Globalization and Development Volume I: Leading issues in development with globalization [1] 9781138781511, 9781138781542, 9781315687100

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GLOBALIZATION AND DEVELOPMENT

Globalization and Development is a “cross-national study” on the “interstate dispersion” of the impacts (on growth, inequality and poverty) that international economic integration provides to the economies of the developing countries. In order to present the “Leading Issues in Development with Globalization” in a balanced manner, to identify differences and commonalities among “Country Experiences” in development with globalization and to introduce diversified development paradigms with forwardlooking discussions “In Search of a New Development Paradigm” for the postMillennium Development Goals era, this publication consists of three volumes and four main parts. Volume I (Part I) introduces the evolution and facets of globalization, and the challenges that we face in our development efforts under globalization. Findings from the old and new empirical studies are consolidated for us to answer the following question. What do we really know about the impacts of globalization? Volume I (Part II) contains thematic and issue-oriented discussions on the key facets of globalization. This book intends to serve as a unique and comprehensive guide for those in the international development community on the subjects of diversified development paradigms/paths under globalization and other challenges in the post-MDGs era. Shigeru Thomas Otsubo is Professor of International Development Economics and Director of the Economic Development Policy & Management Program at the Graduate School of International Development (GSID), Nagoya University, Japan. His recent publications include Leading Issues in Development with Globalization, Introduction to International Development Studies: An interdisciplinary approach (2010 JASID Special Award), and numerous journal articles and reports on global economic integration, development cooperation and on growth, inequality and poverty reduction. He holds a Ph.D. in Economics and Operations Research (Stanford University, USA).

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GLOBALIZATION AND DEVELOPMENT Volume I: Leading issues in development with globalization

Edited by Shigeru Thomas Otsubo

First published 2016 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 711 Third Avenue, New York, NY 10017 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2016 Shigeru Thomas Otsubo The right of the editor to be identified as the author of the editorial material, and of the authors for their individual chapters, has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilized in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data Globalization and development / edited by Shigeru Thomas Otsubo. Contents: Volume I. Leading issues in development with globalization – Volume II. Country experiences – Volume III. In search of a new development paradigm – 1. Globalization–Economic aspects. 2. Economic development. I. Otsubo, Shigeru. HF1365.G576 2015 338.9–dc23 2015002420 ISBN: 978-1-138-78151-1 (hbk) ISBN: 978-1-138-78154-2 (pbk) ISBN: 978-1-315-68710-0 (ebk) Typeset in 10/12.5pt Bembo by Graphicraft Limited, Hong Kong

CONTENTS

Figures Tables Boxes Preface Note on the editor Notes on contributors Acronyms and abbreviations

vii ix xii xiii xxii xxiii xxv

PART I

Development under globalization 1 Leading issues in development with globalization Shigeru Thomas Otsubo 2 Poverty–growth–inequality triangle under globalization: what do we really know about the pro-poor/anti-poor impacts of economic integration? Shigeru Thomas Otsubo and Yumeka Hirano

1 3

52

PART II

Thematic issues related to development under globalization 3 The role of governance and politics in the development of developing countries Hirotsune Kimura

101

103

vi

Contents

4 Globalization and corporate activities: MNCs and FDIs Shigeru Thomas Otsubo

137

5 Globalisation and agriculture: optimising trade policies for small farmers Zamroni Salim

176

6 Global environmental management: globalization of the economy and load on the global environment Kiyoshi Fujikawa and Hikari Ban

200

7 FDIs and environmental management: do we need government interventions? Muhammad Cholifihani

228

8 Global international migration and South-South migration: the case of Thailand and its adjacent countries Akihiro Asakawa

246

9 Aid is good for the poor: development aid in a globalized world Yumeka Hirano and Shigeru Thomas Otsubo

266

10 The effects of global economy on contemporary conflicts Yukiko Nishikawa 11 Impacts of global economic fluctuations on the economic growth and poverty situation of a developing country in the globalized world: the case of Indonesia Hiroshi Osada

305

326

12 Extended GTAP Data Base and a CGE model with global input–output linkage Ken Itakura and Kazuhiko Oyamada

344

Index of names Subject index

365 368

FIGURES

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 1.10 1.11 1.12 1.13 2.1 2.2 2.3 2.4 4.1 4.2 4.3 4.4

Battle in Seattle 9/11 McDonald’s around the world The sinking Tuvalu Changes in world GDP and trade Foreign direct investment by income groups, net inflows, 1975–2012 (% of GDP) Merchandise trade, current US$, 1960–2012 (% of GDP) Trade in goods and services, constant US$, 1960–1995 (% of GDP) Trends in international migrant stock, 1960–2010 (% of population) Remittances received by income groups, 1982–2012 (% of GDP) Financial flows to developing countries, 1978–2011 Commodity prices: commodity foods, metals, and crude oil, 1991–2013 Expenditure per capita on information infrastructure, 1998 (US$) Poverty–growth–inequality triangle under globalization Income convergence among integrators Changes in trade integration and inequality Kinks in decadal growth performance Trends in global FDIs, 1980–2013 (US$ billion) Global savings–investment imbalances, 1982–2012 (US$ billion) FDIs to developing countries, 1981–2004 (US$ billion) Net FDI positions of developing and developed economies, 2005–2012 (% of GDP)

4 5 7 9 24 26 28 28 30 31 32 33 35 52 54 55 66 141 142 143 144

viii

4.5 4.6

Figures

Trends in FDIs to developing regions, 1980–2012 FDIs and trade flows among APEC member countries, correlation between averages of 1992–94 4.7 FDI-funded garment factory and workers in Cambodia B4.1.1 MacDougall’s model of international movement of production factors 4.8 FDI-funded paper mill in Khon Kaen, Northeastern Thailand 5.1 Agricultural machinery including tractors per 100 sq. km of arable land 5.2 Cereal yields (kilograms per hectare) 6.1 Production structure in the GTAP-E model 7.1 CO2 emissions in lower middle income countries (metric tons per capita) 7.2 GNI per capita in lower middle income countries in 1981–2012 7.3 Foreign direct investment, net inflows in lower middle income countries (% of GDP) 7.4 Greenhouse gases and FDI in Indonesia 7.5 GNI per capita and emission reduction in Indonesia 1981–2011 (US$) 9.1 Financial flows to developing countries (1978–2011) 9.2 The conceptual framework and structure of the study 10.1 Conflict termination 1950–2003 11.1 Transmission mechanisms of macroeconomic and external impacts on poverty 12.1 Sourcing of imports in the standard GTAP 12.2 Sourcing-at-border 12.3 Sourcing-by-agent 12.4 Schematic image of GTAP Data Base 12.5 Extension of import matrices 12.6 Schematic image of GTAP-based GIO table

145 147 147 151 171 180 181 203 228 229 229 233 233 267 268 311 333 348 349 350 353 355 358

TABLES

1.1

Globalization and the evolution of global economic systems (from the end of the Age of Discovery to WWII) 1.2 Trend of trade integration (merchandise trade to GDP ratio, %) 1.3 Globalization and the evolution of global economic systems (after WWII) 1.4 Internet access by income groups and developing regions 1.5 ICT Development Index by level of development, 2010–2011 B1.1.1 Impacts of the Asian Financial Crisis on Indonesia 2.1 Characteristics of the short-term dataset (1–4 years, average duration: 1.75 years) 2.2 Characteristics of the medium-term dataset (5–9 years, average duration: 5.72 years) 2.3 Characteristics of the long-term dataset (over 10 years, average duration: 11.17 years) 2.4 Cross-correlations among dependent and explanatory variables 2.5 Medium-term impact of integration on growth 2.6 Growth impact of policies and institutional quality (ICRG composite) by different time dimensions 2.7 Growth impact of policies and institutional quality (ICRG political situation) by different time dimensions 2.8 Impact of policies, institutional quality, and globalization on the poor (inequality) 2.9 Country fixed effects of impact of globalization on the poor (bottom quintile income) 2.10 Impact of policies, institutional quality, and globalization on Gini Index (inequality) (medium-term) 2.11 Impact of policies, institutions, and globalization on poverty (HCR) (medium-term)

16 20 21 34 36 43 68 70 72 75 77 79 80 81 83 84 87

x

Tables

3.1 3.2 4.1 B4.2.1 B4.2.2 B4.2.3 B4.2.4 4.2 5.1 5.2 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9 6.10 6.11 6.12 6.13 6.14 7.1 7.2 7.3 7.4 7.5 8.1 8.2 8.3 8.4 9.1 9.2

Regional poverty estimates High-ranking “developing countries” accepting FDI inward stock, 2012 Number of parent corporations and foreign affiliates of MNCs (by region and economy) Simulation design matrix Changes in capital stock caused by Japan’s direct investment (US$ million) Impact on the world economy Impact on Japan, Asian economies, and other regions Degree of concentration in FDIs to developing countries, 1985–2005 Agriculture in the economic structure by countries (region) Agriculture in the economic structure by income group International I-O table for two regions and two sectors Country/region aggregation Industry aggregation GDP growth rate for each scenario (%) Export and import growth rate for each scenario (%) Output change for each scenario (US$ million) CO2 growth rate for each scenario (%) CO2 change for each scenario (million tons) The top six industries in terms of CO2 changes (million tons) Comparison between electricity and transport services CO2 change for each scenario (million tons) Ex-ante simulation CO2 emissions embodied in trade (million tons) CO2 emissions change under the S1 scenario Effects of EPA on embodied CO2 emissions for each scenario Result of ADF test for non stationarity Johansen Cointegration Test Long run equilibrium equation (long run elasticity) Selected countries commit to reduce emission Major policies by selected developing countries for emission reduction Key economic indicators of Thailand, Cambodia, Lao PDR, and Myanmar Sector of migrant workers registered in 2012, totals Summary of questionnaire survey of migrant workers in Bangkok, August 2011 Number of non-Thai students in 2010 Cross-correlations between dependent and explanatory variables (medium-term dataset, 5–9 years, the late 1990s–2000s) Aid, policies, institutions, and growth

105 125 139 158 159 159 160 164 177 178 204 205 206 207 208 209 211 211 212 213 215 218 220 221 236 237 237 240 241 253 258 259 262 278 280

Tables

9.3 9.4 9.5 9.6 9.7 9.8 9.9 9.10 9.11 9.12 9.13 11.1 11.2 11.3 11.4 11.5 11.6 11.7 12.1 12.2 12.3 12.4 12.5

Impact of aid on growth by different conditions of institutional quality Impact of aid, policies, institutions on the poor (inequality; level regressions) Impact of policies, institutions, and aid on Gini Index (inequality) Country fixed effects of pro-poorness Impact of aid on the poor by countries with pro-poor fixed effects Impact of aid on the quintile income groups (the late 1990s–2000s) Impact of policy, institutions, globalization, and other determinants on the poor (the late 1990s–2000s) Impact of changes in institutional quality on the quintile income groups (the late 1990s–2000s) Impact of changes in trade on the quintile income groups (the late 1990s–2000s) Impact of FDI on the quintile income groups (the late 1990s–2000s) Impact of remittance on the quintile income groups (the late 1990s–2000s) Poverty ratio and per capita income Correlation coefficient between poverty ratios and macro variables, 2002–2011 Fluctuations of major macroeconomic variables Variable list and explanations on data compilation Indonesian macro econometric model Fitness of the model Results of the impact simulations (2007–2011) Regional aggregation Sector aggregation East Asia’s bilateral imports of HeavyMnfc and Ad Valorem Tariffs Percentage changes in QXSirs Percentage changes in key variables for East Asia

xi

283 285 287 288 289 291 293 294 294 295 295 329 330 331 336 337 339 340 351 352 358 359 360

BOXES

1.1 Indonesia suffered “dispersion” from the Asian financial crisis 4.1 MacDougall’s model of international movement of production factors 4.2 Applied general equilibrium model analysis of the economic impact of FDI: economic impact of Japan’s FDI to Asian countries 4.3 Foot-loose multinational corporations: Nike’s sweat shop and the Nike model

42 150 157 166

PREFACE

My involvement with international development has evolved, across decades and continents, along with the evolution of globalization. From 1988 to 1993, I worked for the Department of International Economic and Social Affairs at the UN Headquarters in New York as a core member of two projects. One was Project LINK initiated by Prof. Lawrence Klein, a Nobel prize-winning economist. The other project, Global Interdependence, was led by Prof. Wassily Leontief, also a Nobel laureate in economics. The Department of International Economic and Social Affairs is known for a division which used to carry out the United Nations Development Decade vision study directed by Prof. Jan Tinbergen. The UN, in those times, was intending to analyze the interdependence of the global macro economy in order to carry out short- to medium-term economic policy simulations of the North–South issues through Project LINK which connected the macroeconometric models of member countries using the trade flows of goods and services among those nations. At the same time, the UN was attempting to create a vision of long-term global interdependence through the Global Interdependence project, which aimed to forecast the North–South relationship over a longer time frame, by linking the input–output tables of the countries, and adding the stock and flow of natural and environmental resources to them. That was almost two decades after the 1972 publication of the Club of Rome Report, The Limits to Growth by Donella H. Meadows et al., and the new trend in the late 1980s and early 1990s was to emphasize worldwide approaches to global environmental issues, which eventually led to the 1992 Earth Summit in Rio de Janeiro. From the international political perspective, in the beginning of the 1990s the then UN Secretary General had banned any reference to the New International Economic Order (NIEO) in UN official documents and the UN Secretariat memoranda. The rise of resource nationalism that followed the oil crises in the 1970s, as well as the NIEO Declaration which the UN General Assembly adopted in

xiv Preface

1974 due to the outstanding South–South issues between oil producing and non-oil producing countries, had led to a stronger voice for developing nations while simultaneously encouraging protectionist movements. In line with this trend, the UN Secretariat launched a department to promote “policies on globalization and North–South issues” and started recruiting in-house staff that was well acquainted with this theme. In the early 1990s, at times when the General Assembly was not in session, I was often in the field, supporting the Economic Commission for Africa (ECA in Ethiopia) and the Economic and Social Commission for Asia and the Pacific (ESCAP in Thailand). I became involved in the African Alternative Framework to Structural Adjustment Programmes (AAF-SAP), which allowed me to criticize the IMF’s and World Bank’s structural reforms in Africa and to participate in planning alternative policies which better reflected the actual situation of those nations. The African continent was getting further isolated from the global economy after the failure of industrialization caused by unsuccessful structural adjustments. Africa blamed the developed nations for its economic marginalization from the world economy, but I personally believed that Africa itself needed to make more of an effort to integrate itself into the international economy. In the spring of 1993, I was working for the International Economics Department, Development Economics Vice Presidency (DEC) of the World Bank in Washington, D.C. I wished to work there because a Bretton Woods institution specializing in mid- to long-term development strategies seemed the perfect venue to work on strategies for developing countries’ integration into the world economy. I joined the writers’ group of the Global Economic Prospects and the Developing Countries which the World Bank had started publishing in 1991. This allowed me to analyze, discuss, and participate in policy dialogue on how developing nations could benefit from globalization while minimizing adverse effects and at the same time achieving economic growth. Those days, countries in East Asia (including South East Asia) were trying to achieve financial integration, an integration which was far bigger in size and movement compared to that of trade, while developing their emerging markets on a fast-track basis. Despite there being a risk these nations would fall into financial crisis; every time I picked up this issue, there was no appetite at the World Bank for this discussion. The East Asian Miracle, which was published in 1993 to great fanfare, was touted as the World Bank’s brain trust, and the entire group was aiming to transfer to other developing regions as well this “East Asian growth model,” an export-oriented policy focusing on free trade and foreign capital inflows, in other words a strategy to proactively integrate with the global economy. In this atmosphere, it was taboo to discuss the risks of the East Asian growth system. With no alternative, I decided to participate in an economic TV show in Singapore where I took the opportunity to bring up the subject of the risks that existed in the Asian economy. However, this provoked anger among financial authorities in Malaysia. The Malaysian government sent a letter of protest to the President of the World Bank, and I was reprimanded by my supervisor. The Asian financial crisis then occurred

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within a year and a half. When I visited Washington, D.C. later, after resigning from the World Bank, my then manager economist commented, “Well it was wishful thinking analysis (for you to look forward to only a rosy future for Asia).” It seemed he had completely forgotten that I had been placed on probation for the effort, which was a grave career concern. Back in those days, I was preoccupied with discussions of trade, financial liberalization, and domestic reforms accompanied by (or preceding) liberalization. It was only after I left the World Bank, came back to Japan and started my career at the university that I was able to perceive the “Washington Consensus”—the Bretton Woods doctrine—from a neutral position. From 1999 to 2000, as a Consultant to the Chief Economist of the African Development Bank (AfDB), I was engaged in writing the Millennium Special Edition of the African Development Report on the topic of “Africa’s regional cooperation and integration to the global economy.” Based on my thoughts in the early 1990s that Africa didn’t exert sufficient effort to integrate itself into the world economy, I concentrated on Africa’s original initiatives in integration, while referring to Asia’s growth model and the world trading system that kept on changing under the WTO. Since then, the situation surrounding Africa and the socio-economic environment of Africa itself has turned favorable. Africa is now facing a once in a lifetime opportunity (and unfortunately the last chance within the foreseeable future). Countries in Africa will further deepen their integration with the global economic society with increasing private investment. At least, this is my wish. From 2000 to 2001, I was in Jakarta, Indonesia. The country had been seriously damaged by the Asian Financial Crisis and was in major transition due to forced economic structural changes and resulting social reforms. My role there, as a senior expert for JICA, was to work with the National Development Planning Agency of Indonesia (BAPPENAS) to analyze the national development plans, especially the strategies for reintegration with the world economy. The 1998 Jakarta riot had triggered many (foreign) investors to withdraw from the country, and Indonesia was desperately striving to build a new system amid a situation in which the economy was not recovering easily. The first Bahasa Indonesia I learnt was “Ada demonstrasi, hari ini?” meaning “Is there any demonstration somewhere today?” I had to either avoid or weave through a number of demonstrations before I could safely reach my office. The benefits that globalization had brought to Indonesia through the East Asian growth model had now been erased (whether temporarily or not) by the financial crisis which was attributable to globalization. It takes a long time to achieve economic reform that accompanies social changes. Further, the cost of such reform often affects the socially vulnerable. It was in the autumn of 2008 when another financial crisis occurred. I was in the rural area of Chiang Mai, in the northern part of Thailand, the country where the Asian financial crisis started in 1997, with around 30 students from the Graduate School of International Development (GSID), Nagoya University, where

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I worked as professor and director of the Economic Development Policy and Management Program. We were spending three weeks there to carry out fieldwork training for the regional development of developing countries. The US banking crisis, with its flashpoint in subprime housing loans, spread widely after being triggered by the bankruptcy of Lehman Brothers, eventually turning into another global financial crisis. Again, many developing nations became indirect victims, suffering from stagnating export markets, spiking prices for imports— especially food supplies, and shrinking external development finance, or in other words, cuts in official development aid and private capital inflows. With the mounting Current Account Deficit as a result of excess investment and expenditures over and above its savings and income, the US economy continued to attract money even from the developing countries, and acted as a strong financial intermediary for the world economy. However, the subprime crisis and Lehman ushered in the collapse of this US financial intermediation model, and the steady decline of the leverage ratio in the financial brokerage field. With no doubt, the globalization trend was reaching a turning point: there was a realization that this globalization was actually an “Americanization” deeply rooted in the proliferation of Neoliberalism, which combines an overly US-centric global economic system, “Market fundamentalism” backed by the “Neoclassical economics,” and “democracy.” As represented by the rise of emerging countries in the G20, the multipolarizing global society will have to (1) re-acknowledge the role of governments, and (2) build and rebuild various and distinct systems, including financial ones, as well as the international trading framework for more equitable integration. My relationship with international economic development and international development and cooperation work under globalization continues. Economic globalization keeps on evolving (as do all of the other facets of globalization) with endless emergence of new phenomena such as the rise of BRICS, the price hike of resources, the involvement of developing countries in global environmental issues, and the introduction of new phases. Fortunately, mankind has learnt a great deal, both from the optimistic views of the fast-paced globalization that happened between the end of the 1980s to the mid-1990s, and from the pessimistic viewpoints of the turbulent globalization or the anti-globalism movements that occurred from the late 1990s and continue today, with movements such as Occupy Wall Street that have been initiated in the very seat of globalization in the U.S. We discovered that globalization progresses not only in the field of economy, but also in various areas like politics, culture, institution, and ideology, and that these factors are related closely. Today, with our trained eyes, we hope to be able to take hold of this moving image of globalization and discuss the future orientation of international development that will have to evolve together with it. The late Gerald M. Meier, an Honorary Professor at Stanford University, whom I always regard as my mentor on development ideology and the concepts of development of the developing world, would always say “international

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development studies require an interdisciplinary approach as development has multifaceted aspects that keep on changing and need to be handled and managed in multidimensional ways.” I was even lost trying to understand development issues through a single field of study, which was economics. I asked Prof. Meier how I would be able to make an interdisciplinary approach. “Stretch your arms and legs, join hands together with researchers of other study areas and walk straight toward it as an interdisciplinary team,” he responded to me. Political scientist and public administration researcher, Manfred B. Steger, quotes an ancient Buddhist fable that describes blind scholars who come across an elephant and makes the following analogy. “The ongoing academic quarrel over which dimension contains the essence of globalization represents a postmodern version of the parable of the blind men and the elephant” (Steger 2003, p. 14). In short, when the visually impaired scholars touch different parts of an elephant, they judge the elephant based on their personal impression, clinging to each of their own perspectives. It is foolish to try to imagine the overall elephant just by touching a single part, let alone “understand” globalization, which is in a constant state of moving, growing, and changing. In order to confront the issues of “globalization and development,” we must pool our knowledge and perspectives to adequately comprehend globalization in all of its aspects, and understand how each phase and/or mutual interaction between the various aspects affect the development of developing nations. Moreover, we have to take the individual country’s history of development into account, as that deeply influences the future development trajectory. For the development of developing countries under globalization, it is essential to understand the expanding mechanisms of the domestic and international economic gaps that are inter-linked and have become a multi-layered process. Without deliberate and well-informed efforts, economic growth that leads to poverty reduction (i.e., pro-poor growth) cannot be achieved, as the trickle-down stops with the upper classes. International trade theory and theories of international capital flows stress that international economic integration brings about symmetrical effects and phenomena to the developed and developing nations; thus, it will enable poverty reduction by mainly benefiting the (less skilled) laborers in developing countries. Numerous empirical studies agreed that economic integration contributes to poverty reduction on the basis that it accelerates growth “on average,” while being neutral to the distribution of benefits, again “on average.” However, in reality, there exist a number of “dispersions” in this “average” relationship, both from transnational and chronological aspects. This implies that there are countries in which integration to the global economy does not bring growth. Even if it does produce growth, it does not lead to poverty reduction due to inequality in income distribution and the uneven spatial distribution of industry. Hence, this book, as an outcome of international joint research projects, intends to elaborate a “cross-national study” on the “interstate dispersion” of the tripronged impact (growth, inequality, and poverty) that international economic integration delivers to the economies of the developing countries, along with

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some specific factors that determine the outcome in each nation (such as socioeconomic institutions and policy packages). The ongoing process of globalization involves three major currents of political, economic, and cultural integration. It has also been propelled by four undercurrents in the struggle and integration of (1) ideology, (2) human beings, (3) information, and (4) institutions. Given this multi-layered process of globalization, this research examines “poverty” not only on the basis of economic indicators such as income and expenditures but also from the viewpoints of “multi-dimensional poverty (education, health, environment, etc.),” “subjective well-being,” and “happiness” of the people under consideration. At the end, this book introduces diversified development paradigms under globalization for the post-MDGs (Millennium Development Goals) era. It is presented as a rational evolution from the hegemony of the “Neoliberalism” that has dominated the past couple of decades and motivated current MDG efforts. This work is intended to provide a comprehensive and balanced reference that offers policy makers, researchers, and students in the international development cooperation community a guideline toward post-MDG development strategies and paradigms under a globalized world economy. This book also captures key findings from the following two international joint research projects supported by the Japan Society for the Promotion of Science ( JSPS): 1.

2.

“Controlling the Impact of Globalization on the Poverty-Growth-Inequality Triangle: An International Comparative Study” (2010–2014 JSPS Grants-inAid for Scientific Research: Kiban A (Class A) International Joint Research Project); “Development and Happiness: An Inquiry into the Diversification and Endogenization of the Goals of Development” (2011–2014 JSPS Grants-inAid for Scientific Research: Challenging Exploratory Research Project).

It was also supported, at its compilation stage, by an international joint research fund provided by the Heiwa Nakajima Foundation. The chapters are written by an international selection of authors drawn from Japan, other parts of Asia such as Bhutan, China, Indonesia, Pakistan, Thailand, and Vietnam, and two countries from Africa, the Democratic Republic of Congo (DRC) and Ghana. The contributors include established researchers and professors from Nagoya University, Nagoya City University, Tsukuba University ( Japan), Shanghai Institute of Foreign Trade (China), University of Indonesia, Indonesian Institute of Sciences (Indonesia), Chulalongkorn University (Thailand), Vietnam National University (Vietnam), University of Ghana (Ghana), and University of Bahrain (Bahrain). The contributors also include established researchers and policy makers from the Centre for Bhutan Studies (Bhutan) and the National Economic and Social Development Board (Thailand). They are experts/designers of the Gross National Happiness and Self-sufficient Economy (Green and Happy Society) development paradigms. From the National Development Planning Agency

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(BAPPENAS) of Indonesia, researchers and development planners who deal with bilateral economic cooperation and decentralization initiatives contributed. In order to present the “Leading Issues in Development with Globalization” in a balanced manner, to identify differences and commonalities among “Country Experiences” in development with globalization, and to introduce diversified development paradigms with forward-looking discussions “In Search of a New Development Paradigm” for the post-MDGs era, this publication will consist of three volumes and four main parts.

Volume I: Leading Issues in Development with Globalization Part I has an introductory chapter on the evolution and facets of globalization, and challenges we face in our development efforts under globalization. Another chapter presents the stocktaking of the earlier empirical studies on the impacts of globalization. It also shows the results/findings of our original panel studies. What do we really know about the impacts of globalization? Here, the poverty–growth– inequality (P-G-I) triangle is used as our research framework, and it is tested under the ongoing process of globalization. Part II collects thematic and issue-oriented discussions on the key facets of globalization, including global governance, multi-national corporations (MNCs), and foreign direct investment (FDI) in globalization, globalization and agriculture, global environmental management, FDI and environmental management, global migration, global development cooperation and aid effectiveness, globalization and conflicts, and modeling analyses of global interdependence.

Volume II: Country Experiences Part III presents the country case studies of Bhutan, China, Indonesia, Japan, Thailand, Vietnam, and Ghana, with their respective experiences of development under globalization. Looking into commonalities and differences in their experiences and primary factors underlying their different outcomes, readers will be able to identify key elements and agendas in successful development efforts under globalization. Again, the P-G-I triangle under globalization is used as a common framework for our case analyses. For the African continent, in addition to the Ghanaian case study, another chapter describes the overall African experience under globalization, reflecting the recent emergence of Africa as a global target of investment. All country case studies in Part III are compiled and analyzed by indigenous researchers who have a profound understanding of the local history, and political, economic, and cultural backgrounds.

Volume III: In Search of a New Development Paradigm Part IV consists of descriptive ideological chapters on emerging and existing development paradigms, and chapters with empirical analyses on “Happiness” and

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“Subjective Well-being” as new and expanding targets of development for the post-MDGs era. The inspirational development of Gross National Happiness (GNH) in Bhutan as an alternative to the Gross Domestic Product (GDP) is introduced. Thailand’s unique development paradigm of Sufficiency Economy and a supporting tool Green and Happiness Index are also introduced. After its fast rise to the world’s second largest economy, China’s future course of development is contemplated. Absolute, relative, and subjective measurements of multifaceted poverty are developed and applied to an Indonesian household survey data. A development paradigm with decentralization is presented by an Indonesian government development planner. As a new paradigm for development finance, an expert in Islamic finance presents characteristics and potential roles of Islamic finance. A development paradigm for the “Extremely Poor” is discussed and analyzed using Ghanaian household survey data. Africa’s quest for its own development paradigm(s) from the legacy of colonization is reviewed with an eye to the future. Development paradigms without development, or without sustained economic growth, are analyzed for Latin America. The concluding chapter presents a history/evolution of development paradigms in the global development cooperation community after WWII, and then offers a glimpse into new development paradigms for the post-MDGs era, under a globalized, yet diversified world, referencing imaginative contributions from many parts of the world. The book’s intended readership includes the following:

• • •

Policy makers and practitioners in the international development community such as the governments (and aid-related agencies) of developed and developing countries, international organizations, NGOs, and other civil-society groups. Academics and students seeking well-balanced and comprehensive references to the impacts of globalization on development and development paradigms. Established researchers seeking for a single repository on the evolution of globalization and development paradigms, with a balanced stock of diversified concepts/ideologies/paradigms, rigorous empirics (systematic presentation of facts), and country case studies.

Ms. Lam Yong Ling, Commissioning Editor, Taylor & Francis Asia Pacific (Routledge, Singapore) and her assistant, Ms. Aletheia Heah, have devoted all their passion to this work in cooperation with me from planning, creating, and including up to publication of this book. On behalf of my team, I would like to express my deep gratitude to them. My special thanks go to Dr. Phanida Roidoung, Dr. Yumeka Hirano, and Dr. Carlos A. Mendez Guerra, my Research Assistants for this project, who helped in editing the work; Yumeka and Carlos also participated as writers of this book. My thanks also go to others who served as Research Assistants during the course of this research project: Dr. Eric Osei-Assibey, Dr. Teguh Dartanto, Dr. Zhao Ling, Ms. Panisa Vishuphong, and Mr. Sai Seng

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Sai, Eric Teguh, and Zhao Ling also contributed chapters to this book as professors in their home countries. I would also like to express my sincere appreciation to Ms. Yuria Elvinia, Dr. Jose Elvinia, Ms. Debra J. Saito, and Dr. Francis Peddie for translating some of the Japanese manuscripts into English and/or proofreading English drafts. Administrative assistance provided by Ms. Yuko Takahashi is also acknowledged. On a personal note, I wish to express my gratitude to my wife Mikako, who always supports me on both good and bad days. August 2014 Shigeru T. Otsubo

Reference Steger, M. B. (2003). Globalization: A Very Short Introduction. New York: Oxford University Press.

NOTE ON THE EDITOR

Dr. Shigeru Thomas Otsubo, a Japanese national, is Professor of International Development Economics and Director of the Economic Development Policy & Management Program at the Graduate School of International Development (GSID), Nagoya University, Japan. Prior to his present assignment that started in 1996, he worked as Assistant Professor at the Economics Department of Stanford University, an economic affairs officer at the Department of International Economic and Social Affairs of the United Nations, and as an economist at the International Economics Department, Development Economics Vice Presidency of the World Bank. He also served as a researcher at the Economic Research Institute of the Economic Planning Agency of Japan, a member in the Council of Economic Advisors to Japanese Prime Ministers, an advisor to the National Development Planning Agency of Indonesia (BAPPENAS), a consultant to the chief economist of the African Development Bank for the millennium issue of the African Development Report, and as a visiting fellow for the JICA Research Institute. His recent publications include Leading Issues in Development with Globalization, Introduction to International Development Studies: An Interdisciplinary Approach to Development Studies (2010 JASID Special Award), and numerous journal articles and reports on global and regional economic integration, global crises, and on growth, inequality, and poverty reduction. He holds a Ph.D. in Economics and Operations Research (Stanford University, USA).

NOTES ON CONTRIBUTORS

Akihiro Asakawa is Assistant Professor at the Graduate School of International

Development (GSID) of Nagoya University, Japan. Hikari Ban is Professor at the Faculty of Economics of Kobe Gakuin University,

Japan. Muhammad Cholifihani is the Deputy Director for Balance of Payment

Analysis at National Development Planning Agency of Indonesia (BAPPENAS), Indonesia. Kiyoshi Fujikawa is Professor at the Graduate School of International Develop-

ment (GSID), Nagoya University, Japan. Yumeka Hirano is an Economist at the Office of the Chief Economist, East Asia and Pacific, the World Bank, USA (from Japan). Ken Itakura is Professor at the Faculty of Economics of Nagoya City University,

Japan Hirotsune Kimura is Professor Emeritus at Nagoya University, Japan. Yukiko Nishikawa is Associate Professor at the Graduate School of International Development (GSID) of Nagoya University, Japan. Hiroshi Osada is Professor Emeritus at Nagoya University and Professor, Faculty

of Economics, Teikyo University, Japan

xxiv Notes on contributors

Shigeru Thomas Otsubo is Professor at the Graduate School of International

Development (GSID) of Nagoya University, Japan. Kazuhiko Oyamada is Research Fellow at the Development Studies Center of

Institute of Developing Economies, Japan External Trade Organization (IDEJETRO), Japan. Zamroni Salim is Senior Economic Researcher at Economic Research Center,

Indonesian Institute of Sciences (LIPI), Indonesia.

ACRONYMS AND ABBREVIATIONS

AAF-SAP ABS ADB AEC AfDB AFTA AIDS AIO AJCEP ANDI AoA APEC ARDL ASEAN BAPPENAS BEC BFAL BI BIMSTEC

BIS BLSS BNB BOB BOD BOG

African Alternative Framework to Structural Adjustment Programmes Australian Bureau of Statistics Asian Development Bank ASEAN Economic Community African Development Bank ASEAN Free Trade Area Acquired Immunodeficiency Syndrome Asian International Input-Output Tables ASEAN–Japan Comprehensive Economic Partnership Australian National Development Index Agreement on Agriculture Asia-Pacific Economic Cooperation Autoregressive Distributive Lag Association of Southeast Asian Nations National Development Planning Agency of Indonesia Broad Economic Categories/Classification Bhutan Ferro Alloys Ltd. Bank Indonesia (Central Bank of Indonesia) Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (Bangladesh, India, Myanmar, Sri Lanka, Thailand, Bhutan, and Nepal) Bank for International Settlements Bhutan Living Standard Survey Bhutan National Bank Bank of Bhutan Benefit of Doubt approach Bank of Ghana (Central Bank of Ghana)

xxvi Acronyms and abbreviations

BOP BMIS BPS BRICS BWS CAQ CAR CBS CDO CEPT CES CGE CIF CIT CIW CO2 CNN CPI CPIA CRS CSR CV DAC DCAF DEA DEC DESA DFID DG DGDP DHI DHS DPNBL DRC EAP ECA ECLA ECOWAS EEZ EIA EKC ELQ EPAs

Balance of Payment Bhutan Multiple Indicator Survey Central Statistics Agency of Indonesia Brazil, Russia, India, China, and South Africa Bretton Woods System Consumption Adequacy Question Central African Republic Centre for Bhutan Studies Collateralized Debt Obligation Common Effective Preferential Tariff Constant Elasticity of Substitution Computable General Equilibrium Cost, Insurance, and Freight Corporate Income Tax Canadian Index of Well-being Carbon Dioxide Cable News Network Consumer Price Index Country Policy and Institutional Assessments Creditor Reporting System Corporate Social Responsibility Coefficient of Variation Development Assistance Committee Democratic Control of Armed Forces Data Envelopment Analysis Development Economics Vice Presidency (of the World Bank) Department of Economic and Social Affairs (of the United Nations Secretariat) Department for International Development Democratic Governance GDP deflator Druk Holding and Investments Demography and Household Survey Druk Punjab National Bank Ltd. Democratic Republic of Congo East Asia and the Pacific Economic Commission for Africa (in Ethiopia) Economic Commission for Latin America Economic Community of West African States Exclusive Economic Zone Environmental Impact Assessments Environmental Kuznets Curve Economic Ladder Question Economic Partnership Agreements

Acronyms and abbreviations xxvii

ERP ESCAP EU FAO FDI FfD FOB FRB FSU FTA GATS GATT GDP G/GDP GG GGP GHG GHI GHQ-12 GINI GIO GIPC G-K dollar GLSS GNH GNHCS GNI GNIPC GNP GSI GSS GSSE GSID GTAP GTAP-E GVC G4S G7 G8 G20

Economic Recovery Programme Economic and Social Commission for Asia and the Pacific (in Thailand) European Union Food and Agriculture Organization Foreign Direct Investment Financing for Development Free on Board Federal Reserve Board Former Soviet Union Free Trade Agreement General Agreement on Trade in Services General Agreement on Tariffs and Trade Gross Domestic Product Government Consumption relative to GDP Good Governance Good Governance Plus Green House Gases Green and Happy Index General Health Questionnaire-12 Gini coefficient (measurement of inequality) Global Input-Output Ghana Investment Promotion Center Geary-Khamis dollar Ghana Living Standards Survey Gross National Happiness Gross National Happiness Commission Secretariat Gross National Income Gross National Income per capita Gross National Product Geographical Spread Index Ghana Statistical Service General Services Support Estimate Graduate School of International Development Global Trade Analysis Project Energy-Environmental Version of the GTAP Model Global Value Chain Group for Security Group of Seven (Canada, France, Germany, Italy, Japan, UK, and US, plus EU) Group of Eight (G7 and Russia, plus EU) Group of Twenty (Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, South Korea, Mexico, Russian Federation, Saudi Arabia, South Africa, Turkey, United Kingdom, United States, and the European Union)

xxviii Acronyms and abbreviations

HCR HDI MHT HIES HIPC HIV MoLHR HPAEs ICC ICRG ICRG-C ICRG-E ICRG-F ICRG-P ICT IDE-JETRO IDI IDR IEQ IEWG IEG ILO IMF IMPC IMSF IOM IPCC IPO ISI ISSER ITO ITU IV I-O JICA JPY JSPS KLA KPCS LDCs Lao PDR LPG LSMS

Headcount Ratio Human Development Indicators Medium and High Technology Household Income and Expenditure Survey Heavily Indebted Poor Countries Human Immunodeficiency Virus Ministry of Labour and Human Resources High-Performing Asian Economies International Chamber of Commerce International Country Risk Guide International Country Risk Guide-Composite International Country Risk Guide-Economic International Country Risk Guide-Financial International Country Risk Guide-Political Information and Communication Technology Institute of Developing Economies, Japan External Trade Organization ICT Development Index Indonesian Rupiah Income Evaluation Question International Experts Working Group Independent Evaluation Group International Labour Organization International Monetary Fund Intermediate Parts and Components Intermediate Semi-Finished Goods International Organization for Migration Intergovernmental Panel on Climate Change Initial Public Offering Import-Substitution Industrialization Institute of Statistical Social and Economic Research International Trade Organization International Telecommunication Union Instrumental Variable Input-Output Japan International Cooperation Agency Japanese Yen Japan Society for the Promotion of Science Kosovo Liberation Army Kimberley Process Certification Scheme Least Developed Countries Lao People’s Democratic Republic Liberalization, Privatization and Globalization Living Standards Measurement Study

Acronyms and abbreviations xxix

LTF LTTE MAP MC MDGs MDPI METI MFN MHT MICs MIQ MITI MNEs MNCs MoF MoIC MoLHR MOU MPI MPLA MRIO MSMEs MVA M&A NDP NDPC NESDB NFE NGO NHRDP NICs NIEO NRR NSB NSW NTT NV ODA OECD OECF OffJT OJT OLI

Long-Term Equity fund Liberation Tigers of Tamil Eelam Measures of Australia’s Progress Minerals Commission Millennium Development Goals Multi Dimensional Poverty Index Minister of Economy, Trade and Industry (of Japan) Most Favoured Nation Medium and High Technology Middle Income Countries Minimum Income Question Ministry of Trade and Industry (of Japan) Multinational Enterprises Multinational Corporations Ministry of Finance Ministry of Information and Communication Ministry of Labour and Human Resources Memorandum of Understanding Multidimensional Poverty Index Popular Movement for the Liberation of Angola Multi-Regional Input-Output Micro, Small, and Medium Enterprises Manufacturing Value Added Mergers and Acquisitions New Development Paradigm National Development Planning Commission Office of National Economic and Social Development Board (of Thailand) Non Formal Education Non-governmental Organization National Human Resource Development Policy Newly Industrialized Countries New International Economic Order National Revenue Report National Statistics Bureau National Single Window Nusa Tenggara Timur (East Nusa Tenggara) National Verification Official Development Assistance Organization for Economic Co-operation and Development Overseas Economic Cooperation Fund Off the Job Training On the Job Training Ownership, Location and Internalization

xxx Acronyms and abbreviations

OLS ONET OPEC PAR PD PEA P-G-I PHH Ph.D. PIT PPP PPP PRP PRS PSE RAD-GRK RAN-GRK RASFF RBI REER RIETI RMA RMF RMSPE RNR RPJM RTM RUF R&D SAARC SaB SAFTA SAL SALW SAPs SAPTA SATIS SbA SBI SDGs SEI SET SIDS SIG

Ordinary Least Squares Ordinary National Educational Test Organization of the Petroleum Exporting Countries Poverty Analysis Reports Paris Declaration Political Economy Analysis Poverty-Growth-Inequality Pollution Haven Hypothesis Doctor of Philosophy Personal Income Tax Public-Private Partnership Purchasing Power Parity Poverty-Reduction Paradigm Political Risk Services Producer Support Estimate Regional Action Plan for Greenhouse Gas Emission Reduction National Action Plan for Greenhouse Gas Emission Reduction Rapid Alert System for Food and Feed Reserve Bank of India (Central Bank of India) Real Effective Exchange Rate Research Institute of Economy, Trade and industry Royal Monetary Authority (of Bhutan) Retirement Mutual Fund Root Mean Square Percentage Errors Renewable Natural Resources Medium-term Development Plan in Indonesia Round Table Meeting Revolutionary United Front Research and Development South Asian Association for Regional Cooperation Sourcing-at-Border South Asian Free Trade Area Structural Adjustment Loan Small Arms and Light Weapons Structural Adjustment Programmes SAARC Preferential Trading Arrangement SAARC Agreement on Trade in Services Sourcing-by-Agent State Bank of India Sustainable Development Goals Selected Economic Indicator Stock Exchange of Thailand Small Island Developing States Society for International Development

Acronyms and abbreviations xxxi

SITC SNGs SNS SOSIDER SP SPS SSA SSM SWB TCB TDRI TFP TNCs TOT TPP TSE TSLS T/GDP UDHR UK UN UNCTAD UN DESA UNDP UNHCR UNICEF UNIP UNITA UNSC UN/SG US US$ USSR VLSS VHLSS WDI WTO WW I WW II

Standard International Trade Classification Sub-National Governments Social Networking Services Maluku Steel Mill (in French: Société sidérurgique de Maluku) Special Products Sanitary and Phytosanitary sub-Saharan Africa Special Safeguard Mechanism Subjective Well-being Tourism Council of Bhutan Thailand Development Research Institute Total Factor Productivity Transnational Corporations Terms of Trade Trans-Pacific Partnership (Trans-Pacific Strategic Economic Partnership Agreement) Total Support Estimate Two-Stage Least Squares Trade relative to GDP Universal Declaration of Human Rights United Kingdom United Nations United Nations Conference on Trade and Development Department of Economic and Social Affairs of the United Nations Secretariat United Nations Development Programme United Nations High Commissioner for Refugees United Nations Children’s Fund United States Institute of Peace National Union for the Total Independence of Angola United Nations Security Council Secretary-General of the United Nations United States of America US Dollar Union of Soviet Socialist Republics Vietnam Living Standard Survey Vietnam Household Living Standard Survey World Development Indicators World Trade Organization World War I World War II

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PART I

Development under globalization

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1 LEADING ISSUES IN DEVELOPMENT WITH GLOBALIZATION1 Shigeru Thomas Otsubo

1.1 Prologue The East Asian Miracle published in 1993 by the World Bank produced a great sensation around the globe, evoking discussions on applying the “East Asian development model” to other parts of the world including South Asia, Africa, and Eastern Europe.2 The book introduced the good fundamentals of economic growth observed in the East Asian countries such as the economic institutions and conducive environment that back up a high savings rate and investment, a stable relationship between the government and the market (although the extent of intervention varies), and continuous human resources development established through education. In addition, it suggested the success of development strategies that actively integrate the East Asian economies with the global economy through trade liberalization and induction of foreign capital. Transmission of this successful development model to other developing regions is further suggested. The sustained high economic growth achieved through integration with the global economy was observed as a success in the eight High-Performing Asian Economies (HPAEs) namely Japan, the Four Asian Tigers (Hong Kong, South Korea, Singapore, and Taiwan), and the Asian Newly Industrializing Economies (Indonesia, Malaysia, Thailand) was applied to other countries as follows: China, which continues its high growth through its “Reform and Opening-up” from 1978 onwards; Vietnam which has been showing high economic growth through reform and liberalization, and market economy under the Doi Moi since 1986; and India, which has captured global attention for its high economic growth achieved by the “Liberalization, Privatization and Globalization (LPG)” model following the World Bank and IMF’s Economic Stabilization and Structural Adjustment scheme since 1991. These countries have indeed benefited from globalization of economic activities in their economic development efforts.

4 Shigeru Thomas Otsubo

However, the Asian financial crisis that emerged with Thailand’s abandoning the fixed exchange rate regime in July 1997 involved Indonesia, Philippines, South Korea, Hong Kong, and Malaysia, evolved into Russia’s monetary crisis, and developed into currency crises in Latin American developing nations. Theories such as the “Myth of the East Asian Miracle” emerged, and doubts on economic growth strategy of developing nations under the globalization strategy centered on foreign capital inflow and export promotion were raised.3 Indonesia and South Korea, which were forced to implement fiscal austerity as part of the conditionality of the IMF’s rescue package experienced a riot. However, South Korea carried out rapid economic structural reform which led the private sector to recover international competitiveness and escape from the crisis. Indonesia was obliged not only to make economic reforms but also to make social changes including democracy and decentralization which led the crisis to prolong. There was even a time that the country was believed to have lost the fruit of development and poverty reduction which had been achieved through the efforts of the past three decades.4 The city of Seattle, located along the scenic west coast of the United States, was surrounded by the noise of protest at the end of November 1999. Protesters from around the world gathered in line with the schedule of the World Trade Organization (WTO) ministerial conference to halt further globalization and the negative impact on the (American) workers, (vulnerable) people in the developing nations, and the environment, which were triggered by the WTO discussions. The originally peaceful demonstration evolved into a large-scale riot, which was later named the “Battle in Seattle,” under martial law involving the National Guard as well as the Seattle Police. Not fewer than 40,000 to 50,000 people participated in the so-called N30 (November 30) protest. This day is known as a symbol of the anti-globalization movement that fought against the distortion the “globalization of economic activity” which was associated with the growing multinational corporations (the causal connection needs to be objectively verified, though).5 Simultaneous terrorist acts (9/11) occurred on September 11, 2001, along the East Coast of the United States. A series of hijacked commercial airplanes crashed into the World Trade Center (one of the symbols of globalization) in New York.

FIGURE 1.1

Battle in Seattle

Source: Wikipedia Commons, Photos by J. Narrin (left photo) and by S. Kaiser (right photo) (http://commons.wikimedia.org/wiki/File:Man_Alone_WTO1999_by_J.Narrin.jpg;/File:WTO_ protests_in_Seattle_November_30_1999.jpg)

Leading issues in development with globalization

FIGURE 1.2

5

9/11

Source: Wikimedia Commons (http://commons.wikimedia.org/wiki/Category:9/11)

The entire world was shocked to see on screen how the Twin Towers collapsed. Many people evaluated this tragic incident as a product of friction caused by “globalization of politics and ideology.” In the modern nation-state system based on the Peace of Westphalia, a treaty signed in the mid-seventeenth century to terminate the religious war in Europe, the world is divided into and formed by sovereign states each of which possesses physical territory and nation (citizens). There is no other (i.e., regional or international) authority that supersedes this. A sovereign nation participates in international cooperation only to improve its welfare standards. A propagation of one’s ideology such as a political system and democracy elevates the welfare standards of a country, as it reinforces the social status of that country in global society. The end of the Cold War that started right after World War II was declared by the former USSR President Mikhail S. Gorbachev and the U.S. President George W. Bush at the end of 1989 during the Malta Summit. Ironically, the end of the Cold War triggered the collapse of the balance between the West and the East. Amid the “globalization of politics and ideology,” the doctrine and system called Neoliberalism that centers on free market capitalism (market fundamentalism) and democracy, or “American Hegemony,” rapidly prevailed. This is why many political scientists and ideologists stress that globalization is “Americanization.” 9/11 is said to be a product caused by friction and clash of the expanded American Neoliberalism and the Islamic principles and ideology. The devastating scenes of 9/11 were distributed throughout the world on the CNN global network and gave people a big shock. Later in October 2001, amid the “war against terrorism” led by the U.S. and its allies, Al Jazeera, a TV broadcaster based in Qatar, broadcast a video of Mr. Osama bin Laden talking to the world from (allegedly) a cave in the mountains in Afghanistan under the Taliban. The fact that Mr. Osama bin Laden (believed to be) a leading rebel against the globalization led by the American Hegemony, made use of the “globalization of information” to disseminate his protest, forced the world to be aware of the importance of “information strategy under globalization.”

6 Shigeru Thomas Otsubo

This author/editor studied and worked for universities and international organizations throughout his 15-year stay in the United States. English, which is used as a means of communication there was not necessarily the standardized fluent English but was more of English with an accent on the speaker’s mother tongue (including that of the author). Classmates and colleagues were composed of people with diverse backgrounds from around the globe who spread widely to different areas within a couple of years’ time. The Development Management under Globalization, a course that the author offers at the Graduate School of International Development of Nagoya University, has had students from not less than 30 nationalities within a few years’ span. The writer’s sons who were born during the family’s stay in the U.S. received local education in English enriched in logical thinking and research methods that has made them learn to understand that different people or ethnic groups have different logical thinking methods and accept that fact naturally. Later on when the family moved (migrated?) to Japan, the local public schools in the neighborhood rejected them as “maverick outsiders.” Luckily, the children were accepted in one of the few schools opened for overseas returnees that provide education with value placed on individuality. Aichi Prefecture, where the author is currently residing, is Japan’s leading prefecture in terms of the number of foreign residents and ratio of foreign workers. It will not take so long in the future until Japan, a country facing aging issues, will be forced to open its labor market to non-Japanese residents. The Aichi prefectural office has launched a new policy for globalization and multicultural coexistence of the area, in accordance with its mid-term vision study, the Aichi 2025, which the author served in the council of advisers.6 “Globalization of human resources” has already developed at full scale in the U.S. and Europe. This globalization is gradually spreading to Japan, a country that has been known for long to be closed towards foreign labor.7 The advancement of globalization has homogenized the world’s cultures and values. Some people warn that in this situation each country’s or ethnic group’s unique tradition and culture are disappearing. Others say that, amid this globalization, localization that transforms global public goods and knowledge into something original and unique, or in other words “glocalization,” brings about the rise of unique culture and values despite the changes made to the originals. Meanwhile, Francis Fukuyama, a social theorist known for The End of History and the Last Man considers global homogenization of cultures and values, the expansion of liberal democracy and free market capitalism as something desirable (Fukuyama, 1992). He asserts that “liberal democracy” may constitute the “end point of mankind’s ideological evolution,” and thus the “end of history” (Fukuyama, 1992, p. xi). It is useful to think about the role the Internet, a means of communication dominated by English, plays in the global society.8 Along with the global expansion of the Internet, we should not forget that McDonald’s represents the “globalization of culture” and “cultural imperialism.”9 Thomas L. Friedman, a journalist (for New York Times) who has received the Pulitzer Prize three times, proposes the Golden Arches Theory of Conflict Prevention in one of his books The Lexus and

Leading issues in development with globalization

7

the Olive Tree (Friedman, 2000, pp. 248–250), which states that “no two countries that both had McDonald’s had fought a war against each other since each got its McDonald’s.” Friedman postulates that “when a country reached the level of economic development where it had a middle class big enough to support a McDonald’s network, it became a McDonald’s country.” “And people in McDonald’s countries didn’t like to fight wars anymore.” While verifying the theory, he states that “using McDonald’s as a metaphor,” in trying to make the point: “today’s version of globalization significantly raises the costs of countries using war as a means to pursue honor, react to fears or advance their interests.” Thus, even though “globalization does not end geopolitics,” “it does affect it.”10 Perhaps the theory tries to clarify that homogenization of consumer culture lined up with economic development or income growth brings about peace. In the old days, when I took my family for a car trip in the U.S., we had to make a pit stop every time the M-shaped arch of McDonald’s came into our sight. The family’s favorite was the Teriyaki burger; we only got to know after going back to our home country that the origin of this burger was Japan.11 As of early 2014, there were approximately 34,000 McDonald’s shops in 118 countries around the world, serving some 69 million people each day, and yet the number of branches keeps on growing. Hamburgers are also served in Indonesia, where citizens do not eat pork, and even in India, where many people do not eat beef. To be safe, McDonald’s in Indonesia clearly indicates that their products are “chicken” burgers. Meanwhile in India there are hamburgers for both vegetarians and non-vegetarians. For the non-vegetarian menu, it states that no pork or beef is used. In addition to the local curry taste burgers, Chinese-style and Mexican-style hamburgers are also available. In short, the McDonald’s product has become globalized, then localized to fit each country’s situation and demand, then globalized again. Following the same logic, Thomas Friedman proposed the Dell Theory of Conflict Prevention in The World Is Flat.12 As a result of clarifying the development, manufacturing, and distribution process of his own Dell laptop computer in detail, Friedman found out that the number of companies involved in the supply chain of the computer reached 400 from North America, Europe, and Asia. From this fact, he proposes that “no two countries that are both part of a major global supply chain, like Dell’s, will ever fight a war against each other as long as they are both

FIGURE 1.3

McDonald’s around the World

Sources: McDonald’s India HP; Photo by Faisal

8 Shigeru Thomas Otsubo

part of the same global supply chain” (Friedman 2006, p. 587). When the economic interdependence strengthens in line with the growing global production and distribution network of multinational corporations, it creates a force to prevent wars. In other words, if globalization of economic activities brings about peace, setting aside the tragic fact that human beings faced in the 9/11, it is a blessing. Apart from the theories to prevent conflict, it is really interesting to know that daily necessities, including food and clothes up to industrial products like computers, pass through various companies and workers of different countries before they reach the consumer or end user. In the summer of 2008, when the Japanese version of Globalization and Development was compiled, the author was staying in the baking hot city of Nagoya observing many cities across Japan recording “tropical days” with maximum temperatures exceeding 30 degrees Celsius. Ever since April 2007, a new definition called “extremely hot days,” referring to a day with a maximum temperature of not less than 35 degrees Celsius, had been established in Japan. By then, it had become normal to hear the term “unusual” every time the weather forecast or weather news is broadcasted. According to the long-term forecast announced by the National Institute for Environmental Studies, Center for Climate System Research, University of Tokyo, and the Japan Agency for Marine-Earth Science and Technology, the number of extremely hot days will increase by 60 days annually between 2010 and 2030, and later on will rapidly increase, reaching up to 150 days annually by the end of the century; there were only around 40 days annual of extremely hot days until 2000.13 It seems that global warming has reached an extent that human beings notice it with their eyes and skin. In early 2014, when we were compiling the English version of Globalization and Development, the world was chilled by a big cold wave. It snowed in Egypt! Several years ago, the author visited Madinaty, an expensive residential development in the desert outside Cairo, in conjunction with some activities related to the Egypt-Japan Development Forum. The city was covered with snow! Many said it was the first time in over 100 years that it snowed this much in the Cairo area. The weather in New York City recorded the lowest temperature for the month of January. In Europe, a big chill was followed by cherry blossom. The northern areas of Japan were hit by historically heavy snowfalls. And such strange weather conditions continues. Researchers have already started to show the causal relationships between global warming and global chilling. The 4th Assessment Report issued in 2007 by the United Nations’ Intergovernmental Panel on Climate Change (IPCC) warns that the impact of global warming on the socioeconomy has accelerated quicker than expected.14 Reducing emissions such as CO2 (carbon dioxide) has become a serious task that needs to be tackled immediately. Global warming and other environmental issues are intrinsically a “global” issue. In this book, it should be considered as “globalization and environment” or “globalization of the countermeasures against environmental problems” rather than “globalization of environmental problems.” The World Bank started the World Bank Seminar Series called “Global Issues for Global Citizens” from 2006 using “globalization of information,” in short, through a TV conference system to deliver lectures to universities

Leading issues in development with globalization

FIGURE 1.4

9

The sinking Tuvalu

Source: Website of the South Pacific Islands Project of an international environmental NGO FoE Japan (http://www.foejapan.org/pacific/index.html)

and graduate schools in Europe and Asia. The Graduate School of International Development, Nagoya University, also participates in this global TV conference. In this course, global warming issues are discussed as a borderless task, along with issues concerning infectious disease such as the HIV (Bhargava, 2006). Further approaches on a global level and international cooperation have been long expected.

1.2 What is globalization? The previous section aimed to motivate readers to move through the book, while demonstrating the wide aspects of globalization which cannot be completely covered as well as the factors that this book intends to present and analyze with regard to the leading issues of globalization from a perspective of “globalization and development of the developing nations” and “international development under globalization.” The identification and analyses of these related phenomena in development under globalization will eventually take us to discussions in the search of new development paradigms in the last part of this book. When did we start to hear the term globalization or globalized? As far as I am concerned, the term globalization was not mentioned in academic books or discussions at international organizations until the end of the 1980s. This word came out of nowhere, and could be heard all over the world by the beginning of the 1990s. Until then, the term internationalization had been swaggering around. This book does not aim to provide a unified definition of “globalization.” However, the author (the editor of this book) is an economist (in the field of development economics and international economics), thus, the book intends to center on the area of international development economics while expanding its field with an interdisciplinary team composed of scholars specialized in various study areas. Therefore, the following sections explain the historical view and current situation of the “globalization of economic activities” from the viewpoint of an economist. Before bringing up the leading issues of “globalization and development,” it also introduces the “definition of globalization” proposed by researchers of other disciplines (academic fields).

10 Shigeru Thomas Otsubo

Manfred B. Steger, a scholar in political science and public administration, defines globalization in one of his best-selling introductory books Globalization: A Very Short Introduction as follows (Steger, 2003, p. 13): Globalization refers to a multidimensional set of social processes that create, multiply, stretch, and intensify worldwide social interdependencies and exchanges while at the same time fostering in people a growing awareness of deepening connections between the local and the distant. Sociologists Robin Cohen and Paul Kennedy quote the definition of Martin Albrow that globalization refers “to all those processes by which the peoples of the world are incorporated into a single society, global society” (Albrow, 1996, p. 9) in their publication Global Sociology, while suggesting that globalization is “best understood as a set of mutually reinforcing transformations that are occurring more or less simultaneously.” They suggest that we imagine “a number of threads being woven into a length of multicoloured fabric.” “Once woven together it would be impossible to assign a special role to each thread {. . .}” Moreover, they assert that, at least, the following six identifiable threads are being woven to form the cloth of globalization (Cohen and Kennedy, 2000, p. 24):

• • • • • •

changing concepts of space and time an increasing volume of cultural interactions the commonality of problems facing all the world’s inhabitants growing interconnections and interdependencies a network of increasingly powerful transnational actors and organizations the synchronization of all the dimensions involved in globalization.

Anthony Giddens, a sociologist with a number of publications on globalization and evaluated as “an intellectual powerhouse” by the New Yorker, perceives globalization as a trend that has been inevitably generated as a result of thorough modernity, rather than a next generation that follows modernity. Giddens (1991) further states that: Modernity is inherently globalising—this is evident in some of the most basic characteristics of modern institutions, including particularly their disembeddedness and reflexivity. “Globalisation refers essentially to that stretching process, in so far as the modes of connection between different social contexts or regions become networked across the earth’s surface as a whole” (pp. 63–64).15 In Runaway World: How Globalisation is Reshaping Our Lives, another work which was written a decade later, Giddens states about globalization that “Given its sudden popularity, we shouldn’t be surprised that the meaning of the notion isn’t always clear, or that an intellectual reaction has set in against it,” while stressing

Leading issues in development with globalization

11

that “globalisation has something to do with the thesis that we now all live in one world.” Then, he refers to various definitions of globalization including discourses of the radicals and skeptics (Giddens, 2002, p. 7). Perhaps, this reflects the fact that the state and process of globalization had become increasingly diversified and multi-layered during that decade. Susan George, an activist and theoretical leader in the anti-globalization civil movement who has published global best sellers such as How the Other Half Dies: The Real Reasons for World Hunger, and The Debt Boomerang, defines globalization in La Mondialisation Libérale, which is composed of a discussion with Martin Wolf, a former World Bank economist as follows: What I mean by globalization is that it is always led or boosted by giant multinational corporations, thus it is like a machine that takes the wealth and power to the upper segments of the social class, or a machine that grabs all the good parts in various fields while abandoning the remaining. (George and Wolf, 2002)16 George also quotes, as if to confirm the statement, the definition of Percy Barnevik, former president of ABB (ASEA-Brown Boveri) a Swiss-Swedish major joint venture corporation and an internationally known business person, which goes as follows: For our group company, globalization means to freely receive benefit that allows us to invest, manufacture, purchase and sell goods and services anytime anywhere, while receiving minimum restrictions of labor laws and social agreements. (George and Wolf, 2002) The aforementioned journalist, Thomas Freidman, explains in the introduction of The Lexus and the Olive Tree: Understanding Globalization that “this new era of globalization became the dominant international system at the end of the twentieth century—replacing the Cold War system” (Friedman, 2000, pp. xix–xx). While positioning his own work as “a contribution to the body of literature that has been attempting to define the post-Cold War world” (ibid., p. xx), Friedman picks up the four major works from that cluster including Paul M. Kennedy’s The Rise and Fall of the Great Powers, Francis Fukuyama’s The End of History and the Last Man, various articles and publications of Robert D. Kaplan, and Samuel P. Huntington’s The Clash of Civilizations and the Remaking of World Order. Then, he goes on to criticize them saying that “none of them really captured the postCold War world in any holistic way” (ibid., p. xx). “Each of these works became prominent because they tried to capture in a single catchy thought ‘The One Big Thing,’ the central moving part, the essential motor, that would drive international affairs in the post-Cold War world—either the clash of civilizations, chaos, the decline of empires or the triumph of liberalism” (ibid., p. xxi).

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Then, he states that “if you want to understand the post-Cold War world you have to start by understanding that a new international system has succeeded it—globalization.” “Globalization is not the only thing influencing events in the world today, but to the extent that there is a North Star and a worldwide shaping force, it is this system” (ibid., p. xxi). With regard to the definition of globalization (of economic activity) from the perspective of an economist, the author presents the idea which is slightly old but, yet, retains its validity and was used during those days he was contributing to the World Bank’s Global Economic Prospects and the Developing Countries from 1993 to 1997, as well as committed to strategic analysis and policy dialogue for developing countries to integrate into the global economy, and was used for the World Bank’s board of directors and various presentations held worldwide: Globalization, defined as the integration of production, distribution, and use of goods and services among the economies of the world, has been evolving since the end of World War II. The signs of globalization are manifested at a factor level in the increasing flows of capital and labor, and at the product level in a resounding growth in world trade above and beyond the growth of world output. Further on, the following aspects were used as subjects for analysis and policy dialogue as aspects of economic globalization. The benefits and risks of each aspect that is brought to the developing countries are also included.

• • •

• •

Globalization of goods Globalization of services Benefits: Wider varieties of goods and services have become available at lower prices. Globalization of investment Benefits: Enlarged investment opportunity that results in higher average rate of return, more investment and technology transfer (in the case of foreign direct investment). Risks: Globalization of goods, services and investment often calls for agglomeration (scale economies) that leads to the monopoly of power, and uneven presence of economic activities resulting in both cross-country and regional disparities. Globalization of finance Benefits: More choices for (possible diversification in) development finance. Risks: It creates “hot money” and calls for good governance (by western standards) that often limits policy options in developing countries. Globalization of human resources Benefits: Flows in human resources complement initial endowments and mitigate bottlenecks in the supply of (un)skilled labor. Risk: It accelerates “brain drain.”

Leading issues in development with globalization 13

•

•

•

Globalization of corporate activities Benefits: Global corporate activities connect national economies—consumers and producers alike, create marketing channels, and diffuse technology (technical and managerial). Risks: Large multinational corporations (MNCs) may threaten the sovereignty of developing nations, sometimes inhibiting development of the local corporations and industry. Globalization of information Benefits: Lower cost and timely access to information reduces transaction costs and accelerates the process of catch up. Risk: The undeveloped information infrastructure of developing nations creates “digital divide,” which eventually leads not only to the ex-post gaps in welfare standards, but also the ex-ante gaps in opportunity. Globalization of standards and harmonization Benefits: International harmonization of various standards lower business costs in international trade and overseas economic activities. Risk: International harmonization of standards and institutions often force social changes in developing countries. For example, by imposing democracy, market economy system, the Western style corporate culture, corporate governance, contract system, juridical system, etc.

In this way, researchers involved in analytical studies and policy dialogue of globalization of economic activities have no other choice but to directly or indirectly (as environmental factors) work with globalization and harmonization of the social system and institutions that include not only the economic phenomena which can be evaluated technically and objectively, but also democracy, market mechanism and global, regional, and local governance. There is no end to the discussions of the definition of globalization. In addition, the process and status change of globalization, as introduced in the previous section, continues to diversify and becomes multi-dimensional and multi-layered. Given this situation, the author has attempted to list the “facets of globalization” as follows.

• • •

Globalization of politics A process that enhances political mutual dependence associated with a sovereign nation going beyond the nation’s framework and developing regional and global governance. Globalization of economy A process in which mutual dependence is strengthened through economic activities’ expansion and deepening of production, distribution, and consumption network at a broader and global level. Globalization of culture The complex process between homogenization and assimilation of culture at a global scale, and the process of differentiation and localization of such culture within the social transformation process unique to each country.

14 Shigeru Thomas Otsubo

Beneath these three major currents, the following are four undercurrents that are reciprocal with these major trends.

• • • •

Globalization of ideology The transmission process of social norms and philosophy including the Neoliberalism, centered on free market capitalism (market fundamentalism) and democracy, and the opposing “new protectionism” and “new nationalism.” Globalization of human beings A process in which the “nation-state” system changes through enhanced international flux of human resources (labor force and intelligence) and formation of people’s life cycle that goes beyond the state. Globalization of information These are information aspects that have become the world’s “public goods” through the development of broad media such as the Internet and CNN, and the significant cost reduction in obtaining information. Globalization of institutions A process in which the institutions that exist in each sovereign nation change targeting to create a supranational harmony in line with the expanded flow of goods, services, funds, human resources, and information on a global level.

This is how the author suggests understanding the facets of globalization. Amid the era of globalization, human beings have to tackle environmental issues, population issues (the population explosion in the twentieth century and decreasing population and aging in the twenty-first century), infectious diseases, and so on, as global issues. The development of developing countries and international development cooperation, which focus on approaches toward poverty issues, a major problem that human beings could not solve in the twentieth century, are indeed part of the global issues that the international society under globalization faces. This is the main reason why “globalization and development” need to be dealt with from this perspective.

1.3 Progress status of globalization 1.3.1 Historical overview of globalization As mentioned earlier, the term “globalization” entered the limelight only after the 1990s. However, the historical phenomenon of globalization itself is old if we take into account the interstate trade and the (regional) expansion of financial transactions that backed up such trade, including the domination of the Mediterranean trade by the Phoenicians dating back to the 1200s bce up to the 680s, trade between the West and the East through the Silk Road that lasted until the 130s bce,17 and the extended trade from Europe to Asia and the Americas from the fifteenth century to the beginning of the seventeenth century during the Age of Discovery.

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15

Let us look back on history to clearly show how globalization the world faces today differs from the previous globalization. Table 1.1 shows a summary of the history starting from the Age of Discovery up to the end of World War II, the global economic integration process.18 The ideology that backed up economic activities in Europe (the then developed countries) between the end of the sixteenth century and the eighteenth century was “Mercantilism.” This ideology aimed to reserve national wealth by accumulating gold and silver, the then payment currency, with the belief that making more exports compared to imports will lead the country to become stronger; thus, the governments broadly controlled their own industry and trade. The incentive of the globalization of economic activity was based on initial accumulation of industrial capital. To this end, the following factors were imposed:

• •

protection of domestic industry (especially the textile and metal industries) and development of foreign market and colonies (to secure raw materials such as cotton and precious metals).

Mercantilism, the international trade system of the time, was followed by expansion of protectionism and colonial trading system. England and the Netherlands each established the East India Company in 1600 and 1602, respectively, to extend their trade business in the East.19 The international monetary system shifted from the bimetallism of gold and silver to the gold standard system. Eventually, in the late eighteenth century, the Industrial Revolution that had spread from England to Europe encouraged the start of factory labor and mass production, and established capitalism. An even wider product market with freer trade was required, along with the enhanced capital accumulation and competitiveness in Europe. The following elements were needed for the establishment of European capitalism (and for the rise of the American colony):

• • •

secure trading posts and markets secure plantation colonies supply of slave labor.

With the establishment and development of the colonial system, the international trading system was formed under the colonial trading system of free trade, while the international financial system was stablized under the gold standard system. In terms of international migration, the following phenomena can be picked up: the settlement from Europe to the American continent after the Age of Discovery (the New World), immigrants that continued to enter even after American independence, and the forced migration of Africans to the North and South American colonies brought in as part of the slave trade initiated by Spain in the early sixteenth century, and followed mainly by the Netherlands, France, and England until the beginning of the nineteenth century. The flow of international

16 Shigeru Thomas Otsubo TABLE 1.1 Globalization and the evolution of global economic systems

(from the end of the Age of Discovery to WWII) TIME

late 16th C. (– mid 19th C.) (U.K.– Europe)

latter half of 18th C.

late 18th C. – 19th C.

The Wealth of Nations, 1776 French Revolution, 1789 Declaration of Independence by America, 1776 Global Political/ Economic System

Mercantilism Mercantile System early European Imperialism (15th C. – 18th C.)

Industrial Revolution (1760s– in U.K., 1830s– in U.S.)

Capitalism Colonialism Colonial System (Europeans vs. Asia, Africa, America(s)) 1815–1880 status quo (Free Trade Imperialism)

Underlying Incentives

For primitive accumulation of domestic manufacturing capital. 1) Protections for domestic manufactures (textiles, metal products). 2) Cultivation of foreign markets and colonies. (for inputs and precious metals)

Invention of spinning machine to compete with cotton products imported from India. mass production → needs markets → freer trade

For establishiment of Capitalism in Europe. 1) Trading posts. (15th C.– Portugal) 2) Plantation colony. (17–18th C. Holland & GB) 3) Supply of slave labor. (early 16th C. – Spain) (17th C. – Holland, France, GB)

International Mercantile Trade System Trading Protectionism System East India (Asia, Africa, Americas) Companies, 1600–1774

Colonial Trade under Free Trade Slogan

International From Parallel Standard Financial (silver standard & gold standard w/o fixed System conversion rate between gold and silver) To Bimetallic Standard (with fixed conversion rate) (U.K., 1695; US, 1792, France, 1803)

Gold Standard (U.K. 1816–)

International Migration

Colonization (late 18tn C. – early 20th C.) (UK, other European Powers; later + Russia, US, Japan → Asia, Africa, Americas)

Colonization (15tn C. – late 18th C.) (Portugal, Spain → The East Indies, The Americas)

Slave Trade (Spain: 16th C.–) (Holland, France, UK: 17th C.–early 19th C.) Africa → Colonies in the Americas Exodus of Han Chinese to Southeast Asia Exodus from China triggered (early 17th C.–) (China → Southeast Asia) by Invasion by European Powers (latter half of 19th C.–) (China → Southeast Asia, Americas) Gold Rush Gold Rush (late 17th C.–, Brazil) (19th C., 2nd H.– 20th C., 1st H.) (US, Canada, Australia, S. Africa) Source: Author’s own compilation.

Leading issues in development with globalization 17

TABLE 1.1 (Continued) late 19th C. – early 20th C.

W.W.I 1914 –18

Great Depression 1929.10.24–

W.W.II 1939–45

TIME

Imperialism (monopoly capitalism) Colonialism Colonial System (U.K. Germany, France, Russina, U.S., Japan vs. Asia, Africa, Latin America)

Wartime Regime

Great Depression

Wartime Regime

Global Political/ Economic System

1880–1914 active expansion (full–fledged Imperialism) For investment opportunities of accumulated domestic financial capital. 1) Cultivation of investment markets. (Marx, Lenin) 2) Supply of cheap materials, resources, and foods. 3) Supply of cheap labor. 4) Protected product markets. 5) Military bases.

NY Dow $300s to $50 in 3 years. US unemployment rate up to 25%. Beggar Thy Neighbor Policies (export of unemployment) 1) Higher tariff rates. 2) Devaluation of currency.

Underlying Incentives

Imperial Trade System

Protectionism and Block Trade

International Trading System

Chaotic Global Financial System

International Financial System

Gold Standard (–1914) 1 ounce = $20.67 = 4.247 pound

back to Gold Standard (US, 1919 Japan, 1930)

Colonization (continued)

Exodus from China (continued)

Source: Author’s own compilation.

Jewish Settlement in Palestine (→ Founding of Israel, 1948)

International Migration

18 Shigeru Thomas Otsubo

migration did not end, and the total number of migrants from Europe to the New World is said to have reached 60 million throughout the century until World War I. The total number of African laborers who were forced to migrate under the slave trade is believed to be around 10 million to 20 million. Another big international migration was the massive dislocation of the Han Chinese people to South East Asian countries and the formation of Chinese society that started in the beginning of the seventeenth century after China’s unification by the Manchu people (Qing Dynasty), and the migration of Chinese people in the latter half of the nineteenth century invasion by European powers and who fled to South East Asia and American continents. The gold rush in Brazil from the end of the seventeenth century, the gold rush in the Northern American Rocky Mountains in the latter half of the nineteenth century, other discoveries of gold mines in Australia and South Africa during the same period, also caused international migration. The Jewish migration to the U.S. that rose in the 1930s, along with their migration to Palestine (especially between 1945 and 1949) before and after Israel’s founding (1948), must also be noted. At the end of the nineteenth century, the world reached the maturation of European capitalism. Europe along with Russia, the U.S., and Japan entered the era of rapid expansion of Imperialism under the rise of monopoly capitalism.20 In order to maintain the profit of domestic financial capital accumulated into the monopolist capital of the developed countries and to expand investment opportunities, the following initiatives were needed:

• • • • •

development of overseas investment destination secure cheap raw materials, resources, and food supplies secure cheap labor force expansion of protected product markets secure military bases.

The international trade and investment system was an imperialistic commerce and investment system where mega monopolistic capitals were active; thus, the international finance system was a succession of the gold standard. The first wave of modern globalization is believed to have been between the 1870s and 1914, it was the period when trade, investment, and flow of migration grew under the imperialistic commerce and investment system and the world faced the rise of economic development up to the start of World War I. It was the development of communications and transportation infrastructure, precisely the emergence of telegrams and telephones, development of railways and regular lines of steam vessels, which supported this economic integration. In The Great Illusion, published in 1910 (and revised in 1914) by Norman Angell, later a Nobel laureate for the peace prize, an optimistic discussion was introduced stating that the tightening relationship of mutual economic interdependence in Europe avoids war. This discussion was presented in the midst of the Anglo-German armament confrontation that reflected the then dominant “universal assumption.” “A nation,

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in order to find outlets for expanding population and increasing industry, or simply to ensure the best conditions possible for its people, is necessarily pushed to territorial expansion and the exercise of political force against others” (Angell, 1914, p. vii). He further asserted that “the commerce and industry of a people no longer depend upon the expansion of its political frontiers,” and “military power is socially and economically futile” (ibid., p. viii). Angell further added that “the forces which have brought about the economic futility of military power have also rendered it futile as a means of enforcing a nation’s moral ideals or imposing social institutions upon a conquered people” (ibid., p. ix). John M. Keynes, describing Europe before the War in The Economic Consequences of the Peace, issued in 1920 just after World War I,21 also mentioned that “the inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth,” and “he could at the same moment and by the same means adventure his wealth in the natural resources and new enterprises of any quarter of the world” (Keynes, 1924, p. 9). He went on to say that “the projects and politics of militarism and imperialism, of racial and cultural rivalries, of monopolies, restrictions, and exclusion, which were to play the serpent to this paradise, were little more than the amusements of his daily newspaper, and appeared to exercise almost no influence at all on the ordinary course of social and economic life, the internationalization of which was nearly complete in practice” (ibid., p. 10). Unfortunately, however, World War I was triggered by the fight over colonies between the Triple Entente formed by England, France, and Russia, and the Triple Alliance composed of Germany, Austria, and Hungary, as the “universal assumption” predicted, and it destroyed the so-called “paradise.” Although the world economy improved after the end of World War I, it then faced the Great Depression in 1929. The result of this was:

• •

setting of high import duties currency devaluation war (devaluation and retaliatory devaluations).

In other words, the protective trade under the “beggar-thy-neighbor policy (exporting unemployment)” along with the rise of blocked global trade pushed Germany, Italy, and Japan, countries that ran short of resources without colonies, to colonize other countries, which eventually led mankind to enter into World War II. Amid the wave of globalization today, in the twenty-first century, does the proliferation of Neoliberalism and clash with other ideologies, price hike of natural resources, together with the rise of resource nationalism not imitate the eve of another big World War that human beings (or citizens of particular nations) have started despite benefiting from globalization? This is the time that reinforcement of global governance is strongly called for, which includes the development of institutions that support developing countries in their efforts to benefit from the current process of globalization.

20 Shigeru Thomas Otsubo TABLE 1.2 Trend of trade integration (merchandise trade to GDP ratio, %)

France Germany Japan Netherlands England U.S.A.

1913

1950

1973

1985

1995

2005

2012

35.4 35.1 31.4 103.6 44.7 11.2

21.2 20.1 16.9 70.2 36.0 7.0

29.0 35.2 18.3 80.1 39.3 10.5

38.6 48.3 22.2 100.2 45.3 13.1

37.6 39.1 14.6 92.7 42.8 17.7

45.3 63.2 24.3 120.6 39.2 20.1

47.6 75.1 28.3 161.9 46.4 23.9

Source: Figures for 1913 and up to 1973 were compiled based on Maddison (1987), Table A-23. Rest of the figures were made using World Bank WDI Database (June 2014), http://data.worldbank.org/ indicator/TG.VAL.TOTL.GD.ZS.

When measuring trade dependency (the value of merchandise exports and imports to GDP ratio), as indicated in Table 1.2, it was only after the 1970s that the major developed countries reached the extent of globalization equivalent to that of pre-war times in 1913. From the global point of view, the world economy did not recover the pre-war trade integration standards until the 1980s when many of the developing countries that became independent after World War II escaped the import substitution paradigm and actively worked to become integrated into the world economy.

1.3.2 Progress status of globalization after World War II Table 1.3 summarizes the evolution of post-war globalization and the global economic system. Figure 1.5 indicates how much the world trade (goods and services) and global income have increased in real terms (using constant US$ values). In Figure 1.5 (a), values denominated in 2000 US$ are consistently used for the period 1960–1995, and they are indexed to the starting value (1960 = 100). In Figure 1.5 (b), values denominated in 2005 US$ are consistently used for the period 1978–2011, and they are also indexed (1978 = 100). Figure (a) tells us that during 1960–2005, global trade increased by 15.5 times, while global income grew only by five times. For the more recent period, Figure (b) shows that world trade expanded by six times while world income grew by 2.5 times during 1978–2011. During the same period, exports of goods and services from developing countries as a whole outpaced world trade and expanded by almost eight times.22 The beginning of the post-war global economic system started in July 1944, towards the end of World War II, when the representatives of the Allies gathered in Bretton Woods, in the New Hampshire state of America, and announced the blueprint of the new post-war institution as the Bretton Woods Agreement. This was designed to prevent chaos in the international monetary system caused by the currency devaluation war that triggered the real war, as well as to avoid protectionism and division of the world economy into blocks.23 With the International Bank for Reconstruction and Development (World Bank) and the

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TABLE 1.3 Globalization and the evolution of global economic systems (after WWII) Time

at the end of WWII (1944.7) to early 1970s

early 1970s

1973 –74, 1978–80

Global Political/ Economic System

Breton Woods System (BWS) and Advancement of Globalization

Collapse of the BWS

1st and 2nd Oil Crises

1) Nixon Shock (1971.8) 2) Smithsonian System (1971.12) 3) Fixed to Floating Exchange Rate System (1973.2/3)

1) The 4th Middle-East War OPEC price increase (1973.10; $2.8/barrel to $11) 2) Iranian Revolution (end of 1978 - 1979.2 -) OPEC price increases (1979.6; $14.55/barrel to $23.5) (1980; more than $30/ barrel)

Represetatives from the Uited Nations (the Allies) gathered at Bretton Woods, NH in the United States to build post-war global economic system.

UN Confeence on Human Environment (Stockholm, 1972.6)

3rd Middle East War (1967.6–) 1) US could not maintain $ value, and stopped $-gold conversion. (US$35< gold 1oz.) (depleting stock of gold) 2) G10 to devalue $ and to maintain fixed exchange rates at new levels. ($1 = ¥308, 16.88% revaluation) 1972.6 Pound Crisis 1973.2/3 Another $ Crisis 3) Major developed economies floated their currencies.

1) Oil crises created stagflation in oil importing countries. Inflation in Japan: rB, the capital movement from country B to country A with higher rate of return on capital can be anticipated. With the capital flow from country B to A, the stock of capital in country B decreases, thus, the capital rent increases. On the contrary, the capital stock increases and rent decreases in country A, and, eventually, the capital rent in both countries will be equilibrated at the level of re at point E in the figure. Therefore, a new equilibrium is created and no more inducement for international capital movement exists. Consequently, the capital equivalent to L–K in the figure flows from country B to country A. In the world

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of post capital liberalization, the production volume of consumption goods equivalent to the area of LCEK increases in country A as the total production expands from OAACL to OAAEK, while that in country B the equivalent to the area of KEDL declines as the total production shrinks from OBBDL to OBBEK. Take note that the world’s total production volume of consumption goods (total real world income) has increased by the amount equivalent to the area of triangle CED. This is the reason why international investment (international movement of capital) is called a positive-sum game. The increased portion has been created because the capital L-K, which used to be under a lower marginal productivity state in country B, moved to country A and was used under a higher marginal productivity (with higher rate of return on investment) which produces an extra income. When looking into the income distribution between the two countries under this new equilibrium, it can be said that the real gross “domestic” product (real GDP) equivalent to OAAEK, which has been expanded in country A, includes the portion that accrues to overseas capital, thus, the portion remaining after paying the capital income LGEK to overseas shall be the real gross “national” income (real GNI). This indicates that the real income (real GNI) of country A has increased by the area equivalent to triangle CEG. Thus, in country A, both the real GNI and real GDP have increased. In country B, the real gross “domestic” product (real GDP) has decreased by KEDL (from OBBDL to OBBEK). However, the real gross “national” income (real GNI), which includes the capital income LGEK from overseas, has increased by the amount equivalent to the area of triangle DEG. Thus, in country B, the real GDP decreases, while the real GNI increases. In sum, the total real income (total production volume of consumption goods), which has increased aggregately at the global level based on the total amount equivalent to triangle CED, has been distributed to the country A and B as shown in triangles CEG and DEG, respectively. When focusing on the income distribution in each of the two countries under this new equilibrium, the labor income in country A expands from ACrA to AEre, while that of country B drops from BDrB to BEre. The total capital income of country A has decreased from OALCrA to OALGre (by subtracting the remuneration LGEK to be paid to overseas from OAKEre), whereas the total capital income of country B has increased from OBLDrB to OBLGre (by adding the remuneration LGEK received from overseas to OBKEre). This implies a structure that in country A, as the capital-receiving country, laborers gain while investors lose. On the other hand, in country B, laborers lose while investors gain. This is the basic understanding and explanation of MacDougall’s model of international movement of production factors. Considering this model as a capital flow from country B (developed country) to country A (developing country), the laborers (representing the poor class) in the developing country A shall benefit while lessening the income gap

Globalization and corporate activities 153

with the capitalists (representing the rich class). This is based on two points, as pointed out by Meier (1996), in short, the income redistribution (equivalent to rACGre) from domestic capitalists to domestic laborers and the net increase of real wages (CEG). The reason that this is often not materialized in the developing countries that are the recipients of capital is due to the structure which does not allow income redistribution (equivalent to rACGre), or the net increase of real wages (CEG) to laborers. Studies carried out by MacDougall (1960) deal with general capital flows from overseas and do not necessarily center on foreign direct investment especially made by MNCs or developed countries’ investment to developing nations. Assuming that on top of this model, the production technology and management skills are transferred from developed nations, which is the biggest difference that FDI brings in comparison to other investment flows, then, the host country A’s (developing country) marginal productivity curve changes its curvature (the portion composed of FDI capital will lead the marginal productivity to decline gradually) and/or shifts up (when technology is widely transferred to the industry, the overall marginal productivity curve shifts up). Box 4.2 shows computable general equilibrium (CGE) model simulations of this compound effect. For matters of simplification, it is now assumed that the technology enclosure is inhibited (which actually requires public policies for technology transmission) and, thus, technology improvement is broadly applied. Under this favorable assumption, the marginal productivity curve shifts upward. Readers are suggested to think of the impact caused by the upward shift of the Aa curve in Figure B4.1.1 caused by the movement of capital from country B to country A. Under this situation, an increase of the real income generated for the entire world by the cross-country capital movement is indeed larger. Moreover, an enhanced productivity of capital brought about by the uplifted technology standard in the host country, without any doubt, brings improved rate of return and capital remuneration to capitalists both in the host and the donor countries. Unfortunately, wage payments that have been reduced in the donor country due to capital outflow will be further decreased due to this outflow of technology. However, it is uncertain whether the laborers’ remuneration in the host country increases or decreases (and again, there is room for discussion on public policies). It should also be noted that these simple static analyses do not properly account for even larger dynamic gains from international capital movements. The increase in real income in the host country A supported by technology improvement should expand its demand for country B’s exports. The donor country B should also gain from favorable changes in terms of trade that should be caused by lower import prices as a result of lower production costs in the host country A.

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4.2.2 Empirical analyses of the impact of FDI FDI has two major aspects. One is the “flow” aspect, which is the international movement of capital that targets the use of less-expensive production factors, internalization of the external market for cutting transaction costs, securing superiority in the oligopolistic market, and pursuance of the economies of scale. The other is the “stock” aspect embracing production expansion in the host country brought about by the accumulated capital and further inducement of savings and investment. In addition, FDI often brings about higher productivity in the host country through the transfer of managerial resources such as management know-how and production technology and through access to newer technology embodied in the imported capital goods. These are the key features that indeed make FDI different from other types of investments. This section will pick up a general case to observe the effects on trade and national welfare caused by the transfer of managerial resources through FDI. Managerial resources include knowledge and skills on technology, marketing, sales, and management; thus, when management resources and production technology are transferred through FDI, a technology revolution occurs in the host country. When the host country has comparative advantage in the production of labor-intensive goods, production will expand on the condition that there is technology transfer in the field of labor-intensive production and sales. In such cases, the domestic resources are transferred to the labor-intensive industries; as a result, the export increases and complementary import of capital-intensive goods also grows. However, the terms of trade of the host country worsen, while those of the donor country improve. In this manner, technology transfer for production of goods in which the host country has comparative advantage leads to the expansion of trade and national welfare. There is a debate in the development strategy that, unlike trade liberalization, receiving FDI does not necessarily benefit the host country (which is a developing nation).15 It is believed that there is a risk that overseas investment crowds out domestic investment and domestic corporations. When there is a company in the host country which is in a competing situation with an overseas company expanding its businesses to the host country, there is a risk that the domestic firms will be deprived of the market. However, this argument and phenomenon also occurs when imported products crowd out the import-substituting domestic industries/firms amid the process of trade liberalization. Therefore, the discussion above does not necessarily back up the theory that only FDI, unlike trade liberalization, may not benefit the host country intrinsically. The advantage of the movement of production factors as described in Box 4.1 is a benefit that is secured just like the advantages indicated in the basic theory of trade. The discussion must rather be made on the necessity of “strategically and properly managing” the FDI, while putting focus on the (industrial) structural changes that happen in both the donor and host countries that engage in trade and investment as well as in the impact of income redistribution amid this positive-sum game. In addition, a safety

Globalization and corporate activities 155

net for the “loser” and conformity with the host country’s industrial development strategies must be secured. For example, policies to invite foreign enterprises that may give a monopolized advantage (although it is generally granted only for a limited period) must be avoided, as it will inhibit market participation of other foreign companies as well as the potential domestic corporations. This is the kind of debate that must be carried out. Moreover, as the corporate activities become borderless, what matters is not which company survives, but which industry will develop further (while changing the mixture of overseas and domestic companies) on a sector level. When discussing overall development strategies, it is equally important to address the macro-level impact, including the changes of a country’s overall rate of return on investment, and resulting changes in savings and investment ratios. Micro-level issues such as elimination of certain companies and emergence of frictional unemployment during adjustments must be handled separately by implementing complementary reforms in capital and labor markets, and by providing safety nets such as unemployment insurance and workers’ re-education/re-training. Given these basic ways to understand FDIs in the development context, this section introduces some findings from empirical analyses made on the impact of FDI. When talking about empirical studies on the economic consequences of FDI at the macro level, in other words, the relations between the inflow of FDI, domestic savings and investment, and economic growth, a series of studies conducted by Fry (1993) must be mentioned. According to Fry, FDIs to Latin American countries are often used for filling up the gap (deficit) in the balance of payments. In addition, many of the FDIs are executed in the form of transfer of ownership through capital participation that accompanies privatization of stateowned enterprises. Therefore, it is rather hard for the FDIs to Latin America to expand the production capacity in the host countries. On the contrary, FDI to Asian countries have directly linked to enhance the stock of production capital. It has also been proven that the domestic savings rate and investment rate simultaneously increase in line with the inflow of capital (the “co-financing effect”) in Asia. Similar findings have been observed in estimating investment functions conducted by Agosin and Mayer (2000) on 32 developing countries between 1970 and 1996. In sum, whereas in the Asian region where there was the induction effect of domestic investment, in other words “crowding in” was observed, the opposite phenomenon, or “crowding out,” was pointed out in Latin American countries. Similar researches on this topic stress that FDI does not necessarily induce domestic investment (and, in the worst case, it could even trigger a reduction of the total investment amount); thus, what is essential is to build conducive economic environment in which investment is made.16 In the first place, as Fry (1993) pointed out, in a macroeconomic environment where the top priority is to compensate the large balance of payment deficit, FDI will not bring about the expansion of production capacity. In an environment in which the economic infrastructure is well organized and supply of human resources is secured, FDI creates production expansion and increasing returns on investment, thus inducing

156 Shigeru Thomas Otsubo

further investment and savings, which eventually bring a virtuous circle of higher rate of growth and expanding FDI. Since FDI is fundamentally a microeconomic act of investment by multinational corporations, its technology-enhancement effect must be observed at a micro level (at firm level). Yet, micro empirical studies carried out by Haddad and Harrison (1993), Kokko, Tansini, and Zejan (1996), and Aitken and Harrison (1999) did not show any productivity improvement made through FDI. In fact, the World Bank’s (2001) Global Development Finance 2001 described that the impact of FDI has been verified on a macro-level research represented by an accelerated growth through increase of total investment and improvement in productivity. Does this mean that the effect of FDI is not apparent on a micro level? But, when examined as a total, it shows productivity enhancement. Does it also imply that emphasis be put on the external economy that occurs in sectors and on a macro level (in which small improvement of technology and management skills in each company affect each other positively and create a macro effect)? Moreover, there are a number of studies that call for the necessity of improving the macroeconomic environment so that the FDI impact is clearly observed on a micro level (firm level).17 For example, Borensztein, De Gregorio, and Lee (1998), who noted the crowding out effect of FDI observed in developing countries as a whole, state that domestic investment is induced and growth is accelerated through FDI only when the host country has high-class human resources. Meanwhile, Nair-Reichert and Weinhold (2001) stressed that FDI leads to productivity improvement and accelerated growth only in countries with open economy. Besides, Blomström and Sjoholm (1999) pointed out that, although the ripple effect of enhanced productivity in domestic corporations is not high, a certain amount of productivity growth is observed when a pressure of strong competition is produced through foreign capital participation in the host country’s market. Finally, as introduced in Section 4.1, attention must be paid to the fact that the recent trend of FDI is shifting from the conventional Greenfield FDI, in which companies establish a new production site overseas, to the M&A FDI.18 Calderón, Loayza, and Servén (2004) have made a pioneering study on the differences of economic effect made by these two models of FDI. Using data from 1987 to 2001 on a group of 22 developed nations and another team of 50 developing countries (there is also an analysis conducted only on Latin American nations), an individual empirical analysis was made to compare the results obtained. In developed countries, with a number of M&A model FDIs, the Greenfield investment increases following M&A FDI, while in the developing countries the Greenfield FDI comes first and later on bringing in the M&A FDI. What was common in both the developed and developing world was that the amount of either type of FDI does not increase before economic growth. Rather, there is a mechanism that countries, which have experienced accelerated economic growth, attract more FDI. Summing up all these research results and historical data, it is obvious that the standard set of findings from the discussion on the income convergence can also be

Globalization and corporate activities 157

applied to the debate in this section. In other words, FDIs to developing countries theoretically ought to enhance the real income, yet, do not unconditionally lead to accelerated mid- to long-term growth through improved productivity. Only when various conditions and factors as introduced above are met, FDI creates a positive impact. Here, again, a broad sense of investment-conducive environment and a robust foundation of the supply side are required. In countries that have accomplished enhancement of the supply side, domestic investment becomes active induced by rising rate of return on investment, and this is how the process of growth initiates. By obtaining factors that promote (domestic) investment and initiate a sustained growth, a country can attract FDI. “Under appropriate strategy and management of FDI,” it helps to create long-term growth acceleration through increased domestic investment and technology transfer (productivity increase).

Box 4.2 Applied general equilibrium model analysis of the economic impact of FDI: economic impact of Japan’s FDI to Asian countries Simulation analyses using the GTAP model, a multinational and multisector computable general equilibrium (CGE) global trade model are conducted in order to evaluate the economic consequences of FDIs from Japan to Asian countries, which dramatically increased in the latter half of the 1980s due to the Plaza Accord and the resultant appreciation of the yen. The study focused on the impact both in the donor country and the host country, Japan and Asian countries, respectively, to make assessments consistently and quantitatively both from the macro and micro perspectives. (Refer to Otsubo [1998, 2005] for details.) The majority of existing anti-FDI arguments are either non-economic, represented in the “nationalist” and “dependency” approaches, or, even though based on economic grounds, they are short-term and partial equilibrium discussions such as the “export of employment (import of unemployment)” and “worsening balance of payments” arguments that focus only on the flow aspects of FDIs. FDI is essentially a micro phenomenon, thus, it shall not be responsible for any macro consequences such as the worsening trade balance. The saving–investment imbalance in each country, which is the foundation of balance of payments disequilibrium, is the issue related to the backbone of the long-term national development strategy such as the possibility of creating domestic investment opportunities, which is affected by the demographic changes and socioeconomic institutions. (For details, refer to Otsubo [2005].) This box looks into the mid- to long-term general equilibrium impact, in short, the “stock” impact of FDIs. In concrete, it intends to verify the following: (1) the effect caused by transfer of capital stock from Japan to seven

158 Shigeru Thomas Otsubo

manufacturing sectors (food processing, textile, chemical, metal industries, transport equipment, machine industry, and other manufacturing industries) in nine different economies (China, Hong Kong, Indonesia, Malaysia, Philippines, Singapore, South Korea, Taiwan, and Thailand); (2) the synergetic effect of improved productivity created by the enhanced total factor productivity (improved productivity in the net production function) and higher business efficiency including efficiency gains in procurement of input materials (enhanced productivity in the gross production function) brought about by technology transfer from Japan to its investment destinations in Asia; and (3) the co-finance effect which will be created when the overall rate of return on investment increases due to productivity enhancement and this, in return, induces new and often complementary domestic investment in the host country (this effect has been observed in China and other Asian countries). The simulation design is compiled in Table B4.2.1. In setting the world’s inter-industry input–output structure and the endowments of capital and labor as of 1992 as benchmark, the simulation referred to the relative size of investment from Japan to Asia within the succeeding three years (Table B4.2.2) and dealt with the following cases. For (1) in the table, it assumed that the amount equivalent to 1% of the capital stock in each of the nine Asian countries will be the capital which will be transferred to that country from Japan. For (2) it picked up the cases in which the technology parameter both in the net and gross production functions increased by 1 percent within the seven manufacturing industries that received direct investment. As for 3) it assumed a case in which the same amount of domestic investment as the initial capital transfer is created in each of the targeted manufacturing industries (50–50 joint venture). The simulations were conducted under the following two different market conditions (industrial organizations): a perfectly competitive market (with constant returns to scale) and a monopolistic competition market (with increasing returns to scale). First of all, Table B4.2.3 describes the impact on the world economy of Japan’s foreign direct investment to Asian countries as a whole. The EV (equivalent variation) is an index used in general equilibrium analyses to indicate the variation of the level of welfare. Here, the welfare changes are stated in US dollars. In this table, simulation 3 (or 6) shows only the additional TABLE B4.2.1 Simulation design matrix

(1) Transfer of capital stock (2) Transfer of capital stock and technology (3) Co-finance — joint venture

Source: Compiled by the author.

Perfectly competitive market

Monopolistic competition market (Economies of scale)

Simulation 1 Simulation 2

Simulation 4 Simulation 5

Simulation 3 (Simulation 2+)

Simulation 6 (Simulation 5+)

Globalization and corporate activities 159 TABLE B4.2.2 Changes in capital stock caused by Japan’s direct investment

(US$ million) Capital Stock 1992: a Japan Indonesia Malaysia Philippines Thailand China Hong Kong Taiwan South Korea Singapore

12,088,694 260,626 158,812 149,444 252,487 991,254 281,374 392,752 706,058 167,301

FDI flows 1993

1994

1995

6,510 813 800 207 578 1,691 1,238 292 247 644

8,278 719 742 668 719 2,565 1,133 278 400 1,054

11,778 1,271 590 736 1,271 4,592 1,176 467 461 1,215

3-year average: b

b/a (%)

8,855 934 711 537 856 2,950 1,182 346 369 971

−0.073 0.359 0.447 0.359 0.339 0.298 0.420 0.088 0.052 0.580

Source: Compiled by the author based on the data from Ministry of Finance, Japan, Annual Report on International Finance (various issues) and GTAP Database (v. 3.0). TABLE B4.2.3 Impact on the world economy

(% change) Simulation No. 1

2

3

4

5

6

2,220 0.01

16,141 0.06

5,347 ..

2,837 0.02

16,665 0.04

6,315 ..

0.03 0.07 − 0.02

0.23 0.18 − 0.06

0.00 0.10 − 0.01

0.05 0.08 − 0.01

0.29 0.21 0.00

0.00 0.08 − 0.01

Variable EV (US$ million) World rate of net return on investment World net investment World trade volume World trade prices

Source: Compiled by the author.

economic impact of the additional domestic investment made in the host country on top of the initial capital and technology transfer captured in the simulation 2 (or 5). Therefore, the sum of this incremental impact and the results obtained in simulation 2 (or 5) indicates the overall effect created by the transfer of capital stock and technology and the matching domestic investment (co-finance). What the findings imply is that Japan’s FDI to Asia is indeed a positive-sum game. The FDI increases the world’s welfare and promotes global investment activities through the higher global average rate of return on investment. The world will be able to benefit from the expanded tradable commodities at a cheaper price. The second important finding is that, unlike simple transfer of capital stock, the scale of economic impact created by the transfer of managerial and production technologies is enormous (compare the results of simulations 1 and 2, or 4 and 5). Table B4.2.4 summarizes the impact to Japan, other Asian countries and regions under each simulation. The real GDP (size of economy) decreases in

Japan Indonesia Malaysia Philippines Thailand China Hong Kong, China Taiwan South Korea Singapre USA Western Europe Rest of the world

Total

due to TOT changes

0 0 0 0 0 0 0 0 0 0 0 0 0

due to Technology changes

Equivalent Variation (US$ million)

Simulation 1: Transfer of Capital Stock − 0.11 − 1,811 936 0.59 573 −77 0.63 279 −64 0.49 147 −52 0.69 573 −100 0.37 792 −231 0.52 227 −59 0.4 585 −98 0.46 976 −144 0.44 50 −68 0 −36 33 0 −60 −9 0 −76 −68

GDP quantity index (%)

Impact under Perfect Competition (CRTS)

TABLE B4.2.4 Impact on Japan, Asian economies, and other regions

Total

due to TOT changes

− 585 97 90 39 121 322 61 170 269 104 −5 − 13 − 32

due to Technology changes

Equivalent Variation (US$ million)

Simulation 4: Transfer of Capital Stock −0.13 −2,970 456 0.68 718 − 55 0.77 424 − 10 0.6 221 − 39 0.82 735 − 79 0.45 1,317 − 17 0.6 294 − 49 0.48 760 − 104 0.55 1,346 − 65 0.71 158 − 71 0 − 57 25 0 − 110 − 31 0 2 39

GDP quantity index (%)

Impact under Monopolistic Competition (IRTS)

160 Shigeru Thomas Otsubo

Source: Compiled by the author.

Japan Indonesia Malaysia Philippines Thailand China Hong Kong, China Taiwan South Korea Singapre USA Western Europe Rest of the world

−17 92 73 36 128 251 59 49 299 122 −27 −37 3

Simulation 6: Cofinance–Joint Venture (on top of Simulation 5) 0 220 203 0.67 729 −49 0.76 406 −37 0.61 246 −24 0.83 753 − 93 0.45 1,288 −65 0.59 304 −44 0.32 242 −323 0.56 1,380 −101 0.73 186 −68 0 147 199 0 107 172 0 309 231

Simulation 3: Cofinance–Joint Venture (on top of Simulation 2) 0 310 309 0.59 604 −60 0.62 301 −46 0.51 185 −31 0.71 591 −111 0.38 999 −107 0.52 236 −55 0.4 630 −68 0.46 1,011 −156 0.44 64 −57 0 146 143 0 143 153 0 126 86 0 0 0 0 0 0 0 0 0 0 0 0 0

Simulation 5: Transfer of Capital Stock & Technology −0.15 − 5,279 −1,127 −848 1.74 2,191 63 1,176 2.35 1,265 − 193 755 1.47 708 − 10 421 1.76 1,865 13 1,062 1.22 4,273 −5 3,091 1.49 1,132 108 711 2.77 8,145 2,430 4,090 1.74 5,885 820 3,463 4.12 1,644 − 13 1,394 −0.02 − 1,898 − 817 −656 −0.01 − 1,231 − 664 −565 −0.03 − 2,035 − 621 −1,142

Simulation 2: Transfer of Capital Stock & Technology − 0.11 −3,042 −225 0 1.3 1,520 −40 822 1.72 1,013 −38 534 1.3 654 23 340 1.57 1,619 −24 843 1.24 4,684 323 2,947 1.32 1,015 119 587 1.64 3,231 −68 2,452 1.64 5,301 519 3,341 2.31 861 −38 711 0 − 28 61 0 0 − 717 −595 0 0 31 −18 0

Japan Indonesia Malaysia Philippines Thailand China Hong Kong, China Taiwan South Korea Singapre USA Western Europe Rest of the world

Globalization and corporate activities 161

162 Shigeru Thomas Otsubo

Japan as it loses capital stock, while that of Asian countries, in which the capital stock is added, increases. For readers who intend to compare this with MacDougall’s (1960) model of international movement of production factors which was introduced in Box 4.1, it is suggested that they understand that the simulation in this Box 4.2 describes a situation in which the profit of foreign investment has not yet been repatriated to the donor country (Japan), or either the profit has been re-invested within the host country. In fact, when the author was engaged in a policy dialogue in Beijing as a World Bank economist in the mid-1990s, a Chinese government official boasted that the profit generated from any investments made in China would be continuously re-invested within China given the high potential of market growth. Now, when comparing the simulation results under a perfect market with those under the monopolistic competition market, which is closer to reality, a bigger impact can be observed in the latter in which the merit and demerit of the scale of economy appears (which is indicated in the EV value in technology change under simulation 4). In Asian countries the merit of scale is observed, while in Japan the demerit appears, and a slight downsizing of scale is observed in other areas as capital is attracted to Asian countries due to its enhanced rate of return. Table B4.2.4 decomposes the changes in the welfare level (measured in EV) caused by capital transfer, technology transfer, and the establishment of joint venture, by classifying them into the qualitative effects brought about by changes in terms of trade and enhanced technology. The remaining is the quantitative effect caused by the changes in the size of capital stock. When observing the results obtained from simulations 1 and 4 (under the status of before any repatriation of overseas profit is made to Japan), the welfare level of Japan (the capital donor country) declines, whereas the welfare levels of Asian economies (the host countries) increase. Under this situation, since the expanded Asian manufactured products will be imported to Japan at lower prices, the terms of trade turn favorable for Japan and vice versa for Asia. However, as indicated in the results from simulations 2 and 5, when technology transfer is made in addition to the capital transfer, the degree of variations in welfare levels is amplified in each direction. The terms of trade will also turn against Japan (donor of capital and technology), which will eventually cause secondary losses. This is because Japan’s technological superiority reduces and it is reflected on the import/export price ratio. On the other hand, the welfare levels of countries in Asia, which receive capital and technology transfer, dramatically improve. The results obtained from simulations 3 and 5 imply that active domestic investment, such as the establishment of joint ventures made by Asian countries in line with foreign direct investment, brings mutual benefit for both the Asian countries and Japan. The income from foreign investments (even including those to China) will eventually be repatriated to the originating country (Japan). When this income is sent back to Japan, a gap between the gross “domestic” product (real GDP)

Globalization and corporate activities 163

and the gross “national” income (real GNI) is produced. However, this gap itself is an indicator of the progress of a properly globalizing economic activity. Japan’s loss of welfare, at a minimum (in the case of simulation 1), is US$ 1.81 billion and, at a maximum (simulation 4), it is US$ 5.28 billion. At the same time, the welfare gains in Asia at minimum and maximum will be US$ 3.9 billion and US$ 27.1 billion, respectively. The initial investment (capital stock transfer) of Japan under this simulation is US$ 33.6 billion (which is equivalent to 1 percent of the estimated total capital stock of Asia). When comparing the transfer of capital stock (stock values) and the changes in annual real income (flow values) that is produced through the capital stock transfer, Japan’s direct investment to Asia creates real earnings of an annual rate of 11.6 percent (39/336) even under simulation 1, 80.7 percent (271/336) under simulation 5, and a high welfare earnings rate of 97.1 percent under simulation 6. It is true that in reality there is a big gap between income of the society as a whole and the company’s profit derived from investment activities. However, with this sort of high (welfare) profitability, it seems plausibly easy for Japan to obtain a continuous flow of profit repatriation that covers annual losses and augments the country’s real “national” income (real GNI) while preserving positive benefits in Asia. Note: Refer to Chapter 12 and the GTAP Project Homepage (https://www.gtap.agecon.purdue.edu).

4.3 MNCs and developing countries: the “dark side” (challenges) In the previous section, both the theoretical and empirical analyses on the benefits for capital-scarce developing economies of receiving productive resources through cross-border investment, and, in particular, in the form of FDIs by MNCs that transfer not only capital but also production technology and managerial resources, are presented. While the “bright side” of FDI was stressed, the “dark side” must have been visible from time to time. Many of the readers might have noticed the “challenges” that FDI poses which are as follows: (1) a short-term adjustment cost required to deal with the elimination of certain domestic competitors/industries and the industrial structural changes; (2) sharing the benefits of cross-boarder investment, a positive sum game, between the donor and host countries, between domestic investors and laborers, and between manufacturers and consumers; (3) fiscal and policy costs incurred by countries in order for them to compete with other countries in attracting direct investment that could lead to desired domestic industrial development;19 and (4) the cruel fact that transnational corporations that are sensitive to the “expected profit” will not make investment unless the host country’s basic infrastructure (economic infrastructure, human resources development, and domestic investment environment) for economic growth is

164 Shigeru Thomas Otsubo TABLE 4.2 Degree of concentration in FDIs to developing countries, 1985–2005

Country Name

Rank

1985–2005 Total (US$ million)

Share (%)

Accumulated share (%)

China Brazil Mexico Argentina Poland Russian Federation Chile Malaysia Thailand Hungary India Colombia Czech Republic Venezuela, RB Turkey Peru Nigeria South Africa Romania Kazakhstan Indonesia Egypt, Arab Rep. Vietnam Philippines Ukraine

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

608,604 226,934 211,625 97,169 77,686 66,118 65,825 63,915 51,521 49,172 47,179 43,174 42,434 38,133 28,984 25,676 25,420 24,475 23,776 23,124 22,963 22,502 22,412 20,115 16,036

26.6 9.9 9.2 4.2 3.4 2.9 2.9 2.8 2.3 2.1 2.1 1.9 1.9 1.7 1.3 1.1 1.1 1.1 1.0 1.0 1.0 1.0 1.0 0.9 0.7

26.6 36.5 45.8 50.0 53.4 56.3 59.2 62.0 64.2 66.4 68.4 70.3 72.2 73.8 75.1 76.2 77.3 78.4 79.4 80.5 81.5 82.4 83.4 84.3 85.0

Note: Based on the net inflows of FDIs to 152 low and middle income countries (BOP base, current US$). Source: Compiled by the author based on World Bank, World Development Indicators 2007 CD-ROM.

well organized, the domestic investment is active and a certain level of economic growth is achieved. As indicated in Table 4.2, FDIs by MNCs today are limited to only a certain number of developing nations. The top 25 recipients of FDIs accounted for 85 percent of the total to developing countries during 1985–2005. China, which has been a major host country of the recent FDIs to developing regions (26.6 percent of total during 1985–2005), has also been facing the problems of widening regional gaps between areas where investment was made and those without. It has been said that this widening gap could shake the current state system in the near future. In terms of participation in international trade, proactive policies such as spontaneous liberalization and promotion of exports bring benefit. On the other hand, in attracting foreign investment, the benefits do not occur just by opening a country’s door through investment/financial liberalization. The foundation for

Globalization and corporate activities 165

economic growth must be built step by step while intending to refine the quality of macroeconomic policies and taking into account the factors that could affect foreign enterprises and investors in making (locational) investment decisions. When the domestic economic market is not large enough, as in the case of many developing countries, the host country often has no other choice but to focus on export processing-oriented policies like designating export-processing zones (EPZs) in order to attract foreign investments. Even if this ends partially successfully, there is the secondary issue whether the investments into economic enclaves bring a positive ripple effect to the domestic industries or not. Between 1999 and 2000, the author, as the chief assessor of JICA-sanctioned evaluation team, was involved in a country-wise review of JICA’s aid programs to Bangladesh for the entire period after its independence in 1971. Those were the days the author would often hear Bangladeshi senior government officials complaining: “We did liberalize investment but have not received any foreign investment. What happened to the export processing zones that we established in the suburbs of Chittagong and Dhaka? As if they were enclaves. No trickledown effect has been confirmed to the peripheral companies as we had been expecting.” Despite these complaints, the clothing (especially shirts) industry developed rapidly as represented by Grameen Check that was growing as one of the leading export products. Yet, there were still criticisms made by the local people that “the benefit, which is supposed to accrue to the Bangladeshi economy, cannot be observed.” These complaints were often made based on the contractual disadvantages in transactions (transportation, quality standard, etc.) with the European multinational apparel enterprises. Professor Meier (1996) also referred to the issue of profit sharing between the transnational corporations and the host country as follows: This is the crucial question posed by the attribute of “multinationality.” For multinationality instills foreign investment by an MNE with greater bargaining power because of its tendency to be of larger size, its capability to exercise wide options, and its capacity to avoid some forms of regulation that cannot reach beyond national jurisdiction. (ibid., p. 258) Especially when there is not so much transaction with the local industry as transactions between the “independent companies,” the transnational corporations conduct “transfer pricing” through their own subsidiaries located throughout the globe to maximize their own global profit by taking advantage of transfer pricing and cost allocation. The host country expects contribution to the growth of the host country. However, since these multinational corporations pursue maximization of their global profit, they are often insensitive to the individual host country’s needs. The global production network of transnational corporations is actually established on the ground of “comparative advantage” possessed by each production

166 Shigeru Thomas Otsubo

site of this global entity. Many times, the network also changes by corresponding to the changes of “comparative advantage.” For example, the consecutive closing of factories in Guangdong Province which accounted for 30 percent of China’s exports, the “factory of the world,” was caused by difficulties in employing cheap labor under flexible conditions, as well as the appreciation of Chinese currency. After recording 10 percent plus annual increase in wages for several years and given the enactment of labor law that protects workers’ employment rights (i.e., democratization of labor market regulations) in January 2008, Guangdong Province (China) lost the comparative advantage in assuring cheap labor costs. Since it is a “comparative” advantage, multinational corporations eventually shift their production to other sites where the labor force is still “relatively” cheaper (as a total cost including the cost of observing employment practices/regulations), or they search for new locations. Even if direct investment is made by a multinational company, it does not directly promote industrial advancement all at once going beyond the constraints of “comparative advantage.” In addition, as pointed out in Box 4.3, the speed of expansion and withdrawal of transnational corporations is accelerating even more, given the establishment and development of the “Nike Model,” in which a company does not hold any fixed assets in the developing country, but rather simply signs manufacturing contracts with other multinational corporations or local corporations. Once you have your Nike shoes on, you get foot-loose. Other than these issues, there is the “development sovereignty” problem in which the mega multinational corporations and transnational corporate groups urge the host country government to execute laws and institutions that are favorable to them and other foreign companies. Developing nations have, for a long time, given way to many crucial matters including environmental standards and labor standard laws. In addition, when the government of these countries is in a relatively stronger position, bribery and corruption have occurred. These are issues to be discussed under the theme of governance and global governance, which are dealt with in the following section and in Chapter 3, “The Role of Governance and Politics in the Development of Developing Countries.”

Box 4.3 Foot-loose multinational corporations: Nike’s sweat shop and the Nike model Between 1995 and 1996 when Nike, Inc., an American MNC manufacturer dealing in sporting goods and apparel had their soccer balls manufactured in Pakistan, based on the local customs in which part of the work can be brought home, the child labor issue came to light as some of the workers’ minor family members were found to be engaging in the manufacturing process. This drew global attention which evolved into “Nike’s child labor” scandal.1 This triggered NGOs and mass media to investigate and disclose

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any information on Nike’s contract factories in developing countries, including the poor working conditions and prolonged working hours. Nike-contracted factories were called “sweat shops” and received worldwide criticism which led consumers to boycott Nike products. The term “sweat shop” that the media used to criticize the company’s treatment of their employees derived from sarcasm that Nike laborers had to engage in work with a lot of sweat, as these products were usually called “sweat shirts” in the US. Later in 1998, Nike adopted the Child Labor Standards, the strictest acts in the industry, and set the guidelines. The minimum age for a worker in the manufacturing of equipment and apparel was set at 16 years old and for footwear production the limit was set at 18 years old. The entire supply chain of Nike products manufacturing had become subject to annual audits for child labor, breach of overtime working hours, unjustified wage payment, inappropriate calculation of allowances, and other issues relating to worker’s welfare. Today (August 2014), the Nike USA website has a “Company – Responsibility” section where Nike’s current Code of Conduct is explained and supply chain disclosure is made.2 According to its supply chain disclosure, Nike’s global manufacturing network includes 719 Nike-contracted factories in 44 countries and it employs 990,325 workers in factories worldwide. Nike’s main business unit specializes in management strategies, product and technology development, public relations, and sales promotion. The actual manufacturing of products is basically outsourced to the contract factories. This is the “Nike Model,” a business model that minimizes actual assets holding in other countries (especially in developing regions). Following the child labor issue, Nike, for the first time in the sporting goods and apparel industry, started disclosing the names and addresses of all the contract factories that manufacture its brand products. (Disclosure of detailed data deserves recognition.) This “Nike Model” that outsources manufacturing to contract factories implements a strict regulation that any factory which does not comply with the labor standards will be terminated. While this practice has been conducive to the improvement in labor market regulations in many developing countries, this business model also allows Nike to transfer production from factories that do not meet production targets due to labor disputes to other contract factories (this includes signing of new contracts with new factories or with existing overseas factories). It is a “foot-loose” business model that does not directly lead the company to hold new fixed assets. That is, FDI that creates expanded production capacity has not materialized. When the author was engaged with the National Development Planning Agency of Indonesia (BAPPENAS) as an economic policy advisor from 2000 to 2001, there was a labor dispute in one of Nike’s contract factories in the suburb of Jakarta that was manufacturing golf gloves. This was just a part of the labor disputes that occurred in major foreign-funded or foreign-contracted

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corporations in that area at the time. However, the Jakarta Post reported that Nike had immediately annulled the contract and shifted production to a different factory outside Indonesia. If memory serves me correctly, this contract factory in Jakarta was a Korean-funded company, whose business conditions worsened and had to dismiss its workers at the end, according to the Jakarta Post. In searching for a more recent case of disputes, the closure of the Nike-contracted factory in Cambodia (just outside of Phnom Penh) in May 2013, due to the workers’ clash with police, is another good example. The workers were protesting over payments (changes in minimum wages). Sabrina, a Cambodian garment manufacturing company, owns the factory. New business models of transnational corporations create new markets and employment. For example, VIZIO Inc., an emerging television manufacturer based in California, USA (http://www.vizio.com/) was a “small company” with only around 100 employees that included 60 customer relations staff (telephone operators). It did not own any manufacturing hubs. Rather, it procured panels from Taiwanese and Korean manufacturers and outsourced the assembly work mainly to Chinese factories. With this “borrowed horizontal specialization style” business model (an evolving style of the “Nike Model”), the company achieved a big growth by offering products at a low price. In 2007, VIZIO obtained the top share in the flat screen TV market in the US. With this “big” success in the US market, VIZIO launched its products in Japan in the summer of 2008. As of 1988, when the author left Stanford University in California and started working at the UN headquarters in New York, the only American TV manufacturer at the time was Zenith. Later in 1995, Zenith was acquired by the Korean LG Electronics, thus, the US-capital TV manufacturers vanished. Although the US TV manufacturers did once get chased by the Asian brands and disappeared, VIZIO brought back the USfunded TV manufacturer with a new business model in which it centered its manufacturing sites in contract factories in Asia. It should be noted, however, that these new business models of multinational corporations, which do not possess any fixed assets in the developing countries, prevent the actualization of “development sovereignty” as fixed assets could actually be collateralized (or even pawned?) when developing countries negotiate with (big) MNCs for better and more equitable business ventures. Notes: 1. Sourced from Nike Japan Public Relations Homepage in September, 2008. (http://www.nike.jp/nikebiz/global/childlabor.html). This website is no longer operative as of 2014. 2. Sourced from the Nike USA Homepage on August 27, 2014 (http://nikeinc. com/pages/responsibility).

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4.4 MNCs and development governance 4.4.1 Developing countries’ policies to attract FDIs The main pillar of policies to attract foreign investment in developing nations has been, for a long time, fiscal measures especially to give tax exemptions. When developing countries compete in bringing in foreign investment to their own country, they often allow excessive concessions to foreign companies. This, as a result, creates inequality to other domestic companies. To avoid this, if the government takes tax exemption measures even to domestic firms, it ends up in a form of income redistribution from the poorer laborers to the investors. Meier (1996) states that, “The private investor’s first concern is whether costs will be covered and a profit earned” (ibid., pp. 251–252), and “The foreign investor is likely to be less interested in receiving an exemption after a profit is made than in being sure of a profit in the first instance” (ibid., p. 252). He adds that, “It is therefore most important to raise profit expectations” (ibid., p. 252). The basics are to reduce country risk that exceeds ordinary business risks, protect investment, and to assure the free activities of foreign companies and investors. Any fears against forcible expropriation in the host country must be eliminated, laws and institutions that discriminate foreign corporations and investors must be abolished,20 and foreign exchange controls must be lifted. On top of these measures, economic infrastructure must be developed to increase “profit expectation” while fostering industrial human resources including skilled laborers (or, at least, those who have received minimum education) and mid-level managers to manage locally employed workers. The quality and governance (including measures against corruption) of the host government are often stressed to be important to attract foreign companies; thus, there are various cases in which low-income states are forced to implement rapid governance reforms. The research group at Nagoya University headed by Prof. Otsubo conducted an empirical study on the relations between the governance factors and the economic growth rate and the domestic investment ratio and the FDI attraction rate by classifying the data into low-income, middle-income, and high-income countries. The governance factors in this study include macroeconomic management, economic structural reforms (trade liberalization, financial sector reforms, and business regulations reforms), social policies (especially policies on human resources and labor, gender gap correction, etc.), and public sector management (rule-based governance, securing fiscal revenue, maintaining transparency, managing corruption, etc.).21 The results compiled by Ngov (2008) are as follows: (1) in low-income countries, the improvement of governance slightly promotes domestic investment and growth acceleration, yet, does not link to higher FDI inflows; (2) in middle-income states, better governance brings domestic investment and it even enhances FDI, thus, contributing to the acceleration of growth; and (3) in high-income nations, where governance has already reached a certain level, there is no significant relationship as companies have a low degree of dependence on governance. In short, in

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low-income countries, although macroeconomic management is significant to a certain extent, the top priority is to dispel the country risk, improve the economic infrastructure and to improve the quality of (unskilled) laborers to achieve better cost-performance of the local workforce. These findings can be backed up by the fact that investment to China rapidly increased despite the relatively low governance standards. This implies that a country must improve the basic investment environment, achieve market maturity, and execute policies that improve the quality of governance by the time the country joins the group of middle-income countries.

4.4.2 Strategies to make use of foreign investment Once a country succeeds in receiving foreign investment, it must maximize the benefit within the country while minimizing any adverse effects. The biggest challenge, as demonstrated in this chapter, is how to absorb the production technology and management resources (recall the analytical results presented in Box 4.2). The institutions and mechanisms that facilitate the establishment of the domestic supply chain, human resource development that could absorb the production technology and management skills, and allowing the proliferation of technology as a “public good,” must be formed. This includes, for example, encouraging the launching of joint ventures, attracting multinational R&D and training centers, etc. Moreover, the industrial clusters must be further developed by involving transnational corporations. The economic and transport infrastructure and efficient domestic labor market that facilitate the inter-regional spillover effects of the investment should be developed.

4.4.3 Governance of MNCs and FDIs There is no international organization that sets forth the MNC Charter, monitors the activities of the transnational enterprises on a worldwide scale and controls companies that breach the charter. There are the OECD Guidelines for Multinational Enterprises established in 1976 and modified in 2000, in which the 30 OECD member countries and Latin American countries including Argentina, Brazil, and Chile pledge compliance with the set guidelines for employment and labor–management relationships, maintaining accountability, combating corruption, protecting consumers, and other issues involving human rights and the environment (Tokushige and Hidaka, 2003, p. 295). Based on this guideline, the US enacted the Foreign Corrupt Practices Act in 1977 to regulate American companies’ fraudulent behavior outside the country. However, there is no international punitive clause, and, in fact, there are many countries in which no regulations on this matter exist, or even if they exist, the rules are not enforced in reality (including the case of Japan). The self-regulation guidelines of the International Chamber of Commerce (ICC), a collective of multinational corporations, and the promotion of corporate

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social responsibility (CSR) currently serve as self-imposed regulations. The most successful self-help framework is probably the Global Compact. This concept, which was proposed by the then UN Secretary General Kofi Annan in the World Economic Forum (generally called the Davos Forum) in 1999, stipulates three major standards of environment, human rights, and labor employment practices (divided into nine principles) that transnational corporations must comply with (Tokushige and Hidaka, 2003, p. 297). The multinational companies must demonstrate to the world (and consumers) that they are part of global society by participating in this framework (otherwise, they will take the risk of receiving a bashing from NGOs and consumers). It should be noted that it was the human rights’ NGOs and consumers’ NGOs that forced Nike to take prompt and sincere actions toward the child labor issue that this multinational corporation faced as introduced in Box 4.3. Following this incident, many transnational firms started working on CSR, as maintaining a good brand image is essential for these companies in expanding their business throughout the world. In fact, it is the consumers’ intelligence, dignity, and energy that discipline the activities of multinational corporations which promote globalization as a core player. As often stressed by economists, companies can never win against the “demand curve.” Neither product development nor product pricing will be realized, unless the shape and movement of the “demand curve” is being carefully considered. Establishing brand image and brand loyalty brings about positive effect to the company’s capacity to work on the “demand curve.” However, once the consumers, who are dominated by taste and wants, become knowledgeable and concerned with human rights, labor, and other related issues such as poverty in the developing countries and environmental matters, they become capable of controlling the “demand curve,” thus establishing a robust “consumer sovereignty.” In development amid globalization, what protects the “development sovereignty” of developing nations may well be the (developed countries’) consumers’ self-realization and the establishment of the so-called “consumer sovereignty.” Employment generation in a poor province

FIGURE 4.8

Water pollution issues

FDI-funded paper mill in Khon Kaen, Northeastern Thailand

Source: Photographed by author.

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Notes 1 This chapter is based on the English translation of Chapter 4 (Globalization, MutiNational Corporations and Foreign Direct Investment) in Otsubo (2009) published in Japanese, with revisions and updates. 2 Based on the data from the UNCTAD (2007), World Investment Report 2007, Table A.I.15 and Table A.I.16. The UNCTAD (2008), World Investment Report 2008, which was published in the end of September 2008, ceased the announcement of GSI ranking of companies in the non-financial industries and limited disclosure of information to rankings based on the overseas assets. In more recent years, UNCTAD uses the Transnationality Index (TNI), which is calculated as the average of the following three ratios: foreign assets to total assets, foreign sales to total sales, and foreign employment to total employment. 3 According to the Deutsche Post, there were subsidiaries in 220 countries. However, the UNCTAD statistics considered only those that are majority-owned with a minimum of 50 percent share as an affiliate company. 4 Source from UNCTAD (2008b), World Investment Report 2008, Table A.I.15. The ranking of non-financial MNCs by their foreign assets in 2013 is available in the Annex Table 28 to World Investment Report 2014 (www.unctad.org/wic). General Electric Co. still tops the list with total overseas assets of US$ 331.2 billion, followed by Royal Dutch Shell (US$ 301.9 billion) and Toyota Motor Corporation (US$ 274.4). 5 Referred from the top 100 world’s leading companies listed in the July 2008 edition of the Forbes ( Japanese edition). 6 In the World Investment Report 2007, Bulgaria and Romania were categorized as Eastern Europe. Special attention must be paid to the quality of the corporate statistics in Eastern Europe. As of 2007, there were 78,411 multinational enterprises in the world with a total number of 777,647 overseas subsidiaries and offices. It must be noted that information on countries in which data cannot be obtained was not included. 7 Calculated from the data of National Bureau of Statistics of China (2007). 8 Referred from the Ministry of Economy, Trade and Industry’s Survey of Overseas Business Activities (2006) for overseas production ratio by industry (http://www.meti. go.jp/statistics/tyo/kaigaizi/result/result_37/result_37.html, accessed September 16, 2008). 9 The 2002 Trade White Paper featured the trend of reimport of the Japanese companies. 10 Given the subprime mortgage issues in the US, the Lehman Brothers (below 50th in the finance GSI ranking), the number four securities house in the US, went bankrupt while the share prices of the top securities company Goldman Sachs (36th) fell sharply. Under this situation, the Nomura Holdings (30th) took over Lehman Brothers’ businesses in Asia, Middle East, and Europe, excluding the North American operations. At the same time, the Mitsubishi UFJ Financial Group (32nd) became the largest shareholder of Goldman Sachs. Although the US government nationalized AIG Inc. (17th), this is how the reshuffle of the global banking industry started. 11 The UNCTAD (2008), Trade and Development Report 2008 focused on this paradox. 12 Lately, there has been an increasing acquisition of corporations in the technology-oriented industries and brands made by Chinese companies through M&A. In September 2007, the Sovereign Wealth Fund (SWF) was founded with the objective of managing China’s enormous foreign currency reserves. The Fund drew much attention as it started investments in American investment funds and the British resources industry. 13 In Chapter 1, it is pointed out that the trend which increases the regional gap in a host country of FDI is one of the negative aspects in receiving investment. The policies that enhance the diffusion effect of FDI within the country such as the local-content rules, however, are becoming difficult under the WTO system. 14 In Chapter 12, Ken Itakura, who used to serve as a research fellow at the Purdue GTAP center, explains the structure and applications of this CGE modeling framework. 15 Refer to, for example, Borensztein, De Gregorio, and Lee (1998), who point out the trend of the crowding-out effect of FDI observed in developing countries as a whole.

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16 Similar studies on the impact of FDI from a macro perspective can be found in de Mello (1999), Ericsson and Irandoust (2001), Razin (2002), Basu, Chakraborty, and Reagle (2003), and Choe (2003). 17 On the other hand, after all, the reverse causality that countries, industries, and companies, which have higher productivity and growth rate attract FDI, must not be overlooked. 18 This is different from the limited cases of FDI which did not lead to higher productivity or economic growth as observed in Latin America right after the Debt Crisis and in the economies in transition in Eastern Europe where the (partial) transfer of ownership was achieved by (initial) sales of state-owned enterprises. The M&A FDI often creates global-scale reorganization in the manufacturing, finance, and resources industries and the consequent new investments. 19 This is unlike the conventional FDI made by multinational mining firms to low-income developing nations which happen to have rich energy or mineral resources. 20 This implies the execution of “national treatment” which is one of the five principles of WTO. 21 Strictly speaking, the World Bank’s CPIA (Country Policy and Institutional Assessments) data was used for low-income states, while information processed by the World Bank originating from the ICRG (International Country Risk Guide) data was applied to middle and high-income countries. Therefore, the governance factors are not necessarily integrated among the income group classification. The differences in data source can be attributed to the fact that there is no ICRG data for low-income nations.

References Agosin, M. & Mayer, R. (2000). Foreign Investment in Developing Countries: Does It Crowd in Domestic Investment? UNCTAD Discussion Paper, 146. Aitken, B. J. & Harrison, A. E. (1999). Do Domestic Firms Benefit from Direct Foreign Investment? American Economic Review, 89(3), 605–618. Basu, P., Chakraborty, C., & Reagle, D. (2003). Liberalization, FDI, and Growth in Developing Countries: A Panel Cointegration Approach. Economic Inquiry, 41(3), 510–516. Blomström, M. & Sjoholm, F. (1999). Technology Transfer and Spillovers: Does Local Participation with Multinationals Matter? European Economic Review, 43(4–6), 915–923. Borensztein E., De Gregorio, J., & Lee J., W. (1998). How Does Foreign Direct Investment Affect Economic Growth? Journal of International Economics, 45(1), 115–135. Calderón, C., Loayza, N., & Servén, L. (2004). Greenfield Foreign Direct Investment and Mergers and Acquisitions: Feedback and Macroeconomic Effects. World Bank Policy Research Working Paper, 3192. Choe, J., I. (2003). Do Foreign Direct Investment and Gross Domestic Investment Promote Economic Growth? Review of Development Economics, 7(1), 44–57. De Mello, L (1999). Foreign Direct Investment-led Growth: Evidence from Time Series and Panel Data. Oxford Economic Papers, 51, 133–151. Dunning, J. H. (1977). Trade, Location of Economic Activity and the MNE: A Search for an Eclectic Approach. In Bertil O. et al. (Eds.), The International Allocation of Economic Activities, London: Macmillan, 395–418. ——— (1979). Explaining Changing Patterns of International Production: In Defence of the Eclectic Theory. Oxford Bulletin of Economics and Statistics, Vol. 41 (November). ——— (1988). The Eclectic Paradigm of International Production: A Restatement and Some Possible Extensions. Journal of International Business Studies, 19(Spring), 1–31. Ericsson, J. & Irandoust, M. (2001). On the Causality between FDI and Output: a Comparative Study. International Trade Journal, 15(1), 1–26.

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Fry, M. J. (1993). Foreign Direct Investment in a Macroeconomic Framework. World Bank Policy Research Working Papers, 1141. The World Bank. GTAP (1998). GTAP Database (v. 3.0) [CD-ROM]. West Lafayette: Purdue University GTAP Office. Haddad, M. and Harrison, A. (1993). Are There Positive Spillovers from Direct Foreign Investment? Evidence from Panel Data for Morocco. Journal of Development Economics, 42(1), 51–74. Helpman, E. (1984). A Simple Theory of International Trade with Multinational Corporations. Journal of Political Economy, 92(3), 451–471. Horstmann, I. J. & Markusen, J.R. (1987). Strategic Investments and the Development of Multinationals. International Economic Review, 28(1), 109–121. Hymer, S. H. (1976). The International Operations of National Firms: A Study of Direct Foreign Investment. Boston: MIT Press. Kokko, A., Tansini, R., & Zejan, M. (1996). Local Technological Capability Spillovers from FDI in the Uruguayan Manufacturing Sector. Journal of Development Studies, 32(4), 602–611. Lizondo, S. J. (1991). Foreign Direct Investment. Determinants and Systematic Consequences of International Capital Flows. IMF Occasional Paper, No. 77. MacDougall, G. D. A. (1960). The Benefits and Costs of Private Investment from Abroad: A Theoretical Approach. Economic Record, 36, 13–35. Meier, G. M. (1996). Leading Issues in Economic Development (6th ed.). Oxford: Oxford University Press. Ministry of Economy, Trade and Industry of Japan. (2002). Trade White Paper 2002. ——— (2008). Trade White Paper 2008. Ministry of Finance (1992–1998). Annual Report on International Finance. Various issues. Tokyo: MOF Printing Office. Nair-Reichert, U. & Weinhold, D. (2001). Causality Tests for Cross-country Panels: A New Look at FDI and Economic Growth in Developing Countries. Oxford Bulletin of Economics and Statistics, 63(2), 153–171. National Bureau of Statistics of China (ed.). (2007). China Statistical Yearbook. Beijing: China Statistics Press. Ngov, P. (2008). Governance, Foreign Direct Investment, and Economic Growth. Forum of International Development Studies, 36, 255–278. Otsubo, S. (1998). Economic Impact of Japan’s FDI to Asian Countries. In Ban, K. and Otsubo, S. (eds.), Evaluation of Trade and Investment Liberalization and Environmental Policies using an Applied General Equilibrium Model. Economic Analysis. No.156. Tokyo: Economic Research Institute, Economic Planning Agency of Japan, 77–133. ——— (2005a). Computational Analysis of the Economic Impacts of Japan’s FDI in Asia. Forum of International Development Studies, 28, 1–33. ——— (2005b). Trend of Japan’s International Balance of Payments and East Asia’s Growth Dynamism: From “Asia’s Threat” to “Asia’s Coexistence.” Journal of International Development Studies, 14(1), 1–29. ——— (2009). Globalization to Kaihatsu [Leading Issues in Development with Globalization]. Tokyo: Keisoshobo. Otsubo, S. T. & Umemura, T. (2003). Forces Underlying Trade Integration in the APEC Region: A Gravity Model Analysis of Trade, FDI, and Complementarity. Journal of Economic Integration, 18(1), 126–149.

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Razin, A. (2002). FDI Contribution to Capital Flows and Investment in Capacity. NBER Working Paper, 9204. Romer, P. (1993). Two Strategies for Economic Development: Using Ideas and Producing Ideas. Proceedings of the World bank Conference on Developmnet Economics (ABCDE) 1992. The World Bank. Sekiguchi, S. (1988). Economics of Direct Investment and Technology Transfer. Tokyo: Chuokeizai-sha, Inc. Tokushige, M. and Hidaka, K. (eds.). (2003). Globalization to takokuseki kigyo. Tolyo: Chuo University Press. UNCTAD (2001). World Investment Report 2001: Promoting Linkages. United Nations. New York and Geneva. ——— (2006). World Investment Report 2006: FDI from Developing and Transition Economies —Implications for Development. New York and Geneva: United Nations. ——— (2007). World Investment Report 2007: Trannational Corporations, Extractive Industries and Development. New York and Geneva: United Nations. ——— (2008a). Trade and Development Report 2008. New York and Geneva: United Nations. ——— (2008b). World Investment Report 2008. New York and Geneva: United Nations. World Bank (2001). Global Development Finance 2001: building coalitions for effective development finance.Washington, DC: United Nations. ——— (2007). World Development Indicators 2007 [CD-ROM]. Washington, DC: World Bank. ——— (2008). World Development Indicators 2008 [CD-ROM]. Washington, DC: World Bank. ——— (2014). World Development Indicators (WDI) [Data file]. Washington DC: The World Bank. Retrieved August 15, 2014 from http://data.worldbank.org

5 GLOBALISATION AND AGRICULTURE Optimising trade policies for small farmers Zamroni Salim

5.1 Agriculture in the global economic structure In the world today, there is still a huge number of people who are hungry: around 842 million. This number compares well with the figure for the early 1990s, when there were approximately 1000 million people without sufficient food (FAO, 2014). The vast majority of these people live and work in agricultural sectors in African and in some developing Asian countries.1 It is undeniable that agriculture is important for developing and for developed countries. Agriculture in developing countries is still the most important sector in terms of labour absorption, as well as its contribution to the gross domestic product (GDP) and to economic development (see Table 5.1). Variations in the relative contribution agricultural sectors make to the GDP of trading countries have been dependent on how national governments treat this sector. The decreasing contribution of the agricultural sector to the national GDP of developed and of developing countries is consistent with increases in the contributions made by their manufacturing and service sectors. From Table 5.1, we can see that the labour absorption rates of agricultural sectors are far different for developed and developing countries. Large decreases in the value-added contribution of agricultural sectors have not been proportional to the decreases in labour absorption rates, which means that agricultural sectors still provide relatively more employment, especially in developing countries. In European Union (EU) countries, labour absorption rates have been decreasing and fell to 5.22 per cent in 2010. Similar to the EU countries were the North American countries, where labour absorption was 1.6 per cent. Employment in agricultural sectors in South Asia was around 50.78 per cent and in East Asian developing countries it was 36.66 per cent in 2010. The big difference is because the high dependence on the agricultural sectors in the economies of developing countries remains unchanged and widespread in East Asia, South Asia and African countries.

Globalisation and agriculture 177 TABLE 5.1 Agriculture in the economic structure by countries (region) Indicator EA and Pacific AVA AVAw Empl RuP EU AVA AVAw Empl RuP ME and Naf AVA AVAw Empl RuP North America AVA AVAw Empl RuP South Asia AVA AVAw Empl RuP SSA AVA AVAw Empl RuP

1980

1985

1990

1995

2000

2005

2010

28.75 27.02 25.22 19.28 14.88 12.16 11.03 290.56 349.18 378.92 434.48 496.16 591.09 726.27 na na na 50.84 49.63 43.95 36.66 78.66 75.30 71.84 67.83 63.35 57.93 52.46 4.58 3.97 3.75 3.08 2.42 1.82 1.57 7,180.72 9,199.66 na 11,100.92 14,882.34 18,516.93 18,380.44 na Na na 8.90 7.77 6.18 5.22 31.30 30.53 29.77 29.19 28.60 27.48 26.37 15.30 16.96 18.01 15.97 12.99 10.69 na 1,337.48 1,494.44 1,709.09 1,796.48 1,986.12 2,563.17 na na Na na na Na na na 53.05 50.44 48.33 46.39 44.45 42.45 41.02 2.91 2.40 2.05 1.64 1.23 1.21 1.15 13,766.47 19,397.05 21,921.70 24,865.76 39,607.64 51,497.47 57,495.98 na Na na 3.01 2.67 1.71 1.60 26.07 25.32 24.57 22.70 20.87 19.33 18.01 34.54 30.85 28.89 26.29 23.55 19.23 18.77 384.76 414.18 454.57 481.02 535.27 564.14 638.22 na Na na na 59.21 53.51 50.78 77.67 76.28 74.98 73.84 72.66 71.10 69.40 18.19 21.07 20.51 19.79 17.48 17.47 15.65 506.68 509.12 447.84 491.01 607.97 696.74 na Na na na Na na na 76.38 74.37 72.10 69.86 68.01 66.09 64.07

Notes: EA and Pacific – East Asia and Pacific developing countries; ME and NAf – Middle East and North Africa developing countries; SSA – sub-Saharan Africa developing countries; the EU and North America are developed countries; AVA – Agriculture, value added (per cent of GDP); AVAw – Agriculture value added per worker (constant 2005 US$); Empl – Employment in agriculture (per cent of total employment); RuP – Rural population (per cent of total population); na – data are not available. Source: World Bank (2014).

As the largest employment absorber in the economies of Asian and African countries, the agricultural sector comprises predominantly an abundance of farmers: those with small holdings and those who are landless (Mazoyer, 2001; Vorley, Cotula and Chan, 2012).2 With their limited land ownership, small farmers will perhaps never be able to increase their production. Consequently, they add relatively little value to this sector, which implies a low income for them and their families. How are they to achieve a larger share of the value added to the economy? Leaving aside arguments about giving them opportunities to compete in global markets, in principle, they deserve protection to assure them of a minimum standard of welfare for their survival. Welfare, in this context, refers to the requirement for them to have adequate nutrition and food security. Table 5.1 shows that developing countries in East Asia and the Pacific, the Middle East and North Africa had value added created in their agricultural sectors of around 10 per cent to 11 per cent of GDP. Other developing countries in sub-Saharan Africa (SSA) and South Asia had a larger share of agricultural value added: 15.65 per cent and 18.77 per cent respectively. The comparative figures for the developed countries are 1.57 per cent for the EU and 1.15 per cent for

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TABLE 5.2 Agriculture in the economic structure by income group Indicator Low income

AVA AVAw Empl RuP Middle income AVA AVAw Empl RuP High income AVA AVAw Empl RuP World AVA AVAw Empl RuP

1980

1985

1990

1995

2000

2005

2010

37.68 38.75 37.56 37.40 33.83 29.49 27.92 na na 274.71 263.31 283.21 313.99 354.37 na na na na na na na 81.50 80.02 78.60 77.17 75.85 74.33 72.58 22.29 21.08 19.47 15.72 12.65 10.86 10.06 506.78 550.87 590.11 651.25 727.56 857.31 968.32 na na na na 47.87 42.40 37.61 69.17 66.35 63.66 60.98 58.19 54.95 51.71 3.95 3.37 3.14 2.44 1.94 1.59 1.40 9,013.31 11,805.59 14,797.25 11,509.45 16,372.92 19,870.74 21,927.14 na na na 6.90 6.03 4.72 3.48 28.33 27.05 25.80 24.68 23.64 21.86 20.33 7.28 6.67 6.23 5.01 4.04 3.41 3.20 816.55 861.10 889.22 935.63 1,062.35 1,186.39 1,241.65 na Na na na 37.92 35.11 30.51 60.63 58.80 57.03 55.22 53.32 50.87 48.40

Notes: AVA – Agriculture, value added (per cent of GDP); AVAw – Agriculture value added per worker (constant 2005 US$); Empl – Employment in agriculture (per cent of total employment); RuP – Rural population (per cent of total population); na – data are not available. Source: World Bank (2014).

North American countries. Correspondingly, by groups of income, the developed countries, which are mostly higher income countries, also have larger value added per worker; on the other hand, developing countries (for lower- and middleincome groups) have lower value added per worker (see Table 5.2). From a global perspective, the agriculture contribution to world GDP is also quite low. This lower share does not mean that this sector is unimportant for developed and for developing countries: it is a sign that the agricultural value added of developing countries is very small compared to the world GDP, even though the number of developing countries is large. In other ways, it confirms that the world’s agricultural value added was supplied predominantly by developed countries (see Table 5.2). Under globalisation, this lesser contribution to global GDP from agricultural sectors in developing countries suggests that this sector is in need of special attention. The number of small farmers and rural poor is huge, their incomes and the value they add are limited – how is this set of people to survive under globalisation? The regional and global economic crises in Latin America and Asia, and recently in the USA and the EU have influenced the trade policies and trade relations of those countries to be more stringent. Successful developing countries are those that do not have agriculture as their predominant economic sector (Aksoy and Beghin, 2005). It seems that having a high reliance on agricultural exports under the current international trade regime is risky. There are many uncertainties in agriculture at present for trading countries, such as price volatility and food insecurity. In considering these current uncertain conditions in food markets, trading countries need to redesign their trade policies, especially with regard to small farmers.

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This chapter examines the enormous challenges for developing countries that depend heavily on trade in agricultural products. The discussion focuses on small farmers, who have limitations of land, finance, skills and other resources including a lack of supportive trade-related policies. It is important that these handicaps or limitations, which reduced access to resources, to factors of production and to markets, be acknowledged to enable better policies that are sympathetic to their needs (FAO, 2010). In substance, any kind of constructive policy for these groups is not meant to destroy the current bilateral and multilateral trade arrangement or to be contrary to the process of trade liberalisation. It is just a means to enable decent living standards for this marginalised group by lifting its members out of absolute poverty. So, attention and remediation for this sector are crucial.

5.2 Small farmers in developing countries There are family farms all over the world; the differences between them are easily detectable, especially those between developed and developing countries. In undeveloped countries, the number of small farmers with less than 2 hectares of land is around 500 million, and 87 per cent of them live in Asian and Pacific countries (Thapa and Gaiha, 2011). More specifically, the number of small farmers in China is around 193 million; in India, 93 million; in Indonesia, 17 million; and in Bangladesh, 17 million. In contrast, farmers in rich countries have much larger land holdings and advanced agritechnological equipment. European countries are home to 13.7 million farmers with average land holdings of about 12 hectares; in the USA, there are around two million farmers with an average land holding of about 180 hectares (European Commission, 2013). Small farmers are usually subsistence farmers whose productivity is low and who depend mainly on family labour that forgoes regular wages or income. The predominant crops grown are of staple foods that are sufficient, though not always, to feed their families (Lipton, 2013). The proportion of small farmers in the total world farming population is quite large, so continued reduction in agricultural production in countries with inefficient agricultural practices could increase their dependence on imports of food. One consequence of inefficient domestic agricultural practices, and with many or most farms operating at subsistence level, is that they make it more likely that a country will come to depend on imports of food. One cause of poverty is the inability of low-income households and farmers to have an adequate food supply from their low rates of production in the local or domestic market (a shortage of supplied products tends to cause higher prices), or a food supply from more liberalised economies in which prices in the domestic market are similar to international prices and volatile over time. The household income of poor farmers is not usually enough to withstand the repercussions of price volatility. As a consequence, the deprived small farmers in developing countries seem consigned to endless poverty.

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Poverty may be described as either relative or absolute. The more severe of the two is absolute poverty where people live below the poverty line and are hungry and malnourished. Developing countries use different poverty lines, or the minimum daily income of poor families, to measure the incidence of poverty. Setting a poverty line is not just a matter of economic considerations but, more important, a matter of political consideration (Salim, 2014).3 If we compare poverty incidence in developing and developed countries using the World Bank criterion of a minimum income of US$ 2.00 per day, we will find that absolute poverty is a problem of developing countries only. The World Bank’s vision of “a World without Poverty” would be unachievable if relative poverty were the only definition concerned. How can small farmers in developing countries be guided out of absolute poverty? Different treatments in relation to agricultural protection have been used for the (relative) poor groups in developed and (absolute) poor families in developing countries. Relatively poor farmers in developed countries, in much smaller numbers, have benefited from better supporting policies to increase their value added and protect their incomes. They, basically, even without any support, are able to compete in the global arena with small farmers from developing countries. These relatively poor farmers in developed countries already enjoy comparative advantages in agricultural production (Moon, 2011). In addition, they utilise higher technology equipment, enjoy economies of scale and have much larger production yields in agriculture, as shown in Figures 5.1 and 5.2. 900.00 800.00 700.00 Technology-use Gap

600.00 500.00 400.00 300.00 200.00 100.00

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

0.00

EA&Pacific North America FIGURE 5.1

EU South Asia

ME&Naf SSA

Agricultural machinery including tractors per 100 sq. km of arable land

Source: Processed from World Bank data (2014).

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6000.00

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4000.00

3000.00

2000.00

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EA&Pacific North America FIGURE 5.2

EU South Asia

2007 2008 2009 2010 2011

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Cereal yields (kilograms per hectare)

Source: Processed from World Bank data (2014).

5.3 Different agricultural trade supports for small farmers in developing and in developed countries Trade policies limiting protection in agriculture are related to quantitative commitments of market access, which is easier to deal with at the World Trade Organization (WTO) negotiation table. Agricultural sectors remain highly protected in most trading countries. Why has this aspect not been discussed thoroughly at trade negotiations? There have been many multilateral trade negotiations: the Uruguay Round, the Doha Round, the Doha Development Agenda and their successive trade negotiations, but without any significant result. Under the WTO rounds of negotiation we have witnessed the tariffs on manufactured products decreasing significantly over time but not for agricultural products; the tariffs for these have not been changed substantially. The series of WTO negotiations were unresolved partly because of questions of how countries should protect their agricultural sector. Protection policies have been used by developed and developing countries but their intensity varies between countries. Developed (richer) countries tend to use protective measures such as subsidies to producers, high tariffs, and other non-tariff measures (Aksoy and Beghin, 2005;

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Moon, 2011; Weinberga and Bakker, 2012); developing (poorer) countries tend to use a taxing system (Aksoy and Beghin, 2005). The developing countries from the 1960s to the 1980s have significantly decreased protection for agriculture, in contrast to the modest reductions by Organization for Economic Cooperation and Development (OECD) countries. Developing countries made significant changes in direct protection such as tariffs and taxes and in indirect protection (that included monetary policy). About 28 per cent of domestic production in OECD countries is protected by import quotas with high, out-of-quota tariffs (Aksoy and Beghin, 2005). Developed countries have avoided serious reductions in agricultural protection (Hodur et al., 2003); they have given their agricultural sectors more protection than has been given by developing countries to theirs. Despite the decreasing number of tariffs and non-tariff measures, protection for agricultural sectors remains high and the methods used tend not to be transparent. In OECD countries, there is a kind of policy incoherence that comes from the relatively high support and protection given to agricultural sectors (Brooks, 2012). It is well recognised that developed countries, or groups such as the OECD countries, use the following three common instruments to support their agricultural sectors (Aksoy and Beghin, 2005). First, price support, for which the national government is responsible or bears the risk of price differences between domestic and international markets, including those resulting from tariffs and quantitative restrictions. The second instrument is direct support, which usually comes as direct production-related subsidies to farmers. The third instrument is support for research, training, marketing and infrastructure. This last instrument is the least contested support arrangement and occasions no protest from trade partners because these measures improve trade. Trade-supporting policies in OECD countries can be examined and measured using the Total Support Estimate (TSE) (Brooks, 2012). The TSE comprises a Producer Support Estimate (PSE) and a General Services Support Estimate (GSSE). The PSE is a means of guaranteeing to farmers prices that exceed the world market price and is by direct payments. The GSSE comes as budgetary support to agricultural sectors through research and development, human resources development, advisory systems and other support related to food standards and inspection. In addition to the PSE and GSSE, some governments in the OECD countries help poor consumers with food subsidies. Developing countries have applied similar measures under PSE but less intensively and with less support. In 2012, the PSE in global world trade had increased to 17 per cent of gross farm receipts. This was slightly more than for 2011 when it was 15 per cent (OECD, 2013). In terms of agricultural trade support and possible adverse effects for developing countries from protection policies in developed countries, Panagariya (2005) defends the position of developed countries and argues that their heavily subsidised agricultural sectors should not be seen as causes of the poor performance of the agricultural sectors in developing countries. Panagariya discusses six fallacies about

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protected agricultural sectors under a north–south dimension. One fallacy is that “agricultural border protection and subsidies are largely a developed-country phenomenon”.4 Whether Panagariya’s six fallacies are valid, we can foresee some difficulties for agrifood commodities from developing countries in getting (greater) market access in developed countries. In addition, there have been agrifood commodities from developed countries dumped on markets in developing countries (Dhar, 2007; Moon, 2011; Brooks, 2012). Panagariya’s six fallacies can be put to the test when considering current protection in agricultural sectors. In essence, developed countries are indifferent to developing countries when protecting their agricultural sectors. Protection for this sector is given for the following four reasons: first, protection stems from the realistic condition that most trading countries need to maintain their protection for domestic production in a way that promotes food security and sovereignty. In fact, agricultural trade has been secondary to the sovereignty goal. Second, protection is part of the effort to minimise the effects of market fluctuations in agricultural products (Dupraz and Postolle, 2013). The supply of agricultural products is commonly inelastic to changes in world prices. Because of such inelasticity, farmers have to pay the overall adjustment costs because factors of production are immobile and consequently they lose some possible trade gains. Third, protection is also related to labour absorption problems. The developed countries, which have adopted large-farm agricultural production, tend to have severe rural and urban unemployment (Lipton, 2013). The last employee group that agricultural protection helps is that of agricultural workers who are typically unskilled and low paid (Marjita, Karb and Beladi, 2007). Fourth, in addition to protection being for particular groups, governments protect their agricultural sector because of influence from other interest groups of rent-seekers, from farming institutions or from political parties that compete for economic and political benefits (Moon, 2011). Protecting farmers is frequently affected by political vote-gathering considerations. In addition, the denial and opposition to protection is also more from political groups.

5.4 Pro-poor development barriers of agricultural sectors in developing countries With their large numbers of poor farmers, developing countries have common problems, such as high dependence on natural resources (that the agricultural sector has a part to play in exploiting), poor infrastructure and possibly getting caught in the economic trap (Salim, 2014). Development in developing countries under globalisation is not as easy as in developed countries, especially in handling an uncompetitive agricultural sector. There have been some barriers to achieving satisfaction in this sector, which range from financial to non-financial and include institutional obstacles, imperfect information, uneducated and unskilled labour and failures in the market system. Some barriers to agricultural development in developing countries are discussed in the following section.

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5.4.1 A matter of financial resources Under trade liberalisation, tariffs are continually being reduced, but developing countries do not easily move to price–income support policies, such as subsidies and income transfers to the agricultural sector, as do developed countries. Subsidies in agriculture are a matter of how countries allocate their limited national or local budgets (financial resources) to farming. With their budgets constrained, developing countries have limited income sources and difficulties in budget allocation; meanwhile, developed or rich countries have been easily able to subsidise their agricultural sectors (Dhar, 2007; Moon, 2011). The limited revenue sources of developing countries have been partly a result of the decreasing tariff revenues. Tariffs were one of the predominant sources of revenue for developing countries two decades ago. In addition to the budget constraints, making adjustments is sometimes costly for rural communities in the development and implementation of particular agricultural policies. There is an additional burden: they need more time to adjust to rural and agricultural development as well as to alleviate poverty (Hodur et al., 2003). Under some budget constraints, developing countries may have difficulties in developing their agricultural sectors. So, it is necessary to have policies that are suited to agricultural and rural development. But these policies, whatever they might be, should not distort the relevant markets but provide for the good of the people in rural areas; for example, by improving rural infrastructure (Brooks, 2010). Input subsidies are also beneficial and financially feasible for developing countries; they let farmers plant good quality seed, cheap fertiliser and working capital and credit.

5.4.2 Market operation bias To improve the purchasing power of the poor, trade policies should be able to control fluctuations of domestic prices of agrifood products. Intervention in the market to induce price stability is still essential to protect the rural poor from worsening conditions. In most cases, the central and local governments of developing countries tend to intervene in market operations to control price increases of particular agricultural products. To some extent, these market operations to affect the price and distribution of some basic foods are feasible under a limited budget. The market operation in question is a kind of intervention policy that enables more agricultural products to be supplied directly to meet agrifoods demanded in the rural markets. Of course, with this policy, the government is paying the price subsidy (the difference between the market price and the price under market operation). The question remains: how effective is this kind of operation in controlling the market price? We can say that such an operation is effective if the effect of the price control lasts over the longer term (not just during the period of operation) and if the area the operation covers is extensive enough.

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Generally, these market operations are conducted in very limited areas, for traditional markets and for a short time, usually less than a week. This type of policy has not been so effective in controlling prices in the longer term; there are many negative effects that result from its implementation. One is speculation. Many speculators play the market to gain economic benefits by withholding stocks of products and not selling until the effects of the market operation have disappeared. This activity enables speculators to get a higher price by withholding supply and farmers are not the prime beneficiaries. The government should learn from this and use other policies rather than just market operations. Market operations for some specific products are easy to manage by the government; but they are a short-run way to stabilise market prices. In the longer run, this action is not very effective and tends to be wasteful. It leads to unstable and higher prices for agricultural products, specifically those reliant on underdeveloped and inefficient distribution channels and logistics sectors. Developing better distribution channels and logistics would be a more effective way to increase the share of value added to the farmers.

5.4.3 Infrastructure and logistics A high-cost economy is a common problem for most developing countries. Many factors contribute to a high-cost economy: corruption, ineffective distribution (expensive logistics services), ineffective bureaucracy, national and local regulations at odds with each other, conflicting interests of bureaucrats and other stakeholders, and more. A high-cost economy is also related to inadequate infrastructure and ineffective market institutions. To put it simply, logistics services are to distribute goods from the original sources (producers or farmers) to the intermediate users (processing firms) and thence to consumers. The longer distribution channels for agricultural products in developing countries could generate higher prices but with lower value added. This means that the added values generated do not give significant benefits to the economy, nor to the farmers. The higher prices of agricultural products are mostly enjoyed by middlemen who add no additional value. In many cases, the middlemen are just selling information about the products available to prospective buyers or end users. In return, they receive fees for their services or for information given to farmers and buyers. Under this farmer–middleman–buyer connection, the price of products might increase even though the position and the physical condition of products remains unchanged (that is, there is no value added). A longer distribution chain suggests strongly that the distribution of a particular product is not efficient. There are large numbers of middlemen in the distribution channels because of imperfect information for farmers and few ways for them to get information directly. There are many reasons for farmers not being well informed; less developed physical and logistics channels contribute to this. Small farmers have been hampered in getting access to infrastructure, finance, technical assistance and other inputs (World Bank, 2012). In addition, lacking

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education, economic resources and health care are some reasons that marginalise them from market information. A cutting-edge policy to reduce the obstacles in distribution channels can be promoted through the development of better infrastructure, which could improve the welfare of rural people. Better transport in rural areas could help farmers in selling their products direct to buyers (intermediate or final users or both).5 Further, better transportation might enable better information to flow to farming communities, which could increase their bargaining power with middlemen and buyers. Developing better institutions in rural areas would help farmers in terms of shared value added and income (Brooks, 2010). The volatility of food commodity prices needs government intervention to increase public investment in the agricultural sector, especially investment for developing rural agricultural infrastructure. The presence of public investment is a way to attract further private investment in rural and agricultural sectors, which have not been so attractive for private investors. Investment is important for the agricultural sector to achieve the goals of rural poverty reduction, food security, sustainable uses of natural resources and environmentally friendly farming systems (Vorley, Cotula and Chan, 2012).

5.4.4 Hidden protectionism: SPS and standards Tariffs are everywhere being reduced and this helps and encourages global trade. WTO member countries have put their trust in that organisation to organise globalised multilateral trade without significant barriers, either tariff or other barriers. However, non-tariff barriers, technical and other, have increased substantially over the past decade. Non-tariff measures that are being used increasingly are standards. The flow of trade under a free-trade regime increases more for standardised products than for non-standardised (Maskus and Wilson, 2000). The use of standards for traded products is compulsory to get access to markets and to win the global competition. To increase competitiveness and to be able to give protection to the consumers as well as producers (including small farmers), the government should promulgate strategic industrial and trade policies to this end. Food safety and other standards have metamorphosed to protective policies to block imports from developing countries, negating the benefits from the decline in traditional trade barriers, that is, tariffs and quantitative restrictions (Hooker, 1999; Jongwanich, 2009). The original objective for applying standards for food safety was not solely motivated by the need to protect human health, but it has deviated to being a protective measure from open global competition. Food safety regulation, including standards, determines the access for products from developing countries to markets in developed countries, especially for high-value fresh commodities (Caswell, 2003). The presence of sanitary and phytosanitary (SPS) standards, and of non-trade concerns, are principally to limit access to markets (Gorter et al., 2003).

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There have been many cases of agricultural products being rejected for the markets of developed counties, such as the US and the EU, because of trade-related quality standards. Most were fishery and horticultural products from developing countries that did not comply with the standards and quality requirements in the destination countries. Legal texts of SPS and associated WTO documents related to food safety and standards basically give guidance for trading countries to ensure that transactions are transparent and competition is fair. Under the conditions of globalised trade, developing countries are facing many challenges to continue to have market access to developed countries for their agricultural products. The challenges include more of, and the increasing use of, food safety requirements and standards in developed countries. Meeting the more rigid, stringent and frequent changes to health-related protection and related requirement is very costly for developing countries ( Jongwanich, 2009). The frequent change to standards and requirements (because of the income, preferences and health standards of the people in the importing country) is basically legal under the WTO Agreement on Technical Barriers to Trade. But this agreement has been abused as much as used: documents have been interpreted in such a way as to protect domestic markets (agricultural sectors) from overseas competition, even though scientific evidence is necessary before standards may be altered. In effect, access by developing countries to the markets of developed countries is restricted. For reasons not quite apparent, the WTO allowed flexibility in the standards of member countries. But, with the WTO’s goal of world trade without any barriers, have trading countries worked and striven to reach that goal? In Article 20 of the General Agreement on Tariffs and Trade–WTO, the WTO gives special leave to its member countries to make their own national policies to protect human health, animals, plants and the environment as a whole. There are no general minimum standards specified that countries can apply when developing their own protective measures. Each WTO member has its own standards and these can cause distrust between trading countries. The WTO prohibits its members from applying hidden protection, but many countries use health protection as a barrier to protect their industries and domestic markets from international competition. In addition, different from the imposition of tariffs and quotas, the application of standards, SPS and other health requirements to agrifood, tends to be less than transparent for foreign competitors ( Jongwanich, 2009). Even though with more transparency, developing countries might still have difficulties meeting the overall requirements of standards, SPS and food safety regulations.6 Although it is discouraging in the way the present standards are applied by developed countries, there are some positive effects for developing countries. Increasing specificity of standards and SPS requirements can encourage and push developing countries to improve the quality of their products. Further, higher standards could create higher added value and competitive power (Mutambi, 2008). Of course, good farming practices, well-developed irrigation systems and other infrastructure are

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the basic conditions that need to be promoted seriously by central and local governments in developing countries.

5.4.5 Product inspection in the domestic market Inspection of products in their domestic markets is still a problem for developing countries. In addition to the implementation of standards, product inspection is important to protect local farmers and producers in domestic markets as well as to protect human health from sub-standard and unqualified products and foods. Sub-standard and non-standard foods that are brought to the domestic market illegally; goods that are smuggled, falsely documented or counterfeit, can and have damaged human health and property. There are many reasons for smuggling: to avoid tax, or to take advantage of higher selling price differences (price disparity) in international markets. Price disparity may come from imposed taxes and bans on exports of raw materials that are applied by some developing countries. The national borders of developing countries (either sea or land borders) seem to be the favourite place to smuggle proscribed products into or out of the domestic markets. One of the reasons is that at these border control points, inspections are loose and poorly controlled because staffing and technology are not adequate. Items most frequently smuggled are consumption goods; food and other agricultural products predominate. The border controls are not effective in preventing goods being smuggled out of a country. The most common goods smuggled out of a country are from primary industries or of natural resources such as mining products, forestry and other raw or basic commodities. Developed countries, like the US and those of the EU, have well-established early warning systems that work automatically when illegal and unstandardised products cross their borders. The US Food and Drug Administration and the EU’s Rapid Alert System for Food and Feed (RASFF) are the two inspection bodies that control the flows of goods to their domestic markets. When an illegality is discovered, the RASFF sends the information to all member countries and asks for necessary preventive action. What about similar institutions in developing countries? Few developing countries have well-developed early warning systems and, for most such countries, such systems are still in the early stages of development. How does smuggling have detrimental effects on the economy, especially for small farmers? A flood of imported agricultural products depresses the price of uncompetitive domestic agrifoods. The continued decreases in the selling price tend to reduce the incentives for poor farmers to produce similar commodities, even though what they produce is for their own use. Furthermore, in the long run, if the trend continues, there will be far fewer farmers to plant and harvest particular agrifood crops. One implication of this set of circumstances is that there be an absolute or high dependency on imported products, which over time and without security of income sources creates a kind of structural absolute poverty for households of poor farmers.

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Apart from being the common method for preventing smuggling, product inspection at national borders is the principal method used by governments to control the flow of goods across borders. Increasing the authority and powers of customs officers and border inspectors, developing infrastructure at seaports and airports, and economic development in general must be given priority.

5.5 How could trade help the poor? Trade is open to all commercial groups and farmers in trading countries but, because of all the limitations to factors of production, to farming techniques and to management that small farmers are subject to and that have reduced competitive advantages, global trade has destroyed livelihoods in rural areas. This argument is valid not only for developing but also developed countries. Trade liberalisation under the WTO has shifted the paradigm of agriculture from production-driven to market-driven (Sharma, 2004). With market-driven agriculture, we have been seeing that those commercial organisations that have greater access to capital, and those that have larger land holdings and greater support are able to realise greater gains from trade liberalisation. All trading nations give special treatment to their agricultural sectors but generally they want to be seen to act according to the legal and other requirements of the WTO. Cline (2004) contends that when some of the biases and distortions were removed, global free trade could give developing countries a chance for long-term gains. Surprisingly, more than 50 per cent of the gains would result from the removal of protection in developed countries for specific products, especially agrifood products.7 Cline argues that trade opportunities should be given first to risky low-income countries that comprise the Heavily Indebted Poor Countries (HIPC), the Least-Developed Countries (LDC), and the countries of sub-Saharan Africa (SSA).8 Statistically, we cannot detect easily the relations between trade liberalisation and rural poverty because they are many, complex, and indirect (FAO, 2005; Ghosh, 2005). There are many factors influencing or controlling this complex relation; among them are external factors from international markets or domestic factors related to supply capacities and income distribution within the countries. The price market transmission cannot be relied on solely to ameliorate the effects of trade on impoverished farmers and their families. The effects of trade on poverty and food security depend on country-specific factors, which include the particular circumstances and locations of poor and food-insecure families, and the specific policies that each country might apply. Among domestic factors, in developing and in developed countries, government policies for their agricultural sector and for rural development are key factors in determining the direction and the results of the relation between trade and rural poverty. An overwhelming consensus of analyses might come to wrong or unwise solutions for the plight of the poor. Whether we agree on market-distorting policies applied by trading countries, the simultaneous reform of import and

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export regimes must be accompanied by domestic support for the populations of poor, small farmers. In the political-economic context, comprehensive agricultural liberalisation might not be feasible because of the consequences of increasing prices, in general, for poor farming families (Athukorala, 2000). The transitional problems from agricultural liberalisation must be minimised with an effective short-run distorting policy over agricultural sectors. In examining the discussion about the countries that protect their agricultural sectors, we can see evidence for the “development paradox”, as stated by Weinberga and Bakker (2012). “Development paradox” is the term used to describe a positive relation between income and protection in agriculture. Economic development is a dominant factor in controlling protection in agricultural sectors. The protection is needed because this sector is economically and politically important. The agricultural sector’s relative contribution to the economy decreases as economic development progresses. But this decreasing contribution does not mean that the sector is less important. With the huge number of labourers and small farmers, it is necessary to give incentives to the agricultural sector to enable it to survive and to increase its contribution. The fundamental humanitarian reason is related to the need of any country to ensure that basic food needs are met, no matter how poor the people are. Agriculture, even though its share in the GNP becomes relatively smaller as economic development progresses, is still interesting and important in that it involves bargaining and trade-offs between political, economic and social interests.

5.5.1 How do we help the poor? In principle, Article XIX of the General Agreement on Tariffs and Trade (GATT) gives national governments opportunities to protect human, animal or plant life from adverse effects of trade. This article of GATT gives trading countries authority to take any action in an emergency when a country is facing conditions of uncontrolled imports that will harm domestic producers and farmers. Emergency action is basically to prevent or remediate the effects of trade (imports) on uncompetitive domestic producers and farmers. In addition, the Agreement on Agriculture (AoA) has given trading countries the chance to support their rural sectors with measures that do not cause distortions to trade. Flexibility in the application of GATT varies from developed, to developing, and to least-developed countries, but still the developing countries or even least-developed ones are not able to take advantage of the exemption rules, even though extra time is allowed to them. Other exemptions to Article XIX are outlined under the ministerial decision on measures concerning the possible negative effects of reform programmes on the least-developed and net food-importing developing countries and on modalities for the establishment of specific binding commitments under the reform programme. The ministerial decision recognised that there is a possibility of

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difficulties for least-developed and net food-importing developing countries that can come from external sources and free competition in trade in basic foodstuffs. By this condition, then, the rule tries to give special treatment for least-developed and net food-importing developing countries to secure a proportion of basic foodstuffs in the name of grant form and food-aid programmes. This provision conforms to Article IV of the Food Aid Convention 1986. In addition, the leastdeveloped and net food-importing, developing countries have a chance to improve their agricultural productivity and infrastructure in rural areas with proper technical and financial assistants from other trading (developed) countries. The modalities related to the establishment of specific binding commitments allow developing countries to be flexible in reducing tariffs in the contexts of market access, in domestic support and in export competition. Further, the leastdeveloped countries have extra exemption by having no commitments to reduction. The ministerial decision and modalities for least-developed and developing countries give extra space for them to develop their rural sectors with higher productivity and better infrastructure. From those overall special and differential treatments, to what extent have developing countries abided by these rules? Empirically, not all developing countries have recognised the rules and used them effectively to protect their human and their environmental resources. Meanwhile, the developed countries with all their economic capacities and abilities employ Article XIX as a tool to protect human, animal and plant health based on the WTO principles.

5.5.2 Current global treatment and the way forward The current regime of international agricultural trade is still not transparent and must be clarified at the next round of negotiations (Gorter et al., 2003). The effort to minimise protection and promote more transparent multilateral trade negotiation may be conducted under the WTO rounds of negotiation or under specific regional trade negotiations. It seems that the WTO has no power to control or prevent produce from subsidised farming in developed countries being dumped on the markets of developing countries (Barker, 2007). In addition, small farmers, together with large corporations, have been lobbying strongly for the implementation of support policies and to influence any trade negotiations (Hodur et al., 2003; Lipton, 2005). In effect, this lobbying and the ability of large agricultural organisations to achieve economies of scale might destroy the livelihoods of the poor in developing countries (Lipton, 2005). From this standpoint, it means that the goal of the WTO Agreement on Agriculture (AoA) of creating more effective competition among groups of developed and developing countries, is still far from being met. The AoA did not have any power to limit support for agriculture in rich countries nor to enable better opportunities for market access for developing countries. The AoA was to create opportunities for further trade negotiations despite the lack of political will from the rich countries to implement the agreement; it is used to enable exceptions to the rules for

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themselves (FAO, 2003). There should be leeway for developing countries to adapt their agricultural policies and practices to their needs rather than endorsing full liberalisation or even the “Washington Consensus”. This consensus, which was supported by the World Bank and the IMF, was a substantial and expensive lesson for African countries that adopted industrialisation, together with privatisation and deregulation, which came at the cost of agricultural development. African agriculture is still behind the rest of the poor developing countries (Moon, 2011). Devereux (2009) argued the there was a case of wrong treatment to the poor in relation with trade liberalisation. Misdiagnosis by African governments on problems related to agricultural liberalisation by implementing the Washington Consensus contributed to the under-performance of agriculture in their countries. The under-performance was because of the excessive dependency on market-based food security practices and the withdrawal of the state’s influence on the agricultural system. This situation was exacerbated by the absence of proper protection for small farmers. Farmers from developing countries have no ability to compete on similar terms with their rivals from middle-income and developed countries who are firmly subsidised under well-established financial services, farming technology and infrastructure in rural areas. Subsidised agricultural products from developed countries dumped on the markets in developing countries further lower the returns of farmers in those countries. Even though, under the condition that rich countries abolish trade restrictions and create duty-free market access for agricultural products from developing countries, the market distortions would remain. This is partly because the theoretical foundation of AoA is of market-based transactions and ignores the inelastic demand and supply in agriculture (FAO, 2003). People with no purchasing power still need food; there are no exceptions. The strong assumption in the AoA of equal infrastructure development and investment denies inelastic supply in agriculture, which is very sensitive to climate change and other environmental conditions. In addition, the FAO envisaged that, under an integrated agricultural system, the smaller number of multinational corporations would tend to dominate international trade and supply chains of food to the global markets. So, the objective of the AoA of a fair market-oriented system has still far to go for the negotiating members.

5.5.3 Challenges for food security and food sovereignty Food security is to ensure that all people at all times have sufficient safe, nutritious and affordable food.9 Members of the WTO, after several rounds of negotiations but with no agreement, have tried to ensure food sovereignty for their home countries. The idea of food sovereignty is to promote and to empower developing countries to resist and to restrict the risk of destabilisation of local agricultural production from imports (Dupraz and Postolle, 2013). The bad experience of agricultural markets, related to escalating prices of agricultural products and limited world supply, has given a way for the trading countries to rearrange their agricultural development in general and food security in particular.

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Many trading countries have developed and promoted policies to increase and improve self-sufficiency by promulgating input-subsidy programmes (Gouel, 2013). Increasing world prices of agricultural products should be a fundamental reason to rearrange the global trade agreements and to improve and increase agricultural development. How might we promote and achieve food sovereignty? In the long run, can food sovereignty rely solely on imports? The answer is, of course, no. Food sovereignty must be ensured by developing domestic production with enough genuine protection so that small farmers and their families and, in general, the developing world might avoid the consequences of instability, fluctuations and unfair trade practices in agricultural markets. How can countries minimise the risks of fluctuating prices and unstable conditions of production? Gouel (2013) discusses one policy: to increase self-sufficiency and price stability by creating an organisation for the management of public stock. Such public stock can be preserved by eliminating economic profits from speculation and crowding all private storage out. This concept seems reasonable and reliable and from which, in the short run because there is ‘transitional stock build-up’, the producers will enjoy higher prices. In the long run, the producers might face lower prices because of the need to ensure stable prices. But, in aggregate, the community will enjoy stable prices with large (or enough) stocks of food. The relation between trade policy and food security is complex (FAO, 2005). On the demand side, poor households (consumers) in developing countries can benefit from lower priced, imported food; on the supply side, imported commodities are often not in direct competition with local products because of market segmentation. In this situation, the FAO (2003) has argued that an increase in cheap and subsidised imports (from developed countries) is not always a threat to local producers. In addition, Tutwiler and Straub (2005) argue that a country with a larger share of agricultural trade to agricultural production tends to have fewer malnourished people and underweight children.10 This statement might be true in the situation in which exports comprise the excess of domestic production and the commodities exported are those consumed domestically. There are concerns about some projects in developing countries that involve planting and harvesting commodities that are not consumed in the home country but instead are exported. Such crops are to meet foreign demand only. In this case, these food commodities do not improve national food security; malnutrition would not be alleviated. The factors of production used in producing agricultural goods that are for export only are, by definition, unavailable for producing food and, to that extent, poor rural households are worse off because the export income generated is unlikely to be allocated for their economic betterment. In the long run, how might poor families enjoy lower-priced imported foods while preserving their income from their subsistence production? As is so often the case with those in the lower-income groups, most of their income is used for their basic consumption needs, food in particular. So, in the long run, imported food is a threat to their production and to their only source of income, farming.

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5.5.4 Why do poor small farmers need special treatment? The agricultural sector is home for poor people in developing countries. Better treatment through trade-related policies that could increase their productivity and incomes would benefit them either as small farmers or as workers in this sector. Consigning them to the conditions of a ‘perfect’ market and ignoring their heritage will allow unsustainable dependence on imported food and global charity. From this standpoint, negotiating fairer global trade conditions (that do not assume a perfect market) would improve welfare for small and landless farmers who live and work in the rural areas of developing countries. The poor in agricultural sectors should not be seen or treated in terms of market-based concepts only. However, a twin-track approach by the FAO (2005) to reduce poverty and hunger might fail where the market mechanism does not function.11 Market and non-market institutions have damaged poor families because the current institutions, especially market institutions in rural areas, have not worked well (Braun and Mengistu, 2008). Market failures are common in poor countries (Brooks, 2010). Kydd (2002) considers that the cause of market failure in rural areas is restricted or inadequate information and missing enforcement mechanisms. This is related closely to institutional factors, in which supporting institutions are absent or ineffective. So, protection might be a way to make corrections for market failures. With the limited resources of poor countries, it is difficult for them to overcome problems quickly; problems that might be caused by underdeveloped and weak market institutions and infrastructure that are unable to support the distribution of goods and services in rural areas. The establishment and empowerment of institutions to help the poor would increase rural development effectiveness and help to alleviate poverty in rural areas (Hirano and Otsubo, 2013). These institutions would support the trade-related policies to increase the welfare of small farmers. Absolutely free trade is not suitable for developing countries. Inelastic supply and demand in the markets for agricultural commodities in developing countries is one reason. Small-scale farmers with limited landholding and little access to finance (and less attractive to [foreign] investment), are influencing factors for small farmers, who are price takers in their markets. The large numbers of them are of no consequence to the small number of corporations that control the global supply chains (FAO, 2003). The position of small farmers is still important. Even though their subsistence production is limited, it remains the main source of nutrition, food security, income stability, employment and income in poor countries (Lipton, 2013). Policies and programmes for increasing protection for small farmers, like those that have been implemented by developed countries, are not the best or the most effective way. For example, even though with limited imported food products or without imports, protection is a cause of price increases in domestic markets. This is because the rural communities of landless farmers, small farmers, and poor

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urban households as well, are net buyers of food (Hodur et al., 2003; Moon, 2011). Protective policies that favour the poor could be combined with food security and rural development policies. Such measures can be applied through any instruments that could easily turn an increase in the volume of agricultural products into a high possibility of income redistribution from consumers to poor farmers. Such an instrument need not allow the possibility of increased prices affecting the purchasing power of poor consumers (Dhar, 2007).12 Policies that favour the poor in agricultural trade and development, in the name of food security and rural development, are essential to create benefits for poor farming families. It is crucial to have this kind of protection for agricultural products to reduce poverty resulting from global trade. Any effort that developing countries make to improve the livelihoods of the vast majority of their population needs global trade cooperation. There are some trade-related policies with respect to the adjustable market system that could help thesmall farmers enjoy the benefits of globalization. a.

b.

The policies of the market system approach would be effective if the market institutions and infrastructure were well developed in rural areas. The lack of functioning institutions in rural areas hampers supply and demand. The limited budgets of local and national governments seem to be a common problem in providing public goods in rural areas. Then, inviting (foreign) investors could be another solution. But, how would investors fare in rural areas with all the current limitations of transport and infrastructure and with no or few public goods? So, this situation could not be simply rectified by opening the markets and flooding them with imported products. Accordingly, the development of effective market institutions and infrastructure will enable small farmers to enter the market system. Even though they are small farmers, their production does not supply agricultural products and food to the markets. They produce food but it is limited in quality and quantity. Food shortages cannot be overcome by recklessly importing products. Irresponsible imports, in fact, tend to drastically reduce farmers’ productivity and are a disincentive for them to continue farming on their land. In other words, imported food is just a way to create an absolute dependency on foreign markets without any increase in purchasing power. This could happen in the long run because farmers do not have sufficient resources to improve their production methods.

5.6 Conclusions Agricultural sectors still play significant roles in the economic development of most developing countries even though their share of value added to world GDP is small. The importance of this sector to developing and developed countries entails effort to give agricultural sectors, especially in relation to agrifood, special treatment in global trade. Developing countries must do more than just giving their agricultural sectors status as the predominant sector but pay more attention

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to agriculture’s development and, equally, proper attention to those who work in the sector: the deprived and underprivileged groups, that is, poor, small-scale farmers and their families. Until recently, there has been no single or universal criterion to determine who qualifies as a small farmer; but, a landholding of under 2 hectares or of none at all can be used as an indicator. Agricultural support programmes, those that are based on producer support estimates (for example, those of OECD countries) have not been considering the size of farm landholdings. To be in line with the promotion of freer trade, support for agricultural sectors must be decreased, but not for those sectors in developing countries where production is by small farmers. In this world of global trade, developing countries have been challenged to reap the benefits of globalisation amidst the increasing number of non-tariff barriers and heightened competitive pressure in world trade. Although often without clear intention to reduce the flows of global trade, trading countries tend to be more protective especially on the issues of agriculture and food-related products. Different characteristics and existing treatments for small farmers in developing and developed countries require that empirically adjusted trade policies are needed because a (full) market system is inappropriate to help them. Therefore, choosing a proper set of trade strategies is crucial to respond to this common challenge and to maximise the benefits and minimise the detrimental effects of globalisation for the small farmers and poor families. Agricultural development itself must be promoted to have a higher, and better distributed, value added for these groups. The development could come from supply and from demand sides. On the supply side, the development of infrastructure, rural supporting institutions and better distribution channels for agricultural products are essential to increase the flows of information and the share of value added for small farmers. On the demand side, to be better off in the globalisation era, poor families need to be empowered to have greater productivity by supportive measures such as the provision of subsidised, good quality seed, farming equipment, and producer support estimates. Their limited ability to pay must be protected from the uncertainty of world prices.

Notes 1 The categorisation of developed, developing and least developed countries is made according to the definitions of the World Bank. In practice, in this chapter, the term “developing countries” covers least-developed and developing countries. 2 They own less than 2 hectares and many are just working as family workers and with uncertain pay. Small-scale farmers, around 500 million, support the livelihoods of almost two thousand million people (Vorley, Cotula and Chan, 2012). 3 Poverty lines have been used to show the success of the current or incumbent governments and rulers. Of course, economic development continues but is at times below the expectations of the government. One government goal is to reduce poverty. The World Bank uses the criterion of US$ 2.00 per day as the poverty line. Applying the World Bank poverty line in many undeveloped countries would show enormous numbers of people in poverty. So, to persuade the public that the government has

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4 5 6 7 8

9 10

11

12

been successful in driving poverty down, the easiest way is to use a figure lower than that of the World Bank. Indonesia is an example of this situation; its government has never used the US$ 2.00 poverty line but a lesser figure. The current poverty line used in Indonesia is just around IDR 260,000 per month (BPS, 2014), which is equal to 80 cents per day. For further details of the six fallacies, please refer to Panagariya (2005). Intermediate use here refers to the use of agricultural products as an input to produce different products (or with additional value added). Food safety regulations are to protect human health stemming from food handling, preparation, and consumption and they have become a mandatory control for food entering the markets (Hooker, 1999). The long-term gain from trade would be around US$ 200 billion a year (Cline, 2004). The contents of imports to developed countries coming from developing countries have poverty intensity. The weighted average of poverty intensity is around 45 per cent from imports from the at-risk group of poor countries (HIPC, LDC and SSA); but from the other developing countries it is around 7 per cent, which is less intense. In addition, poverty reduction through the removal of protection could create economic growth in developing countries; and this additional growth in developing countries could reduce their poverty by 2 per cent (Cline, 2004). This definition refers to FAO (the World Food Summit in 1996). Less integrated economies (with great numbers of people in hunger) have limited capacity to import particular foods. Tutwiler and Straub (2005) presented data that show that countries where malnutrition is common, imported less than 10 per cent of their food commodities, but countries with better food security have imports of more than 25 per cent. As such, the twin-track approach (FAO, 2005) is to (a) create opportunities for them through agricultural development from policy reforms and investments; and (b) to ensure direct and immediate activity to combat hunger in the short run. This means that the second track would be relying more on charity in the very short run. Dhar (2007) investigated the use of some protective instruments, such as Special Products (SP) and Special Safeguard Mechanism (SSM). By having “strategic” interventions, the developing countries could easily achieve their development goals.

References Aksoy, M. A. & Beghin, J. C. (eds) (2005). Global Agricultural Trade and Developing Countries. Washington, DC: International Bank for Reconstruction and Development/World Bank. Athukorala, P. C. (2000). Agricultural Trade Policy Reform in South Asia: The Role of the Uruguay Round and Policy Options for the Future WTO Agenda. Journal of Asian Economics, 11, 169–193. Badan Pusat Statistik (BPS). (2014). Poverty Data. Downloaded on 12 January 2014 from http://bps.go.id/tab_sub/view.php?kat=1&tabel=1&daftar=1&id_subyek=23¬ab=1 Barker, D. (2007). The Rise and Predictable Fall of Globalized Industrial Agriculture. A report from the International Forum on Globalization. International Forum on Globalization (IFG). Braun, J. V. & Mengistu, T. (2008). Poverty and the Globalization of the Food and Agriculture System. In J von Braun and E Díaz-Bonilla, Globalization of Agriculture and Food: Causes, Consequences, and Policy Implications. New Delhi: Oxford University Press, 2008. Brooks, J. (2010). Agricultural Policy Choices in Developing Countries: A Synthesis. In Global Forum on Agriculture. Policies for Agricultural Development, Poverty Reduction and Food Security, OECD Headquarters, Paris. 29–30 November 2010.

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——— (2012). Policy Coherence and Food Security: The Effects of OECD Countries’ Agricultural Policies. In Global Forum on Agriculture: Policy Coherence for food Security in Developing Countries, OECD Headquarters, Paris, 26 November 2012. Caswell, J. A. (2003). Food Safety in Food Security and Food Trade: Trends in Food Safety Standards and Regulation: Implications for Developing Countries. FOCUS 10, Brief 4 of 17, September 2003. International Food Policy Research Institute. Cline, W. R. (2004). Reducing Poverty. The Magazine of International Economic Policy. Washington, DC: The International Economy Publications, Inc. Devereux, S. (2009). Agriculture and Social Protection in Africa. Future Agriculture Policy Brief. Policy Brief 027, March 2009. Future Agricultures Consortium. Dhar, B. (2007). Agricultural Trade Protection: A Perspective from India. ARTNeT Policy Brief, Brief No. 11, January 2007. Dupraz, C. L. & Postolle, A. (2013). Food Sovereignty and Agricultural Trade Policy Commitments: How Much Leeway do West African Nations Have? Food Policy, 38, 15–25. European Commission. (2013). Agriculture and Rural Development. Accessed on 28 December 2013 from http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/ Farm_structure_statistics FAO (2003). Trade Reforms and Food Security: Conceptualizing the Linkages. Rome: FAO. ——— (2005). The State of Food And Agriculture: Agricultural Trade And Poverty – Can Trade Work For The Poor? FAO Agriculture Series No. 36. ——— (2010). Characterisation of Small Farmers in Asia and the Pacific. Asia and Pacific Commission on Agricultural Statistics, APCAS/10/28, April 2010. ——— (2014). FAOSTAT Database. Accessed on 5 February 2014 from http://faostat3. fao.org/faostat-gateway/go/to/home/E. Ghosh, J. (2005). Trade Liberalization in Agriculture: An Examination of Impact and Policy Strategies with Special Reference to India. Background Paper for Human Development Report 2005. Gorter, H., Ingco, M., Ignacio, L.,& Hranaiova, J. (2003). Market Access: Agricultural Policy Reform and Developing Countries. Trade Note September 10, 2003. No. 26924, the World Bank Group. Gouel, C. (2013). Optimal Food Price Stabilization Policy. European Economic Review, 57, 118–34. Hirano, Y. & Otsubo, S. (2013). Pro-poor Institutions for Development Effectiveness: Cross-Country Empirical Analyses and a Case Study of Ethiopia. 24th JASID Annual Conference, 2013. Hodur, J., Diao, X., Diaz-Bonilla, E., & Robinson, S. (2003). How Much Does It Hurt? The Impact of Agricultural Trade Policies on Developing Countries. Washington DC: International Food Policy Research Institute, 2003. Hooker, N. H. (1999). Food Safety Regulation and Trade in Food Products, Food Policy, 24, 653–68. Jongwanich, J. (2009). The Impact of Food Safety Standards on Processed Food Exports from Developing Countries. Food Policy, 34, 447–57. Kydd, J. (2002). Agriculture and Rural Livelihoods: Is Globalisation Opening or Blocking Paths Out of Rural Poverty? AgREN Network Paper No. 121 Agricultural Research and Extension Network, January 2002. Lipton, M. (2005). The Family Farming a Globalizing World: The Role of Crop Science in Alleviating Poverty, 2020. Discussion Paper 40, International Food Policy Research Institute, June 2005.

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——— (2013). Staples Production: Efficient “Subsistence”Smallholders are Key to Poverty Reduction, Development, and Trade. In UNCTAD Global Commodities Forum 2013: Recommitting to Commodity Sector Development as an Engine of Economic Growth and Poverty Reduction. Room XVIII Palais des Nations, Geneva, Switzerland. Marjita, S., Karb, S., &Beladi, H. (2007). Protectionary Bias in Agriculture: A Pure Economic Argument. Ecological Economics, 63, 160–64. Maskus, K. & Wilson, J. (2000). Quantifying the Impact of Technical Barriers to Trade: A Review of Past Attempts and the New Policy Context. Paper presented at the World Bank workshop Quantifying the Trade Effect of Standards and Technical Barriers: Is It Possible? Washington, DC, 27 April. Mazoyer, M. (2001). Protecting Small Farmers and the Rural Poor in The Context of Globalization. Rome: FAO. Moon, W. (2011). Is agriculture Compatible with Free Trade? Ecological Economics, 71, 13–24. Mutambi, J. (2008). Advancing Value Addition and Competitiveness through Standardization to Promote Manufacturing. Proceedings of the 2008 Annual International Standards Conference (AISC) June 09th - 12th, 2008, Kampala Uganda. Accessed on 5 February 2014 from http://cedat.mak.ac.ug/wp-content/themes/CEDAT-Theme/ Publications/Advancing%20Value%20Addition%20and%20Competitiveness%20 through%20Standardization%20to%20Promote%20Manufacturing.pdf OECD (2013). Agricultural Policy Monitoring and Evaluation 2013: OECD Countries and Emerging Economies. OECD Publishing. Accessed on 28 August 2013 from http:// dx.doi.org/10.1787/agr_pol-2013-en Panagariya, A. (2005). Agricultural Liberalization and The Least Developed Countries: Six Fallacies. In David Greenaway (ed.), The World Economy, Global Trade Policy 2005. Boston: Wiley-Blackwell. Salim, Z. (2014). Indonesia’s Ways to Sustainable Economic Growth and Development. In R. E. Looney (ed.), Handbook of Emerging Economies. London and New York: Routledge. Sharma, R. (2004). Strengthening Agricultural Support Services for Small Farmer. Report of the APO Seminar on Strengthening Agricultural Support Services for Small Farmers held in Japan, 4–11 July 2001 (SEM-28-01). Asian Productivity Organization, 2004. Thapa, G. & Gaiha, A. (2011). Smallholder Farming in Asia and The Pacific: Challenges and Opportunities. Paper presented at the IFAD Conference on New Directions for Smallholder Agriculture, 24–25 January, 2011. Tutwiler, M. A. & Straub, M. (2005). Making Agricultural Trade Reform Work for The Poor. IPC Position Paper, June 2005. International Food and Agricultural Trade Policy Council. Vorley, B., Cotula, L., & Chan, M. K. (2012). Tipping the Balance: Policies to Shape Agricultural Investments and Markets in Favour ff Small-Scale Farmers. Research Report, December 2012, accessed on 14 September 2013 from www.iied.org Weinberga, J. & Bakker, R. (2012). Betting the Farm on High Food Prices: A Consumer Based Approach to Agriculture Protection. Social Science Journal, 49, 191–201. World Bank (2012). World Development Report 2012: Gender Equality and Development, Washington, DC: World Bank. ——— (2014). Databank. Accessed on 4 February 2014 from http://data.worldbank.org/ indicator#topic-1

6 GLOBAL ENVIRONMENTAL MANAGEMENT Globalization of the economy and load on the global environment Kiyoshi Fujikawa and Hikari Ban

6.1 Introduction Contemporary international society has been characterized by the realization of many economic partnership agreements (EPAs) such as the Trans-Pacific Strategic Economic Partnership Agreement (TPP). EPAs expand not only trade but also foreign direct investment (FDI), which is complementary with trade, and which is expected to encourage the economic and environmental structure of the host country. This study examines how the expansion of trade and FDI affects the global economy and natural environment (such as with the CO2 load). Thereby, the chapter analyzes EPAs between Japan and countries of the Association of Southeast Asian nations (ASEAN); one example of a relevant EPA is the ASEAN– Japan Comprehensive Economic Partnership.1 The expansion of trade and FDI influences markets for goods and services and production factors in a multitude of ways across industries. That is why application of the computable general equilibrium (CGE) model is useful.2 However, while there are many examples of CGE analyses of the effects of a free trade agreement (FTA), there are few CGE analyses on the effects of FDI. One reason for this scarcity of research is that CGE modeling of FDI is not only inherently difficult but also marked by a lack of relevant databases of FDI and multinational corporations.3 Most CGE models do not explicitly address FDI. However, some CGE models address the mobility of international capital. For example, the Global Trade Analysis Project model (GTAP) is an accepted CGE model allowing for the analysis of economic relationships among countries. In the standard GTAP model, regional savings are assembled at the global level and investments are distributed to each region. Although capital movements among countries remain

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as endogenous variables, FDI can be partially analyzed by treating international capital movements as exogenous variables. Previous research had used the GTAP model to examine the economic effects of FDI. Ban et al. (1998) analyzed the economic impact of FDI on technological progress from Japan to Asian countries. The authors examined the impact of a 1 percent increase in capital outflow from Japan to Asian countries and a 1 percent improvement in technological progress in manufacturing industries in host countries. Our study uses the GTAP-E model (an energy-environmental version on the GTAP model) and GTAP Data Base Ver. 8.1, matching the 2007 baseline to simulate FTA, FDI, and energy-efficient technology transfers. Here, we refer to an important study by Ban et al. (1998). The second stage of this study conducts an international input–output (I-O) analysis. International I-O analysis allows us to examine how CO2 directly emitted by one county’s production can be ultimately attributed to another county’s consumption. In other words, I-O tables reveal the interdependence of the CO2 load;4 however, the GTAP Data Base does not describe cross-border trade between industries. Next, the study estimates the ex-ante and ex-post international I-O tables regarding EPAs. These tables also enable us to investigate how the expansion of trade and FDI influences the international distribution of carbon emissions. Chapter 6 is organized as follows. Section 6.2 briefly explains the GTAP-E model and GTAP Data Base used in this chapter. Section 6.3 describes the simulation steps, and Section 6.4 reports the results of our simulation analysis. After explaining basic international I-O analysis in Section 6.5, in Section 6.6, we report the structural change in international distribution of carbon emissions caused by EPAs. The final section summarizes our results and offers some conclusions.

6.2 The GTAP-E model and database To investigate the economic and environmental impacts of FTA and FDI between Japan and ASEAN countries, we use the GTAP-E model and GTAP Data Base. This section briefly describes their components.5

6.2.1 The GTAP-E model Amid ongoing economic globalization and the increasing importance of quantitative analysis, GTAP was established in 1992 at Purdue University. The project contains the construction of a database and a standard global CGE model available publicly, development of application software to use them easily, and promotion of worldwide research networking. Additionally, GTAP has developed a CGE model and a database for environmental and energy research. Energy volume data were introduced into the GTAP Data Base Ver.5 and a CO2 emissions database was introduced in version 8. The

202 Kiyoshi Fujikawa and Hikari Ban

standard GTAP model had not considered energy substitution, which plays an important role in linking economic activity with energy and environment. In contrast, the GTAP-E model incorporates energy substitution into the standard GTAP model to better represent the economic linkages between energy and the environment. In addition, the GTAP-E model can be used to analyze the effects of emission trading and carbon taxes. The GTAP-E model was originally developed by Burniaux and Truong (2002), and the two latest versions of the GTAP-E model are now available. One recent revision is provided by Truong (2007) in which the model can run in two different modes, the standard GTAP model and GTAP-E model, simply by setting the “switch” parameters. Another revision, which improves the CO2 emissions accounting, is provided by McDougall and Golub (2007). We used the McDougall and Golub version. We begin with a brief description of the standard GTAP model, which is the basis of the GTAP-E model. The GTAP model is composed of market equilibrium conditions for factors and goods and includes a consideration of zero-profit conditions, similar to the standard CGE model. The model addresses relevant production factors, from regional households to firms, and includes a constant return to scale production function. The regional household in the GTAP model plays a role in both private households and government. The regional household divides income into consumption, government expenditure, and saving. The GTAP model assumes the operation of two distinct global sectors. The first is a global banking sector that assembles savings and distributes investment to each region. Regional investment is distributed so that the rate of change in the expected rate of return on capital equalizes across regions. The second is a global transportation sector that purchases transportation services from regions and supplies international transportation services. This assumption solves the problem of a lack of information about which particular regional transportation services are associated with particular imports. Figure 6.1 depicts the production function in the GTAP-E model.6 This function has a Leontief structure with zero elasticity of substitution at the top level and a constant elasticity of substitution (CES) structure at the lower level. One feature of the GTAP-E production function is that the energy composite is combined with capital and incorporated into the value-added nest. The elasticity within the capital-energy composite (σKE) is 0.50 for all industries and countries except coal, oil, gas, and petroleum and coal products (σKE = 0.00). The elasticity of substitution between value-added and capital-energy composite (σVAE) differ among industries and regions. For example, the value of Japan’s σVAE ranges from 0.00 (gas) to 4.00 (coal). Energy commodities are incorporated into the energy composite in three levels of nested substitution: (i) substitution between gas, oil, and petroleum and coal products, σNCOL = 1.00 except coal, oil, gas, and petroleum and coal products (σNCOL = 0.00); (ii) substitution between non-coal energy composite and coal,

Global environmental management 203 Output Leontief

Value-added-energy composite

Non-energy inputs

CES Natural resource

Land

CES

σD

σVAE Labor Capital-energy composite σKE

Domestic

Foreign σM

CES

CES

Region 1 …… Region R Capital

Energy composite σENER

CES

Electricity

Non-electric energy

σNELY

CES Non-coal energy

Coal

σNCOL Gas

FIGURE 6.1

CES Oil

Petroleum and coal products

Production structure in the GTAP-E model

Note: For electricity, coal, gas, oil, and petroleum and coal products, a graphical description of substitutability between domestic and imported goods is omitted in the figure. Source: Based on Burniaux and Truong (2002).

σNELY = 0.50 except coal, oil, gas, and petroleum and coal products (σNELY = 0.00); and (iii) substitution between non-electricity energy composite and electricity, σENER = 1.00 except coal, oil, gas, petroleum and coal products, and electricity (σENER = 0.00). The model is based on the Armington assumption that products are differentiated by country of origin. Firms first determine the source of their imports and then compare the prices of domestic goods and the optimal mix of imports. The Armington parameters for regional allocation of imports (σM) and domestic or imported allocation (σD) are different among industries but the same among regions. The value of σM ranges from 1.80 (other minerals) to 30.29 (gas). The value of σD ranges from 0.90 (other minerals) to 10.96 (gas). In the GTAP model, every sector and regional household faces the same price of the optimal mix of imports, indicating that the share of imported goods from a country in total imported goods is the same across both intermediate demand (from each sector) and final demand (from regional households).

204 Kiyoshi Fujikawa and Hikari Ban

6.2.2 The GTAP Data Base We use the GTAP 8.1 Data Base, which corresponds to the global economy of 2007 with 134 countries/regions and 57 industries. It contains regional I-O tables, macro data, bilateral trade data, and protection data. In addition, energy volume data and CO2 emission data are available. The international I-O analysis detailed in Section 6.5 requires international I-O tables. However, the GTAP Data Base used here does not contain enough data on cross-border trade between industries. Therefore, we follow the proportional procedure in Bems et al. (2010, 2011) and in Johnson and Noguera (2012). We assume that the share of imported goods i from country s in total imported goods i is the same across both industries and final demand. Although these assumptions are rather strong, this method is helpful when investigating the structural change due to EPA by combining an I-O model with a CGE model. Additionally, this method is consistent with the Armington approach in the GTAP model. Table 6.1 represents the international I-O table for two regions, two sectors, and a global transportation sector. The row in the global transportation sector indicates international transportation service distribution through sales to sectors and final demand. International transportation services accompanied with imported intermediate input are treated as an intermediate input from the global transportation sector. The global transportation sector purchases transportation services from regional sectors as an intermediate input. In Table 6.1, only sector 2 supplies transportation services. As the GTAP model assumes, the global transportation sector does not use factors.

TABLE 6.1 International I-O table for two regions and two sectors

Intermediate input demand r =1 j=1 s=1 s=2

i=1 i=2 i=1 i=2

s=G Value added Total

Z Z Z Z Z V X

11 11 11 21 21 11 21 21 G1 1 1 1 1 1

r =2 j=2 Z Z Z Z Z V X

11 12 11 22 21 12 21 22 G1 2 1 2 1 2

j=1

j=2

12 11 12 21 22 11 22 21 G2 1 2 1 2 1

Z 12 12 Z 12 22 Z 22 12 Z 22 22 Z G22 V 22 X 22

Z Z Z Z Z V X

Final demand r=G

r=1

r=2

0 Z 1G2 0 Z 2G2 0 0 XG

F 11 1 F 11 2 F 21 1 F 21 2 F G1

F 12 1 F 12 2 F 22 1 F 22 2 F G2

Total

X 11 X 12 X 21 X 22 XG

Notes: The superscript G represents the global transportation sector. Z ijsr, F isr, X is, and V is are purchases of intermediate products from sector i in region s to sector j in region r, purchases of final products from sector i in region s to region r, amount of output of sector i in region s, and value added of sector i in region s, respectively.

Global environmental management 205

Ex-ante and ex-post simulation international I-O tables are necessary to investigate structural changes due to EPAs. We constructed five international I-O tables. One table is calculated with the ex-ante simulation GTAP Data Base. The other tables are calculated with the ex-post simulation database. The ex-post international I-O tables are evaluated by initial prices (in real terms). As described below, we aggregate the GTAP Data Base into 22 regions and 20 industries. Because we consider the global transportation sector, the international I-O tables made from the GTAP Data Base have 441 sectors.

6.3 Simulation scheme In this section, we explain the simulation scheme of FTA and FDI between Japan and ASEAN countries.

6.3.1 Aggregation For the CGE analysis, we use the GTAP 8.1 Data Base, which corresponds to the global economy of 2007 with 134 countries/regions and 57 industries. We aggregate these data into 22 regions and 20 industries, as shown in Table 6.2 and Table 6.3.7 In this study, ASEAN includes the countries Cambodia, Indonesia, Laos, Malaysia, Philippines, Singapore, Thailand, Vietnam, and the Rest of Southeast Asia (“Rest of Southeast Asia” is a composite region consisting of Brunei Darussalam, Myanmar, and Timor Leste).

TABLE 6.2 Country/region aggregation

Code

Description

Code

Description

OCE CHN HKG JPN KOR TWN KHM IDN LAO MYS PHL

Oceania China Hong Kong Japan South Korea Taiwan Cambodia Indonesia Laos Malaysia Philippines

SGP THA VNM RSA IND CAN US EEX EU EEFSU ROW

Singapore Thailand Vietnam Rest of Southeast Asia India Canada United States of America Energy exporter region European Union East Europe and Former Soviet Union Rest of world

Note: Under the GTAP classification, Rest of Southeast Asia is a composite region consisting of Brunei Darussalam, Myanmar, and Timor Leste. Source: The GTAP 8.1 Data Base.

206 Kiyoshi Fujikawa and Hikari Ban TABLE 6.3 Industry aggregation

Code

Description

Code

Description

prm col oil gas p_c ely omn food tex crp

primary coal oil gas petroleum and coal products electricity other minerals food textile and clothing chemical products

ppp i_s nmm mvh otn ele ome omf tsp svc

paper products and publishing ferrous metals mineral products automobile transport equipment electronic equipment other machinery and equipment other manufactured products transportation services other services

Source: The GTAP 8.1 Data Base.

6.3.2 Scenario Four simulations are implemented to evaluate the economic and environmental impact of FTA and FDI within Japan and ASEAN countries. (S1) The FTA scenario The first scenario involves the complete abolition of any ad valorem import tariffs within Japan and ASEAN countries. The tariffs within ASEAN countries also are eliminated. Existing export subsidies and taxes are unaltered. (S2) FDI without an energy efficient technology transfer scenario The second scenario considers the impact of FDI from Japan to ASEAN countries. Specifically, initial capital stock increases by 1 percent in each ASEAN country and decreases by the sum of corresponding amounts in Japan.8 (S3) FDI with an energy efficient technology transfer scenario We assume that FDI from Japan to ASEAN countries improves energy efficiency of all industries in ASEAN countries. The third scenario includes FDI of the S2 scenario and energy-augmenting technological change at the rate of 1 percent for all industries in ASEAN countries. (S4) The FTA and FDI with an energy efficient technology transfer scenario The fourth scenario is a combination of the first and third scenario. It describes the impact of FTA and FDI, which induces energy-augmenting technological change in ASEAN countries.

6.3.3 Initial tax rates The FTA simulation results depend substantially on the initial tariff rates. Some features of the initial tariff rates within Japan and ASEAN countries can be described. First, Singapore’s tariff rates are almost zero and Japanese tariff rates

Global environmental management 207

(except on primary goods, food, textiles, and other manufactured items) are also nearly zero. Second, for energy intensive goods, such as chemical products, paper products, ferrous metals, mineral products, the tariff rates on imports from Japan are relatively high compared with imports from other FTA members. Third, some ASEAN countries impose tariffs on imported energy. Vietnam, Cambodia, and Thailand impose substantially high tariff rates on petroleum and coal products. For example, Vietnam’s tariff rate on petroleum and coal products imported from Japan, Indonesia, and Singapore are 18.5 percent, 18.1 percent, and 18.7 percent, respectively.

6.4 Simulation results 6.4.1 Economic impact of FTA and FDI First, we examine the economic impact of FTA and FDI. Table 6.4 reports the effects on GDP for each scenario. The effects of FTA on GDP do not appear to be significant. Even Thailand, which derives the most benefit from FTAs, only displays a 0.19 percent increase. In contrast, the FDI of the S2 scenario increases GDP by around 0.5 percent in the host countries and slightly decreases it in the source country. Energy efficient technology transfer is likely to increase GDP by roughly 0.2 percent compared with the S2 scenario. The result of the S3 scenario has a dominant influence on GDP in FTA members under the S4 scenario. The effects of FTA on exports and imports are relatively large compared with the effects on GDP (Table 6.5). In particular, Cambodia and Vietnam show TABLE 6.4 GDP growth rate for each scenario (%)

JPN KHM IDN LAO MYS PHL SGP THA VNM RSA CHN US EU World J+A

S1

S2

S3

S4

0.02 0.03 0.03 0.03 0.16 0.18 0.03 0.19 0.03 0.04 −0.01 0.00 0.00 0.00 0.04

−0.09 0.48 0.49 0.42 0.52 0.58 0.55 0.58 0.40 0.46 0.00 0.00 0.00 0.00 0.05

−0.09 0.65 0.66 0.51 0.75 0.73 0.83 0.87 0.65 0.62 0.00 0.00 0.00 0.01 0.10

−0.07 0.67 0.69 0.53 0.92 0.91 0.86 1.06 0.68 0.66 −0.01 0.00 0.00 0.01 0.14

Note: J+A means the total of Japan and ASEAN countries. Source: Authors’ calculations based on the GTAP 8.1 Data Base.

208 Kiyoshi Fujikawa and Hikari Ban TABLE 6.5 Export and import growth rate for each scenario (%)

Export

JPN KHM IDN LAO MYS PHL SGP THA VNM RSA CHN US EU World J+A

Import

S1

S2

S3

S4

S1

S2

S3

S4

0.72 4.68 1.61 2.95 1.13 2.21 0.79 2.61 5.03 1.15 −0.11 0.05 0.03 0.14 1.27

−0.40 0.87 0.66 1.11 0.65 0.91 0.61 0.77 0.64 0.54 0.01 0.02 0.01 0.03 0.17

−0.40 0.66 0.61 1.19 0.73 0.77 0.83 0.81 0.71 0.49 0.01 0.02 0.01 0.03 0.21

0.32 5.37 2.22 4.17 1.87 2.99 1.62 3.43 5.78 1.65 −0.10 0.08 0.04 0.18 1.49

1.61 6.08 2.26 5.47 2.40 2.95 1.23 4.82 7.42 2.47 −0.27 −0.14 −0.04 0.14 2.37

0.05 0.52 0.44 0.58 0.46 0.56 0.48 0.50 0.38 0.27 0.00 0.00 0.00 0.03 0.27

0.05 0.65 0.50 0.77 0.58 0.51 0.64 0.59 0.64 0.28 0.00 0.00 0.00 0.03 0.32

1.66 6.80 2.77 6.33 2.99 3.47 1.88 5.44 8.13 2.77 −0.27 −0.13 −0.04 0.18 2.70

Note: J+A means the total of Japan and ASEAN countries. Source: Authors’ calculations based on the GTAP 8.1 Data Base.

increasing rates of exports and imports. The FDI of the S2 and S3 scenarios increases export in the host countries and decreases it in the source country. The imports of Japan and ASEAN countries increase under both FDI scenarios. The effect on exports and imports for the S2 and S3 scenarios is smaller than it is for the S1 scenario except for exports from Singapore. Table 6.6 shows the change in output by industry of Japan and the entire ASEAN region. We begin with looking at the result of the FTA scenario. As for Japan, increases in output of ferrous metals, textiles, chemical products, and petroleum and coal products, as well as decreases in output of food, electronic equipment, and other machinery, are remarkable. Regarding ASEAN countries, increases in output of food, textiles, petroleum and coal products, automobile and other manufactured products, are also remarkable. With the presence of FTA, the production of energy-intensive industries, such as chemical products, paper products, ferrous metals, and mineral products, appears to shift from ASEAN counties to Japan. Increases in chemical and mineral products are observable in China, the US, and the EU as well.9 We should notice that the output of electronic equipment industry and other machinery in China, the US, and the EU increases while it decreases in the FTA region as a whole. This phenomenon seems to be related to increases in wages and capital rental rates in the FTA members. For example, wages rise by 0.52 percent in Japan, 0.25 percent in Indonesia, and 6 percent in Vietnam; and capital rental rates rise by 0.55 percent, 0.22 percent, and 6.67 percent respectively. In contrast, these rates decline by around 1 percent outside the FTA region.

Global environmental management 209 TABLE 6.6 Output change for each scenario (US$ million)

S1

prm col oil gas p_c ely omn food tex crp ppp i_s nmm mvh otn ele ome omf tsp svc Total

S2

S3

S4

Japan

ASEAN

Japan

ASEAN

Japan

ASEAN

Japan

ASEAN

−584 0 −1 −29 1,052 298 6 −2,804 3,063 2,322 174 4,721 168 602 463 −3,898 −2,833 491 −284 1,404 4,331

734 −195 −453 −645 1,890 6 5 6,990 1,993 −1,818 −43 −1,019 −257 1,788 26 −3,929 511 1,357 239 795 7,974

−66 0 0 −13 −228 −259 −10 −225 −78 −1,013 −151 −625 −114 −1,013 −149 −1,167 −1,257 −620 −435 −3,210 −10,633

225 171 219 400 552 409 117 412 615 1,750 206 256 217 335 172 2,517 1,317 1,142 739 5,227 16,998

−62 0 0 −12 −298 −264 −10 −219 −75 −1,057 −149 −670 −122 −987 −145 −1,055 −1,209 −612 −471 −3,187 −10,606

279 70 111 186 2,026 540 128 474 541 2,755 254 478 318 407 170 1,691 1,027 1,219 1,947 6,744 21,364

−645 0 −2 −42 751 34 −4 −3,022 2,993 1,249 23 4,066 44 −368 319 −4,954 −4,039 −123 −756 −1,785 −6,262

1,006 −127 −341 −453 3,951 544 133 7,466 2,532 925 211 −557 61 2,202 198 −2,265 1,548 2,578 2,204 7,560 29,376

Note: Output is evaluated by the initial prices. Source: Authors’ calculations based on the GTAP 8.1 Data Base.

In the S2 and S3 scenarios, all industries in Japan decrease output because initial capital stock decreases. In contrast, all industries in the entire ASEAN region increase output in these scenarios. As for the S3 scenario, production of petroleum and coal products, chemical products, transportation services, and other services in ASEAN countries expand considerably. When comparing the columns of the ASEAN countries for the S2 and S3 scenarios, we find that energy efficient technology transfer may discourage some industrial output in ASEAN countries. The output of coal, oil, and gas industries in the ASEAN region declines compared with the S2 scenario, because the demand for these products decreases because of energy-augmenting technological change and the substitution of petroleum and coal products and electricity for them. As the share of energy to total cost is lower in coal, oil, and gas industries than in petroleum and coal products and electricity industries, the former products become more expensive than the latter products. Concerning electronic equipment, machinery, textiles, and transportation equipment industries, the output increases for ASEAN countries are smaller in the S3

210 Kiyoshi Fujikawa and Hikari Ban

scenario than in the S2 scenario, while the output increases for most other regions are larger in the S3 scenario than in the S2 scenario. The reason is the same as for scenario S1. That is, wage and capital rental rates in ASEAN countries are higher in the S3 scenario relative to the S2 scenario although they are almost the same in other regions. These industries in the ASEAN region are likely to lower their competitiveness as the result of energy-augmenting technological change. With relation to petroleum and oil products, chemical products, and transportation services and other services industries, the output in the ASEAN region is substantially larger in the S3 scenario compared with the S2 scenario. The countries witnessing increases in outputs include Indonesia, Malaysia, Singapore, and Thailand. Conversely, almost all regions except the ASEAN region reduce the output of petroleum and oil products, chemical products, and transportation services. Energy-augmenting technological change appears to improve competitiveness, most notably in the three energy-intensive industries in the ASEAN region. Compared with the S1 scenario, output in all industries for Japan is smaller in the S4 scenario, whereas output in all industries for the ASEAN region is larger for the S4 scenario. In Japan, production decreases in services, machinery, chemical products, and electronic equipment are significant. In the ASEAN region, production increases in services, chemicals, and petroleum and coal products are remarkable.

6.4.2 The environmental impact of FTA and FDI Next, we discuss the impact on the environment, measured with the CO2 load. The growth rates of CO2 are presented in Table 6.7, and the total amount of change in CO2 emissions and the amount of industrial change in CO2 emissions are presented in Table 6.8. The difference between the total amount of CO2 and the amount of industrial CO2 is the amount of CO2 released from the combustion of fossil fuel for regional households. The column of the S1 scenario indicates that FTAs appear to increase total CO2 emissions in FTA members except in Indonesia and the composite Rest of Southeast Asia. Japan and Vietnam show relatively significant increases in CO2 emissions (Table 6.8). The FTA region increases CO2 emissions at 0.60 percent as a whole, an increase larger than the GDP growth rate shown in Table 6.4. The columns of the scenario S2 in Table 6.7 and Table 6.8 show that FDI from Japan to ASEAN countries decreases CO2 emissions in Japan, but increases in the ASEAN region. These results are consistent with the signs of GDP growth rates shown in Table 6.4. However, by comparison with the S2 scenario, in the S3 scenario, the GDP of all ASEAN countries grows at higher rates, while CO2 emissions in some countries grow at lower rates. In other words, energyaugmenting technological change differs among regions in terms of how much it can reduce CO2 emissions. From the S2 scenario to the S3 scenario, Indonesia shows the largest decrease and Vietnam shows the largest increase in CO2 emissions.

Global environmental management 211 TABLE 6.7 CO2 growth rate for each scenario (%)

JPN KHM IDN LAO MYS PHL SGP THA VNM RSA CHN US EU World J+A

S1

S2

S3

S4

0.42 6.96 −0.04 5.21 0.52 0.47 1.16 0.54 4.97 −0.31 −0.01 −0.03 −0.02 0.02 0.60

−0.10 0.48 0.70 0.83 0.63 0.64 0.49 0.63 0.53 0.62 −0.01 0.00 0.00 0.02 0.26

−0.10 0.85 0.46 1.60 0.63 0.42 0.43 0.62 0.74 0.60 0.00 0.00 0.00 0.02 0.22

0.33 7.89 0.42 7.02 1.15 0.91 1.59 1.15 5.82 0.29 −0.01 −0.03 0.02 0.04 0.82

Note: J+A means the total of Japan and ASEAN countries. Source: Authors’ calculations based on the GTAP 8.1 Data Base.

TABLE 6.8 CO2 change for each scenario (million tons)

Total

JPN KHM IDN LAO MYS PHL SGP THA VNM RSA CHN US EU World J+A

Industry

S1

S2

S3

S4

S1

S2

S3

S4

4.52 0.36 −0.15 0.05 0.96 0.34 0.75 1.22 4.57 −0.06 −0.55 −1.47 −0.73 5.23 12.55

−1.06 0.02 2.53 0.01 1.15 0.46 0.32 1.43 0.49 0.13 −0.27 −0.01 0.16 5.57 5.46

−1.05 0.04 1.65 0.02 1.16 0.30 0.27 1.39 0.68 0.12 −0.16 0.05 0.04 4.87 4.59

3.48 0.40 1.50 0.07 2.11 0.66 1.03 2.60 5.35 0.06 −0.71 −1.43 −0.69 10.20 17.27

4.05 0.34 −0.14 0.05 0.93 0.29 0.74 1.09 4.20 −0.07 −0.42 −0.86 −0.37 5.75 11.48

−1.07 0.02 2.34 0.01 1.09 0.42 0.31 1.34 0.46 0.12 −0.25 0.00 0.15 5.13 5.02

−1.09 0.03 1.25 0.02 1.01 0.25 0.25 1.17 0.59 0.11 −0.16 −0.05 −0.03 3.59 3.58

2.97 0.37 1.10 0.07 1.94 0.55 0.99 2.26 4.89 0.04 −0.59 −0.91 −0.40 9.44 15.18

Note: J+A means the total of Japan and ASEAN countries. Source: Authors’ calculations based on the GTAP 8.1 Data Base.

212 Kiyoshi Fujikawa and Hikari Ban TABLE 6.9 The top six industries in terms of CO2 changes (million tons)

S1 JPN IDN VNM

ely(1.50), i_s(1.09), crp(0.44), tsp(0.42)*, svc(0.34), p_c(0.15) i_s(−0.21), omf(0.09), crp(−0.05), gas(−0.05), tex(0.04), food(−0.04) tsp(2.56), svc(0.60), food(0.25), nmm(0.19)*, omf(0.14)*, crp(0.10)

JPN IDN VNM

ely(−0.49), tsp(−0.19), crp(−0.12), i_s(−0.10), svc(−0.05), p_c(−0.03) ely(0.78), nmm(0.31), tsp(0.30), gas(0.20), p_c(0.15), crp(0.11) ely(0.21), nmm(0.08), tsp(0.04), svc(0.03), crp(0.03), omf(0.02)

JPN IDN VNM

ely(−0.55), tsp(−0.17), crp(−0.10), i_s(−0.10), svc(−0.04), p_c(−0.04) tsp(0.42), ely(0.23), nmm(0.18), i_s(0.12), crp(0.11), p_c(0.09) tsp(0.22), ely(0.14), i_s(0.06), nmm(0.05), svc(0.04), crp(0.03)

JPN IDN VNM

i_s(0.99), ely(0.99), crp(0.33), svc(0.30)*, tsp(0.25)*, nmm(0.11) tsp(0.41), ely(0.25), nmm(0.18), omf(0.12), i_s(−0.09), svc(0.08) tsp(2.86), svc(0.65), food(0.26), nmm(0.24)*, ely(0.19)*, omf(0.16)*

S2

S3

S4

Notes: The asterisk implies that the directions of change in CO2 and output are opposite. The figures in parenthesis are the amount of CO2 change (million ton). Source: Authors’ calculations based on the GTAP 8.1 Data Base.

In the S4 scenario, CO2 emissions increase in all FTA members. Vietnam and Japan show relatively large increases in CO2 emissions. Comparing with the S1 scenario, the change in CO2 emissions is smaller in the S4 scenario in Japan, but larger in the ASEAN countries. The total CO2 emissions of Japan and the ASEAN countries are larger in the S4 scenario than in the S1 scenario. To discuss changes in CO2 emissions by industry, we focus on Japan, Indonesia, and Vietnam, where changes in CO2 emissions are relatively large. Table 6.9 reports the top six industries in terms of the absolute value of CO2 changes in these three countries. As far as Japan is concerned, the electricity and ferrous metals industries increase CO2 emissions relatively more in the S1 scenario while all industries decrease emissions in the S2 and S3 scenarios. In Indonesia, total CO2 emissions decrease in the S1 scenario. The key industries for reducing carbon emissions are ferrous metals, chemical products, and gas industries. Moreover, CO2 emissions increase in all industries in the S2 scenario. Except for ferrous metals and transportation services industries, the extent of increase in CO2 emissions becomes smaller in the S3 scenario than in the S2 scenario. Carbon reduction in the electricity, gas and mineral products industries is remarkable. The largest increases are attained in transportation services, electricity, and mineral products in the S4 scenario. Vietnam witnesses an increase in total CO2 emissions in all the scenarios. Transportation services industries are likely to explain the increase in CO2 emissions. When comparing the S3 scenario with the S2 scenario, transportation services represent the largest difference in terms of CO2 emissions.

Global environmental management 213

The asterisk in Table 6.9 implies that the directions of change in CO2 and output are in opposite directions. There are some industries that decrease output but increase CO2 emissions, such as Japanese transportation services in the S1 and S4 scenarios. This may be because the substitution effect caused by a fall in relative prices of energy becomes sufficiently large. The reasons for declining relative prices of energy differ across countries and scenarios. Regarding Japanese transportation services in the S1 and S4 scenarios, production factors become more expensive and they are substituted mainly with petroleum and coal products.10 Vietnam’s mineral products industry decreases output but increases CO2 emissions in the FTA scenario. This is mainly due to a fall in the price of petroleum and coal products by 7.96 percent and an increase in their demand by 7.10 percent. This is likely to be related to the abovementioned high tariffs on petroleum and coal products in Vietnam. Examining the S2 and S3 scenarios in Table 6.9, we find that in some industries (e.g., electricity industry) energy-augmenting technological change contributes to the reduction of carbon emissions. To understand why, we have to investigate the features of individual industries. Table 6.10 compares the electricity and transportation services industries in Indonesia and Vietnam. The output of electricity grows faster in the S3 scenario than in the S2 scenario, while CO2 emissions grow more slowly in the S3 scenario than in the S2 scenario. As for transportation services, both output and CO2 emissions grow faster in the S3 scenario than in the S2 scenario. In terms of CO2 emissions per output, the carbon loads for both industries are better in the S3 scenario than in the S2 scenario. TABLE 6.10 Comparison between electricity and transport services

Indonesia Electricity

Vietnam Transport

Electricity

Growth rates % Output CO2 Output CO2 Output CO2 S2 0.69 0.74 0.51 0.61 0.69 0.75 S3 1.23 0.22 0.93 0.85 0.86 0.52 Share of total industrial CO2 emission % 33.83 15.80 35.36 Coal cost share to total energy cost % 14.62 0.00 19.62 Petroleum and coal products cost share to total energy cost % 69.92 99.07 24.28 Gas cost share to total energy cost % 9.67 0.02 50.45 Labor cost share to total cost % 3.42 15.77 26.62 Elasticity of substitution between labor and capital-energy composite 1.26 1.68 1.26 Source: Authors’ calculations based on the GTAP 8.1 Data Base.

Transport Output 0.24 2.15 22.39 0.04 97.68 0.00 2.31 1.68

CO2 0.23 1.22

214 Kiyoshi Fujikawa and Hikari Ban

The extent to which energy-augmenting technological change can contribute to CO2 reductions differs across countries and industries. For example, the substitution of gas for coal encourages CO2 reduction.11 However, when the coal industry’s share of total energy cost in transportation services is nearly zero then the substitution effect does not occur. In addition, the elasticity of substitution between labor and a capital-energy composite is relatively higher in the transportation services industry compared with the electricity industry. These conditions in transportation services industry may weaken the CO2 reduction effect. Given a relative rise in the price of labor, substitutability between them may encourage energy consumption. The substitution of petroleum and coal products for gas increases CO2 emissions. Vietnam’s electricity industry, for example, is heavily dependent on gas for its energy input. Hence, the substitution of petroleum and coal products for gas is significant and diminishes the effectiveness of energy-augmenting technological change. In Indonesia, the labor cost share to the total cost is significantly higher in transportation services industry than in the electricity industry, whereas in Vietnam this is reversed. A high-labor cost share means that there is much room for substitution from labor to a capital-energy composite with a lower price. Furthermore, in the transportation services industry, a CO2 increase rate per 1 percent of the output increase rate is higher in Indonesia (0.91 percent in the S3 scenario) than in Vietnam (0.57 percent in the S3 scenario). Changes in industrial CO2 emissions in Japan and the entire ASEAN region are represented in Table 6.11. Under the S1 scenario, electricity, transportation services, and other services industries show relatively significant increases in CO2 emissions in Japan and the ASEAN region. Japan’s ferrous metals and ASEAN’s petroleum and coal products industries also notably increase CO2 emissions. When comparing the S2 and S3 scenarios in Table 6.11, we observe that the energy-augmenting technological change encourages reductions of total CO2 emissions in the ASEAN region, although the extent to which this technological change can contribute to CO2 reduction differs across industries. However, almost all industries in the ASEAN region increase CO2 emissions substantially more in the S4 scenario relative to the S1 scenario.

6.5 International I-O analysis This section briefly analyzes CO2 emissions embodied in trade by using an international I-O model. Assume that the economy consists of N-industries and R-regions. Under a constant input coefficient, the equilibrium conditions for the goods market are as follows: xis =

R

N

R

∑ ∑ aijsrxjr + ∑ f isr, i = 1 … N, s = 1 … R, r=1 j=1

r=1

[6.1]

Global environmental management 215 TABLE 6.11 CO2 change for each scenario (million tons)

S1

prm col oil gas p_c ely omn food tex crp ppp i_s nmm mvh otn ele ome omf tsp svc Total

S2

S3

S4

Japan

ASEAN

Japan

ASEAN

Japan

ASEAN

Japan

ASEAN

−0.06 0.00 0.00 −0.01 0.15 1.50 0.00 −0.06 0.02 0.44 0.06 1.09 0.15 0.00 0.00 −0.02 −0.01 0.05 0.42 0.34 4.05

0.62 −0.08 −0.05 −0.24 0.71 1.02 0.06 0.79 0.11 −0.05 0.07 −0.47 0.14 0.01 0.02 0.01 0.12 0.53 3.40 0.72 7.43

0.00 0.00 0.00 0.00 −0.03 −0.49 0.00 0.00 0.00 −0.12 −0.01 −0.10 −0.03 0.00 0.00 −0.01 −0.01 −0.02 −0.19 −0.05 −1.07

0.03 0.02 0.05 0.28 0.34 2.50 0.02 0.05 0.06 0.26 0.08 0.18 0.68 0.01 0.01 0.02 0.06 0.18 1.06 0.22 6.10

0.00 0.00 0.00 0.00 −0.04 −0.55 0.00 0.00 0.00 −0.10 −0.01 −0.10 −0.03 0.00 0.00 −0.01 −0.01 −0.02 −0.17 −0.04 −1.09

−0.01 0.02 −0.05 −0.06 0.40 0.67 0.01 0.00 0.04 0.29 0.02 0.25 0.41 0.00 0.00 0.01 0.04 0.09 2.31 0.19 4.67

−0.06 0.00 0.00 −0.01 0.11 0.96 0.00 −0.07 0.02 0.33 0.05 0.99 0.11 0.00 0.00 −0.03 −0.02 0.03 0.25 0.30 2.97

0.61 −0.05 −0.09 −0.29 1.12 1.68 0.07 0.79 0.16 0.24 0.09 −0.22 0.55 0.02 0.02 0.02 0.16 0.63 5.79 0.92 12.20

Source: Authors’ calculations based on the GTAP 8.1 Data Base.

where xis denotes the gross output of industry i in region s, a ijsr denotes the direct input coefficient, indicating the amount of intermediate good i produced in region s required to produce a unit of good j in country r, and f isr denotes final demand for good i produced in region s from country r. Let … :

sr ⎛ x1s ⎞ ⎛ a11 ⎜ : ⎟ ⎜ : sr x = ⎜ ⎟, A = ⎜ s sr ⎝ xN ⎠ ⎝ aN1 s

…

sr ⎞ ⎛ f 1s1 + f 1s2 + … + f 1sR ⎞ a1N ⎟ ⎟ s : ⎟ , f = ⎜⎜ : ⎟. sr s1 s2 sR … aNN ⎠ + fN ⎠ ⎝ fN + fN +

With these notations, Equation [6.1] can be represented in matrix form as … :

⎛ x1 ⎞ ⎛ A11 ⎜:⎟ ⎜ : ⎜ R ⎟ = ⎜ R1 ⎝x ⎠ ⎝A

…

A1R ⎞ ⎛ x1 ⎞ ⎛ f 1 ⎞ : ⎟⎟ ⎜⎜ : ⎟⎟ + ⎜⎜ : ⎟⎟ . ARR ⎠ ⎝ xR ⎠ ⎝ f R ⎠

[6.2]

If we know the values of the input coefficients and final demand, we can solve Equation [6.2] for equilibrium gross output. The gross output vector x can be

216

Kiyoshi Fujikawa and Hikari Ban

expressed as a product of the Leontief inverse matrix L and a final demand vector f as follows: x = Lf,

[6.3]

where ⎛ f1 ⎞ ⎜ 2⎟ f f = ⎜⎜ ⎟⎟ : ⎜ R⎟ ⎝f ⎠

− A12 I − A22 : − AR2

… … …

− A1R ⎞ ⎟ − A2R ⎟ ⎟ : ⎟ RR I − A ⎠

−1

⎛ L11 ⎜ 21 L = ⎜⎜ : ⎜ R1 ⎝L

L12 L22 : LR2

… … :

⎛ I − A11 ⎜ 21 L = ⎜⎜ − A : ⎜ ⎝ − AR1

:

⎛ x1 ⎞ ⎜ 2⎟ x x = ⎜⎜ ⎟⎟ , : ⎜ R⎟ ⎝x ⎠

…

L1R ⎞ ⎟ L2R ⎟ . : ⎟ ⎟ LRR ⎠

Next, Lsr is an N × N matrix consisting of coefficients that indicate the amount of total output in each industry of region s directly and indirectly required to satisfy one unit of final demand for each industry in region r. Let eS be the 1 × N direct CO2 emission coefficient vector: es = (e1s, e2s , … eNs ),

[6.4]

where ejs is the CO2 emission coefficient (CO2 emission/gross output) of industry j in region s. We define the R × NR emission coefficient matrix ê as 0 e2

… :

⎛ e1 ⎜ 0 ê = ⎜⎜ : ⎜ ⎝0

…

0

0⎞ ⎟ :⎟ . 0⎟ ⎟ eR ⎠

[6.5]

Pre-multiplying the Leontief inverse matrix L by the CO2 emission coefficient matrix ê generates the following the R × NR matrix that illustrates how CO2 emissions are geographically generated to satisfy one unit of final demand for each industry in each region. … :

⎛ e1L11 êL = ⎜⎜ : R R1 ⎝e L

…

e1L1R ⎞ : ⎟⎟ . R RR e L ⎠

[6.6]

Each element of esLsr presents the amount of CO2 embodied in one unit of each final good produced in region r with origin in region s. In other words, each column of êL shows the geographical division of CO2 directly and indirectly embodied in one unit of each final good.

Global environmental management 217

We use Equation [6.6] to calculate the structure of embodied CO2 emissions in international trade. Multiplying êL by final demand vector f gives CO2 emissions accompanied by equilibrium gross output induced by the final demand: ⎛ e1L11f 1 + … + e1L1Rf R ⎞ ⎟ êLf = ⎜⎜ : ⎟. R R1 1 R RR R … e L f + + e L f ⎝ ⎠

[6.7]

The vector êLf consists of R elements that indicate the CO2 emissions released in specific regions within CO2 emissions induced from the total final demand. Using Equation [6.7], CO2 induced from the final demand from a specified region can be decomposed according to the region where it was released.

6.6 Structural change in international CO2 loads In this section, we discuss the structural change in international CO2 loads caused by FTA and FDI in the previous section by applying an international I-O analysis to the estimated ex-ante and ex-post simulation I-O tables. According to Equation [6.7], we decomposed CO2 emissions induced by the final demand from each region according to the region where the emissions were released. Table 6.12 represents the CO2 emissions embodied in trade calculated using the ex-ante simulation data. Each column shows the source regions of CO2 induced from the region indicated by each column header. The total emissions induced by a certain region represent the consumption-based CO2 emission of that region. Subtracting domestic emissions (the diagonal element) from the consumption-based CO2 of the region indicated by the header yields its CO2 import. Each row shows the export destination of CO2 generated in the region indicated by each row header. Total emissions released in a certain region are referred to as the production-based CO2 emissions in that region. Subtracting part of the domestic absorption (the diagonal element) from the production-based CO2 emissions of the region indicated by the header yields its CO2 export.12 China, the US, the EU, and Japan are important when evaluating consumptionand production-based measurements of CO2 emissions.13 China is the largest producer and exporter of embodied CO2 emissions, while the US is the largest consumer and the EU is the largest importer. Regarding the trade balance of embodied emissions, the deficit is large in the EU (−827 million tons), the US (−657 million tons), and Japan (−177 million tons), and China’s large surplus (1,221 million tons) appears to offset a large part of these deficits. Focusing on the ASEAN region, the export of embodied CO2 emissions is larger than its domestic consumption in Malaysia, Singapore, and Thailand. ASEAN countries import more embodied CO2 emissions from China than from Japan. Indonesia, Thailand, Vietnam, and the Rest of Southeast Asia export more embodied CO2 emissions to Japan than to China. Within Japan and ASEAN countries, the importation of embodied CO2 emissions of Japan from Indonesia, Thailand, and Malaysia is relatively large.

726 0 15 0 8 2 3 10 4 1 139 38 38 125 1,108 382

0 2 0 0 0 0 0 1 1 0 1 0 0 1 6 3

KHM

3 0 221 0 3 0 2 2 1 0 18 4 6 19 279 58

IDN

0 0 0 0 0 0 0 1 0 0 0 0 0 0 2 1

LAO

3 0 2 0 62 0 1 2 0 0 12 3 4 11 100 39

MYS 2 0 1 0 1 45 0 1 0 0 7 2 3 8 69 24

PHL

Source: Authors’ calculations based on the GTAP 8.1 Data Base.

JPN KHM IDN LAO MYS PHL SGP THA VNM RSA CHN US EU Others Total Import

JPN 2 0 1 0 3 0 14 1 0 0 9 5 4 11 50 36

SGP 4 0 1 0 3 0 1 99 0 0 12 4 7 16 148 49

THA 1 0 1 0 1 0 1 2 44 0 13 2 3 10 76 33

VNM

TABLE 6.12 Ex-ante simulation CO2 emissions embodied in trade (million tons)

0 0 0 0 0 0 0 1 0 14 3 0 0 1 20 6

RSA 31 0 7 0 10 2 4 8 2 0 3,375 35 41 186 3,700 325

CHN 48 0 15 0 20 3 7 18 7 1 396 4,010 159 538 5,222 1,212

US 41 1 18 0 25 4 12 26 10 1 389 165 2,679 764 4,135 1,456

EU 70 0 28 0 32 4 17 32 9 1 548 298 364 6,481 7,884 1,403

Others

931 4 310 1 167 62 62 203 79 18 4,922 4,565 3,308 8,170 22,800 5,027

Total

204 1 89 0 105 17 48 103 35 4 1,547 555 628 1,689 5,027

Export

Global environmental management 219

Table 6.13 reports the change in embodied CO2 emissions in trade with the presence of FTAs between Japan and the ASEAN region (the S1 scenario). For example, the embodied CO2 emissions that were released and consumed in Japan increase by 1.5 million tons. Japan increases production-based CO2 emissions, and it is induced mainly by final demand from Japan, Malaysia, and Thailand. This is likely to be related to increases in Japan’s export of ferrous metals to Malaysia (The amount of increase: US$ 2,434 million, the rate of increase: 203.33 percent) and its export of chemical products to Thailand (US$ 1,584 million, 41.38 percent). Japan also increases consumption-based CO2 emissions, and its increase in imports from Thailand is notable and apparently related to Japan’s growing imports of food from Thailand (US$ 3,992 million, 166.10 percent). While Japan increases its exports of embodied CO2 emissions to Malaysia, Thailand, Indonesia, and Vietnam, these countries decrease imports of embodied CO2 emission from China. Vietnam and China increase exports of embodied CO2 emissions to the US and the EU as a result of FTAs between Japan and the ASEAN region. This appears to be related to increases in Vietnam’s exports of textile and clothing to the US and the EU and to China’s exports of electronics, machinery, other manufactured products, and chemical products to the US and the EU.14 Among the FTA regions, Indonesia and the Rest of Southeast Asia decrease their production-based CO2 emissions depending on decreases in emissions induced by domestic final demand. However, this does not necessarily imply a reduction of domestic final demand. Although the level of final demand remains unchanged, CO2 emissions can be reduced when imported intermediate inputs substitute for domestic ones.15 We applied the same international I-O analysis to the results for the S2, S3, and S4 scenarios. Table 6.14 summarizes production- and consumption-based CO2 emissions and exports and imports of embodied CO2 emissions for each scenario. It is important to examine the structural change in international CO2 loads for each scenario on the basis of Table 6.14. First, as a result of FDI from Japan to ASEAN (the S2 scenario), Japan decreases its production-based CO2 emissions but increases its consumption-based CO2 emissions. Because Japan’s final demand decreases by US$ 530 million in the S2 scenario, a possible cause could be the increase in CO2 emissions embodied in final goods. This is likely to be related to the substitution of imported goods with less energy efficiency, as well as to relative increases in energy inputs due to a rise in Japan’s capital rental rates.16 Although ASEAN countries expand both productionand consumption-based CO2 emissions, the increase in production-based emissions is larger than that in consumption-based emissions. Exports of embodied CO2 emissions from Indonesia, Malaysia, and Thailand are relatively large. The final demand of Japan, the US, and the EU, as well as domestic final demand, appear to induce increases in production-based emissions in these countries.17 Compared with the results of the S2 scenario, in the S3 scenario, Indonesia is likely to significantly reduce its production- and consumption-based CO2

1.5 0.0 0.5 0.0 0.5 0.1 0.3 2.7 0.6 0.0 −0.1 0.1 0.4 0.6 7.1 5.6

0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 −0.1 0.0 0.0 0.0 0.2 0.1

KHM

0.7 0.0 −1.0 0.0 0.2 0.0 0.0 0.3 0.1 0.0 −0.6 0.0 0.0 −0.4 −0.8 0.2

IDN

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

LAO

1.1 0.0 0.0 0.0 −0.2 0.0 0.0 0.0 0.0 0.0 −0.6 −0.1 −0.1 −0.4 −0.2 −0.1

MYS 0.3 0.0 0.0 0.0 0.1 0.0 0.0 0.2 0.6 0.0 −0.2 −0.1 0.0 −0.2 0.8 0.8

PHL

Source: Authors’ calculations based on the GTAP 8.1 Data Base.

JPN KHM IDN LAO MYS PHL SGP THA VNM RSA CHN US EU Others Total Import

JPN

TABLE 6.13 CO2 emission change under the S1 scenario

0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.2

SGP 1.0 0.0 0.4 0.0 0.6 0.1 0.1 −0.4 0.2 0.0 −0.7 −0.1 0.0 −0.5 0.8 1.2

THA 0.6 0.0 0.1 0.0 0.2 0.0 0.3 0.2 1.7 0.0 −0.8 0.0 0.0 −0.5 1.8 0.2

VNM 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 −0.1 −0.1 0.0 0.0 0.0 −0.1 0.0

RSA −0.4 0.0 0.0 0.0 −0.1 0.0 0.0 −0.2 0.0 0.0 1.1 0.0 0.0 0.1 0.5 −0.5

CHN −0.3 0.0 0.0 0.0 −0.2 0.0 0.0 −0.6 0.3 0.0 0.6 −0.9 0.0 −0.4 −1.4 −0.5

US −0.1 0.1 0.0 0.0 −0.2 0.0 0.0 −0.6 0.4 0.0 0.3 0.0 −0.8 −0.6 −1.6 −0.9

EU −0.4 0.1 −0.1 0.0 −0.1 0.0 0.0 −0.7 0.3 0.0 0.9 0.2 0.0 −1.7 −1.6 0.1

Others

4.1 0.3 −0.1 0.1 0.9 0.3 0.7 1.1 4.2 −0.1 −0.4 −0.9 −0.4 −4.1 5.7 6.5

Total

2.6 0.2 0.9 0.0 1.1 0.3 0.7 1.5 2.6 0.0 −1.5 0.0 0.4 −2.4 6.5 0.0

Export

Global environmental management 221 TABLE 6.14 Effects of EPA on embodied CO2 emissions for each scenario

a) Production- and consumption based emissions (million tons) Production-based CO2 emissions

JPN KHM IDN LAO MYS PHL SGP THA VNM RSA

Consumption-based CO2 emissions

Ex-ante S1

S2

S3

S4

Ex-ante

S1

930.68 4.05 3.54 0.34 310.17 −0.14 0.90 0.05 166.74 0.93 61.53 0.29 62.28 0.74 202.59 1.09 78.58 4.20 18.32 −0.07

−1.07 0.02 2.34 0.01 1.09 0.42 0.31 1.34 0.46 0.12

−1.09 0.03 1.25 0.02 1.01 0.25 0.25 1.17 0.59 0.11

2.97 0.37 1.10 0.07 1.94 0.55 0.99 2.26 4.89 0.04

1108.08 7.10 5.52 0.19 278.95 −0.76 1.60 0.03 100.36 −0.23 69.34 0.77 50.41 0.25 147.97 0.81 76.46 1.82 20.07 −0.11

S2

S3

S4

0.36 0.02 1.68 0.01 0.41 0.34 0.21 0.71 0.24 0.10

0.22 0.02 0.81 0.00 0.31 0.16 0.19 0.57 0.28 0.04

7.32 0.21 0.06 0.04 0.09 0.94 0.44 1.38 2.12 −0.07

b) CO2 emissions embodied in trade (million tons) Export of embodied CO2 emissions Ex-ante S1 JPN 204.40 KHM 1.47 IDN 88.96 LAO 0.45 MYS 104.96 PHL 16.63 SGP 48.36 THA 103.38 VNM 34.90 RSA 4.43

2.59 0.24 0.86 0.04 1.09 0.33 0.67 1.45 2.55 0.04

Import of embodied CO2 emissions

S2

S3

S4

Ex-ante S1

S2

S3

S4

−0.79 0.01 0.88 0.01 0.77 0.15 0.23 0.79 0.28 0.04

−0.81 0.02 0.58 0.01 0.85 0.16 0.23 0.83 0.44 0.06

1.79 0.27 1.44 0.06 1.94 0.50 0.90 2.27 3.06 0.10

381.79 3.45 57.74 1.14 38.59 24.43 36.50 48.77 32.79 6.18

0.64 0.01 0.22 0.00 0.09 0.08 0.13 0.15 0.07 0.01

0.50 0.01 0.15 0.00 0.15 0.07 0.17 0.22 0.12 0.00

6.13 0.11 0.40 0.03 0.09 0.88 0.36 1.40 0.29 −0.01

5.63 0.10 0.25 0.03 −0.06 0.81 0.18 1.17 0.17 0.00

Note: The columns labeled “Ex-ante” and other columns indicate level of CO2 emissions and difference between ex-ante and ex-post CO2 emissions, respectively. Source: Authors’ calculations based on the GTAP 8.1 Data Base.

emissions. The difference of CO2 emissions between the S3 and S2 scenarios is −1.1 and −0.9 million tons in terms of production and consumption, respectively. Most decreases are induced from domestic final demand (−0.8 million tons). This can be attributed to an improvement of the emission coefficient in the electric industry, as noted in the previous section. Finally, we can examine the results of the S4 scenario. Basically, the result of the S4 scenario is the total of the S1 scenario and S3 scenario. Comparing with the S1 scenario, the ASEAN region’s production- and consumption-based CO2 emissions are larger in the S4 scenario. Despite the energy-augmenting technological change, the environmental load changes for the worse because of increases in capital. Even though we assume an energy-augmenting technological change

222 Kiyoshi Fujikawa and Hikari Ban

of 10 percent, which is an implausible figure, the ASEAN countries—except for Indonesia and Philippines—display higher CO2 growth rates in the S4 scenario relative to the S1 scenario.18

6.7 Concluding remarks In this chapter, we estimated the economic and environmental impact of FTAs, FDI, and energy efficient technology transfers between Japan and ASEAN using CGE and I-O analysis. The outline of our simulation results is as follows: 1.

2.

3.

Although FTAs are not likely to exert large effects on GDP, they are likely to exert relatively large effects on output, exports, and imports by industry. Some energy-intensive industries may move from ASEAN to Japan where energy efficiency is higher with the presence of FTAs. However, total CO2 emissions in Japan and the ASEAN region increase due to expansion of outputs and increases in energy-inputs. As the result of FDI from Japan to the ASEAN region, GDP and CO2 decrease in Japan while they increase in the ASEAN region. Here, FDI appears to have a larger effect than FTA. In Japan, production-based CO2 emissions decrease, but consumption-based CO2 emissions increase. In contrast, CO2 emissions grow in the ASEAN region, as evaluated by both measures. The simulation results show that the effect of energy-augmenting technological change on CO2 emissions varies across countries and industries. The reduction effect for CO2 emissions is dependent on input substitutions between energy, labor, and capital. Instead of energy efficient improvements, the expansion of outputs and the substitution of coal, for example, can increase CO2 emissions.

Overall, this discussion of results reveals the complex ways in which FTAs, FDI, and energy efficient improvements affect CO2 emissions. Changes in rates of technological progress and changes in the comparative advantages of countries could affect production structures. In addition, changes in the relative price of energy could alter the CO2 emissions coefficient. The direction and extent of change in energy prices are different across countries and industries. We also found that the economic relationship with EPA and non-EPA members is important when considering the effects of EPA. Finally, we briefly describe problems in our study and point out future issues. This study examined the effects of FDI under the ad hoc assumptions of specific situations. For a better estimation of the EPA effects, a CGE model with explicit modeling of FDI is helpful. By modeling barriers to FDI as a tax on profit, this can be treated as endogenous. Here, we used a static CGE model, but it is important to extend our research using a dynamic CGE model. Although we followed proportional procedures to estimate international I-O tables, introducing more accurate information into the model is necessary.

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Notes 1 AJCEP entered into force on December 1, 2008 for Japan, Singapore, Vietnam, Laos, and Myanmar, on January 1, 2009 for Brunei Darussalam, on February 1, 2009 for Malaysia, on June 1, 2009 for Thailand, and on December 1, 2009 for Cambodia and on July 1, 2010 for Philippines. The agreement covers trade in goods and services, investment, and economic cooperation. 2 For example, Mukhopadhyay and Thomassin (2010) analyze the economic and environmental impact of free trade in East and South East Asia. 3 Lejour and Rojas-Romagosa (2006) survey the literature on modeling FDI in CGE models. 4 A similar analysis on structure in environmental load can be applied to not only greenhouse gases but also water and land. Shimoda, Ye, and Fujikawa (2011) investigated the structural change in environmental load using an Asian international I-O table. 5 See Hertel ed. (1997) and the GTAP website for details. 6 The utility function of the GTAP-E model used here is the same as the standard GTAP model. 7 See Appendices 6.1 and 6.2 for additional details on the respective aggregation by country/region and industry. 8 The sum of increases in ASEAN countries’ initial capital stock is equal to approximately US$ 34,462 million, which corresponds to 0.218 percent of Japan’s initial capital stock. 9 The amounts of output change evaluated by the initial prices for the S1 scenario are listed in US$ (million dollars) as follows. For chemical products, China 391, the US 255, the EU 208; for mineral products, China 34, the US 314, the EU 6; for the electronic equipment industry, China 2,407, the US 1,556, the EU 1,403; and for other machinery and equipment, China 995, the US 755, and the EU 641. 10 The change rates (percent) of input prices paid by Japanese transport services industry in the S1 scenario are as follows: labor 0.52, capital 0.55, petroleum and coal products 0.09. Consequently, the change rates of Japan’s input demand are as follows: labor −0.23, capital −0.01, and petroleum and coal products 0.23. The shares (percent) of labor, capital, and petroleum and coal products to total cost in Japanese transportation services are 28.9, 13.9, and 14.4, respectively. 11 The change rates (percent) of input prices paid by electricity industry in the S3 scenario are as follows: Indonesia: coal −0.16, oil −0.02, gas −0.10, p_c−0.93, ely−1.35; Vietnam: coal −0.07, oil −0.03, gas 0.02, p_c−0.39, ely−0.31. 12 The CO2 emission here does not contain emission released from the combustion of fossil fuel at household and government. 13 We add a small complement because we omitted the details in Table 6.12. Productionbased CO2: OCE 377, HKG 78, KOR 372, TWN 240, IND 1,191, CAN 459, EEX 1,753, EEFSU 1,956, and ROW 1,745. Consumption-based CO2: OCE 381, HKG 101, KOR 384, TWN 171, IND 1,134, CAN 452, EEX 1,739, EEFSU 1,662, and ROW 1,861 (million tons). 14 For example, increases in Vietnam’s export to the US are as follows: textile and clothing US$ 749, 16.88 percent. Increases in China’s export to the US are as follows: electronics equipment US$ 408 million, 0.47 percent; other machinery and equipment US$ 206 million, 0.42 percent; other manufactures US$ 197 million, 0.26 percent; chemical products US$ 56 million, 0.32 percent. 15 Indonesia decreases industrial CO2 emissions by approximately 0.14 million tons in the S1 scenario. As the results of decomposition of changes in CO2 emissions, we found that the CO2 emission coefficient change contribution is 0.10 million tons, the technology change contribution is −0.35 million tons, and the final-demand change contribution is 0.10 million tons. See details in Appendices 6.3 and 6.4. 16 Japan’s electricity industry grows by −0.17 percent in the S2 scenario. Its input demand change rates (percent) are as follows: capital −0.24, coal −0.10, oil −0.15, gas −0.09, petroleum and coal products −0.16.

224 Kiyoshi Fujikawa and Hikari Ban

17 For example, the breakdown of Indonesia’s increase in CO2 emission (2.3 million tons) is as follows: final demand from own country at 1.5 million tons, Japan at 0.2 million tons, the US at 0.1 million tons, the EU at 0.2 million tons, and others at 0.3 million tons. 18 In the S4 scenario with technological change assumed to grow by 10 percent, Indonesia and Philippines increase CO2 emission by −1.60 percent and − 0.78 percent, respectively. The entire ASEAN region increases its CO2 emissions by 0.83 percent, which is higher than that in the S1 scenario (0.78 percent).

References Ban, K., Ohtsubo, S., Kawasaki, K. Ono, M., Matsuya, M., Tsutsumi, M., Kitaki, H., & Ono, H. (1998). Applied General Equilibrium Analyses of Current Global Issues: APEC Foreign Direct Investment New Regionalism and Environment. Economic Analysis Series, 156, Economic and Social Research Institute, In Japanese. Retrieved March 10, 2014, from http://www.esri.go.jp/en/archive/bun/abstract/bun156-e.html,http://www.esri. go.jp/jp/archive/bun/bun156/bun156.html Bems, R., Johnson, R. C., & Yi, K. M. (2010). Demand Spillovers and the Collapse of Trade in the Global Recession. IMF Economic Review, 58(2), 295–326. ——— (2011). Vertical Linkages and the Collapse of Global Trade. The American Economic Review, 101(3), 308–312. Burniaux, J. M. & Truong T. P. (2002). GTAP-E: An Energy-Environmental Version of the GTAP Model. GTAP Technical Paper, 16. Hertel, T. W. (ed.) (1997). Global Trade Analysis: – Modeling and Applications. Cambridge: Cambridge University Press. Johnson, R. C. & Noguera, G. (2012). Accounting for Intermediates: Production Sharing and Trade in Value Added. Journal of International Economics, 86(2), 224–236. Lejour, A. & Rojas-Romagosa, H. (2006). Foreign Direct Investment in Applied General Equilibrium Models: Overview of the Literature. CPB Memorandum, 169, CPB Netherlands Bureau for Economic Policy Analysis. Retrieved January 10, 2014, from http:// www.cpb.nl/node/10286 McDougall, R. & Golub, A. (2007). GTAP-E: Revised Energy-Environmental Version of the GTAP Model. GTAP Research Memorandum,15. Miller, R. E. & Blair, P. D. (2009). Input-Output Analysis Foundations and Extensions. Second Edition, Cambridge: Cambridge University Press. Mukhopadhyay, K. & Thomassin, P. J. (2010). Economic and Environmental Impact of Free Trade in East and South East Asia. Dordrecht, Heidelberg, London, New York: Springer. Shimoda, M., Ye, Z., & Fujikawa, K. (2011). An Empirical Study on Interdependency of Environmental Load and International I-O Structure in the Asia-Pacific Region. In Ji, H. and Ohnishi, H. (eds.), Essays on Economic Statistics in China and Japan, Beijing: Capital University of Economic and Business Publishing, 200–220. Truong, T. P. (2007). GTAP-E: An Energy-Environmental Version of the GTAP Model with Emission Trading – USER’S GUIDE, GTAP Resource, 2509, Retrieved December 12, 2013, from https://www.gtap.agecon.purdue.edu/resources/res_display. asp?RecordID=2509

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Appendix 6.1 Country/Region Aggregation Code

GTAP region

OCE CHN HKG JPN KOR TWN KHM IDN LAO MYS PHL SGP THA VNM RSA IND CAN US EEX

Australia, New Zealand China Hong Kong Japan Korea Taiwan Cambodia Indonesia Lao People’s Democratic Republic Malaysia Philippines Singapore Thailand Vietnam Rest of Southeast Asia India Canada United States of America Mexico, Argentina, Bolivia, Colombia, Ecuador, Venezuela, Iran Islamic Republic of, Kuwait, Oman, Qatar, Saudi Arabia, United Arab Emirates, Egypt, Rest of North Africa, Nigeria, and Central Africa Austria, Belgium, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, United Kingdom, Bulgaria, and Romania Albania, Belarus, Croatia, Russian Federation, Ukraine, Rest of Eastern Europe, Rest of Europe, Kazakhstan, Kyrgyztan, Rest of Former Soviet Union, Armenia, Azerbaijan, and Georgia Rest of Oceania, Mongolia, Rest of East Asia, Bangladesh, Nepal, Pakistan, Sri Lanka, Rest of South Asia, Rest of North America, Brazil, Chile, Paraguay, Peru, Uruguay, Rest of South America, Costa Rica, Guatemala, Honduras, Nicaragua, Panama, El Salvador, Rest of Central America, Caribbean, Switzerland, Norway, Rest of EFTA, Bahrain, Israel, Turkey, Rest of Western Asia, Morocco, Tunisia, Benin, Burkina Faso, Cameroon, Cote d’Ivoire, Ghana, Guinea, Senegal, Togo, Rest of Western Africa, South Central Africa, Ethiopia, Kenya, Madagascar, Malawi, Mauritius, Mozambique, Rwanda, Tanzania, Uganda, Zambia, Zimbabwe, Rest of Eastern Africa, Botswana, Namibia, South Africa, Rest of South African Customs, and Rest of the World

EU

EEFSU

ROW

Source: The GTAP 8.1 Data Base.

226

Kiyoshi Fujikawa and Hikari Ban

Appendix 6.2 Industry Aggregation Code

GTAP sector

prm

Paddy rice, Wheat, Other cereal grains, Vegetables/fruit/nuts/Oil seeds, Sugar cane/ sugar beet, Plant-based fibers, Other crops, Cattle/sheep/goats/horses, Other animal products, Raw milk, Wool/silk-worm cocoons, Forestry, Fishing Coal Oil Gas, Gas manufacture/distribution Petroleum and coal products Electricity Other minerals Meat (cattle/sheep/goats/horse),Other meat products, Vegetable oils and fats, Dairy products, Processed rice, Sugar, Other food products, Beverages and tobacco products Textiles, Wearing apparel Chemical/rubber/plastic products Paper products, publishing Ferrous metals Other mineral products Motor vehicles and parts Other transportation equipment Electronic equipment Other machinery and equipment Leather products, Wood products, Other metals, Metal products, Other Manufactures Sea transport, Air transport, Other Transport Water, Construction, Trade, Communication, Insurance, Other financial services, Other business services, Recreation and other services, Public Administration/ Defense/Health/Education, Dwellings

col oil gas p_c ely omn food

tex crp ppp i_s nmm mvh otn ele ome omf tsp svc

Source: The GTAP 8.1 Data Base.

Appendix 6.3 Structural decomposition Equation [6.7] can be used for structural decomposition analysis. Compare an economy at two different points in time. Let a prime note a later point in time. The left hand side of Equation [6.7] is as follows: ε = êLf and ε′ = êL′f ′,

[6.A1]

Where ε is the vector of production-based CO2 emission by region. The change in CO2 emission over time is Δε = ê′L′f ′ – êLf.

[6.A2]

According to Miller and Blair (2009, p.606), we can decompose the change in CO2 emission as follows: Δε = (1/2)(Δê)(Lf + L′f ′) + (1/2)(ê(ΔL)f ′ + ê′(ΔL)f ) + (1/2)(êL + ê′L′)(Δf ). [6.A3]

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The first term on the right hand side is the CO2 emission coefficient change contribution, second term is the technology change contribution, and third term is the final demand change contribution. We applied Equation [6.A3] to ex-ante and ex-post international I-O table and decomposed the changes in CO2 emission for each scenario. The results are shown in Appendix 6.4.

Appendix 6.4 Decomposition of Changes in CO2 Emissions a) The S1 and S2 scenarios (million tons) S1 (1) JPN KHM IDN LAO MYS PHL SGP THA VNM RSA

1.97 0.12 0.10 0.01 0.63 0.36 0.12 1.30 2.45 0.00

S2

(2)

(3)

Total

1.61 0.16 −0.35 0.01 −0.39 −0.10 0.34 −1.30 0.01 −0.05

0.47 0.06 0.10 0.03 0.68 0.03 0.27 1.09 1.74 −0.02

4.05 0.34 −0.14 0.05 0.93 0.29 0.74 1.09 4.20 −0.07

(1) 0.30 0.00 0.38 0.00 0.03 0.01 0.02 0.10 0.02 0.01

(2)

(3)

Total

−0.96 0.01 0.79 0.00 0.63 0.16 0.17 0.60 0.24 0.04

−0.42 0.01 1.16 0.00 0.43 0.24 0.11 0.64 0.20 0.07

−1.07 0.02 2.34 0.01 1.09 0.42 0.31 1.34 0.46 0.12

(3)

Total

b) The S3 and S4 scenarios (million tons) S3

JPN KHM IDN LAO MYS PHL SGP THA VNM RSA

S4

(1)

(2)

(3)

Total

(1)

(2)

0.34 −0.02 −1.83 0.00 −0.85 −0.34 −0.38 −1.16 −0.40 −0.13

−1.05 0.02 1.18 0.01 1.05 0.19 0.41 1.03 0.50 0.10

−0.38 0.03 1.89 0.01 0.81 0.39 0.22 1.30 0.49 0.13

−1.09 0.03 1.25 0.02 1.01 0.25 0.25 1.17 0.59 0.11

2.32 0.10 −1.73 0.01 −0.22 0.02 −0.26 0.14 2.06 −0.12

0.55 0.19 0.84 0.02 0.66 0.10 0.75 −0.27 0.56 0.05

0.10 0.08 1.99 0.04 1.50 0.42 0.50 2.39 2.28 0.11

2.97 0.37 1.10 0.07 1.94 0.55 0.99 2.26 4.89 0.04

Note: The columns labeled (1), (2), and (3) indicate the CO2 emission coefficient change contribution, technology change contribution, and final demand change contribution, respectively. Source: Authors’ calculations based on the GTAP 8.1 Data Base.

7 FDIS AND ENVIRONMENTAL MANAGEMENT Do we need government interventions? Muhammad Cholifihani

7.1 Introduction With the ongoing process of globalization, the problems associated with “pollution havens” came to light in the early 1970s. The discussions still continue today on how the world should deal with pollution intensive companies in developed countries—such as those in iron and steel industries, chemical industries, and paper and pulp industries—relocating to developing countries where they can enjoy weaker environmental regulations and lower environmental taxes. As a matter of fact, CO2 emission by the lower middle-income countries has been on the rising trend during the last 30 years with their average per capita GNI more than doubled during the same period. The FDIs percentage to GNI in the lower

1.90 CO2 emissions (metric tons per capita) 1.70 1.50 1.30 1.10 0.90

0.50

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 2010

0.70

FIGURE 7.1

CO2 emissions in lower middle income countries (metric tons per capita)

Source: International Energy Statistics.

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1400.0 GNI per capita (constant 2005 US$) 1200.0 1000.0 800.0 600.0 400.0

0.0

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 2010 2011 2012

200.0

FIGURE 7.2

GNI per capita in lower middle income countries in 1981–2012

Source: World Development Indicator, World Bank.

middle-income countries has increased dramatically from 1.9 percent in 2003 to 3.9 percent in 2008. GNI per capita during the period of 2003 to 2012 pointed out a similar pattern with FDIs percentage to GNI. The growth of GNI per capita during that period increased by an average 6 percent per year. In order to attract new FDIs, the developing countries may purposely undervalue the environment. Do FDIs, seeking a “pollution-haven,” undermine

4.50

Foreign direct investment, net inflows (% of GDP) 4.00 3.50 3.00 2.50 2.00 1.50 1.00 0.50 0.00

1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011

FIGURE 7.3

Foreign direct investment, net inflows in lower middle income countries (% of GDP)

Source: World Development Indicator, World Bank.

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environmental management in the developing countries? On the other hand, does technology transfer associated with FDIs from industrial countries provide cleaner technology and thus potentially improve environmental outcomes in the host developing countries? This chapter introduces some positive and negative experiences among developing countries on the impact of FDIs on growth and environmental outcomes. The chapter also draws cases and empirical analyses from the Indonesian experience. What should the governments of FDI-hosting developing countries do in order to mitigate the conflicts between positive growth impact and negative environmental outcome? What are the possible strategies for the developing countries to make FDIs compatible with better environmental management?

7.2 Literature review Some literature points out that FDI and environmental impacts are debatable, whether a positive or negative impact of FDI to the environment. The Pollution Havens theory suggests that investors will seek other countries to locate their industries where it will be cheaper and more efficient in light of regulatory requirements (Kevin 2002).1 Xing and Kolstad (2002) supported the hypothesis of Pollution Haven. They found that US chemical companies migrated to developing countries basing their decision on the laxity of environmental regulation governing pollutant emission. Levinson and Taylor (2008) examine the effect of environmental regulations on trade flows. A simple model demonstrates how unobserved heterogeneity, endogeneity, and aggregation issues bias standard measurements of this relationship. They applied a reduced-form estimate of the model, using data on US regulations and trade with Canada and Mexico for 130 manufacturing industries from 1977 to 1986, and indicated that industries whose abatement costs increased most experienced the largest increases in net imports. Pollution abatement cost and net imports may be negatively correlated in panels of sector-level data. This negative correlation can easily bias estimates against finding a pollution haven effect. Using a sample of 27 OECD source countries and 99 host countries considered over the period 2001–2007, the study by Kalamova and Johnstone (2011) attempted to find out the relationship between environmental regulation and FDI to see whether the Pollution Haven argument exists. They predicted that increased liberalization of trade may lead to the relocation of pollution from countries with strict environmental regulations to the developing countries by relatively more lax environmental regulation. The result was interesting. They found two major results from the analysis. FDI inflows emerge from developed and developing countries to the host country which has relatively lax stringency. It is a statistically significant positive effect in the range of 2.7 percent to 5.5 percent. The second result shows an inverse U-shape, and thus reverses under a certain level of environmental stringency regulation of developing host countries.

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There are three arguments why non-liniar relationships exist: i.

increasing stringency regulation may increase production costs and reduce the attractiveness of the country for foreign investors in a certain level; ii. economies of standardization across different production locations may lead to investment from OECD to non-OECD investment in a certain level that is more or less costless; and, finally, iii. there may be a signaling role played by environmental policy below this level, with excessively lax policy which indicates less attractive environment for investment. A study by Kevin (2002) identified theories on environmental regulatory competition on Race to the Bottom Theory, Race to the Top Theory, and Regulatory Chill. These theories are mostly a subset of and counter to Pollution Haven Hypothesis (PHH).2 Talukdar and Meisner (2001) found that FDI and the presence of a wellfunctioning domestic financial market are likely to have positive impacts on the environment. They said that FDI in developing countries acts as a “conduit” for advanced and cleaner technology. Kearsley and Riddel (2010) investigated the PHH by applying log functional form of 27 OECD countries. They found that PHH existed weakly in countries observed as more positive and significant coefficients for the dirty imports sector presented in the regression.

7.3 Case study of Indonesia Indonesia has liberalized its FDI regime over the past 25 years. From 1985 to 1997 cumulative FDI inflow to Indonesia increased significantly from US$ 310 million to US$ 4.7 billion. However, due to the 1997 Asian financial crisis, FDI decreased dramatically to −3 percent of GDP in 2000 and to almost 3 percent of GDP in 2005 (World Development Indicator 2011). Since 2000, the average annual FDI inflow was almost US$ 8 billion. FDI in 2010 was recorded at US$ 12.7 billion. It was the first time the FDI inflows have exceeded US$ 10 billion. However, the contribution of FDI to gross fixed capital formation has been relatively small, compared to other ASEAN peers. Nonetheless, FDI has created jobs, boosted productivity growth, and improved access to the global market (OECD 2011). Realization of FDI from January to September 2012 was US$ 18.2 billion. It was higher at around 27 percent when comparing January 2011 to September 2011 (The Investment Coordinating Board of Indonesia/BKPM report, quarter 4, 2012).

7.3.1 Characteristics and figures of FDI and green house gases in Indonesia The three largest sectors of FDI inflow from 2006 to 2012 are manufacturing, mining and quarrying, and transportation, storage, and communications. The FDI in these sectors surged from 2006 to 2012 (Indonesian Financial Statistics, 2013).

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In terms of direct investment flow in Indonesia by sector and ASEAN countries, mostly Singapore, Malaysia, and Thailand are the three largest ASEAN countries that invested in manufacturing, mining and quarrying and transportation, storage, and communication. The other seven ASEAN countries contributed a small amount of investment in Indonesia from 2006 to 2012. Japan is the largest country that invested in Indonesia during realization of FDI from January to December 2013 followed by Singapore and the US. Japan contributed around 16.5 percent of total realization of FDI. Singapore invested 16.3 percent and the US contributed 8.5 percent. The amount of FDI realization during January to December 2013 was significant by US$ 4.7 billion for Japan, US$ 4.7 billion for Singapore, and US$ 2.4 billion for the US (Domestic and FDI Realization in Quarter IV and January–December 2013). The Investment Coordinating Board of the Republic of Indonesia (BKPM) reported that Java is the biggest province to receive FDI, particularly West Java. This province accepted around US$ 7.1 billion. Banten, East Java, and Papua provinces received US$ 3.7 billion, US$ 3.4 billion and US$ 2.4 billion respectively based on realization of FDI from January to December 2013. Comparing other provinces in Indonesia, more than 50 percent of FDI was located in Java. Direct investment flow from abroad noted more than 271,000 laborers were absorbed. This amount is higher than domestic investment absorption of the workforce; the contribution of FDI was significant in the 4th quarter of 2013. Meanwhile, domestic investment absorbed around 37.1 percent of the workforce. Green house gases (GHGs) are defined as gases in the atmosphere both naturally and anthoropogenically, which absorb and re-emit infrared radiation (Presidential Degree No. 61/2011). A GHG3 is a gas in the atmosphere that absorbs and emits radiation within the thermal infrared range. The president of Indonesia has promised to reduce GHGs by 26 percent unilaterally and up to 41 percent with international support in the year 2020 at the G-20 Summit in September 2009. To achieve the GHG target, the Government of Indonesia has issued Presidential Regulation No. 61 Year 2011 on the National Action Plan for Greenhouse Gas Emission Reduction (RAN-GRK). RAN-GRK is a document that provides the legal framework for the Indonesian national and local governments, communities, and business to reduce GHG emissions. The RAN-GRK is a plan to reduce GHG emissions during the period 2010–2020 in accordance with the Long-term Development Plan (RPJP 2005– 2025) and the Medium-term Development Plan (RPJM). To support the goal of 26 percent to 41 percent reduction of GHG emissions, the government of Indonesia issued Presidential Regulation No. 71 Year 2011 on the Regional Action Plan for Green House Gas Emission Reduction (RADGRK) as a guideline for regional governments to create an action plan in each province (Government Action Plan 2013, Bappenas). The targets of 26 percent and 41 percent have been developed based on input from ministries’ strategic planning document in Indonesia. And it will be used as a reference by all related ministries and local government to develop programs for the reducing climate action plan. A reduction of 26 percent of GHGs is equal

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to a decline of 0.767 Gt CO2. The Ministry of the Environment in Indonesia calculated that the cost needed to achieve the 26 percent reduction is 83.3 trillion rupiah (US$ 8.96 billion). The cost will be increased to 168.25 trillion rupiah (US$ 18.09 billion) when the target of 41 percent is achieved. Figures 7.4 and 7.5 show that the trend of CO2 gas emission is rising year by year. Beginning in 1981, CO2 per capita was almost 0.8 metric ton per capita and was getting higher in 1997. From 1998 to 2010, CO2 emission per capita almost doubled. In the same year, FDI peaked by almost 2.5 percent of GDP. However, due to the Asian financial crisis, direct investment from abroad declined dramatically to −2.5 percent of GDP in 2001. Liberalization of trade made the significant 4.00 FDI

2.00 1.00

85 19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 20 09

83

19

−1.00

19

81

0.00

19

Percentage of GDP and metric ton percapita

CO2 3.00

−2.00 −3.00 −4.00

FIGURE 7.4

Greenhouse gases and FDI in Indonesia

Source: International Energy Statistics, and World Development Indicator, World Bank 1800.00

ENV

1600.00

GNI

1400.00 1200.00 1000.00 800.00 600.00 400.00 200.00

FIGURE 7.5

19 87 19 89 19 91 19 93 19 95 19 97 19 99 20 01 20 03 20 05 20 07 20 09 20 11

19 85

19 83

19 81

0.00

GNI per capita and emission reduction in Indonesia 1981-2011 (US$)

Source: International Energy Statistics, and World Development Indicator, World Bank.

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achievement of FDI to almost 3 percent of GDP in 2005, which then fluctuated until 2010.

7.3.2 Empirical study The main objective of this empirical study is to analyze whether FDI to Indonesia resulted in a better environment or vice versa. The model adopted is from the Meisner (Talukdar and Meisner 2001) equation. Meisner (Talukdar and Meisner 2001) investigated whether greater involvement of the private sector in an economy helps or hurts the environment. Meisner used some independent variables such as GNP per capita, value added share of the industrial sector, value added share of the agriculture sector, time trend, degree of private sector involvement, degree of capital market, FDI, and trade.

7.3.3 Empirical model The model for this study is LENVt = a + αLGNICt + βLTRADEt + γ LFDIt + ε α>0β>0γ>0

(1)

where ENV is CO2 metric tons per capita, GNIPC is Gross National Income per capita constant price 2005 (US$), TRADE represents the total value of export and import as a percentage of GDP, and FDI is foreign direct investment as a percentage of GDP.

7.3.4 Data and variables This study uses time series data from a single country analysis of Indonesia from 1981 to 2011. Almost all data are taken from World Development Indicators and International Energy Statistics. This research uses CO2 emissions as the environmental pollution measure since CO2 is believed to be the primary GHG responsible for global warming and its regulation has been an important inter-governmental issue (Talukdar and Meisner, 2001; Hoffman et al., 2005). Other reasons to utilize CO2 as a dependent variable are mostly activities in Indonesia such as agriculture, forestry and peat land, energy and transportation, industry, and waste management exhaust green house emission of CO2 (ICCSR 2009). The emissions produced are quite significant. Finally, series data for CO2 are available.

Gross National Income Per capita (GNIPC) GNIPC is used to calculate the scale impact of the economy on the level of CO2 emissions per capita. GNIPC is tested for whether it has a positive impact on

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CO2. Meisner (Talukdar and Meisner 2001) found that the relationship between a pollutant variable and the economy is likely an inverted U curve (EKC curve). A pollutant is likely to increase due to improving income per capita. Moreover, Cole (2004) tested the linkage between the PHH and the Environmental Kuznets Curve (EKC) inverted U. An early study which investigated EKC is the Grossman and Krueger (1994) paper. They discussed the indicator of urban air quality. Sulfur dioxide and smoke display an inverted U-shaped relationship with GDP. These pollutants appear to rise with GDP at low levels of income, but eventually reach a peak, and then fall with GDP at higher levels of income. A study by Iwata, Okada, and Samreth (2012) investigated EKC for CO2 pollutants from 11 OECD countries by employing the Autoregressive Distributed Lag (ARDL) model of nuclear energy in electricity production. However, in general, the study by Iwata et al. (2012) provides poor evidence for the EKC hypothesis for CO2 gas emission.

Summation of export and import as percentage of GDP (TRADE) This study will test a positive relationship between the trade variable and CO2 emissions. Some literature suggested a positive relationship between FDI and trade and CO2. It was argued that raising output, trade, and FDI intensifies pollution in developing countries. Other studies suggest that trade and FDI have a negative relationship with GHGs. They argue that outward oriented developing countries in the form of higher trade and FDI will have greater access to new, cleaner environmental technologies (Blackman and Wu 1998; Eskelend and Harrison 2003). A recent study by Iwata, Okada, and Samreth (2012) employed trade as one of the independent variables. Trade is defined as the sum of export and imports. They pointed out that the trade variable had a positive and negative effect on CO2 in the countries investigated. However, mostly the variable is not significant.

FDI as percentage of GDP A positive relationship between FDI and CO2 emissions will be tested in this chapter. PHH might exist when a higher contribution of FDI affects higher pollutant (Cole, 2002, Meisner 2001, Blomquist 2008). However, other studies by Blackman and Wu (1998), and Eskelend and Harrison (2003) argue that FDI improves the environment. Increasing FDI from developed countries to recipient countries has improved the environment.

7.3.5 Empirical results The time series literature suggests checking unit root tests in each variable before estimating any equation. Estimating based on non-stationarity (unit root exists)

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may lead to spurious results with high R2 and t statistics, but without any coherent economic meaning and an inconsistent parameter estimator (Granger and Newbold 1974; Pyndick and Rubinfeld 1998). Therefore, it is important to check whether a series is stationary or not before using it in a regression. The formal method to test the stationarity of a series is the unit root test. In order to check the existing unit root in each variable, the Augmented Dicky–Fuller (1979) test is applied using the following equation: ΔYt = f(constat,Trend,Yt−1,ΔYt−1,. . .,ΔYt−p+1)

(2)

where Yt represents the relevant time series.4 The null hypothesis is that the variables under estimation will have unit root. By checking unit root for all variables, it was shown that all variables are stationary in the first difference (delta). It means all series integrated in order one, I (1). The result is shown in Table 7.1. Once all series variables exist in the same first difference, the Johansen cointegration test among those variables (CO2, GNI, trade, and FDI) could be applied. Furthermore, Mukherjee (1998) and Engle and Granger (1987) suggest checking residuals of series of all variables is important to confirm all variables are cointegrated.5 This study uses the Johansen (1988) and Johansen and Juselius (1990) maximum likelihood method to estimate one single cointegration relationship. This method depends on direct investigation of cointegration in the vector autoregressive (VAR) representation and produces maximum likelihood estimators of the unconstrained cointegration vector, but it allows one to explicitly test for a number of cointegration vectors: LENVt = a + αLGNICt + βLTRADEt + γ LFDIt

(3)

By applying the Johansen cointegration test to investigate whether there is more than one single cointegration relationship, this study found that one cointegration exists in the series of variables (Table 7.2). Trace statistics confirm that only one cointegration exists in the series. It means by applying the Johansen cointegration test among all variables, CO2, GNI, trade, and FDI have a long-run relationship (Table 7.3). TABLE 7.1 Result of ADF test for non stationarity

Variables

ADF test in level

ADF test in first difference

LENV LGNI LTRADE LFDI

−1.26 −2.48 −3.28**) −3.75***)

−5.43***) −3.08**) −3.14**) − 6.69***)

Source: Author calculation. All variables are in a number of lags 1. Critical Value: ADF critical value for levels at 1% (***) and 5% (**) significance are −3.68 and −2.97 ADF critical value for first difference at 1% (***) and 5% (**) are −3.71 and −2.98.

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TABLE 7.2 Johansen Cointegration Test

Hypothesized No. of CE

Eigenvalue

Trace Statistic

Probability*)

None At most 1 At most 2 At most 3

0.641837 0.618878 0.275488 0.095865

70.01864 40.24242 12.26797 2.922515

0.0139 0.0903 0.7931 0.8856

Note: Trace test indicated 1 cointegrating equation(s) at the 0.05 level, CE = Integrating equation, *) = MacKinnon–Haug–Michelis (1999) p-values Source: Author calculation.

TABLE 7.3 Long run equilibrium equation (long run elasticity) Dependent Variable: Log CO2 emission per capita

Independent Variables

Coefficient

Log (GNI)***) Log (TRADE)***) Log (FDI)

1.083 0.064 0.015

Notes: 1) The asterisks (***) indicates statistical significance at 1% significance level, 2) The critical value at 1% significance level is 2.576 (two-tail). Source: Author Calculations.

The result shows that only FDI is not significant and the coefficient is positive. Output variable and trade are positively significant. Both variables are plausible and consistent with the hypothesis. An increase of 1 percent elasticity of FDI will likely not reduce environmental quality in Indonesia. Increasing FDI does not lead to influencing green house gas emissions (CO2) in a country. A study by Merican et al. (2007) showed that in the case of Indonesia, the relationship between FDI and CO2 was negative and significant. This result is also consistent with other previous studies by Blackman and Wu (1998), and Eskelend and Harrison (2003). They argued that FDI improves the environment. Increasing FDI from developed countries to recipient countries made the environment cleaner and better. This result is interesting as Indonesia has lots of room to boost investment from abroad. Many MNEs in Indonesia might not deplete the environment during the period of study. FDI in Indonesia has benefited environmental conditions. The negative coefficient of FDI supported the label that the PHH might not exist in Indonesia. Studies by Blackman and Wu (1998) and Eskelend and Harrison (2003) showed an interesting result as trade and FDI are likely improving the environment. They argue that developing countries which are outward oriented, in the form of higher trade and FDI, will have greater access to new, cleaner environmental technologies. This result is also consistent with a study by Abimanyu (2000).

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Applying the general equilibrium model to Indonesia, Abimanyu found that trade flow had a greater negative impact on pollution than domestic production. He suggested that international trade is less harmful to the environment. A variable of capital has a positive coefficient and is significant with CO2. It means more capital leads to environmental degradation. It is plausible and straight forward. Increasing per capita income in Indonesia leads to more CO2. A study by Shofwan and Fong (2011) showed an insignificant relationship between GDP and CO2. The study used a single country analysis of Indonesia. Another study by Y. Merica et al. (2007) showed that the relationship between GNI and CO2 is positive and insignificant in the case of Indonesia. They used data from five ASEAN countries and employed Autoregressive Distributive Lag (ARDL).

7.4 Benefits and costs of FDI on environment Countries benefit from FDI inflow by increasing their productive capacity, gaining spillover effects, and developing their export sector. The spillover effect of FDI inflow may be as technology transfer, capacity building, and training, including skills to domestic firms. Companies are also introducing new technology and refurbishing existing installations, which will result in better environmental performance. In order to gain benefits, countries have incentives to attract foreign investors. These incentives may be financial and fiscal incentives or pressure on labor or environmental standards. However, offering incentives may be similar to giving tax breaks for domestic saving or domestic investment (Boocock, 2002). Capacity building with respect to a policy framework of environment issues in developing countries may be useful as economical and environmental benefits may be attained. Therefore assistance from OECD countries or other multilateral organizations such as the World Bank, ADB, or others may play an important role in facilitating capacity building. Kalamova and Johnstone (2011) argue that the effect of environmental policy stringency on FDI is small relative to other factors. For instance, a general measure of regulatory quality (i.e., bureaucratic transparency, increased flexibility, consistency of enforcement) has significant and positive impacts on FDI inflows. Therefore, the quality of regulation may increase FDI inflows for those countries where weak environmental policies serve as a negative signal to investors. However, lack of institutional capacity is weakening efforts in FDI host countries to implement effective environmental regulation. Another problem is that although environmental laws have been enacted, the actual decrees and regulations setting environmental standards are disseminated only after a long delay (Boocock 2002).6 In this respect, governments should consider applying internationally acceptable environmental standards (e.g. WHO, World Bank) rather than developing home-grown ones. FDI inflow from OECD countries to the sub-Saharan African countries may lead to environment degradation. In Ghana, for example, the cost of environmental degradation to the economy in 1988 was estimated at US$ 189 million,

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of which at least US$ 17 million was a result of mining activities. This is equivalent to 4 percent of GDP, while GDP growth was 5 percent. This growth thus occurred almost entirely at the expense of the country’s natural resource base, and is unsustainable (Acquah, 1995). Therefore, environmental rehabilitation cost is an important matter in mining projects. Dedicated trust funds or bank guarantees are alternative sources to cover rehabilitation costs. Some issues that may need addressing in this respect are (Nazari, 1999): i.

Ensuring that environmental impact assessments and feasibility studies outline cost rehabilitation and closure plans. ii. Premature closure during construction. Mitigation would require completion guarantees and implementation of a satisfactory closure plan. iii. Clear definition of post-mining land use objectives, environmental standards required and sign-off procedures iv. Periodic review of closure plans, costs, and financial guarantees in order to take into account changes to the project, and outside factors such as inflation. v. Financial failure and use of closure funds for other purposes. These can be prevented by setting up a separate non-fungible financial structure for the funds. vi. Guarantees must be provided prior to construction and operation, as closure occurs when a project is no longer viable, and thus unable to generate the necessary funds.

7.5 Environmental management and public policies Environment regulation on controlling pollution started in the 1970s. In order to regulate emissions, emission standards were introduced. However, implementation of regulation related to emission control may face difficulties due to cost of implementation and enforcement. Some policy instruments were introduced to tackle these difficulties such as economic instruments, voluntary approaches including voluntary agreement and informational regulation (Anbumozhi et al. 2011). Voluntary agreement generally involves private companies and government. The government includes central, local, or affected communities. The process is that private companies together with the government commit to reduce emissions to some certain level. Since this agreement is based on the relationship between the private sector and government, it may be easy to bring in regulations. Table 7.4 describes how some countries aim to reduce emissions by 2020. The pledge issued at COP 15 is included in the Copenhagen Accord. Developing countries attempt to reduce emissions by a percentage of their GDP. Action taken by developing countries may involve private companies together with the government to achieve the target (Table 7.5). Some policies and strategies undertaken by the government including an action plan to reduce emissions raise questions regarding how the government should enact the strategies. Which businesses take a part in reducing emissions together with government?

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TABLE 7.4 Selected countries commit to reduce emission

Country’s name Appropriate Mitigation Effort Brazil

• increasing energy efficiency leading to a decrease • • • • •

in electricity consumption by 10% in 2030, compared to current levels; maintaining a high proportion of Brazil’s electricity supply from renewable sources encouraging the increased use of biofuels in the transport sector sustained reduction in de-forestation rates, particularly in the Amazon region increasing research and development to precisely identify environmental impacts and minimize the costs of adaptation eliminating net loss of forest coverage by 2015 through re-forestation and establishment of forest plantations.

Emission Reduction target in 2020 Brazil’s voluntary national greenhouse gas reduction target of between 36.1% and 38.9%

Indonesia

• Sustainable peat land management • Reduction in Rate of deforestation and land degradation • Development of carbon sequestration project in Forestry and Agriculture • Promotion of energy efficiency

26% and 42% (international assistance)

India

Reduce the emission of its GDP

20 –25%

South Korea

The reduction of GHG in the energy sector is being promoted by targeting energy supply and demand, heating and cooling of buildings and transportation fuel. As regards energy demand, GHG reduction is being achieved through an integrally managed energy conservation policy and improvements in energy efficiency. For energy supply, policies are being devised to expand the use of RES and cleaner energy.

It designed to reduce the country’s GHG emissions by 30% from projected levels by 2020.

PRC

• Increase the share of non fossils fuels in primary energy consumption to 15% • Increase forest coverage by 40 million hectares • Forest stock volume by 1.3 billion m3.

Reduce gas emission by 40 –50% in 2020

Source: http://unfcc.int/home/items/5265.php and http://www.climate-policy-watcher.org/

As we know, business can be an engine for developing Asia’s recent economic growth. However, business has also caused environmental degradation in the world. Business has a bigger role due to globalization and modernization and mass production and consumption by them. Therefore issues of collaboration between these sectors (government and private) is inevitable. The UNDP 2003 indicated that it is increasingly in the interest of business to be part of the solution for minimizing emissions rather than part of the problem.7

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TABLE 7.5 Major policies by selected developing countries for emission reduction

Country

Policies and Strategies

Indonesia

• Government of Indonesia issued Presidential Regulation number 61 •

China

South Korea

year 2011 on the National Action Plan for Greeenhouse Gas Emissions Reduction (RAN-GRK). The activities of RAN-GRK comprise the following matters: a) Agriculture; b) Forestry and peat land; c) Energy and transportation; d) Industry; e) Waste management; f ) Other supporting activities.

• Adjust the economic structure to promote optimization (Accelerating service industry in 2000) • Improve energy efficiency and safe energy. • Optimize energy mix and develop renewable energy • Implementing national green growth strategy by Government and action plan with investment 86 million US$ during 5 years.

India

• Set up Indian National Network for Climate Assessment (INNCA) • Set up emission inventory • Develop state action plan • Approve National Policy on Biofuel

Source: http://www.ccchina.govv.ch/, http://india.gov.in/, http://climatechange.menlh.go.id, Korean Energy Management Corporation 2010.

7.6 Concluding remarks Developing countries have benefited from FDI inflow through increasing their productive capacity, gaining spillover effects, and developing their export sector. The spillover effect of FDI inflow may be as technology transfer, capacity building and training, including skills to domestic firms. Companies are also introducing new technology and refurbishing existing installations, which will result in better environmental performance. Government intervention is needed to regulate emissions by introducing emission standards. However implementation of regulations related to emission control may face difficulties due to the cost of implementation and enforcement. Some policy instruments have been introduced to tackle these difficulties such as economic instruments, voluntary approaches including voluntary agreement and informational regulations. Currently, many empirical studies on environment management focus on cross country analysis in various regions instead of individual country analysis. Single country analysis has been rare as each country has its own problems and characteristics concerning the environment issue. Therefore this chapter has also investigated the country analysis of Indonesia. This study analyzed the impact of FDI on CO2 in Indonesia. By applying the Johansen (1990) cointegration test for Indonesia’s

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data from 1981 to 2011, it has been found that increasing 1 percent elasticity of output leads to increasing CO2 gas emissions by 1.1 percent. And increasing 1 percent of the trade variable could increase green house gases by 0.06 percent. The FDI variable indicated a positive coefficient on CO2 by very small elasticity. However the FDI variable is not statistically significant. It means the Pollution Haven did not exist in Indonesia. FDI may not destroy the environment in Indonesia. In sum, GNI per capita and trade variables contributed positive significantly to CO2 gas emission in Indonesia during the period of research. As PHH was not confirmed in the analysis, the government of Indonesia may focus on how to attract more foreign investors. The government may invite multinational enterprises to invest more in Indonesia. To attract more investors, Indonesia should simplify and accelerate the investment procedure with lower costs and a transparent manner. Expansion of the utilization of the National Single Window (NSW)8 facility is mandatory to improve national logistics systems. Finally, improvement of labor workforce conditions is important through harmonizing of labor regulations with the synergy of central and local government policy on labor. Coordination and synchronization between the central government and local governments to reduce CO2 emissions is useful to achieve the target of reducing CO2 by 26 percent, to 41 percent. These agendas could improve direct investment inflow in Indonesia and attract a high quality of FDI. And at the same time they could lead to a better environment. The choice of CO2 as a dependent variable in this chapter might be attached to other green house gas estimations such as SO2, NH4, NOx, and others. Limitations of choice of dependent variable and additional independent variables as estimators are recommended for further research.

Notes 1 2

3 4 5 6

Firms will relocate their investment where they can benefit from incentives in tax, licensing requirement, level of enforcement of regulations. The race to the bottom is a subset of the pollution haven phenomenon as it consists of a positive action by a government lowering environmental standards, which in turn brings in foreign investment. Race to the Top theory leads to stronger environmental policies and can improve competitiveness in the marketplace by fostering innovation and efficiency, therefore attracting investors. Whereas regulatory chill theory explained that countries refrain from enacting strike environmental standards in reply to the fear of losing a competitive edge against other countries in attracting FDI. The primary greenhouse gases in the Earth’s atmosphere are water vapor, carbon dioxide, methane, nitrous oxide, and ozone. Detailed derivation of equation (2) is explained in Johnston and Dinardo (1997), Chapter 7. Checking residual by ADF test shows that residual is stationarity in order level, I(U). It means all series of variables are cointegrated. In some cases the delays may attain several years (for example, in Cameroon despite environmental legislation being passed in 1996, regulations were yet to be drafted in September 2000), which inhibits enforcement of the law. There are probably several reasons for the delays, including lack of institutional capacity and in some cases the desire of governments to develop specific standards for their countries.

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7 8

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See UNDP (2003). Government of Indonesia launched the National Single Window (NSW) for Investment on January 2010. This facility enables investors to apply for license and non-license services online.

References Abimanyu, A. (2000). Impact of Agriculture Trade and Subsidy Policy on the Macro Economy, Distribution, and Environment in Indonesia: A Strategy for Future Industrial Development. The Developing Economies, 38, 547–571. Acquah, P. C. (1995). Natural Resources Management and Sustainable Development: The Case of the Gold Sector in Ghana. UNCTAD New York and Geneva. Anbumozhi, Kimura, & Isono. (2011). Leveraging Environment and Climate Change Initiatives for Corporate Excellence, ADBI Working Paper Series 335, Tokyo. Blackman, A. & Wu, X. (1998). Foreign Direct Investment in China’s Power Sector: Trends, benefits, and barriers. Discussion Paper. Resource for the Future, Washington, DC, 19–22. Boocock, N.C. (2002). OECD Global Forum on International Investment. Conference on Foreign Direct Investment and the Environment in the Mining Sector in sub-Saharan Africa. Lessons to be Learned from the Mining Sector, 7–8 February 2002. Cave, A. L. & Blomquist, C. G. (2008). Environmental Policy in the European Union: Fostering the Development of Pollution Havens? Ecological Economics, 65, 253–261. Cole, M. A. (2004). Trade, the Pollution Haven Hypothesis and the Environmental Kuznets Curve: Examining the Linkages. Ecological Economics, 48, 71–81. Dickey, D.A. & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association, 74, 427–431. Dinda, S. (2004). Environmental Kuznets Curve Hypothesis: A Survey. Ecological Economics, 49, 431–455. Eskelend, G. S. & Harrison, A. E. (2003). Moving to Greener Pastures? Multinaltionals and the pollution Haven Hypothesis. Journal of Development Economics, 70, 1–23. Government Action Plan. (RKP 2013). National Development Planning Agency (BAPPENAS). Indonesia. Retrieved on October 2, 2013 from: http://www.bappenas.go.id Granger, C. W. J. & Newbold, P. (1974). Spurious Regression in Econometrics. Journal of Econometrics, 2(2), 111–120. Gray, R. K. (2002). Foreign Direct Investment and Environmental Impacts—Is the Debate Over?. RECIEL, 11, 306–313. Grossman, G. M. & Krueger, A. B. (1994). Economic Growth and the Environment. NBER Working Paper Series, 4634. Harbaugh, T. W., Levinson, A., & Milson, M. D. (2002). Reexamining the Empirical Evidence for an Environmental Kuznets Curve. The Review of Economics and Statistics, 84, 541–551. Hoffman, R., Chew-ging. L., Ramasamy, B., & Yeung, M. (2005). FDI and Pollution: A Granger Causality Test Using Panel Data, Journal of International Development, 17, 311–317. Indonesia Climate Change Sectoral Roadmap (ICCSR). (2009). Synthesis report, Government of Indonesia. Indonesian Financial Statistics (2013). SEKI, Central Bank, Jakarta. Iwata, H., Okada, K. & Samreth, S. (2012). Empirical Study on the Determinants of CO2 Emissions: Evidence from OECD Countries. Applied Economics, 44, 3513–3519.

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Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamic and Control, 12, 231–254. Johansen, S. & Juselius, K. (1990). Maximum Likelihood Estimation and Inference on Cointegration with Application for the Demand for Money. Oxford Bulletin of Economics and Statistics, 52, 169–210. Johnson, J. & Dinardo, J. (1997). Econometric Methods. McGraw-Hill International Editions. Kalamova, M. & Johnstone, N. (2011). Environmental Policy Stringency and Foreign Direct Investment. OECD Environment Working Papers, No. 33, OECD Publishing. Kearsley, A. & Riddel, M. (2010). A Further Inquiry into the Pollution Haven Hypothesis and the Environmental Kuznets Curve. Ecological Economics, 69, 905–919. Khanna, N. & Plassmannm, F. (2004). The Demand for Environmental Quality and the Environmental Kuznets Curve Hypothesis. Ecological Economics, 51, 225–236. Korea Energy Management Corporation (2010). Energy Policy for Green Growth in the Republic of Korea. Levinson, A. & Taylor, S. (2008). Unmasking the Pollution Haven Effect. International Economic Review, 49(1), 223–254. Merican, Y., Yusop, Z., Noor, M. Z., & Hook, S. L. (2007). Foreign Direct Investment and the Pollution in Five ASEAN Nations. International Journal of Economics and Management. 1, 245–261. Nazari, M. M. (1999). Financial Provisions for Mine Closure. Mining Environmental Magazine, May 1999. OECD (2011). Improving Indonesia’s Investment Climate, Investment Insight, OECD. Pyndick, R. S. & Rubinfeld, D. L. (1998). Economteric Model and Econometric Forecasts. Fourth edition. Singapore: Irwin McGraw Hill. Resosudarmo, B. P. & Irhami, M. (2008). Indonesia’s Industrial Policy Reform and Their Environmental Impacts. Journal of the Asia Pacific Economy, 13, 426–450. Shofwan, S. & Fong, M. (2011). Foreign Direct Investment and Pollution Haven Hypothesis in Indonesia. Journal of Business Systems, Governance and Ethics, 6, 27–35. Talukdar, D. & Meisner, C. M. (2001). Does the Private Sector Help or Hurt the Environment? Evidence from Carbon Diocside Pollution in Developing Countries. World Development, 29, 827–840. UNDP (2003). Business and Millennium Development Goal. New York: United Nations Development Program. World Development Indicator (WDI) (2011). World Bank. Washington DC. Xing, Y. & Kolstad, C. D. (2002). Do Lax Environmental Regulation Attract Foreign Investment? Environmental and Resource Economics, 21, 1–22.

FDIs and environmental management 245 GNI

ENV 1,800 1,600 1,400 1,200 1,000 800 600 400

1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4

1985 1990 1995 2000 2005 2010

1985 1990 1995 2000 2005 2010 TRADE

FDI

.12

.030

.10

.025

.08

.020

.06

.015

.04

.010

.02

.005

.00

.000 1985 1990 1995 2000 2005 2010

1985 1990 1995 2000 2005 2010

APPENDIX 7.1 Figures All Four Variables from 1981 to 2011 Source: International Energy Statistics, and World Development Indicator, World Bank.

8 GLOBAL INTERNATIONAL MIGRATION AND SOUTH-SOUTH MIGRATION The case of Thailand and its adjacent countries Akihiro Asakawa

8.1 Introduction In recent years, there has been an increase in the volume of South-South migration (migration between countries considered relatively less economically developed) due to the improving economies of some South countries. These countries offer more and better employment opportunities and these opportunities attract migrant workers from nearby less developed countries. When their economies were less developed, these accepting South countries were mostly migrant-sending countries. The transition from being a sending country to an accepting country is becoming one of the most important policy challenges these countries face as they strive to cope with the new situation of management and integration of a foreign population. Therefore, as economies develop in many South countries, it is important to consider South-South migration as well as traditional South-North migration. This chapter analyses this issue of South-South migration using the case study of the migration of workers to Thailand from its adjacent countries.

8.2 International migration and role of nation states As globalization has eased the movement of people, international migration has increased in importance not only economically but also socially and culturally in the contemporary world. Related to the improved mobility of individuals is the decreasing individual cost of international migration. This has resulted in circumstances wherein increasing numbers of people who want to emigrate can afford the cost of doing so. The generally high cost of movement tends to discourage people who are financially distressed but improvements in the means of transportation, especially in the late twentieth century, have significantly reduced transportation and time costs. This affordability has increased the number of

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potential migrants who can afford to travel across their national borders. The OECD reported that the percentage of foreign-born populations in the OECD countries increased from 10.26 per cent to 12.60 per cent in the 10 years between 2001 and 2011 (Organisation for Economic Co-operation and Development 2013, p. 37). However, this increase in the number of potential people who can move does not necessarily mean an increase in the actual number of people who move across national borders. There are other factors that influence the likelihood of migration. For one thing, the international movement of people is administrated by each nation state and free movement across all national borders is not the present reality. Therefore, although the number of people who can move across borders is increasing, border controls and immigration policies may prevent such movement. In response to the increased desire to move, nation states have increased their management of international migration. For example, the Japanese Immigration Bureau staff increased 213 per cent between 1990 and 2012 (Immigration Bureau of Japan, 2012, p. 144). This increase likely is in response to the increased volume in and importance of international migration to Japan during this period. Another important change in international immigration policy was the enactment of free movement within the European Union under the Schengen Agreement of 1985. The member states within the Agreement were required to allow virtually free movement within the Schengen Area although they retained control of the movement of people into their countries from outside of the Schengen Area. In addition, the massive influx of people from North Africa to Italy from 2011 resulted in the growing doubt of the effectiveness of this agreement in some countries. Thus, the changing nature of international migration has encouraged nations in our age of globalization to be more involved in the influx of people into their countries. The general policy challenge they face is how to use their national powers to achieve positive outcomes for the migrants as well as themselves. There are two aspects to the role played by the nation state regarding international migration: selection and integration. Selection refers to immigration control of who should be admitted. Selection has two functions. The first function is to determine the selection criteria and legislate those requirements into law and regulation. The second function is the implementation of the rules, mainly immigration control at the border, preventing entry as well as the detection and deportation of people who should not be allowed to stay. The first function sets the standards while the second function is law enforcement of the standards such as raids at work places where there are illegal foreign workers. The state’s law-making function to determine the selection criteria of immigration is very important to the overall immigration policies of the state and is present in virtually all countries in the world. The second aspect of the role of the state regarding international immigration is the integration of migrants into the state’s society. Integration policies generally are not as established as selection policies because many countries do not have large foreign-born populations. In addition, integration involves wide-ranging

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complex policies such as naturalization, education in the host country’s language, employment assistance, and so forth. Countries with small migrant populations have no need for these policies. Moreover, integration policies and programmes are often not necessary simply because of increases in the numbers of long-term migrant residents, and it is unusual that integration programmes are automatically implemented as the numbers increase. It also is likely that a need to integrate migrants is not easily recognized in a country where international migration was previously of little consequence. In sum, as international migration has increased over the last few decades, the role played by nations in the management of the movement of these people has consequently increased. Many countries have felt the need to cope with the changes. On one hand, policies need to address the actual movement of people across national borders by setting criteria regarding who may be admitted. On the other hand, the policy challenge is to find ways to cope with growing resident migrant populations, especially when these populations are relatively large and long-term. Both of these types of policy challenges must be handled and included in migration laws, although the standards, mechanisms, resulting programmes and enforcement will substantially differ from country to country due to the many differences and unique circumstances faced by different nations.

8.3 International migration and development While the increase in international migration is a major challenge to nations, especially those with underdeveloped immigration policies, there also are increased opportunities for the governments of developing countries to formulate policies that help them to economically develop and reduce poverty. As mentioned above, because the flow of people across borders has increased, governments have the opportunity to link policies on international migration to their policies that promote development. One mechanism that promotes this linkage is the Global Forum on International Migration and Development, which has met yearly since 2007. The goal of the Forum is to foster partnerships and cooperation, structure international priorities and agendas, identify policy gaps, exchange good practices and provide a venue for researchers and policy-makers. As a recent initiative of the United Nations Member States, the Forum demonstrates the growing awareness in the international community that migration can play a positive role in a nation’s development when polices are properly managed. One straightforward example of migration’s positive effect on economic development is that the remittances that migrant workers send to their families in their home countries benefit the family and the home country’s economy. Moreover, when an unemployed worker finds work across a border, the unemployment rate in the worker’s origin country is reduced. However, the workers who leave home tend to be a select group of workers who have skills that are in demand elsewhere. The home country’s loss of talent and skill (‘brain drain’) means that the workers remaining in the home country are relatively less talented and skilled. The countries

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that encourage the entry of migrant workers are interested in skilled workers to fill their occupational gaps, and these specialized workers are readily admitted. However, while this is an opportunity for individual migrants, it is a loss of its skilled professionals, often educated in developed countries, for the sending country. It can cause undesirable outcomes for economic development by undermining the extent of local talents and skills. Another problem is that migrant workers are easily subject to human trafficking and other types of exploitation in their destination countries because their low socio-economic status, lack of language skills, and insecure legal status make them vulnerable to predators. Thus, there are positive and negative consequences of increased international migration and the policy challenge is in finding ways to maximize the positive outcomes while minimizing the negative effects. An important challenge for many countries’ international migration policies is the difficulty in moderating the interests of both the sending and the receiving countries. The two parties’ interests seem to be at odds: the sending countries’ goal is to maximize the benefits of international migration to their economies by encouraging their citizens to take advantage of extra-national employment opportunities, while the receiving countries’ goal is to control the inflow and select migrant workers that enhance their economies and do not disadvantage their own work force. Usually, receiving countries have the advantage in international migration because they set the selection criteria to suit their own national interests and sending countries cannot force them to accept migrants simply because they want to be accepted. Governments also generally do not have much control over who leaves or enters their countries because migration is driven by personal motivation. Governments generally do not force people from their countries, although groups sometimes flee due to persecution or civil unrest. Governments also are limited in their ability to prevent skilled workers from leaving. As long as receiving countries continue to accept workers, preventing brain drain will be a challenge. Indeed, according to the Universal Declaration of Human Rights (UDHR), individuals must be given the right to leave any country (Article 13). Thus, the interests of sending countries and receiving countries are secondary to the interests of the migrants themselves, because it is each migrant’s decision when and where to migrate and it is each receiving countries’ decision as to the characteristics of migrants they are willing to accept. It is important to understand that there are conflicting interests among receiving countries, sending countries and individual migrants that cannot be resolved even though government policies may play a significant role in international migration.

8.4 Evolution of South-South migration Scholars have long studied and theorized about the nature and causes of international migration. However, the focus has been on the movement of people from the developing countries to the developed countries, termed ‘South-North’

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migration. Migration tends to occur between countries where there is a difference in employment opportunities, wages and/or currency rates that encourages unemployed or underemployed people to relocate to where conditions are a perceived improvement for them and their families. For most of the twentieth century, the migration flow was from less to more developed countries and has been geographically happening from the South to the North. More recently, two factors seem to be encouraging the flow of migrants from less developed countries to newly ‘emerging’ countries. These ‘emerging’ countries have some characteristics of a developed market economy but they are not fully developed markets and they are located in the South, hence the term ‘South-South’ migration. The first factor that is encouraging South-South migration is the recent downturn in the economies of the historical migrant-receiving North countries. Major economies, such as the US, countries in Europe, and Japan, are experiencing persistent economic recessions and unemployment rates are rising or are steadily high. In particular, recent concerns regarding economies in the Eurozone, the US deficit problem and the 2011 Japanese earthquake have negatively influenced employment opportunities for unskilled labour and this has, in turn, lessened the demand for migrant workers. For example, at the time of the Global Financial Crisis of 2007–2008, many Brazilian migrant workers in the automobile-manufacturing sector in Japan lost their jobs and returned to Brazil when production declined. As a result, the population of Brazilians in Japan decreased almost 45 per cent, from around 317,000 to 175,000 between 2007 and 2014 (Immigration Bureau of Japan, various years). Another example of the effects of changes to a national economy is that in Japan the number of illegal residents has significantly decreased over the past 20 years. In 1993, the number of over stayers in Japan was about 298,000; by 2012, the number was down to about 67,000 (Immigration Bureau of Japan, 2012, p. 40). This decrease likely relates to strong deportation enforcement activities by the Japanese immigration authority. However, it also may be evidence of shrinking employment opportunities for unskilled migrant workers in Japan resulting from the outsourcing of unskilled manufacturing jobs to developing countries where wages are much lower. The case of outsourced Japanese unskilled labour also is an example of the trend among developed countries’ manufacturing corporations to obtain their labour force in ways other than migrant workers. The first factor that encourages South-South migration is a weakening of the historical attraction of developed countries’ economies. The second factor that encourages South-South immigration is the increasing need of unskilled labour in emerging economies. Many of these emerging economies are also experiencing a ‘population transition’ in which the working age population is proportionally increasing and the fertility rate is decreasing. This creates room for economic growth and the need for a bigger labour force. When the need for unskilled labour is not filled by local workers, there is a greater likelihood that the need will be filled by migrant workers. This will be accelerated by the difference in terms of employment opportunities and exchange rate between sending and receiving

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countries. This would be the very basic structure of international migration of ‘push–pull’. As long as there are so many poor people in the world, there is always a push factor for migration, but, as the result of the recent economic development in some South countries, this consequently produced pull factors and enlarged the chance for the poor people in developing countries to migrate. Because of this global trend in the economic development in emerging countries, South-South migration is increasingly important to both the origin and destination countries’ economies and it is worthwhile to point out a main difference between South-North migration and South-South migration. Travel cost is less expensive for South-South migration than South-North migration. According Ratha and Shaw (2007), in 2005, about 47 per cent (73.9 million) of all international migrants from developing countries were in other developing countries while 40 per cent (61.8 million) of them were in OECD countries. They also estimated that South-South migration was overwhelmingly intraregional. Ratha and Shaw’s (2007) research suggests a correlation between the cost of travel to the destination and the destination chosen for migration. Generally speaking, developed countries in the North are geographically further from the sending countries than South destinations that offer economic opportunities. All else being equal, many potential migrants in the South would be more likely to choose the South because of the cost of travel. For the very poor migrant, the North is not even an option even though there are employment opportunities and relative benefits to be gained by the exchange rate. Therefore, according to Bakewell (2009), ‘it is possible that South-South migration may have a much greater overall impact on poor communities than South-North migration’ (p. 53). Interestingly, according to the UN Department of Economic and Social Affairs’ estimates, South-to-South remittances make up 26 per cent of global remittances in 2010. Since North-to-South remittances make up 43 per cent, we can see that South-to-South remittances are increasing in importance (IOM 2013, p. 72). Another difference between South-North and South-South migration is the difference in border and other immigration controls. Receiving developing countries tend to have looser border controls than receiving developed countries. This makes it easier for potential migrants to enter without being detected. To some extent, this is because receiving developing countries tend to lack the technological resources to implement strict border controls. As a case in point, since 2007, the Japanese government has used biometric recognition technologies to require all entering foreigners to submit to facial photography and fingerprint information tests at passport control. This was mainly intended as a counterterrorism measure, but it also prevents people from re-entering Japan simply by changing a name or date of birth after being deported. This kind of strict measure makes it costly for those who wish to stay and work in Japan by illegal means. In sum, recent global economic changes in the rising economies in the South have created emerging markets that, in turn, are creating new opportunities for poor people to migrate and benefit from that migration. The benefits of international migration for reducing poverty through remittances and increased

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employment opportunities, whether to the North or to the South, have received ample research and policy attention. The policy challenges now are in finding ways to maximize the positive consequences while minimizing the negative consequences. The South countries that accept migrant workers have relatively less experience dealing with the challenges of migration; therefore, it is important to consider immigration policies targeted to the particular characteristics of South-South migration.

8.5 The case of Thailand as an example of South-South migration Every South-South migration phenomenon is unique in its own way. However, there are two basic types. The first type is similar to South-North migration where a South country is the migrant’s chosen destination for employment opportunity. Examples include migration between Paraguay and Argentina (Parrado and Cerrutti, 2003) and between Nicaragua and Costa Rica (Gindling, 2009). As in the case of Thailand, the migration occurs between neighbouring countries and the driving force of migration is the migrant’s hope to obtain relatively better employment in the destination country. The second type of South-South migration is ‘transitory migration’. In transitory migration, people from South countries migrate to particular South countries that function as gateway locations to the migrant’s chosen North country. Collyer (2006) described the case of Morocco, where migrants from African countries go for an opportunity to migrate to Europe. Another example is Poland, where migrants from Africa, Asia, and the Former Soviet Union use Poland as a transitory location on their way to Germany (Okolski, 2000). These examples of transitory migration are an important phenomenon in international migration. As an aspect of South-South migration, these destinations are short term; as an aspect of South-North migration, they occur when the desired destination North country does not have an adjacent border with the South country of origin. It is under those conditions that transitory countries (e.g. Morocco) become temporarily involved. As the latter type could be defined as a part of South-North migration, it would be important to emphasize the former type as South-South migration. As discussed above, one important difference between South-North migration and South-South migration is the cost of travel. One reason transitory countries are at all involved in the South-North migration is that travel to the destination country in the North is long and costly. The transitory country can serve as a cheaper, closer midway point that can be afforded and then used as a way to make more money to fund the second half of the trip to the destination North country. These countries serve no other purpose to the migrant. The migrant has no real interest in integrating. However, since the travel cost of migration between neighbouring South-South countries is much lower, these countries are now more frequently the chosen destination. Thus, there is a good reason to

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focus on South-South migration when the South country is the chosen destination, and, therefore, it is distinct from South countries that are used only as transitory stopping points on the way to a chosen destination in the North. We believe that these South country destinations are important to study as a distinct immigration phenomenon. Thailand is an example of a destination country in the present South-South migration phenomenon because it accepts migrant workers from its adjacent countries of Myanmar, Laos, and Cambodia. Thailand has been experiencing economic growth in recent years in part because of a population transition that increased the ratio of the working age population. Another reason for Thailand’s economic growth is the relationships between many of its companies with manufacturing companies from North countries. In these relationships, Thai companies contract as third-party firms, accept outsourced manufacturing jobs, and provide a cheap and reliable workforce. Moreover, Thailand shares long, unsecured land borders with these three neighbouring countries, making it easy for migrant workers to cross the border. Table 8.1 shows some of the key social and economic indicators of Thailand and its adjacent countries. First, compared to Thailand, the adjacent countries have larger young populations that increase their age dependency ratios higher than that of Thailand. Also, the adjacent countries are experiencing more population growth than Thailand. This clear indication of demographic contrast constitutes push and pull factors between Thailand and these countries. Second, it also may be that Thailand is experiencing a lack of a labour force because the labour force participation rate is high and the unemployment rate is low. Third, there is a clear difference in wages and living standards between Thailand TABLE 8.1 Key economic indicators of Thailand, Cambodia, Lao PDR, and Myanmar

(2012) Thailand Cambodia Midyear Population (millions) Age Dependency Ratio (percentage) Population Aged 0 –14 Years (percentage of total population) Growth Rates in Population (percentage) GDP Per Capita at PPP (current international dollars) Unemployment Rate (percentage) Labour force participation rate (percentage) Proportion of Population below $2 (PPP) a Day (percentage) Human Development Index

Lao PDR

Myanmar

64.4 38.7 18.5

14.8 57.2 31.1

6.5 65.4 35.8

61.0 43.9 25.3

0.4 10,757

1.7 2,505

2.0 2,925

1.0 1,801

N/A 87.5 (2011) 43.3 (2011) 0.543

N/A 77.9

4.0 66.3

66 (2008) 0.543

N/A

0.7 72.3 4.1 (2010) 0.690

0.498

Source: Asian Development Bank, Key Indicators for Asia and the Pacific 2013 (http://www.adb.org/ publications/key-indicators-asia-and-pacific-2013, accessed 21 March 2015).

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and its adjacent countries. GDP per capita in Thailand is almost four times higher than in Cambodia or Laos. At the same time, poverty is relatively higher in the adjacent countries as seen by the comparatively higher Proportion of Population below US$ 2 a Day in Cambodia and in Laos. This difference is also reflected in the differences in the Human Development Index between Thailand and its adjacent countries. These differences in demographic, economic, and social indicators are the driving forces of migration from the three countries to Thailand. The main topics covered in the following discussion using Thailand’s case as an example of South-South migration are: 1. 2. 3.

How immigration selection policies influence migration behaviours. How integration policies influence the overall migration phenomenon. How the effects of selection and integration policies benefit sending countries, receiving countries, and individual migrants.

8.6 Selection phase: weak border control In 1992, the Thai government initiated the registration of migrant workers to cope with the influx of foreign workers. Thailand’s laws generally prohibit the entry and employment of unskilled foreign workers. However, Article 17 of the Immigration Act of 1979 allowed the Thai Cabinet to permit foreign workers to enter and work in Thailand as an exception to the general ban (Martin, 2007). Over the years, the Thai government’s policy on registration has changed regarding the types of occupation that must be registered, the amount of the registration fee, and the provinces that are eligible for migrant registration. In addition, the registration fees are imposed on the individual migrants although, normally, employers pay the fees on behalf of the migrants under their employ and then deduct the fees from the migrants’ salaries. Registered migrant workers go through the national verification (NV) process to obtain the necessary travel documents to legally stay in Thailand and work under the protection of Thai laws and regulations. After going through the NV process and obtaining the relevant travel documents, workers must apply for work permits at the Ministry of Labour. As of July 2013, there were 911,526 migrant workers who had completed the NV process. There were 102,420 from Cambodia, 37,932 are from Laos, and 771,174 from Myanmar (Office of Foreign Workers Administration, 2013). The year 2013 experienced an increase of registered migrant workers over previous years in the late 1990s and early 2000s when the total was about 850,000 (Martin 2007). The burdensome nature of the registration procedure suggests that there is poor border control between Thailand and its adjacent countries. For one thing, the fact that legalization of migrant workers occurs in one way or another after their entry into Thailand suggests that immigration control at the borders is not effective, an unsurprising situation considering the long land borders that need to be controlled. According to the Immigration Bureau of the Thai Government,

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there are only about 3,400 staff employees and immigration officers and they are located only at the official entry points of the borders. Were migrants to cross the borders away from the entry points, controlling the border would be the responsibility of the border patrol, the military, and the local police. Therefore, in terms of an immigration selection policy, the Thai government cannot enforce selection criteria of migrants when they cross the borders and thus it attempts to do so after the fact when the migrant has already gained entry to the country. The result is poor control of the inflow of migrants whether or not that is the intention of the Thai government. The difficulty of enforcing immigration control at the border points of entry is also reflected in the legalization of immigration process through Memorandum of Understanding (MOU) with sending countries. Recruitments under the MOUs started in 2006. However, only 3,400 Lao and 600 Cambodian workers arrived under the MOU in 2006 (Martin, 2007). While the numbers of workers under MOU increased to 139,048 in July 2013 (Office of Foreign Workers Administration, 2013), this number is significantly smaller than the number of workers under national verification (NV). The apparent preference for NV may be due to the cost compared to non-MOU entry. According to the calculation of the Cambodia Development Resource Institute, the cost of Cambodian workers to go to Thailand under MOU is US$ 747, which is four or five times more expensive than travelling illegally (Cambodia Development Resource Institute, 2009). The cost, both actual cost and physical barrier, of travel to work in Thailand is quite low, suggesting that low cost is the main reason for influx of migrant workers. Labour migration to Thailand from its adjacent countries appears to be the typical picture of South-South migration because travel costs are less than the costs of travel to other countries in the South or to the developed North countries. According to a survey of Cambodia’s Banteay Meanchey Province of 199 households with a family member working outside the home village, 71 per cent were working in Thailand and 16 per cent were working in another province. Only 1 per cent were working in a country other than Thailand (International Labour Organization, 2005). This finding that just 1 per cent of respondents were working in other foreign countries suggests that the cost of travel to other countries was prohibitively high compared to the cost to go to Thailand. The combination of weak border control and inexpensive cost of travel from the adjacent countries to Thailand increases the number of migrant workers who can afford to and who do cross the borders and work in Thailand. From the perspective of international migration policy, the actual selection of migrants into Thailand is poorly executed because of the geographically long land borders between Thailand and its adjacent countries and also because of its limited resources for border control. The Thai government’s response is the implementation of its registration, NV, and work permit scheme; however, this approach does not strictly control the entry and work of foreigners. Therefore, in Thailand’s case, the selection function of immigration policy is not playing a big role in controlling immigration.

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8.7 Actual work in Thailand and its influence on the home country Considering that the enforcement of the selection of migrants into Thailand is not an effective immigration control, the policy question becomes whether de facto acceptance of migrant workers in Thailand is beneficial for Thailand, for the sending countries, and for the migrant workers. The economic benefits of immigration to Thailand are described by Martin (2007) and Pholphirul and Rukumnuaykit (2009). These studies computed the economic contribution of migrant workers to Thailand using macro modelling. Martin (2007, p. 8) points out ‘if migrants are as productive as the Thais in each sector, their total contribution would be 6.2 per cent of Thai GDP’. Pholphirul and Rukumnuaykit (2009) calculated migrants’ net contribution as, on average, 0.023 per cent of the real national income, or around 760 million baht per year. In addition, Thailand’s high labour force participation and low unemployment rate suggest that there are jobs needing workers, jobs that migrant workers are filling where there are shortages of local Thai workers. These jobs tend to be in agriculture, manufacturing, and domestic services. It is likely that migrant workers from the adjacent countries benefit the Thai economy by increasing the size of the labour force in the sectors not being filled by Thai workers, probably because of low wages. Thus, the supply of migrant workers in Thailand is the overflow of workers from the sending countries who are encouraged to go to Thailand for jobs and by the low cost of travel and weak border control enforcement. Second, a substantial number of research and survey reports have described the working conditions of registered and unregistered migrant workers in Thailand. For example, a survey of returning migrants to one Cambodian neighbouring province states that ‘some 53 percent of the 80 returning labourers who were interviewed reported experiencing various types of abuse and exploitation, including being shouted and cursed at, forced to work long hours, underpaid, not paid, not allowed to leave the workplace, forced to work in dangerous conditions, physical violence, sexual abuse and being arrested’ (International Labour Organization, 2005, p. viii). Another survey report states that ‘20 percent of those interviewed on fishing boats and 9 percent of those interviewed in fish processing stated they were ‘forced to work’ compared [to] only 2 percent in agriculture and 1 percent in manufacturing’. It goes on to point out that ‘employers feel the Thai policy of migrant registration obligates them to restrict migrants’ freedom of movement to protect their financial investment in workers (having paid registration fees upfront) and to prevent workers from changing employers (International Labour Organization, 2006, p. xxi). Other studies, such as Jayagupta’s (2009), have focused on trafficked women to Thailand. These studies importantly direct attention to the human rights protection of migrant workers in Thailand. They directly relate to migrants’ personal welfare and directly influence the extent that working in Thailand contributes to the development of sending countries. However, the fact that nearly one million

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migrants were registered in 2013 shows that working in Thailand fundamentally provides some benefit despite these reported human rights problems. Even though there is personal risk involved for migrants, as long as a labour shortage exists in Thailand, an influx of migrant workers will continue. Therefore, a consideration of the effects that the working experiences of migrant workers in Thailand have on the sending countries, even though there are problems regarding their human rights, is important. Another important factor that influences migrants’ participation in the Thai labour force is their ability to speak the language in the receiving country. Usually, the ability to speak the local language in the receiving country means more employment opportunities for migrant workers and higher wages. Conversely, a lack of language skills in the receiving countries limits employment opportunities except in sectors where language is not important, such as manufacturing or agriculture. An example of the importance of language skills to migrant workers’ labour force participation is the case of Brazilians in Japan. Brazilian migrant workers in Japan were concentrated in the automobile-manufacturing industry because they lacked Japanese language skills. After the Global Financial Crisis and the rapid decline in the automobile-manufacturing industry hit Japan, these migrant workers were forced out of their jobs. Because they lacked Japanese language skills, many of them could not find jobs in other sectors and they returned to Brazil. Brazilians in Japan decreased by almost 45 per cent between 2007 and 2014. Thailand is an example of a country with a language issue in international migration. The Thai language is quite similar to the Lao language and it is easy for Lao people to learn to speak Thai. Thai also is rather similar to Khmer, the language spoken in Cambodia, and it is not difficult for Cambodian people to learn Thai. However, for the Myanmar people, learning Thai is difficult and their lack of language skills affects their participation to the labour force. Table 8.2 shows the nationality and economic sector of registered migrant workers in Thailand in 2012. Migrant workers from Myanmar and Cambodia mainly were concentrated in agriculture and construction. However, migrant workers from Laos are a relatively higher proportion in the services sector compared with the other two nationalities. This is likely because service sector jobs require language skills to communicate with customers and colleagues. Having language skills is a relative advantage to workers from Laos who, therefore, have access to a wider range of job opportunities. In addition to the sorting of migrant workers into occupational sectors, language skills seem to have an impact on salaries. According to the author’s questionnaire survey of 16 migrant workers in Bangkok in August 2011,1 Thai language skills almost directly translate into the amount of a worker’s salary. Table 8.3 is a summary of the survey and it shows three migrant workers with no Thai language skills. Their salaries are low compared with the other workers who work as housemaids. These three workers received 5,000 baht, 3,600 baht, and 6,500 baht per month; many other domestic workers received more than 8,000 baht per month. The conclusion that language deficits are to blame for lower salaries is supported by an in-depth

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TABLE 8.2 Sector of migrant workers registered in 2012, totals

Myanmar Construction 15,374 Agriculture and 10,469 livestock Services 5,242 4,696 Others serivces include financial sector, education, hotels and restaurants, etc. Food and drink 3,177 Wholesale and retail 2,775 trade Agricultural processing 5,236 Textile 3,836 Fishing processing 1,983 Fishing 966 Metal 975 Plastic 1,347 Livestock processing 2,368 Construction materials 1,434 Recycling business 1,155 Transportation by land, 323 marine and warehouse Soil production or 758 products Garage 300 Fuel station 281 Electronic production 430 or products Paper production or 224 products Mining processing 180 Mining/quarrying 155 Education, foundation, 84 association, and medical center TOTAL

Laos

Cambodia

24.1% 16.4%

4,004 8,079

10.1% 20,223 20.3% 11,687

8.2% 7.4%

4,449 5,623

11.2% 14.2%

5.0% 4.4%

4,758 3,181

8.2% 6.0% 3.1% 1.5% 1.5% 2.1% 3.7% 2.2% 1.8% 0.5%

total 31.4% 18.1%

39,601 30,235

5,906 2,440

9.2% 3.8%

15,597 12,759

12.0% 8.0%

3,056 3,496

4.7% 5.4%

10,991 9,452

1,010 2,259 218 397 1,277 1,183 200 799 491 118

2.5% 5.7% 0.5% 1.0% 3.2% 3.0% 0.5% 2.0% 1.2% 0.3%

2,541 875 2,648 3,145 1,310 1,028 844 1,092 1,638 999

3.9% 1.4% 4.1% 4.9% 2.0% 1.6% 1.3% 1.7% 2.5% 1.6%

8,787 6,970 4,849 4,508 3,562 3,558 3,412 3,325 3,284 1,440

1.2%

312

0.8%

197

0.3%

1,267

0.5% 0.4% 0.7%

583 348 140

1.5% 0.9% 0.4%

259 269 307

0.4% 0.4% 0.5%

1,142 898 877

0.4%

173

0.4%

144

0.2%

541

0.3% 0.2% 0.1%

63 17 22

0.2% 0.0% 0.1%

192 57 56

0.3% 0.1% 0.1%

435 229 162

63,768 100.0% 39,704 100.0% 64,409 100.0% 167,881

Source: Office of Foreign Workers Administration, Annual Statistics 2012 http://wp.doe.go.th/wp/images/statistic/sy/sy2555.pdf, accessed 21 March 2015.

interview we had with a Cambodian migrant worker. This 26-year-old male worker was currently working at a small restaurant in Bangkok. He had entered Thailand by crossing the border. After entering, he had worked in Samut Prakarn province as a rice deliverer. This job did not require any Thai language skills but the payment of his salary was very slow, so he quit the job and moved to Bangkok.

Cambodia Myanmar Myanmar Laos

13 14 15 16

M F F F

F F F F F F F F F M F F

23 18 20 20

22 25 23 25 47 17 33 41 22 23 24 23

illegal illegal legal legal

illegal illegal legal legal legal illegal legal legal illegal illegal illegal illegal

2500B 3 1 1 1

housemaid housemaid housemaid housemaid housemaid housemaid housemaid housemaid coffee shop outlet worker employee at grocery store employee selling soft drink employee selling coffee and soft drink employee selling noodles housemaid housemaid housemaid

times in job Thailand

2 1 1 3 3 1 3 3 2 2500B 3 3000B 8 2000B 9

8500B 16000B 18000B 1000B 4000B 800B

sex age form of cost of entry entry

Source: Author’s survey.

Myanmar Myanmar Myanmar Laos Cambodia Myanmar Laos Laos Cambodia Cambodia Cambodia Cambodia

1 2 3 4 5 6 7 8 9 10 11 12

nationality

350B/day 6500B/month 8000B/month 5000B/month

8700B/month 5000B/month 8000B/month 6500B/month 5500B/month 3600B/month 8000B/month 8000B/month 250B/day 290B/day 300B/day 350B/day

salary

TABLE 8.3 Summary of questionnaire survey of migrant workers in Bangkok, August 2011

6000B/month 5000B/month 3000B/month 5000B/month

yes yes no yes yes yes 8000B/month 4000B/month 3000B/month 2000B/month 2000B/month 3000B/month

remittance

yes yes no yes yes yes yes yes no no no no

intention to live in Thailand permanently

fluent no not at all no fluent no fluent yes

fluent not at all fluent fluent yes not at all fluent fluent fluent average fluent fluent

Thai language ability

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In Bangkok, he learned to speak Thai in his daily conversations. He then applied for and got the restaurant job. The salary was 300 baht per day. He mentioned that it would be impossible to get this job without language skills. In this case, the acquisition of language skills led to a more secure and better paying job than he had previously been able to obtain. The relationship between salary and language skills directly results in higher remittances sent home. According to the responses to the questionnaire survey, all of the migrant workers except one were remitting money to their home countries (Table 8.3). Among those who specified the amounts they were remitting, the amounts were large proportions of their salaries. Domestic workers in particular remit large proportions because many of them reside with their employers and they do not pay for living expenses. According to the respondents, one of the most important reasons for working in Thailand was to remit money to their families in their home countries and, for most of them, the more they can earn, the more remittances they can send. Because language skills directly translate into the amount of salary, and the size of a remittance depends on the amount of salary, migrant workers’ language skills affect the contributions they make to their families. The amount of remittances also is important to the sending countries because it lowers poverty and helps the economy through consumer activities. Language skills in the receiving country are just as important to the sending and receiving countries in South-South migration as they are in the case of SouthNorth migration.

8.8 Integration phase The integration of migrant populations may become contentious when migrants, including their second generation, are excluded from labour force participation in the receiving country. Exclusion means the loss of stable income and this instability may result in welfare dependency in countries with generous welfare systems for unemployed people (mainly in developed countries) or in criminal activities. The major barriers to labour force participation in receiving countries are language skills, adequate education, and the particular job qualifications that are in need in the host countries. Language skills play a key role in the ability to attain labour force participation. In the case of Thailand, as described above, Thai language skills seem to directly impact both the types of employment obtained and the amount of salary paid. To the extent that migration from the countries adjacent to Thailand is mainly a temporary phenomenon wherein migrants pursue employment opportunities at the low cost of entry and do not desire to remain for any long period, policies regarding the integration of migrants into Thailand are not useful. As described above, integration with respect to language skills matters to even the short-term migrant’s ability to obtain gainful employment and provide for family back home through remittances. However, so long as migrant workers go back to their countries of origin when they think they have satisfied their initial intentions to

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earn money or when they lose their employment opportunities, integration of these migrant populations would be a wasted investment and would not be a desirable policy to pursue. However, many of the relevant agencies (we) consulted raised the issue of educating migrant children in the Thai education system (Ministry of Foreign Affairs, personal interview, August 22, 2011; Office of National Security Council, personal interview, August 23, 2011; National Economic and Social Development Board, personal interview, August 24, 2011). A concern regarding the nationality of migrant workers’ children was also raised. The Thai government issues birth certificates to migrant children. However, their parents’ home governments do not recognize their nationality and they consequently become stateless. In addition, they are allowed to stay in Thailand as dependents of their parents only until they are 15 years old; once they reach age 15, they have no legal right to stay in Thailand under the current arrangement (Ministry of Foreign Affairs, personal interview, August 22, 2011). Therefore, the integration of migrant populations in Thailand and other receiving countries is becoming an important issue, especially regarding the second generation of migrants. The issue of how to handle second-generation migrants is a difficult challenge for immigration policy to address. The second generation of temporary migrant workers is a group not addressed in most policy regarding temporary migrant workers because the policies focus on short-term stays. The policy gives them short-term temporary legal status through repeated registration and the work permit scheme. Therefore, from the policy perspective of the Thai government, these workers are not expected to live in Thailand permanently or have children; a second generation of migrant workers is simply not addressed in policies that focus on short-term residency. Even so, many of the relevant Thai agencies believe that the education of the second generation of migrant workers is an important issue in terms of integrating migrant population and the Thai government began to offer education to non-Thai children after a 2005 cabinet decision. Table 8.4 shows the number of non-Thai children in the Thai school system, evidencing a significant number of non-Thai children in the educational system. According to the Office of Basic Education Commission, Ministry of Education, Thai schools provide a preparation class for non-Thai students because they do not have basic Thai language skills and the language barrier is considered burdensome to some schools. In addition, even though non-Thai children are entitled to an education in Thai schools, the dropout rate is very high. This can be seen in Table 8.4, from the almost 50 per cent decrease in the number of students from ‘Primary 1-3’ to ‘Primary 4-6.’ It is believed that many children intentionally drop out of school once they have learned the basic Thai language skills and become interpreters for their parents who work in Thailand (Office of Basic Education Commission, Ministry of Education, personal interview, August 25, 2011). Table 8.4 also shows the number of students in the ‘Migrant Learning Center.’ These centres are run by NGOs and we were told that they have problems regarding the quality of education in terms of

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TABLE 8.4 Number of non-Thai students in 2010

Level of Education

Number of students

kindergarten Primary 1–3 Primary 4 – 6 Secondary 1–3 Secondary 4 – 6 Total Migrant Learning Center

13,038 24,479 13,878 7,055 1,707 60,157 15,735

Source: Ministry of Education, Office of Basic Education Commission, Thailand obtained by author.

curricula, attendance, and teaching quality (Office of Basic Education Commission, Ministry of Education, personal interview, August 25, 2011). The data in Table 8.4 suggest there is low educational achievement and attainment among second generation migrants. Low levels of achievement or attainment likely will be a barrier to future participation in the labour force for these children of migrants and it is possible that they will face exclusion from social and economic participation in Thai society. Since these children are either born in Thailand or spend most of their lives in Thailand, deportation to their home countries will be difficult. It may be possible to compel them to leave but forced removal likely will cause difficult problems of re-integration in their home country. Furthermore, in many cases, their parents’ home countries do not recognize their nationalities. This legally and socially puts them in a state of limbo. In the future, especially were Thailand to experience an economic downturn, the problems related to migrant children could become major social and economic issues in Thai society. The North countries that accept temporary migrant workers have already faced a similar problem of de facto permanent residence of temporary migrant workers and a failure to integrate successive generations into the host country. A wellknown South-North example of the various social problems related to the failure of integration is that of Turkish migrants to and their successive generations in Germany. Thailand and its migrant population is an example that similar integration issues are starting to be experienced in South-South migration.

8.9 Conclusion: towards better management of the South-South migration This chapter explains the new and emerging phenomenon of South-South migration using the example of the influx of migrant workers to Thailand from its adjacent countries. One of the biggest differences between South-North migration and South-South migration is the travel cost to the migrant both in terms of the money needed to pay for travel and of border control enforcement by the receiving countries. The relatively lower monetary cost of South-South migration

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presents more opportunity for moving, especially for migrants of very limited means who do not have enough money to go to a North country for employment. Also, the newly emerging countries where jobs are available tend to not have adequate resources for border control and this makes it easier for migrants to travel to those receiving South countries. The combination of proximity, weak border controls, and plentiful job opportunities in emerging countries make them attractive to people who are seeking employment opportunities for migrant workers in receiving countries. In ways similar to the migrant experience in South-North migration, South-South opportunities are translated into employment and the benefit of remittances home to the sending countries. The example of Thailand demonstrates this benefit to sending countries. Similar to the negative consequences of South-North migration, there are problems related to South-South migration that tend to occur regardless of destination. One such problem is the type of labour force participation that is available to migrant workers. There are many barriers faced by migrant workers and one of the most important barriers is the lack of local language skills in the host country. In Thailand, the extent of a migrant worker’s Thai language skills directly affects labour force participation in terms of available sectors and amount of salary. Furthermore, the better skilled migrant workers are able to support their families and sending countries through relatively higher remittances. In the case of migrant workers from Laos and Cambodia in Thailand, a natural similarity between their native languages and Thai is playing a positive role in employment and remittances. South-South migration is also challenged by problems related to the integration of the migrant population. Even in the case of temporary migrant workers, the children born in Thailand or small children who migrate with their parents are becoming an important issue in Thailand. Although educational opportunities are provided for them, the educational outcomes of these children are relatively unfavourable both in terms of school completion and the quality of education. This presents a future challenge for their integration into Thai society. The failure of social integration or the inability to maintain labour force participation in Thailand might lead to exclusion from mainstream society. Exclusion might result in social problems such as criminal activities. In sum, even though South-South migration is a new global phenomenon, the issues that are arising from the phenomenon are similar to those experienced in traditional South-North migration regarding both labour force participation and social integration. Therefore, we can conclude that economic growth is the driving force that attracts the influx of migrant workers, whether the country is a traditional migrant-receiving country (North country) or a newly emerging receiving country (South country). Indeed, many South countries are now accepting migrant workers from other South countries that previously were sending countries to the North. While there are similarities, there also are differences and, because of this background, policy development in terms of migrant receiving is not being properly implemented in South countries, especially regarding border control and the integration of migrant populations.

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In the present global economic climate, it is expected that some South countries will experience more economic growth but they will not be prepared for a migrant work force. It is important that these countries consider the future and prepare for the expected influx of migrant workers from less developing countries. The preparation should include evaluation of and mechanisms for border management to prevent uncontrolled entry of migrant workers. In other words, proper legal channels of acceptance should be opened for migrant workers to avoid exploitation based on illegal status and other problems resulting from uncontrolled migration. It also is important to prepare for the integration of a second generation of migrants by creating educational mechanisms. Education can be a socioeconomic equalizer and it can help to avoid the emergence of migrants as an excluded social group, which would be a burden for receiving countries. As former migrant sending countries, such as Japan, South Korea and Taiwan all now are experiencing an influx of foreign population in one way or another, it is very important for future potential migrant receiving countries to build their capacities for an incoming migrant population. Every country’s immigration experience is unique. However, the nature of the policy challenges related to immigration is, as we discussed above, similar across countries in many ways. Good, sound management of regulations and rules is required to maximize the benefit of migration for receiving countries, sending countries, and the migrants whose present experiences involve both the countries they are from and the countries in which they work. Most North countries have experience in developing effective immigration policies in border management and integration and their support of the efforts of economically emerging countries to create their own migration policies is vital. While the emergence of SouthSouth migration presents a unique challenge for development, it also presents new opportunities for South-North cooperation in terms of creating new and better migration policies and improving the management of human movement at a time when nations play an important role in human movement because the cost of immigration is historically low.

Note 1

This survey was conducted with the strong cooperation of Professor Phaisal Lekuthai of Chulalongkorn University.

References Bakewell, O. (2009). South-South Migration and Human Development: Reflections on African Experiences. Oxford: International Migration Institute, Oxford Department of International Development. Retrieved on March 21, 2105 from http://www.imi.ox.ac.uk/ pdfs/wp/wp-15-oliver-bakewell-south-south-migration/at_download/file Cambodia Development Resource Institute (2009). Costs and Benefits of Cross-Country Labour Migration in the GMS: Synthesis of the Case Studies in Cambodia, Laos, Thailand and Vietnam. Phonm Penh: CDRI.

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Collyer, M. (2006). Undocumented sub-Saharan African Migrants in Morocco. In N. N. Sorensen (Ed.), Mediterranean Transit Migration (pp. 129–145). Copenhagen: Danish Institute for International Studies. Gindling, T. H. (2009). South-South Migration: The Impact of Nicaraguan Immigrants on Earnings, Inequality and Poverty in Costa Rica. World Development, 37(1), 116–126. Immigration Bureau of Japan (2012). 2012 Immigration Control. Retrieved on March 21, 2015 from http://www.moj.go.jp/nyuukokukanri/kouhou/nyuukokukanri06_00025.html —— (various years), Statistics on the Foreigners in Japan. Retrieved on March 21, 2015 from http://www.moj.go.jp/housei/toukei/toukei_ichiran_touroku.html International Labour Organization (2005). The Mekong Challenge Destination Thailand: A Cross-Border Labour Migration Survey in Banteay Meanchey Province, Cambodia. Bangkok: International Labour Office. —— (2006). The Mekong Challenge Underpaid, Overworked and Overlooked: The Realities of Young Migrant Workers in Thailand. Bangkok: International Labour Office. International Organization for Migration (2013). World Migration Report 2013. Geneva: IOM. Jayagupta, R. (2009). The Thai Government’s Repatriation and Reintegration Programs: Responding to Trafficked Female Commercial Sex Workers from the Great Mekong Subregion. International Migration, 47(2), 228–253. Martin, P. (2007). The Economic Contribution of Migrant Workers to Thailand: Towards Policy Development. Bangkok: International Labour Office. Ministry of Foreign Affairs, Thailand (2011, August 22). Personal interview. National Economic and Social Development Board, Thailand (2011, August 24). Personal interview Office of Basic Education Commission, Ministry of Education (2011, August 25). Personal interview. Office of Foreign Workers Administration, Thailand (2013, October). Monthly Statistics. Retrieved on March 21, 2015 from http://wp.doe.go.th/wp/images/statistic/sm/56/ sm1056.pdf Office of National Security Council, Thailand (2011, August 23). Personal interview. Okolski, M. (2000). Illegality of International Population Movements in Poland. International Migration, Special Issue 2000/1, 57–87. Organisation for Economic Co-operation and Development (2013). International Migration Outlook 2013. Paris: OECD Publishing. Parrado, E. A. & Cerrutti, M. (2003). Labor Migration between Developing Countries: The Case of Paraguay and Argentina. International Migration Review, 37(1), 101–132. Pholphirul, P. & Rukumnuaykit, P. (2009). Economic Contribution of Migrant Workers to Thailand. International Migration, 48(5), 174–202. Ratha, D. & Shaw, W. (2007). South-South Migration and Remittances. Washington, D.C.: The World Bank.

9 AID IS GOOD FOR THE POOR Development aid in a globalized world1 Yumeka Hirano and Shigeru Thomas Otsubo

9.1 Introduction Enhancing the effectiveness of aid has long been the international development community’s core agenda, given the limited resources available for the fight against poverty. With the establishment of the Millennium Development Goals (MDGs) in 2000 and the implementation of the Paris Declaration (PD) on Aid Effectiveness in 2005, the international community has continued to improve the impact of aid on development. However, poverty still persists despite drastic changes in the development landscape. While progress has been made toward the MDGs, as well as great strides in poverty reduction over the past few decades, globalization has introduced economic structural changes, and huge income inequality and development disparities persist across and within regions and countries (UN, 2013). As such, while the eradication of poverty remains a challenge in the post-2015 development agenda, inequality has entered the equation. This led the World Bank to establish in 2013 the twin goals of “poverty eradication” and “shared prosperity” (World Bank, 2013a). In the mid-1990s, private capital flows, especially foreign direct investment (FDI) and overseas remittances, surpassed by far the level of Official Development Assistance (ODA), which used to be the main financial flow to developing countries (Figure 9.1). Nevertheless, as highlighted in the Monterrey Consensus for Financing for Development (FfD) adopted in 2002, ODA is still expected to play a key role in assisting developing countries to fully utilize the opportunities presented by globalization. Against this backdrop, the effectiveness of development aid has been debated for decades. While aid is generally considered to have a positive impact on economic growth, which is believed to be a vital force in poverty reduction, crosscountry empirical studies on aid effectiveness for growth have shown ambiguous

Aid is good for the poor

267

(US$ billion) 700 FDI, net inflows 600

Remittances, received

500

Private Debt & Portfolio Equity, net inflows ODA, net received

400 300 200 100 0 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 −100 FIGURE 9.1

Financial flows to developing countries (1978 –2011)

Source: Authors’ compilation based on WDI (World Bank, 2013b).

results. Some studies have confirmed a positive relationship (Gulati, 1978; Hansen & Tarp, 2000; Clemens, Radelet, & Bhavnani, 2004; Minoiu & Reddy, 2010), while others have argued that there is no significant impact of aid on growth (Mosley, Hudson & Horrell, 1987; Boone, 1996; Easterly, Levine, & Roodman, 2003 & 2004). Moreover, some studies have suggested that the positive impact emerges only with certain prerequisite conditions such as good policies (Burnside & Dollar, 2000; Collier & Dollar, 2001, 2002), climate-related geographical environments (Dalgaard, Hansen, & Tarp, 2004), and only in certain forms or categories of aid (Sawada, Kohama, & Kono, 2003; Clemens et al., 2004; Minoiu & Reddy, 2010). Although the current mainstream discourse asserts the importance of good policies for development aid to promote growth effectively, the controversy begs further research. In order to investigate development effectiveness, the impact of globalization, in the forms of trade, FDI, and remittances, for example, should not be neglected. In the literature on globalization and inequality, there has been heated debate about whether the poor benefit from globalization. Numerous past studies confirm that, on average, globalization, or economic integration, contributed to poverty reduction through higher growth. However, some have argued that globalization did not disproportionally benefit the poor (Fischer, 2003; Milanovic, 2005; Ravallion, 2005; Harrison, 2006). That is, globalization did not help the poor more

268 Yumeka Hirano and Shigeru Thomas Otsubo

than other segments of society. One of the most influential papers by Dollar and Kraay, Growth is Good for the Poor (2001, 2002), revealed that the poor benefited from growth, with empirical evidence that the income of the bottom quintile increased equiproportionally to that of the national average. At the same time, they did not find any factors of openness, globalization, policy, or institutions that had systematic effects on the poor other than through growth. In the end, Dollar and Kraay emphasized the importance of growth, as well as policies (including openness policies) and institutions that contribute to growth, for poverty reduction. Their latest paper, Growth Still is Good for the Poor (Dollar, Kleineberg, & Kraay, 2013), reaffirms the importance of growth, while they end up concluding that there is no robust evidence that certain policies, such as openness, education, and health expenditures, are particularly “pro-poor” or conducive to promoting “shared prosperity” other than through their direct effect on overall economic growth (p. 18). The challenge remains to find out if there is any factor that leads to poverty-reducing distributional changes. With their end results and assertions, we came up with a question: “Is aid good for the poor?” With the debate raging on, the current study revisits the discussion of development effectiveness by examining whether aid indeed contributes to promoting growth and reducing poverty. This study undertakes further analysis of the impact of aid, by applying the conceptual framework of globalization and the Poverty– Growth–Inequality (P-G-I) relationship as illustrated in Figure 9.2, with a focus on each leg of the triangular structure: aid and growth, aid and inequality, and growth/inequality and poverty. Globalization Trade · Financial · HR Integration Winner ⇔ Loser Growth Increase in Mean Income Level

Inequality Distribution of Income

Institutions Growth Effects

Poverty Reduction in Absolute Poverty

Distribution Effects

Development Aid Economic · Social · Aggregate Aid

FIGURE 9.2

The conceptual framework and structure of the study

Source: Modified, based on Otsubo (2009, p. 58).

Aid is good for the poor

269

The following questions are addressed in this study, with the corresponding conclusion section in parentheses: 9.1.1 9.1.2 9.1.3 9.1.4

Does aid promote growth? (Section 9.4.1) Do institutions matter for development effectiveness on growth? (Section 9.4.2) Does aid mitigate inequality? (Section 9.4.3) Can policies, institutions, and globalization be good for the poor? (Section 9.4.7)

9.1.1 Does aid promote growth? This question bears repeating, regardless of the past literature addressing it. The current authors suspect that one of the reasons for the ambiguous results in past aid–growth literature comes from the usage of aggregate aid data in their analyses. The insignificant, even negative, results should be regarded as natural because aid is not necessarily, or directly, targeted to produce economic growth. The purposes of aid are diverse depending on the programs or projects. The different effects of aid should be taken into consideration in the specification of the empirical analyses. Unlike most of the previous literature, this study employed sector-level data on economic aid, social aid, as well as aggregate aid, to test the impact of aid. In addition to this more granular view, a re-examination of the aid–growth relationship with the latest data (up to 2010 in this study) is warranted by recent changes in practice. Burnside and Dollar (2004) elucidated these changes, suggesting, “past aid had been allocated indiscriminately with regard to institutions and policies that were critical for growth,” and “now aid is more systematically allocated to countries with sound institutions and policies” (p. 21). Bourguignon and Sundberg (2007) also discussed changes in international aid architecture and aid allocation since the mid-1990s.

9.1.2 Do institutions matter for development effectiveness on growth? Another unique aspect of this research is the focus on institutional quality. We argue that institutional quality, and capacity in particular, are key factors in determining the effectiveness of development aid (Hirano, 2014). Unlike past literature that focused on policy as the control factor, this study pays more attention to institutions (further explained in Section 9.3.3) in the aid–growth empirical analysis. Having a good policy stance (in terms of monetary, fiscal, and trade policies) does not necessarily mean that countries are capable of creating good policy impacts or managing their respective economies effectively.2 Further, policy stances can be changed or improved in a relatively short period of time, with or without

270 Yumeka Hirano and Shigeru Thomas Otsubo

external help. On the other hand, building institutions takes longer than policy changes to bring about effects on economic growth (Williamson, 2000), similar to the impact of aid in the long-run growth theory. However, it is precisely this institutional quality that is a more critical determinant of the effectiveness of aid than policy, as the quality of institutions reflects long-term characteristics of countries that also affect policies and growth (Burnside & Dollar, 2000). Even with good policies, constraints remain, if there is an absence of good institutions. Further, institutions cannot be changed or improved easily until a country becomes self-reliant. In sum, while institutional quality is more challenging to change than policy, it is more consequential when it comes to making aid effective.

9.1.3 Does aid mitigate inequality? Another challenge of this research is to empirically investigate whether aid has mitigated inequality. If the ultimate goal of aid is to reduce or end poverty, aid needs to disproportionally benefit the poor and reduce inequality. If the benefits of aid are not extended to the poor, the gap between the rich and the poor cannot be narrowed. Analyzing the impact of aid on poverty reduction from both growth and distributional perspectives can be considered another original contribution of this study, as there is little past empirical research on aid that has paid attention to the distributional impact of aid for achieving poverty reduction.

9.1.4 Can policies, institutions, and globalization be good for the poor? We look at the effects of aid on the poor in comparison with other factors including policy, institutions, and the facets of globalization. Past literature (Dollar & Kraay, 2001, 2002; Dollar et al., 2013; Milanovic, 2005) seemed to agree that there was no factor of policy, institutions, or globalization that significantly benefitted the poor other than through growth. Our earlier study provides a literature survey and empirical stocktaking of the impacts of (1) globalization (via trade, FDI, and remittances) on growth, (2) inequality on the poor, and (3) inequality on the Gini Index (Chapter 2). Our earlier study also found that no factor of globalization has a significant impact on the poor other than through growth. Taking these assertions into account, we reexamine the impact of policies, institutions, and globalization on the poor with the new dataset, while proposing that development aid could be a key factor with significant impact on the poor.

9.2 Methods and empirical models In order to examine the effectiveness of aid on growth, inequality, and poverty reduction, we conducted a series of cross-country analyses using the two-stage

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271

least squares (TSLS) estimator. We used the unbalanced panel data of worldwide income, aid, poverty, distribution, policy, and institutions.

9.2.1 Leg 1: Aid and growth (growth regressions) We conducted the following regressions, employing the Barro-type ad hoc growth equations (Barro, 1991, 1997) for conditional convergence, with elements of exogenous conditions such as the fertility rate and terms of trade (X ); a set of important factors to consider such as policies, institutions, globalization, and other potential determinants (Z ); and aid (economic aid, social aid, and aggregate aid) (A): (ln yct − ln yc0)/t = α + β1 ln yc0 + γ ln Xct + δ ln Zct + θ ln Act + λt’ + εct’ (9.1) where y is the average per capita income, c and t indicate countries and years, respectively, and λt’ + εct’ is a composite error term. In other words, the dependent variable is the period average growth rate of growth in real per capita income. The natural logarithm of real per capita income of the initial year, ln yc0, is included as an explanatory variable to examine the conditional β-convergence. Furthermore, we examined the impact of institutional quality3 on development effectiveness by dividing the samples into two different groups, by (a) level and (b) change in institutional quality, respectively, in order to show the differences in development effectiveness among different sets of countries: (i) countries whose initial level of institutional quality is higher than the sample mean; (ii) countries whose initial level of institutional quality is lower than the sample mean; (iii) countries whose institutional quality is improving (i.e., the change ratio of institutional quality is positive); and (iv) countries whose institutional quality is not improving (i.e., the change ratio of institutional quality is zero or negative).4

9.2.2 Leg 2: Aid and inequality (inequality regressions) We examined the possible impact of aid on reducing inequality, employing three different equations: (a) level regressions for the average income of the poorest quintile; (b) growth regressions for the average income of the poorest quintile; and (c) growth regressions for the Gini indices. We give most attention to (b), as we consider that looking at the impact of aid to change in the poverty situation of the bottom quintile, rather than levels, is more appropriate and important for assessing development effectiveness. Our interest in (a), conducting level regressions, is to identify pro-poor country fixed effects, which consist of various aspects of a country and make a country pro-poor, but are difficult to quantify. Lastly, we tested the impact of aid on changes in Gini indices, or (c), for a robustness check, as Gini indices are often used in inequality analyses. However, this study pays more attention to changes in the inequality situation of the poor than that of the entire country, in order to assess development effectiveness.

272 Yumeka Hirano and Shigeru Thomas Otsubo

(a) Estimation by the level relationship for the average income of the poorest quintile. We examined the level relationship between average income of the poorest quintile and that of the country, as well as other variables similar to Dollar and Kraay (2002, Eq. 1) by employing a fixed-effects regression model. We looked at the parameter of θ as an indicator of the pro-poorness of aid. Impact of aid to the poor, indicated by the parameter of θ, can be compared with that of policies and institutions, indicated by the parameter of δ: ln y ctp = α + β ln yct + δ ln Zct + θ ln Act + μc + λt + εct

(9.2)

where yp is the average per capita income of the poorest quintile, μc is the unobserved country fixed-effects, λt is the time fixed effects, and εct is a random error term. While looking for the pro-poor explanatory variables, we also intended to identify the country fixed effects, i.e., country-specific factors, that make the country pro-poor, which we call pro-poor country fixed effects, or pro-poor country specific factors. These include the aspects of a country that comprise the degree of its support for lower socioeconomic classes, such as the strength of leadership and degree of dedication to poverty reduction, as well as the strength of traditional socio-economic institutions, in terms of, for example, the civil society network, efficacy of service delivery to the poor, and robustness of the social safety net, which cannot be measured by universal institutional indices.5

(b) Estimation for the growth rates of average income of the poorest quintile. We, in turn, estimate Eq. 9.2 utilizing the growth over change ratio in order to see the impact on the growth rates of average income of the poorest quintile, by variations of average income of the country and other variables. We also explore this examination in more depth, by conducting regressions for the first to the fifth quintiles respectively (quantile regressions): p (ln y ctp – ln y c0 )/t = β(ln yct – ln yc0)/t + δ ln Zct + θ ln Act + λt’ + εct’ (9.3)

We looked into the key parameter β, which measures the elasticity of income growth of the poorest quintile with respect to that of mean income, similar to Dollar and Kraay (2002, Eq. 4). Our main interest is to see the parameter of θ as an indicator of a pro-poor orientation of aid.

(c) Estimation with possible convergence in inequality. We regressed changes in Gini indices on the initial levels of Gini and on the changes in income levels, and (changes in) Z and A variables:

Aid is good for the poor

(ln Ginict − ln Ginic0)/t = α + β1 ln Ginic0 + β2[(ln yct − ln yc0)/t] + δ ln Zct + θ ln Act + λt’ + εct

273

(9.4)

where Gini is a proxy of inequality as measured by Gini coefficients.

9.2.3 Leg 3: Poverty and growth/inequality (poverty regressions)6 We next regressed changes in poverty headcount ratios on the initial levels of poverty, average income growth, and changes in inequality measurements with control variables of A: (ln Povct − ln Povc0)/t = α + β1 ln Povc0 + β2[(ln yct − ln yc0)/t] + β3[(ln Ginict − ln Ginic0)/t] + θ ln Act + λt’ + εct’ (9.5) where Pov is a poverty index. We used poverty headcount ratios in this study.

9.2.4 Description of explanatory variables Aid variables (A) Aid variables are our main interest for assessing the effectiveness of aid in reducing poverty. This study used two different sectoral data of economic aid and social aid, in addition to aggregate aid relative to GDP. It is assumed that economic aid has a positive impact on growth, as it is expected to expand supply capacity. On the other hand, social aid, which includes projects for basic human needs such as education and health, is expected to exhibit a pro-poor orientation in inequality regressions as it is more targeted to the poor. Aggregate aid is also expected to show pro-poorness, as other categories (aggregate aid except economic aid and social aid) which include commodity aid and humanitarian aid, do not have an immediate impact on growth, but assist the poorer segments of society. (Details will be given in Section 9.3.2.)

Factors and conditions (Z)7 Policy variables: This study employed three policy variables (fiscal, monetary, and trade policies), commonly used in the empirical aid–growth literature: government consumption relative to GDP (G/GDP), the period average inflation rate, and trade (exports plus imports) relative to GDP (T/GDP). The G/GDP was included to determine how the size of government affects growth, and whether fiscal policy affects poverty reduction. While excessively large government expenditure is negatively associated with growth, it may have a positive effect on poverty if the expenditure is targeted at the poorer people in society.

274 Yumeka Hirano and Shigeru Thomas Otsubo

Inflation was also included as a policy variable to determine how monetary policy affects holistic growth as well as the poor. Excessive inflation tends to have a strong negative influence on household consumption. We suspect that the negative impact of inflation is much more severe on the poor, whose consumption rate in comparison to the entire income tends to be relatively higher than that of other income groups. The T/GDP, a measure of trade openness, was included to determine whether economic policies on international integration would affect growth in aid recipients. Numerous studies suggest that openness of trade is highly correlated with economic growth. Trade is believed to promote industrialization and enhance technological progress, providing learning opportunities for developing countries, which eventually positively influence economic growth. At the same time, trade volume tends to become larger in some developing countries mainly because of the increasing importation of consumption goods. How much of the benefit of liberalized trade can be derived for growth varies among countries. Taking this into consideration, the impact of trade is expected to be neutral; it depends on many factors.8 Institutional variables: Institutional quality was incorporated as a variable of interest. Many previous studies used an institutional quality index, where particular indices were taken from the International Country Risk Guide (ICRG) indicators (PRS Group, 2012) to define their institutional quality, such as quality of bureaucracy, rule of law, and expropriation risk. Considering the capacity of the recipient country key for development effectiveness, we used the variable of institutional quality which indicates capacity of the government. A country with good institutions, especially capacity, can manage both public and private activities efficiently, which brings about positive effects on growth, as well as development effectiveness. With many previous studies having confirmed the positive relationship between institutional quality and growth, the expected sign of the coefficient is positive.

Exogenous variables (X) The fertility rate and average rate of change in terms of trade (TOT) were added as exogenous variables. These variables are considered to be exogenous, or not correlated with other selected variables, while they have explanatory power for growth. Regional dummies: The current study (for Eq. 9.1) used three regional dummies:9 East Asia and the Pacific (EAP), sub-Saharan Africa (SSA), and the Former Soviet Union (FSU),10 with other regions treated as the base. EAP (or only the East Asian countries) and SSA regional dummies are the ones most often used together in aid–growth empirics (Burnside & Dollar, 2000, 2004; Dalgaard et al., 2004; Rajan & Subramanian, 2008). In addition, we considered it important to include the FSU dummy, as the countries of FSU have experienced rapid reform with economic downturns and remarkable growth thereafter.

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Time dummies: We used the crisis dummy as a time designation, rather than normal time dummies such as annual or decadal time dummies. To have a crisis dummy attached, the period has to contain one of the following: Debt Crisis (1982–83), Asian Financial Crisis (1997–98), or the World Financial Crisis (2008–09). This dummy takes care of time-fixed effects (λt and λt’)11 caused mostly by crises.

Instruments Endogeneity of aid is one of the inevitable limitations of aid–growth studies.12 In light of the shortcoming, instrument variable (IV) estimators are commonly used in the regression analyses. The current study used standardized instruments of lagged values for the levels (including instruments of lagged period averages for explanatory variables of period averages), and initial value and lagged rate of changes for growth spells. Instrumented explanatory variables are identified in the tables of the regression results. In growth regressions for the national average income (Eq. 9.1), variables of trade, institutions, and aid, except for their initial values, were instrumented.13 In regressions for the poorest quintile income (Eqs. 9.2 and 9.3), only national average per capita income was instrumented. In the same manner, only income growth spells were instrumented in the Gini convergence regressions (Eq. 9.4). In the poverty change (P-G-I) regressions (Eq. 9.5), Gini changes were instrumented.

9.3 Data14 The medium-term data set was constructed as a base for the analyses in this study, since our interest is in the impact seen over the medium to long run. The growth spells of the different time durations are compiled from the available data points of bottom-quintile income shares during the period from 1978 to 2010.15 This medium-term database contains 242 growth spells of the five to nine-year period, each with the average duration of 5.72 years, for 98 countries. Out of these, the growth spells of aid sectoral analyses were obtained in accordance with data availability for sectoral aid. The number of observations for sectoral aid is lower, as it was available only after the year 1995. The data for sectoral aid analysis contains 183 growth spells for 60 countries. The data for aggregate aid, which was available during the period 1978–2010, contains 216 growth spells for 87 countries. When comparing the regression results of sectoral aid and aggregate aid, the sample period of aggregate aid was restricted to match that of sectoral aid. Actual numbers of observations were further reduced in IV estimations, when one spell was used as an instrument when necessary.

9.3.1 Data sources Most of the data are taken from the secondary data of various international institutions: major socio-economic data from World Development Indicators (WDIs)

276 Yumeka Hirano and Shigeru Thomas Otsubo

of the World Bank (World Bank, 2012), institutional indicators from the ICRG of the PRS Group (PRS Group, 2012), and aid data from OECD Stat Extracts (OECD-DAC, 2013a). The variables and their data sources are listed in Appendix 9.1.

9.3.2 Aid data Aid data by sector are obtained from the OECD’s Creditor Reporting System (CRS). The CRS provides an aid activity database, which contains detailed quantitative and descriptive data on individual aid projects and programs. The CRS data has made it possible to analyze the sectoral and geographical breakdown of aid for selected years and donors to examine development effectiveness. In the CRS, data on the sector of destination are recorded using purpose codes. There are eight main categories: (I) social infrastructure and services; (II) economic infrastructure and services; (III) production sector; (IV) multi-sector/cross-cutting; (V) commodity aid and general program assistance; (VI) action relating to debt; (VII) humanitarian aid; and (VIII) unallocated/unspecified.16 We used the sectoral data of (I) social infrastructure and services, social aid as we called it, and (II) economic infrastructure, as economic aid, in comparison with the aggregate aid of (I)–(VIII). According to the aid classification of CRS, social aid covers efforts to develop the human resource potential and ameliorate living conditions in aid recipient countries (OECD-DAC, 2007, 2013b). It includes, but is not restricted to: education such as educational infrastructure, services, and investment in all areas; health and population such as assistance to hospitals and clinics, other medical services, including disease control and vaccination programs, and reproductive health and family planning; and water supply, sanitation, and sewerage. Economic aid covers assistance for networks, utilities, and services that facilitate economic activities. It includes, but is not restricted to, transportation, that is, equipment or infrastructure for road, rail, water, and air transport; energy, production and distribution of energy; communication for television, radio, and electronic information networks; and banking, financial, and business services. In addition, we used aggregate aid, which is the sum of the eight main categories mentioned above. The current study used post-1995 economic and social aid commitment data, due to data limitations in prior years. The completeness of CRS commitments for DAC members has improved from 70 percent in 1995 to over 90 percent in 2000, and reached nearly 100 percent by 2003 (OECD-DAC, 2013c). On the other hand, disbursement data completeness was below 60 percent prior to 2002, improved to 90 percent that year, and reached nearly 100 percent starting with 2007 flows. We felt that only using post-2002 data was not sufficient for timeseries cross-country analyses, while including the data before 1995 would bias the results to some extent.17 Since our intention was to examine the significance of the (directional) impact of aid rather than measuring the degree of elasticity in the aid coefficients, this study simply used commitment data. We judged that this

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would not change the significance of the impact of sectoral aid.18 As to the measurement of aid, this study used the period average gross economic and social aid, as well as net aggregate aid received.19

9.3.3 Constructing institutional quality indices The meaning, measurement, and implications of institutions or “institutional quality” can differ considerably among researchers. We used specified institution indices to examine the impact on our research focus as the importance of using different components of institutions for growth regression has been discussed in the literature. Dalgaard et al. (2004, p. 200), pointed out that a composite index of policies might encapsulate some components that enhance the return to aid while others diminish this impact, with the net effect possibly insignificant. Abramovitz (1986) argued that the growth-enhancing effects of economic integration depend on the absorptive capacity of the host economies and that institutional quality was one of the main factors underlying such capacity. We constructed indices for the quality of institutions extracted from the ICRG of the PRS Group. The ICRG indicator is given by the ICRG Rating System, whose rating comprises 22 variables in three subcategories of risk: political (ICRGP), financial (ICRG-F), and economic (ICRG-E) (PRS Group, 2012). Out of the various composites and individual indices contained in the ICRG, we formed the capacity sub-composite (ICRG Capacity) by compiling five specific components from the ICRG-P bracket: government stability, investment profile, corruption, law and order, and bureaucracy quality. Among the 12 indicators in the ICRG-P, these five indicators denote management capabilities of recipient countries, while the seven other indicators represent the security and stability of a country in a different form of “institutional” capacity. We consider institutional quality of a recipient country, and government managerial capacity in particular, to be key for development effectiveness. As for the measurement, we placed greater importance on change in institutional quality rather than the level of institutional quality. While the majority of past research used levels of institutional quality with the assumption that institutional quality does not change much, we consider (directional) changes in institutional quality to matter for assessing development effectiveness. Rapid poverty reduction in low-income countries depends primarily on these countries improving their own policies and institutions (Collier & Dollar, 2001, p. 1787). We emphasize “improving,” that is changing, institutions in this study.

9.3.4 Cross-correlations between variables Table 9.1 shows cross-correlations between dependent variables in the topleft rectangle, between independent/explanatory variables in the bottom-right rectangle, and between dependent and explanatory variables in the bottom-left non-shaded rectangle for the period from the late 1990s to 2000s. We considered

(2) pcYp

(3) Gini

(4) HCR

(5) G/GDP

(6) Inflation

1

1 ----0.6071*** (8.98) 0.8102*** (16.24)

1 ----0.8968*** (23.81)

Note: *, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively. Absolute value of t-statistics calculated with White-corrected standard errors is in parentheses (for aid data variables only). Source: Authors’ compilation.

− 0.2443*** 0.1378 (2.63) (1.45) − 0.1946** 0.0204 (2.07) (0.21) − 0.2625*** 0.0711 (2.84) (0.74)

− 0.5575***

1

1 -----

(7) (8) (9) (10) (11) (12) (13) In_T/GDP Δ_T/GDP In_ICRGC Δ_ICRGC EAID/GDP SAID/GDP AAID/GDP

(1) Period Average Growth 1 Rate of Per Capita Income (2) Period Average Growth 0.5676*** 1 Rate of Per Capita Income of the Poorest Quintile (3) Period Average Rate of − 0.0110 − 0.7007*** 1 Change of Gini Index (4) Period Average Rate of − 0.3970*** − 0.4415*** 0.2209*** 1 Change of the Poverty Head Count Ratio (5) Initial Government 0.0555 0.0907 0.0114 − 0.0163 1 Consumption/GDP (6) Ln(1 + Period Average − 0.0787 − 0.0911 0.0504 0.1713** − 0.0046 1 Inflation/CPI) (7) Initial Trade/GDP 0.1985** 0.2058** − 0.0346 − 0.2033** 0.1960** − 0.0016 1 (8) Period Average Growth 0.1293 0.0569 0.0834 0.2012** 0.0118 0.1019 − 0.2592*** 1 Rate of Trade/GDP (9) Initial Level of Institutional 0.0366 0.0301 0.0629 0.0606 0.4240*** − 0.0660 0.3386*** −0.0069 Quality (ICRG Capacity) (10) Period Average Rate of 0.1602* − 0.0163 0.0754 − 0.0366 − 0.1063 − 0.0139 − 0.3083*** 0.1042 Change of Institutional Quality (ICRG Capacity) (11) Period Average Economic 0.0166 0.0571 − 0.1178 0.1090 − 0.0977 0.1241 − 0.0618 0.1661* Aid/GDP (0.20) (0.67) (1.39) (1.25) (1.13) (1.42) (0.69) (1.83) (12) Period Average Social − 0.1358 0.0355 − 0.1979** 0.0627 0.0125 0.0097 − 0.0248 0.1035 Aid/GDP (1.61) (0.42) (2.37) (0.71) (0.14) (0.11) (0.28) (1.13) (13) Period Average Aggregate − 0.1482* 0.0302 − 0.2034** 0.1051 − 0.0148 0.0631 − 0.0422 0.1084 Aid/GDP (1.76) (0.35) (2.44) (1.20) (0.17) (0.72) (0.47) (1.18)

(1) pcY

TABLE 9.1 Cross-correlations between dependent and explanatory variables (medium-term dataset, 5 –9 years, the late 1990s –2000s)

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correlation among variables in order to avoid a possible bias by multicollinearity when selecting the sets of variables. All three aid variables, e.g., economic, social, and aggregate aid, demonstrate positive correlation with the period average growth rate of per capita income of the poorest quintile. However, social and aggregate aid is negatively correlated with the period average growth rate of a nation’s average per capita income while economic aid has a positive correlation. These comparisons of simple correlation coefficients indicate that the effects of aid could vary between different sectors of aid. All aid variables demonstrate negative correlation with Gini. The impact of social and aggregate aid is significant, indicating that aid may contribute to reducing inequality. In addition, change in institutional quality has a positive correlation with the period average growth rate of per capita income, while the sign of the coefficient turns negative in the relationship with that of the poorest quintile. Among the correlations between aid variables and other explanatory variables, the aid variables are negatively correlated with the initial level of institutional quality (ICRG Capacity): economic aid and aggregate aid are correlated at the 1 percent significance level and social aid at the 5 percent significance level. This suggests that aid is given to lower-income countries, whose initial condition of institutional quality is usually low at early stages of development. On the other hand, the correlation between aid variables and change in institutional quality is positive, but insignificant. The relationship between aid and change in institutional quality shows wide dispersion, unlike the relationship in levels. This suggests that the allocation of aid in the past did not necessarily depend on whether the institutional quality of recipient countries was changing, i.e., improving. The period average growth rate of trade has a significant positive correlation with only economic aid at the 10 percent level. Economic aid has facilitated the improvement of various economic infrastructure, which is key for promoting trade. For instance, Aid-for-Trade Initiatives have been implemented to help developing countries overcome trade-related issues, such as transportation management and custom regulations. In addition, both initial levels and change in institutional quality are significantly correlated with the initial level of trade. We found that institutional quality variables did not have any significant correlation with the growth rate of trade in our sample.

9.4 Regression results 9.4.1 Economic aid promotes growth Table 9.2 shows the regression results of Equation 9.1—growth regressions—with variables of policies, institutions, and aid. The series of regression analyses showed that economic aid indeed promotes growth. First, we examined the impact of three policy variables and an aid variable on growth (Columns 3–5). A negative coefficient for initial G/GDP (fiscal policy) implies that large government is, on average, negatively associated with growth

(2)

Soc Aid (4)

Agg Aid (5)

Policies Eco Aid (6)

Soc Aid (7)

Agg Aid (8) (9)

EcoAid (10)

Soc Aid (11)

Institutions

Dependent Variable: Period Average Growth Rate of Per Capita Income

Agg Aid (12) (13)

Soc Aid (15)

Policies and Institutions EcoAid (14)

Agg Aid (16)

127 0.44

105 0.41

85 0.44

85 0.47

95 0.47

99 0.49

100 0.47

112 0.45

102 0.24

77 0.27

77 0.34

82 0.28

87 0.24

74 0.35

74 0.40

79 0.34

Notes: i) Absolute value of t-statistics calculated with White-corrected standard errors is in parentheses. *, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively. ii) Panel two-stage least squares methods is used for these analyses. iii) # denotes variables are instrumented with; #1 – the initial level and period average growth rate of the previous spell; #2 – the period average rate of the previous spell. Source: Authors’ compilation.

No. of Observations R-squared

0.1188*** 0.1348*** 0.0998** 0.1259*** 0.1204*** 0.0799 0.1162*** 0.1177*** 0.1202*** 0.1358*** 0.1293*** 0.1334*** 0.1257*** 0.1315*** 0.1349*** 0.1319*** (5.99) (5.27) (2.11) (3.94) (4.11) (1.58) (3.55) (4.36) (5.10) (2.96) (4.79) (4.94) (5.19) (2.99) (5.32) (4.99) Initial Ln(Per −0.0082*** −0.0083*** −0.0035 −0.0060* −0.0058* −0.0028 −0.0069** −0.0073** −0.0078*** −0.0096** −0.0085*** −0.0090** −0.0081*** −0.0083* −0.0082*** −0.0080*** Capita Income) (3.83) (3.03) (0.71) (1.78) (1.87) (0.53) (1.99) (2.58) (2.84) (1.99) (2.88) (3.07) (2.86) (1.80) (2.98) (2.74) Initial Ln(Fertility) −0.0253*** −0.0273*** −0.0300*** −0.0342*** −0.0337*** −0.0245** −0.0281*** −0.0269*** −0.0318*** −0.0355*** −0.0386*** −0.0388*** −0.0304*** −0.0342*** −0.0396*** −0.0405*** (4.27) (3.63) (2.90) (3.37) (3.67) (2.57) (3.29) (3.25) (5.34) (2.96) (3.76) (4.10) (4.82) (2.92) (3.83) (4.12) Period Average Rate 0.1142** 0.0918 0.1299** 0.1225** 0.1104* 0.1521*** 0.1474*** 0.1509*** 0.0467 0.0556 0.0557 0.0598* 0.0701 0.0805** 0.0804* 0.0726 of Change of TOT (2.10) (1.45) (2.09) (2.05) (1.94) (2.68) (2.74) (2.88) (1.05) (1.23) (1.23) (1.28) (1.38) (1.82) (1.76) (1.54) Initial Government −0.0005 −0.0005 −0.0008 −0.0007* Consumption/GDP (1.04) (1.05) (1.63) (1.83) Ln(1 + Period −0.0671 −0.1099*** −0.1098*** −0.0741* −0.1132*** −0.1064*** −0.0806** −0.0627* −0.0869*** −0.0860*** −0.0576* Average (1.46) (2.91) (3.14) (1.76) (4.38) (3.93) (2.31) (1.97) (2.67) (2.85) (1.84) Inflation/CPI) Period Average 0.0717 −0.0984 −0.0804 −0.0074 Growth Rate of (0.49) (0.52) (0.43) (0.05) Trade/GDP#1 Period Average −0.0495 0.0176 0.0623 0.0210 −0.0914 0.0542 0.0468 0.0123 Rate of Change (0.92) (0.08) (0.35) (0.20) (0.76) (0.30) (0.30) (0.13) of Institutional Quality (ICRG Capacity)#1 Period Average 0.0111** 0.0034** 0.0013** 0.0099* 0.0017 0.0004 0.0027 0.0028** 0.0010 0.0047 0.0033*** 0.0014* Aid/GDP#2 (2.00) (2.09) (2.57) (1.73) (0.99) (0.74) (0.52) (2.33) (1.53) (0.89) (2.54) (1.91) Regional Dummy 0.0017 −0.0068 −0.0052 −0.0058 −0.0069 −0.0056 −0.0042 −0.0051 0.0032 −0.0037 −0.0020 −0.0035 −0.0914 −0.0064 −0.0055 −0.0065 EAP (0.26) (0.84) (0.59) (0.68) (0.85) (0.78) (0.61) (0.76) (0.43) (0.51) (0.27) (0.46) (0.76) (0.88) (0.74) (0.86) −0.0029 −0.0067 −0.0102* −0.0079 −0.0098** −0.0003 −0.0044 −0.0060 −0.0063 −0.0032 −0.0065 −0.0076 −0.0088 Regional Dummy −0.0065 −0.0026 −0.0054 (1.53) (0.42) (0.79) (0.45) (1.17) (1.85) (1.66) (2.09) (0.04) (0.52) (0.86) (0.90) (0.47) (0.77) (1.10) (1.18) SSA FSU Dummy 0.0199** 0.0198* 0.0235 0.0225 0.0233 0.0259** 0.0254* 0.0246* −0.0140 −0.0324** −0.0365*** −0.0369*** −0.0138 −0.0302** −0.0384*** −0.0398*** (2.18) (1.68) (1.34) (1.25) (1.28) (1.96) (1.89) (1.84) (0.89) (2.13) (2.93) (3.35) (0.82) (2.14) (3.15) (3.53) Crises Dummy −0.0057 −0.0062 −0.0039 −0.0030 −0.0013 −0.0025 −0.0026 −0.0026 −0.0027 0.0005 0.0005 0.0017 −0.0005 −0.0005 0.0001 0.0021 (1.61) (1.55) (0.93) (0.67) (0.34) (0.61) (0.60) (0.67) (0.68) (0.09) (0.10) (0.35) (0.10) (0.10) (0.03) (0.43)

Constant

(1)

Eco Aid (3)

TABLE 9.2 Aid, policies, institutions, and growth

Aid is good for the poor

281

performance. A strong negative coefficient is continuously attached to the inflation variable, indicating that high inflation can be an impediment to growth. This suggests the importance of inflation control (monetary policy). The result of changes of trade/GDP (trade policy) was mixed, and it was statistically insignificant. That is, whether trade promotes growth depends on how each country manages it. This tendency is robust, as it occurred in the same manner in our earlier study (Chapter 2). All the coefficients of economic, social, and aggregate aid were positive at the 5 percent significance level. However, these positive results happened to stem from the relatively high correlation between trade and aid variables, especially for economic aid. To avoid a possible distortion in the results, we decided to use only the inflation variable as a policy variable.20 The estimation results with one policy (inflation) and aid variables are shown in Columns 6–8. A significant negative impact of inflation did persist. We found that the coefficient of economic aid (Column 6) was a positive and significant impact while the coefficients of social aid (Column 7) and aggregate aid (Column 8) were positive, but smaller and insignificant. These results confirm that economic aid contributes to growth regardless of certain prerequisite conditions21 of a recipient country, such as good policies, institutional quality, and climate-related geographical environments. This is no surprise, as economic infrastructure and services have been provided to developing countries to spur economic development. The insignificant positive coefficients attached to social and aggregate aid should be considered natural, as their immediate purposes are not for increasing per capita income growth. We argue that the reason why past literature often failed to prove the significant positive impact of aid on growth is not because aid did not actually promote growth, but because the authors failed to extract the different effects from each aid sector. By carefully considering the uniqueness of each sector/type, aid effectiveness can be appropriately assessed by measuring per capita income. Next, we controlled for change in institutional quality and aid on growth (Columns 10–12). The variable of change in institutional quality was positive, yet insignificant, in all estimations. The significant and positive coefficient of social aid (Column 11), as well as a moderately significant and positive coefficient of aggregate aid (Column 12) was observed. These increasing significance levels of social and aggregate aid could be attributed to joint effects from change in institutional quality. In other words, the impact of aid on growth can be more significant in a recipient country whose institutional quality and capacity in particular are improving. In contrast, the positive coefficient of economic aid lost its significance in this set of variables (Column 10) due to a statistical limitation. This supposedly inaccurate result came from the high correlation between economic aid and change in institutional quality that the current study confirmed in the correlation matrix. On top of these estimations of institutions and aid, we added inflation as a selected policy variable (Columns 14–16). Inclusion of inflation did not change the core results; it only increased the coefficients’ size and significance of all aid

282 Yumeka Hirano and Shigeru Thomas Otsubo

variables. Columns 15 and 16 proved the robustness of this key finding with an additional insight: the effectiveness of social and aggregate aid is larger and more significant with improving institutional quality, and it further increases in a country where monetary policy is appropriately managed. The estimation of economic aid (Column 14) did not show the same result, regardless of our hypothesis that economic aid would work better where institutional quality is improving. The insignificance attached to economic aid simply indicates that the statistical problem arising from the high correlation between economic aid and change in institutional quality remains in this estimation. This issue prevents us from adding these two variables together in growth regressions in the current study. The distorted result cannot be directly compared with the results of social and aggregate aid, which do not have the correlation problem with change in institutional quality. Therefore, the regression results of economic aid with change in institution (Columns 10 and 14) are presented only for reference in this chapter. We also should not ignore the fact that the negative coefficient attached to the SSA regional dummy persisted. The SSA nations tend to lag behind in promoting growth and effectiveness of aid. This suggests that the characteristics of the region should be taken into consideration in formulating and implementing development strategies.

9.4.2 Building institutions matters for development effectiveness22 Table 9.3 shows the impact of aid on countries with different institutional levels and rates of change in institutions. We estimated the effects of aid by dividing samples based on different conditions of institutional quality: high, low, improving, or not improving, as defined in the section detailing model specification. Using the estimation results of Columns 6, 7, and 8 in Table 9.2 as a base (these are listed again in Columns 1, 6, and 11 in Table 9.3 for quick reference), we further examined the impact of economic, social, and aggregate aid in the respective sample groups. When we tested the sample groups divided by initial level of institutional quality, we found that the impact of aid became less significant (Columns 2, 3, 7, 8, and 12) no matter how high or low the institutional quality a country had at the starting point. The impact of economic aid lost its statistical significance level of 10 percent while social aid decreased the t-statistic value. Interestingly, this study found more distinct differences when testing the sample groups divided by directional change in institutional quality. The impact of both economic and social aid became larger with statistical significance in a country where institutional quality was improving (Columns 4 and 9). On the other hand, effects of both economic and social aid became much less significant in a country whose institutional quality is not or improving23 or worsening (Columns 5 and 10). As for aggregate aid, a similar effect was observed in the case of countries where institutional quality is not improving: the coefficient of aggregate aid turned negative in the same manner as social aid (Column 15). However, the

(2)

99 0.49

42 0.44

43 0.57

0.1085 (1.47) − 0.0062 (0.75) − 0.0265 (1.08) 0.1297 (1.57) −0.1122** (2.57) 0.0068 (0.93) − 0.0129 (1.13) − 0.0111 (1.03) 0.0394 (1.32) − 0.0038 (0.49)

(3)

(5)

(6)

Avg_Inst=Ave In_Inst=0

0.0799 0.1428* (1.58) (1.82) − 0.0028 − 0.0100 (0.53) (1.23) − 0.0245** −0.0307** (2.57) (2.08) 0.1521*** 0.2162* (2.68) (1.84) − 0.1132*** − 0.0731 (4.38) (1.25) 0.0099* 0.0024 (1.73) (0.27) − 0.0056 − 0.0093 (0.78) (0.98) − 0.0102* − 0.0091 (1.85) (0.98) 0.0259** 0.0025 (1.96) (0.14) − 0.0025 0.0021 (0.61) (0.29)

(1)

All

Social Aid

Notes: i) Absolute value of t-statistics calculated with White-corrected standard errors is in parentheses. *, ** and *** indicate significance at the 10%, 5% and 1% levels, respectively. ii) Panel two-stage least squares methods is used for these analyses. iii) # denotes variables are instrumented with the period average rate of the previous spell. iv) Samples were divided by different conditions of institutional quality: (i) countries whose initial level institutional quality is high (more than the sample mean) (In_Inst>Ave); (ii) countries whose initial level institutional quality is low (less than the sample mean) (In_Inst=0); and (iv) countries whose institutional quality is not-improving (the change ratio is zero or negative) (Avg_Inst=