainability. Exploitive tendencies on behalf of private enterprise would give rise to rent seeking and be detrimental to growth in the long run. Civil society organizations have a huge role in this process through responsible participation both in government decision making as well as serving as the guardians of public interest. The lessons are politically important not because of the adage that those who fail to learn from history are condemned to repeat it; but because the lessons from the three phases of governance in the sub-continent continue to influence the destiny of a sixth of humanity. These lessons are also pertinent in the context of Brazil whose history has similarities with the sub-continent. We feel that the way forward towards greater socio

•

Inclusive economic planning is necessary that takes into account traditional economic activities, forests & natural resources and people dependent on these for livelihood. Macro-economic planning must allocate due space for such micro-economic spheres of life before ushering in modernization or liberalization. It is important to realize that modernization or liberalization of economy adopted by one developed nation may not per se be applicable in the context of another due to demographic and social peculiarities. North (North, 1994) underlines that “economies that adopt the formal rules of another economy will have very different performance characteristics than the first economy because of different informal norms and enforcement. The implication is that transferring the formal political and economic rules of successful Western economies to the third-world and Eastern European economies is not a sufficient condition for good economic performance.” Both the subcontinent and Brazil have two major components necessary for vitalizing economic growth: higher proportion of young persons in society and a growing level of literacy. Both these factors make available working populations of a size perhaps unmatched in the demographic profile of any other part of the world. Channelizing these factors towards strengthening macro-economic activities, liberalization of micro-credit for entrepreneurial enterprise and strengthening the markets for agricultural and traditional craft produce are areas that appears to hold promise. In other words, these economies need to explore from being labor intensive

249

 Governance Evolution and Impact on Economic Growth

•

economy to skill intensive or knowledge based economy. Participative democratic institutions must be accorded a larger role in government decision making process. Sen (2000) emphatically points out that “what people can positively achieve is influenced by economic opportunities, political liberties, social powers, and the enabling conditions of good health, basic education, and the encouragement and cultivation of initiatives. The institutional arrangements for these opportunities are also influenced by the exercise of people’s freedoms, through the liberty to participate in social choice and in the making of public decisions that impel the progress of these opportunities” (p. 5). Governance being all about and for people, it must provide space for participation by them for inclusive growth.

CONCLUSION The 17th/18th century views that economy is a mere product of private enterprise and property rights; and, that it is the inexorable spirit of the individual entrepreneur which propels growth in a society have changed. The quality of politics, policies and processes of governance and the level of people’s participation have come to play a crucial role in the economic life and growth of people. Capitalism that was being seen as the byword for private profit is also under attack because the distribution of wealth in a society is increasingly seen as the benchmark of its growth. Every society across the world today is concerned about growth in as much as it is concerned about income parity and distributive justice. This change in attitude towards growth is more acute in South Asia than in the Western parts of the world on account of the colonial legacy and wide spread poverty in the region.

250

The political class that took over the independent reins of South Asia, initially saw governance as a ‘top-down approach’ to determine how and how much growth. Kooiman (Kooiman, 2000) classifies this approach as hierarchical governance. However, the state controlled socialistic pattern of governance for nearly twenty five years in the subcontinent witnessed stagnation and wide spread poverty. Though with caution, the opening of economy in late twentieth century witnessed a new vigor and growth. As the economy opened, India particularly witnessed an unstable political environment for nearly a decade (1996-2004). The political volatility gave space for rent seeking behaviors of the private sector. The governments of the day in these years were constantly rocked by corruption scandals. As corruption ate into public life, people became more restive and increasingly resorted to marking for development in their electoral choices. While factors like growing demand for infrastructure, education, health and social welfare began to influence voter behavior, the polity in South Asia came to appreciate that the quality in their governance plays a key role in transforming the society. That this lesson has been registered by the political leadership was amply demonstrated in the Indian elections of 2014. People chose to return a single party (that was out of favor for a decade) on the singular promise of clean government towards development. The history of political economy of India has a vital lesson for economic growth: people remain the most important reason why governments exist. The years of top-driven control mechanisms of the polity have increasingly given way to more generous participation of people in the decision making processes. The experiments with single party majority governments to multiparty coalitions and the reemergence of single party majority amidst a multitude of choices in India have driven this vital lesson home. Gary Becker, the Nobel Laureate for Economics in 1992, said in his Nobel acceptance speech that “the economic approach is not a subject matter, nor is it a mathematical

 Governance Evolution and Impact on Economic Growth

means of explaining “the economy”. Rather, as Levitt and Dubner (2009) say, “it is a decision to examine the world a bit differently. It is a systematic means of describing how people make decisions and how they change their minds…why they will punish one sort of behavior while rewarding a similar one” (p. 13). The political philosophy of ruling regime shapes its institutions. The role played by institutions of government in providing and promoting an atmosphere of stability and growth has been amply demonstrated in various studies across the world. The evidence actually points to the fact that institutions cause economic growth rather than growth improving institutions (Glaeser, La Porta, & Shleifer, 2004, p. 285). While extensive studies on the impact of institutions on growth have been undertaken in Europe, USA and South East Asia, such endeavors have not yet been taken up in detail in South Asia, even though the Indian growth story is over two decades old now. The one salient point that can contribute to future research in the context of developing nations is the role played by strong democratic institutions (The Supreme Court, Election Commission, State Legislatures, etc., for example). Since democratization is the inevitable process that is shaping the contemporary world, explorations into their relationship with growth will bear poignant lessons for future.

ADB. (1999). Governance: Sound development management. Manila: Asian Development Bank (ADB).

REFERENCES

Brown, L. R. (2011). World on the Edge: How to prevent Environmental and Economic Collapse. New York, NY: Earth Policy Institute.

Acemoglu, D., Johnson, S., & Robinson, J. (2005). Institutions as the Fundamental Cause of Long-run Growth. In A. Philippe & S. N. Durlauf (Eds.), Handbook ofEconomic Gmwth (pp. 386–464). Volume, IA: North Holland. Acemoglu, D., Naidu, S., Restrepo, P., & Robinson, J. A. (2004). Democracy Does Cause Growth. National Bureau of Economic Research. Cambridge: National Bureau of Economic Research.

ADB. (2011). Reshaping Global Economic Governance and the Role of Asia in the Group of Twenty (G 20). Sixth European Symposium on Space Environmental Control Systems (pp. 1-73). Manila: ESA Publcity Division. Aleshire, R. A. (1970, June). Planning and citizen participation: Costs, benefits and approaches. Urban Affairs Quarterly, 5(4), 369–393. doi:10.1177/107808747000500401 Aubyn, M. S. (2007). Modernising public administration and Economic Growth. Challenges for Government Spending in EU (pp. 1-34). Frankfurt: European Central Bank Public Finance Workshop. Badun, M. (2005). The quality of governance and economic growth in Croatia. Financial Theory and Practice, 29(4), 279–308. Bardhan, P. (2005). Institutions matter, but which ones? Economics of Transition, 13(3), 499–532. doi:10.1111/j.1468-0351.2005.00229.x Bayly, C. A. (2008). Indigenous and Colonial Origins of Comparative Economic Development: The case of Colonial India and Africa. New York, NY: World Bank Publications. doi:10.1596/18139450-4474

Brown, L. R. (2012). Full Planet, Empty Plates: The New Geopolitics of Food Scarcity. New York, NY: Earth Policy Institute. Chandra, B., Mukherjee, M., Mukherjee, A., Panikkar, K., & Mahajan, S. (2013). India’s Struggle for Independence 1857-1947. New Delhi: Penguin Books.

251

 Governance Evolution and Impact on Economic Growth

Cheema, G., & Mcguire, L. (2002). Democracy, governance and development: A conceptual framework. New York, NY: United nations public administration network (UNPAN). Chekki, D. A. (1979). Participatory Democracy in Action: International Profiles of Community Development (D. A. Chekki, Ed.). New Delhi: Vikas Publishing House Ltd. Chong, A., & Calderon, C. (2000). Causality and feedback between institutional measures and economic growth. Economics and Politics, 12(1), 69–81. doi:10.1111/1468-0343.00069 Clay, H. (1916). Economics: An Introduction for the General Reader (2nd ed.). London: Macmillan and Co Ltd. Clingingsmith, D., & Williamson, J. G. (2005). India’s Deindustrialization in the 18th and 19th Centuries. Cambridge: Harvard University. Codato, A. N. (2006). A Political History of the Brazilian Tansition from Military Dictatorship to Democracy. Revista de Sociologia e Politicia, 2 (SE). Dantwala, M. (1964, July). Economic Ideology of Jawaharlal Nehru. Economic Weekly, July, 1209-1211. Debroy, B. (2014, June 03). Carnegie Endowment for International Peace. Retrieved June 07, 2014, from http://carnegieendowment.org/2014/06/03/ correcting-administrative-deficit/hcgj Dixit, A. (2009, January 04). Governance Institutions and Economic Activity. Retrieved February 21, 2014, from http://www.princeton. edu/~dixitak/home/PresAd_F1.pdf Dutt, R. (1901). Indian Famines: Their Causes and Prevention. London: PS King & Son.

Fayissa, B., & Nsiah, C. (December 2010). The Impact of Governance on Economic Growth: Further Evidence for Africa. Middle Tennessee State University, Department of Economics & Finance. Murfreesboro, TN: Middle Tennessee State University. Feng, Y. (2003). Democracy, Governance and Economic Performance: Theory and Evidence. Cambridge, MA: MIT Press. Fosu, A., Bates, R., & Hoeffler, A. (2006). Institutions, governance and economic development in Africa: An Overview. Journal of African Economies, 15(Supplement 1), 1–9. doi:10.1093/ jae/ejk004 Glaeser, E. L., La Porta, R., Lopez, S., & Shleifer, A. (2004). Do institutions cause growth? Journal of Economic Growth, 9(3), 271–303. doi:10.1023/B:JOEG.0000038933.16398.ed Himanen, V. (2014, June 11). Missing a Decent Living for Everyone. Saarbrucken, Germany: LAP Lambert Academic Publishing. Iyer, L. (2004). The Long-Term Impact of Colonial Rule: Evidence from India. Retrieved June 15, 2014, from www.people.hbs.edu: http://www. people.hbs.edu/liyer/iyer_colonial_oct2004.pdf Kannabiran, K. (2014, August 12). Involving People in Governance. Retrieved September 6, 2014, from http://www.thehindu.com/todays-paper/tp-opinion/involving-people-in-governance/ article6305925.ece Kaufmann, D. (2003). Rethinking governance: empirical lessons challenge orthodoxy. New York, NY: World Bank. Kaufmann, D., Kraay, A., & Lobaton, P. Z. (1999). Governance Matters. Washington, DC: The World Bank. King, B. (1995). West Indian Literature. London: Macmillan.

252

 Governance Evolution and Impact on Economic Growth

Kishor, B., & Singh, B. (1969). Indian Economy Through The Plans. New Delhi: National Publishing House. Kooiman, J. (1993). Modern governance: New government-society Interactions. In J. Kooiman (Ed.), Modern governance: New governmentsociety Interactions (p. 288). London: Sage Publications Ltd. Kooiman, J. (1994). Modern Governance: New Government-Society Interactions. London: SAGE. Kooiman, J. (2000). Societal governance: Levels, models, and orders of socialpolitical Interaction. In J. Pierre (Ed.), Debating governance: Authority, Steering and Democracy (pp. 138–164). Oxford: Oxford University Press. Lehfeldt, R. A. (1940). Descriptive Economics. London: Oxford University Press. Levitt, S. D., & Dubner, S. J. (2009). Super Freakonomics: Global Cooling, Patriotic Prostitutes and Suicide Bombers Should Buy Life Insurance. New York: HarperCollins Publishers. Lisboa, M., & Latif, Z. A. (2013). Democracy and Growth in Brazil. Casa Das Garcas. Rio de Janeiro: Insper. Lyakurwa, W. (2009). Prospects for Economic Governance: Resilient pro-Poor Growth. Foresight, 11(4), 66–81. doi:10.1108/14636680910982449 Maddison, A. (2010). Class Structure and Economic Growth: India and Pakistan since the Moghuls. New York, NY: Routledge. McLeod, J. (2011). Beginning: Postcolonialism. New Delhi: Viva Books. McMichael, P. (2011). Development and Social Change: A Global Perspective (5th ed.). New Delhi: Sage Publications Private Ltd. Mori, A. (2013). Environmental Governance for Suatainable Development: East Asian Perspectives. Tokyo: United Nations University Press.

Nayar, K. (2012). Beyond the Lines. New Delhi: Roli Books. North, D. (1991). Institutions. The Journal of Economic Perspectives, 5(1), 97–112. doi:10.1257/ jep.5.1.97 North, D., Acemoglu, D., Fukuyama, F., & Rodrik, D. (2008). Governance, Growth and Development Decision Making. Washington, DC: World Bank. North, D. C. (1994). Economic Performance through Time. The American Economic Review, 359–368. Panikkar, K. (1967). Asia and Western Dominance. London: George Allen & Unwin Ltd. Przeworski, A. (2004). Democracy and Economic Development. In E. D. Mansfield & R. Sisson (Eds.), The Evolution of Political Knowledge: Democracy, Autonomy, and Conflict in Comaparative and International Politics (pp. 300–324). Ohio: Ohio State University. Rajkumar, A., & Swaroop, V. (2002). Public Spending and Outcomes: Does Governance Matter? Washington, DC: World Bank Policy Research Working paper No. 2840. Rapley, J. (2005). Globalization and Inequality: Neoliberalism’s Downward Spiral. New Delhi: Viva Books Private Limited. Rhodes, R. (1996). The new governance: Governing without government. Political Studies, 44(4), 652–667. doi:10.1111/j.1467-9248.1996. tb01747.x Rhodes, R. (1997). Understanding governance: Policy networks, Governance, Reflexivity and Accountability. Buckingham: Open University Press. Richards, D., & Smith, M. (2002). Governance and public policy in the United Kingdom. New York: Oxford University Press.

253

 Governance Evolution and Impact on Economic Growth

Rivera-Batiz, F. L. (2002). Democracy, governance, and economic growth: Theory and evidence. Review of Development Economics, 6(2), 225–247. doi:10.1111/1467-9361.00151 Rosenau, J. N. (1992). Governance, order and change in world politics. In J. N. Rosenau & E. Czempiel (Eds.), Governance without government: Order and change in world Politics (pp. 1–29). Cambridge: Cambridge University Press. doi:10.1017/CBO9780511521775.003 Rosenau, J. N. (2000). Change, complexity, and governance in globalizing space. In J. Pierre (Ed.), In Debating governance: Authority, steering and Democracy (pp. 167–200). Oxford: Oxford University Press. Roy, T. (2002). Economic history and modern India: Redefining the link. The Journal of Economic Perspectives, 16(Summer), 109–130. doi:10.1257/089533002760278749 Schottli, J. (2009). Strategy and Vision in Politics: Jawaharlal Nehru’s Policy Choices and the Designing of Political Institutions. Heidelberg: University of Heidelberg. Sen, A. (2000). Development as Freedom. New York: Anchor Books. Sibal, D. (2013, June 06). The Untold Story of India’s Economy. Retrieved June 03, 2014, from www.lse.ac.uk: www.lse.ac.uk/ideas/publications/reports/pdf/sr010/sibal.pdf Stocker, G. (1998, March). Governance as theory: Five propositions. International Social Science Journal, 50(155), 17–28. doi:10.1111/14682451.00106 Stuenkel, O. (2014, June 03). Carnegie Endowment for International Peace. Retrieved June 07, 2014, from http://carnegieendowment.org: http://carnegieendowment.org/2014/06/03/ non-western-roots-of-international-democracysupport/hcc1

254

UNDP. (1997). Governance for Sustainable Human Development. New York, NY: United Nations Development Programme (UNDP). Van der Eng, P. (2007). “De-Industrialisation” and Colonial Rule: The Cotton Textile Industry in Indonesia, 1820-1941. Canberra: Research School of Pacific and Asian Studies (RSPAS), College of Asia and the Pacific, Australian national University. Weiss, T. G. (2000). Governance, good governance and global governance: Conceptual and actual challenges. Third World Quarterly, 21(5), 795–814. doi:10.1080/713701075 Wignaraja, P., & Hussain, A. (1989). The Challenges in South Asia: Development, Democracy and Regional Cooperation. New Delhi. Tokyo: Sage Publications and United Nations University. World Bank. (1992). Governance and development. Washington, DC: World Bank. World Bank. (2008). Commission on Growth and Development: The Growth report. Strategies for Sustained Growth and Inclusive Development. Washington, DC: World bank. Ziltener, P., & Kunzler, D. (2013). Impact of colonialism - A research survey. Journal of Worldsystems Research, 19(2), 219–311.

KEY TERMS AND DEFINITIONS Democracy: The term refers to a system of government in which the elected representatives of people form the parliament or legislature which is vested with the power to make rules and policies. Governance: The system of exercising control over a country and its population with the view to provide for physical & social security and development of individuals and groups. A system in which, those vested with power over people act with responsibility and accountability.

 Governance Evolution and Impact on Economic Growth

Inspiration: The term implies the changed outlook on the purpose of governance. Inspired leadership in governance seeks to provide socialeconomic-political justice to people and it allows people to decide their priorities for development by enhancing people’s participation in governance. Institution: The term refers to a specified organizational structure with a set of prescribed processes established by the government to facilitate a service or provide material assistance to citizens in general or specifically targeted segments of population. Political economy: The term refers to economic environment influenced by political institutions. Political Ideology: The term refers to political ideologies, particularly democracy and socialism. Socialism and communism have been used loosely to mean the same political ideology. South Asia: The geographical region comprising of eight countries of the Indian Sub- Continent viz., India, Pakistan, Afghanistan, Bhutan, Bangladesh, Nepal, Sri Lanka and Maldives. Transition: Transition implies the change in the orientation of governance from political ideology to socio-economic development. It marks the beginning of the realization that people are central to all forms of governance irrespective of political ideology. Transparency: The accountability with which a system of governance operates and the level to which it allows the subjects to question its processes.



2



3



4



5



6



7



8



9



10

ENDNOTES

1

According to Freedom House, which has tracked political rights and civil liberties around the world since 1972, fewer than half of the world’s nations were democracies in 1991. By 2006, 64 percent were democracies. Thus, in 15 years, democracy has gone from being considered a mostly Western construct to being the predominant form of



11

government globally, universally perceived as an essential source of legitimacy.[See http://www.usaid.gov/sites/default/files/ documents/1866/USAID%20DRG_%20 final%20final%206-24%203%20%281%29. pdf] Source http://www.un.org/en/globalissues/ governance/ (accessed on 04 December 2013) Panikkar KM, Asia and Western Dominance, Unwin University Books, George Allen &Unwin Ltd, London, p17 Wignaraja, Ponna and Hussain, Akmal, Eds, The Challenge in South Asia: Development, Democracy and Regional Cooperation, United Nations University, Tokyo, Sage Publications, New Delhi, 1989. Universal Declaration of Human Rights, 1948 International Covenant on Civil and Political Rights, 1976 International Covenant on Economic, Social and Cultural Rights, 1976 The Millennium Declaration was adopted on 08 Sep 2000 by all the 189 States who are members of UN. For details see http:// www.un.org/en/development/devagenda/ millennium.shtml See Pt III, Para 13 of the Millennium Declaration (UN Resolution A/55/L.2 adopted on 08 September 2000). Full text at http://www. un.org/millennium/declaration/ares552e. htm For an interesting read on the relationship between democracy and growth in Brazil, see http://www.insper.edu.br/wp-content/ uploads/2013/07/2013_wpe311.pdf (accessed on 07 June 2014) As VeliHimanen observes “A change of a government is, of course, no guarantee that things will improve. In two successfulcountries there were few if any changes in the governing parties during the last half of the 20th century: the Social Democrats in

255

 Governance Evolution and Impact on Economic Growth



12



13



14

256

Sweden and the People’s Action Party (PAP) in Singapore”. (Himanen, Veli, Missing a Decent Living for Everyone, LAP Lambert Academic Publishing, Saarbrucken, Germany, 2014, p 69) VeliHimanen used Corruption Perception Index scores (CPI scores) to explore the relationship between quality of governance and economic and social development across 143 countries. While validating the contributory role of governance in facilitating growth, his study found the use of CPI scores for assessing the quality of governance can be complemented by two other indicators that aid to explain many differing characteristics: ease of doing business and economic inequality. See:(Himanen, Veli, Missing a Decent Living for Everyone, LAP Lambert Academic Publishing, Saarbrucken, Germany, 2014) The term ‘Raj’ refers to the oppressive British rule and ‘License’ refers to procedures and Red Tape. ‘License Raj’ came to be widely used in India to refer to the unending, exhaustive and exploitative bureaucratic procedures that hindered investor’s confidence during the late 1970’s till about 1990. Article 40 under the Directive Principles of State Policy (DPSP) called upon the States to take steps to organize Village Panchayats and provide them with necessary finances and authority to function as self-governments. The intent of the Constitution could not have been more eloquent in integrating citizens into governance, not merely as end-users but as decision makers. The spirit of Art 40 was unambiguous. However, with the passing away of Pandit Nehru in 1964, the thrust for expanding the Panchayati system



through Central monitoring, funding and encouragement almost disappeared. The States provided for cursory Panchayati Institution, mostly bereft of financial powers or authority to implement. But the biggest boost to the Panchayati system came when Rajiv Gandhi assumed prime minister-ship in 1989. Realizing the need to reinforce Panchayati Raj Institutions with Constitutional authority, the LM Singhvi Committee suggested Amendment to the Constitution. The 73rd and 74th Amendments to the Constitution in 1992 sought to bring freedom and sovereign power nearer to the people and make democracy more meaningful for the ordinary citizens at the grass roots. The new constitutional provisions of Part IX and IX A seek to change the structure of Indian polity by giving constitutional status to the third tier, that is the Panchayats. Art 243 to 243 ZG have the effect of reinforcing the basic constitutional value that in a democracy, power belongs to the people. They should be able to feel it in their hands and have the assurance of being able to exercise it themselves. The Amendments ensured that State Finance Corporations were mandated to work out the distribution of revenue between the State and Panchayats. In order to bring the urban and semi-urban poor also within the ambit of self-government, municipalities were brought within the ambit of Panchayati Raj institutions (PRI). The PRIs were empowered to impose certain taxes, collect revenue and undertake planning activities on both the dimensions of life in rural areas – economic development and social justice.

257

Chapter 13

Corporate Governance and Firm Performance:

A Study of Listed Firms in India Devanjali Nandi George College, India Arindam Das The University of Burdwan, India

ABSTRACT Ownership structure is considered to be of prime importance in corporate governance of a firm. The ownership structure significantly varies across the nations. The main focus of this chapter is twofold: firstly to see the impact of ownership structure on performance of the firm and secondly to investigate the relationship between stock market performance and ownership structure during the crisis period. Panel data analysis of CNX 200 companies has been done for the time period of 2006-2013.The study also takes into account the relationship between crisis period stock return and ownership structure. The results of this study reveal a positive relationship of promoter’s shareholding with performance while a negative relationship of performance is found with the non-promoters shareholding. The regression of stock price performance on ownership variable gives a significant negative relationship during the crisis period.

INTRODUCTION Corporate governance deals with the ways in which suppliers of finance to corporations assure themselves of getting return on their investment (Shliefer & Vishny, 1997).The development of corporate governance is a global occurrence and is a complex area having legal, cultural, ownership and other differences. Corporate governance

systems are usually classified according to the following five key features (Miguel, Pindado & Torre, 2003): the level of ownership concentration, the effectiveness of boards, the development of capital markets, and the role of the market for corporate control and the legal protection of investors. The publication of Jensen and Meckling’s model resulted in a voluminous body of research, both theoretical and empirical. Through the 1970s

DOI: 10.4018/978-1-4666-8274-0.ch013

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Corporate Governance and Firm Performance

and 1980s that research was largely focused on the governance of US corporations, and US-based corporate governance research continued to expand. By the early 1990s, however, research on governance in countries other than the US began to appear. In the beginning, that research focused mainly on other major world economies, primarily Japan, Germany, and the United Kingdom. More recent years, however, have witnessed an explosion of research on corporate governance around the world, for both developed and emerging economies. The governance mechanisms that have been most extensively studied in the US can be broadly characterized as being either internal or external to the firm. Gompers, Metrick and Ishii (2003) identify four dimensions of corporate governance at the level of the firm that can help to minimize the agency problem: board of directors, ownership structure, executive incentive contracts and charter and bye law provisions. Among these the board of directors and the equity ownership structure of the firm can be defined as internal factors. The primary external mechanisms are the external market for corporate control (the takeover market) and the legal/regulatory system. There are many opposing views regarding the role of controlling shareholder and family owned businesses in corporate governance. Wiwattanakantang (2001) investigate whether the presence of controlling shareholder has negative effects on firm value. The literature suggests that the firms with more than one controlling shareholder have higher ROA relative to firms with no controlling shareholder. They focus on pyramidal ownership and cross shareholdings. Pyramidal ownership is the process of controlling via layers of companies. Cross shareholding is a mechanism for not only assuming effective control, disproportionate to ownership, but also to protect the power of controlling shareholders (Bebchuk, Kraakman & Triantis, 2000). The family as controlling shareholders has two opposite arguments-the first argument states the family might put their own interest above the interest of

258

shareholders. The second argument states family firms provide good monitoring services thus reducing agency costs (Fama & Jensen, 1983). Miller, Le Breton-Miller and Scholnick (2008) suggest two major perspectives of family owned business namely stewardship perspective and stagnation perspective. The stewardship perspective includes stewardship over continuity which views family owned businesses having favourable relationship with stakeholders, stewardship over employees and stewardship over customer relationship. The stagnation perspective on the other hand provides an opposing view and suggests that family owned business face problems like resource restrictions follow conservative strategies and are slow growing. The authors find a significant support for all three elements of stewardship perspective of family owned business while no evidence is found in support of stagnation perspective. Lee and O’Neil (2003) suggest that there is a disparity between the interests of owners and managers. The authors observe that the stewardship theory offers an alternative perspective that is interests of managers are aligned with that of owners. Davis, Schoorman and Donaldson (1997) suggest that a steward will gain more satisfaction by serving the group not himself. They opine that national culture is an important aspect of this kind of behavior. They focused on two measures of national culture that is individualism or collectivism and power distance. In collectivism the group is seen beyond the individual and manager act on the basis of long term relationships. In high power distance situation the manager yield to the way of hierarchy and avoid conflicts with the principals. Jung and Kwon (2002) also suggest two opposing views regarding the role of institutional investors and earning informativeness namely active monitoring and strategic alliance hypothesis. According to active monitoring institutional investors are long term investors with significant incentives to actively oversee managers. On the other hand strategic alliance hypothesis suggest that owners and institutional investors cooperate which reduces

 Corporate Governance and Firm Performance

monitoring resulting in a negative relation between firm value and earning informativeness. According to Claessens and Fan (2002), the Asian corporations are characterized by presence of concentrated ownership in the hands of family members. The company is often controlled by business group which is also controlled by the same family. The modern corporations are divided into insider and outsider system. The insider system of corporate governance is characterized by cross shareholding, involvement of investors in decision making and concentration of share ownership. It is more prevalent in continental Europe and Japan. The outsider system is characterized by an active market for corporate control where shareholders can exercise control over management decision making. It is more prevalent in the US and UK. The ownership of Indian firms is also dominated by families and there is concentration of ownership. The Indian system have the characteristics of both market based Anglo American system and control based system of continental Europe and Japan .The major governance challenge in India is the conflict between dominant shareholder and minority shareholders (Sarkar & Sarkar, 2000). Corporate governance has received much attention in recent years, partly due to the financial crisis in Asia. A review of the literature on corporate governance issues in Asia confirms that, similar to many other emerging markets, the lack of protection of minority rights has been the major corporate governance issue (Claessens & Fan, 2002). There have been a few studies regarding the association of ownership structure and stock price performance during Asian Financial Crisis of 1997(Mitton, 2002; Lemmon & Lins, 2003; Baek, Kang & Park, 2004). According to Lemmon and Lins (2003) the crisis represents a negative shock to the investment opportunities raising the incentives of controlling shareholders to expropriate the minority shareholder. Baek et al. (2004) suggest that during the 1997 Korean financial crisis, firms with higher ownership concentration by unaffiliated foreign investors

experienced a smaller reduction in their share value. The authors also opined that firms whose quality of disclosure is high and use alternative sources of external financing were less affected while firms with concentrated ownership by controlling family shareholders experienced a larger drop in the value of their equity. There have been several studies that link ownership structure with firm performance (McConnel & Servaes, 1990; Demsetz & Villalonga, 2001) but there are few studies which link ownership structure with investment decision. This study fills in this gap by examining the impact of ownership structure on stock returns during the crisis period of 2008.It also finds an association between ownership structure and firm performance using panel data. This study uses shareholding by different groups of owners and its impact on performance of firm in Indian context. In this paper we seek to examine the impact of ownership structure on firm’s performance using panel data for the period of 2006-2013. This study takes the shareholding of promoters as a proxy of insider ownership and that of non promoters as proxy of diffused ownership in lines with Rao and Halder (2011) and Ganguly (2005).A positive association is found between the promoter’s shareholding and firm performance while a negative association is found between non promoters shareholding and performance. Insider ownership leads to better performance of the firm due to three main reasons firstly as Jensen and Meckling (1976) suggest that greater equity ownership by insiders improves performance as agency problems disappear when manager is the majority shareholder. Secondly Shleifer and Vishny (1997) argue that controlling block holders are more capable of monitoring the manager even when they are not involved in management. Thirdly Stein (1989) suggests that family owned firms make better investment decisions. The period of this study is 2006 -2013 which also includes the period of global economic crisis. This the reason that one of the objectives of this study is to find a link between ownership structure

259

 Corporate Governance and Firm Performance

and crisis period stock return. There have been prior research that links stock price adjustments with ownership structure during East-Asian stock market crisis of 1997 (Mitton, 2002; Baek et al., 2004) but the evidence regarding global economic crisis is still in a nascent stage. This study investigates whether the stock price performance depend on the ownership structure of the company during periods of 2008 stock market crisis using data from Indian corporate sector. The main objectives of this study are twofoldfirstly to see the impact of ownership structure on performance of the firm and secondly to investigate the relationship between stock market performance and ownership structure during the crisis period. The study is divided into four parts, the first part deals with survey of literature in this context. The second part focuses on data and methodology while the results are in the third part. The fourth part concludes the paper and provides scope for future research.

LITERATURE REVIEW Previous studies regarding the relationship between ownership structure and firm performance give diverse results. According to some studies (Morck, Shleifer, & Vishny, 1988; Agarwal & Knoeber, 1996; Cho, 1998) ownership concentration has positive impact on firm performance which is known as monitoring hypothesis. Some studies suggest a negative relation between the two widely known as expropriation hypothesis (Kumar, 2003).This study mainly incorporates the impact of ownership structure on firm performance during the period 2006-2013.Since the time period also covers the period of global financial crisis, this study tries to find out if there is any relationship between crisis period returns and the ownership structure of the firm. This paper contributes to an emerging body of research that attempts to identify the mechanisms that influenced how severely the firms were im-

260

pacted by the 2007-2008 crises. The study tries to establish a relation between impacts of the crisis on ownership structure of the firm. Prior studies on the 1997-1998 Asian financial crisis find that greater external monitoring is associated with better performance during the crisis (Johnson, Boone, Breach, & Friedman, 2000; Mitton, 2002).But there has been very limited research regarding the impact of global financial crisis on ownership structure. The literature review thus covers two areas firstly the impact of ownership structure on firm performance and secondly the studies which cover the relationship between ownership structure and financial crisis.

Studies Related To Ownership Structure and Firm Performance Lamba and Stapledon (2009) opine that a block holder in a publicly traded firm may secure two types of benefits namely shared benefits of control and private benefits of control. Shared benefits are enjoyed by both block holders and shareholders while private benefits are enjoyed only by the block holders. These may include misappropriation of corporate assets at the expense of minority shareholders. Claessens and Fan (2002) suggest that weak state of enforcement of property rights as the main reason for ownership concentration in Asian corporations as they face weak legal system, poor law enforcement and corruption .Another reason for prevalence of groups in Asia may be poorly developed external markets. Many studies relating to ownership concentration and firm performance find a positive relationship between the two. The reason behind this is that block holders have both the ability and incentive to monitor and control agent. This is called incentive alignment. La Porta, Lopezde-Silanes, Shleifer and Vishny (1998) suggest low investor protection will lead to higher ownership concentration to protect the interest of minority shareholders. Other studies suggest

 Corporate Governance and Firm Performance

that increased control by block holders reduces the interest of managers which is known as over monitoring (Burkart, Gromb, & Panunzi, 1997). High ownership concentration will give more power and control to block holders (Burkart et al, 1997). Fama and Jensen (1983) suggest that higher ownership concentration leads to lower liquidity of stock. Thus stock become more risky and cost of capital rises. The proponents of this theory suggest that ownership concentration has the potential to limit the agency problem and then generate improved corporate performance. This positive impact of ownership can be explained by efficient monitoring hypothesis which states that higher concentration of ownership gives large shareholders strong incentives and greater power to lower monitoring cost. The study by King and Santor (2008) uses 613 Canadian firms over the period of 1998-2005.They use random effects model because a number of the variables used are either time invariant or exhibit few changes over time. The impact of ownership is examined on two measures of firm performance ROCE and ROA. They find that family owned firms with single share class have similar market performance based on Tobin’s Q, ROA and have higher financial leverage than other firms. On the other hand family owned firms that use dual class shares have valuations that are lower by 17% on average relative to widely held firms despite having similar ROA. Another group of studies suggest that no observable relationship is found between ownership structure and firm performance The argument behind this being firms perform equally well under different ownership structures. Non linear relationship are found using piecewise linear regression (Morck et al, 1998) while some studies found a curvilinear relationship between ownership structure and firm performance (McConnel & Servaes, 1990). Wiwattanakantang (2001) investigate whether the presence of controlling shareholder has negative effects on firm value. According to their study a controlling shareholder is defined as an

entity who owns 25% of firm’s share directly or indirectly as per definition of stock exchange of Thailand. Ownership there is based on control rights and not on cash flow rights. The author finds a positive association between controlling shareholders and ROA. The results indicate that separation of voting rights and cash flow rights has no significant effect on performance. Jung and Kwon (2002) examine the relationship between corporate ownership structure in Korea and earning informativeness for 760 companies during the period 1993-1998.In Korea the majority of shares are owned by one major shareholder and this control may extend to many companies forming a corporate group called chaebol. The authors examine the relationship between the holding of the largest owner and earning informativeness on the first place. Their second objective is to find the role of institutional investors and block holders in the presence of largest shareholder. Thirdly they examine if there is any difference between the earning informativeness of chaebol and non chaebol companies. They suggest that market places more importance on positive side of manager’s holding than the negative side. The earning becomes informative with increase in holding of institutions. In Indian context Deb and Chaturvedula (2003), Pant and Pattanaik (2007) and Srivastava (2011) have studied the impact of ownership concentration on firm performance .Deb and Chaturvedula (2003) have studied the relationship between ownership concentration and firm value. The authors investigate the relationship between ownership structure and value in Indian firms by testing for “Monitoring and Expropriation” hypothesis and “Convergence of Interest” and “Entrenchment hypothesis”. Their study has been based on cross-section data of 443 Indian firms (from both manufacturing & service sector) included in S&P CNX 500 index of National Stock Exchange (NSE) of India. The authors have studied 443 manufacturing and service listed Indian companies in 2003 and have found that firm performance

261

 Corporate Governance and Firm Performance

(measured by Tobin’s Q) is significantly related to ownership structure. The findings of these studies put forward evidences in support of ownership structure as an effective corporate governance mechanism. Khanna and Palepu (2000) have examined the relative efficiency of domestic financial institutions and foreign institutions in governing group affiliated and non-group companies. Sarkar and Sarkar (2000) in their study on Indian firms using 1994-95 data find no evidence of expropriation by insiders at any level of holdings. The authors have found that block-holdings by directors’ increases company value after a certain level of holdings. However, the authors did not obtain any evidence of active governance from institutional investors. Kumar (2003) has empirically examined the impact of ownership structure on firm performance for a panel of Indian corporate firms from an agency perspective. The author has examined using panel data framework, effect of foreign, corporate, institutional and managerial ownership on performance of BSE listed companies from1994-2000.The author concludes that the foreign shareholding pattern does not influence the firm performance significantly. The author has documented that institutional investors especially the development financial institutions affect firm performance positively once their ownership crosses a threshold level.

Studies Related To Ownership Structure and Financial Crisis Weak corporate governance has frequently been cited as one of the causes of the East Asian financial crisis of 1997 to 1998 (Stiglitz, 1998). The study by Mitton (2002) states that the state of corporate governance practices in East Asian countries made them vulnerable to the crisis. The author also opines that corporate governance could become more critical in a financial crisis for two reasons. First, expropriation of minority shareholders could become more severe during a crisis.

262

Second, a firm may have higher disclosure quality if its auditor is one of the Big Six international accounting firms. Shleifer and Vishny (1997) argue that ownership concentration is, along with legal protection, one of two key determinants of corporate governance. The aspect of corporate governance studied here is ownership structure where we take into account the percentage of share held by promoters and non-promoters. Consistent with the view that large shareholders can prevent expropriation, higher ownership concentration is associated with significantly better stock price performance during the crisis (Mitton, 2002). Lemmon and Lins (2003) take a sample of 800 firms from eight East Asian countries and examine whether the difference in firm performance is impacted by difference in ownership structure during East Asian Financial crisis. They test the hypothesis by examining the variation across firms in stock returns during the crisis period as a function of ownership structure. They find evidence that corporate ownership structure plays an important role in determining the incentives of insiders to expropriate minority shareholders during the time of crisis. Baek et al. (2004) focused on Korean Business groups, chaebols, and found that during the 1997 Korean financial crisis, chaebol firms with higher ownership concentration by unaffiliated foreign investors experienced a smaller reduction in their share value. Mitton (2002) use firm level data to study the impact of corporate governance on firm performance during financial crisis in five east Asian economies namely Korea, Indonesia, Malaysia, the Philippines and Thailand. They suggest that corporate governance became more critical during crisis for two reasons firstly due to increase in expropriation of minority shareholders during the crisis. Johnson et al. (2000) suggest that crisis can lead to increase in expropriation as managers indulge in such behavior as return on investment fall. Secondly crisis can lead the investors to recognize the weakness of corporate governance that was existing for long in that region.

 Corporate Governance and Firm Performance

Liu, Uchida and Yang (2012) suggest that stock returns during a crisis period serve as an appropriate measure of the expropriation problem that is evident in countries with weak legal protection of investor rights in Chinese context. However once the crisis period begins and expected return fall, investor begin to consider corporate governance weaknesses. It can be concluded from the existing literature that there have been several studies that relate ownership structure with firm performance across the world. But in Indian context there have been few studies in this regard. The relationship between investment decision and ownership structure has not been studied much in context of global financial crisis. This study fills in this research gap and contributes to the existing literature.

Variables Selection

DATA AND METHODOLOGY

ROCE (Return on capital employed) given by earnings before interest and tax divided by capital employed is used as proxy for firm performance. ROA (Return on Assets) given by earnings before interest and tax divided by total assets as proxy for measuring firm performance. Stock return: We take the log of stock return during the crisis period as proxy for crisis period stock return. We do not incorporate beta for calculation of abnormal return as data limitations prevent calculation of pre crisis betas. So we use size and leverage as control variables to control factors that could affect returns (Mitton, 2002). Independent Variable: This study follows the model suggested by Demsetz and Villalonga (2001). They suggested two ownership variables, viz., the shareholdings of the firms’ five largest shareholders and the shareholding of the firm’s top management as criteria for concentration of ownership. We modified the model as per Indian scenario given by Ganguly (2005). Thus, the proxy used for ownership is the equity-holding structure. Thus, this study includes two ownership variables namely promoter shareholding and non-promoter

The study is based on the companies listed in CNX 200 listed in NSE for the year 2006-2013. The firm level panel data for our study is primarily obtained from the corporate database PROWESS maintained by CMIE, the Centre for Monitoring the Indian Economy. The data used in the analysis consists of CNX 200 companies, for which we could get their historical share holding pattern. We have excluded the banking companies as they are governed by banking regulation act and are different from the companies governed by companies act. We also exclude the companies whose data are not available for all the variables. We do not take into account the public sector companies as they are governed by many political and social obligations. This brings our sample size to 134 firms. We analyse data from 2006 to 2013. In the time period of our study we cover the year 2007-08 which was the period of global financial crisis. We collect the closing stock price data for this time period for the sample firms during the crisis period from PROWESS database of CMIE.

Using data from the years 2006-2013 we have used the ownership variables namely promoters shareholding and non-promoters shareholding. These are as per clause 35 of the listing agreement. All the listed companies are required to report the ownership structure for each quarter in the format outlined in this clause. This clause requires the firm to report promoter following the definitions in the subsection 11(e) to 11(h) of substantial acquisition and takeover act, 1997. Thus according to this clause total promoters means the sum of promoters and persons acting in concert with promoters. All the other shareholding is reported as non promoters.

Dependent Variable

263

 Corporate Governance and Firm Performance

shareholding for representing concentrated ownership and diffused ownership respectively. The promoter’s shareholding is further divided into Indian promoters and foreign promoters and non promoter’s shareholding into institutional and non institutional non promoters.

Control Variables Control variables introduced in the study include size, age and leverage. Size: Natural logarithm of assets is used to control for firm size. A vast amount of literature has investigated the relation between size and performance of firms. Firm size can be measured in different ways; one of the ways is using total assets as a proxy of firm size. Gilson (1997) used the natural log of total assets as a proxy of firm size. Age: The age measures the number of years the firm is in existence since its incorporation. Ang, Colwm and Wuh Lin (1999) argued that due to the experience older firms are likely to be more efficient than younger ones. Thus, a better performance should be expected. However, older companies are rigid, prone to inertia and lack adaptability, which may lead to lower performance. Leverage: The debt equity ratio is used as the proxy for measuring leverage. It is used to control the impact of capital structure. Impact of leverage on firm performance has mixed opinions. In this context a Modigliani-Miller model suggest firm to be independent of capital structure. Thus according to them capital structure does not have any impact on firm performance. Theories of capital structure and ownership provide the role of debt in reducing the agency problems. Jensen and Meckling (1976) argue that managers prefer lower financial leverage because it reduces the risk of bankruptcy and protects their undiversified human capital. In contrast, Stulz (1988) argue that firms with controlling shareholder should exhibit higher financial leverage. Majority of the studies following Holderness and Sheehan (1988) find a negative relationship between managerial owner-

264

ship and financial leverage. King and Santor (2008) find that family owned firms with single share class have similar market performance based on Tobin’s Q, ROA and have higher financial leverage than other firms. According to Ganguly (2005), it is necessary to formulate two sets of regression equation because inclusion of both promoters’ and non-promoters’ shareholding in the same equation will lead to near-perfect multi-collinearity as by definition if promoters’ holding is p and non-promoters’ holding will be (1-p). Later Halder and Rao (2011) used a similar model for measuring the impact of ownership concentration on firm’s performance. Following their model we form the equations one with promoter’s ownership and one with non-promoter’s ownership. We further divide promoter’s ownership into Indian and foreign promoter’s ownership and regress it to performance. On the similar lines we divide non-promoters ownership into institutional and non institutional ownership. Pit = a + β (OWN) + yXit + δi + u it it

Here, Pit= performance of firm i at time t (OWN)it =percentage of share held by firm i at time t Xit = control variables age, size and leverage δi, uit =Error terms

RESULTS AND DISCUSSIONS In India ownership is concentrated with Indian promoters. Although India has a tradition of equity ownership by promoters, the institutional investors especially foreign institutional investors have been consolidating their holdings in companies since they were allowed to invest in 1998-99. The promoters are generally the dominant share-

 Corporate Governance and Firm Performance

Table 1. Ownership of the sample companies between various categories of shareholders 2006

2007

2008

2009

2010

2011

2012

2013

46.82

51.2752

52.11

52.37

51.71

52.4688

52.6613

52.4688

Indian promoter share

35.9

45.513

46.62

46.93

46.67

47.8305

48.1066

47.8305

Foreign promoter share

22.7

25.5712

30.02

28.8

28.7

28.8265

28.6254

28.8265

53.17

49.4504

47.88

47.69

48.42

47.6749

47.4734

47.6749

28.1

27.9253

26.75

25.45

28.35

29.5638

28.9481

29.5638

25.08

21.5255

21.13

22.24

20.06

18.1119

18.5266

18.1119

Promoter share

Non promoter share Non promoter(institutional) share Non promoter (non institutional) share

holders followed by the institutional investors. The individual investors are the least significant in terms of large stake. The Indian system has the characteristics of both market based Anglo American system and control based system of continental Europe and Japan. Since 2001 all the listed companies are required to report the details as per clause 35 of the listing agreement. According to Clause 35 of the listing agreement insiders are the promoters of the company and PACs (persons acting in concert) while outsiders are defined as non promoters. The promoters are further classified as Indian promoters, foreign promoters and person acting in concert. With regard to non-promoter holdings, any shareholding other than promoters was required to be disclosed under the revised Clause 35 under the heading non-promoters which includes institutional non-promoters and non-institutional non-promoters. Holdings by government-owned financial institutions, public and private sector commercial banks, government-owned and private sector insurance companies, public and privatelyowned mutual funds, foreign institutional investors, venture capital funds, foreign venture capital investors, central and state governments, and others, fall under institutional public shareholdings. Under non-institutional public shareholdings are corporate bodies, individuals, and others. The ownership trend is analyzed for the components of the aggregate ownership of an unbal-

anced panel of companies from Prowess for the period 2006-2013. Table 1 presents the descriptive statistics in respect of pooled data. It can be seen from table 4 that promoters’ shareholding mean as 51.36% while that of non promoters is 48.3%. Out of this the share of Indian promoters is 46.15%while that of foreign promoter is 26.08%. This suggest concentration of shareholding in the hands of Indian promoters. The prevalence of insider control in Indian companies can be seen in Table 2 revealing concentrated ownership and control structures in India since the early years of Indian industrialisation from a regulated economy to a liberal and open economy (Khanna & Palepu, 2005).The data for the period 2006-2013 has been analysed. This was the period chosen as in 2006 most of the companies started following the mandatory requirements of corporate governance in their annual reports. The time period of the study also include the year 2008 which was the time of global financial crisis. We thus associate the stock returns during this period with ownership structure to analyse the impact of crisis on ownership structure.

Random Effects or Fixed Effects Green (1997) maintains that the panel data sets allow researchers to capture both time series and cross-sectional relations. There are both fixedeffects and random-effects panel models. The

265

 Corporate Governance and Firm Performance

Table 2. Summary statistics Observation ROCE

Minimum

Maximum

Mean

Std Deviation

-38.8400

188.4600

17.730469

19.422

-26.05

128.40

11.1764

10.39521

15.4200

90.0000

51.367768

17.2178226

Indian Promoters - Shares held

.0000

90.0000

46.152278

18.9110568

Foreign Promoters - Shares held

.0000

86.8700

26.084595

23.8070842

10.0000

99.7000

48.302937

17.3834627

1.4400

78.1600

20.350317

11.5686968

Non-promoter Institutions - Shares held

.0800

71.3200

27.953042

13.3275906

D/E

.0000

17.5800

.666360

1.1468

size

5.5703

14.9743

10.652021

1.3986966

Age

1

116

37.82

25.664

ROA Promoters - Shares held

Non-promoters - Shares held Non-promoter non institutions shares held

regression of the dependent variable ROA and ROCE which signify performance on various explanatory variables have been done. By (OWN) it is meant promoters’ and non promoters’ shareit holding. By Xit it is meant the control variables that are size, age and leverage. The use of either of the above models hinges on whether the cross section specific error components are correlated with the explanatory variables.

If they are correlated, use of Random Effects or Error Component Model would be inappropriate. The Breusch Pagan LM test is applied first to find whether OLS is better or a Random effect is better. The test gives significant value of χ2 and it is concluded that Random effect is better than OLS in this case. Now it is determined whether one should employ fixed effect or random effect on this model. For testing this, the Hausman Test

Table 3. Results with ownership structure and firm performance when ROCE is dependent variable Explanatory variable Promoters share

Model 1

Model2

Model 3

0.113(2.06)**

Indian promoters share

0.129(2.10)**

Foreign promoters share

0.1899(2.82)*

Non promoters share

-0.097(-1.78)***

Non-promoters (institutional) share

-0.026(-0.43)

Non-promoter(non institutional) share age

Model 4

-0.219(-3.04)* 0.1066(2.17)**

0.115(2.39)**

0.0234(0.43)

0.120(2.48)**

-2.013(-3.89)*

-2.001(-3.91)*

-3.801(-3.79)*

-1.76(-3.40)*

Size

-3.52(-5.83)*

-3.47(-5.82)*

-2.10(-2.95)*

-3.91(-3.40)*

Constant

46.53(6.67)*

56.33(8.39)*

32.78(4.03)*

61.21(8.79)*

Leverage

Notes: Model 1: Pit = α + β(Promoters share)it+ γXit + δi + Ɛit, Model 2:Pit = α + β(Non Promoters share)it+ γXit + δi + Ɛit, Model 3:Pit = α + β1(Indian Promoters share)it+β2(Foreign Promoters share)+ γXit + δi + Ɛit, Model 4: Pit = α + β1(Non Promoters(institutional) share)it+β2(Non Promoters(non institutional) share)+ γXit + δi + Ɛit. Here Pit = ROCE and Xit=control variables age, size and leverage. t- statistics are in brackets and significance levels are*1%, ** 5%, *** 10%

266

 Corporate Governance and Firm Performance

Table 4. Results with ownership structure and performance when ROA is dependent variable Explanatory variable

Model 1

Promoters share

0.056(1.94)***

Model 2

Model 3

Indian promoters share

0.468(1.08)

Foreign promoters share

0.096(2.06)*

Non promoters share

Model 4

-.049(1.70)***

Non-promoters (institutional) share

-0.0016(-0.005)

Non-promoter(non institutional) share

-0.128(-3.29)*

Age

0.0109(0.45)

0.0185(0.76)

-0.012(-0.33)

0.0213(0.88)

D/E

-1.36(-4.68)*

-1.37(0.00)*

-2.72(-3.96)*

-1.21(-4.11)*

Size

-1.79(-5.38)*

-1.76(0.00)*

-1.39(-2.82)*

-2.04(-6.09)*

constant

27.63(7.32)*

32.4(0.00)*

25.19(4.45)*

35.4(9.42)*

Notes: The models are same as Table 3. t-statistics are in brackets and significance levels are*1%, ** 5%, *** 10%

for cross – section random effects is employed. Here we get a χ2 value which is significant and hence employ fixed effects for our model. The results of Hausman test and Breusch Pagan test are presented in Tables 6 and 7. Firstly the regression is performed on promoter’s shareholding as independent variable with respect to ROA and ROCE. Then the test is performed on non promoter’s shareholding as independent variable with respect to ROA and ROCE. The results of the fixed effect regression presented in table 3 and 4 reveal that after controlling for age, size and leverage the ownership concentration represented by percentage of promoter share is positively related to firm performance. The results are presented in form of two tables –one with ROCE as dependent variable and one with ROA as dependent variable. In each of the tables we have four models -model 1 representing promoters share and model 2 representing non –promoters share as independent variable. The promoter’s share is further divided into Indian and foreign promoter share and is presented in model 3. Model 4 gives the details of division of non-promoters into institutional and non institutional shares as independent variable. Looking at the tables we can observe a positive relationship between promoters’ share and

firm performance represented by ROCE as well as ROA. When we see the results of model 3 we find that shareholdings of both Indian and foreign promoters are significantly related to ROCE as well as ROA of the firm. In case of non promoters’ shareholding shown in model 2 it is found to be negatively related to performance. The result is significant at 10% in case of ROA as well as ROCE. The non- promoter (non-institutional) shareholding is found to be negatively related to firm performance. We find that in case of promoters, age has a positive significant impact on firm performance in case of ROCE. It is observed that size and leverage (D/E) are negatively related to performance in case of both ROA and ROCE. Table 5 describes the regression results of stock returns during crisis period with ownership variables. We formulate four models to describe this relationship. In all the models we take age, size and leverage as control variables. We consider two measures for ownership that is concentrated ownership represented by promoter’s shareholding and dispersed ownership reflected by non promoter’s shareholding (Ganguly, 2005; Rao & Haldar, 2011). The promoters’ shareholding is further divided into Indian promoters holding and foreign promoters holding while nonpromoters holding include both institutional and

267

 Corporate Governance and Firm Performance

Table 5. Results of ownership structure and performance when crisis period stock returns is dependent variable Explanatory Variables Promoter

Model 1

Model 2

Model 3

-0.010(2.18)

Indian promoter

-0.020 (-1.345)

Non promoter

0.008 (1.73)*

Non promoter(institutional)

age

0.015 (1.890)*** 0.096 (1.383)

0.089 (0.279)

0.034 (0.531)

0.030 (0.456)

0.064 (0.990)

-0.029 (-0.182)

0.048 (0.755)

0.075 (1.103)

-0.005 (-1.46)

0.004 (0.372)

-0.004 (-1.398)

-0.005 (-1.561)

3.61 (4.989)*

5.406 (2.660)**

2.929 (4.39)*

2.624 (3.635)*

Adjusted R2

0.060

0.106

0.025

0.027

Durbin Watson

1.964

constant

2.23

1.930

1.974

Notes: The models are same as Table 3. t-statistics are in brackets and significance levels are*** 10%;** 5%; and *1%

non-institutional holding. Table 7 and 8 provide the results of Hausman test and Breush Pagan LM test. Model 1 presents the model with promoter’s shareholding as independent variable. Model 2 includes Indian promoters share and foreign promoter share. It is found that promoter’s shareholding along with Indian promoter’s ownership is negatively significant meaning the lower the ownership concentration, the higher the stock returns. We repeated the analysis using the shareholdings by the non-promoters in model 3 and found no relationship. In model 4, we split the non promoter shareholding into-institutional and non–institutional shareholding categories and find that the non institutional shareholding of non promoters is significantly associated with

268

Collinearity Statistics Tolerance

VIF

age

.913

1.095

size

.937

1.068

d_e

.924

1.082

prom_share

.942

1.062

Model 2 0.004 (0.767)

Non promoter (non institutional)

size

Model 1 (Constant)

-0.031 (-2.608)**

Foreign promoter

D/E

Model 4

Table 6. Variance Inflation Factors for testing multicollinearity among variables of crisis period stock return

(Constant) age

.815

1.226

size

.823

1.216

d_e

.863

1.159

ind_prom

.594

1.685

for_prom

.628

1.592

Model 3 age

.885

1.130

size

.875

1.143

d_e

.819

1.221

non_prom

.891

1.122

age

.861

1.161

size

.759

1.317

d_e

.815

1.227

nprom_inst

.873

1.146

nprom_noninst

.870

1.149

Model 4

stock prices. Overall the results from table 5 show that both dispersed ownership by non promoters (Non-institutional) and ownership concentration by promoters are considered by investors to make price adjustments during periods of crisis. Table 6 provides the VIF (variance inflation factors) of the variables and we observe them to be within limit of 1.5 describing no multicollinearity. To reduce multicollinearity problems we have framed our models taking promoters and non promoters shareholdings separately.

 Corporate Governance and Firm Performance

Table 7. Diagnostic test results with ownership structure and performance when ROA is dependent variable

Table 8. Diagnostic test results with ownership structure and performance when ROCE is dependent variable

Model 1

Model 1

Breush and Pagan Langragian multiplier test for random effects

Chibar2(01)=715.06*

Prob>chibar2=0.00

Breush and Pagan Langragian multiplier test for random effects

Chibar2(01)=1105.82

Prob>chibar2=0.00

Fixed or Random: Hausman test

Chi2(4)=11.59**

Prob>chi2=0.026

Fixed or Random: Hausman test

Chi2(4)=10.09

Prob>chi2=0.012

Breush and Pagan Langragian multiplier test for random effects

Chibar2(01)=740.90*

Prob>chibar2=0.000

Breush and Pagan Langragian multiplier test for random effects

Chibar2(01)=1134.25

Prob>chibar2=0.00

Fixed or Random: Hausman test

Chi2(4)=12.31**

Prob>chi2=0.035

Fixed or Random: Hausman test

Chi2(4)=10.42

Prob>chi2=0.018

Model 2

Model 2

Model 3

Model 3

Breush and Pagan Langragian multiplier test for random effects

Chibar2(01)=114.78*

Prob>chibar2=0.00

Breush and Pagan Langragian multiplier test for random effects

Chibar2(01)=144.57

Prob>chibar2=0.00

Fixed or Random: Hausman test

Chi2(4)=6.37**

Prob>chi2=0.045

Fixed or Random: Hausman test

Chi2(4)=9.29

Prob>chi2=0.010

Breush and Pagan Langragian multiplier test for random effects

Chibar2(01)=746.46*

Prob>chibar2=0.00

Breush and Pagan Langragian multiplier test for random effects

Chibar2(01)=1140.28

Prob>chibar2=0.00

Fixed or Random: Hausman test

Chi2(4)=13.06**

Prob>chi2=0.021

Fixed or Random: Hausman test

Chi2(4)=10.29

Prob>chi2=0.013

Model 4

Model 4

CONCLUSION AND FUTURE DIRECTION OF RESEARCH The results of the analysis reveal that shareholding of promoters has a significant impact on corporate performance. This is consistent with work of earlier studies in this regard .The shareholding of non-promoters have been found to be negatively related to firm performance. When a promoter is divided into Indian and foreign promoters a significant relationship is found with performance after controlling for age, size and leverage. In case of non-promoters a negatively significant relationship is found in case of institutional non promoters which include mutual funds, banks, financial institutions etc. The association of stock price with ownership structure during the

crisis period gives a negative and significant association between the two variables. There have been varied views regarding the concentration of ownership and stock price performance during the crisis period. According to some studies large shareholders can prevent expropriation and protect the rights of minority shareholders (La porta et al., 1998).In such cases presence of block holders may positively impact the stock prices during crisis period(Mitton, 2002).Large shareholders may sometimes themselves engage into expropriation and may pursue their own objectives at the cost of minority shareholders (Morck, Strangeland, & Yeung, 2000); Bebchuk et al., 2000).They are likely to indulge in this kind of act generally when they are involved with management or if their voting rights exceed their cash flow rights (Claessens

269

 Corporate Governance and Firm Performance

& Fan, 2000). Our results support the argument of expropriation due to ownership concentration during the period of crisis. Scope for future research: 1. The causes of different ownership structures and their relationship with institutional environment of the country can be studied .Ownership structure varies across the countries and over time .Thus examining the cross national differences in corporate governance environment can be studied. 2. The impact of family ownership on firm performance can be analyzed empirically. The emphasis of these studies should be on evolution of corporate governance in family owned companies and better alignment of interest of controlling family with other stakeholders. The implication of ownership structure on corporate strategies like dividend policy, takeovers, investment decisions etc. could be an interesting area of research. 3. The issue of endogenity needs to be addressed closely and empirical tests should be carefully designed and the results should be accurately interpreted. 4. The study of impact of financial crisis on ownership structure can be studied with respect to pre crisis and post crisis periods. 5. Other aspects of corporate governance like board structure, CEO duality and executive compensation can be studied along with ownership structure.

REFERENCES Agarwal, A., & Knober, C. (1996). Firm performance and mechanisms to control agency problems between managers and shareholders. Journal of Financial and Quantitative Analysis, 31(3), 377–397. doi:10.2307/2331397

270

Ang, J. S., Colwm, R. A., & Wuh Lin, J. (1999). Agency costs and ownership structure. The Journal of Finance, 55(2), 478–517. Baek, J. S., Kang, J. K., & Park, K. S. (2004). Corporate governance and firm value: Evidence from the Korean financial crisis. Journal of Financial Economics, 71(2), 265–313. doi:10.1016/ S0304-405X(03)00167-3 Bebchuk, L., Kraakman, R., & Triantis, G. (2000). Stock pyramids, cross-ownership, and dual class equity. In R. Morck (Ed.), Concentrated Corporate Ownership (pp. 295–315). Chicago: The University of Chicago Press. Berle, A. A., & Means, G. C. (1932). The Modern Corporation and Private Property. New York: MacMillan Co. Burkart, M., Gromb, D., & Panunzi, F. (1997). Large Shareholders, monitoring and the value of the firm. The Quarterly Journal of Economics, 112(3), 693–728. doi:10.1162/003355397555325 Cho, M. H. (1998). Ownership structure, investment, and the corporate value: An empirical analysis. Journal of Financial Economics, 47(1), 103–121. doi:10.1016/S0304-405X(97)00039-1 Claessens, S., Djankov, S., & Lang, L. (2000). The separation of ownership and control in East Asian corporations. Journal of Financial Economics, 58(1), 81–112. doi:10.1016/S0304405X(00)00067-2 Claessens, S., & Fan, J. P. H. (2002). Corporate governance in Asia-A Survey. International Review of Finance, 3(2), 71–103. doi:10.1111/14682443.00034 Davis, J. H., Schoorman, D. F., & Donaldson, L. (1997). Towards a stewardship theory of management. Academy of Management Review, 22(1), 20–47.

 Corporate Governance and Firm Performance

Deb, S. S., & Chaturvedula, C. (2003).Ownership structure and firm value: empirical study on corporate governance system of Indian firms. SSRN Working Paper Series, no. 594221. Retrieved from http://papers.ssrn.com/sol3/papers. cfm?abstract_id=594221 Demsetz, H., & Villalonga, B. (2001).Ownership structure and corporate performance. SSRN Working Paper Series, no.266101. http://ssrn.com Denis, D. K., & McConnell, J. J. (2005). In K. Keasey., S. Thomson, & M. Wright (Eds.), Corporate governance: Accountability, enterprise and international comparisons, England: John Wiley and Sons. Fama, E., & Jensen, M. (1983). Separation of ownership and control. The Journal of Law & Economics, 26(2), 301–325. doi:10.1086/467037 Ganguly, S. K. (2005). Capital Structure-Does Ownership Structure matter? Theory and Indian Evidence. Retrieved from http://papers.ssrn.com/ sol3/papers.cfm?abstract_id=1618747 Gilson, S. (1997). Transaction costs and capital structure choice: Evidence from financial distressed firms. The Journal of Finance, 52, 161–195. Gompers, P., Ishii, J., & Metrick, A. (2003). Corporate governance and equity prices. The Quarterly Journal of Economics, 118(1), 107–155. doi:10.1162/00335530360535162 Green, W. H. (1997). Econometric Analysis (3rd ed.). Upper Saddle River, NJ: Prentice-Hall. Holderness, C. G., & Sheehan, D. P. (1988). The role of majority shareholders in publicly held corporations: An exploratory analysis. Journal of Financial Economics, 20(1/2), 317–346. doi:10.1016/0304-405X(88)90049-9

Jensen, M. C., & Meckling, W. (1976). Theory of the firm: Managerial behavior, agency cost, and capital structure. Journal of Financial Economics, 3(4), 305–360. doi:10.1016/0304405X(76)90026-X Johnson, S., Boone, P., Breach, A., & Friedman, E. (2000). Corporate governance in the Asian financial crisis. Journal of Financial Economics, 58(1–2), 141–186. doi:10.1016/S0304405X(00)00069-6 Jung, K., & Kwon, S. Y. (2002). Ownership structure and earnings informativeness: Evidence from Korea. The International Journal of Accounting, 37(3), 301–325. doi:10.1016/S00207063(02)00173-5 Khanna, T., & Palepu, K. (2000). Is group affiliation profitable in emerging markets? An analysis of diversified Indian business groups. The Journal of Finance, 55(2), 867–891. King, M. R., & Santor, E. (2008). Family values: Ownership structure, performance and capital structure of Canadian firms. Journal of Banking & Finance, 32(11), 2423–2432. doi:10.1016/j. jbankfin.2008.02.002 Kumar, J. (2003). Does Ownership Structure Influence Firm Value? Evidence from India. EFMA 2004 Basel Meetings Paper. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_ id=464521 La Porta, R., Lopez-de-Silanes, F., & Shleifer, A. (1999). Corporate Ownership around the World. The Journal of Finance, 54(2), 471–517. doi:10.1111/0022-1082.00115 La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. W. (1998). Law and Finance. Journal of Political Economy, 106(6), 1113–1155. doi:10.1086/250042

271

 Corporate Governance and Firm Performance

Lamba, A. S., & Stapeldon, G. (2009). The determinants of ownership structure: Australian evidence. Retrieved from http://papers.ssrn.com/ sol3/papers.cfm?abstract_id=279015 Lee, P. M., & O’Neill, H. M. (2003). Ownership structures and R&D investments of U.S. and Japanese firms: Agency and stewardship perspectives. Academy of Management Journal, 46(2), 212–225. doi:10.2307/30040615 Lemmon, M., & Lins, K. (2003). Ownership structure, corporate governance, and firm value: Evidence from the east asian financial crisis. The Journal of Finance, 58(4), 1445–1468. doi:10.1111/1540-6261.00573

Morck, R., Shleifer, A., & Vishny, R. W. (1988). Management ownership and market valuation:an empirical analysis. Journal of Financial Economics, 20(1–3), 293–315. doi:10.1016/0304405X(88)90048-7 Morck, R., Strangeland, D., & Yeung, B. (2000). Inherited Wealth, Corporate Control and Economic Growth: The Canadian disease? In C. C. Ownership (Ed.), R. Morck (pp. 319–372). Chicago: The University of Chicago Press. Pant, M., & Pattanaik, M. (2007). Insider ownership and firm value-Evidence from Indian corporate sector. Economic and Political Weekly, 42(16), 1459–1467.

Liu, C., Uchida, K., & Yang, Y. (2012). Corporate Governance and firm value during the global Financial Crisis: Evidence from China. International Review of Financial Analysis, 21, 70–80. doi:10.1016/j.irfa.2011.11.002

Patibandla, M. (2006). Equity pattern, corporate governance and performance: A study of Indian corporate sector. Journal of Economic Behavior & Organization, 59(1), 29–44. doi:10.1016/j. jebo.2004.04.004

McConnell, J. J., & Servaes, H. (1990). Additional evidence on equity ownership and corporate value. Journal of Financial Economics, 27(2), 595–612. doi:10.1016/0304-405X(90)90069-C

Pattanayak, M. (2008). Insider Ownership and Firm Value. MPRA Paper No. 10971, September. Retrieved from http://mpra.ub.uni-muenchen. de/10971

Miguel, A., Pindado, J., & Torre, C. (2003). Ownership Structure and Firm Value: New Evidence from the Spanish Corporate Governance System. Paper presented in EFMA 2003 Helsinki meetings. http://ssrn.com/abstract=292282

Rao, S., & Haldar, A. (2011). Empirical study on ownership structure and firm performance. Indian Journal of Corporate Governance, 4(2), 27–34.

Miller, D., Le Breton-Miller, I., & Scholnick, B. (2008). Stewardship vs. Stagnation: An empirical comparison of small family and non-family businesses. Journal of Management Studies, 45(1), 51–78. Mitton, T. (2002). A coss-firm analysis of the impact of corporate governance on the east asian financial crisis. Journal of Financial Economics, 64(2), 215–241. doi:10.1016/S0304405X(02)00076-4

272

Sarkar, J., & Sarkar, S. (2000). Large shareholder activism in corporate governance in developing countries: Evidence from India. International Review of Finance, 1(3), 161–194. doi:10.1111/14682443.00010 Shleifer, A., & Vishny, R. W. (1997). A survey of corporate governance. The Journal of Finance, 52(2), 737–783. doi:10.1111/j.1540-6261.1997. tb04820.x Srivastava, A. (2011). Ownership structure and corporate performance: Evidence from India. International Journal of Humanities and Social Science, 1(1), 23–29.

 Corporate Governance and Firm Performance

Stein, J. C. (1989). Efficient capital markets, inefficient firms: A model of myopic corporate behavior. The Quarterly Journal of Economics, 104(4), 655–669. doi:10.2307/2937861 Stiglitz, J. (1998). The Role of International Financial Institutions in the Current Global Economy. Address to the Chicago Council on Foreign Relations, February 27. Stulz, R. M. (1990). Managerial discretion and optimal fnancing policies. Journal of Financial Economics, 26(1), 3–27. doi:10.1016/0304405X(90)90011-N Wiwattanakantang, Y. (2001). Controlling shareholders and corporate value: Evidence from Thailand. Pacific-Basin Finance Journal, 9(4), 323–362. doi:10.1016/S0927-538X(01)00022-1

ADDITIONAL READING Chhibber, P. K., & Majumdar, S. K. (1999). Foreign ownership and profitability: Property rights, control, and the performance of firms in Indian industry. Journal of Law and Finance, 42(1), 209–239. CII. (1998). Desirable corporate governance: A code. Confederation of Indian Industry. Claessens, S., & Djankov, S. (1999). Ownership concentration and corporate performance in the Czech Republic. Journal of Comparative Economics, 27(3), 498–513. Clarke, D. C. (2003). Corporate governance in China: An overview. China Economic Review, 14(4), 494–507. Faccio, M., & Lasfer, M. (1999). Managerial Ownership, Board structure and firm value: The UK Evidence. Retrieved from http://papers.ssrn. com/sol3/papers.cfm?abstract_id=179008

Gordon, E. A., Henry, E., & Palia, D. (2004). Related party transactions and corporate governance. Advances in Financial Economics, 9, 1–27. Himmbelberg, C. P., Hubbard, R. G., & Palia, D. (1999). Understanding the determinants of managerial ownership and the link between ownership and performance. Journal of Financial Economics, 53, 353–384. Holderness, C. G. (2003). A survey of blockholders and corporate control. FRBNY. Economic Policy Review, 9(1), 51–64. Hu, Y., & Zhou, X. (2008). The performance effect of managerial ownership: Evidence from China. Journal of Banking & Finance, 32(10), 2099–2110. Klapper, L. F., & Love, I. (2004). Corporate governance, investor protection, and performance in emerging markets. Journal of Corporate Finance, 10(5), 703–728. OECD. (2006).Methodology for Assessing the Implementation of the OCED Principles on Corporate Governance, December, Available at http:// www.oecd.org/daf/corporate-affairs World Bank. (2005). India: Role of institutional investors in the corporate governance of their portfolio companies. Finance and Private Sector Development Unit, South Asia Region. Washington, D.C.: World Bank.

KEY TERMS AND DEFINITIONS Agency Theory: The agency theory represents the relationship between two parties the principal and the agent. The agents act on behalf of the principal as they have the decision making authority. In a company the shareholders are the principal and the directors or the managers are their agents. Agency conflicts arise due to inefficiency of information.

273

 Corporate Governance and Firm Performance

Global Financial Crisis: The financial crisis of 2007-08 is referred to as the global financial crisis and is considered to be the worst financial crisis since the great depression of 1930s by many economists. The immediate cause of the crisis was the bursting of United States housing bubble in 2005-06 resulting in an increase of subprime and adjustable rate mortgages. Hausman Test: It is a statistical hypothesis test which evaluates the significance of an estimator versus an alternative estimator. It can be used in panel data to differentiate between fixed effect and random effect. Multicollinearity: It is a statistical phenomenon in which two or more variables in a multiple regression model are highly correlated. The multicollineraty can be detected in many ways in the data. One of the suggested methods is detection of variance inflation factor for multicollinearity. Variance Inflation Factor provides an index that

274

measures how much variance of an estimated regression coefficient is increased because of collinearity. Ownership Concentration: Ownership concentration means the amount of stock held by individual investor and large block holders (investors holding at least 5% of equity ownership within the firm).Higher ownership concentration is associated with stronger monitoring power as the large investors are proactive in protecting their investments. In India the ownership is concentrated in the hands of Indian promoters. Panel Data Analysis: It is a statistical method which deals with data collected over time and cross-section for same firms or individuals. Panel data refers to multidimensional data frequently involving measurements over time. The main approaches of panel data analysis are independently pooled panels, random effects model and fixed effect model.

275

Chapter 14

Globalization, Governance, and Food Security: The Case of BRICS Sebak K. Jana Vidyasagar University, India Asim K. Karmakar Jadavpur University, India

ABSTRACT Food security is a major area of concern for the five nations that constitute BRICS. BRICS countries account for more than 40% of the world population and 25% of world GDP in PPP terms. Besides, these countries have a key role to play in the post-crisis global economy as producer of goods and services, receivers and exporters of capital, and/or consumer market on large potential. More importantly, these ones envisage ways to promote food security and food production in Third World countries by raising agricultural productivity and output via initiatives like the creation of basic agricultural information exchange system of these countries; enhancing investments in the food supply chain; developing a social safety net through conditional income transfer programmes for the poorest of the poor. In this context the present chapter examines the status of food security of BRICS economies in the context of globalization and governance and its implications thereof.

INTRODUCTION Food security has emerged as a serious concern for policymakers of the world over. Globally, food security is under serious threat, raising the very real fear that the Millennium Development Goals (MDGs) of halving the proportion of hungry people during 1990 – 2015 may not be met. Accordingly to the Global Hunger Index (GHI)

Report 2010, the number of undernourished people exceeded one billion in 2009. In the late nineties, and particularly since 2000, food security has become a standing item on the global agenda and the object of various intergovernmental processes (most notably a series of world food summits dealing with food security in 1996, 2002, 2008). Though food security is a national problem, it is now undisputedly accepted as an interna-

DOI: 10.4018/978-1-4666-8274-0.ch014

Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Globalization, Governance, and Food Security

tional responsibility. As a concept, food security has evolved from being traditionally defined in terms of food availability and price stability to more recent definitions that encompass economic access and nutritional balance. The 1996 World Food Summit (WFS) during Nov.13-17, at the Rome headquarters of the Food and Agriculture Organization (FAO) declared, “Food Security at the individual, household, regional, national and globally exists when all people, at all times, have physical and economic access to sufficient, safe and nutritious food to meet their dietary needs and food preferences for an active and healthy life.” The broadened understanding of what constituted food security led the agreement by the 2012 Committee for World Food Security that (Page 2013): “Food and nutrition security exists when all people at all times have physical, social and economic access to food, which is safe and consumed in sufficient quantity and quality to meet their dietary needs and food preferences, and is supported by an environment of adequate sanitation, health services and care, allowing for a healthy and active life.” From 1990 to 2000, relative stability in the global food supply resulted in a period of complacency and reduced investment and innovation in food industries compared to other sectors. The exceptional food price hikes in 2008-13 brought back to the forefront the understanding that effective markets and national-level policy decisions are not sufficient for preventing major imbalances among nations and among specific vulnerable population groups, and that uncoordinated short-term national policies can result in destabilizing global impacts on prices and access to food in other countries. Globalization has made a scope for increased cooperation among the BRICS (the acronym for Brazil, Russia, India, China, and South Africa invented earlier in 2001 including South Africa by the chief economist Goldman Sachs, with the claim that these countries would become the major players in a future world economy) to promote food security, which at present a serious concern for

276

policymakers, by raising agricultural productivity and output via initiatives including the creation of basic agricultural information exchange system of these countries; enhancing investments in the food supply chain; developing a social safety net through conditional income transfer programmes for the poorest of the poor; as well as undertaking measures to reduce the negative impact of climate change on food security, enhancing agricultural technology cooperation and innovation as well as through promotion of inter- trade and investment in agriculture. Also the BRICS countries could envisage ways to promote food security and food production in Third World counties. To make these efforts prudent, governance of globalization and food security system among these countries is urgently called for. BRICS countries appeared increasingly eager to engage on the global stage. Whatever had occurred in their past was over and done with. Globalization was happening and they wanted to be part of it. There were other unique economic factors which determined the BRICs status as countries to watch. India is witnessing demographic dividend. Russia had already been invited to join the G7 in 1997 as the West sought to encourage the country towards free markets and democracy following the collapse of communism. Brazil seemed an increasingly likely candidate because, like China during the Asian crisis, it had recently become a more thoughtful economic player. We have chosen these BRICS countries because the countries accounted for about 40% of the world population and about 25% of world GDP in PPP terms in 2010. Nay, the share of the BRICS in world merchandise exports has increased enormously. While the share of the emerging and developing economies (EDEs) in world merchandise exports has increased from 25.4 per cent in 2000 to 42.3 per cent in 2012, nearly 60 per cent of this increase is on account of the BRICS countries whose share increased from 7.6 per cent to 10.1 per cent. Within BRICS, the largest increase is in China’s share, followed by

 Globalization, Governance, and Food Security

Russia, India, and Brazil. This tectonic shift in trade shares in the 2000s and early 2010s is mainly on account of China’s trade which also witnessed the highest growth rate of 20.3 per cent and to a lesser extent the three BRICS countries - Russia, India, and Brazil. Besides, these Countries have a key role to play in the post-crisis global economy as producer of goods and services, receivers and exporters of capital, and/or consumer market on large potential. Given their large population, resurgent middle-class and huge share of land (nearly 30% of global share), and natural resources, the BRICS formed a significant part of the world economy. Further, the recent recovery of BRICS economies from the global economic tsunami points towards their robust macroeconomic fundamentals and the nature of recovery show the growing significance of the BRICS in the new global order. More importantly, the BRICS is a symbol of the shift in global economic power away from the developed G7 economies towards the developing world. In their first meeting in Moscow 2010, the Ministers of Agriculture and Agrarian Development of the BRICS countries laid the groundwork for an action plan (2012-2016) relating to agricultural cooperation with focus on the creation of an agricultural information base system; the development of a general strategy for ensuring access to food for the most vulnerable population; the reduction of the negative impact of climate change on food security and adaptation of agriculture to climate change; and enhancing agricultural technology cooperation and innovation (Page 2013). The 2013 Global Hunger Index (GHI), which reflects data from the period 2008–2012, shows that global hunger has improved since 1990, falling by one-third. Across regions and countries, GHI scores vary considerably. South Asia and Africa, south of the Sahara are home to the highest GHI scores. The 2013 GHI has been calculated for 120 countries for which data on the three component indicators are available and for which measuring hunger is considered most relevant. A country’s

Table 1. Global hunger index 1990

1995

2000

2005

2013

Brazil

8.7

7.6

6.4