Foreign Capital and Economic Growth in India: Time Series Estimation 9819922984, 9789819922987

Citation preview

Foreign Capital and Economic Growth in India Time Series Estimation m a h e n dr a pa l

Foreign Capital and Economic Growth in India

Mahendra Pal

Foreign Capital and Economic Growth in India Time Series Estimation

Mahendra Pal Department of Commerce Delhi School of Economics University of Delhi New Delhi, Delhi, India

ISBN 978-981-99-2298-7 ISBN 978-981-99-2299-4 (eBook) https://doi.org/10.1007/978-981-99-2299-4 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Palgrave Macmillan imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Dedicated to My Parents

Preface

After the introduction of New Economic Policy of 1991, India liberalized her economy in terms of finance, money and trade. Foreign capital in the form of FDI and FPI channels was invited in a massive scale to fill the two gaps mainly saving and investment and import and exports. Moreover, to meet the growing requirements of economic and social infrastructure foreign capital was required. This research work, presented in the book, is based on the research conducted under the UGC sponsored project. “Foreign Capital & Economic Growth: A Disaggregated approach Cointegration & VECM Estimations from India.” Before starting this project, a number of research presentations were made on: Foreign Capital and Economic Growth in Developing Countries—an Econometric Analysis notably at Swedish School of Economics, Helsinki, KLK International Conference, Delhi School of Economics, Annual conferences of Indian Economic Association at Mysore and Meenakshi University and long-term teaching and research on the topic Foreign Capital and Growth at Delhi School of Economics. Taking the advantage of feedback from the students and participants in the conferences, we decided to develop the major research study to take into account more theoretical and empirical work on the role of foreign capital in the growth process of an emerging and rapidly growing economy like India. Indian economy has been one of the largest recipients of Foreign Aid and has become a role model in terms of Aid

vii

viii

PREFACE

effectiveness and its productivity. Now, India has become the major destination in attracting foreign private capital, especially FDI, FPI and foreign remittances, however, not to replace Foreign Aid but to complement the inflow and productivity of FDI. During the research period, a number of papers based on the study were presented at Queens University of London, World Finance Conference, Venice, Italy, TIES Conferences at Central University of Rajasthan, IGDR Bombay, Patiala University and NIFT, New Delhi, IEA Conferences at Meenakshi and Udaipur Universities and the Department of Commerce, DSE within May 2013 to December 2015. I am deeply grateful to Prof. A. K. Singh, Dean and Head of the Department of Commerce, Delhi School of Economics, University of Delhi, and to Prof. K. V. Bhanumurty, Prof. J. P. Sharma and Prof. Kavita Sharma for their invaluable help and they allowed me to work with the excellent center of the Department of Commerce, Delhi School of Economics. I also gratefully acknowledge the insightful inputs I received from the students of M.Com. (Finance) for long time and the faculty members notably Prof, Y. P. Singh, Prof. Sri Ram Khanna, Prof. Sanjay K. Jain, Prof. Ajay Kumar Singh, Late Prof. Vanita Tripathi, Dr. Niti Bhashin, Dr. Abha Shukla, Dr. Sunaina Kanojia, Dr. Rinku Mahindru, Dr. Nidhi Kapoor, Ms. Deepali Malhotra, Ms. Silpi Narula, Ms. Hina Kashyap, Mr. Chetan Yadav, Ms. Rajni Chopra and Mr. Kamal Kant of the Department of Commerce. I gratefully acknowledge Prof. K. L. Krishna, Prof. V. N. Pandit and Prof. Pammi Dua of Delhi School of Economics for their always invaluable inputs and always good friends and guide. I am also grateful to Prof. Suresh Aggarwal who not only read summary of my study but also gave valuable comments to improve my study. Dr. Rajeev Singh, Professor, Delhi University, deserves special thanks and credit goes to him for giving this book a technical shape in terms of data generating process and technical graphs and diagrams and overall giving a good shape to the manuscript and without whose technical assistance this book would not have been possible and all deserves special thanks and gratitude. I am deeply thankful to the authorities of UGC for their prestigious Award UGC Emeritus Fellow on the project Foreign Capital and Economic Growth: A Disaggregated approach-cointegration & VECM Estimation from India and invaluable financial support. I am also grateful to the authorities of the University of Delhi for their invaluable help

PREFACE

ix

and giving official acceptance to undertake the research project in the Department of Commerce, Delhi School of Economics. The author is highly thankful to my discussants, notably Ghatak (London), Chatterjee (New Zealand) and Purrna Banerjee (IGDR), for their valuable comments and also comments from the number of noted economists such as Ramachandran (Pondicherry), Raghvander Jha (Australia), Abdou Saum (USA), Sushant Mallick (London) Narain Sinha (Botswana) Joao Paula Vieito (Portugal) and Biswajit Chatterjee (Calcutta). I am also greatly thankful to the authorities of Palgrave Macmillan: Ms. Surinder Kaur and Ms. Hemapriya Eswanth for giving their kind acceptance to consider this book for publication. Dr. Nupur Singh who helped me in the publication of my research paper in Springer publication deserves special thanks. It would not have been possible for me to prepare and publish this study without the support from my family members: wife Ms. Kusum Lata, M.A. (Economics) for giving me all types of help and acting as my care taker, Dr. Pratibha Singh, Delhi University, Dr. Sanjeev Singh, M.D., Dr. Supriya Singh, Master Harshit Singh, Dishita Singh and Riya Singh. In the end, I am deeply thankful to Dr. Lokesh Sharma, very dynamic and encouraging librarian and other members of the staff of Ratan Tata Library, Delhi School of Economics, University of Delhi, for providing me all the necessary facilities. The views expressed in the study are those of the author and do not necessarily represent those of the institution he represents. Finally, I acknowledge that I am solely responsible for any error, if any. New Delhi, India

Mahendra Pal

Contents

1

1

Introduction

2

Macrodeterminants of FDI in India: Cointegration and Causality

23

3

FDI-Growth Nexus in India: Cointegration and Causality

61

4

Foreign Aid-Growth Nexus in India: Cointegration and Causality

85

5

Foreign Capital-Growth Nexus in India: Cointegration and Causality

119

6

PCY, Foreign Aid and FDI: A Test of Complementarity

143

7

Summary and Conclusions

173

Index

181

xi

Abbreviations

ADF ADR ARCH ARDL ARIMA ASEAN CAC CAL CPIA DF-GLS DGP DTAA FCAC FCCB FDI FE FEMA FIIs FIPB GFCF HBS IBRD IDA IDB IFS IIP

Augmented Dickey-Fuller American Depository Receipt Autoregressive Conditional Heteroskedasticity Autoregressive Distributed Lag Autoregressive Integrated Moving Average Association of Southeast Asian Nations Capital Account Convertibility Capital Account Liberalization Country Policy and Institutional Assessment Dickey-Fuller Generalized Least Squares Data Generating Process Double Tax Avoidance Agreement Fuller Capital Account Convertibility Foreign Currency Convertible Bonds Foreign Direct Investment Foreign Exchange Foreign Exchange Management Act Foreign Institutional Investors Foreign Investment Promotion Board Gross Fixed Capital Formation Handbook of Statistics on Indian Economy International Bank for Reconstruction and Development International Development Association India Development Bonds International Financial Statistics Index of Industrial Production xiii

xiv

ABBREVIATIONS

IMF IRF LDCs NBER NRE(R) A NRIs ODA OECD OLS PBC PPP RBI REER RMSE SDRs SEBI SSA UDC VAR VDC VECM WDC WDI WDR WPI

International Monetary Fund Impulse Response Function Lower Developed Countries National Bureau of Economics Research Non-Resident External (Rupee) Accounts Non-Resident Indians Official Development Assistance Organization for Economic Co-operation and Development Ordinary Least Square People’s Bank of China Purchasing Power Parity Reserve Bank of India Real Effective Exchange Rate Root Mean Square Error Special Drawing Rights Securities and Exchange Board of India Sub Saharan Countries Underdeveloped Countries Vector Autoregressive Variance Decomposition Vector Error Correction Model World Development World Development Indicators World Development Report Wholesale Price Index

List of Figures

Fig. 2.1

Fig. 2.2 Fig. 2.3 Fig. 2.4

Fig. 2.5

Fig. 2.6

Fig. 2.7

Fig. 2.8 Fig. 2.9

Trends of net FDI inflow to India (1971–2013) (US million dollar) (Source Author’s own work based on Table 2.1) Net FDI as a percentage of GDP in India (1971–2013) (Source Author’s own work based on Table 2.1) Foreign investment as a percentage of GDP (1971–2013) (Source Author’s own work based on Table 2.1) Trends of net FDI, net portfolio and total investment (2001–2018) (Source Author’ own work based on the Data from HBS [RBI]) Trends of gross, reinvested and repatriation of FDI in India (2001–2018) (Source Author’ own work based on the Data from Hand Book of Statistics on Indian Economy, RBI) Trends of foreign investment/GDP ratio (%) in India (1971–2013) (Source Author’s own work based on Table 2.2) Trends of net FDI inflow in India in US $billion (1971–2013) (Source Author’s own work based on Table 2.2) GDP trends in India (US $billion) (1971–2013) (Source Author’s own work based on Table 2.2) Trends of Indian PCY (US $) (1971–2013) (Source Author’s own work based on Table 2.2)

28 29 29

31

31

35

36 39 39

xv

xvi

LIST OF FIGURES

Fig. 2.10 Fig. 2.11 Fig. 2.12

Fig. 2.13

Fig. 3.1

Fig. 3.2

Fig. 3.3

Fig. 3.4

Fig. 3.5

Fig. 3.6 Fig. 3.7 Fig. 4.1

Fig. 4.2 Fig. 4.3 Fig. 4.4

Fig. 4.5

Trends of real GDP growth rate in India (1971–2013) (Source Author’s own work based on Table 2.2) Trends of T.O. (X + M/GDP %) in India (1971–2013) (Source Author’s own work based on Table 2.2) Trends of financial deepening (M3/GDP %) in India (1971–2013) (Source Author’s own work based on Table 2.2) Trends of nominal exchange rate (Rs./US $) in India (1971–2013) (Source Author’s own work based on Table 2.2) Trends of growth rate and net FDI level (US $Billion) (1971–2013) (Source Author’s own work based on Table 2.1 and also HBS RBI and WDI [World Bank]) Plot of log FDI (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) Plot of dlog FDI (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) Plot of log GDP (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) Plot of dlog GDP (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) Plot of log differences of FDI and growth rate (Source Author’s own work) Impulse response function (IRF) (Source Author’s own estimation) Foreign Aid to India (1981–2018) US billion dollars (Source Author’s own work based on the data from HBS [RBI]) Plot of log Aid (Source Author’s own work) Plot of dlog Aid (Source Author’s own work) Plot of log Gr (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) Plot of dlog Gr (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work)

40 40

41

41

69

69

70

70

71 71 76

96 98 98

99

99

LIST OF FIGURES

Fig. 4.6

Fig. 4.7 Fig. 4.8 Fig. 5.1 Fig. 5.2 Fig. 5.3

Fig. 5.4

Fig. 5.5 Fig. 5.6 Fig. 5.7 Fig. 5.8 Fig. 6.1 Fig. 6.2 Fig. 6.3 Fig. 6.4

Plot of log differences of growth rate and Aid (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) (Color figure online) Response of log GDP and log ODA to Cholesky One S.D. innovations (Source Author’s own work) Aid—Growth Nexus Model—An analytical tour Trends of CAD/GDP (%) and NCF/GDP (%) (1971–2013) (Source Author’s own work) Trends of growth rate (Source Author’s own work) Plot of log growth rate (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) Plot of dlog GDP growth rate (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) Trends of net foreign capital flows (NFC)/GDP (as % of GDP) (Source Author’s own work) Plot of log NFC/GDP (%) Plot of dlog NFC/GDP (%) Plot of log differences of GDP and NFC (Source Author’s own work) (Color figure online) Trends of PCY, Aid, FDI, export (1971–2013) (Source Author’s own work) Structural break between Aid/GDP ratio and FDI/GDP ratio (Source Author’s own work) Response to Cholesky One S.D. Innovations (Model for PCY, Aid, FDI (Source Author’s own work) Response to Cholesky One S.D. Innovations (Model for PCY, Aid, FDI and Export) (Source Author’s own work)

xvii

100 106 110 126 127

127

128 128 129 129 131 153 154 160

163

List of Tables

Table 2.1 Table 2.2 Table 2.3 Table 2.4 Table 2.5 Table 2.6 Table 2.7 Table 2.8 Table Table Table Table

2.9 3.1 3.2 3.3

Table 3.4 Table 3.5 Table 3.6 Table 3.7

Trends of FDI and foreign investment in India (1971–2013) (US $million) Time-series data on Macrodeterminants of FDI in India (1971–2013) Results of Augmented Dicky Fuller (ADF) and Phillips-Perron (PP) unit root tests Results of Johansen Cointegration test (trace statistics) Results of Johansen Cointegration test (maximum Eigenvalue) Pairwise Granger causality tests Johansen cointegration: multivariate model Johansen cointegration unrestricted cointegration rank test (maximum eigenvalue) Granger causality tests ADF unit roots tests for stationary of variables Results of Phillips-Perron (PP) unit root test Results of Johansen cointegration test (trace statistics) for FDI and growth Results of Johansen cointegration test (maximum eigen statistics) for FDI and economic growth Pairwise Granger causality tests Results of vector error correction model for FDI and growth Variance decomposition of growth rate and FDI

27 37 44 45 45 46 49 49 50 72 72 73 73 73 74 77

xix

xx

LIST OF TABLES

Table 4.1 Table 4.2 Table 4.3 Table 4.4 Table 4.5 Table 4.6 Table 4.7 Table 4.8 Table 4.9 Table 4.10 Table 4.11 Table 5.1 Table 5.2 Table 5.3 Table 5.4 Table 5.5 Table 6.1 Table 6.2 Table 6.3 Table 6.4 Table 6.5 Table 6.6 Table 6.7 Table 6.8 Table 6.9 Table 6.10 Table 6.11 Table 6.12

Trends of Aid GDP ratio (%) and growth rate of India (1971–2013) Tests for stationary of the variables (1971–2013) Results of Phillips–Perron (PP) unit root test Results of Johansen cointegration test (trace statistics) for Aid and growth Results of Johansen cointegration test (maximum eigen-value) for Aid and growth Normalized cointegrating coefficients Granger causality results Results of Vector Error Correction Model for Aid and growth rate Variance decomposition of log GDP Variance decomposition of log Aid The range of grant element associated with various types of external source Time-series data for estimation of models of net foreign capital/GDP ratio and growth rate in India (1971–2013) Tests for stationary of the variables (1971–2013) Results of Phillips-Perron (PP) unit root Ttst Results of Johansen cointegration test (trace statistics) for growth rate and foreign capital Results of Vector Error Correction Model for foreign capital and growth Types of foreign capital available to India Composition of debt creating capital to non-debt creating capital in India Macroeconomic variables for model estimation Results of Augmented Dicky Fuller (ADF) and Phillips-Perron (PP) unit root test Results of Johansen cointegration test (trace statistics) for PCY, FDI and Aid Unrestricted cointegration rank test (maximum eigen value) Normalized co integrating coefficients (standard error in parentheses) Pairwise Granger causality tests Results of Vector Error Correction Model for PCY, Aid, FDI Variance decomposition of LogPCY Variance decomposition of LogAid Variance decomposition of LogFDI

98 100 101 101 102 102 102 104 105 105 109 125 131 132 132 134 149 149 152 156 156 157 157 157 158 160 161 161

LIST OF TABLES

Table 6.13 Table 6.14 Table 6.15 Table 7.1

LogPCY, LogFDI, LogAid, LogEXPORT Model 2 Pairwise Granger causality tests Result of Vector Error Correction Model for PCY, Aid, FDI and Export Summary of short- and long-term dynamics

xxi 161 162 164 177

CHAPTER 1

Introduction

Recently, some distinctions have emerged to conceptualize the various types of foreign capital. First distinction arises between official capital and private capital. Official capital includes Foreign Aid and bilateral and multilateral Aid. Private capital includes FDI, portfolio, commercial borrowing, remittances and NRI. Second distinction has also emerged between debt creating and non-debt creating foreign capital. Debt creating capital includes Foreign Aid, bilateral, multilateral, commercial borrowing and NRI, while non-debt creating capital includes FDI and portfolio capital. Third type of distinction is also possible in terms of longterm and short-term foreign capital. Long-term capital includes bilateral Aid channel through the Consortium Technique, multilateral Aid channel through the World Bank (IBRD and IDA) IFC and ADB and FDI while short-term capital includes portfolio, commercial borrowing, NRIs and short-term debt probably which cannot be rolled back. The decade of 1990s experienced a radical shift in the pattern of external capital flows from debt creating to non-debt creating sources. In the development literature, the effectiveness of foreign capital inflows on growth process has been a topic of an intense, controversial and unending debate in the last few decades. This has led to a substantial body of empirical and sophisticated research by the development economists.1

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. Pal, Foreign Capital and Economic Growth in India, https://doi.org/10.1007/978-981-99-2299-4_1

1

2

M. PAL

In the rapidly growing economies, the questions of relative significance of the various types of foreign capital in the economic growth of developing countries have figured. The new pattern of external development finance raises a lot of related issues for developing and emerging countries. The most important question is whether a recent explosion in the magnitude of FDI is benefitting the host country and further what are the major and potential macrodeterminants necessary to attract more FDI. Second, whether Foreign Portfolio Investment (FPI) is sustainable form of foreign capital? Third, whether Foreign Aid/ODA, with more than 25% grant element (ODA Type) or concessional Foreign Aid with grant element of more than 80% (IDA Type), is effective, adequate and how to raise this resource and improve its quality in the recipient nation notably India. Fourth, whether external commercial borrowing and NRI/banking capital prove to be reliable source of external finance? Fifth, over the last decade the magnitude of remittances have alarmed the major recipients in terms of its magnitude being received by the recipient countries notably India and its resultant impact on the effective demand in the host countries. At present, the topic of foreign capital inflows which includes Foreign Aid with different types of concessionalities and conditionalities, FDI, portfolio capital, external commercial borrowing, NRIs and remittances has become a broader issue. Different types of capital flows have different impact on the economy. These capital flows observe complete imperfect market. For example, Bosworth and Collins (1999) investigated the effect of financial flows on investment by types of financial flows; however, they do not consider official inflows in their study. The present study tries to fill this gap and takes into account the separate role of FDI, ODA, trade openness and net foreign capital inflow to study the separate effect of different capital inflows on the growth process and also to examine the relative significance of FDI, Aid and export promotion.

1.1

Magnitude of Global Foreign Capital

If we look at the data on the different channels of foreign capital, we find that growth of FDI inflow increased in an alarming rate in the developing countries during the last two and half decades. It was only US $54 Billion in 1980 which increased to US $2.1 Trillion in 2007. However, since the year of 2008, FDI inflow remained in the range of US 1.8 Trillion annually. Recently, the magnitude of FDI inflows has shown declining

1

INTRODUCTION

3

trends. For example, it declined to US $1.41 Trillion in 2018 and further declined to US $1.39 Trillion in the recent year of 2019.2 While, on the other hand ODA/Foreign Aid/Aid has increased from US $7.6 Billion in 1971 to US $41 Billion in 1987 and it increased to US $107 Billion in 2005 and since than ODA/Aid has increased to US $166 Billion in 2018.3 In other words, during the period of 2005 to 2018, it remained on an average US $140 Billion.4 Another feature of foreign capital inflows has emerged from the remittances flows. These capital flows have shown an alarming trends which have increased in an exponential form to the extent of US $554 Billion in 2018, three times more than ODA which is around US $166 Billion a year. However, Foreign Aid, a conventional, traditional and major source of foreign exchange to poor and emerging nations, notably sub-Saharan nations, remains even less than the volume of FDI, FPI and foreign remittances. This type of pattern of foreign capital has become a new development paradigm in the rapidly changing world economy. At present, remittances have become significant sources of cross-border financing. However, remittances are of different nature than the capital flows discussed above. Remittances are private flows related to personal transmigrants to friends and families that are recorded in the income balance of the current account. Remittances flow directly to households, thereby having an effective role in reducing poverty and financing imports, but with limited direct effect on investments at the microeconomic level. Foreign remittances have emerged as a stable source of foreign exchange inflows for emerging nations. Foreign remittance corresponds to a capital which is similar to that, analyzed by the Dutch Disease Theory. The main concern of this theory is to access the effects of capital inflow on the real exchange rate and country’s international competitiveness.5

1.2

Foreign Capital to India: An Overview

Indian economy adopted a model of import-substitution during her initial planning period. The economists alleged this economic model which contributed a widespread economic inefficiency, poor performance and implementation of the development projects in infrastructure sector during that period. Before 1991, Indian economy was financially repressed economy. The first phase of financial sector reforms was framed by the recommendations of the Committee on the Financial System (GOI 1991).6

4

M. PAL

The New Economic Policy of 1991 dismantled the existing administered interest rate mechanism and removed other government controls on finance, trade, foreign capital and industrial expansion. Following these major economic reforms with a main focus on the development of economic and social infrastructure has increased at a rapid pace with massive increase in per capita income. India has been passing through the process of financial liberalization, where the objective is to accelerate the pace of economic development in an environment of reasonable price stability. Now, India is one of the G20 major economies and a member of BRICS.7 India’s recent performance with a third of the world’s population and nearly 2/3rd of the world’s poor, the sustained high growth of the country over the last two decade is an unprecedented event in India. Now, India has managed to sustain such high growth rate which clearly tells an important lesson to both development theoreticians and practitioners such as economists, researchers and policy makers. Economic growth rate which was 10.3% in 2010 has come down; however, it has been around 7.5% on an average since then and has the potential to record around 8% as per forecast by the international agencies such as IMF and World Bank. The recent global financial crisis of 2008 has made foreign capital and its relationship with economic growth, a topic of great academic and empirical interest. During the last two and half decades, the role of foreign capital in the process of economic growth has increased at an alarming rate in India. India has always been a favored destination of foreign capital before and after 1991. Till mid-1980s, Foreign Aid played a strategic role in removing financial and physical constraints, removing poverty and increasing economic development in India at macro- and micro-level. During late 1980s, commercial borrowing, NRIs money and shortterm debt capital and hard capital (IBRD type) tried to compensate the shortage of Foreign Aid. New Economic Policy of 1991 shifted the foreign capital regime from debt to non-debt creating capital in which FDI and portfolio capital have assumed a significant role.8 Net Foreign capital (NFC/GDP) ratio increased from 0.9% in 1971 to 2.2% in 1991 and to 8.6% of GDP in 2007–2008. However, it declined to 0.5% in 2008–2009 and again rose to 6.1% in 2013. Foreign investment/GDP ratio ranged from 0.1% in 1971 to 5% in 2007–2008 and 2.7% in 2013. In absolute value, FDI increased from US $50 million in 1971 to US $1.1 Billion in 1994,

1

INTRODUCTION

5

which increased to US $47 Billion in 2008. Further, it declined to US $29 Billion in 2013. Cumulative figure of FDI inflow (stock) increased from US $93 million in the year of 1971 to around US $282 Billion in 2013. FDI/GDP ratio increased from 0.1% in 1992 to 3.8% in 2008 and 1.8% in 2013. India ranked 2nd in attracting FDI. So far net inflow of Foreign Aid is concerned during the period of 15 years from 1980 to 1995 net inflow of Aid averaged US $0.5 Billion. During the last decade, i.e. 2006–2013, net Aid inflow has been around US $3 Billion annually, on an average ranging from US $1.5 Billion in 2009–2010 to US $4.8 Billion in 2010–2011. Aid/GDP ratio declined from 1.5% in 1971 to 0.13% in 2013. In terms of borrowing from Multilateral Development Banks (MDBs), India has been the 3rd largest borrower from the IBRD (hard loan), while the top and largest recipient from the IDA (soft loan).9 India has received US $104 Billion from the World Bank (US $54 Billion from the IBRD) and (US $50 Billion from the IDA) for the period from fiscal year of 1948 to December 31, 2015. However, India still has been receiving US $5 Billion annually on an average from the World Bank (IBRD and IDA).10 If we look at the increase in external commercial borrowing (ECB), its volume has increased in India from US $1.5 Billion to US $2 Billion on an average during the period of 13 years (i.e. from 1991 to 2004) while during the period from 2005 to 2014, ECB averaged about US $10 Billion annually. So far NRI money is concerned, it remained in the range of US $2 Billion to US $3 annually in the period from 1991 to 2003, but in the recent past, NRI money has increased from US $12 Billion in 2012 to US $39 Billion in 2014. For detailed analysis on the theory of NRI money, see Appendix 1.1. During the recent past, another major and unconventional source of foreign capital has become available to India in the form of foreign remittances which have increased from US $2.1 Billion in 1991 to US $37.2 Billion in 2008, and again, this source has increased to US $70 Billion which was about 4% of Indian GDP and it also increased to US $83 Billion in 2019. During the last decade, India has been receiving around US $60 Billion annually on an average. Remittances in India have emerged as a stable source of foreign exchange inflows for the country. India has been the highest remittance receiving country in the world, followed by China and has helped in financing almost all the entire trade deficit. In this way, India stands the largest recipient of foreign remittances.

6

M. PAL

If we look at the data relating to debt flows which ranged from 2.2% of GDP in 1990–2001 to 3.3% of GDP in 2007–2008 and on an average remained around 2%.of GDP, debt creating foreign capital declined constantly till the year of 2003–2004 and again started to increase. In the same way, non-debt capital continued to increase till the year of 2003–2004 and after that year started to decline and then again started to increase. From this fluctuating trends between debt and nondebt creating foreign capital, one can conclude that both types of foreign capital do not reveal the substitution but complementarity. See Chapter 6 of this book for comprehensive analysis on the topic of debt to non-debt creating capital. The study reviews the major studies on the different channels of foreign capital carried out by Agarwal (1980), Bacha (1990), Chakraborty and Basu (2002), Corsepius et al. (1989), Balasubramanyam et al. (1999), De Mello (1997, 1999) Chakraborty and Nannenkamp (2008), Dunning (1977), Griffin (1970), Griffin and Enos (1970), Harrod-Domar (1939, 1946), Chenery and Strout (1966), Papanek (1972, 1973), Dowling and Hiemenz (1983), Burnside and Dollar (2000), Mosley (1980, 1987), Taylor (1990), Dua and Rashid (1998), Prasad, et al (2007), Johansen and Juselius (1990) and Glauco and Khine (2009).

1.3

Motivations of the Study

During the decade of 1990s, capital flows were mainly in the form of FDI and portfolio investment in addition to the existing flows of ODA. Typically, many existing studies on the capital flows tend to concentrate on either private or official capital inflows. Both official and private capital flows are separately specified in the empirical models. Next, FDI and Aid are also specified separately in the empirical models. The central issue is to study the effect of various types of capital flows on per capita GDP growth and GDP growth rate. Earlier studies have focused on FDIGrowth nexus along with other variables. This study focuses mainly on direct relationship between FDI and Growth and their causal direction. During the last two decades, scholars have applied their mind in testing empirically the macrodeterminants of FDI mainly in developing and emerging economies. They have studied mainly market size hypothesis which includes GDP level, growth rate and PCY. In addition to market size other determinants such as trade openness (X + M/GDP), exchange

1

INTRODUCTION

7

rate depreciation/appreciation, infrastructural facilities and labor productivity have also been as major determinants. This study includes the variable of financial deepening (M3/GDP = C + DD + TD/GDP) ratio as an important determinant of FDI. This study also introduces the role of financial development specially Bank Intermediation in effectiveness of the growth effect of the foreign capital. Earlier, the role of financial markets was neglected in the economic development (see, Shumpeter 1911, 34) but now the role of financial development has become the essential prerequisite to make the effective use of foreign capital and to reduce the volatility of foreign inflows especially short-term and portfolio capital inflows. The sound financial system provides the financial stability in the country. For comprehensive survey on the issue of financial system and growth, see Pal (2013, 2014a, b).

1.4

Objectives of the Study

Main objective of this study is to investigate the positive relationship and causal direction between different channels of foreign capital such as FDI, Aid, net capital inflows, export promotion and foreign investment which includes both FDI and portfolio capital on economic growth in India in a disaggregated model. The study fills the research gap in terms of longer period, methodology and disaggregation of foreign capital. Analytically and conceptually, this study improves upon. Against the backdrop of the arguments advanced above, the present study is an attempt to trace the role of foreign capital in Indian economy. The main objectives of the study are as follows: First, the study traces the relationship between foreign capital and economic growth. Second, to study the causal direction whether foreign capital causes economic growth in India. Third, to study the major determinants of FDI in India.

1.5

Methodology and Selected Variables

For the purpose of models estimation, we have applied modern time-series analysis which includes unit root testing, cointegration technique developed by Johansen and Juselius (1990). The study is technique driven and is based on the terms such as unit root testing with the help of ADF and Phillips-Perron methodology, Granger causality (1988). For testing long-run relationship among the variables, we have used Johansen and

8

M. PAL

Juselius (1990) cointegration technique, which is based on VAR methodology. Then, trace statistic and maximum eigenvalue have been checked, and then, Vector Error Correction Model (VECM) model has also been applied to trace the short- and long-term relationship dynamics. Further Impulse Response Function (IRF) and Cholesky Variance Decomposition (VDC) have been applied. For detailed discussion on the theory of modern time series, see Banerjee et al. (1993), Johansen (1991, 95), and Johansen and Juselius (1990). Further, for detailed analysis on methodology, see Appendix 1.3. Selected variables have been used for empirical estimation: GDP growth rate, PCY, net foreign capital (NFC), FDI, portfolio investment, NRI, trade openness (X + M)/GDP ratio), financial deepening (M3/GDP ratio), X/GDP ratio, Aid, exchange rate, etc. Annual data have been used and collected from the reports of the RBI, World Bank and IMF for the period of 42 years (i.e. 1971–2013). For explanation of selected variables, see Appendix 1.2.

1.6

Potential Contribution of the Study

The role of foreign capital in the process of economic development has been recognized by distinguished economists like Rosentein–Rodan (1961), Griffin (1970), Griffin and Enos (1970), Papanek (1972, 73), Gupta (1975), Mosley (1980), Bhagwati (1998), Chenery and Strout (1966), Bacha (1990), Taylor (1990), Dua and Sen (2013) and Prasad et al. (2007). Further, a critical role has been played by foreign capital in economic development, yet a distinction needs to be made between potential contributions of foreign capital as opposed to the actual contribution. Under sound financial system, foreign capital can raise the productivity of the nation. Increased financial saving is intermediated by the banking sector toward real investment with beneficial effects for the economy through operational and allocative efficiency. Financial constraints of the firms are relaxed at the micro- and macro-level. It has positive impact on economic stabilization through different channels; that is, it reduces inflation, reduces external disequilibrium through reduction in current account deficit and tries to save the economy from global financial crisis. Hence, under sound financial system, foreign capital can increase its productivity and can have more potential in the growth process in Indian economy.

1

1.7

INTRODUCTION

9

Limitations of the Study

There are certain limitations of the study. The study focuses mainly on the determinants of FDI in India, FDI-Growth nexus, Aid-Growth nexus, net foreign capital-growth nexus, relative contributions of private foreign capital and official foreign capital or debt creating and non-debt creating foreign capital. This study does not deal with most debated, highly controversial and researched issue such as the relationship between foreign capital and domestic saving. Whether foreign capital leads to low saving or does low saving attracts more foreign capital in the host country? This study does not also deal with technology transfer, volatility of capital inflows, management of capital inflows in terms of sterilization policy and exchange rate fluctuations in terms of appreciation and depreciation of Indian currency. For detailed analysis for management of capital inflows, see Dua and Sen (2013), Dua and Ranjan (2010) and Kohli (2001, 2003, 2009).

1.8

Topics for Future Research

During the last two decades, the role of FDI and its determinants has been theoretically and empirically explored, debated and tested. Second emphasis has been given on FDI-Growth nexus in many emerging and developed economies. They need to be reviewed again in terms of their structural break. Dummy variable can be used after the introduction of New Economic Policy of 1991 because this year started a new era of development paradigm in the Indian economy. Moreover, in addition to testing annual time series, a quarterly data can be used for empirical estimation. However, further exploration of this topic is recommended which takes into account the relative contribution of various types of foreign capital inflows and growth effect separately. Chapter 2 attempts to test empirically the potential determinants of FDI in India with the help of new time-series methodology. This chapter takes into account testing empirically two models. Model 1 includes seven variables such as FDI, trade openness, financial deepening, GDP, growth rate, PCY and nominal exchange rate. After confirming the order of integration, we find two cointegrating equations and rejects null hypothesis of no cointegration and shows long-run relationship among variables. Model 2 includes only four variables such as FI, GDP growth rate, financial deepening and trade openness. We find two cointegrating equations in

10

M. PAL

this model. Trace statistic and maximum eigenvalues are more than their critical value at low probability value. Then, we find pairwise Granger causality in the number of variables and find the desired results. GDP, growth rate, financial deepening and trade openness have been explored as potential determinants to attract FDI and foreign investment both. More emphasis should be given on increasing the level of four variables as pointed out above. Chapter 3 attempts to test empirically the long-run relationship between growth rate and FDI in India and their causal direction with the help of new time-series methodology for the period of (1971– 2013). After testing the order of integration for both the variables with the help of ADF and Phillips-Perron test, we find both the variables to be stationery after first differencing. After confirming the order of integration, we use Johansen cointegration test to check the long-run relationship among the variables. Our results confirm the existence of positive and long-run relationship. Trace test and maximum eigenvalue both indicate one cointegrating equation at the 0.05 level with the assumption of linear deterministic trend. Granger causality also confirms unidirectional causality running from FDI to growth in India. Our ECT term in VECM model shows minus sign and its value is equal to -0.41 which demonstrates that 41% disequilibrium is corrected in one year. Results are also reconfirmed with the help of JRF and VDC. Our findings are mainly consistent with the findings of other major studies on FDI-Growth nexus and causal direction carried out mainly by De Mello (1997), Huang (2004), and Rati and Zhang (2002). Chapter 4 attempts to test empirically the positive relationship between Foreign Aid and Economic Growth in India. The chapter improves upon earlier work on Foreign Aid-Growth nexus, because it involves Johansen Cointegration technique of 1991 to trace the long-run relationship between Foreign Aid and economic growth in India. This chapter contributes also a detailed survey of literature especially on Indian economy. Our trace statistic and maximum eigenvalue results confirm the positive and long-run relationship between Foreign Aid and Economic Growth in India. Normalized function shows that 1% rise in Aid/GDP ratio causes about 0.36% growth rate to increase in India. In VECM upper panel, elasticity coefficient also resembles the normalized results. ECT term value is equal to −0.31 which shows that during one year period, the level of disequilibrium is corrected by 31%. Granger causality results also confirm the causal direction which runs from Aid to Growth in

1

INTRODUCTION

11

India at one lag and two lags. Impulse response function (IRF) and variance decomposition (VDC) results also support our findings. It appears that Foreign Aid has made positive contribution in the Indian economy. Result of this model remains unconventional; however, these findings should not be surprising in light of recent research on the high effectiveness of Foreign Aid. Trends between growth rate and Aid/GDP ratio are in the opposite direction, but positive and long-run relationship is established. Positive results between these two variables confirm the Burnside and Dollar (2000) hypothesis in India. The much debated hypothesis of Aid effectiveness takes in to account the good monetary and fiscal policy. India has achieved good rate of growth with the help of low level of Aid/ GDP ratio. India stands good example of this hypothesis testing. Chapter 5 traces the relationship between foreign capital and growth rate in India. Foreign capital includes both official and private capitals. Foreign capital stands for Net Capital Inflow/GDP ratio. Both the variables net capital/GDP ratio and growth rate in India are integrated at the first order (I). We find two cointegrating vectors between net foreign capital/GDP ratio and growth rate which show a long-run, positive and significant relationship. However, only trace value is significant at 5% level, and maximum eigenvalue is not significant. From the VECM upper panel, we find that 1% rise in foreign capital causes 0.30% rise in growth rate. Our ECT term also shows the minus sign expected from the theory; its value is around −0.99% which shows that model corrects 99% disequilibrium in one year period and shows high speed of adjustment. Results are quite satisfactory with expected signs and significance of the coefficients. Foreign capital is found to have a positive significant impact on the growth process of the Indian economy. The results approve the foreign capital-led growth hypothesis. Findings are consistent with the results of Abdelhafidh (2013), Rahman and Shahbaz (2013), and Ranjan and Kumar (2012). Chapter 6 examines the relative significance of debt creating (official) and non-debt creating (private) capital in India and also tests two empirical models. Model 6.1 incorporates three variables such as PCY, FDI and Aid. After conforming the order of integration, model confirms one cointegrating vector and shows positive and long-run relationship 1% increase in Aid causes. 1.1% rise in PCY, while 1% increase in FDI causes only 0.04% rise in PCY. Comparatively Aid coefficient shows better performance than FDI. ECT value is in the minus sign; however, its value

12

M. PAL

is around 0.08 which shows poor adjustment in correcting disequilibrium in one year. We extend Model 6.1 by incorporating export variable to capture the effect of export variable on the growth process. In this model, one cointegrating vector is also found which tells long-run relationship. However, in this model, FDI shows better impact on the PCY than Aid variable. It shows that export variable has good impact on the FDI. ECT term in this model is also in minus terms and its value is around −0.17 which shows low speed of adjustment and only 17% disequilibrium is corrected in one year. Granger causality results also support desired directions. Supremacy of private capital over official capital is not established during the study period. In India, private capital and official capital remain complementary not as substitute. These four macrovariables have been reinforcing each other to increase the economic growth process in India. These findings are consistent with the results of Burnside and Dollar (2000). Chapter 7 presents the summary of main findings. The major objective of this chapter is to summarize the main objectives, methodology, discussion, interpretation, core findings, conclusions and suggestions. Study is to examine the long-run relationship between foreign capital and growth in India. After an introductory chapter, Chapter 2 provides empirical estimation of major determinants of FDI in India with an emphasis on increasing the level of financial deepening, trade openness, GDP and growth rate. Chapter 3 examines the positive and long-run relationship of FDI-Growth nexus, with a clear causal direction from FDI to Growth, however with weak coefficient; Chapter 4 examines Aid-Growth nexus with positive and long-run relationship with a clear causal direction from Aid to growth with a strong coefficient. We find most robust findings of this model; Chapter 5 examines the growth effect of net foreign capital inflow on growth. Results demonstrate positive and long-run relationship, however, with no causal direction between the two variables. Chapter 6 examines the relative significance of Aid (debt) and FDI (nondebt) foreign capital, and for this, two models are estimated. Model 6.1 reveals that Aid is more productive than FDI, while model 6.2 which includes export variable shows FDI more productive than Aid. Superiority of FDI over Aid is not established in India; hence, two variables remain complementary to each other.

1

INTRODUCTION

13

Appendix 1.1: NRIs Money: Some Underlying Theory The underlying theory of NRI is based on differential rate of interest (i.e. difference in interest rates on deposits in the commercial banks in two different countries). For example, if in the USA, deposit rate in the commercial banks is equal to 2% while in India the deposit rate is equal to 10%, now in this case in both the countries interest rate difference is equal to 8%. In this case, capital flight-in takes place in India, because NRIs want to take the advantage of 8% interest on their deposits in Indian commercial banks, less than 1% exchange rate risk so that net gain is equal to 7%. Banking deposits in the commercial banks in the USA may be diverted in the Indian commercial banks. But if the deposit interest rate in the commercial banks is high in the USA, then capital flight-out will take place from India. Not only this, a country’s credit worthiness and business confidence in the country are also important. In addition, this money can be deposited either in Indian rupee or in US dollar terms, but repayment is done only in US dollar terms and a country concerned has to return the entire money in dollar terms only within a limited period of time, especially when a country faces economic and financial crisis. It is also generally available when the country is moving in economically and financially upward. In other words, it is always “Procyclical.” But it is very important to note that when the concerned country faces economic crisis NRI money may go back within short period of time in US dollars terms only; hence, NRIs money further accelerates the economic crisis. This type of capital remains unfaithful, reversible, as it comes in, it also goes out in the same way; it cannot be a reliable source of external finance. Moreover, NRI money cannot be used for economic and social infrastructure facilities such as railways, electricity generation and distribution, telecommunications, education, water, sanitation and health. NRI money generally increases the level of foreign exchange reserves, which provides business confidence in the country. Further, this is like a Loan Push Theory. In 1973, oil prices increased from US $5.12 per barrel in October 1973 to US $30 per barrel in September 1980, and further, oil prices increased to US $34 per barrel in October 1981. In this manner, Oil Producing and Exporting Countries (OPEC) such as Saudi Arabia, Kuwait and UAE collected large amount of Petro Dollars, but at the same time OPEC did not have any advanced banking system; hence, they deposited their collected Petro Dollars with

14

M. PAL

the European Banks and because of that European banks were flooded with Petro Dollars. These banks adopted a loan push theory to remove the excess liquidity of funds lying with the Europeans banks. Latin American countries, notably Mexico, Brazil and Argentina, borrowed this money as short-term loans, but after some time they were unable to repay these short-term loans and denied to repay the amount, and thus, entire world economy faced severe debt crisis of 1980s, and in this way, this decade was called as Lost Decade. For further detail on loan push theory and MBA external debt crisis, see Pal (1989). India faced this problem in 1989 when NRIs demanded their money back. In early 1980s, massive capital inflow took place in India. India had 20% of total net capital inflow as NRI money in early 1980s, and in 1985, it increased to 60%, but in 1989 when country was heading toward had economic crisis it declined to 3% only. In this period, NRI money was dried up and NRI demanded their money back. Hence, NRIs were mainly responsible for accelerating India’s economic crisis. But India being an emerging country now the NRI money has come back again in India after India got stabilized its economy under the IMF SAP program of 1991. See Appendix 2.1 in Chapter 2.

Appendix 1.2: Source of Data Depending on the studies mentioned above, we analyze the following variables spelled out in the literature. Data used in this study are published, unpublished and self-generated data. Published data are available from various publications of the Reserve Bank of India (RBI), World Development Indicators (World Bank), International Financial Statistics (IFS), CD ROM (IMF), Handbook of Statistics on Indian Economy (RBI), RBI Bulletins, Reports on Currency and Finance (RBI) and Economic Survey and its various issues, and Ministry of Finance (Government of India), Statistical Outline of India, 2002–2003, Tata Services Ltd. Mumbai. The study broadly covers the period of 42 years (1971– 2013). This period of study was selected because many countries like India started liberalization process of their economies and financial system during this period. Further, India started her financial sector reform in 1991; however, it was started in 1985, but got momentum after New Economic Policy of 1991. During this period, financial deepening, i.e. M3 /GDP ratio, private corporate saving, GDP growth rate, PCY, quasi

1

INTRODUCTION

15

money/GDP ratio, trade openness (X + M/GDP) all the variables have shown a rapid rising trend.

Appendix 1.3: Research Methodology for Estimation For the purpose of models estimation, we have applied modern timeseries analysis which includes unit root testing with the help of ADF and Phillips-Perron methodology, Granger causality (1988). For testing long-run relationship among the variables, we have used Johansen and Juselius’s (1990) cointegration technique, which is based on VAR methodology. Then, trace statistic and maximum eigenvalue have been checked, and then, Vector Error Correction Model (VECM) has also been applied to trace the short- and long-term relationship dynamics. Further Impulse Response Function (IRF) and Cholesky Variance Decomposition (VDC) have been applied. For detailed discussion on the theory and application of modern time-series analysis, see Banerjee et al. (1993), Johansen and Juselius (1990), Dua and Sen (2013), Dua and Garg (2013, 2015), Dua and Ranjan (2012), Dua and Rashid (1998), Pandit B.L. (2015), Pandit B.L. et al. (2006), Johansen S. (1988), Dematriades and Hussein (1996), Wadud Md. A. (2000), Giri and Kamaiah (2006), Pethe and Karnik (2000), Vadlamannati C. K. (2008), Biswas J. (2008), Thornton J. (1996), Verma and Arora (2009), Kaur M. (2015), Jana S. S. et al. (2020), Bathla S. (2008), and Kurihara Y. (2015).

Notes 1. For a comprehensive discussion on this debate, see Bacha (1990). 2. The unexpected growth of FDI inflows during the last two decades, i.e. in 1990s and 2000s, was due to economic liberalization policy adopted by the emerging nations and also due to the recovery of the Latin American economies from their severe external debt crisis of early 1980s. 3. According to UN target, the developed countries should devote 0.7% of their Gross National Income (GNI) in the form of Official Development Assistance (ODA) to Aid recipient countries which were underdeveloped now emerging nations. However, this issue has become a controversial topic nowadays because certain countries which were Aid recipient countries for long time have been trying to pose themselves as Aid donor nations notably China and India. In this way, a threshold of PCY level has become a redundant target.

16

M. PAL

4. ODA, Foreign Aid, Aid and external assistance are interchangeably used in this study. 5. The term Dutch Disease was coined by The Economist magazine in 1977 when the publication analyzed an economic crisis which occurred in Netherlands after the discovery of vast natural gas deposits in the North Sea in 1959. Dutch disease is a concept that describes an economic phenomenon. 6. Nowadays framing effective financial policy has emerged as one of the important development challenges of the new financial century of 2000s in India. The administered interest rate policy before New Economic Policy of 1991 adversely affected the operational and allocative efficiency of the financial system. This system resulted in high cost of financial transactions and small expansion of financial services. Ultimately, financial and banking industry faced low profitability, assets quality deterioration and erosion in the capital base (i.e. Capital Adequacy Ratio, which is also called Capital to Risk Asset Ratio (CRAR)) of the banking industry. See Rangarajan (1998). 7. India is the only South Asian country representing G20 Finance Ministers Forum established in 1999. India holds annual conference to deliberate some important, strategic and contemporary issues at this annual meet. Major issues include climate change, financial and monetary sector reforms, fiscal, growth rate and reforms in International Financial Institutions (IFIs) such as IMF and World Bank Group which consists of IBRD, IFC, IDA and MIGA in terms of increasing her voting rights and quota shares as per the economic strength of India. 8. In 1991, government shifted its policies from debt creating capital to non-debt creating capital. Four points may be pointed out for shifting this policy: First, external debt in terms of magnitude increased in large amount. Debt service ratio (DSR) also increased at an alarming rate. Second, in the late 1980s, the composition of Foreign Aid was changed, hard component of Aid (IBRD type loan) increased and soft component of Aid (IDA type loan) declined which ultimately resulted in heavy debt burden in the late 1980s and also served as one of the important factors in accelerating severe economic crisis of 1990s. Third, due to China’s policies of trade openness, financial liberalization and inviting private foreign capital. Fourth, due to success of East Asian Tiger countries, notably Malaysia, Thailand, Philippines, South Korea, etc. For detailed analysis of the economic crisis episode in India, see Pal (1989, 2015). 9. Foreign capital markets in India and elsewhere are imperfect and segmented where substitution does not take place. India still needs all types of foreign capital because India is a poor country in terms of economic and social infrastructural facilities and sheltering a high level of poverty. India still needs Foreign Aid such as ODA, IBRD and IDA

1

INTRODUCTION

17

Aid. The recent record of Foreign Aid to India shows that US $4 Billion to US $8 Billion annually is being utilized in terms of economic and social overhead or physical infrastructure. In the fiscal year of 2010, World Bank provided US $9 Billion to India. We can say that India is still using huge amount of Foreign Aid, commercial barrowing and NRI money in addition to FDI and FPI. 10. From the Appendix 4.1 in Chapter 4, we gather information about trends of grant element given to India by the donor nations such as US, UK, Japan, USSR and East European countries and Multilateral Development Banks (MDBs) such as IBRD, IDA and ADB. These donor nations and institutions have provided about 25% grant element to India during the period of last six decades, i.e. 1950–2018. During this period, West Germany and Japan‘s share remained very low which was around 10% on an average, while IBRD (5%) and IDA (74%) maintained their traditional standard. However, in the recent past, Japan has increased her grant element to the extent of 47%, and thus, Japan has become the second largest nation of concessional Foreign Aid giver to India after IDA. For comprehensive work on the grant element theory and practice in India, see Sharma (1973) and Pal (1985).

References Agarwal, J.P. 1980. Determinants of foreign direct investment: A survey. Welwirtschaftliches Archiv 116 (4): 739–773. Ahluwalia, M.S. 2002. Economic reforms in India since 1991: Has gradualism worked? Journal of Economic Perspectives, American Economic Association 16 (3): 67–88. Bacha, E.L. 1990. A three gap model of foreign transfers and GDP growth rate in developing countries. Journal of Development Economics 32 (2): 279–296. Balasubramanyam, V.N., et al. 1999. Foreign direct investment as an engine of growth. Journal of International Trade and Economics 8 (1): 27–40. Balassa, A.B. 1982. The theory of economic integration. Westport, CT: Greenwood Press. Banerjee, A., et al. 1993. Co-integration, error-correction, and the econometric analysis of non-stationarity, advanced text in econometrics. Oxford: Oxford University Press. Bathla, S. 2008. Agriculture reforms and market integration: A spatial analysis of food and non-food commodities. Journal of Social and Economic Development 10 (2): 196–221. Bhagwati, J. 1998. The design of Indian development, the economic reforms and development. In Essay for Man Mohan Singh, ed. I.J. Ahluwalia and J.M.D. Little, 23–39. Delhi: Oxford University Press.

18

M. PAL

Biswas, J. 2008. Does finance lead to economic growth? An empirical assessment of 12 Asian economies. The Journal of Applied Economic Research 2 (3): 229– 246. Bosworth, B., and Susan M. Collins. 1999. Capital flows to developing economies: Implications for saving and investment. Brookings Papers on Economic Activity, Washington 30 (1): 143–180. Burnside, C., and D. Dollar. 2000. Aid, policies and growth. American Economic Review 90 (4): 847–868. Chakraborty, C., and P. Basu. 2002. Foreign direct investment and growth in India: A cointegration approach. Applied Economics 34 (9): 1061–1073. Chakraborty, C., and P. Nannenkamp. 2008. Economic reforms, FDI and economic growth in India: A sector level analysis. World Development 36 (7): 1192–1212. Chandrasekhar, C., and P. Pal. 2006. Financial liberalization in India: An assessment of its nature and outcomes. Economic and Political Weekly 41 (11): 975–985. Chenery, H.B., and A.M. Strout. 1966. Foreign assistance and economic development. American Economic Review 56 (4): 679–733. Cohen, D. 1982. LDC borrowing with default risk. National Bureau of Economic Research (NBER) working paper, 925, Cambridge. Corsepius, U. et al. 1989. Debt versus equity finance in developing countries— An empirical analysis of the principal-agent model of international capital transfers, 328. Turbingen: Kiel Institute for World Economy (ifw). de Glauco, and S.K. Khine. 2009. Growth effects of FDI and portfolio investment flows to developing countries: A disaggregated analysis by income levels. Applied Economics Letters 16 (3): 277–283. De Mello, L.R. Jr. 1997. Foreign direct investment in developing countries and growth: A selective survey. The Journal of Development Studies 34 (1): 1–34. De Mello, L.R. Jr. 1999. Foreign direct investment-led growth: Evidence from time series and panel date. Oxford Economic Papers 51 (1): 133–151. Dematriades, P.O., and K.A. Hussein. 1996. Does financial development cause economic growth? Time series evidence from 16 countries. Journal of Development Economics 51 (2): 387–411. Dickey, D., and W.A. Fuller. 1981. Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 49 (4): 1057–1072. Dickey, D., D.W. Jansen, and D.L. Thronton. 1991. A primer on cointegration with an application to money and income. USA: Federal Reserve Bank of St. Louis. Domar, E. 1946. Capital expansion, rate of growth and employment. Econometrica 14 (2): 137–149. Dowling, J.M., and U. Hiemenz. 1983. Aid, saving and growth in Asian region. The Developing Economies 21: 3–13.

1

INTRODUCTION

19

Dua, P., and A.I. Rashid. 1998. Foreign direct investment and economic activity in India. Indian Economic Review 33 (2): 153–168. Dua, P., and R. Garg. 2013. Foreign portfolio investment flows to India— Determinants and analysis. Working papers 225, Centre for development economics, Delhi School of economics. D.U: 1–36. Dua, P., and R. Garg. 2015. Macroeconomic determinants of foreign direct investment: Evidence from India. The Journal of Developing Areas 49 (1): 133–155. Dua, P., and R. Ranjan. 2010. Exchange rate policy and modeling in India. New Delhi: Oxford University Press. Dua, P., and R. Ranjan. 2012. Exchange rate policy and modeling in India. New Delhi: Oxford University Press. Dua, P., and A.I. Rashid. 1998. Foreign direct investment and economic activity in India. Indian Economic Review 33 (2): 153–168. Dua, P., and P. Sen. 2013. Capital flows and exchange rates: The Indian experience. Indian Economic Review 48 (1): 189–220 and reprinted in Krishna, K.L., V. Pandit, K. Sundaram, and P. Dua. 2017. Perspectives on economic development and policy in India. Springer. Dunning, J. H. 1977. Trade, location of economy activity and the MNE: A search for an eclectic approach. In International allocation of economic activity, ed. Ohlin B. et al., 395–418. London: MacMillan. Engle, R.F., and C.W.J. Granger. 1987. Cointegration and error correction representation, estimation and testing. Econometrica 55 (2): 251–276. Engle, R.F., and B.S. Yoo. 1987. Forecasting and testing in cointegrated system. Journal of Econometrices 35 (1): 143–159. Ghosh, J. 2009. The cost of “coupling”: The global crisis and the Indian economy. Cambridge Journal of Economics 33 (4): 725–739. Giri, A. K., and B. Kamaiah. 2006. Search for stable money demand function for India: A cointegration approach. In Studies in macroeconomics and welfare, ed. B.B. Bhattacharya and Arup Mitra. New Delhi: Academic Foundation. Griffin, K.B. 1970. Foreign capital, domestic savings and economic development. Oxford Bulletin of Economics and Statistics 32 (2): 99–112. Griffin, K.B., and J.L. Enos. 1970. Foreign assistance: Objectives and consequences. Economic Development and Cultural Change 18 (3): 313–327. Gupta, K.L. 1975. Foreign capital inflows, dependency burden and savings rates in developing countries: A simultaneous equation model. Kyklos 28: 358–374. Harrod, R.F. 1939. An essay in dynamic theory. The Economic Journal 49 (193): 14–33. Huang, T., Jr. 2004. Spillovers from FDI in China. Comtemporary Economic Policy 22 (1): 13–25.

20

M. PAL

Jana, S.S., T.N. Sahu, and D.K. Pandey. 2020. How far is FDI relevant to India’s foreign trade growth? An empirical investigation. Journal of Economic Structure 9 (1): 1–19. Johansen, S. 1988. Statistical analysis of cointegration vector. Journal of Economic Dynamics and Control 12: 231–254. Johansen, S., and K. Juselius. 1990. Maximum likelihood estimation and inference on co-integration—With application to the demand for money. Oxford Bulletin of Economics and Statistics 52 (2): 169–210. Kanbur, R. 2016. Can a country be a donor and recipient of aid? In Development in India: Micro and macro perspectives, ed. S.M. Dev and P.G. Babu. New Delhi: Springer. Kaur, M. 2015. Factors affecting interest rate structure in India: An application to VECM approach. The Indian Journal of Economics, XCVI (381): 325–344. Kohli, R. 2001. Capital account liberalization: Empirical evidence and policy issues-II. Economic and Political Weekly 36 (16): 1345–1348. Kohli, R. 2003. Capital flows and domestic financial sector in India. Economic and Political Weekly 38 (08): 761–768. Kohli, R. 2009. Financial integration, capital controls and monetary independence. Economic and Political Weekly 44 (26): 57–61. Kurihara, Y. 2015. Debt and economic growth: The case of Japan. Journal of Economics Library 2 (2): 45–52. Lall, S. 1983. The new multinationals: The spread of third world enterprises. Chichester, West Sussex: Wiley, New York. Lall, S. 1988. Patterns & impact of foreign direct investment flows into and from India. Development Paper, 10 UN. Ministry of Finance. 1991. Report of the committee on the financial system. New Delhi: Narasimham Committee, Government of India. Mosley, P. 1980. Aid, saving and economic growth revisited. Oxford Bulletin of Economics & Statistics 42: 79–95. Mosley, P. 1987. Foreign aid: Its defense and reform. Brighton, England. Narasimham Committee Report on the Financial System (NCR I 1991) and (NCR II 1998) Government of India. New Delhi. Pal, M. 1985. World bank and the third world countries of Asia. New Delhi: National Publishing House. Pal, M. 1989. Recycling of Japanese financial surplus by MDBs, Indian Economic Association publication (Conference Journal) Jadavpur University, Calcutta 27th–29th December, 1989. Pal, M. 2013. Finance-growth nexus in India: Evidence from co-integration & VECM. The Indian Econometric Society (TIES). Annual Conference Proceedings National Publishing House, New Delhi.

1

INTRODUCTION

21

Pal, M. 2014a. Financial development in India: An empirical test of the McKinnon-Shaw model analytical issues in trade, development and finance. New Delhi: Springer. Pal, M. 2014b. Financial policy of India-theory and evidence from co-integration. H.R Journal of Management, India. Pal, P. 2015. The management and impact of cross-border capital flows in India. In Economics, Vol 2: India and the International Economy, ed. Jayati Ghish. New Delhi: Oxford University Press. Pandit, B.L. 2015. The global financial crisis and the Indian economy. New Delhi: Springer. Pandit, B.L. et al. 2006. Transmission of monetary policy and the bank lending channel: Analysis and evidence for India. Development Research Group Studies Series, Study No. 25, RBI Mumbai. Papanek, G.F. 1972. The effect of aid and other resource transfer on savings and growth in less developed countries. The Economic Journal 82 (327): 934–950. Papanek, G.F. 1973. Aid, foreign private investment, saving and growth in less developed countries. Journal of Political Economy 81 (1): 120–130. Pethe, A., and A. Karnik. 2000. Do Indian stock markets matter? Stock market indices and macro-economic variables. Economic and Political Weekly 35 (5): 349–356. Prasad, E.S., R. Rajan, and S. Arvind. 2007. Foreign capital and economic growth, 153–255. Brookings, Papers in Economic Activity, Washington. Rahman, M.M., and M. Shahbaz. 2013. Do imports and foreign capital inflows lead economic growth? Cointegration and causality analysis in Pakistan. South Asia Economic Journal 14 (1): 59–81. Rati, R., and K.H. Zhang. 2002. Foreign direct investment and economic growth: Evidence from cross-country data for the 1990s. Journal of Economic Development and Cultural Change 50 (1): 205–215. Rangarajan, C. 1998. Financial development and economic growth. Journal of Social and Economic Development 1 (1): 10–23. Rangarajan, C. 2001. Leading issues on monetary policy: Sukhamoy Chakravarty Memorial Lecture, RIS New Delhi. Ranjan, R., and S. Kumar. 2012. An empirical investigation of the impact of capital inflows on domestic investment in India. Indian Economic Review XXXVII (1): 15–32. Ratha, D. 2007. Leveraging remittances for development, Migration Policy Institute, Policy Brief, Washington DC, World Bank. Rodan, R. 1961. International aid for under-developed countries. Review of Economics and Statistics 43 (2): 107–138. Sasi, J. Raro. 2016. The FDI—Economic growth nexus. International Review of Economics and Finance 42: 116–133.

22

M. PAL

Schumpeter, J. 1911. The Theory of economic development: An inquiry into profits, capital, credit, interest, and the business, Harvard Economic Studies, No, 46. Harvard University Press. Sharma, R.K. 1973. Grant element in external assistance to India. The Indian Economic Journal, XXI : 124–131. Stock and Watson. 2003. Introduction to econometrics. New York: Prentice Hall. Taylor. 1990. A three gap analysis of foreign resources flow and developing country growth. In The rocky road to reform, ed. L. Taylor, WIDER, Helsinki, Finland. Tendulkaer, S. et al. eds. India industrialization in a reforming economy: Essays for K.L Krishna. New Delhi: Academic Foundation. The Prowess database comprises firm level data, collected by the Centre for Monitoring the Indian Economy (CMIE) a private company in India. Thornton, J. 1996. Cointegration, error correction, and the demand for money in Mexico. Review of World Economics 132 (4): 690–699. UN. 2013. The MDG gap task force report, global partnership for development: The challenge we face. U.N. Publication. Uppadhyay, P.G. 2008. Remittances and economic growth. The European Journal of Development Research 20 (3): 497–506. Vadlamannati, C.K. 2008. Do insurance sector growth and reforms affect economic development? Empirical Evidence from India. The Journal of Applied Economic Research 2 (1): 43–56. Vasudevan, A. 2006. Note on portfolio flows into India. Economic and Political Weekly 41 (2): 90–92. Verma, S., and R. Arora. 2009. Foreign direct investment and economic growth in India: A macroeconomic appraisal. Asian Economic Review 51 (2): 229– 248. Wadud, Md.A. 2000. Cointegration and error-correction models in estimating causality between exports and economic growth in Bangladesh. Pakistan Journal of Applied Economics 16 (1–2): 25–35. World Economic Situation and Prospects. 2014. Global Economic Outlook U.N. New York.

CHAPTER 2

Macrodeterminants of FDI in India: Cointegration and Causality

2.1

Introduction

FDI provides a corresponding benefit to the host and home countries. Host countries are directly benefitted from the availability of finance, foreign exchange reserve which supports domestic saving, source of technology transfer, managerial and entrepreneurial skills, export development, more employment opportunities resulting ultimately increase in firms productivity. Magnitude FDI flows to emerging nations increased more than six fold between 1990 and 1998. For detailed analysis, see Chakraborty and Basu (2002). De Mello (1997) points out that growth of privatization, financial and trade globalization, political stability, trade openness and investment liberalization have been major factors for FDI inflow in the emerging nations.1 Further financial globalization led liberalization mainly in finance, trade and foreign capital from debt creating to non-debt creating foreign capital and this liberalized regime has been mainly responsible for the explosion of MNCs. If we look at the exponential growth of FDI inflows in the developing countries, it was only US $54.1 Billion in the year of 1980, which increased to fourfold to the level of US $208 Billion in 1990. Further, it also increased to the amount of US $1.5 Trillion in 2006 and it also increased again in an exponential form to the level of US $2.1 Trillion in the historic year of 2007. After that year, FDI inflow declined to US $1.6 Trillion in 2008. However, FDI inflow increased further on an average to © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. Pal, Foreign Capital and Economic Growth in India, https://doi.org/10.1007/978-981-99-2299-4_2

23

24

M. PAL

the tune of US $1.5 Trillion annually during the period of last 10 years (i.e. from 2008 to 2019). So far definition of FDI is concerned, it has become a controversial issue. In simple language, FDI is generally processed through collaborations and there are three types of collaborations: Government Party to Government Party; Government Party and Private Party and Private Party and Private Party. It generally comes in the four major areas such as manufacturing, processing, marketing and technology. It is processed through MNCs and it has a direct impact on the product market. In the FDI operational process, a project is undertaken and it may be up to 5 to 10 years. Generally, FDI is equity based; it may be 51% or 49%. In case of FDI, there is no interest burden involved. Moreover, FDI is not interest sensitive. Investment is based on profit and loss involved in the project, and there is no debt service burden on the host countries in the case of FDI. Moreover, FDI provides the enclave culture, through which MNCs have a positive impact on the economic development of the host countries which are willing to develop. The general public of these countries provide full support for their growth and development. MNCs try to use un-used pool of existing domestic resources and make it productive, and in this way, MNCs also help in reduction of poverty level in a country like India. Enclave culture means mobilization of resources, mall culture, good road connectivity and high quality of basic necessities of the public. Earlier work has been experimented with a number of determinants, but no study has taken into account the indicator of financial deepening (M3/GDP ratio), which reflects the soundness of financial system, enhances macrostability, reduces inflationary pressure and reduces the cost of financial transaction. Hence, to make foreign capital more productive, to reduce its volatility and to make it more sustainable, the sound financial system is an important prerequisite. The major objectives of this chapter are: First to study the trends and financial magnitude of FDI in India especially since 1991; second, to study the major and potential determinants of FDI in India with their theoretical backdrop. Third to examine their long-term relationship and their causal direction with the help of Johansen and Juselius (1990) cointegration test. The plan of this chapter is structured as: Sect. 2.2 discusses the evolution of foreign investment policy in India. Section 2.3 provides a detailed analytical and empirical review of the determinants of FDI. Section 2.4 deals with the model specification and discusses the results. Section 2.5 concludes the chapter.

2

MACRODETERMINANTS OF FDI IN INDIA …

25

2.2 Foreign Investment Policy in India---An Overview The Government of India changed its industrial policy under the New Economic Policy of 1991. Some points in relation to the New Economic Policy are worth mentioning. Under this policy, an automatic approval route for FDI approval was created and 51% of equity investment was allowed in 34 priority sector industries. While no automatic route was allowed in rest of the industries, however, in these cases, Foreign Investment Promotion Board (FIPB) was created to approve FDI on case-by-case basis. Second, foreign investment was allowed in oil sector in 4 areas such as production, refinery, exploration and marketing. Third, coal industries were allowed to be run and owned by the private sector. Fourth, India joined Multilateral Investment Guarantee Agency (MIGA) in April 1992.2 Foreign Exchange Regulation Act (FERA) of 1973 was relaxed,3 NRIs were allowed to buy house property in India without RBI permission. Seventh, NRIs were also allowed to invest 100% in the equity capital of sick industries, trading houses, tourism, hotels, hospitals, etc. Eighth, foreign companies were also allowed to use their trade marks on the sale of domestic goods. This increase of FDI inflow was due to the revised FDI Policy in March 2005; an important element of the policy was to allow FDI up to 100% foreign equity under the automatic route in townships, housing, built-up infrastructure and construction-development projects. The year of 2005 also witnessed the enactment of the Special Economic Zones Act, which engaged a lot of construction and township development that came into force in February 2006. Table 2.1 shows the annual flows of net FDI in absolute value, FDI stock or in cumulative value, Net Foreign Investment/GDP ratio and Net FDI/GDP ratio during the period of 42 years. In absolute value, FDI ranged around US $50 million a year during the first thirteen years, i.e. from 1971 to 1984. Further, FDI increased from US $100 million in 1985 to about US $1.1 Billion in 1994 during the period of early 1990s, and it is especially due to the initiatives of New Economic Policy when Structural and Adjustment Programme (SAP) was applied in India.4 Further, during the period of 10 years, i.e. from 1995 to 2005, FDI increased from US dollar 2.2 Billion to US dollar 7.3 Billion. After that year, FDI increased in an exponential form especially since the year of 2006. It was US $20 Billion in 2006 which increased to the extent of

26

M. PAL

more than US $47 Billion in 2008, just within two years. The year of 2008 can be considered a peak year in the Indian history of FDI inflow. However, in the later period, i.e. from 2009 onward, FDI remained in the range of US $35 Billion to US $43 Billion on an average. Further FDI stock increased from US $93 million in the year of 1971 to around US $282 Billion in 2013. FDI upward trends in absolute US $Billion are shown in Fig. 2.1. Further FDI/GDP ratio which was less than 0.1% in the year of 1971 increased to 0.2% in 1993. In other words, it is worth mentioning to note that during the period of twenty years the FDIGDP ratio remained less than 0.1% of GDP. However, it started to increase after 1993. For the first time, FDI/GDP ratio increased to the level of 1.1% in 2001 and which also increased to the level of 2.1% in 2006, and further, this ratio increased to the level of 3.5% in 2008. This year was a peak year of FDI inflow, as pointed above, and after that, it declined to the level of 1.52% in 2013. The upward trends of FDI/GDP ratio are shown in Fig. 2.2. Further, if we look at the foreign investment/GDP ratio which increased from 0.1% in 1971 to 0.1% in 1993 that is during the period of more than 20 years FI/GDP ratio remained constant around 0.1%, sometimes negative. From the year of 1994 to 2003, again it remained more or less constant around 1.2% FI/GDP ratio. But it started to increase from 2.6% in 2004 and increased to the level of 5% in 2008. However, it declined to 3.1% in 2013. Figure 2.3 reveals the trends of FI/GDP ratio in India during the research period. FDI inflows in India have attracted FDI inflows from the number of countries. Between 1991 and 2005, investment from 10 top countries accounted for about 80 percent of total FDI. The share of these top investing countries increased to 91 percent during the period 2005–2009. The major FDI investors in India have Mauritius, USA, Singapore, UK, Netherlands, Japan, Germany, Cyprus, France, Switzerland, etc. Now, India is ranked among top 20 host economies for FDI inflows in: UN Report (2017–2018). During the period of last two decades, Mauritius has been the major source and dominant contributor of FDI accounting for more than 35% of top 5 investing countries. The main reason of Mauritius dominance is that India has a DTAA with Mauritius. This type of taxation agreement has also been made with Singapore and USA.5 In terms of state distribution, Maharashtra, Delhi-NCR (National Capital Region is a part of Haryana & U.P.), Karnataka, Andhra Pradesh, Goa and Gujarat are the

2

MACRODETERMINANTS OF FDI IN INDIA …

27

Table 2.1 Trends of FDI and foreign investment in India (1971–2013) (US $ million) Year

FDI

FDI (stock)

FDI ($ billion)

FDI/GDP ratio (%)

FI/GDP ratio (%)

1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

47.66 17.79 37.91 56.97 85.09 51.11 −36.06 18.09 48.57 79.16 91.92 72.08 5.64 19.24 106.09 117.73 212.32 91.25 252.11 236.69 75.11 252.01 532.11 978.01 2151.11 2525.01 3619.11 2633.11 2168.11 3585.01 5472.11 5627.12 4323.11 5771.01 7606.11 20,336.11

93.12 110.91 148.82 205.79 290.88 341.99 295.93 314.02 362.59 451.75 543.67 615.75 621.39 640.63 746.72 864.45 1076.77 1168.02 1420.12 1656.81 1731.81 1983.81 2515.81 3489.81 5640.81 8165.81 10,630.11 14,065.36 15,426.11 17,517.12 20,326.61 25,418.77 29,741.88 35,512.89 43,119.11 63,455.11

0.05 0.02 0.04 0.06 0.09 0.06 0.04 0.02 0.03 0.08 0.09 0.07 0.01 0.01 0.11 0.12 0.21 0.11 0.25 0.23 0.08 0.26 0.54 1.11 2.21 2.51 3.61 2.61 2.21 3.61 4.31 6.21 5.11 4.31 7.31 20.22

0.01 0.02 0.02 0.01 −0.01 −0.01 −0.03 0.01 0.03 0.04 0.05 0.04 0.04 0.01 0.04 0.05 0.07 0.03 0.08 0.07 0.03 0.09 0.19 0.29 0.58 0.61 0.85 0.61 0.46 0.81 1.11 1.07 0.71 0.81 0.87 2.11

0.1 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.2 0.1 0.1 0.0 0.1 0.2 1.5 1.5 1.4 1.6 1.3 0.6 1.2 1.5 1.7 1.2 2.6 2.2 2.6

(continued)

28

M. PAL

Table 2.1 (continued) Year

FDI

FDI (stock)

FDI ($ billion)

2007 2008 2009 2010 2011 2012 2013

25,125.11 47,139.01 35,657.11 21,125.11 36,190.01 25,543.12 26,853.12

88,580.22 135,719.2 171,376.3 192,501.3 228,691.5 254,234.7 281,187.7

25.22 47.23 35.51 33.11 36.22 24.11 28.22

FDI/GDP ratio (%) 2.04 3.55 2.91 2.91 1.98 1.31 1.52

FI/GDP ratio (%) 3.1 5.0 2.3 4.8 3.5 2.7 3.1

Source Author’s compilation from the different sources such as World Development Indicators (World Bank), OECD, IFS of the IMF of different years: HBS (RBI)

50,000

40,000

30,000

20,000

10,000

0

-10,000 75

80

85

90

95

00

05

10

Fig. 2.1 Trends of net FDI inflow to India (1971–2013) (US million dollar) (Source Author’s own work based on Table 2.1)

top states in receiving FDI. In the year of 2009–2010 out of total FDI received, more than 50% of FDI was received by Maharashtra (Mumbai) and Delhi (NCR).

2

MACRODETERMINANTS OF FDI IN INDIA …

29

3.6 3.2 2.8 2.4 2.0 1.6 1.2 0.8 0.4 0.0 -0.4

75

80

85

90

95

00

05

10

Fig. 2.2 Net FDI as a percentage of GDP in India (1971–2013) (Source Author’s own work based on Table 2.1)

Fig. 2.3 Foreign investment as a percentage of GDP (1971–2013) (Source Author’s own work based on Table 2.1)

30

M. PAL

If we talk about the effectiveness of FDI inflows in terms of utilization and disbursement during the period of one decade of 1980s, degree of FDI utilization (disbursement over /actual) was very poor (i.e. around 30%) on an average, because of certain fundamental problems in India such as poor quality of physical infrastructure and lack of transparency. However, in a single year of 1992, after the economic reforms the performance of FDI utilization increased with a record of 66%, but after that the record was very poor till 1998. The average utilization remained at around 24%. It shows the poor utilization of FDI during 1990s. During 2000s, degree of utilization increased at an alarming rate more than the previous year’s record, and it was around 100%. It means quick disbursement and high utilization of FDI inflows were observed. For effective utilization of FDI, see Dua and Rashid (1998). 2.2.1

Repatriation and Reinvested Earning from FDI Inflows

If we look at the recent trends in the repatriation and reinvested earnings from the FDI, we find different picture. Reinvested earnings are invested back into the Indian economy. Figures 2.4 and 2.5 reveal the facts about the trends of different macroindicators regarding the gross, net, repatriation of FDI earnings, which were very less till the year 2008–2009, started to increase from about 18% of the FDI equity inflows in 2009–2010 to the level of 48% in 2017–2018. In addition to the amount of repatriation, the reinvested earnings which were very high in the beginning to the extent of 60% of FDI equity inflows in the period of 2002–2004 declined to 28% in 2017– 2018. The trends of repatriations and reinvested earnings indicate that more profits from foreign capital have been flowing out of the economy, which have also been responsible for neutralizing the potential benefits of FDI in the Indian economy. Further, this profit could have benefited the Indian economy in the long run. For detailed discussion on this issue, see the Discussion Paper on Industrial Policy (2017) of Government of India and also, see Rao et al. (1999).6

2.3

Review of Literature

To highlight important and potential determinants of FDI, we will discuss in brief some select studies. C. Sinha and K. Sen (2016), Ravinthirakumaran et al. (2015), Bhanumurthy and Sinha (2015), Sahoo et al. (2014),

2

MACRODETERMINANTS OF FDI IN INDIA …

31

160 140 120 100 80 60 40 20 0

Net Foreign Direct Investment

Net Portfolio Investment

Total

Fig. 2.4 Trends of net FDI, net portfolio and total investment (2001–2018) (Source Author’ own work based on the Data from HBS [RBI])

70 60 50 40 30 20

Gross Inflows/Gross Investment Repatriation/ Direct Investment to India FDI by India

10 0

Net Foreign Direct Investment

Fig. 2.5 Trends of gross, reinvested and repatriation of FDI in India (2001– 2018) (Source Author’ own work based on the Data from Hand Book of Statistics on Indian Economy, RBI)

32

M. PAL

Dua and Garg (2013, 2015), Neelakanta (2013), Nayak (2012), Shahid (2012), Pattnaik and Kumar (2011), Rana and Muhammad (2010), Nurudeen and Wafurea (2010), Ang (2008), Verma and Arora (2009), Pradhan (2008), Adeolu (2007), Ruiz (2005), Masayuki and Ivohasina (2005), Hasan (2004), Yves and Hans (2006), and Zahir and Ahmed (2003). C. Sinha and K. Sen (2016) examine the spectacular growth in the inflow and significant outflows of global capital from the Global South. They also point that Asia is one of the important regions where FDI outflows take place. In their two empirical studies on the determinants of FDI and portfolio investment in India, Dua and Garg (2015) examine the macroeconomic determinants of FDI flows in India using cointegration technique with 1(1) exogenous variable. Their results indicate that the exchange rate depreciation, high economic growth, and good infrastructural facilities and good domestic returns are detected as major determinants of FDI flows in India. In their second study, P. Dua and R. Garg (2013) analyze the determinants of disaggregated portfolio investment which consists of FIIs and GDRs and ADRs in India for the sixteen-year period from 1995 to 2011. Their study uses the portfolio balance model in partial manner to examine the portfolio determinants. Main findings indicate the exchange rate, booming stock market and economic growth as the most significant determinants of portfolio investment in India. Ravinthirakumaran et al. (2015) empirically examine the role of FDI in Sri Lanka using annual data for the period of 1978–2013 with the help of new time-series analysis. Market size, trade openness and status of infrastructural facilities have a positive impact on FDI inflows. A finding from the cointegration exhibits the existence of long-run relationship between GDP and FDI. Granger causality test also indicates the existence of a unidirectional causality which runs from economic growth to FDI. They conclude that economic growth is an essential condition for attracting FDI in Sri Lanka. Bhanumurthy and Sihna (2015) in their panel regression methodology examine the determinants of FDI with the help of Principal Component Analysis (PCA) and identify infrastructure, labor market, trade openness and human resource development as important determinants of FDI in the host country. Sahoo et al. (2014) examined the role of FDI in enhancing the economic growth in the South Asian countries, notably in Sri Lanka, Pakistan, India, Nepal and Bangladesh with the help of methodology

2

MACRODETERMINANTS OF FDI IN INDIA …

33

which includes time-series analysis, panel data, AEDL and annual data for the period from 1980 to 2010. They conclude that the impact of FDI on the growth process in host countries is determined by human capital, trade openness, financial development, economic and social infrastructure, etc. The coefficient of FDI is highest in case of Indian economy which shows that one unit increase in FDI inflow causes 0.05% increase in growth rate, while in other South Asian countries Pakistan shows 0.03%, Sri Lanka 0.04% and Bangladesh 0.008%. Their findings reveal the fact that India’s capacity to absorb FDI is very high and effective, which further explores that India has become a favored destination of foreign capital inflows in the world economy. Neelakanta (2013) examined the dynamic causal relationships between FDI, GDP per capita and pollution level in India by applying the bound test (ARDL) model developed by Pesaran et al. (2001) to cointegration technique for the period from 1978 to 2009. Results confirm stable sortrun and long-run relationships among the three variables and exhibit a bidirectional Ganger causality which runs from GDP to FDI and CO and reverse is also possible. R. K. Nayak (2012) examines the GDP, interest rates, exchange rate movement, macroeconomic stability and trade openness as major determinants of FDI in India with the help of regression analysis and using quarterly data from 1996 Q1 to 2010 Q4. H. M. Shahid (2012) investigates GDP level as most significant determinant of FDI in the long run in Pakistan economy over the period 1973 to 2004 using a cointegration time-series technique. Pattnaik and Kumar (2011) say FIIs due to their pro-cyclical and highly volatile behavior can have impact on the money and financial sector in Indian economy. Rana and Muhammad (2010) in their study find that one percent decrease in Pakistan’s exchange rate is associated with 0.41 percentage point increase in FDI annually. They conclude that depreciation of the currency encourages the inflow of FDI. Nurudeen and Wafurea (2010) examine the market size, deregulation, exchange rate depreciation and political instability as the main determinants of FDI and conclude that exchange rate remains to be an important determinant in attracting in FDI. One percent depreciation in exchange rate causes FDI to increase by 0.02 percentage point. Ang (2008) examines the determinants of FDI for Malaysia by using annual data for the period 1960–2005. Study suggests that the increase in the market size, level of real GDP, growth of financial development, infrastructural facilities and trade openness remain as

34

M. PAL

main determinants to attract FDI, while growth rate shows poor result in attracting FDI in Malaysia. S. Verma and R. Arora (2009) develop a macroeconometric model which consists of five variables such as LogGDP, LogFDI, LogEXPO, LogNGCF and LogNEMPL and examine the long-run relationship with the help of cointegration technique developed by Johansen and Juselius (1991). Their empirical analysis suggests that domestic investment in infrastructure and in the manufacturing sector is important determinant to attract more FDI inflows in Indian economy. R. P. Pradhan (2008) empirically finds that the development of infrastructural facilities shows a negative impact on FDI inflows in India, while trade openness determines the FDI inflows during the study period from 1970 to 2004. B. A. Adeolu (2007) reveals the fact that the formation of the New Partnership for Africa’s Development (NEPAD) has been an instrumental in attracting the foreign investment to Africa and Nigeria. Results suggest that trade openness, stable macroeconomic policy, market size and infrastructural facilities have been identified as major determinants of FDI and have a positive impact in Nigeria in terms of increase in economic growth. I. C. Ruiz (2005) examines the relationship between exchange rate and FDI and provides a detailed survey on the topic exchange rate as a major determinant of FDI in Latin American countries. Masayuki and Ivohasina (2005) present an econometric analysis of the determinants of FDI inflows into Japan. The size of the market, volatility of exchange rates, price movements, cost of establishing Greenfield plants and deregulations of the environment for investments are important determinants in Japan. B. Yves and F. Hans (2006) study the macroeconomic impact of foreign remittances on the real exchange rate in Cape Verde and conclude that remittances cause a problem of Dutch Disease which has an adverse effect on the competitiveness of the export sector. Z. Shah and M. Qazi (2003) in their study calculate the cost of capital with the application of the Jorgenson’s investment model developed by Ahmed (1997). The model works effectively in the long run as being proved by Johansen and Juselius (1990) test for cointegration. Likelihood ratio (LR) tests indicate 3 cointegration equations at 5 present level of significance which shows very effective significance level. Their null hypothesis of no cointegration is rejected at 1% significance level which suggests that the variables show long-run relationship.

2

MACRODETERMINANTS OF FDI IN INDIA …

35

6 5 4 3 2 1 0

75

80

85

90

95

00

05

10

Fig. 2.6 Trends of foreign investment/GDP ratio (%) in India (1971–2013) (Source Author’s own work based on Table 2.2)

Z. Hasan (2004) reviews literature relating to the determinants of FDI inflows and their empirical application in Malaysia. Economic growth rate, level of infrastructure, exports and exchange rate have been identified as significant determinants of FDI in Malaysia. On the basis of studies reviewed above, we try to spell out the most applied, significant and popular hypotheses on the determinants of FDI in the developing countries, especially on Indian economy during the last two decades (Figs. 2.6 and 2.7). 2.3.1

Market Size and FDI

Market size and growth potential are significant determinants for FDI inflows. Large size of market means high per capita income; high GDP growth rate reflects high aggregate demand. Thus, an economy with a large market size is expected to attract more FDI. Hence, we hypothesize that higher the size of domestic market, higher shall be the level of FDI in Indian economy. Table 2.2 reveals the facts that GDP growth rate, PCY and GDP level all have shown a rising trends. Figures 2.8, 2.9 and 2.10 show the upward trends in GDP, PCY and growth rate in India. These upward trends have been responsible to reflect the large size of market in India.

36

M. PAL

50,000 40,000 30,000 20,000 10,000 0 -10,000

75

80

85

90

95

00

05

10

Fig. 2.7 Trends of net FDI inflow in India in US $ billion (1971–2013) (Source Author’s own work based on Table 2.2)

2.3.2

Trade Openness and FDI

Trade openness means export + import divided by the GDP. Earlier export/GDP ratio was used as measure of trade openness, but now openness of trade to GDP has assumed a significant determinant for FDI attraction. The number of economists has talked about that trade openness influences export-oriented FDI positively in the host economy. Hence, we hypothesize that higher the degree of trade openness, higher shall be the level of FDI. Figure 2.11 shows the rising trends of trade openness in India. 2.3.3

Financial Deepening and FDI

It is a well-established research that a high level of financial deepening and effectiveness of capital inflows go together. There are two types of financial system in the world economy. Direct finance in which corporate sector directly borrows money from the household sector through direct instruments such as equity, debenture, bonds and preference share. Another is indirect finance in which financial intermediation through financial institutions provides funds indirectly to the investment class with the help of indirect securities such as bank deposits and currency. The main role of the good financial system has been to promote the domestic financial intermediation. The main indicator of financial intermediation or financial deepening is M2/GDP or broad money/GDP

FI/GDP ratio (%)

0.1 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.1 0.1 0.0 0.0 0.2 1.5

1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994

7.0 7.3 7.7 7.8 9.8 11.4 11.7 11.2 12.0 13.2 13.5 12.8 13.1 12.3 12.3 11.6 11.4 11.8 13.0 14.1 14.6 14.7 17.6 17.9

Trade openness/GDP ratio (%) 25.4 27.4 29.5 28.3 26.6 28.3 32.1 34.3 37.4 41.1 40.1 41.2 41.7 44.4 45.5 48.3 49.3 48.9 50.5 50.5 52.2 52.8 50.1 52.1

M3/GDP ratio (%) 119 123 144 163 158 161 186 206 224 266 270 274 291 277 296 311 340 354 346 367 340 320 310 330

PCY (US $) 67 71 86 100 99 103 121 137 153 186 193 201 218 212 233 249 279 296 296 321 327 288 279 327

GDP (US $ billion) 5.1 1.1 −0.3 4.6 1.2 9.1 1.2 7.5 5.5 −5.2 7.2 6.1 3.1 7.7 4.3 4.5 4.3 3.8 10.5 6.7 5.6 1.3 5.1 5.9

Growth rate % (GDP at factor cost)

Time-series data on Macrodeterminants of FDI in India (1971–2013)

Year

Table 2.2

7.5 7.5 7.7 7.8 7.9 8.8 8.9 8.6 8.3 8.3 7.9 8.9 9.6 10.3 11.9 12.2 12.8 12.9 14.5 16.6 17.9 24.5 36.6 31.4

Nominal exchange rate (Rs/$)

MACRODETERMINANTS OF FDI IN INDIA …

(continued)

0.05 0.02 0.04 0.06 0.09 0.06 0.04 0.02 0.03 0.08 0.09 0.07 0.01 0.01 0.11 0.12 0.21 0.11 0.25 0.23 0.08 0.26 0.54 1.11

Net FDI inflow (US $ billion)

2

37

1.5 1.3 1.6 1.3 0.6 1.2 1.5 1.7 1.2 2.6 2.1 2.6 3.1 5.0 2.3 4.8 3.5 2.8 3.0

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

19.4 21.4 21.4 21.2 19.6 20.6 22.5 21.2 23.3 24.4 28.3 31.4 33.7 34.2 40.6 35.4 37.4 44.4 44.3

Trade openness/GDP ratio (%) 52.5 52.1 55.1 53.9 55.9 44.7 42.9 65.7 69.6 69.6 66.1 66.1 68.9 73.1 78.1 78.6 79.6 80.1 80.6

M3/GDP ratio (%) 380 410 420 420 440 450 460 470 530 630 740 820 950 1070 1102 1358 1458 1502 1450

PCY (US $) 360 367 416 421 459 468 485 515 608 709 820 941 1217 1199 1342 1676 1823 1828 1857

GDP (US $ billion)

Source Author’s own work based on the Data from HBS (RBI), WDI (World Bank)

FI/GDP ratio (%)

(continued)

Year

Table 2.2

7.3 7.3 7.8 4.8 6.5 6.2 4.3 6.1 4.2 8.5 9.5 9.7 9.6 9.3 6.7 8.4 8.4 6.5 7.4

Growth rate % (GDP at factor cost) 31.4 33.4 35.5 37.2 42.1 43.3 45.7 47.7 48.4 45.9 44.9 44.3 45.3 40.2 52.4 53.5 54.4 54.5 54.4

Nominal exchange rate (Rs/$)

2.21 2.51 3.61 2.61 2.21 3.61 4.31 6.21 5.11 4.31 7.31 20.22 25.22 47.23 35.51 33.11 36.22 24.11 28.22

Net FDI inflow (US $ billion)

38 M. PAL

2

MACRODETERMINANTS OF FDI IN INDIA …

39

2,000 1,600 1,200 800 400 0

75

80

85

90

95

00

05

10

Fig. 2.8 GDP trends in India (US $ billion) (1971–2013) (Source Author’s own work based on Table 2.2) 1,600 1,400 1,200 1,000 800 600 400 200 0

75

80

85

90

95

00

05

10

Fig. 2.9 Trends of Indian PCY (US $) (1971–2013) (Source Author’s own work based on Table 2.2)

ratio and credit/GDP ratio. Broad money consists of currency in circulation, demand deposits, time and saving deposits at commercial banks. For example, in India, Table 2.2 and Fig. 2.12 indicate that M3/GDP ratio has gone up especially after the introduction of New Economic Policy of 1991. For comprehensive survey, see (Pal, 2013, 2014a, b). We hypothesize that higher the level of financial deepening, higher shall be the attraction of capital inflow, especially FDI and portfolio investment.

40

M. PAL

12 8 4 0 -4 -8

75

80

85

90

95

00

05

10

Fig. 2.10 Trends of real GDP growth rate in India (1971–2013) (Source Author’s own work based on Table 2.2) 45 40 35 30 25 20 15 10 5

75

80

85

90

95

00

05

10

Fig. 2.11 Trends of T.O. (X + M/GDP %) in India (1971–2013) (Source Author’s own work based on Table 2.2)

2.3.4

Exchange Rate and FDI

Exchange rate strength influences FDI inflows in India and in other emerging nations. A number of researchers in the field of economics have examined that an appreciation of the domestic currency is expected to reduce the FDI inflows in the host country. Ang (2008) has found a negative relationship between exchange rate appreciation and FDI inflow. For detailed discussion on the issue of exchange rate as determinant of

2

MACRODETERMINANTS OF FDI IN INDIA …

41

90 80 70 60 50 40 30 20

75

80

85

90

95

00

05

10

Fig. 2.12 Trends of financial deepening (M3/GDP %) in India (1971–2013) (Source Author’s own work based on Table 2.2) 60 50 40 30 20 10 0

75

80

85

90

95

00

05

10

Fig. 2.13 Trends of nominal exchange rate (Rs./US $) in India (1971–2013) (Source Author’s own work based on Table 2.2)

FDI, see Ruiz (2005), Rana and Muhammad (2010), Nurudeen and Wafurea (2010) and James (2009). Figure 2.13 shows the exchange rate depreciation of Indian rupee. Table 2.2 shows the trends in macrodeterminants for the study period 1971 to 2013. Time-series data are used for estimation purpose.

2.4

Econometric Model Specification

Over the period of the last two decades, studies on FDI have attracted the work of theoreticians and empirics with sophisticated techniques and availability of data. Number of research studies have been carried on the

42

M. PAL

determinants of FDI in the emerging economies and developed countries. India has become a good destination for FDI investors; however, it remains far behind taking into account some theoretical and empirical points. Following the technique and findings of different studies such as Sahoo et al. (2014), Nayak and Ranjan (2012), James (2009), Verma and Arora (2009), Kavinthirakumarn et al. (2015), and Sinha and Sen (2016), we have developed the following model which is an adopted synthesis, and to test this model, we use the following determinants of FDI to find out the long-run relationship among the number of variables such as FDI, financial deepening, growth rate, trade openness, exchange rate, PCY, GDP and FI. FDI = f (GDP, Y, PCY. M3/GDP,

) Trade Openness, Exchange Rate

(2.1)

FDI = α0 + β1 GDP + β2 PCY + β3 Y + β4 Trade Openness + β5 M 3 /GDP + β6 Ex rate + et

(2.1a)

Variables explained GDP = Gross Domestic Product. Y = Real GDP growth rate. PCY= Per Capita Income M3 /GDP = Broad Money (C + DD + TD/GDP) as proxy for Financial Deepening. Trade Openness (TO) = Trade openness is defined as (Imports + Exports)/GDP. This ratio is taken as a proxy for the trade relations India maintains with other foreign countries. Greater degree of trade openness means India has accepted large volume of foreign goods and services and various types of foreign capital. FDI = Foreign Direct Investment in net absolute value of US $ Billion. Exchange Rate = Nominal Exchange of Indian Rupees in terms of U.S.Dollar/Rs. Exchange rate is taken as proxy to check how volatility of exchange rate of Indian Rupees with respect to currency of developed countries can affect the flow of FDI to India.

2

MACRODETERMINANTS OF FDI IN INDIA …

43

Model 2.1 includes seven variables such as FDI, trade openness, financial deepening, GDP, GDP growth rate, PCY and nominal exchange rate. Table 2.3 shows that all the selected variables of the model are integrated of the order one after first differencing. Further from Tables 2.4 and 2.5, we find two cointegrating equations and rejects null hypothesis of no cointegration and shows long-run relationship among variables. In this model, value of trace statistic and maximum eigenvalues are more than their critical value at low probability value. Table 2.6 reveals the facts about the Granger causality in the number of variables.

2.5 Foreign Investment and Its Potential Determinants In this model, we select the foreign investment which includes FDI and portfolio investment both and its major determinants.7 During the last two decades, empirical studies on the relationship between foreign capital and growth and potential determinants of foreign capital have concentrated mainly on FDI and its determinants. However, a number of studies have spelled out number of determinants of portfolio investment and its impact on growth process in emerging countries and also on Indian economy. For detailed analysis on this topic, see Aggarwal (2011) and Dua and Garg (2013). We use the following four determinants of foreign investment to find out the long-run relationship among the four variables such as foreign investment, financial deepening, growth rate and trade openness. This exercise shows strong evidence of long-run relationship among the four variables. Econometric Model for Estimation Model 2.2. FI = f (Y, M3/GDP, X + M/GDP)

(2.2)

FI = Foreign Investment/GDP ratio. FI includes FDI and Portfolio Investment. Y = Growth Rate. M3/GDP ratio = Financial Deepening. X + M/GDP ratio = Trade Openness.

44

M. PAL

Table 2.3 Results of Augmented Dicky Fuller (ADF) and Phillips-Perron (PP) unit root tests ADF Variables Log PCY Level First Difference Log FDI Level First Difference Log Y Level First Difference Log Open Level First Difference Log M3 GDP Level First Difference Log GDP Level First Difference FI /GDP Level First Difference Log Ex Rate Level First Difference

P. P.

Without trend

With trend

Conclusions

−0.2437

−1.6888

−2.217

−3.7091

−5.039*

−6.2388* 1(1)

−5.0837*

−6.2377* 1(1)

−0.9475

−3.2654

−0.6417

−3.2649

−5.1979* −5.1187* 1(1)

−9.8086*

−9.1703* 1(1)

−3.1296

−3.4932

−1.3786

−3.8939* −5.5143* 1(1)

−5.5947*

−7.4116* 1(1)

−0.1518

−0.0423

−2.5819

−6.7718* −6.7029* 1(1)

−6.7659*

−6.6929* 1(1)

−1.3471

−1.4582

−2.7820

−1.1515

−1.7973

−2.9304

−6.3712* −6.3013* 1(1) −0.0833

−1.2905

Without trend

With trend Conclusions

−10.3502* −11.2758* 1(1) −0.1171

−1.5279

−5.2375* −5.1618* 1(1)

−5.2023*

−5.1229* 1(1)

−0.5042

−1.1461

−3.5521

−3.5531

−8.6280* −8.1069* 1(1) −0.5418

−1.4815

−6.1431* −6.0709* 1(1)

−16.0034* −15.8838* 1(1) −0.5516

−1.8472

−6.1487*

−6.0747* 1(1)

Significance at the 1%, 5% and 10% level is indicated by *, ** and *** (i) Critical value for ADF without Trend 1% (−3.6576), 5% (−2.9591), 10% (−2.6181) (ii) Critical values for ADF with Trend are: 1% (−4.2820), 5% (−3.55614), 10% (−3.2138) Without Trend: 1% (−3.6537), 5% (−2.9514), 10% (−2.6171) With Trend: 1% (−4.712), 5% (−3.5562), 10% (−3.2109) Source Author’s computation by using EViews-6

2

MACRODETERMINANTS OF FDI IN INDIA …

45

Table 2.4 Results of Johansen Cointegration test (trace statistics) Trend assumption: Linear deterministic trend Series: LogFDI, LogGDP, LogGR, LogPCY, LogOPEN, LogM, LogEXRATE Lags interval (in first differences): 1 to 1 Unrestricted Cointegration Rank Test (Trace) Hypothesized No. of CE (S)

Eigenvalue

Trace Statistic

0.05 Critical value

Prob.**

None* At most At most At most At most At most At most

0.0889845 0.748009 0.545852 0.332793 0.232421 0.191925 0.010308

168.5182 97.93043 53.82282 28.56419 15.61523 7.150783 0.331581

125.6154 95.75366 69.81889 47.85613 29.79707 15.49471 3.841466

0.0000 0.0351 0.4692 0.7886 0.7390 0.5602 0.5647

1* 2 3 4 5 6

Trace test indicates 2 cointegrating eqn(s) at the 0.05 level * Denotes rejection of the hypothesis at the 0.05 level ** MacKinnon-Haug-Michelis (1999) p-values Source Author’s computation by using EViews-6

Table 2.5 Results of Johansen Cointegration test (maximum Eigenvalue) Hypothesized No. of CE (S)

Eigenvalue

Max-Eigen Statistic

0.05 Critical value

Prob.**

None* At most At most At most At most At most At most

0.0889845 0.748009 0.545852 0.332793 0.232421 0.191925 0.010308

70.58779 44.10762 25.25862 12.94897 8.464446 6.819202 0.331581

46.23142 40.07757 33.87687 27.58434 21.13162 14.26460 3.841466

0.0000 0.0167 0.3677 0.8877 0.8731 0.5107 0.5647

1* 2 3 4 5 6

Trace test indicates 2 cointegrating eqn(s) at the 0.05 level * Denotes rejection of the hypothesis at the 0.05 level ** MacKinnon-Haug-Michelis (1999) p-values Source Author’s computation by using EViews-6

Empirical Results and Discussion Table 2.3 demonstrates the results of unit roots of four variables such as FI, Y, financial deepening and trade openness. Since four variables are stationary after first differencing, it is now appropriate to test whether four

46

M. PAL

Table 2.6 Pairwise Granger causality tests Sample: 1971–2013 Lags: 2 Null Hypothesis: LogEXRATE does not Granger Cause LogFDI LogFDI does not Granger Cause LogEXRATE LogGDP does not Granger Cause LogFDI LogFDI does not Granger Cause LogGDP LogPCY does not Granger Cause LogFDI LogFDI does not Granger Cause LogPCY LogGR does not Granger Cause LogFDI LogFDI does not Granger Cause LogGR LogM does not Granger Cause LogFDI LogFDI does not Granger Cause LogM LogOPEN does not Granger Cause LogFDI LogFDI does not Granger Cause LogOPEN LogGDP does not Granger Cause LogEXRATE LogEXRATE does not Granger Cause LogGDP LogPCY does not Granger Cause LogEXRATE LogEXRATE does not Granger Cause LogPCY

Obs

F-statistic

Prob.

38

8.56096*

0.0010

0.34261

0.7124

0.79695

0.4592

2.29400

0.1167

0.35641

0.7028

2.33117

0.1130

1.30843

0.2868

3.35816

0.0498

0.82098

0.4488

1.18077

0.3197

0.62282

0.5426

4.89981**

0.0137

0.19249

0.8257

1.96357

0.1551

7.45281*

0.0020

1.26550

0.2943

EXr → FDI 38

FDI → GDP 38

FDI → PCY 32

FDI → Gr 38

38

FDI → TO 41

41

PCY → EXr

(continued)

2

MACRODETERMINANTS OF FDI IN INDIA …

47

Table 2.6 (continued) Sample: 1971–2013 Lags: 2 Null Hypothesis: LogGR does not Granger Cause LogEXRATE LogEXRATE does not Granger Cause LogGR LogM does not Granger Cause LogEXRATE LogEXRATE does not Granger Cause LogM LogOPEN does not Granger Cause LogEXRATE LogEXRATE does not Granger Cause LogOPEN LogPCY does not Granger Cause LogGDP LogGDP does not Granger Cause LogPCY LogGR does not Granger Cause LogGDP LogGDP does not Granger Cause LogGR LogM does not Granger Cause LogGDP LogGDP does not Granger Cause LogM

LogOPEN does not Granger Cause LogGDP LogGDP does not Granger Cause LogOPEN LogGR does not Granger Cause LogPCY

Obs 35

EXr → Gr 41

41

41

PCY → GDP 35

Y → Gr 41

M → GDP GDP → M 41

TO → GDP 35

F-statistic

Prob.

1.44253

0.2523

3.57976

0.0403

1.04611

0.3617

1.23017

0.3042

1.67560

0.2015

1.47321

0.2427

8.62502*

0.0009

1.71311

0.1947

0.83765

0.4426

3.19084

0.0554

2.03025

0.1461

3.53332

0.0397

3.38922

0.0448

0.95441

0.3946

2.00630

0.1521

(continued)

48

M. PAL

Table 2.6 (continued) Sample: 1971–2013 Lags: 2 Null Hypothesis:

Obs

LogPCY does not Granger Cause LogGR LogM does not Granger Cause LogPCY LogPCY does not Granger Cause LogM LogOPEN does not Granger Cause LogPCY LogPCY does not Granger Cause LogOPEN LogM does not Granger Cause LogGR LogGR does not Granger Cause LogM LogOPEN does not Granger Cause LogGR LogGR does not Granger Cause LogOPEN LogOPEN does not Granger Cause LogM LogM does not Granger Cause LogOPEN

PCY → Gr 41

PCY → M 41

35

M → Gr 35

41

F-statistic

Prob.

7.77722*

0.0019

2.20502

0.1249

4.63168**

0.0162

1.75355

0.1876

1.08681

0.3481

3.30243

0.0506

0.34939

0.7079

2.44004

0.1043

0.23453

0.7924

3.75047

0.0331

0.14471

0.8658

TO → M Note Significance at the 1%, 5% and 10% level is indicated by *, ** and ***, respectively Source Author’s computation by using EViews-6

macrovariables have any long-run association? The first step of Johansen and Juselius cointegration procedure is to determine the lag order, and then, we use the cointegration test to check the long-run relationship among the four variables. Table 2.7 and Table 2.8 demonstrate the results of the cointegration tests for four variables such as FI, GDP growth rate, M3/GDP ratio and X + M/GDP ratio. From the results, we find that trace test and maximum eigenvalue both indicate 2 cointegrating equations at 5% level of significance. These results show long-run relationship

2

MACRODETERMINANTS OF FDI IN INDIA …

49

Table 2.7 Johansen cointegration: multivariate model Series: LogFI, LogY, Log TO, LogM3/GDP Hypothesized No. of CE(s)

Eigenvalue

Trace Statistic

0.05 Critical value

Prob.**

None* At most 1* At most 2 At most 3

0.893471 0.754532 0.117909 0.021682

79.61750 32.59132 3.094981 0.460331

47.85613 29.79707 15.49471 3.841466

0.0000 0.0232 0.9625 0.4975

Trace test indicates 2 cointegrating eqn(s) at the 0.05 level * Denotes rejection of the hypothesis at the 0.05 level ** MacKinnon-Haug-Michelis (1999) p-values Source Author’s computation by using EViews-6

Table 2.8 Johansen cointegration (maximum eigenvalue)

unrestricted

cointegration

rank

test

Hypothesized No. of CE(s)

Eigenvalue

Max-Eigen Statistic

0.05 Critical value

Prob.**

None* At most 1* At most 2 At most 3

0.893471 0.754532 0.117909 0.021682

47.02617 29.49634 2.634650 0.460331

27.58434 21.13162 14.26460 3.841466

0.0001 0.0026 0.9680 0.4975

Maximum eigenvalue test indicates 2 cointegrating Eqn(s) at the 0.05 level * Denotes rejection of the hypothesis at the 0.05 level ** MacKinnon-Haug-Michelis (1999) p-values Source Author’s computation by using EViews-6

among the four variables of the model. Table 2.9 also shows positive Granger causality tests.

2.6

Conclusions

This chapter attempts to test empirically the potential determinants of FDI in India with the help of new time-series methodology. This chapter takes into account testing empirically two models. Model 2.1 includes seven variables such as FDI, trade openness, financial deepening, GDP, growth rate, PCY and nominal exchange rate. After confirming the order of integration, we find two cointegrating equations and rejects null

50

M. PAL

Table 2.9 Granger causality tests Null Hypothesis

Obs

F-statistic

Prob.

LogGDP does not Granger Cause Log INVESTMENT LogINVESTMENT does not Granger Cause LogGDP

31

2.77833

0.0921

0.22864

0.7982

3.99701

0.0356

0.72632

0.4966

1.33276

0.2873

1.53408

0.2412

3.29140

0.0515

0.94253

0.4013

3.26143

0.0528

0.36763

0.6956

0.73794

0.4854

4.47527

0.0186

LogOPENN does not Granger Cause LogINVEST LogINVESTMENT does not Granger Cause LogOPENNESS LogM3 does not Granger Cause LogINVEST LogINVESTMENT does not Granger Cause LogM3 LogOPENNESS does not Granger Cause LogGDP LogGDP does not Granger Cause LogOPENNESS LogM3 does not Granger Cause LogGDP LogGDP does not Granger Cause LogM3 LogM3 does not Granger Cause LogOPENNESS LogOPENNESS does not Granger Cause LogM3

GDP → INVSET 34

OPEN → INVEST 34

34

OPEN → GDP 34

M3 → GDP 40

M3 → OPEN Notes Significance at the 1%, 5% and 10% level is indicated by *, ** and ***, respectively Source Author’s computation by using EViews-6

hypothesis of no cointegration and shows long-run relationship among variables. Model 2.2 includes only four variables such as FI, GDP growth rate, financial deepening and trade openness. We find two cointegrating equations. In this model, trace statistic and maximum eigenvalues are more than their critical value at low probability value. Then, we find pairwise Granger causality in the number of variables and find the desired results. GDP, growth rate, financial deepening and trade openness have

2

MACRODETERMINANTS OF FDI IN INDIA …

51

been explored as potential determinants to attract FDI and foreign investment both. More emphasis should be given on increasing the level of four variables as pointed out above.

Appendix: IMF-World Bank SAP---An Application to India SAP includes two namely stabilization programs which are applied by the IMF and Structural Adjustment Lending (SAL) performed by the World Bank. Before 1985, World Bank and IMF were two separate institutions and their functions were totally different. Before 1985, there were two types of conditionalities, i.e. IMF conditionality and World Bank conditionality. IMF conditionality is based on macroeconomic conditions which include low fiscal deficit, low DSR, low debt/GDP ratio, low current account deficit, competitive exchange rates and comfortable level of foreign exchange as a safety device to control the economic crisis, while the World Bank conditionality is based on microlevel, i.e. project and sector level, which includes that funds should be utilized for actual purpose and no diversion of funds is allowed, and also, there is no place for the policy of economic distortions in the economy. If a crisis-ridden country needs a loan from World Bank, the country concerned has to take permission from the IMF, and then, the IMF provides a certificate to the country concerned. Whether a country is eligible for a loan or not, the amount of conditionality may be 10–50% of the total adjustment loan. Now, generally, the IMF loan-seeking nations have been put under this type of conditionality. In the year of 1990–1991, Indian Government received a loan under joint operation of Fund-Bank SAP program. In the late 1980s, India was heading toward severe economic crisis, and ultimately, in the year of 1989, India had to face a problem of likely default, because India was declared as low credit worth nation by the credit rating agencies such as Moody and Standard and Poor. IMF provided a loan amounting to US $2.5 Billion; however, India recovered her economy very soon and achieved strong economic fundamentals for further sustainable development path. Pal (2016) examined the IMF conditionality in India and found India as success story of IMF stabilization for comprehensive survey on IMF conditionality in India, see Pal (2001, 2016). Under SAL operation India undertook financial sector reform program in addition to other programs such as trade openness and capital account

52

M. PAL

liberalization. Before 1990, India had the problem of Financial Repression; however, after New Economic Policy of 1991 Financial Repression, it has been rolled back and due to that reason financial deepening that is M3/GDP ratio, a well-researched indicator, increased from 50% in 1991 to around 80% in 1992. Pal (2014c) empirically examines the finance-led growth hypothesis in India, Zambia and South Africa. In case of India, he traces the long-run and positive relationship between the M3/GDP ratio and growth rate with the help of cointegration technique for the period from 1971 to 2012. He concludes that 1% increase in the level of M3/GDP ratio causes growth rate to rise by 0.54%. For theoretical and empirical discussion on the issue of Finance-Led Growth hypothesis in India, see Pal (2013, 2014a, b).

Notes 1. For comprehensive survey on the determinants of FDI in the developing countries, see De Mello (1997). 2. India joined Multilateral Investment Guarantee Agency (MIGA) in April 1992. MIGA is an insurance window of the World Bank which was established in 1988. It does not provide loan to any country, but it provides guarantee for undertaking non-commercial risks. Now, the MIGA has 179 member governments, consisting of 152 developing and 25 industrialized countries as on June 30, 2017. There are two types of risks such as commercial risk and non-commercial risk. Commercial risks are insurable while non-commercial risks are non-insurable, e.g. political risk, civil disturbance, war and strike, etc. Hence, the MIGA undertakes non-commercial risks to promote private investment in developing countries, especially in risky countries where high investment risk is involved. 1980s decade was called as the “Lost Decade” when the three countries, Mexico, Brazil and Argentina (MBA), put the entire world into external debt crisis, because these three nations were not ready to repay their loans, and in this way, private investors lost their confidence in developing countries and thus private investment declined. In the initial stage, India was reluctant to join MIGA because of her political reasons, but later keeping in view the cost and benefit, Indian Government decided to join MIGA in April 1992 under the New Economic Policy of 1991. 3. Foreign Exchange Regulation Act (FERA) of 1973 was relaxed under New Economic Policy of 1991. The Act came into force to regulate foreign payments, currency import and export, securities and purchases of fixed assets by foreigners. Later on Foreign Exchange Management Act (FEMA)

2

4.

5.

6.

7.

MACRODETERMINANTS OF FDI IN INDIA …

53

replaced the FERA. The Tarapore Committee (1997) recommended FEMA to regulate foreign exchange in the country. IMF has advanced a number of loans to India to meet economic crises. In 1989, India had serious economic crisis and was likely to default on her foreign obligations. At the same time, Bank of England came to help India, and India had to put some amount of gold to save her position, but at the same time the IMF came into picture and saved India’s position by giving loan of US $2.5 Billion for stabilization and structural adjustment program (SAP). The outcome of this macroeconomic crisis management proved to be fruitful, see Appendix. Mauritius has low rates of taxation and an agreement with India on Double Tax Avoidance Agreement (DTAA), and due to that reason numbers of multinational corporations have set up their head offices in Mauritius before investing in Indian economy. For detailed discussion on the issues of repatriation and reinvested earning of FDI in general, see Thrilwall (1989, 592–596), while particularly for India, see, Industrial Policy 2017, a Discussion Paper, Department of Industrial Policy and Promotion, Ministry of Commerce and Industry, New Delhi, and Challapati Rao et al. (1999). Foreign portfolio investments in India include investments in ADRs, GDRs, FIIs. Before 1992, Non-Resident Indians (NRIs) and Overseas Corporate Bodies only were allowed to enter in FPI in September 1992. It is significant to note that FIIs were also allowed to participate in primary and the secondary market of Indian stock market.

References Adeolu, B. A. 2007. Foreign direct investment and economic growth evidence from Nigeria: African Economic Research Consortium. Research Paper 165. Agarwal, J.P. 1980. Determinants of foreign direct investment: A survey. Welwirtschaftliches Archiv 116 (4): 739–773. Aggarwal, P. 2000. Economic impact of foreign direct investment in South Asia. Indira Gandhi Institute of Development Research, Mumbai. Ali, S., and W. Guo. 2005. Determinants of FDI in China. Journal of Global Business and Technology 1 (2): 21–33. Ang, J.B. 2008. Determinants of foreign direct investment in Malaysia. Journal of Policy Modeling 30 (1): 185–189. Asiedu, E. 2002. On the determinants of foreign direct investment to developing countries: Is Africa different? World Development 30 (1): 107–119. Aziz, G.O., and A. Mishra. 2015. Determinants of FDI inflows to Arab countries. Journal of International Trade and Economic Development 25 (3): 1–32.

54

M. PAL

Bacha, E.L. 1987. IMF conditionality: Conceptual problems and policy alternatives. World Development 15 (12): 1457–1487. Bacha, E.L. 1990. A three gap model of foreign transfers and GDP growth rate in developing countries. Journal of Development Economics 32 (2): 279–296. Balsubramanyam, V.N., and D. Sapsford. 2007. Does India need a lot more FDI? Economic and Political Weekly 42 (17): 1549–1555. Bell, C., and P.L. Rousseau. 2001. Post-independence India: A case of finance-led industrialization? Journal of Development Economics 65 (1): 153–175. Bende, N.A. 2002. FDI determinants in Sub Sahara Africa, a cointegration. Economic Bulletin, Access Economy 6 (4): 1–19. Bery, S. 2010. Who “Owns” the foreign exchange reserves? Economic and Political Weekly 45 (11): 1–10. Bevan, A., and S. Estrin. 2004. The determinants of foreign direct investment into European transition economies. Journal of Comparative Economics 32 (4): 775–787. Bhanumurthy, K.V., and M.K. Sihna. 2015. Inward foreign direct investment and economic development: A global perspective. Journal of International Business 2 (1): 53–75. Bhavan, T. 2011. Determinants and growth effect of FDI in South Asian economics: Evidence from a panel data analysis. International Business Research 4 (1): 43–50. Blonigen, B.A. 2005. A review of empirical literature on FDI determinants. Atlantic Economic Journal 33 (4): 383–403. Boateng, A. 2015. Examining the determinants of inward FDI: Evidence from Norway. Economic Modelling 47 (C): 118–127. Casi, L., and L. Resmin. 2010. Evidence on the determinants of foreign direct investment: The case of EU regions. Eastern Journal of European Studies 1 (2): 93–118. Chakrabarti, A. 2001. The determinants of foreign direct investment: Sensitivity analysis of cross-country regression. Kyklos 54 (1): 89–114. Chakraborty, C., and P. Basu. 2002. Foreign direct investment and growth in India: A cointegration approach. Applied Economics 34 (9): 1061–1073. Chaudhuri, S., and U. Mukhopadhyay. 2014. Foreign direct investment in developing countries—A theoretical evaluation. New Delhi: Springer. Das, K.C. 2013. Home country determinants of outward FDI from developing countries. Margin, the Journal of Applied Economic Research 7 (1): 93–116. De Mello, L.R., Jr. 1997. Foreign direct investment in developing countries and growth: A selective survey. The Journal of Development Studies 34 (1): 1–34. Demirhan, E., and M. Masca. 2008. Determinants of foreign direct investment flows to developing countries: A cross-sectional analysis. Prague Economic Papers 4: 356–369.

2

MACRODETERMINANTS OF FDI IN INDIA …

55

D’Souza, E. 2008. Globalisations’s underbelly: Capital flows and Indian economy. Economic and Political Weekly 43 (35): 34–38. Dua, P., and A.I. Rashid. 1998. Foreign direct investment and economic activity in India. Indian Economic Review 33 (2): 153–168. Dua, P., and R. Garg. 2013. Foreign portfolio investment flows to India— Determinants and analysis. Working papers 225, Centre for development economics, Delhi School of Economics. D.U: 1–36. Dua, P., and R. Garg. 2015. Macroeconomic determinants of foreign direct investment: Evidence from India. The Journal of Developing Areas 49 (1): 133–155. Dunning, J.H. 1977. Trade, location of economy activity and the MNE: A search for an eclectic approach. In International allocation of economic activity, ed. B. Ohlin et al., 395–418. London: Macmillan. Dunning, J.H. 1988. The eclectic paradigm of international production: A restatement and some possible extensions. Journal of International Business Studies 19 (1): 1–31. Dunning, J.H. 1993. Multinational enterprises and the global economy: Readings. Wisely, UK: Addison. Durham, J.B. 2004. Absorptive capacity and the effects of foreign direct investment and equity foreign portfolio investment on economic growth. European Economic Review 48 (2): 285–306. Franking, R., and A. Ahmad. 1979. Empirical determinants of manufacturing direct foreign investment in developing countries. Journal of Economic Development & Cultural Change 27 (4): 751–767. Gang, I.N., and M.A. Khan. 1990. Some determinants of foreign aid to India, 1960–1985. World Development 16 (3): 431. Ghatak, S., and U. Utkulu. 1995. Trade liberalization and endogenous growth: The Asian experience: Turkey, Malaysia and India, IIDS Conference; Swedish Academy of Science, Helsinki, 1–33. Ghosh, J. 1991. Foreign private investment without illusions. Economic and Political Weekly 26 (42): 2397–2398. Glauco, D., et al. 2008. Determinants of capital flows to developing countries; A structural VAR analysis. Journal of Economic Studies 35 (4): 304–322. Gordon, M.J.P.F., and M.P. Gupta. 2003. Portfolio inflows into India: Do domestic fundamentals Matter? IMF Working Paper 20: 1–37. Gould, D.M., et al. 2014. Attracting foreign direct investment: What can South Asia’ lack of success teach other developing countries? South Asia Economic Journal 15 (1): 133–174. Guris, S., and K. Gozgor. 2016. Trade openness and FDI inflows in Turkey. Applied Econometrics and International Development 15 (2): 53–62. Hara, M., and I.F. Razafimahefa. 2005. The determinants of foreign direct investments into Japan. Kobe University Economic Review 51: 21–34.

56

M. PAL

Hasan, Z. 2004. Determinants of FDI flows to developing economies: Evidence from Malaysia. In Foreign investment in developing countries, ed. H.S. Kehal, Chapter 8, 154–170. Basingstoke: Palgrave Macmillan. Industrial Policy. 2017. A discussion paper. Department of Industrial Policy and Promotion, Ministry of Commerce and Industry, Government of India, New Delhi. Janicki, H.P., and P.V. Wunnava. 2004. Determinants of foreign direct investment: Empirical evidence form EU accession candidates. Applied Economics 36 (5): 505–509. Jayasekara, S.D. 2014. Determinants of foreign direct investment in Sri Lanka. Journal of the University of Ruhana 2 (1–2): 4–13. Johansen, S. 1991. Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica 59 (6): 1551–1580. Johansen, S., and K. Juselius. 1990. Maximum likelihood estimation and inference on cointegration – with application to the demand for money. Oxford Bulletin of Economics and Statistics 52 (2): 169–210. Joshi, V., and S. Sanyal. 2004. Foreign inflows and macroeconomic policy in India, India Policy Forum, Brookings Institution, Washington, DC and National Council of Applied Economic Research, (NCAER). New Delhi 1 (1): 135–188. Kameniky, O., and M. Kumho. 2014. Trade openness and exchange rate regime. Journal of Money, Credit and Banking 46 (8): 1657–1659. Kant, C. 1966. Foreign direct investment and capital flight, Princeton Studies in International Finance, Department of Economics. USA: Princeton University. Kavinthirakumarn, K., et al. 2015. Determinants of foreign direct investment in Sri Lanka. South Asia Economic Journal 16 (2): 233–256. Khan, M. 1998. Capital flows to developing countries: Blessing or curse? The Pakistan Development Review 37 (4): 125–151. Khan, M.S., P.J. Montiel, and N.U. Haque. 1990. Adjustment with growth: Relating to analytical approaches of the IMF and the World Bank. Journal of Development Economics 32 (1): 155–180. Khan, R.E., and M.A. Nawaz. 2010. Economic determinants of foreign direct investment in Pakistan. Journal of Economics 1 (2): 99–104. Khanindra, C.D. 2013. Home country determinants of outward FDI from developing countries. The Journal of Applied Economic Research 7 (1): 93–116. Kumar, N. 1998. Liberalisation and changing patterns of foreign direct investments; has India’s relative attractiveness as a host of FDI improved? Economic and Political Weekly 33 (22): 1321–1329. Kumar, N. 2002. Globalisation and the quality of foreign direct investment. New Delhi: Oxford University Press.

2

MACRODETERMINANTS OF FDI IN INDIA …

57

Lal, D., and D.K. Joshi. 1994. From closed to open economy macroeconomics; The real exchange rate and capital inflows. Working Paper No. 51, NCAER, New Delhi. Liu, H., et al. 2020. Does financial deepening attracts foreign direct investment? Fresh evidence from panel threshold analysis, Research in International Business and Finance, 53. Masayuki, H., and F. Ivohasina. 2005. The determinants of foreign direct investment into Japan. Kobe University Economic Review 51. Ministry of Finance. 2004. Report of the committee on liberalisation of foreign institutional investment. Chaired by Ashok Lahiri, Government of India, New Delhi. Ministry of Finance. 2005. Report of the expert group on encouraging FII flows and checking the vulnerability of capital markets to speculative flows. Chaired by Ashok Lahiri, Government of India, New Delhi Ministry of Finance. 2010. Report of working group on foreign investment. Department of Economic Affairs, Ministry of Finance, New Delhi. Mishra, B.R. 2013. Estimating country specific determinants of FDI flows in India: Evidence from VAR and innovation accounting model. In Foreign direct investment, trade and economic growth: Challenges and opportunities, ed. Shahid Ahmad. New Delhi: Routledge. Mottaleb, K.A., and K. Kalirajan. 2010. Determinants of foreign direct investment in developing countries a comparative analysis. Margin, Journal of Applied Economic Research 4 (4): 369–404. Nasser, O.M.A., and X.G. Gomez. 2009. Do well-functioning financial systems affect the FDI flows to Latin America? International Research Journal of Finance and Economics 29: 60–75. Nayak, R.K. 2012. Determinants of foreign direct investment: Empirical investigation into post-reform era. Artha Vijnana LIV (4): 491–498. Nayyar, D. 1995. Economic liberalization in India: Analytics experience and lesson. Calcutta: Orient Longman. Neelakanta, N.T. 2013. Relationship between FDI, environment and economic growth in India: An application of ARDL approach. In Econometric application in management the Indian Econometric Society (TIES) annual conference proceedings, ed. K.C. Sharma et al. Delhi: National Publishing House. Nonnemberg, M.B., and M.J. Cardoso de Mendonca. 2004. The determinants of foreign direct investment in developing countries. http://www.anpec.org.br/ encontro2004/artigos/A04A061.pdf Nurudeen, A., and O.G. Wafurea. 2010. Determinants of foreign direct investment in Nigeria: An empirical analysis. Global Journal of Human Social Science 10 (1): 26–34. Pal, M. 1993. Stabilization & structural adjustment reforms in India—An econometric analysis. Paper presented at Second International Conference

58

M. PAL

on Development and Future Studies at The University of Western Australia, Perth, 13–15 December. Pal, M. 2013. Finance-growth nexus in India: Evidence from cointegration & VECM. In Econometric application in management, annual conference proceedings (TIES), ed. R.C. Sharma and S.K. Garg, 16–32. Delhi: National Publishing House. Pal, M. 2014a. Financial development in India: An empirical test of the McKinnon-Shaw model. In Analytical issues in trade, development and finance, ed. A.N. Ghoh and A.K. Karmakar, 405–420. New Delhi: Springer. Pal, M. 2014b. Financial policy of India-theory and evidence from cointegration, H.R Journal of Management 7 (1): 1–27. Ghaziabad, India. https://papers. ssrn.com/sol13/papers.cfm?abstract_id=253633. Pal, M. 2014c. Determinants of FDI in India (revisited): An evidence from cointegration & causality. Paper presented at the 97th Annual Conference of Indian Economic Association at Mohanlal Sukhadia University, Udaipur, 27–29 December. Pal, M. 2016. The IMF conditionality: Theory and application in India. In International monetary system past, present and future, ed. D. Bhowmik, 72–98. New Delhi: Regal. Pal, M. 2001. The monetary model: Theory, evidence and validity in developing countries. In International institutions and economic development of under developed countries, ed. M.R. Agarwal, 149–163. New Delhi: Deep and Deep. Pal, P. 2005. Volatility in the stock market in India and foreign institutional investors: A study of the post-election crash. Economic and Political Weekly 40: 765–772. Pattnaik, R.K., and S.N.V. Kumar. 2011. Foreign Institutional Investor (FII) flows: Some Indian perspectives. Foreign Trade Review 46 (1): 3–23. Pesaran, H.M., et al. 2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrices 16 (3): 289–326. Piteli, E.N. 2010. Determinants of foreign direct investment in developed economies: A comparison between European and Non-European countries. Contributions to Political Economy 29 (1): 111–128. Pradhan, R.P. 2008. Does infrastructure play a role in foreign direct investment?, VI (2): 48–60. The ICFAI University Press. Rao, K.S. Chalapati, M.R. Murthy, and K.V.K. Ranganathan. 1999. Foreign direct investment in India since liberalisation: An overview. Journal of Indian School of Political Economy 11 (3): 423–454. Ramasamy, B., and Y. Matthew. 2010. The determinants of foreign direct investment in services. The World Economy. Ravinthirakumaran, K., et al. 2015. Determinants of foreign direct investment in Sri Lanka. South Asia Economic Journal 16 (2): 233–256.

2

MACRODETERMINANTS OF FDI IN INDIA …

59

Rodriguez, X., and J. Pallas. 2008. Determinants of foreign direct investment in Spain. Applied Economics 40 (19): 2443–2450. Rubio, O.B., and S.S. Rivero. 1994. An econometric analysis of foreign direct investment in Spain, 1964–89. Southern Economic Journal, 61(1). Ruiz IC (2005) Exchange rate as a determinant of foreign direct investment: Does it really matter? Theoretical Aspects, Literature Review and Applied Proposal, Ecos de Economía No. 21 Medellín, Sahoo, P., and R.K. Dash. 2012. Economic growth in South Asia: Role of infrastructure. The Journal of International Trade & Economic Development 21 (2): 217–252. Sahoo, P., G. Natraj, and R.K. Dash. 2014. Foreign direct investment in South Asia, policy, impact, determinants and challenges. New Delhi: Springer. Schneider, F., and B.S. Frey. 1985. Economic and political determinants of foreign direct investment. World Development 13 (2): 161–175. Schumpeter, J.A. 1911. The theory of economic development: An enquiry in to profits, capital, credit and the business cycle, reprinted in 1951. New York: Oxford University Press. Shah, Z., and M. Qazi. 2003. The determinants of foreign direct investment in Pakistan: An empirical Investigation. The Pakistan Development Review 42 (4): 697–714. Shahid, H.M. 2012. An unsupervised approach to develop stemmer. International Journal on Natural Language Computing (IJNLC) 1 (2): 15–23. Singhania, M., and A. Gupta. 2011. Determinants of FDI in India. Journal of International Trade, Law & Policy 10 (1): 64–82. Sinha, C., and K. Sen. 2016. The determinants of foreign direct investment: An analytical survey. In International trade and international finance explorations of contemporary issues, ed. M. Roy and S. Saikat, 333–362. Springer. Srivastava, S. 2003. What is the true level of FDI flows to India? Economic and Political Weekly 36 (12): 1201–1209. Summer, R., and A. Heston. 1993. Penn World tables, an expanded set of international companies, 1950–1988. Quarterly Journal of Economics 106 (2): 327–368. Tatoglu, E., and F. Erdal. 2002. Locational determinants of foreign direct investment in an emerging market economy: Evidence from Turkey. Multinational Business Review 10 (1). Thrilwall, A.P. 1989. Growth and development (with special reference to developing economies). Palgrave. UN Centre on Transnational Corporations. 1999. World Investment Report. Foreign Direct Investment and Challenge of Development, UNCTAD, Geneva.

60

M. PAL

Verma, S., and R. Arora. 2009. Foreign direct investment and economic growth in India: A macroeconomic appraisal. Asian Economic Review 51 (2): 229– 248. Walsh, J.P., and J. Yu. 2010. Determinants of foreign direct investment a sectoral and institutional approach. Working Paper No. 187, IMF. Washington, DC. Wijeweera, A., and S. Mounter. 2008. A VAR analysis on the determinants of FDI inflows: The case of Sri Lanka. Applied Econometrics and International Development 8 (1): 189–198. Williams, M., and A. Scaperlanda. 1995. The determinants of capital intensity in foreign-owned manufacturing across U.S. Regions. Review of Urban & Regional Development Studies. Yves, B., and F. Hans. 2006. Emigrants’ remittances and Dutch Disease in Cape Verde. International Economic Journal 20 (3): 267–284.

CHAPTER 3

FDI-Growth Nexus in India: Cointegration and Causality

3.1

Introduction

During the recent decades, a number of emerging and middle-income countries, notably China, Malaysia, India, Sri Lanka, Nigeria, etc., have changed their conservative ideology which was based on imperialistic ideology and have realized the pros and cons of private foreign capital which mainly includes FPI and FDI. A radical shift from debt creating to non-debt creating capital has taken place in these middle-income countries. Main factors behind policy change has been financial globlalization which opened the new channels of trade, finance and foreign capital flows to Foreign Aid dependent and recipient, now emerging nations. Over the period, a tough competition has taken place in emerging and FDI seeking nations how to attract more and more FDI and FPI and also to examine the long-run relationship and causal direction on their economic growth rate and overall economic development. For comprehensive survey on the theory and empirics, see Dua and Rashid (1998).1 During the last one and half decades, the worldwide debate on the issue of determinants of FDI and FDI-Growth nexus has invited an alarming situation in terms of studies undertaken by the economists, academic researchers and empirical experiments. These studies take into account theory and empirics with the application of modern time-series methodology. This emerging literature has become an hindrance for the policy makers how to take decisions on the validity of FDI in flows in the host countries, because of inclusive decision. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. Pal, Foreign Capital and Economic Growth in India, https://doi.org/10.1007/978-981-99-2299-4_3

61

62

M. PAL

3.2

FDI-Growth Nexus: Some Theory

The neo-classical and endogenous growth theory spell out the basic foundation for the theoretical relationship between FDI and economic growth in the host countries. The neo-classical growth theory developed by Solow (1956) and which was derived from Cobb–Douglas production function is also known as exogenous theory. The theory emphasizes that FDI increases the level and volume (i.e. accumulation of capital) of foreign investment which is accompanied by the efficiency of investment in the long term and thus increases growth rate in the host country. While, on the other hand, endogenous growth theory developed by Romer (1986, 1990, 1994), Lucas (1988) tries to establish a relationship between increase in the level of FDI and economic growth through the provision of technology transfer, human resource development and increase in management skill. This topic has invited an intense debate during the last two decades. For comprehensive and good debate on the comparative advantages on the above two mentioned development theories, see Solow (1956), Romer (1990, 94), Lucas (1988) and Barro and Sala I Martin (1995). FDI-Growth nexus debate has taken two shapes: One school of thought is related to the long-run relationship between the FDI and growth and talk about the causal direction. These theoretical propositions about the positive and long-run relationship between FDI and economic growth are supported by the number of theoretical and empirical studies. Huang (2004); Rati and Zhang (2002); Zhang (2001, 1); Borensztein et al. (1998); De Mello (1999). Another school of thought has traced out a negative relationship between FDI and growth. Herzer et al. (2008); Chakraborty and Basu (2002); De Mello Jr. (1997); Mah (2010a, 2010b) find no support for FDI-Led growth hypothesis. In Chapter 2, we have already discussed the theory of major macrodeterminants of FDI and their empirical application in India with the help of Johansen Cointegration and Granger causality test. The basic purpose of this chapter is to trace the long-run relationship between the FDI and growth rate in India and also to see the direction of causality between these two important macrovariables for the period of 42 years from 1971 to 2013. Rest of the chapter is structured as: Section II deals with the survey on theoretical and empirical debate on the FDI-growth relationship and their causal direction, and Section III deals with model

3

FDI-GROWTH NEXUS IN INDIA: COINTEGRATION …

63

specification and discussion of empirical results. Section IV concludes the chapter.

3.3

Literature Review: Theory and Empirics

FDI-Growth nexus is based mainly on the two schools of thought: First school is FDI-led growth while second is Growth-led FDI. We have analyzed some important and path-breaking studies on FDI-Growth nexus. Following studies deal with some theory and empirics on the FDI-Growth nexus: Blomstrom, K. and Zejan (1992), De Mello (1997), Frankel (1999), Zhang (2002), Dunning (1977), Dunning, J.H. (1988), Chaudhuri, S. Mukhopadhyay, S. (2014), Sasi J. Raro (2015), Mahembe and Odhiambo (2014), Dogan, E (2014), Akinlo, E. A. (2004), Srinivasan, et al. (2012), Mah, S. Jai (2010a, 2010b), Herzer et al. (2008), Ilhan O. (2007), Hansen and Rand (2006), Adewumi (2006), Ahmad, et al. (2003), Basu et al. (2003), Chowdhury and Mavrotas (2003) and Zhang (2001). Blomstrom, K. and Zejan (1992) examine the issue of productivity which increases the spillover effects of the FDI. It is generally known fact that spillover effects are available when domestic firms in the host countries have increased the absorption generated by the backward and forward linkages.2 De Mello (1997) talks about two main channels such as labor training and skill enrichment and management practices through which FDI increases the productivity and economic growth in the host country. Frankel (1999) argue that FDI increases the growth through the creation of investment demand in terms of filling in saving and investment gaps. Zhang (2002) also pointed out the contribution of FDI to economic growth in terms of the provision of financial resources, transfer of technology, boosting competitive potentials and enhancing domestic savings and investment.3 Dunning (1977) developed a MNCs theory which is based on certain ownership and locational advantages in the host countries and also internationalizing the production process. In this way, these favorable factors serve as an important instruments in attracting the high volume of the FDI.4 In his another study, Dunning, J.H. (1988) examines the principle which analyzes economic rationality of organizations mainly MNCs. Chaudhuri, S. and Mukhopadhyay, S. (2014) provide the theoretical backdrop of the various facts of FDI which have been instrumental for making the suitable policies for foreign capital. According to these writers,

64

M. PAL

FDI inflows in the host economies work as a multipurpose tool for reducing the poverty level in terms of low saving, investment and low per capita income. Sasi J. Raro (2015) investigates FDI-growth relationship with the help of a simultaneous equation model by using cross-country data of 124 countries for the period 1971–2010. Results indicate that FDI impact is positively associated with economic growth. Dogan, E (2014) examines the causal relationship between FDI and GDP growth rate in Zambia with the help of Johansen Cointegration technique for the period of 1970– 2011. Two series show cointegration, which indicate the existence of long-run relationship between GDP growth rate and FDI. Granger causal direction exhibits unidirectional which runs from FDI to growth rate in Zambia. Mahembe and Odhiambo (2014) examine theoretical linkages between FDI and economic growth taking into account neo-classical/exogenous and endogenous development theories in a very systematic and scientific manner. They conclude that FDI contributes economic growth largely through the upgradation of technology management and organizational level in the host country. Akinlo, E. A. (2004) investigates the FDI-growth long-run relationship in Nigeria during the period of 1970–2009 with the help of VAR model. Estimation results show that real GDP oil FDI and non-oil FDI demonstrate long-run relationship and there is only unidirectional causality running from real GDP to non-oil FDI in the short run. Nonoil FDI has larger significant positive impact on economic growth than oil FDI. Srinivasan, et al. (2012) examine the long-run relationship and causal nexus between FDI and economic growth in ASEAN countries with the help of Johansen Cointegration technique and pairwise Granger causality test. They examine the long-run relationship between FDI and GDP for the five ASEAN countries, namely Indonesia, Malaysia, Philippines, Singapore and Vietnam. The empirical results of vector error correction model exhibit a long-run causality running from GDP to FDI for Indonesia, Philippines and Singapore. Mah, S. Jai (2010a, 2010b) has examined the relationship between FDI and economic growth as a case study of Korea with the help of cointegration; however, pairwise Granger causality does not run from FDI to per capita real GDP. However, reverse takes place that is per capita real GDP to FDI. Herzer et al. (2008) applied time-series techniques from 1970 to 2003 for 28 developing countries, 10 countries from Latin

3

FDI-GROWTH NEXUS IN INDIA: COINTEGRATION …

65

America, 9 countries from Asia and 9 countries from Africa. They found weak evidence that FDI enhances either a long-run or short-run GDP. Their findings indicate that there is no clear evidence about the impact of FDI on economic growth. Ilhan O. (2007) provides a detailed review of very important studies on the relationship and causal direction between FDI and GDP Growth taking into account the number of variables such as FDI, trade openness, investment climate and fiscal incentives, the quality of infrastructural facilities, tax incentives, market size, free trade zones, trade regime and human capital base in the host country. Further, financial market regulations, banking system, market size, regional integration arrangements and economic and /political stability are also potential determinants of FDI, which have a positive and significant impact on overall economic growth. He has examined 52 empirical studies on the issue of longrun relationship between FDI and economic growth. He reveals one important fact that out of 52 studies, 40 studies have shown positive and long-run relationship between FDI and growth in different set up of emerging, developing and developed countries. In his conclusions, he finds a consensus that has been reached among policy makers, academicians and practitioners that FDI has a positive and significant effect on economic growth. Hansen and Rand (2006) examine empirical relationship between FDI and GDP for 31 developing countries for the period from 1970 to 2000. They found that there is a cointegration relationship between FDI and GDP. Their findings also indicate that FDI inflows are positively correlated with GDP, whereas GDP has no long-run effect on FDI. Adewumi (2006) examined the contribution of FDI to economic growth in Africa using annual series, by applying time-series analysis from 1970 to 2003. He found that FDI contributes positively to economic growth in most of the countries, but it is not statistically significant. Ahmad, et al. (2003) examine the effects of trade openness in the Pakistan economy by taking into account both the trade and FDI-growth links. In their paper, they analyze the existence between export, FDI and domestic output in Pakistan over the period 1972–2001. They find the long-run relationship between FDI, export and growth. Their results support the export-led hypothesis but also the existence of FDI-Growth nexus. They find significant spillovers effect from FDI to domestic output. Basu P, Chakraborty C and Reagle, D (2003) in their paper examine bidirectional causal relationship between FDI and growth for a panel

66

M. PAL

of 23 developing countries within the framework of panel cointegration and their results exhibit a long-run cointegrating relationship between FDI and GDP after taking into account heterogeneous country effects. Further, the cointegrating vectors reveal bidirectional causality between GDP and growth for more open economies. They further also reveal the fact that less developed economies’ long-run causality runs from GDP to FDI. Chowdhury and Mavrotas (2003) examine causality detection between FDI and growth for the period of 1969–2000 in three countries, namely Chile, Malaysia and Thailand. All three countries are major recipients of FDI. Granger pairwise unidirectional causality runs from growth to FDI in the case of Chile while in the case of Malaysia and Thailand causal direction confirms bidirectional causality between FDI and economic growth.5 Zhang (2001) examines long-run causality based on an error correction model, which indicates a strong Granger-causal relationship between FDI and GDP growth. In six counties out of 11 countries studied, there is no cointegration relationship between the FDI and growth and only in one country Granger causality exists from FDI to growth. Rati R. and Zhang K. Honglin (2002) examine empirically FDI-Growth nexus for the decade of 1990s which attracted an explosive increase in the FDI flows in low-income, now emerging and the middle-income countries. 3.3.1

Indian Studies on FDI-Growth Nexus

Following Indian studies deal with some theory and empirics on the FDIGrowth nexus: Bhattacharya, B. and Mukherjee, J. (2016), Bains, P. and Kaur, S. (2016), Biswas, S. and Dasgupta, B. (2013), Kaushik et al. (2008), Chakraborty, C. and Nunnenkamp, P. (2008), Basu P. Nayak N.C. Vani A. (2007), Balasubramanyan, V.N. and Sapsford D (2007), and Chakraborty, C & Basu, P (2002). Bhattacharya, B. and Mukherjee, J. (2016) by using cointegration and Granger causality analysis take into account the number of macroeconomic variables such as Treasury bill rate, trade openness real GDP, exchange rate, inflation rate and US Dow Jones Index value to trace the long-run relationship with FDI in Indian economy. Bains, P. and Kaur, S. (2016) by using modern time-series technique for the period the 1991 to 2014 examine the existence of long-run relationship between FDI and

3

FDI-GROWTH NEXUS IN INDIA: COINTEGRATION …

67

growth and results also exhibit unidirectional causal direction running from growth to FDI in Indian economy. Biswas, S. and Dasgupta, B. (2013) estimate the causal direction for the period from 1997–98 to 2010–11 by using quarterly data between services driven growth and FDI inflow. Findings reveal unidirectional causal direction which runs from FDI to GDP growth. Kaushik et al. (2008) by using Johansen and Juselius’s cointegration analysis and a VECM model investigate the relationship between economic growth, export, growth instability and investment in India during the period of 1971–2005. There exists a long-run relationship among these variables and also exhibits causal flow is unidirectional Granger causality running from real exports to real GDP. Chakraborty, C. and Nunnenkamp, P. (2008) with the help of Granger causality tests examine the growth effect of FDI in India within a panel of cointegration framework. A growth effect of FDI varies across sectors in India. FDI in service sector has promoted growth in the manufacturing sector. Basu P., Nayak N.C. and Vani A. (2007) in their paper on FDI in India intend to study the qualitative shift in the FDI inflows in India. They say that India is not only cost effective but also a country of hot destination for research and development activities. Balasubramanyan, V.N. and Sapsford D (2007) in their study try to compare the level of FDI in India and China. Their results show that FDI in India is one-tenth of that in China. Chakraborty, C and Basu, P (2002) examine the two-way link between FDI and growth for India with the existence of two cointegrating vectors between GDP, FDI and the unit labor cost. Their VECM model reveals that FDI does not cause GDP in India but reverse takes place. Further, FDI reduces the labor cost which promotes the policy of labor displacement in India.

3.4 Model Specification and Empirical Discussion Keeping in mind the problems of cross-section and time-series studies, this chapter examines the impact of FDI on the economic growth in India. This study contributes to the existing literature in terms of its search for cointegrating relation and thereby estimating for policy conclusions. Unlike the previous studies, this chapter attempts to trace the relationship and also to detect the causal direction between economic growth and FDI only to see the direct nexus. Following research carried

68

M. PAL

out by the number of economists such as Dua and Rashid (1998). Chakraborty, C and Basu, P (2002) Chakraborty, C. and Nunnenkamp, P. (2008) Dogan, E (2014) Akinlo, E A (2013) Srinivasan, et al. (2012) Bains, P. and Kaur, S. (2016). We develop a single equation model to trace the relationship between FDI and GDP growth in India. Econometric Specification of the model Y = a + b(F D I ) + e

(3.1)

Log Specification of the model Log Y = a + bLog(F D I ) + e

(3.2)

Variables explanation and measurement. FDI stands for Net FDI inflow in US $ terms. Y stands for GDP Growth Rate. Net FDI is inflows in the Indian economy less outflows from the Indian economy of investments. It includes reinvestment of earnings, equity capital and also short-term and long-term capital. Net FDI variable has been used extensively in the literature to trace the long-run relationship between FDI and economic growth in the host economies. However, some studies have used Net FDI/GDP ratio and FDI stock as dependent variables to trace the long-run relationship between FDI and GDP growth rate. Figure 3.1 reflects the upward trend of GDP and FDI during the period of 1971 to 2013. Figures 3.2 and 3.4 show the Log level of FDI and GDP. Figures 3.3 and 3.5 show the first difference in level of the variables. Figure 3.6 shows the long-run relationship between FDI and growth rate of GDP. Figure 3.6 demonstrates log differences of FDI and growth rate. Further, Fig. 3.6 reflects the long-run behavior of both the variables. Deviation of variables from each other seems very high in the early period of study. However, after 1990s onward, deviations of both the variables from each other seem to be very less which demonstrates high effectiveness of FDI on the growth process in Indian economy. We can infer that there has been a long-run and positive relationship, however, weak. Table 3.1 and 3.2 report the values of the test statistics both on their level form and on their first difference level. It is found that the absolute value of the Log GDP and LogFDI is smaller than their critical values,

3

FDI-GROWTH NEXUS IN INDIA: COINTEGRATION …

69

50 40 30 fdi-bill

20

Growth Rate

10 0 1960

1970

1980

1990

2000

2010

2020

-10

Fig. 3.1 Trends of growth rate and net FDI level (US $ Billion) (1971–2013) (Source Author’s own work based on Table 2.1 and also HBS RBI and WDI [World Bank]) 12 10 8 6 4 2 0

75

80

85

90

95

00

05

10

Fig. 3.2 Plot of log FDI (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work)

implying that they are non-stationary in the level form. However, in the next step, test statistics of the variables in their first differences exceed the critical value irrespective of the test applied. Therefore, we can conclude that two variables are integrated of order one I (1). The ADF test for the variables in the level form is based on the inclusion of an intercept and a trend term.

70

M. PAL

1.5 1.0 0.5 0.0 -0.5 -1.0

1975

1980

1985

1990

1995

2000

2005

2010

Fig. 3.3 Plot of dlog FDI (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) 2.4 2.0 1.6 1.2 0.8 0.4 0.0

75

80

85

90

95

00

05

10

Fig. 3.4 Plot of log GDP (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work)

From Table 3.3 and 3.4, we find the existence of positive and long-run relationship between FDI and economic growth rate in India because the value of trace statistics and maximum eigenvalue is more than their critical value and their probability value is also very low. Table 3.5 demonstrates the pairwise Granger causality results which confirm our hypothesis of strong causal direction from FDI to Growth in India. Table 3.6 demonstrates the VECM results. Further, ECT term shows the minus sign which is correct sign as per economic theory. Its value is equal to –0.41 which shows that during one year period, the level of disequilibrium is corrected by 41%. Our VECM results show some important

3

FDI-GROWTH NEXUS IN INDIA: COINTEGRATION …

71

3 2 1 0 -1 -2 -3

80

75

85

90

95

00

05

10

Fig. 3.5 Plot of dlog GDP (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) 3 2 1 0 -1 -2 -3

75

80

85

90

DLOGFDI

95

00

05

10

DLOGGR

Fig. 3.6 Plot of log differences of FDI and growth rate (Source Author’s own work)

72

M. PAL

Table 3.1 ADF unit roots tests for stationary of variables

Variables

Log GDP level First Difference LogFDI Level First Difference

A.D.F

Conclusions

Without Trend

With Trend

−3.1296

−1.1515

−3.8939*

−5.5143*

−2.0492

−3.6702

−6.4771*

−6.1316*

1 (1)

1 (1)

Source Author’s own computation by using EViews-6 Notes (i) Critical value for ADF without Trend 1% (−3.6576); 5% (−2.9591); 10% (−2.6181). (ii) Critical values for ADF with Trend are: 1% (−4.2820) 5% (−3.55614) 10% (−3.2138) Significance at the 1%, 5% and 10% level is indicated by *, ** and ***, respectively

Table 3.2 Results of Phillips-Perron (PP) unit root test

Variables

Log GDP level First Difference LogFDI Level First Difference

Phillips-Perron

Conclusions

Without Trend

With Trend

−3.4932

−1.3786

−5.5947*

−7.4116*

−2.2170

−3.7091

−6.5323*

−6.1659*

1(1)

1 (1)

Source Author’s own computation by using EViews-6 Notes Without Trend:−1% (−3.6537) 5% (−2.9514), 10% (−2.6171) With Trend:-1% (−4.712) 5% (−3.5562), 10%(−3.2109) Significance at the 1%, 5% and 10% level is indicated by *, ** and ***, respectively

features: (a) GDP in India is Granger caused by FDI. (b) The pairwise Granger causality runs more from FDI to GDP. (c) FDI tends to increase the productivity in Indian economy.

3

FDI-GROWTH NEXUS IN INDIA: COINTEGRATION …

73

Table 3.3 Results of Johansen cointegration test (trace statistics) for FDI and growth Included observations: 32 after adjustments Trend assumption: Linear deterministic trend Series: Log GR Log FDI Lags interval (in first differences): 1 to 1 Unrestricted Cointegration Rank Test (Trace) Hypothesized Trace No. of CE(s) Eigenvalue Statistic None * 0.475780 21.24468 At most 1 0.017891 0.577690

0.05 Critical Value 15.49471 3.841466

Prob.** 0.0061 0.4472

Source Author’s own computation by using EViews-6 Trace test indicates 1 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values

Table 3.4 Results of Johansen cointegration test (maximum eigen statistics) for FDI and economic growth Hypothesized No. of CE(s) None * At most 1

Eigenvalue 0.475780 0.017891

Max-Eigen Statistic 20.66699 0.577690

0.05 Critical Value 14.26460 3.841466

Prob.** 0.0043 0.4472

Source Author’s own computation by using EViews-6 Maximum eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values

Table 3.5 Pairwise Granger causality tests Sample Period: 1971 2013 Lags: 2 Null Hypothesis: LogFDI does not Granger Cause LogGR LogGR does not Granger Cause LogFDI

Obs 32

F-Statistic 3.35816*** 1.30843

Notes Significance at the 1%, 5% and 10% level is indicated by *, ** and ***, respectively Source Author’s own computation by using EViews-6

Prob 0.0498 0.2868

74

M. PAL

Table 3.6 Results of vector error correction model for FDI and growth

Included observations: 30 after adjustments Standard errors in () & t-statistics in [] Error Correction:

D(LogGR)

−0.413594 (0.33885) [−4.17180] D(LogGR(−1)) 0.421430 (0.27411) [ 1.53743] D(LogGR(−2)) 0.346864 (0.19689) [ 1.76172] D(LogFDI(−1)) −0.133937 (0.09948) [−1.34641] D(LogFDI(−2)) −0.025449 (0.09185) [−0.27706] C 0.057606 (0.07528) [ 0.76520] R-squared 0.561311 Adj. R-squared 0.469918 Sum sq. resids 3.499842 S.E. equation 0.381873 F-statistic 6.141698 Log likelihood −10.34096 Akaike AIC 1.089398 Schwarz SC 1.369637 Mean dependent 0.029003 S.D. dependent 0.524502 Determinant resid covariance (dof adj.) Determinant resid covariance Log likelihood Akaike information criterion Schwarz criterion CointEq1

D(LogFDI) −0.314453 (0.54790) [−0.57392] 0.309157 (0.44323) [ 0.69751] −0.060775 (0.31836) [−0.19090] −0.209164 (0.16085) [−1.30036] −0.254345 (0.14852) [−1.71248] 0.373524 (0.12173) [ 3.06852] 0.211249 0.046926 9.150546 0.617473 1.285571 −24.75740 2.050493 2.330733 0.282275 0.632491 0.053882 0.034484 −34.62756 3.241838 3.895730

Source Author’s own computation by using EViews-6

3

FDI-GROWTH NEXUS IN INDIA: COINTEGRATION …

75

It is a well-known fact that the individual coefficient derived from VECM is not in a position to simplify and interpret the results. For this, it is important to analyze the dynamic properties of the model by examining the Impulse Response Function (IRF) and Variance Decomposition (VDC). In order to reconfirm the results, we undertake the IRF for GDP. This analysis allows us to examine further how an unanticipated shock to FDI will have an impact on the growth rate. The anticipated shock analysis can be conducted using the estimated coefficients. An IRF traces the effect of one time shock to one of the innovations on current and future values of endogenous variables. For stationary series, the impulse responses should die out to zero and the accumulated response should asymptotic to constant. The impulse response function coming from standard deviation shocks to FDI with the response of GDP is traced out in Fig. 3.7. Response from shocks in variable provides paths for GDP. In the case of FDI, the path declined and climbed after two years, again after 3 years declined, and then climbed up to 5 years and then becomes constant up to 10 years. The results from Cholesky variance decomposition technique show that a good proportion of the variance in GDP shocks is attributable to shocks in FDI (Table 3.7).

3.5 FDI-Growth Nexus Should Be Strengthened with the Following Suggestions First, in case of unidirectional Granger causality which runs from FDI to growth, the host country should increase the effectiveness of FDI inflows to increase the economic growth. Second, in case where Granger causality runs from growth to FDI, the concerned authorities should promote the economic growth and overall economic development to attract foreign capital especially FDI and portfolio inflows. Third, in host countries where bidirectional causality exists, both FDI and growth must reinforce each other. Fourth, to increase the productivity and absorptive capacity of FDI inflow, financial system which includes the development of money, banking and capital market, should be promoted and well regulated. Further measures such as liberalization of the financial system, as established reality, can have positive effect on the growth of FDI host nations. To control liberalized financial system, Basel norms (1988) which deal with high capital adequacy ratio or capital to risk asset ratio (CRAR) and effective prudential norms should be implemented effectively by the banking industry.

76

M. PAL

Response to Cholesky One S.D. Innovations Response of LOGGR to LOGGR

Response of LOGGR to LOGFDI

.4

.4

.3

.3

.2

.2

.1

.1

.0

.0

-.1

-.1

-.2

1

2

3

4

5

6

7

8

9

10

-.2

1

2

Response of LOGFDI to LOGGR .8

.6

.6

.4

.4

.2

.2

.0

.0

1

2

3

4

5

6

7

8

4

5

6

7

8

9

10

Response of LOGFDI to LOGFDI

.8

-.2

3

9

10

-.2

1

2

3

4

5

6

7

8

9

10

Fig. 3.7 Impulse response function (IRF) (Source Author’s own estimation)

3.6

Conclusions

This chapter attempts to test empirically the long-run relationship between growth rate and FDI in India with the help of new time-series methodology which takes into unit roots testing to check the order of integration, testing Johansen (1991) cointegration test to check the long-run relationship between two variables for the period of (1971– 2013). We have tested the order of integration for two variables with the help of ADF and Phillips-Perron test. We find both the variables to be stationery after first differencing. After confirming the order of integration, our results confirm the existence of positive and long-run relationship between FDI and growth. Trace test and maximum eigenvalue both indicate 1 cointegrating equation at the 0.05 level. Granger

3

Table 3.7 Variance decomposition of growth rate and FDI

FDI-GROWTH NEXUS IN INDIA: COINTEGRATION …

Period

S.E

LogGR

Variance Decomposition of LogGR: 1 0.381873 100.0000 2 0.382183 99.83767 3 0.386340 97.93957 4 0.408739 95.91394 5 0.411138 94.81454 6 0.411974 94.50512 7 0.414916 94.21695 8 0.416019 93.73663 9 0.417588 93.04230 10 0.419366 92.34917 Variance Decomposition of LogFDI: 1 0.617473 3.089916 2 0.796346 3.035863 3 0.884056 3.197077 4 0.989567 2.574013 5 1.087362 2.169046 6 1.167435 2.006526 7 1.242495 1.807429 8 1.316655 1.628184 9 1.386719 1.472040 10 1.452896 1.349027

77

LogFDI

0.000000 0.162328 2.060433 4.086060 5.185458 5.494882 5.783047 6.263369 6.957697 7.650827 96.91008 96.96414 96.80292 97.42599 97.83095 97.99347 98.19257 98.37182 98.52796 98.65097

Source Author’s own computation by using EView -6

causality also shows unidirectional causality running from FDI to growth in India. Our ECT term shows minus sign and is equal to -0.41, which demonstrates that 41% of disequilibrium is corrected within one year period. To reconfirm our results, we check the results from Cholesky variance decomposition and IRF. Our results on FDI-Growth nexus are consistent with the findings from de Melloo (1997); Huang (2004); Rati and Zhang (2002).

Notes 1. For detailed analysis, see Dua and Rashid (1998). 2. A forward linkage means when investment initiates in investment in subsequent projects to be undertaken, while the concept of backward linkage encourages investment in facilities that enable the project to succeed. Hirschman (1958) introduced the concept of backward and forward linkages of the development theory.

78

M. PAL

3. For comprehensive discussion, refer Zhang (2002). 4. Dunning (1988) developed the market-seeking FDI hypothesis which talks about that increasing the size of domestic markets for services such as telecommunications, gas, electricity, retail commerce and financial services provided by the financial and money markets attracts more FDI in the host emerging nations. 5. For detailed analysis on the theoretical analysis, see Chowdhury and Mavrotas (2003).

References Adewumi, S. 2006. The impact of FDI on growth in developing countries: An African. Sweden: Jonkoping International Business School. Aggarwal, P. 2000. Economic impact of foreign direct investment in South Asia, Indira Gandhi Institute of Development Research, Mumbai. Ahmad, H.M., and other,. 2003. Foreign direct investment, export and domestic output in Pakistan. The Pakistan Development Review 42 (4): 715–723. Ahamad, M.G., F. Tanin., and Z. Uddin. 2010. Does FDI intensify economic growth? Empirics from Bangladesh, MPRA paper no. 21022, Munich. Alfaro, L., C. Areendam, S. Kalemli-Ozcan, and S. Selin. 2003. FDI and economic growth: The role of local financial markets. Journal of International Economics 61 (1): 512–533. Akinlo, A. 2004. Foreign direct investment and growth in Nigeria: An empirical investigation. Journal of Policy Modeling 26 (5): 627–639. Akinlo, E.A. 2013. Government spending and national income nexus for Nigeria. Global Journal of Business Research. The Institute for Business and Finance Research 7 (1): 33–41. Bains, P., and S. Kaur. 2016. FDI and economic growth: An analysis in the context of Indian economy during post-liberalization period. Asian Economic Review 58 (2): 175–185. Balasubramanyam, V.N., M. Salisu, and D. Sapsoford. 1996. Foreign direct investment and growth in EP and IS countries. The Economic Journal 106 (434): 92–105. Balasubramanyam, V.N., M. Salisu, and D. Sapsoford. 1999. Foreign direct investment as an engine of growth. Journal of International Trade and Economics 8 (1): 27–40. Balsubramanyam, V.N., and D. Sapsford. 2007. Does India need a lot more FDI? Economic and Political Weekly 42 (17): 1549–1555. Banga, R. 2003a. Impact of government policies and investment agreements on FDI inflows, working paper, No. 116, Indian Council for Research in International Economic Relations, New Delhi.

3

FDI-GROWTH NEXUS IN INDIA: COINTEGRATION …

79

Barro, R., and Sala-I-Martin. 1995. Economic Growth Cambridge, MA: Mc Graw–Hill, 539. Basel Committee on Banking Supervision. 1988. International convergence of capital measurement and capital standards. www.bis.org. Basu, P., C. Chandana, and D. Reagle. 2003. Liberalization, FDI and growth in developing countries: A panel cointegration approach. Economic Inquiry 41 (3): 510–516. Better, G., and A. Zarraro. 2012. Remittances and financial development, substitute or complements in economic growth. Bulletin of Economic Research 64 (9): 1–28. Bhagwati, J.N. 1985. Essays on development economics: Wealth and poverty, 192– 193. USA: MIT Press Cambridge. Bhattcharya, B., and J. Mukherjee. 2016. Foreign direct investment and macroeconomic indicators in India: A causality analysis in Roy, Roy M, Saikat S eds. International trade and international finance -explorations of contemporary issues, Springer, 373–384. Bhasin, N., and A. Gupta. 2017. Macroeconomic impact of FDI inflows: An ARDL approach for the case of India. Transnational Corporations Review, Taylor & Francis Journals 9 (3): 150–168. Biswas, S., and B. Dasgupta. 2013. Foreign direct investment and economic growth in India during the post—reform period. Asian Economic Review 55 (2): 257–274. Blomstrom, M., and M. Zejan. 1992. What explains developing country growth?, NBER working paper 4132. Borensztein, E., J.D. Gregorio, and J.W. Lee. 1998. How does foreign direct investment affect economic growth? Journal of International Economics 45: 115–135. Carkovic, M., and R. Levine. 2002. Does foreign direct investment accelerate economic growth? Finance department, Carlson School of Management, University of Minnesota Centre of Economic Performance, Working Paper, 1265 Chakraborty, C., and P. Basu. 2002. Foreign direct investment and growth in India: A cointegration approach. Applied Economics 34 (9): 1061–1073. Chakraborty, C., and P. Nannenkamp. 2008. Economic reforms, FDI and economic growth in India: A sector level analysis. World Development 36 (7): 1192–1212. Chaudhuri, S., and U. Mukhopadhyay. 2014. Foreign direct investment in developing countries -A theoretical evaluation. New Delhi: Springer. Chowdhury, A., and G. Mavrotas. 2003. FDI and growth: What causes what? The World Economy: United Nations University.

80

M. PAL

De Mello, L.R., and Jr. 1997. Foreign direct investment in developing countries and growth: A selective survey. The Journal of Development Studies 34 (1): 1–34. De Mello, L.R., and Jr. 1999. Foreign direct investment –led growth: Evidence from time series and panel date. Oxford Economic Papers 51 (1): 133–151. Dogan, E. 2014. Foreign direct investment and economic growth in Zambia. International Journal of Economics and Finance 6 (1): 148–154. Dua, P., and A.I. Rashid. 1998. Foreign direct investment and economic activity in India. Indian Economic Review 33 (2): 153–168. Dunning, J.H. 1977. Trade, location of economy activity and the MNE: A search for an eclectic approach”. In B. O. al., International Allocation of Economic Activity (pp. 395–418). London: Holmes and Meier. Dunning, J.H. 1988. The eclectic paradigm of international production: A restatement and some possible extensions. Journal of International Business Studies 19: 1–31. Elboiashi, H.A. 2011. The effect of FDI and other foreign capital inflows on growth and investment in developing economies, PhD thesis, Department of Economics, University of Glasgow Frankel, J.A. 1999. Does trade cause growth? The American Economic Review 89 (3): 379–399. Gaiiani, S., K. Stephen, and Z. Ben. 2014. The effect on growth: evidence from an quasi experiment, Washington D C, World Bank, Policy Research Working Paper, No.6865 Ghali, K.H. 1998. Public investment and private capital formation in a vector error correction model of growth. Applied Economics 30 (6): 837–844. Ghosh, D.N. 2005. Foreign direct investment and reform. Economic and Political Weekly 40 (31): 5388–5392. Hansen, H., and J. Rand. 2006. On the causal links between FDI and growth in developing countries. The World Economy 29 (1): 21–41. Herzer, D., et al. 2008. In search of FDI-led growth in developing countries: The way forward. Economic Modelling 25 (5): 793–810. Hirschman, A.O. 1958. The strategy of economic development. New Haven: Yale University. Huang, T., Jr. 2004. Spillovers from FDI in China. Comtemporary Economic Policy 22 (1): 13–25. Ilhan, O. 2007. Foreign direct investment-growth nexus: A review of the recent literature. International Journal of Applied Econometrics & Quantitative Studies 4 (2): 79–98. Islam e.al. 2012. Trade, FDI and economic growth linkages in selected South Asian countries. In Shahid A eds. FDI, Trade and economic growth, challenge and opportunities. Routledge, London.

3

FDI-GROWTH NEXUS IN INDIA: COINTEGRATION …

81

Jain, S., and N.R. Bhanumurty. 2005. Financial markets integration in India. AsiaPacific Development Journal 12 (2): 15–33. Javaid, M.I. et al. Causal link between foreign direct investment and economic growth in Pakistan, ADB, India Resident Mission, INRM. Johansen, S. 1991. Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica 59 (6): 1551–1580. Kathurai, V. 2002. Liberalization, foreign direct investment and productivity spillovers: An analysis of Indian manufacturing firms. Oxford Economic Papers 54: 668–718. Kaushik, et al. 2008. Export growth, export instability, investment and economic growth in India: A time series analysis. The Journal of Developing Areas 41 (2): 155–170. Lall, S., and R. Narula. 2004. Foreign direct investment and its role in economic development: Do we need a new agenda? European Journal of Development Research 16 (3): 442–464. Li, X., and Liu,. 2005. Foreign direct investment and economic growth: An increasingly endogenous relationship. World Development 33 (3): 393–407. Lipsey, R.E., and F. Sjoholm. 2004. FDI and wage spillovers in Indonesia manufacturing. Review of World Economics 140 (2): 287–310. Lipsey, R.E. 2011. Inward FDI and growth in developing countries. Transnational Journal of Corporations 9 (1): 83–84. Lucas, R. 1988. On the mechanics of economic development. Journal of Monetary Economics 22: 3–42. Mah, J.S. 2010a. Foreign direct investment inflows and economic growth. The Case of Korea, Review of Development Economics 14 (4): 726–735. Mah, J.S. 2010b. Foreign direct investment inflows and economic growth of China. Journal of Policy Modeling 32 (1): 155–158. Mahembe, E., and N.M. Odhiambo. 2014. Foreign direct investment and economic growth: A theoretical framework. Journal of Governance and Regulation 3 (2): 63–70. Manjula, G.T. 2011. Impact of FDI on corruption in India. The Asian Economic Review 53 (1): 53–62. Moosa, A.A. 2002. Foreign direct investment, theory, evidence and practice, Palgrave, 98–101. Muhammad, S.D., and Others,. 2016. Do FDI inflows promote growth: A case of selected SAARC countries. Asian Economic Review 58 (1): 79–87. Nachane, D.M. 2007. Liberalisation of the capital account; perils and possible safeguards. Economic and Political Weekly 42 (36): 3633–3643. NCAER. 2009. FDI in India and its growth linkages, National Council of Applied Economic Research, (NCAER), New Delhi, India, Available https://www.ncaer.org/wp-content/uploads/2009/08/FDI-in-India_ NCAER_Report.pdf, last accessed on 18 October, 2013.

82

M. PAL

Nagaraj, R. 2003. Foreign direct investment in India in the 1990s. Economic and Political Weekly 38 (17): 1701–1712. Neelakanta, N.T. et al. 2013. Relationship between FDI, environment and economic growth in India: An application of ARDL approach in Sharma KC et al. eds. Econometric Application in Management The Indian Economeric Society (TIES) Annual Conference Proceedings, National Publishing House, Delhi,118–141. Pal, M. 2014a. Financial development in India: An empirical test of the McKinnon-Shaw model in Ghoh, AN and Karmakar, A K eds, Analytical issues in trade, development and finance, Springer, New Delhi, 405–420 Pal, M. 2014b. Financial policy of India-theory and evidence from cointegration, H.R Journal of Management, Ghaziabad, India 7(1): 1–27. https://papers. ssrn.com/sol13/papers.cfm?abstract_id=253633 Pal, M. 2013. Finance-growth nexus in India: evidence from cointegration & vecm, in Sharma, RC and Garg, SK eds. Econometric Application in Management, Annual Conference Proceedings (TIES) National Publishing House, New Delhi, 16–32. Rangarajan, C. 1995. Impact of liberalization on foreign direct investment and employment opportunities in India. Reserve Bank of India Bulletin 49 (1): 43. Rati, R., and K.H. Zhang. 2002. Foreign direct investment and economic growth: Evidence from cross-country data for the 1990s. Journal of Economic Development and Cultural Change, Chicago 50 (1): 205–215. Ray, S. 2012. Impact of foreign direct investment on economic growth in India: A cointegration analysis. Advances in Information Technology and Management 2 (1): 2167–2172. RiuzI, C. 2005. Exchange rate as a determinants of foreign direct investment does it matter? Theoretical Aspects, Literature Review and Applied Proposal, Ecos De Economia: A Latin American Journal of Applied Economics 9 (21): 153–171. Romer, P.M. 1986. Increasing returns and long run growth. Journal of Political Economy 94 (5): 1002–1037. Romer, P.M. 1990. Endogenous technological change. Journal of Political Economy 98 (5): S71–S102. Romer, P.M. 1994. The origin of endogenous growth. Journal of Economic Perspectives 8 (1): 3–22. Sahoo, P., G. Natraj, and R.K. Dash. 2014. Foreign direct investment in South Asia, policy, impact, determinants and challenges. New Delhi: Springer. Sahoo, P., and M.K. Mathiyazhagan. 2003. Economic growth in India: Does FDI inflow matter? Singapore Economic Review 48 (2): 151. Sala, I., and X. Martin. 2002. 15 years of new growth economics: What have we learnt? Journal Economia Chilean 5 (2): 5–15.

3

FDI-GROWTH NEXUS IN INDIA: COINTEGRATION …

83

Sasi, J. 2015. The foreign direct investment-economic growth nexus, International Review of Economics and Finance 42 (C): 116–133. Iamsiraroj, Sasi and Uluba¸so˘glu, Mehmet Ali, 2015. Foreign direct investment and economic growth: A real relationship or wishful thinking?, Economic Modelling, Elsevier, 51(C): 200–213 Sasidharan, S., and A. Ramanathan. 2006. Foreign direct investment and technology spillovers: Evidence from the Indian manufacturing sector International Journal of Trade and Global Markets 1 (1): 5–22 available at SSRN. Schumpeter, J.A. 1911. The theory of economic development: An enquiry in to profits, capital, credit and the business cycle, reprinted in 1951. New York: Oxford University Press. Solow, R. 1956. A contribution to the theory of economic growth. Quarterly Journal of Economics 70 (1): 65–94. Srinivasan, P., M. Kalaivani, and P. Ibrahim. 2012. An empirical investigation of foreign direct investment and economic growth in SAARC nations. Journal of Asia Business Studies 5 (2): 232–248. Thirlwall, A.P. 1999. Growth and development, 6th ed. London: Macmillan Press Ltd. Trevino, L., and K.P. Upadhyaya. 2003. Foreign direct investment and economic growth: Evidence from Asian countries. Transnational Corporations 12 (2): 119–136. Vani, A., N.C. Nayak, and P. Basu. 2007. Foreign direct investment in India: Emerging horizon. Indian Economic Review, New Series 42 (2): 255–266. Yanikkaya, H. 2003. Trade openness and economic growth: A cross-country empirical investigation. Journal of Development Economics 72 (1): 57–89. Zhang, K.H. 2001. Does FDI promotes economic growth? evidence from East Asia and Latin America. Contemporary Economic Policy 19 (2): 175–185.

CHAPTER 4

Foreign Aid-Growth Nexus in India: Cointegration and Causality

4.1

Introduction

Foreign resources are convenient method of getting development fund which can act as an instrument for raising the standard of living in the poor countries of the world. The main aim of Foreign Aid is to provide every country with an opportunity to achieve steady growth. The recipient countries regard Foreign Aid as a source through which they can raise its rate of investment to fill the saving-investment gap or foreign exchange gap. Number of economists have identified and investigated the large number of issues relating to Foreign Aid and its impact on growth process and saving rate during the last 4 decades. Whether Foreign Aid should be on bilateral or multilateral terms? Whether it should be a project tied, untied, double tied, reverse tying or program Aid? Whether Aid should be on hard terms with 6% grant element (IBRD type) or on normal terms with grant element of 25%. (Aid type)1 or on highly concessional terms with 80% grant element, (IDA type).2 Whether it should be on commercial terms based on LIBOR rate? What is the absorptive capacity or volatility of Foreign Aid during the SAP period?3 What is the level of commitment or disbursement? Whether a recipient country adopts a good or bad policy in terms of good macro, monetary and fiscal policy? Recently, some studies have appeared on the demise of Foreign Aid. c says that Foreign Aid has turned into a white man’s burden which has © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. Pal, Foreign Capital and Economic Growth in India, https://doi.org/10.1007/978-981-99-2299-4_4

85

86

M. PAL

neither been able to reduce the poverty level nor improve the economic conditions of poor countries especially in Sub-Saharan African (SSA) continent. In addition some studies notably Moyo (2010) points out that Foreign Aid is like a dead thing. However recently, WIDER study (2018) does not support the findings of Easterly (2007a, b) and Moyo (2010) on the demise of Foreign Aid. According to WIDER study which was carried out by Addison et al. (2018) says that Aid is not dead but Aid can increase 20% marginal productivity.4 The motivation to investigate the impact of Foreign Aid on the growth process in India, especially at the time when India is being debated on the status of Foreign Aid as a donor nation. Why should not India be debarred from concessional pool of Foreign Aid? A lot of controversy and debate worldwide has taken place on the status of India’s development paradox. Here development paradox means that on the one hand, India has been trying to establish her image as a lender, and has been providing strategic Aid to her neighboring countries such as Nepal, Bhutan, Sri Lanka and also to African countries, while on the other hand India has been one of the largest recipient countries in the world receiving Foreign Aid hard as well as soft from developed countries and multilateral institutions like World Bank (IBRD–IDA), ADB, etc. A basic question arises whether a country can be both a lender as well as a recipient. During the last current decade, India, China and South Korea, etc., have turned as Foreign Aid lenders (not as donor as per the OECD definition) to the neighboring countries. China lags behind India in terms of Foreign Aid giving provision. Further India has also established her image as lender nation and is likely to establish her own lending window to provide Aid to her neighboring emerging nations. For comprehensive survey on this debate, see Kanbur (1987, 2005), The Economist (2011).5 This research on Foreign Aid-Growth nexus in this chapter differs in many ways from the existing literature. First, it covers longer period and uses new time-series methodology for estimation. Second, analytically and conceptually it improves upon and it also provides a detailed survey of Foreign Aid to India not available in detail in any study. Third, during the last four decades, Aid-growth relationship has acquired different forms of estimation techniques. Hence, on the basis of number of studies reviewed we attempt to test empirically a direct relationship between Foreign Aid and growth in the form of single equation for a single country like India. Fourth, since 1991 onwards Government of India has shifted her foreign capital policy regime from debt creating to non-debt creating foreign

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

87

capital. The basic motivation of this chapter is to evaluate the role of Foreign Aid in India in the shifting development paradigm. The main objectives of this chapter are: First, to evaluate the role of Foreign Aid in India. Second, to examine empirically the long-run relationship between Foreign Aid and economic growth in India. Third, to study its causal direction between economic growth and Foreign Aid with the help of new time-series analysis such as testing unit roots for checking order of integration in the data, cointegration, VECM, IRF and VDC to check the validity of findings. The plan of this study is structured as: Section II deals with a survey of the theoretical and empirical debate on the role of Foreign Aid in an economy and especially in India also; Section III deals with a brief survey on the role of Foreign Aid in India; Section IV deals with model specification and measurement of variables; Section V deals with the results and discussion; and Section VI concludes the chapter.

4.2

Three Gap Debate: Some Theory

According to Harrod (1939) and Domar (1946) model, the rate of growth of income is equal to the rate of saving which can be divided by the incremental capital-output ratio (ICOR). In terms of basic growth / equation is written G = S C, while G is the rate of growth of output, S stands for rate of saving and C denotes the incremental capital-output ratio (ICOR). During the last seven decades, the two gap theory developed by Chenery and Strout (1966), and now the three gap theory developed by Bacha (1990) and Taylor (1990), has been the most applied tool of economic planning in the hands of economists especially at the level of governments and multilateral institutions such as World Bank, ADB, AIDB, etc. The two or dual gap can be discussed with three variants of gap model. First gap is the saving gap (I − S) developed by Rosenstein-Rodan, (1961) which treats Foreign Aid as a supplement to domestic saving in the Aid recipient country. Second is the trade gap (M − X) model developed by Balassa (1964) which considers Foreign Aid as a source of foreign exchange earnings that can be used to increase the capacity of import in the recipient country. Third is the two gap model developed by Chenery and Strout (1966) which takes into account both trade and saving gap. In this model, Chenery and Strout (1966) have extended the HarrodDomar equation with the inclusion of Aid variable and have developed the idea that Foreign Aid acts as a supplement to the domestic savings

88

M. PAL

/ and thus Aid raises the growth rate to (S + A) V where A stands for Foreign Aid and is expressed as a percentage of GNP of recipient country. This increase in the growth rate would increase the income level of recipient country. Economic theory also believes that the marginal propensity to save (MPS) is higher than the average propensity to save (APS) in low-income countries. This process would increase the saving and investment rate in Under Developed Countries (UDCs) resulting in higher growth rate. These authors further claim that increase in growth rate will cause a self-sustaining stage of development. Self-sustaining stage of the Aid recipient country is the threshold where concerned nation does not require outside financial help in future.6 (I − S) = F = (M − X − T)

(4.1)

From the Eq. 4.1, we find that the internal gap (I − S) is equal to the net capital inflows (F), which in turn should be equal to the current account deficit (M − X − T). The most significant contribution of two gap model is that it reveals the fact that with an unit increase in capital inflows, the level of investment (I) and import (M) may increase in a one-to-one basis. Moreover, the model does not say anything about causal direction which causes what. Recent development in the gap theory includes a Third Gap or Fiscal Gap. Third Gap which was developed by Bacha (1990) and Taylor (1990) has been added to the traditional foreign exchange and saving gap to calculate the growth in the emerging countries. Third Gap takes into account the double transfer problem which is linked to fiscal and foreign transfer limitations on policy choice.7 4.2.1

Critique of Gap Model

The dual gap theory has served as an important and very sophisticated instrument in the hands of economists, researchers and policy makers for calculating the growth rate with a given level of saving rate and ICOR in the developing countries for the period of more than seven decades that is from 1950 to 2020s. However, the operational part of dual gap model has always been facing severe criticism on certain grounds, for example, the model does not differentiate between private and official foreign capital in the developed and underdeveloped regions of Aid recipient countries, It also does not deal with debt service charges and interest burden in terms of heavy indebtedness in the recipient countries. However, one point that should be highlighted here is that highly concessional Aid provided by

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

89

the IDA (soft window of the World Bank) does not generate heavy debt burden on the recipient countries like India because IDA Aid contains grant element more than 75%. Even after this criticism, the dual gap model still is in operation to calculate the saving-investment and importexport gap effectively by the economists, researchers and economic planners in the Aid recipient countries. For a brief analysis of Aid-Growth Nexus, see Appendix 4.2. 4.2.2

Foreign Aid: An Empirical Controversy

The issue of Foreign Aid has always been a highly controversial subject which covers different schools of thought covering pro-Aid, radical, conservative and anti-Aid view. We have dealt with five schools of thought in brief.8 Pro-Aid view by Chenery and Strout (1966), Papanek (1972, 1973), Resenstein-Rodan (1961) supports the outcome of dual gap model. They also say that in addition to solve the two gap, financial constraints Aid also helps in getting latest technology and advanced managerial talent. Most important point which they highlight is that the surplus saving/capital from the developed countries with low rate of return is transferred to capital-deficient countries which can acquire high rate of return accompanied by high allocative and operational efficiency in the Aid recipient countries. All these studies claim to increase the rate of economic growth in the Aid recipient countries.9 Second school is related to radical view which talks about that foreign capital causes significant negative effects on the recipient countries because it substitutes rather than complement domestic saving. However, on the issue of substitution principle, the empirical findings still remain inconclusive, see Griffin (1970), Griffin and Enos (l970), Weissikoff (1972a, 1972b), and Papanek (1973).10 Third school of thought is related to the conservative view which alleges that Foreign Aid has created bulk size of government bureaucracies, generated corruption, bad governments, heavy debt burden, increase income inequalities in terms of increasing number of rich people in poor economies, mal allocation of precious financial funds in terms of aid fungibility, under utilization of Aid, Dutch disease, etc. For comprehensive survey on this debate, see Bauer (1971a), Peter and Yamey (1981), Easterly (2001).11 Fourth school of policy effectiveness led by Burnside and Dollar (1997, 2000, 2004), Collier and Dollar (2001, 2002) say that while Aid works in

90

M. PAL

all countries, it works better in countries which are equipped with better economic policies in terms of effective monetary, fiscal, trade, micro and macro policies. Their findings have become a new development paradigm in the area of ODA effectiveness in the Aid recipient countries.12 Fifth school of without policy effectiveness argues that Foreign Aid works even in those Aid recipient countries also which do not follow good economic policies that are related to fiscal, monetary and budgetary, as pointed by Burnside and Dollar (2000).13 We may conclude that all the schools of different ideology come to an agreement that Foreign Aid works in all respects. The debate must come to an end. Now from a rational point of view, policy of Foreign Aid must be rationalized on the basis of cost and benefit analysis. To study this chapter, we take a rational and pragmatic view on the Aid effectiveness in India and try to examine the quantitative impact of Foreign Aid on economic growth in India, using an improved theoretical and econometric framework and a unique data set on India.

4.3 Recent Empirical Advances in Aid-Growth Relationship Keeping in view some studies have been carried out: Chowdhury (2011), Minoiu and Reddy (2010), Gounder (2010), Rajan and Subramanian (2008), Mbaku (2006), Bazoumana and Strobl (2008), Dalgaard et al. (2004), Burnside and Dollar (2000), Howard White (1992), and Levy (1988). Chowdhury M. (2011) examines the relationship between Aid and growth in five South Asian economies: Bangladesh, India, Nepal, Pakistan and Sri Lanka. Using both country-specific time series and a panel cointegration procedure over the period 1976 to 2008, his results suggest a positive long-run relationship between growth rate of per capita real GDP and Aid as a percentage of GDP for four out of five countries. However, this positive and long-run relationship is not established in India. Hence, this investigation tends to support the Aid effectiveness hypothesis for South Asian countries except India. Minoiu, C. and Sanjay G. Reddy (2010) analyze the growth impact of Aid in developing countries. They distinguish the effects of two kinds of Aid, i.e. developmental and non-developmental Aid. Their results indicate that developmental Aid promotes long-run economic growth. Gounder, R. (2010) a neo-classical production function is applied to estimate the Aid-Growth nexus in Fiji for the period of 1968 to 1996.

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

91

With an application of ARDL technique to cointegration, their empirical results show that Aid flows have a significant and positive impact on economic growth in Fiji. Rajan, R. and Subramanian A. (2008) examine the effects of Aid on growth in cross-section and panel data. They find little robust evidence of a positive or negative relationship between Aid inflows and economic growth. Mbaku, M (2006) with an application of the neo-classical production in Cameroon tests the relationship between Foreign Aid and economic growth in Cameroon economy from 1971 to 1990. Results show that domestic resources have a stronger impact on economic growth in Cameroon than foreign resources. Bazoumana, O and Eric Strobl (2008) include project Aid, program Aid, technical assistance, grants and food Aid as explanatory variables in an endogenous growth model. They find that project aid affects positively, with a condition of diminishing returns while other types of Aid show insignificance statistically. Dalgaard, C.J., Henrik, H. and Finn T. (2004) re-examine the effectiveness of Foreign Aid theoretically and empirically with an application of OLS methodology. Findings reveal that Foreign Aid affects long-run productivity. Burnside and Dollar (2000) argue that Aid is most effective when supported by sound and good economic policy adopted by the Aid recipient countries. Their findings have now become an effective weapon for Aid giving nations (OECD) and Aid agencies like World Bank and ADB through which more disciplined monetary and fiscal policies can be enforced in the Aid recipient countries so that they receive more Aid. However, this research has attracted much criticism in the world economy. However, Aid researchers have reached to some conclusions after the publication of World Banks Assessing Aid Paper (1998) which reveals the facts that Foreign Aid works in the Aid recipient countries in such a manner that growth rates would have been lower in the absence of Foreign Aid. In support of World Banks study, another study carried out by the Swedish International Development Agency (SIDA) (2000) estimates that growth rates would have been around (0.5 to 1%) lower without the availability of Foreign Aid in the Aid recipient countries. This study uses a general equilibrium growth model to link Aid effectiveness to the economic policies of the recipient countries. Howard White (1992) examines the relationship between Foreign Aid and private investment in less developed countries (LDCs) in a simple macroeconomic framework. He examines causal direction which runs from Aid to crowding in private investment in the Aid recipient countries. Levy, V. (1988) examines the relationship between Aid and economic

92

M. PAL

growth in the sample of underdeveloped countries of SSA. Aid exhibits significant and positive relationship with investment and growth rate. Mosely (1987) talks about micro–macro paradox. This paradox reveals the fact that Aid works at micro-level, while there is no evidence of its positive effect at macro-level. 4.3.1

Indian Studies on Foreign Aid-Growth Nexus

India being the largest recipient and most favored nation in terms of Foreign Aid, has not been studied in detail, while India has been responsible for reshaping the economic policies of donor nations and MDBs such as the World Bank and the IMF. Keeping India in view, some studies have been carried out: Marjit and Mukherjee (2016)„ Mavrotas (2002), Dawson and Tiffin (1997), Lipton and Toye (1991), Cassen and associates (1986), Bajaj and Panchmukhi (1990), Riddell (1987), Bowles (1987), Pal (1985), Chaudhuri (1978), Sharma (1977), Streeteen and Roger (1971), Bauer (1971b). These studies reveal the fact that India has been the major architect in reshaping the policies of donor nations that have bilateral and multilateral view on the Foreign Aid. For detailed analysis on this issue, refer Pal (1985). Marjit, S., and Mukherjee, V. (2016) talk about the issue of corruption which is being promoted in the Aid recipient countries. Their study notes that the white elephant project is undertaken by the Government and its undertakings are equipped with inefficient and unproductive employment. Untied or program Aid which is given to state governments in poorer states of India increase the degree of corruption. Mavrotas G. (2002) examines the impact of Foreign Aid on growth in India, a single country study, for the period of 1970–1992 with the help of modern time-series technique based on general-to-specific modeling and Johansen Cointegration (1990) Empirical findings reveal that the composition of Foreign Aid does matter in case of Indian economy. Dawson P. J. and Tiffin R.’s (1997) study traces the negative long-run relationship between Aid and per capita GDP in India, with the help of modern time-series methodology. He takes into account only two variables such as GDP and ODA. In this study Aid variable does not show unit root while GDP contains unit root in the series for the study period of 31 years, i.e. from 1961 to 1992. Lipton, M. and Toye, J. (1991) evaluate the success story of Foreign Aid projects in India at both the macro and microeconomic level, with a special emphasis on poverty alleviation. Cassen, R. and Associate (1986) examine the effectiveness of micro

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

93

projects funded by ODA, with Aid evaluation and detailed economic analysis of major economic and social infrastructure projects in seven country case studies. They also recommend IDA Aid for India taking into account her poverty level. Bajaj and Panchmukhi (1990) examine the role of Foreign Aid in the 1990s with special reference to the lending of the World Bank and IDA. Empirically, they analyzed the relationship between per capita IDA commitment as a dependent variable and rate of growth of per capita GDP, rate of change of terms of trade as independent variables with the help of OLS regression technique. They find that the Asian countries with their deteriorated balance of payment position have received relatively less per capita IDA money than the other countries, which have experienced improvement in the balance of payment. During the period of 1990s, India’s rank in terms of IDA absolute amount was 1st and India was also the IDA’s largest borrowers while in terms of per capita IDA Aid availability, India’s rank was XII. Riddell, R.C. (1987) argues that due to effective degree of Aid utilization income-earning capacity has increased in India and poverty level has been reduced. Foreign Aid has also increased the food production through the operation of Green and White revolution and expanded the employment opportunities, agricultural research and extensions. Bowles, P. (1987) demonstrates relationship between ODA and rate of domestic saving in India and empirically finds that a 1% rise in Aid/GDP ratio causes saving rate to decline by −0.8 to −1.11% in India. Pal, Mahendra (1985) talks about the specific role of the hard window (IBRD) of the World Bank. He takes into account the micro study of the projects funded by the World Bank and concludes that the World Bank has accelerated the process of economic growth and development in India and served as a major development partner of India in promoting the basic economic and social infrastructural facilities. Chaudhuri, P. (1978) examines empirically the relationship between Aid utilized, saving, investment, net national product and budget deficit. At highly aggregated level, he finds no evidence that Aid has either reduced the saving ratio or has enabled the Government of India to run higher budget deficit. The evidence is inconclusive. His results show strong and positive effect of the Foreign Aid on the level of investment within the Indian economy, Investment coefficient remains doubled in value, if food Aid component, which goes directly into consumption, is not taken into account.

94

M. PAL

Sharma, R.K. (1977) has studied the grant element in Foreign Aid to India. He tried to compare the grant element of different bilateral donors and multilateral institutions. He concludes that the IDA Aid remains to be the most concessional Foreign Aid having grant element more than 78% while the IBRD provides hard loans i.e. grant element remains around 6%. Grant element in donor nations such as the USA, Canada, West Germany and the then USSR remains around 30% to 35%. Streeteen, P. and Roger, H. (1971) talk about on the value of Foreign Aid that if Foreign Aid is provided in foreign exchange which is freely spendable in the foreign exchange market, then its value is likely to exceed its nominal value. They argue that the World Bank Aid is freely spendable because it is source tied, hence its value exceeds its nominal value in India. These studies reveal the fact that Indian economy has been the major architect in reshaping the donors’ i.e. bilateral and multilateral view on the issue of Foreign Aid policy. Bauer (1971b) has bitterly criticized the role of Foreign Aid to developing countries and argue that much of the Foreign Aid which was received by the underdeveloped now developing countries, notably India, has not been able to enhance the income-earning capacity of these countries, but on the other hand, Foreign Aid has made them heavily indebted nations, even debt servicing capacity has not been improved. Bauer’s (1971b) criticism provides no empirical evidence in support of his findings. Lipton and Toye (1991) do not agree with Bauer and argue that ODA which was advanced to India, no doubt, was very less in absolute amount and also in terms of ODA per capita but ODA has played and continues to play a very significant role in economic welfare of Indian economy (1984).14

4.4

Foreign Aid to India: An Overview

India is one of those countries, in whose economic development, external assistance has played and continues to play a decisive and an important role. India’s Five Year Plan has appreciated the vital role of foreign capital in the country’s economic development. Although 90% of resources for India’s economic development have come from domestic resources, yet foreign capital has played an important role in Indian economy. India has shifted her Foreign Aid regimes from debt creating to nondebt creating policy in 1991. The main reasons were fatigue or failure of Foreign Aid, high level of debt service ratio (DSR), under utilization of Foreign Aid which remained in the pipeline for long time and

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

95

causing a heavy debt burden on Indian economy, low effectiveness, fungibility which arises from shifting Aid from selected projects to unidentified projects. Major share of Foreign Aid remains in the pipeline because of the shortage of local component of funds. There has always been a dispute among the central, state and local bodies in the process of completion of projects. In this way the problem of cost overrun and time overrun is a glaring example in India. See Singh (2009), Rao (1952, 63).15 Foreign Aid was generally utilized in the Public Sector. The share of net Foreign Aid to the public sector investment was 13.4% in the First Five Year Plan, which increased to 30.6% in her Second Plan, it increased to 33.4% in Third Plan, 48.8% in her Annual Plans, 26.5% in Fourth Plan and 18.4% in her Fifth Plan. However, since 1980 onward utilization of Foreign Aid continued to share around 10% in her total public sector investment in subsequent five year plans. During the last two and a half decades, the performance of Aid utilization, i.e. disbursement/ commitment remained very effective ranging from 70 to 100%. Further in terms of percent of capital formation, the share of Foreign Aid was 38% in 1965–1966 which reduced to 22% in 1966–1967. So far net inflow of Foreign Aid is concerned, during the period of 15 years from 1980 to 1995; net inflow of Aid averaged US $0.5 Billion. During the last decade, i.e. 2006–2013 net Aid inflow has been around US $3 billion on an average ranging from US $1.5 billion in 2009– 2010 and US $4.8 billion in 2010–2011. So far grant is concerned, India has been receiving grants from the developed countries in the range of US $0.5 billion yearly even now. Net inflow of Foreign Aid/GDP ratio decreased from 3.8% in 1965–1966 to 1.80% in 1971 which further declined to 0.13% in 2013. Figure 4.1 demonstrates the details of Foreign Aid availability, debt servicing and net Foreign Aid availability to India during the period of 1981 to 2018. During the last 65 years of development planning period, India has received Foreign Aid from the industrial, socialist countries, World Bank and the ADB. The USA which is the largest Aid donor in the World has gradually decreased its share to India from 57.7% in 1965–1966 to 27% in 1982 and now its share is negligible or around US $50 million a year in the form of grant only. Foreign Aid from the World Bank has also played an important and complementary role. The share of the World Bank in the gross Aid utilization increased from 17% during the period of early 1950s to 65% annually during the decades of 2000s. In multilateral lending IDA still plays a dominant role in MDBs lending having 1st rank lender to India.16 During the last 5 years, net disbursement of Foreign

96

M. PAL

14 12 10

Authorisation

8 Utilisation

6 4

2017-18

2014-15

2011-12

2008-09

2005-06

2002-03

1999-00

1996-97

-4

1993-94

-2

1990-91

Net Inflow Aid 1987-88

0 1984-85

Debt Service Payments 1981-82

2

-6 Fig. 4.1 Foreign Aid to India (1981–2018) US billion dollars (Source Author’s own work based on the data from HBS [RBI])

Aid coming to India ranged from US $915 million in 2007 to US $2.20 billion in 2011–2012 from the UK, Japan, Germany. Individually these donor nations have been providing US $500 million on an average. For a detailed analysis on grant element in Indian Foreign Aid, see Appendix 4.1. India has traditionally been one of the largest recipients of Foreign Aid but in terms of Aid per head, India received US $ 1.5 per capita head in 1961 and only US $1.8 in 1995. India has been the largest borrower in the world. Almost every nation has helped India, and the main reason was that India had too much poverty and democratic setup. Moreover, India’s borrowing history reveals the fact that India never defaulted on her repayment, except one time rescheduling in the late 1960s.17 The role of Foreign Aid remained as a catalyst. During the period of 10 years of 1951–1961, Aid generated share in national income was 2% while 98% came from domestic resources. With the help of Foreign Aid, saving and investment had gone up from 5 to 7% now India has secured more than 30% saving and investment rate. In 1950, during the 1st five year plan, India had only 2.5 million kw electricity generation capacity but now India has more than 150 million

4

97

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

kw electricity generation capacity because all major dams such as Tehri, Sardar Sarovar, Bhakra Nangal and Damodar Valley have been helped financially by the Foreign Aid. In agriculture irrigation, agriculture credit, extension, agriculture research, marketing, storage facilities and famous revolutions such as Green, White and Silk revolutions have been helped financially by the Foreign Aid. In industry all major industries such as iron and steel, fertilizer, etc. have been financed by Foreign Aid. In SOC also, education, training health, medical, sanitation have been financed by Foreign Aid. Hence, we can say that Foreign Aid has played a very important, significant and strategic role in the development process of EOC and SOC. Without Foreign Aid, India would have been a different nation.

4.5

Econometric Specification of the Model

On the basis of the literature reviewed theory and empirical relationship on the Aid-Growth nexus carried by the number of economists notably Dawson and Tiffin (1997), Chaudhuri (2011), Mallik (2008) and Qayyum (2011), we develop a bivariate model to trace the longrun relationship and to check the causal direction between Foreign Aid and Growth for a single country like India. Table 4.1 provides time-series data for model estimation (Figs. 4.2, 4.3, 4.4 and 4.5). Y = a + b(Aid) + e

(4.2)

log Y = a + blog(Aid) + e

(4.3)

Log Specification

where, Y = GDP growth rate Aid = Foreign Aid as % of GDP Figure 4.6 plots the log differences of growth rate and Aid and also reflects the long-run behavior of both the variables. Deviation of both the variables from each other seems very high in the early period of study. However after 1990s onward, deviation of both the variables from each other seems to be very close which demonstrates high effectiveness of Aid on the growth process in Indian economy. From this empirical exercise, we can infer that there has been a long-run and positive relationship between Foreign Aid and Growth process in Indian economy.

98

M. PAL

Table 4.1 Trends of Aid GDP ratio (%) and growth rate of India (1971–2013) Year

Aid % of GDP

1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985

1.47 0.85 0.9 1.22 1.61 1.67 0.8 0.81 0.87 1.15 1 0.8 0.83 0.78 0.67

GDPgr

Year

Aid% of GDP

GDPgr

Year

Aid % of GDP

GDP

5.1 1.1 −0.3 4.6 1.2 9.1 1.2 7.5 5.5 −5.2 7.2 6.1 3.1 7.7 4.3

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

0.79 0.6 0.65 0.59 0.43 1.01 0.84 0.52 0.7 0.48 0.48 0.39 0.38 0.32 0.29

4.5 4.3 3.8 10.5 6.7 5.6 1.3 5.1 5.9 7.3 7.3 7.8 4.8 6.5 6.2

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

0.35 0.34 0.12 0.11 0.23 0.15 0.11 0.17 0.18 0.17 0.18 0.09 0.13

4.3 6.1 4.2 8.5 9.5 9.7 9.6 9.3 6.7 8.4 8.4 6.5 4.5

Source Author’s own compilation based on the Data from WDI (World Bank), HBS (RBI) 1.0 0.5 0.0 -0.5 -1.0 -1.5 -2.0 -2.5

75

80

85

90

95

00

05

10

15

Fig. 4.2 Plot of log Aid (Source Author’s own work) 1.2 0.8 0.4 0.0 -0.4 -0.8 -1.2

75

80

85

90

95

00

Fig. 4.3 Plot of dlog Aid (Source Author’s own work)

05

10

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

99

2.4 2.0 1.6 1.2 0.8 0.4 0.0

75

80

85

90

95

00

05

10

Fig. 4.4 Plot of log Gr (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) 3 2 1 0 -1 -2 -3

75

80

85

90

95

00

05

10

Fig. 4.5 Plot of dlog Gr (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work)

4.6

Empirical Results and Discussion 4.6.1

Order of Integration

Following convention, we use the Logarithm of Foreign Aid and the Logarithm of real GDP (Y) so that first differences of these variables reflect the rate of change. A unit roots analysis is carried out to investigate the stationarity properties of the data. Tables 4.2 and 4.3 report the results of the ADF and Phillips–Perron Unit roots tests for real GDP growth and Aid. The results indicate that the first differences of the two variables are on a stationary process, and hence both real GDP growth rate and Foreign Aid are integrated of order 1, i.e. 1 (1).

100

M. PAL

2 1 0 -1 -2 -3 75

80

85

90

95

00

05

10

Blue line =Growth Rate Red line = Aid

Fig. 4.6 Plot of log differences of growth rate and Aid (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) (Color figure online)

Table 4.2 Tests for stationary of the variables (1971–2013)

Variables

Log GDP level First Difference LogAid level First Difference

A.D.F

Conclusions

Without Trend

With Trend

3.1296

1.1515

−3.8939*

−5.5143*

1 (1)

−1.0921 −5.3705*

−2.7263 −5.2696*

1 (1)

Notes Critical values for ADF without Trend are 1% (−3.6537), 5% (−2.9571), 10% (−2.6171); Critical values for ADF with Trend are 1% (−4.2820), 5% (−2.3.5614), 10% (−3.2138) Significance at the 1%, 5% and 10% level is indicated by *, ** and ***, respectively Source Author’s own computation by using EViews-6

Table 4.4 and Table 4.5 report the values of the test statistics both on their level and their first differences. It is found that the absolute value of the Log GDP and Log Foreign Aid is smaller than their critical values, implying that they are non-stationary in level. However, in the next step, test statistics of the variables in their first differences exceed the critical value irrespective of the test applied. Therefore, we can conclude that all

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

Table 4.3 Results of Phillips–Perron (PP) unit root test

Variables

Phillips–Perron Without Trend

Log GDP level First Difference Level LogAid level First Difference Level

101

Conclusions

With Trend

3.4932 −5.5947*

−1.3786 −7.4116*

1(1)

−1.2050 −5.3908*

−2.6141 −5.2079*

1 (1)

Notes Without Trend 1% (−4.2605), 5% (−3.5514), 10% (−3.2081); With Trend 1% (−4.712), 5% (−3.5562), 10% (−3.2109) Source Author’s own computation by using EViews-6

Table 4.4 Results of Johansen cointegration test (trace statistics) for Aid and growth Series: LogGDP LogAid Hypothesized No. of CE(s)

Eigenvalue

Trace Statistic

0.05 Critical Value

Prob.**

None* At most 1

0.444955 0.017585

20.01278 0.585469

15.49471 3.841465

0.0097 0.4442

Notes Trace test indicates 1 cointegrating eqn(s) at the 0.05 level; *denotes rejection of the hypothesis at the 0.05 level; **MacKinnon-Haug-Michelis (1999) p-values Source Author’s own computation by using EView-6

variables are integrated of order one I (1). The ADF test for the variables in the level form is based on the inclusion of an intercept and a trend term while the tests for the first difference do not include a trend term. The lag chosen for the ADF test is determined using popular information criterion like AIC or BIC. 4.6.2

Johansen Cointegration Test

From the Tables 4.4, 4.5 and 4.6, we find the positive and long-run relationship between Aid and economic growth in India because the Trace Statistics is more than its critical value (i.e. 20.01 more than 15.49). Our results are also supported by the value of Maximum Eigenvalue which is

102

M. PAL

Table 4.5 Results of Johansen cointegration test (maximum eigen-value) for Aid and growth Hypothesized No. of CE(s)

Eigenvalue

Max. Eigen Statistic

0.05 Critical Value

Prob.**

None * At most 1

0.444955 0.017585

19.42731 0.585470

14.26460 3.841466

0.0070 0.4441

Notes Max. eigenvalue test indicates 1 cointegrating eqn. at the 0.05 level; *denotes rejection of the hypothesis at the 0.05 level; **MacKinnon-Haug-Michelis (1999) p-values Source Author’s own computation by using EViews-6

also more than its critical value. And our normalized function value also supports the positive results, which shows that one percent rise in Foreign Aid causes 0.36% rise in growth rate in India. Table 4.7 demonstrates the pairwise Granger causality results which confirm our hypothesis of strong causal direction from Aid to Growth in India at one lag and two lags also. Table 4.8 demonstrates that in VECM upper panel, Aid elasticity coefficient also resembles with the normalized results. Further, ECT term value is equal to −0.31 which shows that during one year period, the level of disequilibrium is corrected by 31%. Our VECM reveals two important features: (a) GDP in India is Granger caused by Aid the causality runs Table 4.6 Normalized cointegrating coefficients

LogGDP

LogAid

1

0.359550 (0.00149)

Note Significance at 1%, 5% and 10% level is indicated by *, ** and ***, respectively Source Author’s own computation by using EViews-6

Table 4.7 Granger causality results Null Hypothesis

Obs

F-Statistic

Prob

Log Aid does not Granger Cause Log GDP Log GDP does not Granger Cause Log Aid

35

4.92939** 0.12159

0.0141 0.8859

Aid → GDP Note Significance at the 1%, 5% and 10% level is indicated by *, ** and *** respectively Source Author’s own computation by using EViews-6

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

103

more from Aid to GDP (b) Aid tends to increase productivity in Indian economy. Theoretically, it is important to know the fact that the individual coefficient from VECM is very difficult to simplify and interpret the result. For this, it is important to analyze the dynamic properties of the model by examining the impulse response function (IRF) and Variance Decomposition (VDC). Table 4.9 and Table 4.10 show the results from Cholesky variance decomposition technique. A good proportion of the variance in GDP shocks is attributable to shocks in Aid. The impulse response functions coming from standard deviation shocks to Aid with the response of GDP are traced out in Fig. 4.7. Response from shocks in variable provides a path for GDP. In the case of Aid, the path declined and climbed after two years, again after 3 years declined, and then climbed up to 5 years and then becomes constant up to 10 years. IRF and variance decomposition results also support our findings. It appears that Foreign Aid has made positive contribution in Indian economy, even after declining trends of Aid/GDP ratio in India. These findings are supported by the Burnside and Dollar (2000) model of Aid effectiveness.

4.7

Conclusions

The chapter attempts to test empirically the positive relationship between Foreign Aid and Economic Growth in India for the period of 1971–2013. The chapter improves upon earlier work on Foreign Aid-Growth nexus, because it involves Johansen Cointegration technique of 1991 to trace the long-run relationship between Foreign Aid and economic growth in India. Trace Statistic and Maximum Eigenvalue results confirm the positive and long-run relationship between Foreign Aid and Economic Growth in India. Normalized function shows that 1% rise in Aid/GDP ratio causes 0.36% growth rate to increase in India. In VECM upper panel also, elasticity coefficient also resembles the normalized results. ECT term value is equal to –0.31which shows that during one year period, the level of disequilibrium is corrected by 31%. Granger causality results also confirm strong causal direction from Foreign Aid to Growth in India at one lag and two lags also. Our VECM reveals two important features: (a) GDP in India is Granger caused by Aid the causality runs more from Aid to GDP (b) Aid tends to increase productivity in Indian economy. IRF and variance decomposition results also support our findings. It appears that Foreign Aid has made positive contribution in Indian economy, even

104

M. PAL

Table 4.8 Results of Vector Error Correction Model for Aid and growth rate

Cointegrating Eq:

CointEq1

LogGDP(−1) LogAid(−1)

1.000000 0.285093 (0.06888) [4.13910] −1.489016

C Error Correction:

D(LogGDP)

D(LogAid)

CointEq1

−0.303345 (0.36631) [−3.55806] 0.142490 (0.28043) [0.50812] 0.218033 (0.17688) [1.23264] −0.055797 (0.24769) [−0.22526] −0.190864 (0.22280) [−0.85664] −0.021507 (0.07584) [−0.28356]

0.504815 (0.26802) [1.88349] −0.447898 (0.20518) [−2.18291] −0.179050 (0.12942) [−1.38345] −0.651142 (0.18123) [−3.59285] −0.711520 (0.16302) [−4.36456] −0.159394 (0.05549) [−2.87226]

D(LogGDP(−1))

D(LogGDP(−2))

D(LogAid(−1))

D(LogAid(−2))

C

R-squared Adj. R-squared Sum sq. resids S.E. equation F-statistic Log likelihood Akaike AIC Schwarz SC Mean dependent S.D. dependent

0.711031 0.657518 4.531068 0.409655 13.28713 −14.06340 1.215964 1.488056 −0.003965 0.700003

Determinant resid covariance (dof adj.) Determinant resid covariance Log likelihood Akaike information criterion Schwarz criterion

0.481172 0.385092 2.425758 0.299738 5.008065 −3.753977 0.591150 0.863242 −0.075939 0.382241 0.015077 0.010093 −17.81719 1.928314 2.563196

Source Author’s own computation by using EViews-6

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

Table 4.9 Variance decomposition of log GDP

105

Perid

S.E

LogGDP

LogAid

1 2 3 4 5 6 7 8 9 10

0.426551 0.474386 0.481911 0.490571 0.495367 0.500115 0.503832 0.507097 0.509827 0.512166

100.0000 92.83232 91.08077 88.44005 86.73615 85.16957 83.93516 82.88651 82.01952 81.28999

0.000000 7.167679 8.919231 11.55995 13.26385 14.83043 16.06484 17.11349 17.98048 18.71001

Source Author’s own computation by using EViews-6

Table 4.10 Variance decomposition of log Aid

Perid

S.E

LogGDP

LogAid

1 2 3 4 5 6 7 8 9 10

0.367890 0.441687 0.512957 0.561378 0.601417 0.633018 0.659045 0.680421 0.698202 0.713037

1.104772 0.907533 1.506209 1.464891 1.563211 1.578675 1.607785 1.622496 1.636202 1.645937

98.89523 99.09247 98.49379 98.53511 98.43679 98.42133 98.39222 98.37750 98.36380 98.35406

Source Author’s own computation by using EViews-6

after declining trends of Aid/GDP ratio in India. Findings of this paper are consistent with the model of Aid effectiveness: Burnside and Dollar (2000), Addison et al. (2018), Mallik (2008), Collier and Dollar (2002).

106

M. PAL

Response of LOGGDP to Cholesky One S.D. Innovations

.5 .4 .3 .2 .1 .0 -.1 -.2

1

2

3

4

5

6

LOGGDP

7

8

9

10

LOGODA

Response of LOGODA to Cholesky One S.D. Innovations

.4

.3

.2

.1

.0

1

2

3

4

5

LOGGDP

6

7

8

9

10

LOGODA

Fig. 4.7 Response of log GDP and log ODA to Cholesky One S.D. innovations (Source Author’s own work)

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

107

Appendix 4.1 Measuring concessionality in Foreign Aid—An Application to India Measuring Concessionality in Foreign Aid: Following Ohlin (1966) and Sharma (1975), we have empirically estimated the concessionality in the external Aid in India. Concessionality in Aid may be defined as any capital transfer, the interest and repayment terms of which are less than those available to the recipient in the private market and is provided principally for non-commercial objectives. Grants generally have 100% grant element. Some credits especially from the IDA, a soft loan window of the World Bank has a very high grant element of nearly 90% as they are repayable over a period of 50 years with 10 years grace period and no interest charges except service charge of 0.75%. The most concise approach in finding the grant element and value was formulated by Ohlin (1966). According to him, the grant element and the grant value are found by solving the following equations that accommodate the possibility of a loan’s grace period. With the help of Ohlin’s formula, we have calculated the grant element in external Aid. The following is the standard model developed by Ohlin (1966). However, it has been empirically tested by the number of writers. The following is the Ohlin model. Ohlin Model )( ) ( e−qG − e−qT i 1− ×L (4.4) G.E. = 1 − q q(T − G) Examples: 1 L = loan amounting to $30.0 million i = interest rate of 3 percent q = discount rate of 10 percent G = grace period of 5 years T = maturity period of 15 years E = base of natural Log of 2.718 Grant element, GE will be: (

( / ) G.E = 1 − 0.03 0.10

−0.10×5 −2.718−0.10×15 0.10(15−5)

1− 2.718

= 0.7 × (1 − 0.6 + 0.223) = 0.43162 = 43.16% Grant value, GV will be: GV = GE × L

)

108

M. PAL

= $30.0 million × 0.43162 = $12.9486 million Putting these values in terms of formula, we find 43.6% grant element in this loan. In other words, grant value will be equal to grant element to be multiplied by the loan amounting to US $30 ( ) million, i.e. GV/ =( (Grant Value) = GE × L $30 × .43162 = 12.95 OR G.E. = / ) GV L 13 30 = .4333 . Now if the r is increased to 4%, we find that GE will be less (i.e.) around 25%. Hence we can conclude that higher the r lower will be GE. The IDA has been the main instrument in perfecting the concept of concessional development finance in the world. It continued to occupy major position having more than 60% in total concessional lending provided by the Multilateral Development Banks (MDBs). Table 4.11 reveals the fact that IDA credits contain grant element about more than 78% among major Aid donors to India. Major donors like the USA, the UK, West Germany, Canada provided grant element of around 21 to 36%. The socialist countries like the USSR have shown grant element within the range of 11–16%. However, now Japan has become the second largest concessional Aid provider to India after IDA. India has been the most fortunate and favored nations in receiving high position in IDA lending position. During 1960 and 1970s, India used to receive about 40% of total IDA lending in the World. Even now when India is going to establish her own lending institution, a question is being debated “Why India should not be graduated from the soft pool,” India remains as a top borrower of IDA global lending. Table 4.11 The range of grant element associated with various types of external source Countries

I

G

T

GE as %age of Face Value

Canada IDA IBRD USA U.K USSR Japan

6 0.75 4–9 3.5 to 5.5 3.5 2–3 4–5

3–6 10 5 1–10 5–7 1 3–5

15–25 50 7–25 7–40 11–25 7–12 9–18

37 78 3.4 35 24 17 47

Source Author’s own calculation

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

109

Appendix 4.2 See Fig. 4.8.

Case Studies

Grant –Element in India Sharma (1975)

World Bank in Asia Pal M. (1985)

Fig. 4.8 Aid—Growth Nexus Model—An analytical tour

110

M. PAL

Notes 1. As per OECD, ODA/Foreign Aid/External Assistance has been defined in such a way that the loan amount which is granted by the donor nations to Aid recipient emerging nations must include at least 25% grant element. This is an essential condition if Aid is to be named as Aid. It means that Aid recipient will repay only 75% of loan after the expiry of grace period and maturity period, may be 20 years. Grace period generally ranges from four to five years, in this period no repayment is done; hence, 75% portion of loan will be repaid in 15 years. ODA is advanced through bilateral countries and MDBs such as the IBRD and the IDA, but there are two variants in ODA, IBRD loan contains only 6% grant elements and IDA credits contain more than 75% grant element. ODA is designed to promote the economic development and welfare of developing countries. Military assistance is not included in ODA. Hence, ODA needs further conceptual clarification by the OECD authorities. 2. International Development Association (IDA), a soft loan window of the World Bank, provides credits to poor nations with a grant element of around 80%. India has been the largest beneficiary in the World acquiring more than US $50 billion till December 31, 2015. IDA has advanced about US $222 billion, while its annual lending comes on an average to the tune of US $13 billion. 3. Stabilizations and Structural Adjustment Programme (SAP) is designed by the IMF and World Bank both to help the crisis-ridden countries to solve their economic crisis by providing loans under two different conditions. India was helped in the year of economic crisis in 1991 with the help of a big loan under SAP conditions. With the help of IMF and World Bank loan, India stabilized her economy and undertook some structural adjustment reforms and in this way SAP laid down strong foundation for further economic growth and development in India. 4. Addison et al. (2018) in their study provide four new findings on Foreign Aid-Growth nexus: First, Foreign Aid shows 20% marginal productivity. Second, micro–macro paradox of Mosley (1987) does not exist. Third, Aid does not increase the Dutch Disease. Fourth: Aid increases tax revenue rather than reducing Principle of Substitution (Griffin 1970), Griffin and Enos 1970) does not apply in this case. 5. For comprehensive study on the debate on the economic status of India being a donor nation on the one hand and being one of the largest recipients of Foreign Aid in the World on the other hand, detailed analysis and effective debate on this topic, see Kanbur (2016), Aid 2 The Economist (2011). 6. For a comprehensive survey on the Harrod-Domar model, see Bowles (1987) and Easterly (1999).

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

111

7. For detailed theory and empirical discussion, see Bacha (1990) and Taylor (1990). 8. External assistance/ODA/Foreign Aid has become a very critical and unresolved topic in the World economy especially in the Aid recipient emerging nations notably India. After the destruction of the European, the USA introduced a famous Marshal Plan to help the European countries. For a detailed analysis on this topic, see Islam (1999). 9. For a detailed analysis on the development paradigm, see Papanek (1972, 1973) and also Chapters 5 and 6 of this book. 10. See, Griffin (1970); Griffin and Enos (1970). 11. For a detailed analysis, see Bauer (1971a), Easterly (2001). 12. For a comprehensive analysis, see Burnside and Dollar (2000). 13. For a comprehensive analysis, see Dalgard and associates (2004). 14. For a detailed and systematic survey of different case studies on India, see notably Lipton and Toye (1991), Cassen and associates (1986) and Riddell (1987). 15. For a detailed analysis on the topic of cost overrun and time overrun relating to infrastructure projects in India, see Singh (2009) and for external funds in the pipeline for long time causing heavy debt burden and high debt servicing ratio, see Rao (1952, 1963). 16. The close co-operation between India and the World Bank goes far beyond the normal creditor and debtor nations. As a World Development Agency, a number of steps have been taken by the Bank in response to India’s complex and compelling problems. The active association of India and the World Bank is nearly of 70 years of standing. It began two years after India attained independence. A good deal of progress has been made to India during the past seven decades. India has created a large and complex industrial structure and laid the foundation for accelerated growth in agriculture. For comprehensive view on India and World Bank close relationship, see Pal (1985). 17. Under the theory of re-scheduling time period of loan, repayment is rescheduled. The basic concept is that: “Don’t pay today” “pay tomorrow” or day-after tomorrow”; hence, it is a relaxation of time period. If a nation is likely to default in her repayment in international obligations market, the nation is debarred for long time from the international market. However, sovereign defaults should not be allowed. Nowadays, crisis-ridden countries are protected from the default. However, sometimes, it happened, as a recent example of European countries. In brief, we can say that the IBRD has been the major partner in India’s development process and India has never defaulted in her repayment of foreign obligations except one time. India’s repayment was re-scheduled in 1967. For a detailed analysis, see Pal (1985).

112

M. PAL

References Acharya, R., and S. Kar. 2001. International trade and economic development. Oxford: New Delhi. Addison, et al. 2018. Aid is not dead, Policy Brief. UNU-WIDER, Helsinki, Finland. Bacha, E.L. 1990. A three gap model of foreign transfers and GDP growth rate in developing countries. Journal of Development Economics 32 (2): 279–296. Bajaj, J.L., and V.R. Panchamukhi. 1990. Aid in the 1990s with special reference to the World Bank and IDA, RIS Occasional Paper No. 30. Balassa, B. 1964. The capital needs of the developing countries. Kyklos 17 (2): 197–206. Bauer, P. 1991. The development economics. Cambridge, MA: The MIT Press. Bauer, P.T. 1971a. Dissent on development. London: Weindenfeld and Nicholson. Bauer, P.T. 1971b. Reality and rhetoric studies in the economic of development. London: Weidenfeld and Nicolson. Bazoumana, O., and Eric Strobl. 2008. Aid, policy and growth: Does Aid modality matter? Review of World Economics 144 (2): 347–365. Bhagwati, J.N. 1985. Essays on development economics: Wealth and poverty, 192–193. Cambridge, USA: MIT Press. Bhagwati, J. 1998. The design of indian development, the economic reforms and development. In Essay for Man Mohan Singh, ed. I.J. Ahluwalia and J.M.D. Little, 23–39. Delhi: Oxford University Press. Boone, P. 1994. The impact of foreign aid on savings and growth, Working Paper, No. 1265. London: Center for Economic Performance. Bowles, P. 1987. Foreign aid and domestic saving in LDCs: Some tests for causality. World Development 15 (6): 789–796. Brautigarb, D.A., and S. Knack. 2004. Foreigm aid, institutions and government in Sub-Saharan Africa. Economic Development and Cultural Change 52 (2): 255–285. Burnside, C., and D. Dollar. 1997. Aid policies, and growth. Policy Research Working Paper 1777. World Bank, Development Research Group, Washington, DC. Burnside, C., and D. Dollar. 2000. Aid, policies and growth. American Economic Review 90 (4): 847–868. Burnside, C., and D. Dollar. 2004. Aid, policies, and growth: reply. The American Economic Review 94 (3): 781–784. Cassen, R., and Associates. 1986. Does aid work? Report to the intergovernmental task force. Oxford University Press. Chaudhuri, P. 1978. The Indian economy poverty and development. New Delhi: Vikas Publishing House. Chenery, H.B., and A.M. Stout. 1966. Foreign assistance and economic development. American Economic Review 56 (4): 679–733.

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

113

Chenery, H.B., and P. Eckstein. 1970. Development alternatives for Latin America. Journal of Political Economy 78 (4): 966–1006. Chowdhury, M., and A. Das. 2011. Aid-growth nexus in South Asia: Evidence from time series and panel cointegration. Research in Applied Economics, Macrothink Institute, Online Publication 3 (1): 1–19. Collier, P. 2007. The bottom Billion: Why the poorest countries are failing & what can be done about it. Oxford: University Press. Collier, P., and D. Dollar. 2001. Can the world cut poverty in half? How policy reform and effective aid can meet international development goals. World Development 29 (11): 1787–1802. Collier, P., and D. Dollar. 2002. Aid allocation and poverty reduction. European Economic Review 46 (8): 1475–1500. Crag, B., and D. Dollar. 1997. Aid, the incentive regime and poverty reduction, Policy Research Working Paper, 1937. Washington, DC: World Bank. Dalgarrd, C.J., H. Hansen, and F. Tarp. 2004. On the empirics of foreign aid and growth. The Economic Journal 114 (496): 191–216. Dawson, P.J., and R. Tiffin. 1997. Is there a long-run relationship between ODA and GDP? The Case of India, Applied Economic Letters 6 (5): 275–277. DFID. 2010. Annual Report. London: DFID. Dollar, D., and L. Pritchett. 1998. Assessing aid, what works, what does not, and why. A World Bank Study: Oxford University Press, World Bank, Washington, DC. Domar, E. 1946. Capital expansion, rate of growth and employment. Econometrica 14 (2): 137–149. Doucouliagas, H., and M. Paldam. 2009. Conditional aid effectiveness: A meta analysis. Journal of International Development 21 (7): 1582–1601. Dowling, J.M., and U. Hiemenz. 1983. Aid, saving and growth in Asian region. The Developing Economies 21: 3–13. Easterly, W. 1999. The ghost of financing gap: Testing the growth model used in the International Financial Institutions (IFIs). Journal of Development Economics 60 (2): 423–438. Easterly, et al. 2004. Aid, policies and growth: Comment. American Economic Review 94 (3): 774–780. Easterly, W. 2007a. Reinventing foreign aid. Cambridge, Massachusetts, USA: The MIT Press. Easterly, W. 2007b. The whitemans burden, why the west’s efforts to aid the rest have done so much ill and so little good. Oxford. Easterly, W., I. Roumeen, and J.E. Stiglitz. 2001. Shaken and stirred: Explaining growth volatility. In Annual World Bank Conference on Development Economics, ed. B. Pleskovic and N. Stern. Washington, DC: World Bank. Friedman, M. 1958. Foreign economic aid. Yale Review 47 (4): 501–516.

114

M. PAL

Ghulam, M. 2005. Impact of foreign aid in economic development in Pakistan (1960–2002). Gounder, R. 2010. Aid-growth nexus: Empirical evidence from Fiji. Applied Economics 33 (8): 1009–1019. Griffin, K.B. 1970. Foreign capital, domestic savings and economic development. Oxford Bulletin of Economics and Statistics 32 (2): 99–112. Griffin, K.B., and J.L. Enos. 1970. Foreign assistance: Objectives and consequences. Economic Development and Cultural Change 18 (3): 313–327. Hansen, H., and F. Tarp. 2000. Aid effectiveness disputed. Journal of International Development 12 (3): 375–398. Harrod, R.F. 1939. An essay in dynamic theory. The Economic Journal 49 (193): 14–33. Iqbal, Z., J. Jeffrey, and G. Pyatt. 2000. Three gap analysis of structural adjustment in Pakistan. Journal of Policy Modeling 22 (1): 117–138. Islam, A. 1992. Foreign Aid and economic growth: An econometric study of Bangladesh. Applied Economics 24 (5): 541–544. Islam, A.M. 1999. Foreign assistance and development in Bangladesh. In Foreign aid: New perspectives, recent economic thought, vol. 68, ed. K.L. Gupta, 211– 231. Boston: Springer. Javid, M., and A. Qayyum. 2011. Foreign aid and growth in Pakistan: The role of macroeconomic policies, Working Paper, 1–15. Islamabad: Pakistan Institute of Development Economics. Kanbur, R. 1987. Measurement and alleviation of poverty: With an application to the impact of macroeconomic adjustment. IMF Staff Papers World Bank, Washington, DC, 60–85. Kanbur, R. 2005. Reforming the formula: A modest proposal for introducing development outcomes in IDA allocation procedures. CEPR Discussion Paper No. 4971. Kanbur, R. 2016. Can a countrybea donor and recipient of aid? In Development in India: micro and macro perspectives, ed. S.M. Dev and P,G. Babu. New Delhi: Springer. Karras, G. 2006. Foreign aid and long run economic growth: Empirical evidence for a panel of developing countries. Journal of International Development 18 (7): 15–28. Knack, S. 2000. Aid dependence and the quality of overnice: A cross country empirical analysis. Washington, DC: World Bank Policy Research Paper. Lensink, R., and O. Morrissey. 2000. Aid stability as a measure of uncertainty and the positive impact of aid on growth. Journal of Development Studies 36 (3): 31–49. Levy, V. 1988. Aid and growth in the Sub-Saharan Africa: The recent experience. European Economic Review 32 (9): 1777–1795.

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

115

Lipton, M., and T. John. 1991. Does aid work in India? A country study of the impact of ODA: Routledge. Mallik, G. 2008. Foreign aid and economic growth: A cointegration analysis of the six poorest African countries. Economic Analysis and Policy 38 (2): 251–260. Marjit, S., and V. Mukherjee. 2016. Does foreign aid corrupt? A theoretical note. In Understanding development—An Indian perspective on legal and economic policy, ed. B. Swepnendu and others. New Delhi: Springer. Mbaku, M. 2006. Foreign aid and economic growth in Cameroon. Applied Economics 25 (10): 1309–1314. Mavrotas, G. 2002. Aid and growth in India: Some evidence from disaggregated aid data. South Asia Economic Journal 3 (1): 19–48. Mc Gillivreay, M., S. Feeny, N. Hermes, and R. Lensink. 2006. Controversies over the impact of development aid: It works, it does not, it can, but that depends. Journal of International Development 18 (7): 1031–1050. McKinnon, Ronald I. 1964. Foreign exchange constraints in economic development and efficient aid allocation. Economic Journal 74 (294): 388–409. Minpiu, C., and G.R. Sanjay. 2010. Development aid and economic growth: A positive long-run relation. The Quarterly Review of Economics and Finance 50 (1): 27–39. Morrisey, O. 2001. Does aid increase growth in Cameroon. Progress in Development Studies 1 (1): 37–50. Mosley, P. 1980. Aid, saving and economic growth revisited. Oxford Bulletin of Economics & Statistics 42 (2): 79–95. Mosley, P. 1985. The political economy of foreign aid: A model of the market for a public good. Economic Development and Cultural Change 33 (2): 373–393. Mosley, P. 1987. Foreign aid: Its defense and reform. Brighton, England. Mosley, P. 1986. Aid effectiveness: The micro-maro paradox, Istitute of Development Studies (IDS) Bulletin. Sussex 17 (2): 22–35. Moyo, D. 2010. Dead aid: Why aid is not working and how there is a better way for Africa. Penguin. Nikhakht, E. 1984. Foreign loans and economic performance, the experience of less developed countries. Praeger. Ohlin, G. 1966. Foreign aid policies reconsidered. Paris: Organization for Economic Cooperation and Development (OECD). Over, M. 1975. An example of the simultaneous equations problem: A note on foreign assistance: Objectives and consequences. Journal of Economic Development and Cultural Change 23 (4): 751–756. Pal, M. 1985. World bank and the third world countries of Asia. New Delhi: National Publishing House.

116

M. PAL

Pal, M. 1995, August 28–30. Foreign capital - growth nexus in India Paper presented at IIDS international conference held at Swedish Academy of Science. Helsinki, Finland. Pal, M. 2017. Foreign aid to India—A case study of IDA (World Bank soft window) and Indian economy (1960–2018) unpublished, available on request to the author. Pallage, S., and M.A. Robe. 2001. Foreign aid and the business cycles. Review of International Economics 9 (4): 641–672. Pandey, A.K. 2014, December. Evidence of trade led growth in India: Cointegration, impulse response and variance decomposition analysis. Paper presented at the annual conference of Indian Economic Association, Udaipur. Pandit, B.L. 2015. The global financial crisis and the Indian economy. New Delhi: Springer. Papanek, G.F. 1972. The effect of aid and other resource transfer on savings and growth in less developed countries. The Economic Journal 82 (327): 934–950. Papanek, G.F. 1973. Aid, foreign private investment, saving and growth in less developed countries. Journal of Political Economy 81 (1): 120–130. Peter, B., and B. Yamey. 1981. The political economy of foreign aid. Lloyds Bank Review 0 (142): 1–14. Raghuram, C.R., and A. Subramanian. 2008. AID and growth: What does the cross-country evidence really show? The Review of Economics and Statistics 90 (4): 643–665. Rao, V.K.R.V. 1952. India’s first five year plan—A descriptive analysis. Pacific Affairs 25 (1): 3–23. Rao, V.K.R.V., and D. Narain. 1963. Foreign aid and India’s development. Bombay: Asian Publishing House. Riddell, R.C. 1987. Foreign aid reconsidered. Baltimore, USA: The Johns Hopkins University Press. Rodan, R. 1961. International aid for under-developed countries. Review of Economics and Statistics 43 (2): 107–138. Sharma, R.K. 1973. Grant element in external assistance to India. The Indian Economic Journal XXI: 124–131. Sharma, R.K. 1977. Foreign aid to India: An economic study, 110016. New Delhi: Marwah Publication. Singh, R.D. 1985. State intervention, foreign economic aid, savings and growth in LDCs: Some recent evidence. Kyklos 38: 216–232. Singh, R. 2009. Delays and cost overruns in infrastructure projects: An enquiry into extents, causes and remedies, Working Paper No. 181, Centre for Development Economics, Delhi School of Economics, University of Delhi. Streeten, P., and H. Roger. 1971. International capital movements, Queen Elizabeth House, University of Oxford, 1970 (mimeo).

4

FOREIGN AID-GROWTH NEXUS IN INDIA: COINTEGRATION …

117

Sukhatme, V. 1983. Assistance to India. In The development impact of economic assistance to LDCs (Vol. II), ed. A.O. Krueger and V.W Rutten. Economic Development Centre, University of Minnesota. Synder, D.W. 1993. Donor bias toward small countries: An overlooked factor in the analysis of foreign Aid and economic growth. Applied Economics 25 (4): 481–488. Taylor. 1990. A three gap analysis of foreign resources flow and developing country growth. In The rocky road to reform, ed. L. Taylor. Helsinki, Finland: WIDER. The Economist. 2011, August 13. India is thinking about setting up its own aid agency. Why should others give Aid to India? http://www.economist.com/ node/21525899 White, H. 1992. Aid, investment and growth: What prospects in the 1990s? Working Paper Series No. 133, 1–30. Edward Elgar. World Bank. 1998. Assessing aid, what works, what doesn’t and why. Oxford University Press. Weisskoff, T.E. 1972a. An econometric test of alternative constraints on the growth of underdeveloped countries. The Review of Economics and Statistics 54 (1): 67–78. Weisskoff, T.E. 1972b. The impact of foreign capital inflow on domestic savings in underdeveloped countries. Journal of International Economics 2 (1): 25– 38. Weissman, S. 1974. The trojan horse: A radical look at foreign aid. San Francisco: A Pam parts Press Reader. Zafar, I., J. Jeffrey, and G. Pyatt. 2000. Three-gap analysis of structural adjustment in Pakistan. Journal of Policy Modeling 22 (1): 117–138.

CHAPTER 5

Foreign Capital-Growth Nexus in India: Cointegration and Causality

5.1

Introduction

During the last two and a half decades, large number of researchers have applied their academic exercise on two channels of foreign capital that is Foreign Aid and FDI. They have applied their mind on the FDI-Growth nexus and potential macrodeterminants of FDI and also on Foreign AidGrowth relationship in the developed and emerging nations. However, recent work on the impact of foreign remittances on the growth process in the emerging economies has also been carried out. Very few studies dealing with a direct relationship between net capital inflow and growth in the developing countries have appeared. Basic relationships between the net capital inflow and growth have a significant benefit for the developing economies around the world. Countries with sound economic policies and sound financial system which includes money, capital markets and financial institutions, have a great potential to attract the massive amount of foreign capital with its positive impact on the economic development and economic growth in the capital recipient countries. After studying the pros and cons of FDI-Growth nexus and Foreign Aid-Growth nexus separately in India in separate models in Chapters 3 and 4, we now turn to see the growth effect of aggregate net foreign capital inflows (hereafter NFC) on the growth process in India. Khan (1998) defines net capital inflows which comprise net foreign direct investment, net portfolio investment and other long- and short-term © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. Pal, Foreign Capital and Economic Growth in India, https://doi.org/10.1007/978-981-99-2299-4_5

119

120

M. PAL

net investment flows including official and private borrowing.1 Foreign capital in this chapter includes official as well as private capital.2 In Chapter 4, we have given a detailed analysis of theoretical backdrop of two gap and three gap models and their inherent and operational problems in the policy making and application in Aid recipient countries. Keeping in view the basic requirement of the current research and debate and to fill the existing gap in the literature, the basic objectives of this chapter are: first, to examine the trends and magnitude of net aggregate foreign capital which include both public (debt creating foreign capital) and private (non-debt creating foreign capital) in India. Second, to examine the long-run relationship between the net capital inflows and economic growth and third objective is to examine the causal direction between NFC and growth in India. Rest of the chapter is structured as: Section 5.2 provides the review of specific studies dealing with ore or less the direct relationship between the two variables such as NFC and growth rate with the help of modern time-series technique. Section 5.3 deals with the trends and magnitude of net capital inflows and growth rates in India. Section 5.4 provides the model specification, empirical results and discussion derived from the results. Section 5.6 concludes with the main findings of the chapter.

5.2

Review of Empirical Literature

We have already discussed some theoretical detail on Foreign capitalGrowth nexus which takes into account three gap analysis, neo-classical and endogeneous growth theory of development economics in the Chapter 3 and notably in Chapter 4 also. In this chapter, we will focus on the studies which try to establish the direct empirical relationship between NFC inflows and growth in the emerging economies. We have identified some select and important studies: Dua and Sen (2013), P. Gupta (2016), A. N. Khan and N. Ansari (2014), M. M. Rahman and M. Shahbaz (2013), S. Abdelhafidh (2013), R. Rena and G. Ramakrishna (2013), C. Rangarajan and M. Prachi (2013), R. Ranjan and S. Kumar (2012), T. Hiroyuki (2011), N. C. Pradhan (2011), R. Dauda and S. Oladoyin (2008), Prasad et al. (2007), B. Yasmin (2005), N. Hachicha (2003), I. Chakraborty (2006), Hernandez et al. (2001); P. Sen (2007) and Khan (1998). P. Dua, and Sen P. (2013) examine the relationship between real exchange rate and the volatility of capital flows for the Indian economy

5

FOREIGN CAPITAL-GROWTH NEXUS IN INDIA …

121

for the period 1993 Q2 to 2010 Q4. Other variables include fiscal policy, monetary policy and indicators of external macrovariables. Estimation results indicate that the macrovariables indicate long-run relationship and each variable Granger-causes the real exchange rate . The VDC shows the determinants of the real exchange rate, in declining order in terms of their significance. A. N. Khan and N. Ansari (2014) examine the existence of positive and long-run relationship between net capital inflows and economic growth in India by using cointegration technique developed by Johansen and Juselius (1990) and Granger causality (1987) for the period 1991–92 to 2012–13. Findings confirm the unidirectional causality running from growth rate to net capital flows. Rena, R. and Ramakrishna, G. (2013) by using VECM, their findings show that foreign capital inflows are causing imports to rise and imports are causing inflows of foreign capital to rise and there exists a bidirectional causal relationship between two variables. Further they note that FPI remains more volatile than FDI flows in India. In their analysis of performance of external sector C. Rangarajan and M. Prachi (2013) estimate the sustainable level of CAD/GDP ratio which should be equal to 2.3% and to maintain this ratio, India needs net capital inflows in the order of US $ 50–70 billion annually. P. Gupta (2016) examines the facts that capital account liberalization has integrated Indian economy with global economy since the early 1990s. Further, she also points out that the macro policy measures such as foreign exchange reserve and liquidity management have been instrumental to manage sudden capital flight-in and sudden capital flight-out from the emerging economy of India. M. M. Rahman and M. Shahbaz (2013) investigate the positive and long-run relationship between foreign capital, imports and economic growth and also demonstrate the bidirectional causality with strong Granger causal direction running from foreign capital inflows and imports to economic growth in Pakistan. S. Abdelhafidh (2013) investigates causal direction between potential financial source of investment and economic growth in North African countries. With the application of VAR, he finds that domestic saving follows economic growth. His results also confirm foreign capital led growth hypothesis in Egypt and Algeria. R. Ranjan and S. Kumar (2012) in their empirical study they point out that like many other emerging market economies, India has also experienced a significant surge in foreign capital inflows since the period of mid-1990s with the help of cointegration technique. Their study

122

M. PAL

reveals that the contribution of foreign capital in the process of GDCF is recorded very high. VDC reveals the contribution of capital inflows to GDCF, where variation increases and reaches to about 13 percent by 10th period. Further short-term dynamics of the co integration shows ECT term which is around 23%. Their ECT term is significant and shows a minus sign which demonstrates the long-run equilibrium among the variables indicating also high speed of adjustment in Indian economy. T. Hiroyuki (2011) provides empirical evidence on the relationship between capital inflows and asset prices in selected East Asian emerging market economies such as Thailand, China, Hong Kong, Indonesia and Korea during the 2000s within the framework of IRF and VAR. He takes in to account direct and the indirect channel. Positive responses of share prices to portfolio inflows into stock market have been found to work in direct channel, whereas sterilization in foreign exchange markets works in the indirect channel. N. C. Pradhan (2011) empirically traces the long-run relationship between capital account liberalization and economic growth of non-agricultural GDP in India with the help of cointegration test. Granger pairwise causality coefficients are not significant; hence no causal direction between the two variables is detected. R. Dauda and S. Oladoyin (2008) investigate the impact of foreign private capital flows on economic development in Nigeria from 1986 to 2006 with the help of Granger-Causality test and OLS regression method findings demonstrate that Nigerian economy is mainly based on domestic investment. There is also a positive relationship between index of openness, foreign private capital and GDP. Prasad et al. (2007) try to trace the link between foreign capital inflows and economic growth in developing countries and question the validity of effectiveness capital inflow. According to them validity of capital inflows has invited a worldwide intense debate among the economic policy makers, researchers and economists. They conclude capital inflows cause overvaluation of exchange rates in non-industrialized nations which may cause decrease in growth rate. Further they point out that developing countries have limited amount of absorption capacity of FDI. They also point out that research on capital inflows must be optimistic which could serve as an instrumental in increasing the absorption capacity of foreign capital inflows in emerging countries. B. Yasmin (2005) applies the simultaneous equation model for the years 1970–71 to 2000–2001 for FCI, GNP and Savings. A positive and statistically significant relationship between FCI and growth appears

5

FOREIGN CAPITAL-GROWTH NEXUS IN INDIA …

123

to be established. FDI as a component of FCI demonstrates a positive and significant relationship with growth rate in Pakistan. Study further recommends FDI as growth-enhancing component of foreign capital. N. Hachicha (2003) examines the relationship between capital inflows and savings in Tunisia with an application of Johansen and Juselius (1990) cointegration technique, simultaneous error correction model and weak exogeneity test. Empirical estimates show a negative relationship between foreign capital inflows and country’s domestic savings. Further Granger’s causal direction in the long run runs from domestic saving to foreign capital while bidirectional causality appears in the short period. I. Chakraborty (2006) examines the existence of cointegration relationship between net inflows of foreign capital, real exchange rate and interest rate differential in India during the decade of 1990s. The similar upward trend of all these variables was due to efficacy of RBI policy of sterilized intervention in the foreign exchange market which also resulted in controlling the volatility of the real exchange rate. ECM also operates between net inflows of foreign capital and the real exchange rate. Hernandez et al. (2001) estimate the effect of contagion on capital inflows and conclude that the pull factors are the primary determinants of private capital inflows. Sen. P. (2007) says that due massive relaxation of capital account controls, India has invited unprecedented level of foreign capital which may serve as warning for further opening-up of the capital account. Khan (1998) explores the harmful effects of private foreign capital in the host countries in terms of management of large-scale foreign capital inflows. Many countries benefitted from inflows of large-scale private capital, but later due to flight-out of capital flows, these nations notably Mexico in the year of 1994 and financial crises in Asian Tigers in the 1997–98 experienced an adverse impact in terms of financial sector instability, expansion in money supply which caused upward inflationary trends, appreciation in real exchange rate , heavy indebtedness and ultimately increase in current account deficit.

5.3 Volatile Trends of Net Foreign Capital Inflow in India As already pointed out in this chapter, we use the term NFC which comprises both official and private foreign capital. If we look at the magnitude and trends of NFC, it was US $ 7.1 billion in 1991 and which

124

M. PAL

gradually increased to US $ 28 billion in 2005 and further increased to US $ 45 billion in 2007 and again massive amount (upsurge) of NFC to the extent of US $ 108 billion in 2008, entered Indian economy. This amount of NFC was around 8.6% of GDP. In absolute amount NFC inflow exceeded the value by US $ 92 billion while the absolute value of CAD was only US $ 15 Billion in 2008. Further, due to famous financial crisis of 2008, NFC declined to only US $7.2 billion in the year of 2009. However, NFC got momentum again in 2010 onward ranging from US $ 53 billion to US $ 68 billion in 2012–13. A lot of literature on the issue of surge and sudden stop of NFC has appeared during the last decade. For comprehensive survey on the fluctuating behavior of net capital inflows, see Rangarajan and Prachi (2013), Dua and Sen (2013), Ranjan and Kumar (2012) and Pal (2015)3 and also see Pithford thesis.4 If we look at the pattern of NFC/GDP ratio during the period of 10 years of 1971–80, NFC/GDP ratio remained 0.5% on an average, while during the period of 1981–90, the ratio increased from the level of 1.2 to 1.9% except one year when it was 2.1%. During the period of 1991–2000, it increased from 1.3 to 3.2%. However, NFC increased from 2.1% in 2003 to 8.6% in the peak year of 2008 while declined to a very low level around 0.5% in 2009. However, again it increased to more than 4.5% on an average since 2010 onward and also 6.1% in 2013. Table 5.1 provides time-series data for model estimation and also demonstrates the trends and fluctuations of current account deficit/GDP ratio and net capital inflow/GDP ratio during the study period from 1971 to 2013. The fluctuating trends of three macrovariables shown in Table 5.1 are demonstrated in Fig. 5.1. Further Figs. 5.2, Fig. 5.3 and Fig. 5.4 show the trends of growth rate, plot of log of growth rate and plot of d log of GDP growth rate, respectively. Figure 5.5 shows the upward trends of NFC/GDP ratio with highly volatile behavior from 2007 to 2009 with a sudden upsurge in 2008. Figure 5.6 depicts the plot of log of NFC/GDP ratio and also Fig. 5.7 demonstrates the plot of dlog of NFC/GDP ratio.

5.4

Model Specification, Data and Estimation

On the basis of number of studies which have shown long run relationship and direction of causality between foreign capital and growth (already reviewed empirically in the chapter, notably Prasad, et.al. (2007), Dua and Sen (2013), Khan (1998), we have developed a model of a single

5

Table 5.1 Time-series data for estimation of models of net foreign capital/GDP ratio and growth rate in India (1971–2013)

FOREIGN CAPITAL-GROWTH NEXUS IN INDIA …

125

Year

NFC/GDP (%)

CAD/GDP (%)

GDP growth rate

1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

0.9 1.2 0.4 0.1 1.1 0.3 0.2 0.2 0.9 0.4 1.2 0.8 1.8 2.1 1.4 1.9 1.8 1.9 1.9 1.9 2.2 1.5 1.6 3.2 2.6 1.2 3.1 2.4 2.1 2.3 2.1 1.8 2.1 2.8 3.9 3.1 4.8 8.6 0.5

−1.0 −1.0 −0.6 1.7 −1.2 −0.2 1.0 1.1 −0.2 −0.5 −1.5 −1.7 −1.7 −1.5 −1.2 −2.1 −1.9 −1.8 −2.7 −2.3 −3.0 −0.4 −1.4 −0.4 −1.0 −1.7 −1.2 −1.3 −1.0 −1.0 −0.6 0.7 1.3 2.3 −0.3 −1.2 −1.0 −1.3 −2.3

5.1 1.1 −0.3 4.6 1.2 9.1 1.2 7.5 5.5 −5.2 7.2 6.1 3.1 7.7 4.3 4.5 4.3 3.8 10.5 6.7 5.6 1.3 5.1 5.9 7.3 7.3 7.8 4.8 6.5 6.2 4.3 6.1 4.2 8.5 9.5 9.7 9.6 9.3 6.7

(continued)

126

M. PAL

Table 5.1 (continued)

Year

NFC/GDP (%)

CAD/GDP (%)

2010 2011 2012 2013

4.1 4.3 4.1 6.1

−2.8 −2.8 −4.2 −4.8

GDP growth rate 8.4 8.4 6.5 7.4

Source Author’s own compilation from different Data sources such as WDI (World Bank), IFS of the IMF and CD Rom. Statistical Outline of India, 2002–03, Tata Services Ltd. Mumbai, p. 90, RBI Bulletin, 2012 (11): 12–13 and HBS (RBI)

10 8 6 4 2 0 -2 -4 -6

75

80

85

90 CAD

95

00

05

10

NETCPT

Fig. 5.1 Trends of CAD/GDP (%) and NCF/GDP (%) (1971–2013) (Source Author’s own work)

equation to trace the long run relationship between growth rate of Indian GDP and net capital /GDP ratio for the time period 1971–2013. On the basis of number of studies which have shown long-run relationship and direction of causality between foreign capital and growth already reviewed empirically in the chapter, notably Prasad et.al. (2007), Dua and Sen (2013) and Khan (1998). We develop a model of a single equation

5

FOREIGN CAPITAL-GROWTH NEXUS IN INDIA …

127

12 8 4 0 -4 -8

75

80

85

90

95

00

05

10

Fig. 5.2 Trends of growth rate (Source Author’s own work) 2.4 2.0 1.6 1.2 0.8 0.4 0.0

75

80

85

90

95

00

05

10

Fig. 5.3 Plot of log growth rate (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work)

to trace the long-run relationship between growth rate of Indian GDP and net capital/GDP ratio for the time period 1971–2013. Econometric Specification of the model   Y = a + b Foreign Capital + e (5.1) Log Specification   LogY = a + bLog Foreign Capital + e

(5.2)

128

M. PAL

3 2 1 0 -1 -2 -3

75

80

85

90

95

00

05

10

Fig. 5.4 Plot of dlog GDP growth rate (Note Blank space in the figure shows variable turned negative during this period. Source Author’s own work) 9 8 7 6 5 4 3 2 1 0

75

80

85

90

95

00

05

10

Fig. 5.5 Trends of net foreign capital flows (NFC)/GDP (as % of GDP) (Source Author’s own work)

Net Foreign Capital/GDP ratio. The term of foreign capital has been derived. This term includes all types of capital (i.e.) Official foreign capital and private foreign capital and also it covers debt creating and nondebt creating capital. This variable also takes into account long-term and short-term capital flows. The variable explains the net capital inflow

5

FOREIGN CAPITAL-GROWTH NEXUS IN INDIA …

129

3

Fig. 5.6 Plot of log NFC/GDP (%)

2 1 0 -1 -2 -3

Fig. 5.7 Plot of dlog NFC/GDP (%)

75

80

85

90

95

00

05

10

85

90

95

00

05

10

3 2 1 0 -1 -2 -3

75 80

130

M. PAL

and is explained in terms of GDP. To see the effect of foreign capital on the economic development of any recipient country, economists and researchers on foreign capital have used this variable to see the growth effect of foreign capital. Massive amount of literature on Foreign capitalGrowth nexus has used this net capital/GDP ratio. Hence, the variable is justified on theoretically and empirically ground. Net capital inflows are equal to current account balances—foreign exchange reserves. Scale Variable GDP Growth Rate: As choice of the scale variable, we use real gross domestic product (GDP) GDP as a proxy for the level of economic activity. GDP is a measure of total production of financial goods and services in the country during a specified period usually a year. The Growth Rate of GDP is the most important indicator of the performance of the economy. Figure 5.8 demonstrates log differences of growth rate and NFC/ GDP ratio further Fig. 5.8 reflects the long-run behavior of both the variables. Deviation of each other seems very less in the early period of study. However after 1990s onward, deviations of both the variables from each other seem to be very high, which demonstrates low effectiveness of FDI on the growth process in Indian economy. We can infer that there is long run and positive relatonship but it is weak.

5.5

Empirical Results and Discussion 5.5.1

Order of Integration

Following convention we use the Logarithm of Foreign Capital and the Logarithm of real GDP (Y) growth rate so that first difference of these variables reflect the rate of change. A unit roots analysis is carried out to investigate the stationarity properties of the data. Table 5.2 and Table 5.3 report the results of the ADF and Phillips-Perron Unit roots tests for real GDP growth and Foreign Capital. The results indicate that the first differences of the two variables are on a stationary process, and hence both real GDP growth rate and foreign capital are integrated of order 1, i.e. 1 (1). From the Table 5.4, we find a positive and long-run relationship between foreign capital and growth rate in India. Trace test indicates 2 cointegrating equations at 0.05% level. Trace statistic (17.72) is more than

5

FOREIGN CAPITAL-GROWTH NEXUS IN INDIA …

131

3 2 1 0 -1 -2 -3

75

80

85

Blue line = GDP

90

95

00

05

10

Red line = NFC

Fig. 5.8 Plot of log differences of GDP and NFC (Source Author’s own work) (Color figure online) Table 5.2 Tests for stationary of the variables (1971–2013)

Variables

A.D.F Without Trend

Log GDP level First Difference LogNetCpt level First Difference

Conclusions With Trend

3.129

1.1515

−3.8939*

−5.51437*

−3.145197

−5.851488

−8.343799*

−8.242702*

1 (1)

1 (1)

Notes Critical value for ADF without Trend 1% (−3.6576); 5% (−2.9591); 10% (−2.6181). Critical values for ADF with Trend are: 1% (−4.2820); 5% (−3.5614); 10% (−2.2138) Significance at the 1%, 5% and 10% level is indicated by *, ** and ***, respectively Source Author’s own computation by using EViews-6

132

M. PAL

Table 5.3 Results of Phillips-Perron (PP) unit root Ttst

Variables

Log GDP level First Difference LogNet Capt level First Difference

Phillips-Perron

Conclusions

Without Trend

With Trend

3.4932304

−1.378627

−5.594795*

−7.411661*

−3.183019

−5.948809

−13.45,232*

−13.45392*

1(1)

1 (1)

Notes Without Trend 1% (−4.2605) 5% (−3.5514), 10% (−3.2081); With Trend 1% (−4.712), 5% (−3.5562) 10% (−3.2109) Significance at the 1%, 5% and 10% level is indicated by *, ** and ***, respectively Source Author’s own computation by using EViews-6

its critical value (15.494) (1). However, Max. Eigenvalue test indicates no cointegration at the 0.05 level. As per theory of time-series analysis, Trace test is more reliable than Max. Eigenvalue. Further, we find no Granger Pairwise causality direction, (i.e.) causality is not observed in any direction. Neither capital inflow causes growth rate nor growth rate has any effect on net aggregate foreign capital in Indian economy. From the Table 5.5 we find that in the upper panel of VECM, 1% rise in foreign capital causes growth rate to rise in India by 0.30%. Our ECT term also shows the minus sign which is expected from the theory. The Table 5.4 Results of Johansen cointegration test (trace statistics) for growth rate and foreign capital Series: LogGR LogNFC Hypothesized No. of CE(s) None* At most 1*

Eigenvalue 0.314480 0.120827

Trace Statistic 17.72231 4.507094

Trace test indicates 2 Cointegrating eqn(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level ** MacKinnon-Haug-Michelis (1999) p-values Source Author’s own work

0.05 Critical Value 15.49471 3.841466

Prob.** 0.0227 0.0337

5

FOREIGN CAPITAL-GROWTH NEXUS IN INDIA …

133

value of ECT is around—0.99 which shows high level of speed of adjustment in Indian economy. Main argument in this model is that the growth impact of all types of net capital inflows in aggregate form is studied. Our VECM model reveals three important features: (a) GDP growth rate in India is Granger caused by NFC that is net aggregate inflow of foreign capital. (b) the causality runs more from net capital inflow to GDP (c) economic liberalization policy of 1991 of the Indian government has some positive, short-run as well as long-run impact on the attractiveness and productivity of foreign capital inflows in India. The major policy recommendation that emerges from this study is the need to put in place the policies that would promote stable and conducive macroeconomic environment, which would encourage foreign capital inflows into the economy of India.

5.6

Conclusions

The basic objective of this chapter is to trace the long-run relationship and also to detect the causal direction between the net foreign capital and growth with the help of cointegration test and Granger pairwise causality for the time period 1971–2013. Both the variables NFC/GDP ratio and growth rate in India are integrated at the first difference order (I). We find two Cointegrating vectors between NFC/GDP ratio and growth rate which show a long-run, positive and significant relationship. However, only Trace value is significant at 5% level, Max. Eigenvalue is not significant. From the VECM upper panel, we find that 1% rise in NFC/GDP ratio causes 0.30% rise in growth rate. Our ECT term also shows the minus sign expected from the theory. Its value is around − 0.99% which shows that model corrects 99% disequilibrium in one year period and shows high speed of adjustment. However no Granger pairwise causality is detected from the model. Neither NFC nor growth rate Granger causes each other. Foreign capital is found to have a positive and significant impact on the growth process in Indian economy. The results support the foreign capital-led growth hypothesis. Findings are mainly consistent with the results of Abdelhafidh (2013), Rahman and Shahbaz (2013), Ranjan and Kumar (2012) and Pradhan (2011).

134

M. PAL

Table 5.5 Results of Vector Error Correction Model for foreign capital and growth

Vector Error Correction Estimates Co integrating Eq:

CointEq1

LogGR(−1) LogCAPITAL(−1)

1.000000 0.276578 (0.11626) [−2.37901] −1.591079

C Error Correction:

D(LOGGR)

D(LogCAPITAL)

CointEq1

−0.995378 (0.33150) [−3.00262] 0.102926 (0.27634) [ 0.37246] 0.213795 (0.18099) [1.18123] −0.253329 (0.13804) [ −1.83524] −0.299228 (0.11707) [−2.55604] 0.018467 (0.07876) [0.23448] 0.654708 0.590766 5.402815 0.447330

0.209247 (0.44983) [0.46517] 0.044027 (0.37498) [ 0.11741] −0.135245 (0.24560) [ −0.55068] −0.730999 (0.18731) [−3.90270] −0.532370 (0.15885) [−3.35135] 0.093275 (0.10687) [0.87280] 0.457945 0.357565 9.948105 0.606999

d(LogGR(−1))

d(LogGR(−2))

d(LogCAPITAL(−1))

d(LogCAPITAL(−2))

C

R2 Adj. R 2 Sum sq. resids S.E. equation

(continued)

Notes 1. For comprehensive survey on the role of foreign private capital in an emerging economy like India, see Khan (1998). 2. See, Chapter 6, for detailed classification and brief conceptual clarification of various types of foreign capital. 3. Under capital account, foreign capital inflows are to be classified either by instruments (debt or equity) or by maturity period (short or long

5

Table 5.5 (continued)

FOREIGN CAPITAL-GROWTH NEXUS IN INDIA …

Error Correction:

D(LOGGR)

F-statistic 10.23896 Log likelihood −6.96678 Akaike AIC 1.391926 Schwarz SC 1.664018 Mean dependent −0.000172 S.D. dependent 0.699265 Determinant resid covariance (dof adj.) Determinant resid covariance Akaike information criterion Schwarz criterion

135

D(LogCAPITAL) 4.562096 −27.03940 2.002388 2.274480 0.070276 0.757310 0.064652 0.043279 3.384161 4.019043

Source Author’s own computation by using EViews-6

term). The main components of capital account include foreign investment, Foreign Aid/Foreign loans/external assistance and banking capital. Foreign investment consists of FDI and Foreign Portfolio investment (FPI) and which consists of FIIs, ADRs/GDRs and represents non-debt creating capital. Foreign loans/external assistance, commercial borrowing, NRI banking capital represents debt creating capital. On the issue of capital account liberalization and capital account convertibility, a number of committees set by the Government of India and the RBI. For example high-level Committee on Balance of Payment (BOP) was set up by the Government of India under the Chairmanship of C. Rangarajan in November, 1991. On the issue of capital account convertibility RBI set up the two committees under the chairmanship of S. S. Tarapore (1997, 2006). 4. The Pitchford (1989c) thesis states that a current account deficit does not matter if it is driven by the private sector. This theory has been applied by the Australian economy and has proved true. Australian economy exercised a persistent current account deficit for continuously 18 years (1991–2009) and achieved impressive economic growth. For acomprehensive survey on Pitchford thesis, see Pitchford (1989).

References Abdelhafidh. 2013. Potential financing sources of investment and economic growth in North African countries: A causality analysis. Journal of Policy Modeling 35 (1): 150–169.

136

M. PAL

Adams, S., E.K.M. Klobodu, and R.O. Lamptey. 2017. The effects of capital flows on economic growth in Senegal. The Journal of Applied Economic Research 11 (2): 121–142 Adler, J.H., and P. Kuznets. 1967. Capital movements and economic development. New York: Macmillan. Ahmad, S. 1986. Domestic saving & foreign capital inflow: The case of Bangladesh. Bangladesh Development Studies 14 (1): 79–91. Alamgir, M.M. 1974. Foreigncapital inflow, saving and economic growth: A case study of Bangladesh. Bangladesh Development Studies 2 (2): 577–598. Balassa, A.B. 1982. The theory of economic integration. Greenwood Press. Banday, U.J. 2016. Dynamic nexus between budget deficit and current account deficit: Some empirical results relating to the Indian economy. Asian Economic Review 58 (1): 29–87. Berrill, K. 1963. Foreign capital and the take-off. In The economics of take-off in to sustained growth, ed. W.W. Rostow. New York: St. Martin’s Press. Bosworth, B., and Susan M. Collins. 1999. Capital flows to developing economies: Implications for saving and investment. Brookings Papers on Economic Activity, Brookings, Washington, DC 30 (1): 143–180 Bowles, P. 1987. Foreign aid and domestic saving in LDCs: Some tests for causality. World Development 15 (6): 789–796. Chakraborty, I. 2005. Capital inflows in to India in the post-liberalization period: An empirical investigation, Occasional Paper, IDS, Calcutta. Chakraborty, I. 2006. Capital inflows during the post-liberalization period. Economic and Political Weekly 41 (2): 143–150. Chenery, H.B., and A.M. Stout. 1966. Foreign assistance and economic development. American Economic Review 56 (4): 679–733. Dauda, R., and S. Oladoyin. 2008. Trends, behavioral patterns and growth implications of foreign private capital flows in Nigeria. Journal of Financial Economics, ICFAI 6 (3): 29–40. Domar, E. 1946. Capital expansion, rate of growth and employment. Econometrica 14 (2): 137–149. Dua, P., and P. Sen. 2013. Capital flows and exchange rates: The Indian experience. Indian Economic Review 48 (1): 189–220 and reprinted in Krishna, K.L., V. Pandit, K. Sundaram, and P. Dua. 2017. Perspectives on economic development and policy in India. Springer. Dua, P., and R. Ranjan. 2012. Exchange rate policy and modeling in India. New Delhi: Oxford University Press. Dutt, A.K. 2006. Flawed logic of capital account liberalisation. Economic and Political Weekly 41 (19): 1850–1853.

5

FOREIGN CAPITAL-GROWTH NEXUS IN INDIA …

137

Edison, H., K. Michael, R. Luca, and S. Torsten. 2002. A capital account liberalization and economic performance: Survey and synthesis. IMF Working Paper, Washington, DC. Gallagher, K.P. 2011. The IMF, capital controls and developing countries. Economic and Political Weekly 46 (19): 12–16. Garg, R., and P. Dua. 2015. Macroeconomic determinants of foreign direct investment: Evidence from India. The Journal of Developing Areas 49 (1): 16–28. Ghosh, S.K. 2004. Monetary policy, sterlisation and capital mobility; dilemma of RBI. Economic and Political Weekly 39 (51): 5365–5367. Government of India. (1993). Report of high-level committee on balance of payments (Chairman: C. Rangarajan). New Delhi. Government of India. (2009). Report of the high-level committee on estimation of saving and investment (Chairman: C. Rangarajan). New Delhi. Griffin, K.B. 1970. Foreign capital, domestic savings and economic development. Oxford Bulletin of Economics and Statistics 32 (2): 99–112. Gulati, U.C. 1978. Effect of capital imports on savings and growth in less developed countries. Economic Inquiry 13 (4): 563–569. Gupta, K.L. 1975. Foreign capital inflows, dependency burden, and saving rates in developing countries: A simultaneous equation model. Kyklos 28 (2): 358– 374. Gupta, K.L., and M.A. Islam. 1983. Foreign capital, saving and growth—An international cross section study. Boston: Reidel Publishing Company. Gupta, P. 2016. Capital flows and central banking: The Indian experience, monetary policy in India: A modern macroeconomic Perspective, 385–424. Springer. Harrod, R.F. 1939. An essay in dynamic theory. The Economic Journal 49 (193): 14–33. Hachicha, N. 2003. Capital inflows-national saving dynamics in Tunisia: Evidence from cointegration, weak exogeneity and simultaneous error correction modelling. International Economic Journal 17 (4): 43–60. Hernandez, L., P. Mellado, and R. Valdes. 2001. Determinants of private capital flows in the 1970 and 1990s: Is there evidence of contagion? IMF working paper/01/64. Hiroyuki, T. 2011. Relationship Between Capital Inflows and Asset Prices in East Asian, China, Hong kong. Iftikhar, S.F. 2015. The nexus of capital account liberalization, financial development and economic growth. Asian Economic Review 57 (3): 1–17. Islam, N. 1960. Foreign capital and economic development: Japan, India and Canada, Rutland and Tokyo, Vt.: C.E. Tuttle Co., 245.

138

M. PAL

Johansen, S., and K. Juselius. 1990. Maximum likelihood estimation and inference on cointegration—With application to the demand for money. Oxford Bulletin of Economics and Statistics 52 (2): 169–210. Khan, A.N., and N. Ansari. 2014. Capital inflows and economic growth in India: A cointegration analysis. The Indian Economic Journal, Special Issue, Indian Economic Association (IEA) India. Khan, M.S. 1998. Capital flows to developing countries: Blessing or curse. The Pakistan Development Review 37 (4): 125–151. Kohli, R. 2001. Capital flows and their macroeconomic effects in India. ICRIER Working Paper 64, Indian Council for Research on International Economic Relations (ICRIER) New Delhi. Kohli, R. 2001. Capital account liberalization: Empirical evidence and policy issues-II. Economic and Political Weekly 36 (16): 1345–1348. Kohli, R. 2003. Capital flows and domestic financial sector in India. Economic and Political Weekly 38 (8): 761–767. Kohli, R. 2009. Financial integration, capital controls and monetary independence. Economic and Political Weekly 44 (26): 57–61. Kyaw, K.S., and M. Ronald. 2009. Capital flows and growth in developing countries: A dynamic panel data analysis. Oxford Development Studies 37 (2): 101–122. Lockwood, W.W. 1958. Enterprise and foreign capital in India: A review article. Pacific Affairs 31 (4): 390–397. Lucas, R.E. 1990. Why doesn’t capital flow from rich to poor countries. American Economic Review 80 (2): 92–96. Majumdar, T. 2005. Capital flows into India, implications for its economic growth. Economic and Political Weekly 40 (21): 2183–2189. Mallick, S., and T. Moore. 2008. Foreign capital in growth model. Review of Development Economics 12 (1): 143–159. Mohan, R. 2008. Capital inflows to India, bank for international settlements. Available at www.bis.org/pub/bppdf/bispap44.htm. Last accessed on 1 October 2013. Montiel, P.J., and C.M. Reinhart. 1999. Do capitals and macroeconomic policies influence the volume and composition of capital flows? Evidence from the 1990s. Journal of International Money and Finance 18 (4): 619–635. Pal, M. 2014a. Financial deepening, capital inflows and economic growth nexus in India—Evidence from cointegration. Paper presented at the 51th Annual Conference of The Indian Econometric Society (TIES) at Punjabi University, Patiala, 12–14 December.

5

FOREIGN CAPITAL-GROWTH NEXUS IN INDIA …

139

Pal, M. 2014b. Financial deepening, trade openness, capital inflow and growth in India—An evidence from cointegration. Paper presented at the 4th IIFT Conference, New Delhi, 18–19 December 2014. Pal, M. 1995. Foreign capital—Growth nexus in India. Paper presented at IIDS International Conference held at Swedish Academy of Science, Helsinki, Finland: 28–30 August 1995. Pal, M. 2013. Determinants of Foreign Capital in India—A cointegration approach. Paper presented at the 96th Annual Conference of Indian Economic Association at Meenakshi University, Chennai, 26–28 December. Pal, P. 2015. The management and impact of cross-border capital flows in India. In India and the international economy, economics, vol. 2, ed. Jayati Ghish. New Delhi: Oxford. Papanek, G.F. 1972. The effect of aid and other resource transfer on savings and growth in less developed countries. The Economic Journal 82 (327): 934–950. Papanek, G.F. 1973. Aid, foreign private investment, saving and growth in less developed countries. Journal of Political Economy 81 (1): 120–130. Parikh, A., and B. Rao. 2006. Do fiscal deficit influence current accounts? A case study of India. Review of Development Economics 10 (3): 492–505. Pitchford, J. 1989. A skeptical view of Australian’s current account and debt problem. Australian Economic Review 86: 5–14. Pradhan, N.C. 2011. Nexus between capital flows and economic growth. IPE Journal of International Trade 2 (1). Prasad, E.S., R. Rajan, and S. Arvind. 2007. Foreign capital and economic growth. Brookings, Papers in Economic Activity, Washington: 153–255. Rahman, M.M., and M. Shabbaz. 2013. Do imports and foreign capital inflows lead economic growth? Cointegration and causality analysis in Pakistan. South Asia Economic Journal 14 (1): 59–81. Rahman, M.A. 1968. Foreign capital and domestic saving: A test of Haavelmo’s hypothesis with cross country data. Review of Economics and Statistics 50 (1): 137–138. Rajwade, A.V. 2007. Risks and rewards of capital account convertibility. Economic and Political Weekly 42 (1): 29–34. Ramakrishna, G., and R. Rena. 2013. Inflows of capital, exchange rates and balance of payments: The post liberalization experience of India. Asian Economic Review 55 (2): 223–242. Rangarajan, C., and M. Prachi. 2013. India’s external sector do we need to worry? Economic and Political Weekly 48 (7): 52–59. Ranjan, R., and S. Kumar. 2012. An empirical investigation of the impact of capital inflows on domestic investment in India. Indian Economic Review XXXVII (1): 15–32.

140

M. PAL

Rao, M.J. 1997. Macro-economics of capital account convertibility. Economic and Political Weekly 32 (51): 3261–3267. Reserve Bank of India. 1997. Report of the committee on capital account convertibility (Chairman: S. S. Tarapore) New Delhi. Reserve Bank of India. 2006. Report of the committee on fuller capital account convertibility. (Chairman: S. S. Tarapore). New Delhi. Rodrik, D. 1998. Who needs capital- account convertibility? In Should the IMF pursue capital account convertibility?, ed. Stanley Fisher, Richard N. Cooper, Roudiger Dornbusch, Peter M. Garber, Carlos Massad, Jacques J. Polak, Dani Rodrik, and Savak S. Tarapore. Princeton Essays in International Finance Series, 207: 55–65. Princeton, NJ: Princeton University. Rodan, R. 1961. International aid for under-developed countries. Review of Economics and Statistics 43 (2): 107–138. Sen, P. 2004. Modelling foreign capital inflows and fiscal deficits. Economic and Political Weekly 39 (40): 4478–4480. Sen, P. 2006. Case against rushing into full capital account convertibility. Economic and Political Weekly 41 (19): 1853–1857. Sen, P. 2007a. Capital inflows, financial repression, and macroeconomic policy in India since the reforms. Oxford Review of Economic Policy 23 (2): 292–310. Sen, A. 2007b. Does capital account openness lower inflation? Indian Council for Research on International Economic Relations, Working Paper No. 191:1–26, New Delhi Sethi, N. 2013. Causal relationship between foreign capital inflows and economic growth: Empirical evidence from India. International Journal of Economics, Finance and Management 2 (1): 65–69. Singh, N., and T.N. Srinivasan. 2004a. Foreign capital, deficits and growth. Economic and Political Weekly 40 (21): 2196–2197. Singh, N., and T.N. Srinivasan. 2004b. Foreign capital, inflation, sterilisation, crowding out and growth: Some illustrative models. Economic and Political Weekly 39 (24): 2469–2482. Sotom, M. 2000. Capital flows and growth in developing countries: Recent empirical evidence. Working Paper No. 160, OECD Developing Centre, Paris. OECD Publishing. Accessed on 2 February 2014. https://doi.org/10.1787/ 633871307443. Stoneman, C. 1975. Foreign capital and economic growth. World Development 3 (1): 11–26. Subramanian, A. 2007. Capital account convertibility: A neglected consideration. Economic and Political Weekly 42 (25). Swan, T. 1956. Economic growth and capital accumulation. Economic Record 32 (34): 334–361. Tamajai, A. 2000. The impact of capital flows on Asian economic growth. Ph.D Thesis, New York.

5

FOREIGN CAPITAL-GROWTH NEXUS IN INDIA …

141

Thiriwall, A.P. 2005. Growth and development (with special reference to developing economies). New Delhi: Palgrave Macmillan. Vivodas, C.S. 2013. Exports, foreign capital inflow and economic growth. Journal of International Economics 90 (4): 337–349. Weisskoff, T.E. 1972a. The impact of foreign capital inflows on domestic savings in under developed countries LDCs. Journal of International Economics 2 (1): 25–38. Weisskoff, T.E. 1972b. An econometric test of alternative constraints on economic growth of under developed countries. Review of Economics and Statistics 54 (1): 67–78. Yasmin, B. 2005. Foreign capital inflows and growth in Pakistan: A simultaneous equation model. South Asia Economic Journal 6 (2): 207–219.

CHAPTER 6

PCY, Foreign Aid and FDI: A Test of Complementarity

6.1

Introduction

Foreign Aid played a very significant and strategic source of foreign resources and tried to remove the shortage of foreign exchange and domestic saving for underdeveloped, now emerging countries, in the decade of mid-1970s. Foreign Aid accounted for 6% of GDP in 1975 while its importance in terms of absolute amount and its percentage in terms of GDP declined to the extent of 0.6% in 2012. Now the FDI, FPI and remittance have become main source of foreign capital to emerging nations. For instance, the share of FDI has increased from 0.6% of GDP in 1975 to 3% of GDP in 2012. Role of Foreign Aid and its effectiveness in this changing global environment clearly requires a strong complementarity between public and private investment. Further this complementarity requires more Foreign Aid that must be associated with the provision of technical assistance (World Bank 1998).1 In addition, new evidence on foreign capital indicates that it is not the accumulation of capital stock but the productivity of foreign capital which matters.2 Almost all the studies on foreign capital and growth nexus have identified the problem at macro level. As we have already pointed out in Chapter 5 that Foreign capital includes Aid, external commercial borrowing, FDI, FPI, FIIs, NRIs and remittances, each of these capital inflows is received by the different economic agents and these capital flows have different impact on the different sectors and growth process © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. Pal, Foreign Capital and Economic Growth in India, https://doi.org/10.1007/978-981-99-2299-4_6

143

144

M. PAL

in the recipients countries. For the first time, Papanek (1973) found that the different components of foreign capital have different impact on investment levels and growth rates in the recipient countries. Further, he goes on to claim that the justification for the disaggregation used in this chapter is beneficial specially in emerging and rapidly growing developing countries like India, where financial and capital markets are imperfect and segmented.3 This pattern of disaggregation can further be captured by distinguishing a private and public sector. For example, official flows such as Foreign Aid flows are specially related to the saving and investment gap of the public sector. Public sector specifically deals with the improvement of economic and social overhead facilities such as railways, roads, electric generation and distribution, telecommunications, water, education, sanitation and health services. These basic utilities are governed mainly by the government, while private capital flows such as foreign direct investment (FDI) is more related to the private sector and commercial activities. However, recent public–private partnership (PPP) model is in the trial shape, because of its different directions. Its success still remains disputed and does not show a clear performance.4 Against this background the main issue in this chapter is to test empirically the long-run relationship among the macrovariables such as PCY, Foreign Aid, FDI and export in India and also to see the relative impact of each type of capital on the growth process in India. The plan of this chapter is structured as: Sect. 6.2 provides literature review relating to the theory and empirical evidence of studies which are related to the relative effectiveness of various types’ capital inflows, Sect. 6.4 deals with the behavior of shifting from debt creating to non-debt creating foreign capital. Sect. 6.5 deals with model specification, estimation and discussion and Sect. 6.6 concludes with the main findings of the chapter.

6.2

Review of Literature

During the last three decades, a number of studies have been carried out on the issue of disaggregation of foreign capital inflows. The literature is reviewed in relation to the relative effectiveness of official (Aid) and private (FDI) foreign capital and is also related to the disaggregation approach of foreign capital. Moreover, some studies focus on policy shifting from debt creating to non-debt creating foreign capital.

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

145

We can divide this literature in two regimes. During the first regime covering the period of 1970s and 1980s number of economists, led by Papanek (1972, 73) worked on the relative significance of various types of foreign capital. Other economists notably include: K. L. Gupta (1975), Gorgens (1976), Mosley (1980), Dowling and Hiemenz (1983), B. Sharma (1986), P. B. Rana and J. M. Dowling Jr. (1988); Second regime of 1990s decade onward includes U. Lachler and P. Nunnekamp (1989), Calvo and Reinhart (1998), Bosworth and Collins (1999), Montiel and Reinhart (1999), Trivino and Uppadhyay (2003), P. Sahoo and M. K. Mathiyazhagan (2003), S. Mallick and T. Moore (2008), K. S. Kyaw and R. Macdonald (2009), A. K. Tiwari and B. Pandey (2014), R. Arunachalam (2014), S. B. Majumder and R. N. Nag (2016), Lamptey et al. (2017) and P. Aggarwal (2017). Papanek (1972) questioned the validity of the aggregation of all foreign inflows because various types of foreign capital are likely to differ to their growth-enhancing effects. Further he in (1973) also examined the relative significance of Foreign Aid, foreign private capital and other foreign resources for the first time. His work on foreign capital led a new development paradigm. He applied the cross-country regression analysis to take sample of 34 countries in the 1950s and 51 countries for the decade of 1960\he empirically examined the model which takes into account Aid, foreign private investment, domestic saving and other financial resources as independent variables and income as dependent variable. His main findings are related to three points. First, the effect of foreign Aid is substantially greater than the effects of other variables. Second, his findings also indicate that growth is positively correlated with Foreign Aid variable. Third, the empirical relationship is not only just positive, but Aid has a coefficient nearly twice that of coefficients of other independent variables in all regressions. K. L. Gupta (1975) estimates of the growth rates of income equations and supports the findings of Papanek (1973) on the ground that foreign capital inflows have a more significant effect on growth rate than domestic saving. Further his results differ from Papanek (1973) on the ground that Foreign Aid has the smallest effect among the three 3 types of foreign resources. Gorgens (1976) reveals facts that growth effectiveness of Foreign Aid remains zero in planned economies, while, Aid demonstrates positive effect in market economies. In one of his studies Mosley (1980, 87) demonstrates pessimistic conclusions about the effectiveness of ODA, while in his another study, talks about micro–macro paradox.

146

M. PAL

This paradox reveals the fact that Foreign Aid works better at micro-level, while there is no evidence of its positive effect at macro-level. Dowling and Hiemenz (1983) study the role of Foreign Aid in the Asian economies during the period of 1970s and their results also confirm the findings of Papanek (1972, 73) and also further goes on to contradict of Mosley’s pessimistic findings on Foreign Aid growth nexus in the developing countries. B. Sharma (1986) examines the effects of equity capital (foreign private capital) and debt capital (Foreign Aid) on the economic growth of a sample of 62 developing countries (the then underdeveloped countries) for the period 1970–1977. He concludes that equity (FDI) capital is more beneficial to economic growth than debt (Foreign Aid) capital. P. B. Rana and J. M. Dowling Jr. (1988) in their simultaneous model which includes nine Asian developing countries, examine the effect of foreign capital on growth process in Asian economies. Core findings of the study conclude: foreign capital flows have made a positive contribution to the growth. FDI can generate more growth in the host economy with the provision of more financial resources and further by improving technical and investment efficiency, comparatively, foreign private investment and exports remain better than ODA. U. Lachler and P. Nunnekamp (1989) examine the effects of various modes of foreign capital inflows on economic growth, domestic savings and investment level. Authors find that FDI can act as a risk sharing instrument for developing now emerging countries however, they do not establish the superiority of FDI on Foreign Aid (debt) flows. Calvo and Reinhart (1998) in their post-crisis study disaggregate capital inflows into FDI, Portfolio investment and banking capital to see the impact on various macroeconomic indicators including growth. Study concludes that whether investment is financed by the foreign capital or not does not increase growth rate in the host country. Bosworth and Collins (1999) examine the impact of capital inflows on investment and growth in 58 emerging countries of Asia, Africa and Latin America and find that one dollar increase in capital inflow in aggregated form causes 0.50 cent increase in domestic investment, while FDI alone causes oneto-one US dollar in domestic investment in the host country. Montiel and Reinhart (1999) estimate a panel regression on 15 countries for the period 1990–1996 and try to explain the composition of different types of foreign capital inflows. Study finds that capital inflows respond to the short-term macroeconomic policies in the host countries.

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

147

Trevino and Upadhyaya (2003) study the relative significance of ODA and FDI in five Asian emerging economies. FDI is positively associated with economic growth and finds. FDI to be as more superior than ODA in economies which follow high degree of trade openness. P. Sahoo and M. K. Mathiyazhagan (2003) study the role of FDI in enhancing the economic growth through the process of export promotion for the period from 1979–1980 to 2000–2001 with the help of cointegration technique. Results demonstrate that GDP, FDI and export show a long-run relationships with an added emphasis on export promotion in case of Indian economy. S. Mallick and T. Moore (2008) with the help of endogenous growth theory empirically examine the impact of foreign capital on economic growth for a panel of 60 developing nations. FDI flows can have complementarity effects on the capital formation among nations of different income groups. The Foreign Aid increases investment in the middleincome economies, but not in the low-income countries because of malallocation of Foreign Aid. K. S. Kyaw and R. Macdonald (2009) examine the foreign capital flow-growth nexus with the help of model which includes contemporaneous influences and contemporaneous expectations. Findings confirm their hypothesis that private capital flows increase the rapid growth in upper-middle-income countries than low and emerging nation. A. K. Tiwari and B. Pandey (2014) examine the impact of AID, FDI and economic freedom on economic growth in the ASEAN nations. The countries which adopt more economic freedom should experience rapid economic growth with the help of Aid and FDI. They examine the long-run empirical validity among main indicators of economic freedom, Foreign Aid and FDI in the framework of panel data for six ASEAN nations for the period 1998–2007. R. Arunachalam (2014) examines the impact of capital flows on macroeconomic variables such as economic growth, export, imports and balance of payments and banking sector variables. His study finds that trade openness has a significant impact on growth rate in India as compared to other variables. S. B. Majumder and R. N. Nag (2016) examine the behavior of net capital inflow and its components since the introduction of economic liberalization policy in India in 1991. Capital inflow in India is volatile because it is procyclical. Different types of foreign capital have different types of market. Even after a high degree of volatility in various modes of capital inflows, they find an empirical evidence of complementarity

148

M. PAL

among all types of capital except between FDI and FPI, where they detect substitutability in India. Lamptey et al. (2017) compare the role of foreign remittances and external debt with an application of ARDL technique over the period 1970–2014 and conclude that remittances cause economic growth in Senegal in the long run, while external debt demonstrates a negative effect on economic growth. Further no long-run relationship is established neither between FDI and growth nor between ODA and growth, P. Aggarwal (2017) in his research on foreign capital and its impact on economic growth and capital formation in emerging Asian economies concludes that FDI and FPI have a significant impact on the GDP and also remain more preferred as compared to foreign debt version of FPI.

6.3

Types of Foreign Capital

Foreign capital can be broadly categorized into two types: official capital and private capital. Official capital can be further divided into bilateral and multilateral. Private capital can be divided into foreign direct investment (FDI), portfolio investment, commercial borrowings, NRI and banking capital. Table 6.1 demonstrates the classification of private and official foreign capital. Table 6.2 demonstrates the main components of debt creating and non-debt creating foreign capital.

6.4

Shifting from Debt to Non-debt Creating Capital in India

As we have already pointed out, New Economic Policy of 1990–1991 shifted the trends of foreign capital inflows. Some studies on the trends of debt and non-debt creating trends demonstrate that in the initial period of the decade of 1990s, debt creating capital dominated the scene and had more than 90% share in total capital inflows, but after radical reforms of early 1990s, its share declined to 53% in the year of 2003–04. However, 2004–05 onwards debt creating capital inflows again have shown a rising trends. On the other hand, the share of non-debt creating capital which was very small or negligible in the period of early 1990s increased to 47% in the year of 2003–04. However, 2004-05 onwards again, nondebt creating capital flows have shown a decling trends. For detailed analysis on this issue, see Ranjan and Kumar (2012). From these fluctuating trends on shifting of foreign capital policy, it is clearly established

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

149

Table 6.1 Types of foreign capital available to India

Official Capital

Private Capital

Official Capital Bilateral Capital Multilateral Capital International Monetary Fund (IMF) World Bank Group International Bank for Reconstruction and Development (IBRD) International Development Association (IDA) International Finance Corporation (IFC) Multilateral Investment Guarantee Agency (MIGA)

Private Capital Foreign Direct Investment (FDI) Portfolio Investment Commercial Borrowings NRI and Banking Capital Foreign Remittances (Dutch Disease) Source Author’s own work

Table 6.2 Composition of debt creating capital to non-debt creating capital in India Foreign Aid/Official development assistant/External assistance Commercial borrowings NRI money Loans from IBRD Loans from ADB and IDA

Source Author’s own work

1) Foreign Direct Investment 2) Portfolio investment FIIs ADRs GDRs IDRs Remittances

150

M. PAL

that the role of debt capital cannot be underestimated in Indian economy. For an excellent and comprehensive survey on the policy of shifting from debt to non-debt creating capital, in India, see Dua and Sen (2013), Dua and Ranjan (2012), Ranjan and Kumar (2012), Sikdar (2006), Banday (2016), Mazumdar (2005), and Chakraborty (2005). Following arguments may have been the main reasons for shifting foreign debt policy, in addition to reasons pointed out in the abovementioned studies. First, the most important reason might have been the fatigue or failure of Foreign Aid, increasing high level of debt service ratio (DSR), under utilization of Foreign Aid which remained in the pipeline for long time causing a heavy debt burden on Indian economy, fungibility and low level of effectiveness of Foreign Aid and shifting Aid from selected projects to unidentified projects. Second, however, Aid cannot be blamed for its fatigue in India and elsewhere because major share of Foreign Aid remains in the pipeline for long time, which causes heavy debt burden. The main reasons for debt burden are not because of ineffectiveness of Foreign Aid, but because of the shortage of local component of project funding. Third, there has always been a dispute among the central, state and local bodies in the process of completion of projects. In this way, problems of cost overrun and time overrun are glaring examples in India. For a detailed analysis on this topic, see Singh (2009) and Rao (1952, Rao and Narain 1963). Fourth, high levels of economic distortions have been responsible for the declining trends in absolute amount of Foreign Aid in India. There has been a big gap between collection of user charges from the users (public) and the cost of public utilities and services incurred on the projects (public goods) which makes it difficult to maintain the full life of the project. Empirical studies and their findings on Foreign Aid have been so controversial that a researcher and policy makers of recipient countries get confused and disturbed to take any major and right decisions for the country. Fifth has been the availability of private capital such as FDI, FIIs, ADRs, GDRs and also increasing level of productivity of private capital. Stability of FDI inflow is doubtful while, portfolio investment remains a highly volatile in developing countries. However, private foreign capital

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

151

has become a major source of foreign resource transfer in emerging and developing countries. Sixth, massive dose of financial liberalization has relaxed financial constraint of emerging economies specially China, India, Malaysia, Turkey, etc. In these countries financial liberalization has relaxed the financial constraint at micro and at the macro level through the increase in the level of financial inclusion and financial deepening (M3/GDP) which has increased from 40% in 1980 to 81% in 2013 in India. For detailed analysis on the role of financial deepening in Indian economy, see Pal (2014). Table 6.3 provides the time-series data for estimation of Models 6.1 and 6.2. Figure 6.1 depicts the increasing trends of four macrovariables such as PCY, Aid, FDI and Export. Figure 6.2 explains the behavior of two important variables that is FDI/GDP ratio (non-debt capital) and Aid/GDP ratio (debt capital) with structural breaks in the year of 1995. Before 1995 Aid/GDP ratio was higher than FDI/GDP ratio but after 1995 a radical shift took place. After the year of 1995 FDI/GDP ratio had become more than Aid/GDP ratio. Aid/GDP ratio which was 1.50 in 1971 came down to 0.13 in 2013. After 1995, both the variables have been showing trends in reverse directions.

6.5 Model Specification, Estimation and Discussion Following the research methodology adopted by Papanek (1972, 1973), Griffin and Enos (1970, 73), Dowling and Hiemenz (1983), Rana and Dowling (1988), Gupta (1975), Sharma (1986), Mallick and Moore (2008), and Bosworth and Collins (1999), we develop two models. The empirical analysis is a simple one that includes economic variables that have a sound theoretical and empirical justifications studied in most of the empirical studies. We estimate the following two models. Model 6.1 includes three macrovariables such as PCY, FDI and Aid to capture the separate effect of FDI (which represents the non-debt creating capital) and Aid (which represents the debt creating capital) on the PCY. Model 6.2 incorporates export variable to capture the separate effect on growth process. Hence, Model 6.2 incorporates four macrovariables such as PCY,

152

M. PAL

Table 6.3 Macroeconomic variables for model estimation Year

FDI/GDP ratio (%)

Aid/GDP ratio (%)

PCY (Rs.)

X/GDP ratio (%)

1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

0.01 0.02 0.02 −0.01 −0.01 −0.01 −0.03 0.01 0.03 0.04 0.05 0.04 0.04 0.01 0.04 0.05 0.07 0.03 0.08 0.07 0.03 0.09 0.19 0.29 0.58 0.61 0.85 0.61 0.46 0.81 1.11 1.07 0.71 0.81 0.87 2.11

1.47 0.85 0.91 1.22 1.61 1.67 0.81 0.81 0.87 1.15 1.11 0.81 0.83 0.78 0.67 0.79 0.61 0.65 0.59 0.43 1.01 0.84 0.52 0.71 0.48 0.48 0.39 0.38 0.32 0.29 0.35 0.34 0.12 0.11 0.23 0.15

8091 7949 7703 7870 7767 8305 8204 8639 8917 8185 8594 8895 8890 9409 9536 9709 9899 9978 10,769 11,188 11,535 11,406 11,796 12,207 12,739 13,402 14,231 14,565 15,231 15,881 16,173 16,769 17,109 18,317 24,095 25,969

3.60 3.96 4.14 4.75 5.55 6.57 6.27 6.21 6.63 5.2 4.6 4.5 4.8 4.6 4.8 4.1 4.2 4.6 4.9 5.8 5.8 6.8 7.7 8.2 8.3 9.1 8.8 8.7 8.2 8.3 9.9 9.4 10.6 11.1 11.8 12.6

(continued)

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

153

Table 6.3 (continued) Year

FDI/GDP ratio (%)

2007 2008 2009 2010 2011 2012 2013

Aid/GDP ratio (%)

PCY (Rs.)

X/GDP ratio (%)

0.11 0.17 0.18 0.17 0.18 0.11 0.09

28,074 30,316 32,416 34,416 36,342 38,037 40,254

13.6 13.4 15.4 13.4 15.1 17.1 16.8

2.04 3.55 2.91 2.91 1.98 1.31 1.51

Source Author’s own work and Data has been collected from the HBS (RBI) Economic Survey 2009–2010, RBI, WDI (World Bank)

25 20 15 10 5 0 -5 -10

1975

1980

1985

1990 GPCY FDI

1995

2000

2005

2010

ODA EXPORT

Fig. 6.1 Trends of PCY, Aid, FDI, export (1971–2013) (Source Author’s own work)

FDI, Aid and Export.5 Y = a + β1 FDI + β2 Aid + e1

(6.1)

Y = a + β1 FDI + β2 Aid + β3 X + e2

(6.2)

154

M. PAL

3.6 3.2 2.8 2.4 2.0 1.6 1.2 0.8 0.4 0.0 -0.4

75

80

85

90 ODA

95

00

05

10

15

FDRATIO

Fig. 6.2 Structural break between Aid/GDP ratio and FDI/GDP ratio (Source Author’s own work)

β1 >< 0; β2 >< 0; β3 > 0; Y = Per capita income FDI = ratio of foreign direct investment to GDP Aid = ratio of Foreign Aid to GDP X = ratio of export to GDP, e1 and e2 are the stochastic terms required to satisfy the assumption of (U1) = 0 Dependent Variable: Y Independent Variables: FDI, Aid, X Given the controversy among the economists on the questions of relationship between foreign capital and growth, the sign of β1 , β2 , β3 , could be either positive or negative.

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

6.5.1

155

Johansen Cointegration Results

Table 6.4 demonstrates the results of unit root testing. Unit root testing takes into account the ADF and Phillips-Perron methods. Results reveal the order of integration and stationarity in the variables after first differencing. The results of the Model 6.1 are presented in Table 6.5 which shows one cointegrating vector (i.e.) Trace Statistics (31.90) > its critical value (29.80) at 5% level of significance or at the 0.05 level while p value is around 0.0276 at linear deterministic trend. In Table 6.6, results demonstrate Maximum Eigenvalue test which indicates 1 cointegrating equation and rejects the null of no-cointegration. Maximum Eigenvalue (23.829) > its critical value (21.131) at p value 0.0203. Table 6.7 indicates the normalized value which shows that 1% increase in FDI causes 0.04% in PCY Growth rate, while AID shows strong coefficient value, 1% rise in AID causes more than 1% rise in PCY growth rate. Table 6.8 demonstrates the Granger Causality results which reveal the facts that PCY and AID show bidirectional causality, which means that AID and PCY are causing each other and reinforcing each other with strong F value. Secondly, FDI is also causing AID with strong value of F. From the Table 6.9, the outcome of VECM is reported. It is a known fact that the individual coefficient from VECM is very difficult to simplify and interpret. For this reason, it is important to analyze the dynamic properties of the model by examining the Impulse Response Function (IRF) and Variance Decomposition (VDC). Figure 6.3 shows the Impulse Response to Cholesky One S.D. Innovations. Tables 6.10, 6.11 and 6.12 show the results from Cholesky variance decomposition of LogPCY, LogAid and LogFDI. 6.5.2

Model 2 Johansen Cointegration Results

Table 6.13 shows the results of Trace statistics which is more than its critical level and shows positive and long-run relationship. Table 6.14 shows the results of Pairwise Granger causality. Results are very encouraging and FDI is causing export volume (Fig. 6.4). We extend Model 6.1 by incorporating export variable to capture the effect of export variable on the growth process. Table 6.13 shows the Trace statistics which is more than its critical level and shows positive and long-run relationship among four estimated variables of the model

156

M. PAL

Table 6.4 Results of Augmented Dicky Fuller (ADF) and Phillips-Perron (PP) unit root test ADF

PP

Variables

Without trend

With trend

LogPCY level First difference LogFDI level First Difference LogAid level First Difference LogX level First difference

−2.9616 −0.9828 −5.0924* −6.216*

Conclusions

Without trend

With trend

Conclusions

1(1)

−2.9618 −0.9838 −5.1373* −6.2811* 1(1)

−2.0492 −3.6702 −6.4771* −6.1316* 1(1)

−1.7813 −2.8383 −6.5323* −6.1659* 1(1)

−1.0921 −2.7263 −5.3705* −5.2696* 1(1)

−1.2050 −2.6141 −5.3908* −5.2079* 1(1)

−1.0921 −0.3583 −6.7718* −6.7029* 1(1)

−0.5098 −1.8479 −6.7659* −6.6929* 1(1)

Notes Significance at the 1%, 5% and 10% level is indicated by *, ** and ***, respectively (i) Critical value for ADF without Trend 1% (−3.6576); 5% (−2.9591); 10% (−2.6181) (ii) Critical values for ADF with Trend are: 1% (−4.2820); 5% (−3.55614); 10% (−3.2138) Without Trend: 1% (−3.6537), 5% (−2.9514), 10% (−2.6171). With Trend: 1% (−4.712), 5% (−3.5562), 10%(−3.2109) Source Author’s own computation by using EViews-6

Table 6.5 Results of Johansen cointegration test (trace statistics) for PCY, FDI and Aid Model 1: LogPCY LogFDI LogAid Hypothesized No. of CE(s) None* At most 1 At most 2

Eigen value

Trace Statistic

0.05 Critical value

Prob.**

0.525105 0.224313 0.000654

31.97827 8.149116 0.020937

29.79707 15.49471 3.841466

0.0276 0.4496 0.8849

Notes Trace test indicates 1 cointegrating eqn(s) at the 0.05 level *denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values Source Author’s own computation by using EViews-6

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

157

Table 6.6 Unrestricted cointegration rank test (maximum eigen value) Hypothesized No. of CE(s) None* At most 1 At most 2

Eigen value

Max-eigen Statistic

0.05 Critical value

Prob.**

0.525105 0.224313 0.000654

23.82915 8.128179 0.020937

21.13162 14.26460 3.841466

0.0203 0.3658 0.8849

Notes Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level *denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values Source Author’s own computation by using EViews-6

Table 6.7 Normalized co integrating coefficients (standard error in parentheses) LogPCY 1.000000

LogFDI

LogAid

0.043878 (0.05809)

1.017087 (0.15473)

Source Author’s own computation by using EViews-6

Table 6.8 Pairwise Granger causality tests Null hypothesis

Obs

F-statistic

Prob

LogFDI does not Granger Cause LogPCY LogPCY does not Granger Cause LogFDI LogAid does not Granger Cause LogPCY LogPCY does not Granger Cause LogAid

32

1.14494 1.01725 7.97134* 7.57726*

0.3332 0.3750 0.0014 0.0018

1.23951 4.44763*

0.3055 0.0214

LogAid does not Granger Cause LogFDI LogFDI does not Granger Cause LogAid

40 Aid → PCY PCY→Aid 32 FDI → Aid

Notes Significance at the 1%, 5% and 10% level is indicated by *, ** and ***, respectively Source Author’s own computation by using EViews-6

such as PCY, Aid, FDI and export. Table 6.14 shows the results of Pairwise Granger causality. Results are very encouraging. However, in this model FDI shows better impact on the variable of PCY than Aid variable.

158

M. PAL

Table 6.9 Results of Vector Error Correction Model for PCY, Aid, FDI Cointegrating Eq

CointEq1

LogPCY(−1) LogAid(−1)

1.000000 1.425011 (0.32101) [ 4.43913] 0.132088 (0.10669) [ 1.23805] −8.093467

LogFDI(−1)

C Error correction

D(LogPCY)

D(LogAid)

D(LogFDI)

CointEq1

−0.085814 (0.02859) [−3.00152] −0.111851 (0.15843) [−0.70600] −0.100994 (0.16597) [−0.60852] 0.059515 (0.03746) [1.58884] −0.011572 (0.03097) [−0.37364] 0.024972 (0.01580) [1.58035] −0.004729 (0.01350) [−0.35025] 0.058596 (0.01362) [4.30292]

−0.290497 (0.26577) [−1.09303] −1.227207 (1.47276) [−0.83327] 0.045395 (1.54282) [0.02942] −0.071684 (0.34821) [−0.20586] −0.373172 (0.28790) [−1.29620] 0.082587 (0.14689) [0.56224] 0.141139 (0.12551) [1.12448] −0.097082 (0.12659) [−0.76691]

0.335161 (0.44891) [0.74661] 1.772944 (2.48760) [0.71271] 1.119991 (2.60595) [0.42978] −0.001468 (0.58816) [−0.00250] −0.328548 (0.48628) [−0.67563] −0.165487 (0.24811) [−0.66700] −0.144341 (0.21200) [−0.68084] 0.005024 (0.21382) [0.02350]

d(LogPCY(−1))

d(LogPCY(−2))

d(LogAid(−1))

d(LogAid(−2))

d(LogFDI(−1))

d(LogFDI(−2))

C

(continued)

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

159

Table 6.9 (continued) Error correction

D(LogPCY)

R-squared 0.582169 Adj. R-squared 0.442892 Sum sq. resids 0.027337 S.E. equation 0.036080 F-statistic 4.179933 Log likelihood 59.86972 Akaike AIC −3.577222 Schwarz SC −3.200037 Mean dependent 0.050694 S.D. dependent 0.048338 Determinant resid covariance (dof adj.) Determinant resid covariance Log likelihood Akaike information criterion Schwarz criterion

D(LogAid)

D(LogFDI)

0.431172 0.241563 2.362296 0.335396 2.274003 −4.788123 0.881940 1.259125 −0.076881 0.385121 4.47E−05 1.70E−05 35.83104 −0.609037 0.663962

0.141410 −0.144786 6.739604 0.566510 0.494102 −19.98944 1.930306 2.307492 0.088711 0.529475

Source Author’s own computation by using EViews-6

It shows that export variable has a positive impact on the FDI which has increased the growth effect of FDI. Encouraging FDI is also causing export volume. Table 6.15 demonstrates the results of VECM. ECT term in this model is also in minus sign and its value is around −0.17 which shows low speed of adjustment and only 17% disequilibrium is corrected in one year. Granger Causality results also support desired directions. However, in this model FDI shows better impact on the variable of PCY than Aid variable. It shows that export variable has a positive impact on the FDI which has increased the growth effect of FDI. Supremacy of private capital over official capital is not established during the study period. In India, private capital and official capital remain complementary not as substitute because the effectiveness of Foreign Aid has improved the effectiveness and productivity of FDI inflow in India.6 These four macrovariables used in this model have been reinforcing each other to increase the economic growth process in India. These findings are consistent with important studies such as Papanek (1973), Burnside and Dollar (2000), Addison et al. (2018), S. Mallick and T. Moore (2008), Collier and Dollar (2002). New evidence from Lipsey (2011) and Easterly et al. (2001) indicates that it is not the change in the level of capital stock but change in the faster

160

M. PAL Response to Cholesky One S.D. Innovations Response of LOGPCY to LOGFDI

Response of LOGPCY to LOGODA

Response of LOGPCY to LOGPCY .04

.04

.04

.00

.00

.00

-.04

-.04

-.04

-.08

-.08

-.08

-.12

1

2

3

4

5

6

7

8

9

10

-.12

1

Response of LOGODA to LOGPCY

2

3

4

5

6

7

8

9

10

-.12

.4

.4

.3

.3

.3

.2

.2

.2

.1

.1

.1

.0

.0

.0

-.1

-.1

-.1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

6

7

8

9

10

.6

.6

.4

.4

.4

.2

.2

.2

.0

.0

.0

-.2

-.2

-.2

2

3

4

5

6

7

8

9

10

1

2

3

4

5

6

7

8

9

3

4

5

6

7

8

9

10

2

3

4

5

6

7

8

9

10

Response of LOGFDI to LOGFDI

.6

1

1

Response of LOGFDI to LOGODA

Response of LOGFDI to LOGPCY

2

Response of LOGODA to LOGFDI

Response of LOGODA to LOGODA

.4

1

1

10

1

2

3

4

5

6

7

8

9

10

Fig. 6.3 Response to Cholesky One S.D. Innovations (Model for PCY, Aid, FDI (Source Author’s own work) Table 6.10 Variance decomposition of LogPCY Period 1 5 10

S.E

LogPCY

LogAid

LogFDI

0.036080 0.114274 0.212149

100.0000 29.81068 11.83560

0.000000 64.77048 77.94928

0.000000 5.418841 10.21511

Source Author’s own computation by using EView-6

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

161

Table 6.11 Variance decomposition of LogAid Period 1 5 10

S.E

LogPCY

LogAid

LogFDI

0.335396 0.433468 0.466293

0.175620 1.465806 2.294500

99.82438 96.53882 95.79224

0.000000 1.995374 1.913257

Source Author’s own computation by using EView-6

Table 6.12 Variance decomposition of LogFDI Period 1 5 10

S.E

LogPCY

LogAid

LogFDI

0.566510 1.185398 1.680934

3.875641 10.22251 11.00704

0.925280 1.516899 1.490395

95.19908 88.26059 87.50256

Note Cholesky Ordering: LogPCY, LogAid, LogFDI Source Author’s own computation by using EViews-6

Table 6.13 LogPCY, LogFDI, LogAid, LogEXPORT No. of CE(s) None* At most 1 At most 2 At most 3

Eigen value

Statistic

Critical value

Prob.**

0.544720 0.348600 0.298219 0.001951

50.28997 25.11102 11.39480 0.062494

47.85613 29.79707 15.49471 3.841466

0.0290 0.1575 0.1883 0.8026

Notes Trace test indicates 1 cointegrating eqn(s) at the 0.05 level *denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values Source Author’s own computation by using EView-6

productivity of foreign capital that promotes economic growth.7 Another evidence is also available on the cost and benefit analysis on FDI and loan finance in the host countries, see Thirlwall (1989).8

162

M. PAL

Table 6.14 Model 2 Pairwise Granger causality tests Null hypothesis

Obs

LogFDI does not Granger Cause LogEXPORT LogEXPORT does not Granger Cause LogFDI

32

F-statistic

Prob

7.40178* 0.0027 3.26097*** 0.0539

FDI → Export 40 2.05733 7.25134* Export → Aid LogPCY does not Granger Cause LogEXPORT 40 0.60752 LogEXPORT does not Granger Cause LogPCY 2.35035 LogAid does not Granger Cause LogFDI 32 1.23951 LogFDI does not Granger Cause LogAid 4.44763** FDI → Aid LogPCY does not Granger Cause LogFDI 32 1.01725 LogFDI does not Granger Cause LogPCY 1.14494 LogPCY does not Granger Cause LogAid 40 7.57726* LogAid does not Granger Cause LogPCY 7.97134* PCY→Aid Aid → PCY LogAid does not Granger Cause LogEXPORT LogEXPORT does not Granger Cause LogAid

0.1430 0.0023 0.5503 0.1102 0.3055 0.0214 0.3750 0.3332 0.0018 0.0014

Notes Significance at the 1%, 5% and 10% level is indicated by *, ** and ***, respectively Source Author’s own computation by using EViews-6

6.6

Conclusions

This chapter examines the relative significance of debt (official) and nondebt (private) creating capital in India and also tests two empirical models. Model 6.1 incorporates three variables such as PCY, FDI and Aid. After confirming the order of integration, model confirms one cointegrating vector and shows positive and long-run relationship, 1% increase in Aid causes 1.1% rise in PCY, while 1% increase in FDI causes only 0.04% rise in PCY. In this model growth effect of Aid records more than the growth effect of FDI, ECT value is in the minus, which is a correct sign as per economic theory, however, its value is around 0.08 which shows very poor adjustment in correcting disequilibrium in one year. Model 6.2 is extended by incorporating export variable. In this model also one cointegrating vector is confirmed which tells positive and long-run relationship among the variables. In this model FDI shows better impact on the PCY than Aid variable. It shows that export has good impact on the FDI. ECT term is also in minus and its value is around −0.17 which again shows low speed of adjustment; it means that only 17% disequilibrium is

6

163

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY Response to Cholesky One S.D. Innovations

Response of LOGPCY to LOGEXPORT

Response of LOGPCY to LOGFDI

Response of LOGPCY to LOGODA

Response of LOGPCY to LOGPCY .06

.06

.06

.06

.04

.04

.04

.04

.02

.02

.02

.02

.00

.00

.00

.00

-.02

-.02

-.02

-.02

1

2

3

4

5

6

7

8

9

1

10

-.06

-.06

-.06

-.06

-.04

-.04

-.04

-.04

2

3

4

5

6

7

8

9

1

10

3

4

5

6

7

8

9

1

10

.4

.4

.4

.4

.3

.3

.3

.3

.2

.2

.2

.2

.1

.1

.1

.1

.0

.0

.0

.0

1

2

3

4

5

6

7

8

9

1

10

2

3

4

5

6

7

8

9

1

10

2

3

4

5

6

7

8

9

1

10

.6

.6

.6

.6 .4

.4

.4

.4

.2

.2

.2

.2

.0

.0

.0

.0

-.2

-.2 1

2

3

4

5

6

7

8

9

2

3

4

5

6

7

8

9

1

10

Response of LOGEXPORT to LOGODA

2

3

4

5

6

7

8

9

1

10

Response of LOGEXPORT to LOGFDI

.08

.08

.08

.06

.06

.06

.06

.04

.04

.04

.04

.02

.02

.02

.02

.00

.00

.00

.00

-.02

-.02

-.02

-.02

-.04 1

2

3

4

5

6

7

8

9

10

-.04 1

2

3

4

5

6

7

8

9

10

6

7

8

9

10

2

3

4

5

6

7

8

9

10

2

3

4

5

6

7

8

9

10

Response of LOGEXPORT to LOGEXPORT

.08

-.04

5

-.2

-.2 1

10

Response of LOGEXPORT to LOGPCY

4

Response of LOGFDI to LOGEXPORT

Response of LOGFDI to LOGFDI

Response of LOGFDI to LOGODA

Response of LOGFDI to LOGPCY

3

-.1

-.1

-.1

-.1

2

Response of LOGODA to LOGEXPORT

Response of LOGODA to LOGFDI

Response of LOGODA to LOGODA

Response of LOGODA to LOGPCY

2

-.04 1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

6

7

8

9

10

Fig. 6.4 Response to Cholesky One S.D. Innovations (Model for PCY, Aid, FDI and Export) (Source Author’s own work)

corrected in one year. Granger causality results also support desired directions. Supremacy of private capital over official capital is not established during the study period. In India, private capital and official capital remain complementary not as substitute. These four macrovariables have been reinforcing each other to increase the economic growth process in India. Findings are consistent with Papanek (1973), Burnside and Dollar (2000) Addison et al. (2018), S. Mallick and T. Moore (2008), Collier and Dollar (2002) and UN (2014). New evidence from Easterly et al. (2001) indicates that it is not the change in the level of capital stock but change in the faster productivity of foreign capital that promotes economic growth.

164

M. PAL

Table 6.15 Result of Vector Error Correction Model for PCY, Aid, FDI and Export Cointegrating Eq

CointEq1

LogPCY(−1) LogAid(−1)

1.000000 0.189799 (0.13943) [1.36130] 0.224625 (0.05796) [ 3.87550] −1.340613 (0.22749) [−5.89312] −5.991596

LogFDI(−1)

LogEXPORT(−1)

C Error correction

D(LogPCY)

D(LogOD)

D(LogFDI)

D(LogEXPORT)

CointEq1

−0.169234 (0.05208) [−3.24927] 0.160159 (0.13275) [1.20646] 0.224451 (0.13591) [1.65144] −0.022152 (0.02006) [−1.10430] −0.085862 (0.02339) [−3.67099] 0.023521 (0.01537) [1.53061] −0.033923 (0.01599) [−2.12220] −0.372943 (0.13695) [−2.72326]

−0.316506 (0.52764) [−0.59985] −0.331294 (1.34486) [−0.24634] 1.067215 (1.37689) [0.77509] −0.366187 (0.20322) [−1.80189] −0.630957 (0.23695) [−2.66281] 0.058606 (0.15568) [ 0.37646] 0.047997 (0.16194) [0.29639] −0.895756 (1.38737) [−0.64565]

−1.922344 (0.75815) [−2.53557] 0.604665 (1.93238) [0.31291] −0.439432 (1.97840) [−0.22212] 0.537403 (0.29200) [1.84039] 0.158025 (0.34047) [0.46414] −0.038981 (0.22369) [−0.17427] 0.019511 (0.23269) [0.08385] −1.198694 (1.99346) [−0.60131]

0.030376 (0.09358) [0.32462] 0.128281 (0.23851) [0.53785] −0.311267 (0.24419) [−1.27471] −0.074494 (0.03604) [−2.06692] −0.008586 (0.04202) [−0.20431] −0.088820 (0.02761) [−3.21711] 0.001709 (0.02872) [0.05951] −0.098618 (0.24605) [−0.40081]

D(LogPCY(−1))

D(LogPCY(−2))

D(LogAid(−1))

D(LogAid(−2))

D(LogFDI(−1))

D(LogFDI(−2))

D(LogEXPORT(−1))

(continued)

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

165

Table 6.15 (continued) Error correction

D(LogPCY)

−0.145784 (0.09354) [−1.55855] C 0.058667 (0.01378) [4.25663] R-squared 0.640334 Adj. R-squared 0.469966 Sum sq. resids 0.023531 S.E. equation 0.035192 F-statistic 3.758528 Log likelihood 62.04328 Akaike AIC −3.589192 Schwarz SC −3.117711 Mean dependent 0.050694 S.D. dependent 0.048338 Determinant resid covariance (dof adj.) Determinant resid covariance Log likelihood Akaike information criterion Schwarz criterion D(LogEXPORT(−2))

D(LogOD)

D(LogFDI)

D(LogEXPORT)

−0.127280 (0.94761) [−0.13432] −0.127240 (0.13963) [−0.91129] 0.418471 0.143009 2.415045 0.356522 1.519163 −5.108336 1.041954 1.513436 −0.076881 0.385121 1.34E−07

−0.576060 (1.36158) [−0.42308] 0.196901 (0.20062) [0.98144] 0.364808 0.063927 4.986019 0.512271 1.212466 −15.61968 1.766874 2.238356 0.088711 0.529475

0.354983 (0.16805) [2.11231] 0.064013 (0.02476) [2.58511] 0.550684 0.337850 0.075957 0.063228 2.587384 45.05158 −2.417350 −1.945869 0.057823 0.077701

2.47E−08 89.41228 −3.131881 −1.057364

Source Author’s own computation by using EViews-6

Notes 1. For detailed analysis and comprehensive survey on the issue of complementarity between public and private investment, see World Bank (1998). 2. For comprehensive study on the topic, see Thirlwall (1989). 3. India has acquired almost all types of debt creating and non-debt creating capital. The need of foreign capital is based in Indian economy on certain grounds: India needs ODA, IBRD and IDA money for the development of Economic Overhead Capital (EOC) and Social Overhead Capital (SOC) such as transport, electricity generation and distribution, irrigation and telecommunications, health, education and sanitation. Private investment is needed for boosting the industrial product and economic confidence. Commercial borrowing, NRI and remittances money are required when traditional sources of foreign capital are exhausted. India needs all types of capital because each type of foreign capital has its own merits and demerits.

166

M. PAL

4. Under capital account, capital inflows can be classified by instruments (debt or equity) and maturity (short or long term). The main components of capital account include foreign investment, foreign loans and banking capital. Foreign investment includes FDI and Portfolio. While portfolio investment consists of FIIs, ADRs/GDRs and represents non-debt liabilities, while foreign loans include external assistance, ECBs and trade credit and banking capital which also includes NRIs deposits, represent debt creating liabilities. Further, overall balance includes total current account balance, capital account balance and error and omissions. 5. For detailed analysis on this issue, see Rana and Dowling (1988). 6. For comprehensive survey on Aid effectiveness, see World Bank Research Report (1998). 7. Collier and Dollar (2002) apply the CPIA to study the Aid effectiveness of Aid in the Aid recipient countries. The CPIA analysis is based on the responsiveness of Foreign Aid to the quality of economic policies in the Aid recipient countries. Its main findings reveal that 1% increase in Foreign Aid causes 0.6% increase in economic growth in economies which follow good economic policies, while 0.4% causes growth in economies with average policies and 0.2% causes economic growth in economies which follow poor economic policies. The CPIA economic model has proved a very effective instrument of Aid allocation to poor countries which follow good economic policies. Recent examples are Vietnam, a success case story study and Zambia, a failed case story. CPIA main findings are consistent with the findings of World Bank (1998) and Burnside and Dollar (2000). 8. FDI inflow is also not without demerits such as repatriation of high profit, regional imbalances, income inequality, overheating of upper-middleincome class in a rapidly growing economy like India, transfer of outdated technology in the host country, host country loses her control on economic policy. Further if the cost of FDI and Foreign Aid is compared, we find very interesting results. FDI repatriation or outflow of profit on FDI may be more than the cost of debt service ratio (DSR) on Foreign Aid. Moreover, loan or Foreign Aid creates an obligation or liability for fixed maturity period, it may be 20–40 years, while FDI involves unlimited commitment. For comprehensive survey on this topic, see Thirlwall (1989, 2005).

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

167

References Adams, S., et al. 2017. The effects of capital flows on economic growth in Senegal. Margin: The Journal of Applied Economic Research 11 (2): 121–142. Addison, T., et al. 2018. Aid is not dead. Policy Brief, UNU-WIDER, Helsinki, Finland. Aggarwal, P. 2017. Economic impact of foreign capital inflows in emerging Asia. In Sustaining high growth in India, ed. P. Aggarwal, 235–236. New Delhi: Cambridge University Press. Arunachalam, R. 2014. Impact of capital flows on some macro variables in India. The Indian Economic Journal 34: 420–427. Banday, U.J. 2016. Dynamic nexus between budget deficit and current account deficit: Some empirical results relating to the Indian economy. Asian Economic Review 58 (1): 29–87. Bosworth, B., and M. Collins. 1999. Capital flows to developing economies: Implications for saving and investment. Brookings Papers on Economic Activity 30 (1): 143–180. Bowles, P. 1981. Foreign aid and domestic saving in LDCs: Some tests for causality. World Development 15 (6): 789–796. Burnside, C., and D. Dollar. 2000. Aid, policies and growth. American Economic Review 90 (4): 847–868. Calvo, G., and C. Reinhart. 1998. The consequences and management of capital inflows: Lessons for Sub-Saharan Africa. RGDP, Paper No. 2. Chakraborty, I. 2005. Capital inflows in to India in the post-liberalization period: An empirical investigation. Occasional Paper, IDS, Calcutta. Chakraborty, C., and P. Nannenkamp. 2008. Economic reforms, FDI and economic growth in India: A sector level analysis. World Development 36 (7): 1192–1212. Chenery, H.B., and A.M. Stout. 1966. Foreign assistance and economic development. American Economic Review 56 (4): 679–733. Collier, P., and D. Dollar. 2002. Aid allocation and poverty reduction. European Economic Review 46 (8): 1475–1500. Corsepius, U., et al. 1989. Debt versus equity finance in developing countries— An empirical analysis of the principal-agent model of international capital transfers. Working Paper 328, Kiel Institute for World Economy (IFW), Turbingen. Dauda, R., and S. Oladoyin. 2008. Trends, behavioral patterns and growth implications of foreign private capital flows in Nigeria. ICFAI Journal of Financial Economics 6 (3): 29–40. de Vita, G., and S.K. Kyaw. 2009. Growth effects of FDI and portfolio investment flows to developing countries: A disaggregated analysis by income levels. Applied Economics Letters 16 (3): 277–283.

168

M. PAL

Domar, E. 1946. Capital expansion, rate of growth and employment. Econometrica 14 (2): 137–149. Dowling, J.M., and U. Hiemenz. 1983. Aid, saving and growth in Asian region. The Developing Economies 21: 3–13. Dua, P., and P. Sen. 2013. Capital flows and exchange rates: The Indian experience. Indian Economic Review 48 (1): 189–220 and reprinted in K.L. Krishna, V. Pandit, K. Sundaram, and P. Dua. 2017. Perspectives on economic development and policy in India. Springer. Dua, P., and R. Ranjan. 2012. Exchange rate policy and modeling in India. New Delhi: Oxford University Press. Easterly, W., I. Roumeen, and J.E. Stiglitz. 2001. Shaken and stirred: Explaining growth volatility. In Annual World Bank conference on development economics, ed. B. Pleskovic and N. Stern. Washington, DC: World Bank. Edward, S. 1990. Capital flows, foreign direct investment and debt-equity swaps in developing countries. Working paper No. 3497, NBER, Cambridge. Griffin, K.B., and J.L. Enos. 1970. Foreign assistance: Objectives and consequences. Economic Development and Cultural Change 18 (3): 313–327. Gupta, K.L. 1975. Foreign capital inflows, dependency burden, and saving rates in developing countries: A simultaneous equation model. Kyklos 28 (2): 358– 374. Gorgens, E. 1976. Development aid—An obstacle to economic growth in developing countries? German Economic Review 14 (3–4): 204–216. Harrod, R.F. 1939. An essay in dynamic theory. The Economic Journal 49 (193): 14–33. Khalifa, G. 1998. Public investment and private capital formation in a vector error-correction model of growth. Applied Economics 30 (6): 837–844. Kulshrestha, M., and B. Nag. 2000. Some methodological comments on public investment and private capital formation in a vector error-correction model of growth, by K.H Ghali. Applied Economics Letters 7 (8): 581–583. Kyaw, K.S., and R. Macdonald. 2009. Capital flows and growth in developing countries: A dynamic panel data analysis. Oxford Development Studies 37 (2): 101–122. Lachler, U. 1985. Debt vs equity in development finance. Working Paper, 248, Institute for Weltwitsxhaft (IFW) Kiel. Lachler, U., and P. Nunnekamp. 1989. The effects of debt versus equity inflows on savings and growth in developing economies. Kiel Working Papers 276, Kiel Institute for the World Economy (IFW Kiel). Lamptey, R.O., et al. 2017. The effects of capital flows on economic growth in Senegal. The Journal of Applied Economic Research 11 (2): 121–142. Law, S.H. 2009. Trade openness, capital flows and financial development in developing economies. International Economic Journal 23 (3): 409–426.

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

169

Lipsey, R.F. 2011. Inward FDI and growth in developing countries. Transnational Journal Corporation 9 (1): 83–84. Liu, X., P. Burridge, and P.J.N. Sinclair. 2002. Relationship between economic growth, foreign direct investment and trade: Evidence from China. Applied Economics 34 (11): 1433–1440. MacKinnon, J.G., A.A. Haug, and L. Michelis. 1999. Numerical distribution functions of likelihood ratio tests for cointegration. Journal of Applied Econometrics 14: 563–577. Majumder, S.B., and R.N. Nag. 2016. Understanding the behavior of capital flow and its components: The Indian experience. Margin: The Journal of Applied Economic Research 10 (3): 355–380. Mallick, S., and T. Moore. 2008. Foreign capital in growth model. Review of Development Economics 12 (1): 143–159. Mazumdar, T. 2005. Capital flows into India: Implications for its economic growth. Economic and Political Weekly 40 (21): 2183–2188. Montiel, P.J., and C.M. Reinhart. 1999. Do capitals and macroeconomic policies influence the volume and composition of capital flows? Evidence from the 1990s. Journal of International Money and Finance 18 (4): 619–635. Mosley, P. 1980. Aid, saving and economic growth revisited. Oxford Bulletin of Economics & Statistics 42: 79–95. Mosley, P. 1985. The political economy of foreign aid: A model of the market for a public good. Economic Development and Cultural Change 33 (2): 373–393. Mosley, P. 1987. Foreign aid: Its defense and reform. Brighton, England. Pal, M. 1995. Foreign capital—Growth nexus in India. Paper presented at IIDS International Conference held at Swedish Academy of Science, Helsinki, Finland, 28th–30th August. Pal, M. 2013. Determinants of Foreign Capital in India—A cointegration approach. 96th Annual Conference of Indian Economic Association at Meenakshi University, Chennai, 26th–28th December. Pal, M. 2014. Financial development in India: An empirical test of the McKinnon-Shaw model. In Analytical issues in trade, development and finance, ed. A.N. Ghoh and A.K. Karmakar, 405–420. New Delhi: Springer. Pal, P. 2015. The management and impact of cross-border capital flows in India. In Economics, Vol 2: India and the international economy, ed. Jayati Ghish. New Delhi: Oxford University Press. Pal, M. 2016. Foreign capital led growth in India—A disaggregated model. Paper presented at 92nd Annual Conference of The Indian Econometric Society (TIES) IIM, Kozhikode, 4th–6th January. Papanek, G.F. 1972. The effect of aid and other resource transfer on savings and growth in less developed countries. The Economic Journal 82 (327): 934–950. Papanek, G.F. 1973. Aid, foreign private investment, saving and growth in less developed countries. Journal of Political Economy 81 (1): 120–130.

170

M. PAL

Peter, N. 1987. The effects of debt versus equity inflows on savings and growth in developing economies. Welt Archive 12: 631–650. Pradhan, N.C. 2011. Nexus between capital flows and economic growth. Journal of International Economics 2 (1): 18–37. Prasad, E.S., R. Rajan, and S. Arvind. 2007. Foreign capital and economic growth, 153–255. Washington, DC: Brookings Papers in Economic Activity. Rachdi, H., and H. Saidi. 2011. The impact of foreign direct investment and portfolio investment on economic growth in developing and developed economics. Interdisciplinary Journal of Research in Business 6 (1): 10–17. Ramakrishna, G. 2005. Volatility in trade openness, capital inflows and economic growth: The case of India. The IUP Journal of Financial Economics 3 (3): 7–18. Rana, P.B., and J.M. Dowling Jr. 1988. The impact of foreign capital on growth: Evidences from Asian developing countries. The Developing Economies 26 (1): 3–11. Rangarajan, C. 2000. Capital flows: Another look. Economic and Political Weekly 35 (50): 4421–4427. Ranjan, R., and S. Kumar. 2012. An empirical investigation of the impact of capital inflows on domestic investment in India. Indian Economic Review XXXVII (1): 15–32. Rao, V.K.R.V. 1952. India’s first five year plan—A descriptive analysis. Pacific Affairs 25 (1): 3–23. Rao, M.J., and S. Balwant. 1998. Optimising the pace of capital account convertibility. Economic and Political Weekly 33 (21): 1247–1254. Rao, V.K.R.V., and D. Narain. 1963. Foreign aid and India’s development. Bombay: Asian Publishing House. Rashid, A., and H. Fazal. 2013. Capital inflows, inflation and exchange rate volatility: An investigation for linear and non linear causal linkages. Pakistan Development Review 52 (3): 183–206. Rodan, R. 1961. International aid for underdeveloped countries. Review of Economics and Statistics 43 (2): 107–138. Sachs, J.D., and D. Cohen. 1982. LDC borrowing with default risk. Working Paper, 925, National Bureau of Economic Research (NBER), Cambridge, MA. Sahoo, P., and M.K. Mathiyazhagan. 2003. Economic growth in India: ‘Does FDI inflow matter?’ Singapore Economic Review 48 (2): 151. Schumpeter, J. 1911. The theory of economic development: An inquiry into profits, capital, credit, interest, and the business. Harvard Economic Studies, No. 46, Harvard University Press. Sethi, N. 2013. Causal relationship between foreign capital inflows and economic growth: Empirical evidence from India. International Journal of Economics, Finance and Management 2 (1): 65–69.

6

PCY, FOREIGN AID AND FDI: A TEST OF COMPLEMENTARITY

171

Sharma, B. 1986. Foreign capital and economic growth of developing countries: Debt vs. equity. Studies in Comparative International Development 21 (1): 60–70. Sikdar, S. 2006. Foreign capital inflow into India: Determinants and management. India Resident Mission (INRM) Policy Brief, No. 4, Asian Development Bank, New Delhi. Singh, G. 2006. More on capital account convertibility. Economic and Political Weekly 41 (33): 3617–3619. Singh, R. 2009. Delays and cost overruns in infrastructure projects: An enquiry into extents, causes and remedies. Working Paper No. 181, Centre for Development Economics, Delhi School of Economics, University of Delhi. Singh, B. 2009. Changing contours of capital flows to India. Economic and Political Weekly 44 (43): 58–66. Thirlwall, A.P. 1989. Growth and development: With special reference to developing economies. Palgrave Macmillan. Tiwari, A.K., and B. Pandey. 2014. Foreign aid, economic freedom and economic growth in Asian countries. The Indian Economic Journal, Special Issues, Indian Economic Association (IEA) India. Trevino, L.J., and K.P. Upadhyaya. 2003. Foreign aid, FDI and economic growth: Evidence from Asian countries. Transnational Corporations 12 (2): 119–136. UN. 2014. World economic situation and prospects. New York: United Nations. Uppadhyay, P.G. 2008. Remittances and economic growth. The European Journal of Development Research 20 (3): 497–506. Weisskopf, T.E. 1972a. The impact of foreign capital inflows on domestic savings in under developed countries. LDCs Journal of International Economics 2 (1): 25–38. Weisskopf, T.E. 1972b. An econometric test of alternative constraints on economic growth of underdeveloped countries. Review of Economics and Statistics 54 (1): 67–78. World Bank. 1998. Assessing aid: What works, what does not and why? Washington: World Bank Study.

CHAPTER 7

Summary and Conclusions

7.1

Introduction

Foreign Capital in the process of economic growth has increased at an alarming rate in India. India has always been a favored destination of Foreign Capital before and after 1991. Till mid-1980s Foreign Aid played a strategic role in removing financial and physical constraint in Indian economy. During late 1980s commercial borrowing, NRI and short-term capital tried to fill the two gaps, and also tried to compensate the shortage of Foreign Aid and soft Aid from the IDA. New Economic Policy of 1991 shifted from debt to non-debt creating policy in which FDI and Portfolio capital have assumed a significant role. The main research question of this study is to investigate the positive relationship and causal direction between foreign capital and growth in India in a disaggregated model for the period of 42 years (i.e. from 1971 to 2013) with a research gap in terms of longer period, methodology, disaggregation of foreign capital and conceptual clarification. India shifted her economic policy from debt creating to non-debt creating foreign capital flows. Net capital inflows ranged from 1.5% of GDP to 3% GDP mainly with certain fluctuations of 4.8% of GDP in 2006–09 to 8.6% of GDP in 2007–08 while declined to 0.5% of GDP in 2008–09 and again increased to 4.1% of GDP in 2010. Net foreign investment ranged from 0.1% of GDP in 1992 to 6% of GDP in 2008. Debt flows ranged from

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. Pal, Foreign Capital and Economic Growth in India, https://doi.org/10.1007/978-981-99-2299-4_7

173

174

M. PAL

2.2% of GDP in 1990–01 to 3.3% of GDP in 2008, on an average it remained 1.5% to 2% of GDP.

7.2

Core Findings

Finding 1 attempts to test empirically the potential determinants of FDI in India with the help of new time-series methodology. Chapter two takes into account testing empirically two models. Model-1 includes seven variables such as FDI, Trade openness, Financial Deepening, GDP, growth rate, PCY and Nominal Exchange Rate. After confirming the order of integration, we find two cointegrating equations and reject null hypothesis of no cointegration and show long-run relationship among variables. Model 2 includes only four variables such as FI, GDP growth rate, Financial Deepening and Trade Openness. We find two cointegrating equations. In these models trace statistic and Max. Eigen values are more than their critical value at low probability value. Then we find Pairwise Granger causality in the number of variables and find the desired results, GDP, growth rate, Financial Deepening and Trade Openness have been explored as potential determinants to attract both FDI and Foreign Investment. More emphasis should be given on increasing the level of four variables as pointed out above. Finding 2 attempts to test empirically the long-run relationship between growth rate and FDI in India and their causal direction. After testing the order of integration for both the variables with the help of ADF and Phillips-Perron test, we find both the variables to be stationary after first differencing. After confirming the order of integration, we use Johansen Cointegration test to check the long-run relationship among the variables. Our results confirm the existence of positive and longrun relationship. Trace test and Maximum Eigenvalue both indicate one cointegrating equation at the 0.05 level with the assumption of linear deterministic trend. Granger causality also confirms unidirectional causality running from FDI to growth in India. Our ECT term in VECM model shows minus sign and its value is equal to − 0.41 which demonstrates that 41% disequilibrium is corrected in one year. Results are also reconfirmed with the help of JRF and VDC. Our findings are mainly consistent with the findings of other major studies on FDI-Growth nexus and causal direction carried out mainly by de Melloo (1997); Huang (2004) and Rati and Zhang (2002).

7

SUMMARY AND CONCLUSIONS

175

Finding 3 attempts to test empirically the relationship between Foreign Aid and Economic Growth in India. The chapter improves upon earlier work on Foreign Aid-Growth nexus because it involves Johansen Cointegration technique of 1991 to trace the long-run relationship between Foreign Aid and economic growth in India. Trace Statistic and Maximum Eigenvalue results confirm the positive and long-run relationship between Foreign Aid and Economic Growth in India. Normalized function shows that 1% rise in Aid/GDP ratio causes 0.36% growth rate to increase in India. ECT term value is equal to –0.31which shows that during one year period, the level of disequilibrium is corrected by 31%. Granger Causality confirms strong causal direction from Foreign Aid to Growth in India at one lag and two lags. IRF and VDC results also reconfirm our findings. It appears that Foreign Aid has made positive contribution in Indian economy, even after declining trends of Aid/GDP ratio in India. Findings of this paper are consistent with the models of Aid effectiveness: Burnside and Dollar (2000), Addison et al. (2018), Mallik (2008), Collier and Dollar (2002). Finding 4 traces the long-run relationship and also detects the causal direction between the foreign capital and growth with the help of cointegration test and Granger pairwise causality. Both the variables NFC/GDP ratio and growth rate in India are integrated at the first order (I). We find two cointegrating vectors between NFC/GDP ratio and growth rate which show a long-run, positive and significant relationship. However, only Trace value is significant at 5% level, Max. Eigenvalue is not significant. From the VECM upper panel, we find that 1% rise in foreign capital causes 0.30% rise in growth rate. Our ECT term also shows the minus sign expected from the theory. Its value is around −0.99 which shows that model corrects 99% disequilibrium in one year period and shows high speed of adjustment. However, no Granger Pairwise causality is detected from the model. Neither NFC nor growth rate Granger causes each other. Foreign capital is found to have a positive and significant impact on the growth process in Indian economy. The results approve the foreign capital-led growth hypothesis. Findings are mainly consistent with the results of Abdelhafidh (2013), Rahman and Shahbaz (2013), Ranjan and Kumar (2012) and Pradhan (2011). Finding 5 examines the relative significance of debt (official) and nondebt (private) creating foreign capital in India and for this, we intend to test two empirical models. Model 6.1 incorporates three variables such as PCY, FDI and Aid. After conforming the order of integration, model

176

M. PAL

confirms one cointegrating vector and shows positive and long-run relationship. 1% increase in Aid causes 1.1% rise in PCY while 1% increase in FDI causes only 0.04% rise in PCY. ECT value is in minus; however; its value is around 0.08 which shows poor adjustment in correcting disequilibrium in one year. Model 6.2 is extended by incorporating export variable and confirms one cointegrating vector which tells the long-run relationship among the variables. In this model, FDI shows better impact on the PCY than Aid variable. It shows that export has good impact on the growth process. ECT term is also in minus and its value is around −0.17 which again shows low speed of adjustment; it means that only 17% disequilibrium is corrected in one year. Granger Causality results also support desired directions. Supremacy of private capital over official capital is not established during the study period. In India, private capital and official capital remain complementary not as substitute. These four macrovariables have been reinforcing each other to increase the economic growth process in India. Our findings are mainly consistent with the studies carried out by the number of studies namely Papanek (1973), Burnside and Dollar (2000), Addison et al. (2018), Mallik (2008), Collier and Dollar (2002). New evidence from Lipsey (2011), Easterly et al. (2001) indicates that it is not the change in the level of capital stock but change in the faster productivity of foreign capital that promotes economic growth. Table 7.1 demonstrates a brief summary of technical findings of five models.

7.3

Key Takeaway

1. To attract more FDI in India, Government of India should increase the level of financial deepening, trade openness, growth rate and GDP level. The increase in four major valuables will also increase business conference in India which is also essential to increase the productivity of FDI. Moreover, it will also be an instrument in attracting more foreign investment, which includes both FDI and Portfolio investment. 2. To confirm that FDI contributes positively to economic growth and increase in productivity, India will have to attain high degree of absorptive capacity in terms of increasing high level of (FDI.GDP) ratio as confirmed. 3. Granger Causality runs from FDI to Growth in India.

7

SUMMARY AND CONCLUSIONS

177

Table 7.1 Summary of short- and long-term dynamics Nexus

FDI-Growth Aid-Growth F.C.–Growth Pcy, FDI, Aid, Pcy, FDI, Aid, Export

Order of Integration

Cointegration Trace Statistics

Max-Eigen Value

(1) (1) (1) (1) (1) (1) (1)(1)(1)

1 co-int. equ 1 co-int. equ 2 co-int. equ 1. co. int equ

1 co-int. equ 1 co-int. equ not significant 1. co-int. equ

(1)(1)(1) (1)

1. co. int N.A equ

Normalized Value(1% rise causes growth

ECT should be in (−) term

Granger Causality

N.A

−0.41 FDI→G

0.36

−0.30 Aid→G 30% −0.98 FC–G

0.30 1.01 0.04 0.19 0.22

−0.08 PCY→Aid FDI→ Aid −0.17 N.A

Notes Aid = Foreign Aid, FDI = Foreign Direct Investment, F.C = Foreign Capital, F.I = Foreign Investment, Pcy = Per Capita Income, Y. = GDP growth rate, TO = Trade Openness, M3/GDP = Financial Deepening, C.V. = Calculated Value, T.V = Tabulated Value Source Author’s own work

4. India has been receiving very handsome amount of FDI, but about half of FDI inflow has been flowing out of India in terms of repatriation and FDI by Indian investors outside. 5. Financial Liberalization and trade liberalization have good impact on FDI inflow and will also serve as an instrumental in increasing the FDI/GDP ratio. 6. Over the last decades, the inflow of Foreign Aid in terms of Aid/GDP ratio and in absolute net amount has declined to a considerable level. However, the growth effect of Foreign Aid is considerably high. Results from Aid-Growth nexus in India shows long-run and positive relationship with Granger causality running from Aid to GDP. 1% increase in Aid/GDP ratio causes 0.36% increase in growth rate. The main reason is that Foreign Aid utilization is more effective in India because of good policy implementation in terms of fiscal and monetary policy. This is evidenced by the studies from Burnside and Dollar (2000); Collier and Dollar (2002); Addison et al. (2018).

178

M. PAL

7. Government should not undermine the role of Foreign Aid, but to make it more effective, infrastructure projects where Foreign Aid is being utilized, should be implemented in time, so that the severe problem of cost overrun and time overrun in the projects, should be avoided. For detailed analysis, see Rao (1952), Rao and Narain (1963) and Singh (2009). 8. So far foreign capital-growth nexus is concerned, there is a long-run and positive relationship between aggregated net foreign capital and growth in India. Capital account opening-up has proved a success story. 9. Our findings reveal the facts that there is no substitution between FDI and Aid but remains as complementary to each other. Superiority of FDI is not established over Foreign Aid in India during the study period.

7.4

Policy Choice and Interventions

India has received all types of foreign capital. Our empirical experiments reveal that current economic liberalization policy is in the right direction to accelerate the process of economic growth in India. All macrovariables we have discussed in our study have been reinforcing each other to increase the economic growth process. India needs all types of capital, i.e. official as well as private capital because of her financial and capital market segmentation. India still needs large amount of Foreign Aid for the improvement of physical infrastructure, which is an essential activity. India still is 3rd largest borrower from the IBRD and one of the top recipients of IDA soft Aid. India is still far off from its Aid termination point. India needs FDI for the direct impact on the product market and FDI is also productive potential. India needs portfolio investment for direct impact on financial market. FDI/FIIs cannot be used for economic and social overhead facilities but these are needed for general confidence to boost industrial production and confidence. Commercial borrowing and NRI money remain procyclical but their entry cannot be denied, when country faces economic crisis.

7

SUMMARY AND CONCLUSIONS

179

The supremacy of private capital over official capital is not established. Official capital still has a role to play. In India official capital and private foreign capital remain complementary but not as a substitute. Because debt (Aid) and equity finance (FDI) involves different types of capital inflows and also involve different compensation rules. India will have to be careful in deciding which type of foreign capital is suitable to achieve rapid economic growth in India. The findings of this research should be helpful and informative to policy makers in India. A main conclusion is that abundant foreign capital does not guarantee economic prosperity for developing country like India but its effective utilization increases the productivity of foreign capital. It is this contribution that author hopes will make thus look worth reading and understanding. The End.

References Abdelhafidh, S. 2013. Potential financing sources of investment and economic growth in North African countries: A causality analysis. Journal of Policy Modeling 35 (1): 150–169. Addison et al. 2018. Aid is not dead, Policy Brief, UNU-WIDER, Helsinki, Finland. Burnside, C., and D. Dollar. 2000. Aid, policies and growth. American Economic Review 90 (4): 847–868. Collier, P., and D. Dollar. 2002. Aid allocation and poverty reduction. European Economic Review 46 (8): 1475–1500. De Mello, L.R., Jr. 1997. Foreign direct investment in developing countries and growth: A selective survey. The Journal of Development Studies 34 (1): 1–34. Easterly, W., I. Roumeen, and J.E. Stiglitz. 2001. Shaken and stirred: Explaining growth volatility. In Annual World Bank conference on development economics, ed. B. Pleskovic and N. Stern. Washington, DC: World Bank. Huang, T., Jr. 2004. Spillovers from FDI in China. Comtemporary Economic Policy 22 (1): 13–25. Lipsey, R.E. 2011. Inward FDI and growth in developing countries. Transnational Journal of Corporations 9 (1): 83–84. Mallik, G. 2008. Foreign aid and economic growth: A cointegration analysis of the six poorest African countries. Economic Analysis and Policy 38 (2): 251–260. Pradhan, N.C. 2011. Nexus between capital flows and economic growth. Journal of International Economics, Institute of Public Enterprises 2 (1): 18–37.

180

M. PAL

Rahman, M.M., and M. Shabbaz. 2013. Do imports and foreign capital inflows lead economic growth? Cointegration and causality analysis in Pakistan. South Asia Economic Journal 14 (1): 59–81. Ranjan, R., and S. Kumar. 2012. An empirical investigation of the impact of capital inflows on domestic investment in India. Indian Economic Review XXXVII (1): 15–32. Rao, V.K.R.V. 1952. India’s first five year plan—a descriptive analysis. Pacific Affairs 25 (1): 3–23. Rao, V.K.R.V., and D. Narain. 1963. Foreign aid and India’s development. Bombay: Asian Publishing House. Rati, R., and K.H. Zhang. 2002. Foreign direct investment and economic growth: Evidence from cross-country data for the 1990s. Journal of Economic Development and Cultural Change 50 (1): 205–215. Singh, R. 2009. Delays and cost overruns in infrastructure projects: An enquiry into extents, causes and remedies, Working Paper No. 181, Centre for Development Economics, Delhi School of Economics, University of Delhi.

Index

A Aid–as highly controversial subject, 89 Aid Consortium (World Bank), 91, 94 Aid effectiveness, 11, 90, 91, 103, 105, 166, 175 Aid/GDP ratio, 5, 10, 11, 93, 95, 103, 105, 151, 154, 175, 177 Aid–growth nexus, 9, 10, 12, 86, 89, 90, 97, 103, 110, 119, 146, 175, 177 Association of Southeast Asian Nations (ASEAN), 64, 147 Augmented Dickey-Fuller (ADF), 7, 10, 15, 44, 69, 72, 76, 99–101, 130, 131, 155, 156, 174 B Balasubramanyam, V.N., 6 Bosworth and Collins (1999), 2, 145, 146, 151 Burnside and Dollar Aid growth model (2000), 6, 11, 12, 90, 91, 103, 105, 111, 159, 163, 166, 175, 176

C Capital account convertibility (CAC), 135 Capital account liberalization (CAL), 52, 121, 122, 135 Capital–flight–in, 13 Capital–flight–out, 13, 121, 123 Capital flow–growth nexus, 9, 120, 130, 143, 147, 178 Causality, 7, 10, 12, 15, 32, 33, 43, 49, 50, 62, 64, 66, 67, 70, 72, 75, 77, 102, 103, 121–124, 126, 132, 133, 155, 157, 159, 174–177 Chenery and Strout (1966), 6, 8, 87, 89 Coefficient, 10–12, 72, 75, 93, 102, 103, 122, 145, 155, 157 Collier and Dollar analysis (2002) uses the CPIA, 166 Compensation rule, 179 Complementarity effects, 147 Concessionality in Foreign Aid, 107

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 M. Pal, Foreign Capital and Economic Growth in India, https://doi.org/10.1007/978-981-99-2299-4

181

182

INDEX

Cost–overrun of the project, 95, 111, 150 Country Policy and Institutional Assessment (CPIA), 166 Creditworthiness, 13 Current account deficit, 8, 51, 88, 123, 124, 135 D Debt vs Equity, 134 De Mello, L.R., (1997), 6, 10, 23, 52, 62, 63, 77, 174 Diminishing return, 91 Direct finance, 36 Disequilibrium, 8, 10–12, 70, 77, 102, 103, 133, 159, 162, 174–176 Double Tax Avoidance Agreement (DTAA), 26, 53 Dutch disease, 3, 16, 34, 89 E Econometric results, 34, 90 Economic growth, 2, 4, 7, 10, 12, 32, 34, 35, 61–68, 73, 75, 87, 89–93, 101, 103, 110, 120–122, 135, 146–148, 159, 161, 163, 166, 173, 175, 176, 178, 179 Economic overhead capital (EOC), 97, 165 Economic reforms, 4, 30 Emerging countries, 2, 14, 43, 88, 122, 143, 146 Emerging market, 121, 122 Endogenous growth theory, 62, 147 Error correction term (ECT), 10–12, 70, 77, 102, 103, 122, 132, 133, 159, 162, 174–176 Exchange rate appreciation, 7, 40 Exchange rate depreciation, 7, 32, 33, 41

External Commercial Borrowing (ECB), 2, 5, 143

F FDI as a risk sharing device, 146 FDI/GDP ratio, 4, 5, 25, 26, 68, 151, 154, 177 FDI–Growth nexus, 6, 9, 10, 12, 61–63, 65, 66, 75, 77, 119, 174 Financial deepening, 7–10, 12, 14, 24, 36, 39, 41–43, 45, 49, 50, 52, 151, 174, 177 Financial development, 7, 33 Financial intermediation, 36 Financial liberalization, 4, 16, 151, 177 Financial repression, 52 First difference, 44, 45, 68, 72, 73, 99–101, 130–133, 156 Foreign capital, 1–9, 11, 12, 16, 23, 24, 30, 33, 42, 43, 61, 63, 86–89, 94, 119–124, 126, 128, 130, 132–134, 143–150, 154, 161, 163, 165, 173, 175–179 growth nexus, 9, 120, 130, 143, 178 Foreign capital accumulation, 143 Foreign Direct Investment (FDI), 42, 119, 144, 148, 149, 154, 177 Foreign Exchange (FE), 3, 5, 13, 23, 51, 53, 85, 87, 88, 94, 121–123, 130, 143 Foreign Exchange Management Act (FEMA), 52, 53 Foreign Exchange Regulation Act (FERA), 25, 52, 53 Foreign Institutional Investors (FIIs), 32, 33, 53, 135, 143, 149, 150, 166, 178 Foreign investment (FI), 4, 7, 9, 10, 24–29, 34, 35, 37, 38, 42–45,

INDEX

48, 50, 51, 62, 135, 166, 173, 174, 176, 177 Foreign Investment Promotion Board (FIPB), 25 F–Statistics, 46–48, 50, 73, 74, 102, 135, 165 Fungiblity in Foreign Aid, 89, 150

G GDP growth, 6, 8, 9, 14, 35, 40, 43, 48, 50, 64–68, 97, 99, 124–126, 128, 130, 133, 174, 177 Global financial crisis, 4, 8 Globalization, 23 Good policy means good monetary and fiscal policy, 177 Granger Pairwise causality, 46, 73, 157, 162 Granger’s Causality Test, 50 Grant element, 2, 17, 85, 89, 94, 96, 107, 108, 110 Grant value, 107, 108 Griffin and Enos (1970), 6, 89, 110, 111 Gross Domestic Product (GDP), 4–12, 14, 25–29, 32, 33, 35–39, 41–44, 46–50, 52, 64–68, 70–72, 75, 90, 92, 93, 97–103, 106, 121, 122, 124–133, 143, 147, 148, 152–154, 173, 174, 176, 177 Growth process, 2, 8, 11, 12, 33, 43, 68, 85, 86, 97, 119, 130, 133, 144, 146, 151, 155, 175, 176 Growth rate, 4, 6, 9–12, 16, 33–35, 37, 38, 42, 43, 49, 50, 52, 62, 64, 68, 69, 71, 75–77, 88, 90–92, 97, 98, 100, 102, 103, 120–125, 127, 130, 132, 133, 144–147, 155, 174–177

183

H Harrod–Domar model, 6, 87, 110 I IMF–Structural Adjustment Programme (SAP), 53, 110 Impulse response function (IRF), 8, 11, 15, 75–77, 87, 103, 122, 155, 175 Incremental capital–output ratio (ICOR), 87, 88 India–as largest recipient of IDA soft Aid, 178 Indian Financial System (IFS), 14, 28, 126 Indirect finance, 36 Infrastructural facilities, 7, 16, 32–34, 65, 93 Infrastructure, 3, 4, 13, 17, 25, 30, 32–35, 93, 177, 178 International Bank for Reconstruction and Development (IBRD), 1, 4, 5, 16, 17, 85, 86, 93, 94, 108, 110, 111, 149, 165, 178 International Development Association (IDA), 1, 2, 5, 16, 17, 85, 86, 89, 93–95, 107, 108, 110, 149, 165, 173 International Financial Statistics (IFS), 14 International Monetary Fund (IMF), 4, 8, 14, 16, 51, 53, 92, 110, 126 J Johansen and Juselius (J.J.) (1990), 6, 8, 15, 24, 34, 67, 121 Johansen, S. (1988), 15 L Level form, 68, 101

184

INDEX

Likelihood Ratio (LR), 34 Loan Push Theory, 13, 14 Long-run-relation, 32, 33, 67, 92, 121

M Macroeconomic model, 51 Mal–allocation of Foreign Aid, 147 Market size, 6, 32–35, 65 Mexico, Brazil and Argentina (MBA), 14, 52 Micro-macro paradox, 92, 110, 145 Modeling, 92 Model specification, 24, 41, 62, 67, 87, 120, 124, 144, 151 Monetary policy, 121, 177 Mosley, P. (1987), 6, 110, 145 Multilateral Investment and Guarantee Agency (MIGA), 16, 25, 52 Multinational Companies (MNCs), 23, 24, 63

N Neo-classical theory, 62, 120 Net Foreign Capital (NFC), 2, 4, 8, 9, 11, 12, 119, 120, 123–126, 128, 131, 133, 175, 178 New Partnership for Africa’s Development (NEPAD), 34 Nexus, 9, 64, 66, 67, 177 NFC/GDP ratio, 124, 130, 133, 175 Non-Resident Indians (NRIs), 1, 2, 4, 13, 14, 25, 53, 143, 166

O Official capital, 1, 6, 12, 148, 159, 163, 176, 178 Official Development Assistance (ODA), 2, 3, 6, 15, 16, 90,

92–94, 106, 110, 111, 145–148, 165 Official flows, 144 Ordinary Least Squire (OLS), 91, 93, 122 Organization for Economic Co-operation and Development (OECD), 28, 86, 91, 110

P Pal, Mahendra (1985), 17, 92, 93, 111 Papanek, G.F. (1973), 6, 8, 89, 111, 144–146, 151, 159, 163, 176 Per Capita Income (PCY), 6, 8, 9, 11, 12, 14, 15, 35, 37–39, 42–44, 46–49, 63, 144, 151–160, 162, 164, 174–177 Phillips and Perron test (PP), 10, 44, 72, 76, 101, 132, 156, 174 Pitchford thesis, 135 Portfolio investment, 6, 8, 32, 39, 43, 53, 119, 146, 148–150, 166, 176, 178 Private capital, 1, 6, 11, 12, 120, 122, 123, 134, 144–148, 150, 159, 163, 176, 178 Procyclicality, 13, 33, 147, 178

R Real deposit rate of interest, 13 Real Effective Exchange Rate (REER), 3, 34, 121, 123 Regression, 32, 33, 93, 122, 145, 146 Re-invested earning, 30, 53 Relative significance of foreign capital, 2 Remittances, 1–3, 5, 34, 143, 148, 149, 165 Repatriation of FDI inflow, 30

INDEX

185

Reserve Bank of India (RBI), 8, 14, 25, 28, 31, 38, 69, 96, 98, 123, 126, 135, 153 Rosenstein–Rodan (1961), 87

US $, 2–5, 13, 17, 23, 25–27, 36–39, 41, 42, 51, 53, 68, 69, 95, 96, 110, 121, 123, 124

S Simultaneous equation approach, 64, 122 Social Overhead Capital (SOC), 97, 165 Speed of adjustment, 11, 12, 133, 159, 162, 175, 176 Spillover effects, 63 Structural Adjustment Programme (SAP) of the IMF, 53, 110 Sub-Saharan Africa (SSA), 86, 92

V Variance decomposition (VDC), 8, 10, 11, 15, 75, 77, 87, 103, 105, 121, 122, 155, 160, 161, 174, 175 Vector Auto Regression (VAR), 8, 15, 64, 121, 122 Vector Error Correction Model (VECM), 8, 10, 11, 15, 64, 67, 70, 72, 74, 87, 102–104, 121, 132–134, 155, 158, 159, 164, 174, 175 Volatility, 7, 9, 24, 85, 120, 147 Volatility of exchange rate, 34, 42, 123

T Tarapore Committee (1997), 53 Three Gap model by E.L. Bacha (1990) & Lance Taylor (1990), 88 Time–overrun of the project, 95, 111, 150 Time–series analysis, 7, 15, 32, 33, 65, 87, 132 Trade liberalization, 177 U Unit root test, 7, 15, 72, 101, 132, 155, 156

W World Bank, 4, 5, 8, 14, 16, 17, 51, 52, 87, 89, 91–93, 95, 107, 110, 111, 143, 165, 166 World Development Indicators (WDI), 14, 28, 126, 153

X X/GDP, 8, 152, 153