Crisis, Complexity and Conflict, Volume 9

CRISIS, COMPLEXITY AND CONFLICT

Contributions to

Conflict Management, Peace Economics and Development Volume 9 SERIES EDITOR

MANAS CHATTERJI BOOKS IN THE SERIES

Eurasia: A New Peace Agenda, edited by M. D. Intriligator Cultural Differences between the Military and Parent Society in Democratic Countries, edited by G. Caforio Managing Conflict in Economic Convergence of Regions in Greater Europe, edited by F. Carluer Military Missions and Their Implications Reconsidered: The Aftermath of September 11th, edited by G. Caforio and G. Kuemmel Conflict and Peace in South Asia, edited by M. Chatterji and B. M. Jain War, Peace, and Security, edited by Jacques Fontanel and Manas Chatterji Armed Forces and Conflict Resolution, edited by G. Caforio, G. Kümmel and B. Purkayastha Regional Development and Conflict Management: A Case for Brazil, by Raphael Bar-El Crisis, Complexity and Conflict, by I. J. Azis Putting Teeth in the Tiger: Improving the Effectiveness of Arms Embargoes, edited by Michael Brzoska and George A. Lopez (Forthcoming) Peace Science: Theory and Cases, by P. Gangopadhyay and M. Chatterji (Forthcoming) Advances in Military Sociology: Essays in Honor of Charles C. Moskos (Two Volume Set), edited by Giuseppe Caforio (Forthcoming)

Contributions to Conflict Management, Peace Economics and Development volume 9

CRISIS, COMPLEXITY AND CONFLICT IWAN J. AZIS Regional Science, and Johnson Graduate School of Management, Cornell University, USA

United Kingdom – North America – Japan India – Malaysia – China

Emerald Group Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2009 Copyright © 2009 Emerald Group Publishing Limited Reprints and permission service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. No responsibility is accepted for the accuracy of information contained in the text, illustrations or advertisements. The opinions expressed in these chapters are not necessarily those of the Editor or the publisher. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-84855-204-3 ISSN: 1572-8323 (Series)

Awarded in recognition of Emerald’s production department’s adherence to quality systems and processes when preparing scholarly journals for print

CONTENTS LIST OF FIGURES

vii

LIST OF TABLES

xi

FOREWORD

xiii

PREFACE

xv

ACKNOWLEDGMENT

xvii

CHAPTER 1 INTRODUCTION

1

CHAPTER 2 GLOBAL IMBALANCES

5

CHAPTER 3 FINANCIAL CRISIS

25

CHAPTER 4 REGIONAL FINANCIAL ARRANGEMENT

55

CHAPTER 5 OIL PRICE INCREASE

99

CHAPTER 6 MITIGATING CLIMATE CHANGE

v

155

vi

CONTENTS

CHAPTER 7 LESSONS AND CONCLUSIONS

173

REFERENCES

187

INDEX

191

LIST OF FIGURES Figure 2.1 Figure 2.2 Figure 2.3 Figure 2.4 Figure Figure Figure Figure Figure Figure

2.5 2.6 3.1 3.2 3.3 3.4

Figure 3.5 Figure 3.6 Figure 4.1 Figure 4.2 Figure 4.3 Figure 4.4 Figure 4.5 Figure 4.6 Figure 4.7 Figure 4.8 Figure 4.9 Figure 4.10 Figure B1

Current Account Balances (Percentage of GDP) . . . U.S. Deficit (Inverted Sign) and Oil Producers Surplus of Current Account . . . . . . . . . . . . . . . . . . Current Account Balance, Saving and Investment: Industrial Countries . . . . . . . . . . . . . . . . . . . . . . . Current Account Balance, Saving and Investment: Emerging Markets and Oil Producing Economies . . . Effect of Rising Imports . . . . . . . . . . . . . . . . . . . . Effect of Higher Preference Towards U.S. Assets . . . US Financial Sector’s Investment in Financial Assets . Spread between 3–Mo LIBOR and OIS . . . . . . . . . Trade-off between Dollar Value and Recession . . . . US Aggregate Supply (AS) and Aggregate Demand (AD) Slopes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sources of U.S. Output Growth and Inflation Shocks . Total Values of M&A Announced by SWF and the Share Going To Western Financial Institutions . . . . Impulse Responses to 1 SD Exchange Rate Shock . . Searching for Preferred Form of RFA: Model Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Searching for Preferred Form of RFA: Benefit Model . Searching for Preferred Form of RFA: Opportunity Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Searching for Preferred Form of RFA: Cost Model . Searching for Preferred Form of RFA: Risk Model . Results with Feedback Effects (Network) under Different BOCR Ratings . . . . . . . . . . . . . . . . . . . . Results without Feedback Effects (Hierarchy) under Different BOCR Ratings . . . . . . . . . . . . . . . . . . . . Sensitivity with Respect to Benefit and Opportunity . Sensitivity with Respect to Cost and Risk . . . . . . . . Hong Kong (China) Dollar . . . . . . . . . . . . . . . . . . vii

...

6

...

7

...

8

. . . . . .

.. 9 . 20 . 21 . 30 . 33 . 38

.. ..

41 42

.. ..

46 59

.. ..

64 65

.. .. ..

67 68 70

..

75

. . . .

76 76 77 86

. . . .

viii

Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure

LIST OF FIGURES

B2 B3 B4 B5 B6 B7 B8 C1 C2 C3 C4 C5 C6 5.1

Figure 5.2 Figure 5.3 Figure 5.4 Figure 5.5 Figure 5.6 Figure 5.7 Figure 5.8 Figure 5.9 Figure A1 Figure D1 Figure D2 Figure D3 Figure D4 Figure D5

Indonesian Rupiah . . . . . . . . . . . . . . . . . . . . . . . . Malaysian Ringgit . . . . . . . . . . . . . . . . . . . . . . . . . Philippines Peso . . . . . . . . . . . . . . . . . . . . . . . . . . Singapore Dollar . . . . . . . . . . . . . . . . . . . . . . . . . . South Korea Won . . . . . . . . . . . . . . . . . . . . . . . . . Taipei (China) Dollar . . . . . . . . . . . . . . . . . . . . . . Thai Baht . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Linear Hierarchy . . . . . . . . . . . . . . . . . . . . . . . . . . Feedback Network . . . . . . . . . . . . . . . . . . . . . . . . Supermatrix of a Hierarchy . . . . . . . . . . . . . . . . . . Supermatrix of a Holarchy . . . . . . . . . . . . . . . . . . . Supermatrix of a Network . . . . . . . . . . . . . . . . . . . Entry in the Supermatrix of a Network . . . . . . . . . . Average CIF Cost of Imported Crude Oil (IEA Total) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . How Oil Price Increase Affects Poverty . . . . . . . . . . Real GDP Growth Rates (2003–2006) . . . . . . . . . . Structural Path of Oil-Intensive Rubber–Petroleum– Plastic Industries in India . . . . . . . . . . . . . . . . . . . Structural Path of Oil-Intensive Transport and Telecommunication Sector in China . . . . . . . . . . . . Structural Path of Oil-Intensive Transport Sector in Thailand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Structural Path of Oil-Intensive Chemical Industry in Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . India: Kerosene and Diesel Wholesale Price Index . . Domestic Fuel Price Increases in Some Countries . . Global Influence: All Elementary Paths and Circuits Linking i and j . . . . . . . . . . . . . . . . . . . . . . . . . . . China Impulse Response: Fuel Subsidy - Fuel Price - Interest Rate - Inflation - Poverty Line . . . . . China Impulse Response: Fuel Subsidy - Kerosene Price - Interest Rate - Inflation - Poverty Line . China Impulse Response: Fuel Subsidy - Fuel Price - Manufacturing - Agriculture - Rural Poor . . . China Impulse Response: Fuel Subsidy - Fuel Price - Manufacturing - Agriculture - Urban Poor . . China Impulse Response: Fuel Subsidy - Kerosene Price - Manufacturing - Agriculture - Rural Poor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . .

. . . . . . . . . . . . .

86 87 87 88 88 89 90 91 91 92 92 93 93

. . .

101 102 103

.

110

.

114

.

117

. . .

118 125 129

.

132

.

135

.

136

.

136

.

137

.

137

ix

List of Figures

Figure D6

Figure D7 Figure D8 Figure D9 Figure D10 Figure D11 Figure D12 Figure D13 Figure D14 Figure D15 Figure D16 Figure D17 Figure D18 Figure D19 Figure D20 Figure D21 Figure D22 Figure D23

Figure D24

China Impulse Response: Fuel Subsidy - Kerosene Price - Manufacturing - Agriculture - Urban Poor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . China Impulse Response: Fuel Subsidy - Fuel Price - SOC - Rural Poor . . . . . . . . . . . . . . . . . . . . . China Impulse Response: Fuel Subsidy - Kerosene Price - SOC - Rural Poor . . . . . . . . . . . . . . . . . India Impulse Response: Fuel Subsidy - Kerosene Price - Interest Rate - Inflation - Poverty Line . India Impulse Response: Fuel Subsidy - Diesel Price - Interest Rate - Inflation - Poverty Line . India Impulse Response: Fuel Subsidy - Kerosene Price - GDP - Rural Poor . . . . . . . . . . . . . . . . . India Impulse Response: Fuel Subsidy - Diesel Price - GDP - Rural Poor . . . . . . . . . . . . . . . . . India Impulse Response: Fuel Subsidy - Kerosene Price - Services - Rural Poor . . . . . . . . . . . . . . . India Impulse Response: Fuel Subsidy - Kerosene Price - Services - Urban Poor . . . . . . . . . . . . . . India Impulse Response: Fuel Subsidy - Diesel Price - Services - Rural Poor . . . . . . . . . . . . . . . India Impulse Response: Fuel Subsidy - Diesel Price - Services - Urban Poor . . . . . . . . . . . . . . Korea Impulse Response: Diesel Price - SOC Poor Households . . . . . . . . . . . . . . . . . . . . . . . . . Korea Impulse Response: Gasoline Price - SOC Poor Households . . . . . . . . . . . . . . . . . . . . . . . . . Korea Impulse Response: Diesel Price - Interest Rates - Inflation - Poverty Line . . . . . . . . . . . . . Korea Impulse Response: Gasoline Price - Interest Rates - Inflation - Poverty Line . . . . . . . . . . . . . Korea Impulse Response: Gasoline Price Manufacturing - Agriculture - Poor Households . Korea Impulse Response: Gasoline Price Manufacturing - Agriculture - Poor Households . Thailand Impulse Response: Fuel Subsidy Kerosene Price - Interest Rates - Inflation Poverty Line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Thailand Impulse Response: Fuel Subsidy - Diesel Price - Interest Rates - Inflation - Poverty Line .

.

138

.

138

.

139

.

139

.

140

.

140

.

141

.

141

.

142

.

142

.

143

.

143

.

144

.

144

.

145

.

145

.

146

.

146

.

147

x

LIST OF FIGURES

Figure D25 Thailand Impulse Response: Fuel Subsidy Kerosene Price - Manufacturing - Agriculture Poor Households . . . . . . . . . . . . . . . . . . . . . . . . . Figure D26 Thailand Impulse Response: Fuel Subsidy - Diesel Price - Manufacturing - Agriculture - Poor Households . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure D27 Thailand Impulse Response: Fuel Subsidy Kerosene Price - SOC - Poor Households . . . . . . Figure D28 Thailand Impulse Response: Fuel Subsidy - Diesel Price - SOC - Poor Households . . . . . . . . . . . . . Figure D29 Indonesia Impulse Response: Fuel Subsidy Kerosene Price - Interest Rates - Inflation Rural Poverty Line . . . . . . . . . . . . . . . . . . . . . . . . Figure D30 Indonesia Impulse Response: Fuel Subsidy Kerosene Price - Interest Rates - Inflation Urban Poverty Line . . . . . . . . . . . . . . . . . . . . . . . Figure D31 Indonesia Impulse Response: Fuel Subsidy - Diesel Price - Interest Rates - Inflation - Rural Poverty Line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure D32 Indonesia Impulse Response: Fuel Subsidy - Diesel Price - Interest Rates - Inflation - Urban Poverty Line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Figure D33 Indonesia Impulse Response: Fuel Subsidy Kerosene Price - GDP - Rural Poor . . . . . . . . . Figure D34 Indonesia Impulse Response: Fuel Subsidy Kerosene Price - GDP - Urban Poor . . . . . . . . . Figure D35 Indonesia Impulse Response: Fuel Subsidy - Diesel Price - GDP - Rural Poor . . . . . . . . . . . . . . . . Figure D36 Indonesia Impulse Response: Fuel Subsidy - Diesel Price - GDP - Urban Poor . . . . . . . . . . . . . . . . Figure 6.1 Incomes, Poverty Line, Food Output, and Prices . . . Figure 6.2 Demand for Food, Exports, Agriculture Share, and Gini Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

.

147

.

148

.

148

.

149

.

149

.

150

.

150

.

151

.

151

.

152

.

152

. .

153 164

.

165

LIST OF TABLES Table 2.1 Table 4.1 Table 4.2 Table 4.3 Table 4.4 Table Table Table Table Table Table Table Table Table

A1 A2 A3 A4 A5 A6 A7 A8 5.1

Table 5.2 Table 5.3

Table 5.4 Table 5.5 Table B1 Table 6.1

Net International Reserves (US$ billions) . . . . . . . . Net Results (Ranking) of the Benefits Cluster with Feedback Effects . . . . . . . . . . . . . . . . . . . . . . . . . . Net Results (Ranking) of the Opportunity Cluster with Feedback Effects . . . . . . . . . . . . . . . . . . . . . . Net Results (Ranking) of the Cost Cluster with Feedback Effects . . . . . . . . . . . . . . . . . . . . . . . . . . Net Results (Ranking) of the Risk Cluster with Feedback Effects . . . . . . . . . . . . . . . . . . . . . . . . . . Hong Kong (China) Dollar . . . . . . . . . . . . . . . . . . Indonesian Rupiah . . . . . . . . . . . . . . . . . . . . . . . . Malaysian Ringgit . . . . . . . . . . . . . . . . . . . . . . . . . Philippines Peso . . . . . . . . . . . . . . . . . . . . . . . . . . Singapore Dollar . . . . . . . . . . . . . . . . . . . . . . . . . . South Korea Won . . . . . . . . . . . . . . . . . . . . . . . . . Taipei (China) Dollar. . . . . . . . . . . . . . . . . . . . . . . Thai Baht . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Backward and Forward Multipliers of Oil-Intensive Sectors in China, India, Indonesia, and Thailand . . . How India’s Oil-Intensive Rubber–Petroleum–Plastic Industries Affect Household Incomes . . . . . . . . . . . How China’s Oil-Intensive Transport and Telecommunication Sector Affects Household Incomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . How Thailand’s Oil-Intensive Transport Sector Affects Household Incomes . . . . . . . . . . . . . . . . . . How Indonesia’s Oil-Intensive Chemical Industry Affects Household Incomes . . . . . . . . . . . . . . . . . . What Poor and Rich Households Spend on Their Additional Incomes . . . . . . . . . . . . . . . . . . . . . . . . Average Growth Rates, 2005–2050 . . . . . . . . . . . . . xi

..

11

..

72

..

73

..

74

. . . . . . . . .

74 80 81 81 82 83 83 84 85

. . . . . . . . .

.

107

.

111

.

115

.

116

.

120

. .

133 163

This page intentionally left blank

FOREWORD The topics of the books published in this series not only relate to peace and international relations but also to conflicts in other areas such as the environment, development, and physical and human resources. However, all of these subjects are interrelated. Past and present financial crises are a case in point. Regionalism as against globalization has been proposed in this volume to minimize the probability of such a crisis in the future and manage the conflict. This book links crisis management to regionalism and presents a strategy (regional financial management) to reduce conflict. The author formulates a set of strategic criteria to maximize the net short and longterm benefits. In the short term, financial cooperation, more risk taking, macroeconomic coordination, avoidance of currency-cum-maturity mismatch, etc., may be the appropriate policy. Examples of long-term benefits are diversifying risks and stronger regulation. Examples of short-term costs are coordination failures and moral hazard. The long-term cost is the reduced degree of compliance. Control standards need not be the same for every case particularly for the domestic standards, e.g., rural vs. urban. The question of trade-off arises not only in the concepts of financial crisis but also in the formation of regional cooperation. This regionalism to manage conflict is seen as a contradicting force to the globalization and liberalization process. To make this strategy more applicable to most situations, the author uses a quantitative model which can be empirically estimated. Manas Chatterji Series Editor May 2009

xiii

This page intentionally left blank

PREFACE This book is about factors that generate conflict-prone behavior and situations. These factors can of course lead to steps that later do away with conflict and hostility. But in the many cases which do not, conflict analysis must turn to examination of the earlier situations of clashes— clashes arising from ideological differences between countries, regions, organizations, political groups, religions, ethnicities, etc. Thus, it is very often imperative to understand the process through which a conflict-prone behavior comes about. Numerous factors associated with that process may play a key role in generating the outcome as well as in resolving the conflict. In this book Azis examines conflict from global imbalances that led to the 2008 global financial crisis, to imbalances in resource endowments among nations and the resulting differences in conflict prone steps they are likely to take. The meltdown in the U.S. economy sparked such behavior in many individual nations. What are these upcoming conflict-prone behaviors? One set is clearly on the horizon. As discussed in chapter 6, there are one or more nations producing coal and wanting to protect themselves from loss of revenue from constraints imposed on their production. The same can be said for those engaged in nuclear power production. Another set is associated with those in automobile production because of constraints imposed on carbon dioxide emissions and other types of pollution. Here is where Azis analysis is of great value, and should be considered a must in various forms of reading by economists, regional scientists, peace scientists, and conflict analysts. As Azis concludes, ‘‘conflict in various forms is a natural consequence of the power of one party to take actions and decisions that affect others. It can be studied from many different standpoints. In policy conflict, the relative complexity or simplicity depends very much on whose interests are being considered as new measures are debated. Many policy issues are more complex than most people thought. They are simplified for public debate. Some interests are marginalized while others remain central to the discussion. Realizing the inherent trade-offs, knowing what elements of

xv

xvi

PREFACE

debate are present and absent, and what are the causes of the policy structure that we observe, are all central to understanding the representative nature of policy conflicts. This is what the book is all about.’’ Walter Isard Cornell University, May 2009

ACKNOWLEDGMENT This book would not have been in the current form without long discussions, debates, and interactions I had with many of my students, colleagues, and those individuals who are directly and indirectly involved in the events or issues discussed in the book. First of all, many thanks go to scholars, specialists, experts, and reporters, on whose research and arguments the analysis in this book rests. Homo sapiens are a social species; almost all of what we know we learn from each other. ‘‘Aren’t all of us plagiarist,’’ a Nobel laureate friend of the author once jokingly said. The timing of the book writing cannot be more apposite given what is going on in the global economy. When thinking and collecting ideas about what to write in a book about contemporary global issues with the emphasis on policy conflicts, it was not too difficult to find the major issues to cover. For some years the world has been enduring deep imbalances in current account and investment saving, and countries experiencing failures of policy response to a financial crisis have been exploring a closer cooperation among themselves. An oil price surge is equally obvious, and not new, although the latest episode was rather different than the experience in the past. On the longer-term subject, the effect of climate change has also become the talk-of-the-town. All these issues are familiar to most economists; at least they are known by public at large. As economic crisis in the United States continued to unfold, starting with atrocious amount of unpaid mortgage obligations followed by many financial firms entering a stage of paralysis, tons of information came out. As the meltdown lasted longer, new information still came out, and many more to come. This is helpful and exciting, I mean from the book writer’s point of view, but at the same time it has become risky to make any prognosis under such circumstances, although readers will still find some (when this author’s conviction is ‘‘significantly different from zero’’). I feel fortunate to have been able to obtain data and information not only from the secondary sources and published documents but more importantly from those who are right in the middle of the unfolding events, either as policy makers, players, or individuals affected by the crisis. They are everywhere: in the United States, Asia, Europe, and Latin America. I cannot xvii

xviii

ACKNOWLEDGMENT

mention their names one by one, but I am so grateful to all of them. Talking to the right individuals is sometimes better than reading tons of books. Special mention should also be made of my students at Cornell in the ‘‘Economics of Financial Crisis,’’ and ‘‘Macroeconomics and International Trade’’ classes for the intellectual inputs, perspectives, comments, and criticisms they shared. The original inspiration of writing the book came from my years of teaching those courses. Appreciation also goes to all my teaching assistants during those semesters. Most sincere thanks go to Mirko for the quickly available cover design, and those directly involved in turning rough chapters into a polished publication. They all made an incalculable contribution. Finally, I want to thank my wife, Erina, who has steadfastly supported my work, offered comments and criticisms with boundless energy, and who has been full of understanding and patience. In her own way she seems to remind me all the time that writing this book is not a sprint, but a marathon. My debt to her can never be repaid. But for all that, I thank her most of all for Mirko and Mariko, and for our sweet life together.

CHAPTER 1 INTRODUCTION History is typically the story of one party (unit of organization, segment of a society, or person) dominating another, in which the dominance can come in many forms and usually involves conflict at some point. But a conflict can go beyond just clashes between parties; it can include ideological differences between countries, regions, organization, political groups, religions, and ethnicities. Economic opportunities that create greed in party that has them and jealousy in party that does not, can also create a conflict. So can disparity in socio-economic conditions, for example, the rich versus the poor. When the wealthy segment of a society gains from a particular policy, and the poor does not, inequality worsens. It, too, can create conflicts of various types. Although all these are important to recognize, however, it is imperative to understand the process through which a conflict-prone outcome is arrived at. Numerous factors associated with that process may play a key role in generating the outcome as well as in resolving the conflict. In a general and more practical term, conflict can be viewed as a situation where there are differences in perspectives. Under this broader definition, those in conflict can be opinions or viewpoints, or, it can also be goals, objectives, and means (policies) to achieve them. In this context, a conflict may reflect an irreconcilable contention between two or more opinions or objectives. A conflict resolution is essentially an attempt to either reduce the differences, let each party with conflicting opinions feel satisfied, find a common ground, or, allow the conflicting objectives to amalgamate while keeping some or all of the differences. In either case, equilibrium may or may not be reached. In the process, those in conflict can learn one another and benefit from a variety of perspectives about the issues at hand. The diversity of perspectives can generate new changes. When managed wisely, a conflict of opinion or perspective can be a source of opportunity for new ideas and better alternatives. If unmanaged, it can be extremely harmful, creating disorder, crisis, and disharmony. If harmony exists, it does so because virtues prevail, underlining the unity and convergence among those with conflicting ideas. When virtues diminish, the system moves 1

2

IWAN J. AZIS

toward disharmony. We hear a lot about conflicts being arisen from miscommunication and judgment, followed by episodes of accusations, entanglement of the highly charged emotional energies, then a disruption, or even a possible sabotage by those whose opinions and policy ideas are omitted. According to this view, therefore, communication is the logical solution to a conflict, be it at the personal or larger unit level. But there is another type of conflict that has little to do with miscommunication; instead, it emanates from different belief and sense of priority, greed, suspicion, mismanagement, or simply ignorance. When there is a choice between achieving macro stability and reducing poverty, for example, the policy solution depends on the priority set by policy makers on the competing alternatives. When a financial crisis erupts, leading to a multidimensional conflict, greed is often the underlying cause of it. When the price of oil increases, causing energy conflict around the world, it is likely that the source is ignorance over the scarcity of non-renewable resources. Rising poverty driven by lower productivity, mass migration, and water shortage can be the results of climate change; they all can provoke domestic and international conflicts. Those phenomena may also be associated with greed, inappropriate set of priority, and ignorance. These are the kinds of issues discussed in the book. Although it is useful to understand what causes a conflict, it is not necessarily helpful trying to classify its sources, because many of them play a role only in the space of what they mean to us, depending on our values, norms, and status. Thus, things like global imbalances, financial crisis, price instability, rising energy prices, climate change, falling income, and policy mismanagement do not themselves carry a conflict potential; they can become a conflict structure only if they are in our space of what we mean in terms of their repercussions, for example, on instability, poverty, inequality, and other socio-economic insecurity. Countries, people, and policies can be in conflict over a very simple thing, but that simple thing may represent something serious to some parties, because it has a special meaning to them, for example, from disputes over the shape of a table during the negotiations to end the Vietnam War, to conflicting opinions over the level of subsidy needed to improve welfare, and conflicts over whether to consume less now or in the future given the negative externalities affecting future generation. A conflict arises because that special meaning is translated into the protective ‘‘need’’ which subsequently energizes a particular interest as part of the attitudinal lattice connecting the needs to the goals. It is the stimulation of needs that transforms a conflict structure into a conflict situation.1

Introduction

3

Needs may be stimulated by either the truth about some distraught situations (poverty), or propaganda (the magic of market power, causes of climate change, etc.), or indoctrination that imposes a singular perspective or ideology without necessarily involving any propaganda (capitalist’s exploitation of labor). Needs for security can be applicable to many aspects of life, some are more prominent than others in energizing the interest that leads to a conflict.2 Insecurity caused by higher inflation and fluctuating exchange rate may be considered less significant than insecurity due to lower spending power, higher health risks associated with air pollution, and deeper poverty. Either way, they can generate a profound conflict manifested through mass protest, strikes, riots, etc. Although the book discusses various types of conflicts, the main focus is on policy conflicts and the process by which a conflict-prone outcome is generated. More specifically, it emphasizes on alternative measures that may come out of policy conflict incited by either mismanagement, greed, misguided priority, or ignorance. The book is not about finding ‘‘the’’ best solution, but more about looking into the nature and mechanisms of policy conflicts through which alternative solutions are explored. By so doing, it is expected that courses of actions can be compared and evaluated. For that purpose, one needs to think hard in digging out alternative measures that may be different from standard prescriptions. It also forces us to come to terms with the new problems and challenges. Some of the proposed measures will not and cannot produce the intended outcomes in all fronts. A policy measure may be effective to overcome an overheating economy caused by excesses, but it may result in more people out of job and income to fall. A preferred policy to mitigate climate change may require scarce resources which otherwise can be devoted to tackling other problems that need to be urgently addressed in many developing countries, such as poverty and other socio-economic challenges. A policy response to macroeconomic imbalances may contradict with the long-term objective of reducing the imbalances. Allowing financial market to grow with little regulation may be good for growth, but also poses a risk of a meltdown and economy-wide crisis. The analysis of these factors involves trade-offs and policy conflicts. Although the selection, nature, and importance of target variables are largely the jurisdiction of politicians, essentially normative, some general principles remain warranted. Such principles should be established based on the specific conditions of the areas or countries under study. When macro stability is confronted with poverty reduction, the earlier may receive a greater weight in industrial countries, whereas reducing poverty likely

4

IWAN J. AZIS

dominates problems faced by developing countries. To the extent that imbalances or crisis can be caused by (the lack of) regulation, the solution may involve more regulations. When policy response from several countries is needed, it is only natural to think of cooperation among them. Such cooperation is complex, needs to be done in stages. It is argued in the book that in searching for a particular form of regional cooperation, like in most conflict situations, policies must be predicated not on an ideal world but on the world as it is. For that, one needs to do prioritizing. Too often many factors are treated as important, yet not all of them are mutually supporting. The specific issues of policy conflicts discussed in the book range from global imbalances that played an important role in the 2007/2008 crisis (Chapter 2), the episode of subprime and financial crisis that led to worldwide recession (Chapter 3), regional financial cooperation as a response to failed policies during a crisis (Chapter 4), oil price shock and its repercussions on socio-economic conditions (Chapter 5), and possible trade-offs in mitigating externalities caused by climate change (Chapter 6). Interactions among different systems, unregulated market (regulatory neglect), excesses in growth and its socio-economic effects, and growing scarcity, are among the components to be discussed. These factors reflect problems that require clear policy responses.

NOTES 1. The observed interests are vectors of power toward achieving a specific goal; they may be determined by the culture and society’s value system. 2. Note that in some cases people do not only want security and status for themselves but also for helping others. That is, human being’s esteem is not always wholly selfish.

CHAPTER 2 GLOBAL IMBALANCES INTRODUCTION A news report from South Africa reads, ‘‘Clothing and Textile Workers’ Union (SACTWU) members held a string several meter long with 40,000 pieces of fabric attached to display their agitation over cheap Chinese imports which has claimed thousands of jobs loss. Due to cheap Chinese imports over 67,000 jobs had been lost and more than 350,000 people have been suffering who were engaged in clothing, footwear and textile sectors.’’ A saver in Southeast Asia once complained, ‘‘When I opened up my dollar savings account about 3 years ago, I bought a sizable amount of the green bucks at Philippine peso 56.40. Today, the peso–dollar exchange rate stands at Philippine peso 43.27. That’s a net loss of Php13.13 for every dollar that I have in the bank. That loss closely amounts to a brand new car or a down payment for a house and lot. And I thought going with a dollar savings was the best fiscal move I made in years.’’ Other savers in many countries are also affected since their local currencies have become much stronger against the U.S. green bucks. In Latin America, the dollar trouble in Portuguese-speaking Brazil and other countries in the region have been apparent too. Most Latin American economies are tied closely to the dollar, either officially or in practice. Hotel prices have barely budged over the past few years. Once on the ground, U.S. travelers will find their dollars going a long way, whether in Argentina, Peru, Costa Rica, or Mexico. The effect in Europe was equally grim. In 2003, Daimler reported that the second-quarter revenues of EUR34.3 billion from selling vehicles worldwide were lower than in the previous year (EUR39.3 billion), as a result of the appreciation of the euro against the dollar. Weakening dollar has indeed serious ramifications for many countries around the world. It has been at the center stage of a phenomenon called global imbalances, a prominent feature of which is the large and widening

5

6

IWAN J. AZIS

current account deficit in the world’s largest and most powerful economy, the United States, and the growing surplus in emerging markets particularly in East Asia (Fig. 1). Reaching at an annual rate of more than $800 billion, or over 7 percent of GDP, the U.S. current account deficit was far beyond the ‘‘dangerous threshold’’ of 4–5 percent. More dramatically was the fact that this deficit represented around 70 percent of the global current account deficits! On the surplus side, almost half of the global surpluses were generated in East Asia. No wonder a large portion of the U.S. deficit had been financed by ‘‘borrowing’’ from this region. This suggests that any meaningful efforts to resolve the global imbalances must effectively deal with the imbalances between these two economies. The surge of oil price also made oil-exporting countries to become a major player on the scene. With the doubling of their surplus within a

Fig. 1. Current Account Balances (Percentage of GDP). Notes: ANIE ¼ Asian Newly Industrializing Economies; ASEAN-4 consists of Thailand, Malaysia, the Philippines, and Indonesia. An Alternative Chart to Demonstrate the Imbalances Would be One that Shows the Ratio of Each Country’s Deficit to World GDP; The Resulting Paths, However, are Similar with the One Shown Above. Source: Author’s Calculation Based on WEO Database, September 2006.

Global Imbalances

7

three-year span, they became important counterparts to the U.S. current account deficit. As shown in Fig. 2, the current account surplus of oil producing countries represented about 40 percent of U.S. deficit in 2005. This made recycling oil revenues imperative in any attempts to resolve the imbalances. The current account deficit is also affected by the U.S. net international investment position (‘‘valuation effect’’). The latter is important to consider in an open system where inflows and outflows of capital are significant in size. Consider the case in 2002–2004, during which the Fed’s major currencies trade-weighted exchange rate index depreciated by nearly 27 percent. Associated with the current account deficits during this period were financial flows into the United States totaling $1.6 trillion. However, because foreign claims on U.S. assets were denominated in dollars to a far greater extent than United States claims on foreign assets, the depreciation increased the dollar value of U.S. assets abroad relative to foreign assets in the United States. The total valuation impact stemming from exchange rate changes was $919.0 billion, or 57 percent of the net financial flows. During that period, the U.S. net international investment position decreased by $202.8 billion. Absent the exchange rate adjustment, the position would have decreased by more than $1.1 trillion.

Fig. 2. U.S. Deficit (Inverted Sign) and Oil Producers Surplus of Current Account. Source: Processed from IMF Balance of Payment Statistics (Various Years).

8

IWAN J. AZIS

The other side of the ‘‘two-gap’’ coin is the investment-saving imbalance. As depicted in Figs. 3 and 4, not only the current account in industrial countries showed a widening deficit and in the emerging market and oilproducing economies an increasing surplus, but the investment-saving gap was also in a similar position: deficit in the former, surplus in the latter (China’s investment was the primary reason that investment share in Fig. 4 fell into the positive territory). Notice that this imbalance began to emerge particularly after the Asian Financial Crisis (AFC) in 1997, subsequently followed by a series of crisis in other countries including Russia and Argentina (Azis, 2005a, 2005b). It is argued in this chapter that the global imbalances could create several types of conflict, ranging from trade disputes, conflicts between multinationals and domestic companies, and internal conflicts sparked by contradictory interpretations of law within a country. It is also argued that unattended imbalances could cause abrupt adjustments that would spark a worldwide recession. Indeed, the origin of the 2007/2008 financial crisis and the global recession were closely linked with these imbalances. Since the size and composition of the imbalances had been unprecedented, and the trajectory was unsustainable, it is imperative to explore policy measures that could mitigate the imbalances.1 It is shown that the process of selecting the appropriate policy response involves severe trade-offs or

Fig. 3.

Current Account Balance, Saving and Investment: Industrial Countries. Source: Rajan (2005).

Global Imbalances

Fig. 4.

9

Current Account Balance, Saving and Investment: Emerging Markets and Oil Producing Economies. Source: Rajan (2005).

conflicts between different targets at different times, although the overall objective remains the same, that is, reduce the global imbalances. More specifically, it is shown that the policy response which may seem appropriate in the short run can instead exacerbate the problems, because it contradicts with the long-term objective of reducing the imbalances. Before discussing the policy measures, it is important to understand the origin of the global imbalances and the nature of possible conflicts that may arise.

ORIGIN OF IMBALANCES AND POTENTIAL CONFLICTS The episodes of financial crisis in many countries around the world during the 1990s, and the resulting information technology (IT) bubble, had a lot to do with the origin of global imbalances. On the one hand, the upbeat mood that caused over-investment during the pre-crisis period turned into super cautious attitudes among governments and investors that led to a falling investment in emerging markets. On the other hand, accommodative fiscal and monetary policies in industrial countries led to over consumption and credit boom, including housing market boom. To the extent that this had

10

IWAN J. AZIS

widened their fiscal deficit and reduced savings – especially household savings – they suffered from a classic dual-gap problem (investment-saving gap and trade gap). In the emerging markets, the opposite predicament stood out, that is, excess current account surplus and under-investment. Why did the Fed adopt accommodative monetary and fiscal policies at the first place? The end of the cold war followed by a growing number of countries embracing market system (e.g., Eastern Europe and China) along with trade and financial liberalization in emerging economies (e.g., East Asia, Latin America), provided arbitrage opportunity for the corporate sector to shift a big chunk of their production to these lower-cost economies. At the same time, fiscal consolidation and economic reforms including those promulgated in countries with a long history of excessive budget deficit such as Latin America had allowed budget deficits to decline. All these contributed to a reduction in the world’s inflation rates, and provided a room for accommodative monetary and fiscal policies. The dynamics of the process, however, was far more complex. Economic reforms and liberalization made the economies of many emerging market more flexible, but at the same time their asset markets were also more susceptible to a shock. The Asian Financial Crisis was the turning point. A too open system with insufficient supervision and weak institutions collapsed. As a result, asset prices fell, prompting the fear of a deflationary pressure. The accommodative policy by the Fed was partly influenced by such a fear. The subsequent tech burst in 2000 added to the deflationary fear. The accommodative policy continued when looming Iraq war exerted further deflationary pressure. There was also a problem related to a low domestic supply elasticity of demand. The Fed’s accommodative policy caused not only excessive spending that prompted investment-saving deficit, but also raised imports, particularly imports from China and India, exacerbating the U.S. current account deficit. Flushed with financial resources flowing from the United States and other industrial countries, China and India were able to raise investment to stimulate stronger economic growth. Thus, the Fed’s accommodative policy contributed not only to the U.S. growth but also to the economic expansion in China and India. Of all the explanations on the causes of the oil price surge that began in 2004 (discussed in Chapter 5), strong demand spurred by robust growth in these countries was the most compelling one.2 In turn, the oil revenue of the major oil-exporting economies reached more than doubled in a short span of time, that is, from US$262 billion in 2002 to an estimated US$614 billion in 2005. This aggravated the global imbalances.

11

Global Imbalances

With large and widening U.S. current account deficit, the financial market bet against the dollar. This was translated into market expectations for currency appreciation in some Asian economies, particularly in China. With such expectations, capital inflows surged, allowing China to accumulate a huge amount of foreign reserves. As shown in Table 1, by April 2006, for the first time China’s reserve (US$895 billion) surpassed that of Japan (US$841 billion). Traditionally, Asian central banks assumed the risk on the dollar value and pumped the money into the U.S. bond market. But with rising expectation of weaker dollar, and continued increase of reserve beyond liquidity needs, diversification was inevitable. Return considerations may become more important. One strong indication pointing to this direction was the emergence of active government-controlled investment companies in many East Asian countries.3 The main task of these companies is to manage a portion of official foreign reserves (to adjust the portfolio composition) to mitigate the rising costs of holding a huge amount of reserve.

Table 1. Country (ranking)

1 2 3 4 5 7 8 9 10 11 12 13 14 15

China Japan Taiwan (Province of China) Korea Russia India Hong Kong SAR Singapore Mexico Malaysia Algeria Turkey Brazil Thailand

World Source: IMF (2006).

Net International Reserves (US$ billions). 1997

2001

2003

2004

2005

April 2006

Percent of Reserves to GDP

Annual imports

141 209 84

213 389 123

404 654 207

611 826 243

820 830 254

895 841 260

37 18 73

124 161 139

20 14 25 93 71 28 20 8 19 51 26

103 33 46 111 75 44 29 18 19 36 33

155 74 98 118 95 58 43 33 34 49 41

198 122 126 124 112 63 65 43 36 53 49

210 176 132 124 115 73 69 57 50 54 51

223 219 154 127 127 78 75 66 60 56 56

27 23 17 70 98 10 53 55 14 7 30

80 128 98 42 59 33 61 282 51 69 43

1,687

2,334

3,330

4,081

4,698

4,941

–

–

12

IWAN J. AZIS

Most western observers and policy makers believed that currency revaluation in Asia could have solved the global imbalances. But the emerging markets of Asia flatly rejected such a notion. They instead believed that reducing U.S. fiscal deficit was far more important. A conflict of opinion thus emerged. Members of the U.S. Congress had been quick to put the blame on China’s manipulation of the Yuan. They claimed that China did not play by the rule of the game. Although at the beginning this might not necessarily reflect the U.S. administration view, it certainly echoed a widespread sentiment among the American public. European countries also maintained that China obtained unfair trade advantages that led to the rise of the bilateral trade imbalance. Facing a financial crisis comparable to the 1930s depression, the U.S. administration escalated the accusation. In his testimony before the U.S. Senate as part of hearing for his confirmation as the new Treasury secretary, in January 2009 Timothy Geithner said, ‘‘President Obama, backed by the conclusions of a broad range of economists, believes that China is manipulating its currency . . . ’’ This was a very serious allegation. Conducting a currency manipulation means a political decision translated into monetary policies that can cause the currency to move (depreciate) to boost exports. If this is true, it will have international consequences, and the relations between countries can go sour because of it. What rules that China was blamed for not abiding to? Who made such rules? Matters related to trade are within the World Trade Organization (WTO) realm, whereas policies influencing the exchange rate are under the IMF domain. The problem is, for so long the board of the IMF has been dominated by the Western countries. When Japan was at the center of the bilateral imbalances with the United States and Europe in 1970s and 1980s, rules were made to prevent Japan from manipulating their currency. As a result, in the 1984 Plaza Accord they ‘‘forced’’ Japan to appreciate its currency. The Yen appreciated sharply since then (Yendaka), causing a lot of problems for an economy that relies heavily on exports. Although this was not the main reason that caused the Japanese recession in the 1990s, it had some contributions to the malaise. As the bilateral imbalances between China and the United States and Europe have grown rapidly during the past several years, a similar pressure is now put on China. International trade relations are fine until one of the participating countries accumulates a large surplus. Unlike Japan, however, China has taken a firmer stand by refusing to give in to the pressure. They allowed Yuan to appreciate, albeit modestly, since mid-2005. In fact, given the U.S. inflation, in real terms the Yuan value in 2008 remained more or

Global Imbalances

13

less the same. For an export-reliant economy that still depends largely on the United States and the European market (despite the growing share of the Asian market in China’s trade), and with strong domestic interest coalition, it is not realistic to expect that China will act like Japan in the 1980s, although too much managed rate is ill-suited to a market-based exchange rate system favored by most of China’s trading partners. The mantra of market-based exchange rate itself is in fact still debatable. Economists are not always in agreement as to what exchange rate regime to adopt. The appropriateness of a particular regime depends on each country’s conditions. Even if the global trend has shown that increasingly there are more floaters than fixers, it remains to be determined what is really defined as floating exchange rate, because in reality the IMF supports the efforts made by industrial countries to coordinate their monetary and fiscal policies that can ‘‘manipulate’’ the exchange rate in the interest of global financial stability. At least the fund does not place any obligations on those countries when they conduct such efforts. The arising trade conflict is not new. The world has witnessed several trade wars before, and it is not impossible that they recur especially with the faltered multilateral trading agreement (the Doha Round). If the global imbalances get worse, the probability of their recurrence is bigger. Given the fact that many countries have opted for regional trading arrangements as a reaction to the failure of the WTO agreement, the nature of the new conflict may be different, but it is still a serious conflict in that it can incite more protection and global recession. What has really happened is that, the rise of China has made the macroeconomic coordination among industrial countries of the West more difficult. This fact alone could have created a trade conflict and rising protectionist demand in the industrial countries. The problems are even more serious considering the fact that a rising China has posed a critical and more difficult challenge to the United States than that posed by the Soviet Union during the Cold War. This will lead to a profound change in the United States and Asia’s strategic environment. The global imbalances have also caused a conflict of interest between the domestic-oriented corporate sector in United States and Europe and their multinational companies operating in emerging Asian markets like China. Although the latter strongly favors a strong and good relation with Asia and China since they profit from such a relation, the domestic companies want the U.S. administration to press hard on China to revamp the exchange rate system with the hope that the imported goods from that country will no longer pose a competitive threat to their products.

14

IWAN J. AZIS

Global imbalances also create an internal conflict within the surplus countries that may spark the debate about the preferred currency value. The fact that some countries prefer to have a weaker value of its currency has a lot to do with the currency mismatch, which itself poses a problem of risk management for the creditor countries. Thus, running surpluses in the current account and using foreign reserves to ‘‘lend’’ to foreigners, Asian countries tend to keep the lending (foreign claims) denominated largely in dollars. When the value of this foreign lending became large (at the time of the writing the size of China’s foreign reserves was recorded at more than $1.8 trillion), the last thing these countries wanted was an appreciation of its currency. Thus, as the United States continues to argue about the unfair treatment of the Yuan, and threatens a trade sanction, China faces an internal conflict herself, known as the syndrome of conflicted virtue, a term coined by McKinnon and Schnabl (2004) and McKinnon (2005). An appreciation of local currency in net-creditor countries is also feared by corporate sector and banks whose balance sheets reflect a currency mismatch, that is, foreign currency governs the asset and local currency dominates the liability. Japan is a notable example. Foreign currency assets in Japan can earn higher yields than what the local currency assets can offer because the country has suffered from a liquidity trap. Consequently, Japanese banks and insurance companies prefer to have foreign currency-denominated assets in their balance sheets. But this is precisely the reason why their portfolio equilibrium is precarious. An appreciation of the Yen will surely worsen their balance sheet position. Like in the case of China, therefore, the syndrome of conflicted virtue among Japanese financial sector abound. There is also a conflict related to the domestic legal and sovereignty matter arising out of the growing global imbalances. For example, there is a tendency in the United States to question whether having joined an international treaty through organization such as the WTO will detract from the democratic legitimacy of the laws that govern the U.S. domestic interest. Such questioning arises out of the fact that the WTO, for example, its tribunals, is a nondemocratic institution. When U.S. industries complain that the flood of imported goods is due to an unfair trade practice, be it through tariff and nontariff barriers or through an exchange rate manipulation, but the WTO confirms that no rules have been violated, tension can still arise. The issue becomes far more complex because it makes a way into the internal debate about the relation between international laws and domestic laws. There seems to be two opposing views in this respect. One argues that in the age of modern liberal democracy, law derives its legitimacy from being enacted by elected representatives of the people. Like

Global Imbalances

15

the Constitution, law is designed to create domestic order. If a significant increase of imports is interpreted as endangering the economic stability, hence the domestic order, there is a legitimate legal argument to do something about it.4 This inward oriented interpretation is the opposite of a more liberal view. The latter tends to believe that law is conceived as a global ideal, not as a national phenomenon. Thus, the U.S. law should be pictured alongside international law (external-oriented), implying that the provision of rights should be applied universally, not just for U.S. citizens. These two opposing schools of thought carry a very different implication in terms of the policy response to trade imbalances. Although the inwardoriented school is more inclined to take a unilateral reaction to the global imbalances, the outward-oriented school favors a compliance with the WTO rules.

SUSTAINABILITY AND IMPLICATIONS If the growing imbalances have the potential to bring down an economy and create so many conflicts, one wonders why there was no serious and coherent effort to mitigate the imbalances. The 2007/2008 global financial crisis can make things worse as it likely takes away the attention from resolving the imbalances, although the natural reaction to the meltdown may, however, help reduce the imbalances (e.g., Americans tend to save more). The policy response to the crisis can also directly affect the size of the imbalances. Looking at just the size alone, it is hard to imagine that the current imbalances can be sustainable. A scenario of the United States borrowing billions of dollar per day from foreign investors to finance the current account deficit plus its own outward foreign investment cannot, by any stretch of imagination, be maintained both economically and politically. It is also inconceivable that some 80 percent of all foreign investment by the rest of the world will continue to move into dollar assets. Even before the current financial turmoil hit the U.S. economy, some analysts had argued that a continued widening of current account deficit would raise the U.S. debt to a point that could not be sustainable and caused investors to lose confidence in the economy’s ability to service its debt. Once this happens, interest rates must rise or the borrowing country’s currency must depreciate to enable the country to continue financing its deficit. Although the implied risks are indeed real, however, the likelihood that the impact is directly applicable in the near terms is small, given the low interest rate policy needed to stimulate the economy following the 2007/2008

16

IWAN J. AZIS

meltdown. Also, the U.S. net international debt measured as a percentage of GDP was, at least until the crisis began, still relatively low, that is, 13 percent compared to 15 percent in United Kingdom, 36 percent in Canada, and 59 percent in Australia. Before 2008, these countries were not in any danger of collapse. Although relying too much on foreign investors to finance the current account deficit cannot and should not be sustained, it is hard to conceive that frictions or conflicts between countries will not escalate if trade imbalances continue to grow.5 Indeed, forces that can make the imbalances unsustainable may not necessarily come from the economic front; the political force often can be more powerful. What will happen if the imbalances continue uncorrected? Even without the 2007/2008 financial crisis, a wide sell-off of U.S. currency can throw the world financial system into a damaging disorder that will eventually lead to a global recession. The ballooning U.S. current account deficit will bring down sharply the value of U.S. dollar that can spark massive capital outflows and lead to rising interest rates. In turn, output will fall. Falling output and rising inflation create a classic dilemma to the monetary authority: spurring growth through lower interest rates stokes a flare-up in prices, putting the Fed’s two goals – price stability and economic growth – in conflict. More importantly, falling output in the United States and other industrial countries can pose serious problems to the rest of the world, as the 2007/2008 crisis has shown. No one is spared. The good news is, such a drastic and nonorderly process will eventually correct the imbalances. The bad news, the costs of adjustments can be enormous, and it will take a long time for the resulting global recession to recover. A number of scenarios can be constructed, ranging from a very soft landing, whereby the declines in the U.S. dollar value and investor confidence take place in an orderly fashion, to a scenario of not-so soft landing where the U.S. interest rates will increase significantly and a considerable amount of U.S. assets sales has to take place. Each scenario implies the need for a certain set of policies. Like in many other cases, a combination of policies may have the most desirable consequences in terms of achieving multiple goals: reducing the imbalances, minimizing risks of abrupt adjustments, and maintaining the global economic growth. With a proper policy combination the probability for each individual region/country to get better is higher. Increased consumption will occur in Asia (due to a more favorable terms-of-trade), euro area, and Japan (due to higher productivity), and private and public savings will recover in the United States, allowing further fall in the interest rates. Still, some risks remain impending: if structural adjustment in the euro area and Japan worsens investors’

17

Global Imbalances

confidence, the global growth can be weaker than expected, and the required exchange rate adjustment may have to be very large. This is the reason why it is often suggested that policymakers together with private sector need to ensure that national economies and financial and nonfinancial corporations are resilient in the face of potential changes (see IMF, 2005). It is unclear which scenario is more feasible economically and politically. But one thing is clear: adjustments need to be made by all countries to avoid a ‘‘prisoner’s dilemma’’ situation. Each agent must be involved in the process. Government or private sector alone cannot resolve the problem. Even global institutions (the World Bank, the IMF, WTO, or Regional Development Banks) cannot effectively manage the current global imbalances without full participation and commitment from all member countries.6 This is not too encouraging. It is hard enough to find a consensus in each country as to what strategy to implement and what policies to use, let alone managing the imbalances through global institutions. Even if a consensus is reached, there is no guarantee that the market will react according to what is intended by the policy. Domestic political interventions may further complicate the tasks, and there is also a risk that individual countries conduct their policies without regards to global imbalances. They may be aware of the problem, but they either expect others will make the first move or assume that corrective measures taken by others will be sufficient (free rider). Managing the imbalances is not easy. Many policy measures have been recommended, although not all are based on a sound and consistent analytical framework that can capture the interactions among relevant variables. More importantly, many analyses tend to focus on a short-term solution, neglecting the dynamics of some variables of interest, for example, exchange rate, current account deficit, size of debt, and interest payment. Yet, understanding the dynamic trajectory of these variables is important to ensure the sustainability of the policy outcome.

POLICY CONFLICTS Some policy responses needed to mitigate the global imbalances is discussed in this section by taking into account the dynamics of all relevant variables and using a more realistic specification (imperfect substitutability between domestic and foreign assets). It should be clear from the discussions later that the policy conflict appeared in the attempts to resolve the global imbalances is quite profound.

18

IWAN J. AZIS

First, in looking at the trend and long-run equilibrium of current account deficit and exchange rate, one has to realize that debt position matters. The interest payment on debt affects the size of current account deficit, and hence the extent of exchange rate depreciation. If U.S. net debt increases, the value of the U.S. dollar tends to depreciate more than what is required by the increase in trade deficit, because larger holding of U.S. assets by foreign investors also means larger interest payment in the future. In a standard balance-of-payment framework, future debt position (Dtþ1) is determined by the current debt (D) and the interest rate (i) plus the trade deficit (TB). The latter is influenced by the exchange rate (e) and the shift parameter (m), for example, rising imports due to greater preference for foreign goods. Thus, Dtþ1 ¼ ð1 þ iÞ D þ TBðetþ1 ; mtþ1 Þ Since U.S. gross liability is largely denominated in U.S. dollar, future debt position is also influenced by what happens with the value of assets (assets revaluation). If the U.S. dollar depreciates, the dollar value of U.S. holding of foreign assets will increase, and the U.S. net debt position will decrease through improved trade balance and asset revaluation.7 Both effects will influence the U.S.’ future debt position. What happens with the equilibrium in the current account? Denote W as the wealth of U.S. investors, W* is foreign wealth, EXP(R) is the expected rate of return, d is the share of U.S. assets to which U.S. investors allocate their wealth; thus, (1d) is a share allocated to foreign assets, and i is the interest rate. If foreign investors invest a share (d*) of their wealth W* in foreign assets and a share (1d*) in U.S. assets. Following Blanchard, Francesco, and Filipasa (2005) the U.S.’ future net debt position can be written: W* ð1 þ iÞ þ TBðetþ1 ; mtþ1 Þ e e  ½1  dðEXPðRÞ; pWð1 þ i*Þ etþ1

Dtþ1 ¼ ½1  d ðEXPðRÞ; pÞ

where the last term represents the valuation effect, and p denotes a shift variable capturing all the factors that can shift portfolio shares for a given relative return. An increase in p leads to U.S. and foreign investors’ decisions to increase the share of U.S. assets in their portfolio. Thus, the preceding equation implies that net debt in the next period equals to the value of U.S. assets held by foreign investors next period, plus

Global Imbalances

19

the trade deficit next period, minus the value of foreign assets held by U.S. investors next period. Note that the value of U.S. assets held by foreign investors next period equals to this period’s wealth in terms of U.S. goods, times the share of U.S. assets they are holding, times the gross rate of return on U.S. assets. Meanwhile, the value of foreign assets held by U.S. investors next period equals to this period’s U.S. wealth times the share they invest in foreign assets times the rate of return on foreign assets in terms of U.S. goods. Also important to note is, D, d*, and d are not independent. Thus, Dtþ1 can be expressed in terms of any two of the three. The above equation can be rewritten (see Blanchard et al., 2005): Dtþ1 ¼ ð1 þ iÞD þ TBðetþ1 ; mtþ1 Þ     1 þ i* e ðS  DÞ þ ð1  dðEXPðRÞ; pÞð1 þ iÞ 1  1 þ i etþ1

ð1Þ

which is the ‘‘current account balance relation.’’ Thus, the larger the U.S. net debt, the greater the probability that there will be a shift of demand away from U.S. asset (home bias), and the larger the trade surplus required for interest payment. Eventually this will cause the U.S. dollar to depreciate. Next is the equilibrium in assets market. Total supply of U.S. assets (S) equals to total demand of U.S. assets by both U.S. investors and foreigners. That is,   W* S ¼ d½EXPðRÞ; pW þ ½1  d*ðEXPðRÞ; pÞ e Since by definition W ¼ SD, and similarly W*/e ¼ (S*/e)þD, we can write    S* þD (2) S ¼ d½EXPðRÞ; p W þ ½1  d*ðEXPðRÞ; pÞ e which is the ‘‘portfolio balance relation.’’ In an extreme case of no substitution between U.S. assets and foreign assets, d and d* are independent of the rate of return R, in which case the equilibrium exchange rate is determined solely by the world distribution of wealth or the portfolio preferences, not by the current account balance (deficit). According to the specification of the model, when foreign demand for U.S. assets increases, the U.S. dollar will initially appreciate, and imports will rise. This will cause a rapid increase of current account deficit. But

20

IWAN J. AZIS

because of higher future interest payment, the U.S. dollar will eventually depreciate, slowly but steadily. Indeed, this is what has happened since mid1990s. The reason the model is capable of capturing these facts, unlike in the standard uncovered interest parity (UIP) model, is because it does not assume a perfect substitution between U.S. assets and foreign assets. The lower the degree of substitutability, the higher the anticipated interest payment as a result of an increase in foreign demand for U.S. assets. In turn, this will generate a larger expected depreciation. It is clear from Eqs. (1) and (2) that the lines relating net debt position D and the exchange rate r have a negative slope (see Fig. 5). More precisely de=e d þ d*  1 ¼ o0 dD ð1  d*ÞS*=e Take the case of accommodative policy by the Fed, along with loosened fiscal policy. This combined policy measure raised demand, including e

Portfolio Locus

A B

Current Account Balance Locus

C

D

Fig. 5. Effect of Rising Imports.

21

Global Imbalances

housing demand that caused a housing market boom. But with low domestic supply elasticity, import demand (especially from China) also increased. In Eq. (1), this is captured by an increase in m. Based on this equation, for any given D the current account balance locus will shift downward as depicted in Fig. 5. The steady state equilibrium moves to C through the following mechanisms. The shift in trade deficit due to higher m is shown by the movement from A to B. Initially, this has caused an unexpected depreciation of U.S. dollar. As debt accumulates, further depreciation is inevitable (the shift from B to C). Meanwhile, the current account deficit worsens due to rising m.8 If the shift is not in the goods (imports) market, instead in the asset market, the portfolio balance will play an important role. As evidenced during the 1990s, there has been a shift reflecting high preferences toward U.S. assets (the term p in Eq. (2) moves upward).9 This is captured by a rightward shift of portfolio balance relation as shown in Fig. 6. At a given debt position D, the portfolio balance requires an appreciated exchange rate. Initially, U.S. dollar will appreciate (the shift from A to B), but as this hurts competitiveness, the current account deficit tends to increase, and the U.S. dollar depreciates (from B to C). e

Portfolio Locus

B

Current Account Balance Locus A

C

D

Fig. 6.

Effect of Higher Preference Towards U.S. Assets.

22

IWAN J. AZIS

What really happened since the mid-1990s was that, both m and p shifted upward. An initial pressure of combined depreciation (from rising m) and appreciation (from rising p) has led to a smaller-than-expected depreciation of U.S. dollar. But with the anticipated larger interest payment due to rising debt, the expected depreciation is large. Also, the relatively small elasticity of domestic supply to demand and the low degree of substitutability between U.S. assets and foreign assets have caused the current account deficit to increase fast. This is the reason why the actual U.S. deficit has widened rapidly despite a not too fast depreciation during the period. The scenario captured in Fig. 6 is similar to a case whereby the Fed raises the interest rate, a policy often recommended by analysts to resolve the current global imbalances. The problem with such a policy is that, it overlooks the resulting increase in net debt position that will cause the expected exchange rate to depreciate further. To generate an adjustment process that is more orderly, it is better if the Fed reduces the interest rate. The initial depreciation caused by such a policy is mitigated by improved competitiveness and lower net debt position. The potential overheated economy should be countered by lowering fiscal deficit. Such a policy mix could help reduce the U.S. current account deficit – an important step in resolving the global imbalances – without causing disorderly adjustment in the exchange rate. The problem is, given the deep financial crisis and recession in 2007/2008 (discussed in the next chapter), lowering fiscal deficit is no longer a likely scenario. Thus, a new and more difficult-to-resolve policy conflict has to be faced by policy makers. To repeat the obvious, however, a real resolution to global imbalances cannot be reached even by such a unilateral policy measure. Unless the surplus countries also take action, it is unlikely that a scenario of orderly adjustment can come about. Some even doubted that an international organization such as the IMF would be effective and sufficient enough to deal with the problem. Ideas had been floated to utilize the G20 which includes both developed and emerging nations. Still, a policy measure taken by the United States holds a critical role in the overall efforts, simply because of the size of its economy and that it holds the largest portion of the global current account deficit.

NOTES 1. For a good summary of the historical perspectives of global imbalances, see Bordo (2005).

Global Imbalances

23

2. Unlike the oil price increases in 1970s and early 1980s that were preceded by wars (pure supply shocks), this time the rising oil price was prompted by an extraordinary strong demand, although concerns over future supply related to the Middle East crisis may have a role too. At any rate, this partly explains why the current oil price increase is not followed by a worldwide recession. 3. Noted examples are: Singapore’s Government Investment Corporation (GIC), Korea Investment Corporation (KIC), and Malaysia’s Khazanah Nasional. Capital outflows have been also encouraged, either through national pension fund, for example, Korea’s Pension Fund Association, Thailand’s Pension Fund, Japan’s Government Pension Investment Fund, or through individual investment, for example, the 1990s liberalization in Japan, the increased limit of foreign assets holding allowed by the Malaysian government, China’s provision of greater access to individual savers to foreign assets (announced on April 2006). 4. In a more extreme way, any interpretation of the laws and Constitution that restricts U.S.’ security or sovereignty is considered perilous (e.g., extending constitutional rights to noncitizens encountered on battlefields overseas). 5. Imagine what happens in Capitol Hill if a growing trade imbalance occurs when the U.S. economic growth is weaker as expected to happen in the next few years. 6. With its limited leverage, however, questions arise as to how the Fund can help steer the big players toward politically painful but necessary steps to reduce the imbalances without triggering a recession. 7. The opposite applies to emerging market where the gross liabilities are mostly denominated in foreign currency. De Gregorio (2005) argued that the valuation effect is less important from a longer-term view (the exchange rate adjustment operates mainly through the traditional trade effect). Only in the short run, and particularly from the point of view of emerging economies, that the valuation effect could play a far more important role. Short-term movements in capital flows could be partially offset by changes in valuation because emerging economies cannot borrow in their own currencies. When the domestic currency depreciates, the return on liabilities increases in terms of local goods, and the burden of liabilities rises. This is precisely the opposite of what happens in industrialized countries, that is, valuation effect helps the external adjustment. 8. At a lower degree of substitutability, however, the size of depreciation is smaller although future anticipated depreciation can be large. 9. The growing preferences toward U.S. assets is one of the anomalies actually observed during the recent years. The other anomalies are: the sustained rise in the U.S. current account deficit and the decline in long run real rates. According to Caballero, Farhi, and Gourinchas (2006), these anomalies can be rationalized and are actually an equilibrium outcome of two phenomena, that is, potential growth differentials among countries, and heterogeneity in countries’ capacity to generate financial assets from real investments.

This page intentionally left blank

CHAPTER 3 FINANCIAL CRISIS INTRODUCTION A comment by an analyst-cum-investor reads, ‘‘A year ago, I didn’t expect the U.S. economy to fall into recession in 2008 because I was confident consumers would continue to do what they do so well: spend money. I had plenty of company, and ultimately we were all wrong.’’ During the Fall of 2007, while working in Tokyo to prepare a manuscript for publication, I wrote, ‘‘I come to a rather disturbing prognosis about the U.S economy: high likelihood of a recession’’ (Azis, 2008). Indeed, it is always tricky to predict crisis and recession, let alone to comprehend how a small segment of a financial market, that is, subprime credit, could bring down the world’s largest economy into the worst recession since World War II. Every Spring semester on the first day of my class on ‘‘Economics of Financial Crisis,’’ I always cautioned students that financial crisis is explainable but not predictable. In December 2007, the then President George Bush continued to argue that the U.S. economic fundamentals were strong despite the banking crisis and Wall Street meltdown. Most people also thought that the U.S. house of card was unlikely to fall. But something unusual does not mean unlikely to happen. As British novelist Wodehouse remarked, ‘‘never confuse the unusual with the impossible.’’ By the Fall of 2008, the impossible set in. Economic numbers in the United States began to terrify the market. Banks did not lend, businesses and consumers were not spending, and manufacturing plunged everywhere, a situation close to what happened at the beginning of the Great Depression. The U.S. financial market, world-known for its size and strength, was destroyed, production across all sectors fell precipitously, and the labor market flashed a deepest recession in decades. The bulk of the discussion in the current chapter is devoted to the meltdown of the U.S. economy following a financial crisis that began in the summer of 2007 (hereafter 2007/2008 crisis). The discussion links the meltdown with some policy trade-offs and other conflicts that emerged 25

26

IWAN J. AZIS

following the crisis. When looking for a resolution to a crisis, policy conflicts can be severe, for example, measures to avert further declines in output are likely to be detrimental to the value of currency and inflation rate, bailing out troubled financial institutions may lead to a serious conflict of interest since it will mean handing in financial resources to the very sector that caused the financial meltdown in the first place. Combined with large trade deficit, a financial crisis also provides a fertile ground for trade conflict as crisis countries tend to impose protection or accuse trading partners for not playing by the rule. The ‘‘Buy American’’ provisions in the U.S. economic stimulus bill, proposed during the Fall of 2008, were seen by trading partners as a protection that could make the United States vulnerable to a trade war. Remarks made by Treasury secretary in the early 2009, blaming China for manipulating its currency, threatened to stoke tension between two of the world’s biggest economies. They also undermined cooperation to counter the global recession. Within a country, a financial crisis and economic downturn can also threaten social stability when many people feel the hardship. There is another type of conflict sparked by acquisition of assets, involving the Sovereign Wealth Fund (SWF) or financial institutions that represent the interest of foreign governments. French President Sarkozy, in responding to SWF’s aggressive move during a crisis told the European Parliament in Strasbourg in October 2008, ‘‘I don’t want European citizens to wake up in several months’ time and find that European companies belong to non-European capital, which bought at the share price’s lowest point. This might be an opportunity to create our own sovereign wealth funds,’’ he said. ‘‘And maybe these national sovereign wealth funds could eventually coordinate to form a business response to the crisis.’’ In the meantime, the French government injected 10.5 billion euros ($13.75 billion), into six large banks, spurring a rebound in their long-battered share prices. In the United States, members of Congress criticized the government for not taking enough time to consider security implications when the interagency Committee on Foreign Investment in the United States (CFIUS) approved the acquisition of several U.S. port operations by state-owned Dubai Ports World. They demanded that the related laws need to be strengthened by requiring CFIUS to spend more time vetting deals and to keep Congress better informed. In effect, obtaining CFIUS approval will get tougher as Congress begins focusing on the increasing trend of financial sector buyouts. Senator Evan Bayh (D-Ind.) told a special committee examining U.S.–China economic relations that CFIUS ‘‘has largely been a toothless watchdog’’ and asked for tighter regulations ‘‘otherwise we risk

27

Financial Crisis

another Dubai Ports deal situation . . . It’s time to start asking questions about these Wall Street investments.’’ The sentiment against a takeover of assets by foreigners can lead to political and economic conflicts as foreigners look at it as a protectionist move. This is particularly frequent during a crisis because asset prices fall, making them good bargains for buyers. During the 2007/2008 crisis, surplus countries of Asia and the Middle East tried to take advantage of the falling asset prices in Europe and the United States. The first part of this chapter discusses the background of subprime crisis that led to turbulences and severe recession. It explains how a small segment of mortgage market known as subprime could bring down the world’s largest economy. The discussion is subsequently followed by policy analysis that shows the limited effectiveness of monetary and fiscal policy. Using the example of the interrelations between exchange rate and output growth, policy conflicts and trade-offs are highlighted. Falling asset prices, subsequent aggressive move by SWF, and other crisis-related conflicts are discussed in the last section.

THE GOOD TIME Two main factors contributed to the declining world’s inflation rate: production shift to low-cost countries (e.g., ‘‘Chindia’’ factor: cheap imports of consumer goods from China, and outsourcing of services to India), and smaller fiscal deficit due to fiscal consolidation and economic reforms, especially in the traditionally large deficit countries (e.g., Latin America). This allowed many countries to lower their interest rates. In the United States, the low rate was first prompted by the fear of a deflationary pressure following the 1997 Asian Financial Crisis. Subsequently, the Fed adopted a more accommodative policy to forestall looming problems created by the bursting stock, high-tech, and telecommunication bubbles that came along with the recession in 2001. This enabled the U.S. economy to avert a deeper and longer-lasting recession. But as the recovery began, the environment of easy money also produced record levels of home equity borrowing and home sales, funded among others by ‘‘creative’’ financial companies operated like hedge funds. This led to borrowing-fueled speculative spree especially in the housing market, similar to the Internet-stock mania in the 1990s. The rules and regulations governing these financial companies were generally less restrictive than those for banks, mutual funds, and other financial institutions.

28

IWAN J. AZIS

Since the LTCM debacle in 1998, and despite pressures on the U.S. financial authorities to put tougher controls on hedge fund operations, there were practically no major improvements in the financial regulation.1 This explains why ‘‘creative’’ financial activities multiplied in number during the past few years. One of such activities involved the asset-backed securities (ABS) or commercial paper used to finance mortgage firms, credit card companies, auto lenders, etc. At the beginning, many of the issuers of such commercial paper were real estate-related financial companies. They expanded the assets in the balance sheet by lending mortgages to future homeowners and sold these assets to investors by issuing the commercial paper (the essence of ABS is to sell commercial paper backed by such assets). As mortgage loans increased sharply since the mid-1990s, so did the ABS. What distinguished the operation of these paper issuers from the traditional way of lending was that, they packaged the loans into securities pools before selling it to investors. In so doing, they collected monthly principal and interest payments from borrowers and disbursed them to investors who held the commercial paper. They received fees for performing such services. Thus, paper issuers got the trust of investors by consistently paying them on a regular basis with incomes received from homeowners. As long as the flow of these incomes could be secured, and investors continued to receive the payment, everybody was happy. Investors were also ‘‘blinded’’ by the bundling of the loans, because good and bad loans were put together such that buyers could not see the bad ones. This type of operation was clearly different from a traditional lending as loans were financed directly by investors rather than indirectly by bank depositors. Yet, it was seen as a ‘‘healthy’’ operation because the risks involved were shared with others. But greed triumphed. With more mortgages sold and more securities issued, mortgage firms received more incomes. This put them in a position to buy more risky assets and to attract more investors by paying them with earnings from those assets. As more new investors arrived, more investment money flowed in, allowing the firms to use the money to pay the existing investors: that is, one group of investors paid another group of investors. All these were initiated by securitizing mortgage lenders and passing the rights to the mortgage payments and related credit/default risk to third-party investors via mortgage-backed securities (MBS) and collateralized debt obligations (CDO). Welcome to Ponzi Game 101! Mortgage firms did it, hedge fund did it, and so too other financial firms like the one managed by Bernard L. Madoff. But what really transformed the financial sector was when investment banks also jumped into this ‘‘financial innovation.’’

Financial Crisis

29

This decision marked the beginning of the problem that eventually brought the U.S. economy into its knees. Lured by the prospect of huge profits, investment banks operated beyond just performing as the underwriter for mortgage companies. They got directly involved in the mortgage loan scheme. Once they managed to lure homebuyers to get the mortgages, the next and most important step was to sell securities backed by such mortgages (MBS). This was the most important stage because from this stage they could earn a large amount of money. Thus, essentially investment banks transformed their role from being underwriter to become seller of loans. In the process, they shared the risks of mortgage loans with other investors. At the same time they collected a large sum of ‘‘new loans’’ from those investors. Many of the buyers of the securities were wealthy and reputable individuals, as well as institutions including schools, local governments, charitable organizations, and banks. As if the risks were not low enough, many investment banks also insured the MBSs and CDOs they issued through a financial derivative known as credit default swap (CDS). In CDS, the buyer of the insurance contract agreed to pay a fixed spread to the seller of the contract. In exchange, given the approved term (usually five years) the seller agreed to buy the securities from the buyer at par in the event of a default. In this way, investment banks as the buyer received protection, insurance company as the seller (e.g., American International Group, AIG) collected a lot of premium income. Practically nonexistent until late 1990s, CDS market grew very rapidly, reaching a staggering $62 trillion in 2008, more than four times the U.S. GDP! An important motivation for investors to buy MBS was the strong perception that housing prices would always go north. As the number of interested investor increased, it made easier for banks to finance the scheme. It also opened up more opportunities for other players such as brokers and realtors. Everybody did not want to miss out the opportunities. The combination of wanting to fulfill the ‘‘American dream,’’ taking advantage of the lucrative interest rate, and expecting that housing prices would continue to rise, allowed hundreds of thousands of Americans to buy homes they never believed they could afford. It also offered an opportunity and handsome profits for homeowners-to-be and lenders, respectively.2 As a result, the number of risky portfolio holder surged. The investment banks conducted the operation on a large scale, before long only a few handfuls of banks that had not been part of these risky investments.3 This means more loans and more mortgages. As shown in Fig. 1, mortgage lending clearly shot up since the mid-1990s, dominating the U.S. financial sector’s investment.

30

Fig. 1.

IWAN J. AZIS

US Financial Sector’s Investment in Financial Assets. Source: Author’s Calculation Based on a Series of U.S. Flows-of-Fund.

Actually, mortgage lending started to grow fast since the Tax Reform Act of 1986.4 But it was not until 1998 that the craze began when large numbers of people decided that real estate, which still had not recovered from the early 1990s slump, became a bargain. What was not the same with the past housing bubbles and the experience of other countries, however, was the fact that the fastest growth occurred in the subprime category. From virtually nothing, subprime credit surged to reach $1.3 trillion, roughly 10 percent of GDP, within two years. Most borrowers were low-income households wanting to own house, car, or credit card. The default probability of such credits was high, and the transaction was usually less transparent. In commercial paper programs also known as conduits, for example, banks as lenders typically used the off-balance sheet vehicles on behalf of the paper issuer, and the transparency of the conduits contents was very poor (it is paradox that in a globalized financial world the degree of transparency was less, not more). Although huge amounts of money was being made by underwriting subprime loans, banks and mortgage companies all but abandoned their prime loan guidelines. Many of the loans were made under NINJA (no income, no job, no asset) condition. Lenders got greedy, trying to extract as much juice from the borrowers as possible by extending credit without much, if any, regard for borrowers’ ability to repay the full amount.5 They basically functioned like a hedge fund, exempted from many of the rules and regulations governing other financial institutions such as banks and mutual funds. This explains why hedge funds tend to be aggressive in their investing strategy.

31

Financial Crisis

THE BAD TIME Pandemonium set in when homeowners began to have a difficulty with their payments. Some struggled to get loans for subprime refinance deals. A wave of foreclosure or hangover from a heady time suddenly hit the housing market. Investment banks had to force margin calls to protect themselves from the collapsing loan value, and mortgage companies and hedge funds were being forced to sell assets to meet these margin calls. As the value of the underlying mortgage assets declined, corporate, individual, and institutional investors holding MBSs and CDOs faced significant losses. What would you do if you invest in such companies? Vote with your feet! That was exactly what happened: investors tried to withdraw. The problem was, many of them lived on credits granted by the same investment banks who tried to force the margin calls (e.g., Lehman Brothers, Merryl Lynch, or large companies’ financial branches like General Motors). Other major financial companies such as Bear Stearns and Bank of America had also faced a sudden wave of withdrawals by investors.6 Many of them acted like a bank and a hedge fund. The bank part made loans to hedge funds, including its own, and the hedge funds part used the loans to buy other loans and bonds. They also faced difficulties to sell the loans. Some of the loans could not be sold to government-sponsored enterprises like Fannie Mae or Freddie Mac because they were too big. As the number of firms needing more cash increased, liquidity problems set in. Each tried to borrow liquidity from others. As a result, inter-bank rates shot up. A severe liquidity crunch hit the financial market. It was hedge fund equivalent of a bank run, that is, the 21st century run! In Europe, a large German Bank, IKB Deutsche Industriebank, holding a substantial share of subprime investments, came close to a collapse. Fearful that it could create systemic effects, the Bundesbank (German central bank) decided to bail it out. France’s largest bank, BNP Paribas, also had to stop withdrawals from its asset-backed securities funds, arguing that it could no longer value them accurately because of problems in the subprime market. In a matter of days, more funds and companies had either closed or halted investor withdrawals as they sorted out the value of their subprime and other mortgage-related investments. One may wonder, why did not policy makers see the potential systemic risk of such risky investment, and how did investors get involved in the risky deal at the first place? No one worried about risk spreading because banks had sold off the underlying mortgages to investors, and the mortgages were insured through CDS. Rating agencies also gave a nod to these mortgages.

32

IWAN J. AZIS

Many investors jumped in because they could get high returns through leverage, for example, making $100 million bets with only $1 million of their own money and $99 million in debt. If the value of investment rose, they could easily multiply their money. Also, the mortgage loans allowed interest rates to be reset from low teaser to high rates, thereby promising a larger cash flow than prime loans that carried lower fixed rates. Hedge funds, wealthy individuals, and other reputable institutions also had confidence in the arrangement because even if the loan or credit went bad, they perceived that securities backed by bad credit could still be safe. After all, most of the securities had received good ratings from agencies like Moody, Fitch, and Standard & Poor. Even international investors piled into this debt market. The idea that the risks were shared collectively with other parties, that is, issuers, underwriters, borrowers, and insurance firms, was appealing. But these features meant very little when the delinquency rate surged. Worse, although the complex and synergic relationships might have created a favorable system, any shock in the market could create a ‘‘domino effect’’ that would raise the risk of a system-wide failure. Since some of the lending carried prohibitive prepayment penalties, effectively made refinancing impossible, investors could be on the hook for bad mortgages. Before late (some were already too late), they tried to quit. With less money available in the market, liquidity crunch was exacerbated. One by one major financial institutions disclosed their problems associated with the subprime lending and mortgage-backed assets. Deutsche Bank had to write down its losses (at the time estimated at $3.1 billion). Citigroup and UBS had to do the same thing. BNP Paribas and Socie´te´ Ge´ne´rale, two big French institutions, and Barclays of Britain were next on the line. Even in Japan, where banks typically do not sell high-risk mortgage products such as subprime loans, they could not escape losses. In early October, its largest bank, Mitsubishi UFJ, reported f5 billion losses on subprime loan linked investments. The list got longer, not counting many smaller banks and other financial institutions. The defining moment was really when holders of high-risk portfolios had to face a double whammy: investors demanded their money back, and lenders shut the door in their face. As some of these troubled institutions were forced to close down, insolvency set in. With millions U.S. households either on the brink or already gone to foreclosure, and hundreds of subprime mortgage lenders already gone belly up, the liquidity problems quickly turned into solvency problems (this was the prime reason that led this author to predict as early as in the Fall of 2007 that the U.S. economy will fall into recession).

Financial Crisis

33

The liquidity problem was evident as many commercial banks found liquid assets or very short-term loans and longer-term liabilities were no longer available in the market. As shown in Fig. 2, beginning in August the spread between three-month London inter-bank rate (LIBOR) and the expected overnight rates (overnight index swaps or OIS) widened as liquidity concerns had been priced into terms rates.7 To avert a full-blown catastrophic credit squeeze, a series of massive liquidity injections were conducted by the Fed, the European Central Bank (ECB), Bank of Japan (BOJ), and other central banks. The solvency problem, however, was not immediately realized by the authority. Two hedge funds operated by The Bear Stearns Co Inc (one of the biggest players in securities industry) slipped to the brink of collapse because of their exposure to subprime mortgages. Nearly a third of its revenue came from fixed-income trading.8 The probability of their default increased sharply, and the spreads on its CDS soared to 1,000 basis points (it costs $1 million to insure against a default of $10 million face value of bonds). Had Bear Stern defaulted, the market would have had to try to unravel the complex web of trades that could create a logistical headache for bankers, because a CDS contract in effect pledged to protect an investor against loss from a default. Being counterparty on so many trades, which theoretically means Bear Stern needed to get hold of bonds to pay back many investors, the complexity would have been unprecedented. This was the reason why the Fed arranged a guarantee for a forced marriage of Bear Stearns to rival JP Morgan Chase & Co (the acquiring cost was $2 per share, way below $80 in the weeks before). A similar ‘‘bailout’’ scheme also took place in August when Bank of America acquired a $2 billion equity stake in Countrywide in a bid to bolster the confidence of creditors and investors in the failing mortgage lender.

Fig. 2.

Spread between 3–Mo LIBOR and OIS. Source: Gray and Stella (2008).

34

IWAN J. AZIS

The imploding home prices and rising foreclosures brought down the value of the insured mortgage pools. The looming credit crisis took its toll on leveraged loans by expanding the losses on the insured loan pools. Facing potential markdowns on the values of CDOs, banks and buyers of CDS asked for a payout from the insurers. The latter suffered when homeowners could no longer get out of the existing mortgage by selling their house for a profit. Firms like AIG began to feel the heat. Through the first quarter of 2008, its CDO liabilities and swap-related write-downs reached in excess of $20 billion, and the cumulative losses over the past three quarters of that year amounted to $18 billion. The firm’s ratings fell badly, triggering an additional $14 billion collateral call as margin against its CDS. Fearing that the collapse of AIG could pose a serious threat to the financial system, the U.S. government seized control of the firm through an $85 billion deal in September 2008. But a more serious problem was just about to emerge. When the government seized Fannie Mae and Freddie Mac, default in the CDS market became an option, raising questions about how dealers would unwind billions of dollars worth of contracts. With so many CDS attached to CDOs, holders of all securities including good CDOs faced a high risk of their securities being priced unfavorably by the market, because speculators were short selling the CDS index that was tied to CDOs, that is, proxy of CDO price when no one knows exactly the real price. They argued that no one would buy it because of the unknown price (due to the complexity and uncertainty of mortgage duration, foreclosure events, etc.). The entire security market eventually got hit. That was not the end of the story. Profitable investors who needed to borrow money also could not get the lending because market bet against their ability to repay, as reflected by more expensive CDS. This affected many sectors as activities could not be financed. Troubles in insurance firms not only led the costs of CDS to surge and the capital markets to suffer, but it also squeezed out borrowers by driving up the cost of capital. What started as a crisis in the subprime and mortgage market had now reached the entire credit markets; the spread between high quality bond yield (e.g., corporate bonds rated BBB and AAA) and treasury notes widened. What does this mean for the economy? First, the effect on investment or capex (capital expenditure). The incentive to invest weakened because cost of money was higher as reflected in the widening spread. Added by increased uncertainty, this caused total investment to stagnate. Although the day-to-day performance of the stock market fluctuated, the general trend clearly went south. Tobin’s q, the ratio of market value of an asset to

Financial Crisis

35

its replacement cost, suggests that this will pull investment downward. In response, the Fed cut the interest rates rate aggressively. But even that failed to end market upheaval, because unlike in the LTCM debacle and 2001 recession, this time the liquidity problems were compounded with insolvency. The outlook of consumption was equally gloomy. Yet, consumption holds the key to the problem as it constitutes more than 70 percent of the U.S. GDP, and its fluctuations are influenced by what happens with assets prices including housing prices (‘‘wealth-effect’’).9 During the past few years, housing-related effects of low interest rates accounted for at least one quarter of growth in personal consumption expenditures; it was responsible for the robust economic recovery after the 2001 recession (Greenspan, 2003). As mortgage delinquencies and foreclosures continued to rise, and more people and lenders were forced to sell homes, home prices fell precipitously, cutting the value of homeowner’s equity. With lower asset value and falling consumers’ income, spending declined. This led producers’ income and investment spending to fall. Economic losses arising from lower asset prices and falling spending exacerbated the financial sector’s predicament. In turn, activities in real sector stagnated. A virtuous cycles set in. What was once called the subprime mortgage crisis had since transformed into an economywide credit chill. Some believe that the turning point was the day when Lehman Brothers announced its bankruptcy (September 15, 2008). The following weekend was ‘‘The Weekend that Wall Street Died.’’ Founded in 1850 by two cotton brokers in Montgomery, Alabama, the company grew into one of Wall Street’s investment giants. The trouble began at the same time when the mortgage crisis started to unfold in the summer of 2007. At the time, Lehman share reached its peak at $82 a share. Suffering from huge losses in the mortgage market, and investors lost their confidence, the share plunged to $7.79 in early September 2008, when a potential buyer, Korean Development Bank, decided to put talks on hold. When no new buyers came to a rescue, the Ponzi game ground to a halt. Unlike in the Bear Stern case, the Fed and the U.S. government decided not to bail Lehman out. People were stunned that one of the oldest, richest, and most powerful investment banks in the world was not too big to fail. But what most people did not realize at the time was that, Lehman fall became a turning point from which one financial group after another collapsed, wiping out thousands of billions worth of value for investors.10 More seriously, what had largely been an American crisis suddenly went global. From New York, the tremor spread to London, Paris, Eastern Europe, Asia, and Latin

36

IWAN J. AZIS

America. One by one financial firms operating in these countries went into trouble, some of which collapsed. Traveling in these countries and watching financial news there was like watching a soap opera with unhappy ending (some were close to a horror movie). The impending doom that was only abstract and discussed at the theoretical level became reality. As the economic downturn deepened, people started to make a comparison with the Wall Street Crash of 1929. Some declared that the Second Great Depression had arrived. Others even equated the 2007/2008 crisis with the Panic of 1873. The arrest of Bernard L. Madoff, accused of defrauding thousands of investors in a $50 billion Ponzi scheme, only exacerbated the already diminished trust on Wall Street and the financial market. On December 2008, the NBER’s business cycle dating committee made the date of the U.S. recession official: December 2007. The 73-month economic expansion had ended (the previous expansion, lasted for 10 years, ended in 2001).11 By the Fall of 2008, many countries had already fallen into recession as well. Everyone was exposed. Even emerging markets that had a relatively robust financial sector had to face the unfortunate reality. For many of them, the major blow came through the trade channel (falling exports). To stop the cycle, Fed Chairman Ben Bernanke argued that the housing bust had to end first. Yet, a gloomy prospect of housing market was likely to prolong for the following reasons: (1) the expansion in the housing market that led to the 2007/2008 crisis was the longest in the past 50 years; (2) historically, housing recessions started to bottom out only after close to 40 percent drop from the moving average peak, while at the time of the writing the drop had been less; and (3) even with the falling prices housing construction still continued in some states (Roubini & Menegatti, 2007). It is also important to note that historically housing downturn preceded an economy-wide recession. Henceforth, the 2007/2008 recession was severe and likely to last long. Under the Obama administration, stimulus programs and other new policies had been tried. They may or may not have helped slowed the downturn. No one knows exactly. Even if it did slow the downward spiral, it is hard to judge the relative effectiveness of those programs because any downturn will ultimately end, and any recession economy will eventually recover. Those in charge always tend to argue that something has to be done, no matter how imperfect that something is, because the outcome of doing nothing will be much worse. Even if that is the case, however, policy trade-offs need to be understood, because they exist in virtually any policy measures to revive the economy. To understand these policy trade-offs

Financial Crisis

37

better, they need to be analyzed in a broader context by looking at the background and the policy environment that prevailed before the meltdown. This and various conflicts that emerged after the crisis are discussed next.

POLICY TRADE-OFFS AND CONFLICTS Reaching at an annual rate of roughly $800 billion, or 7 percent of GDP, the U.S. current account deficit (CAD) during the 1990s represented roughly 70 percent of the global CADs. This was unprecedented, and played a key role in the global imbalances discussed in the preceding chapter. When a country has a large CAD, two things can happen: large capital inflows to ‘‘finance’’ the deficit and a weakened currency. What was the evidence? We know that there had been a large sum of foreign capital flowing into the United States from surplus countries. We have also observed the depreciation of the U.S. dollar relatively orderly before the market turbulence, and with increased fluctuation after the turbulence. Not foreseen was the great destruction to the financial sector and the sharp fall in the U.S. output. Although theoretically foreigners could start feeling uncertain about investing in the greenback, the evidence even after the 2007/2008 crisis broke out did not show any significant change in the foreigners’ interest; at least not yet. However, as the CAD continued to worsen, foreigners began to pull out some of their assets from U.S. dollar investment. As a result, further dollar weakening was inevitable, implying that importing goods from the United States would be much cheaper but import prices that U.S. consumers ought to pay became more expensive. Theoretically, one scenario coming out of it could have been a faster growth of export. Had this been the case, CAD would decline. But if the dependence of U.S. consumption on imports continued to be high (low domestic supply elasticity), a falling CAD was unlikely, at least not in the short run. Even if CAD can be narrowed, the inflationary pressure from the dollar’s sharp depreciation, that is, imported inflation, may force the Fed to raise the interest rates. This will put the last nail in the ‘‘R’’ coffin, and it will translate into falling demand for imported goods from all over the world. We began to observe this trend in the second half of 2008. Thus, two unwelcome scenarios emerged from the global imbalances: a sharp fall in dollar value and recession. Before the subprime crisis began, very few analysts believed that recession scenario was imminent; most of them believed that a soft landing was more likely, that is, U.S. dollar would depreciate in an orderly fashion. But with the subprime crisis and its

38

IWAN J. AZIS

contagion effect in the real sector, the probability of a hard landing increased significantly. This posed a serious policy conflict. Higher interest rates were necessary to strengthen the dollar, but it raised the likelihood of recession. On the other hand, lowering the interest rates to avoid recession might push the value of the dollar down further. Suppose the ideal exchange rate is ei (optimal prices for exporters and importers), and the long-run equilibrium level of output is Yi (see Fig. 3). Given the market turbulence that led to a credit crunch and falling dollar discussed earlier, equilibrium point Abad is at the intersection of money supply M and aggregate demand AA, where output level and the exchange rate are, respectively, Y1 and e1. In a crisis, this ‘‘bad’’ equilibrium is stable. The following analysis focuses on policy scenarios that allow the system to depart from Abad. If the dollar value is to be strengthened, the Fed can raise the interest rates. Essentially, money supply line is shifted to the left from M to Mu. At the new equilibrium B, the dollar value strengthens to e2 (note that Fig. 3 is drawn such that an upward movement along the y-axis implies a weakening dollar; vice-versa). But this will pull output level further to Y2, raising the risk of recession. The exchange rate adjustment under such circumstances is: U.S. dollar weakens (exports expand). Thus, point B is dynamically unstable. The implied policy conflict in this case is straightforward: tightening monetary policy to strengthen the currency versus nontightening policy to avoid output fall. If bringing back output level to its long-run equilibrium (i.e., to increase output) is the priority, the Fed must lower the interest rates or raise the

Fig. 3.

Trade-off between Dollar Value and Recession.

Financial Crisis

39

money supply to Muu. The move by the Fed to inject liquidity in the market and lower the Federal Fund rate reflects this shift. As clearly shown in Fig. 3, this will weaken the dollar value further to e3. Thus, the policy tradeoff concerns the goal to raise output versus the goal to strengthen the currency value. If raising output is preferred, the resulting fall of the dollar value will cause import prices to increase, and this can lower consumption and investment expenditures, causing output to fall. Therefore, the original output increase due to the accommodative monetary policy cannot be sustained; that is, C1 is dynamically unstable. The only stable equilibrium is Abad, which is a position we are trying to depart from. On the expenditure front, an expansion shown by a rightward shift to AAu will result in a stronger dollar, that is, point C2. At this equilibrium, however, the dollar appreciation fails to stimulate output, presumably due to a dampened growth of exports. Thus, another policy trade-off may arise. But when increased expenditure is combined with accommodative monetary policy, output will increase to Yi, and the exchange rate will be in Ei, still stronger than e1. Although such a combined policy is desirable, however, it may not be easy to implement. First of all, to increase government expenditure given the prevailing fiscal deficit is politically difficult, let alone the potential conflict that may arise due to the deep philosophical differences between the Democrats and the Republicans in terms of how to stimulate the economy. Also, the Fed may restraint from a more accommodative policy if the inflation expectation is on the rise due to factors other than exchange rate, for example, higher oil prices, rising trade protection, etc. But a series of interest rate declines since the Fall of 2007 and several fiscal stimulus packages issued since March 2008 indicated that the Fed and the Bush administration were more concerned with the risk of recession. The question is: will it be effective? Policy choices should not be delinked from the symptoms and causes of the crisis. The monetary and fiscal policy discussed earlier would have been effective if the main source of the slowing output growth is of the aggregate demand (AD) type. However, if the main reason of the economic slowdown is the aggregate supply (AS) shock, the effectiveness of such a policy is limited. Since in reality AS and AD exert some shocks simultaneously, one needs to measure both, and evaluate which of the two shocks exerts the largest pressure on the output growth. The strength of each shock can be reflected by the size of the slopes of the AS and AD curves. Generating these two curves cannot be done by simply plotting the data of GDP growth and inflation. To the extent that both

40

IWAN J. AZIS

shocks jointly determine the changes in output and price, a decomposition procedure needs to be applied. By using the structural vector autoregression (SVAR) technique and the Blanchard-Quah decomposition, the author found that since the credit crisis began the slopes of both the AS and AD curves in the U.S. economy became steeper. Although the absolute size of the AS slope was always greater than that of the AD slope, during the crisis the gap between the two widened (i.e., from .55 versus .23, to .89 versus .34, see Fig. 4). What does this mean? A steeper AS curve implies that the effectiveness AD expansion is limited. Given a particular level of expansion the output growth will be smaller than under a scenario where the AS curve is flat. In the earlier period (1994–2005), such a policy would have been more effective since the slope of the AS curve was smaller. The earlier conclusion is consistent with the finding based on the dynamic analysis of the AS and AD slopes. As shown in Fig. 5, the downward pressures on the output during 2007 originated in the supply shock, not the demand shock. The latter dominated the source of the upward pressure on inflation. Thus, aside from the sheer magnitude of the financial losses and the uncertainties that bruised market confidence, based on this analysis alone the stimulus package issued by the administration and the loosening monetary policy by the Fed would only have a limited effectiveness to counter the downturn pressure. Other things also made things worse. Not only the risks of credit and dollar crisis were higher than in the previous recessions, but insolvency also made the problems more difficult to solve. Above all, repairing market confidence is always far more difficult than anything else. The authority had to face a dilemmatic problem since some of the ‘‘creative’’ financial institutions involved in the debacle were outside its controlling screen (either they were not banks, or the transactions were recorded off-balance sheet). Like hedge funds, the products of these institutions were complex, not widely traded, exotic, involving so many types of assets, hard to locate, and difficult to value (‘‘Where’s Waldo’’ problem). Much of the financial losses also originated in SIV or SPV (special investment and special purpose vehicle), the transactions of which never appeared in the bank’s balance sheet although they were set up by banks. They may be located in tax-heaven places like Cayman Island. The unknown size and institutions that held the losses made the policy scope of the Fed and the effectiveness of many stimulus policies limited. Yet, in a crisis situation such policies are needed. This type of policy conflict always arises when an economy is experiencing a financial crisis.

Financial Crisis

Fig. 4.

41

US Aggregate Supply (AS) and Aggregate Demand (AD) Slopes. Source: Author’s Calculation Based on SVAR and the Blanchard-Quah Decomposition.

42

IWAN J. AZIS

Fig. 5. Sources of U.S. Output Growth and Inflation Shocks. Source: Author’s Calculation Based on SVAR and the Blanchard-Quah Decomposition.

Financial Crisis

43

If market turmoil was relatively mild, and the problem was only about liquidity, the Fed intervention and the fiscal stimulus package would have been enough to end the turbulence. But historically there were almost no cases where a meltdown of this proportion could be halted with one single policy. It would need much more to stabilize market conditions especially when the source of the problem was so interlinked, involving different institutions, not just banks. Although the source was complex, enabled by a new system of financing, the institutions that tried to ‘‘solve’’ the problem were those created to deal with the old system’s problems.12 These institutions had little regulatory oversight of the financial companies and securities that were in trouble, and they also did not know exactly who was holding what. For many years, mortgage brokers were allowed to offer loans underwritten at the initial (teaser) rate. Only later on bank regulations required that loans be underwritten at the fully indexed rate. There are other regulations of this type that need to be explored to prevent a similar crisis in the future and to protect less-informed borrowers.13 There has been a kind of regulatory laissez faire during the past years despite the increased number of ‘‘creative’’ financial institutions in a brave new world of financial globalization. It is appalling that more than a decade after the LTCM debacle people are still in the state of calling for better regulations. As argued in the preceding section, an accommodative monetary policy ought to be combined with fiscal expansion. But to select policy of this nature given the large fiscal deficit will not be easy. Finding alternative fiscal policy that will allow the system to raise business investment such that the equilibrium point C3 in Fig. 3 can be reached is an important direction to take. An example of such policy measure is to revoke some tax cuts, and lower the marginal tax rates on capital income. The latter has been proven capable of producing large deadweight losses even when the effect on saving is small (Feldstein, 2006).14 Switching to consumption tax, away from using investment tax may also be worth to consider.15 Another fiscal policy to focus on is at the state level, since taxes in many states have been proven to be deterrence for business operations.16 The problem is, while the concept and the objective of lowering tax may be clear, many states had already suffered from fiscal deficit even before the crisis and Federal aids dried up. This posed a difficult policy choice. A crisis often forces states to cut funding to state agencies and municipalities.17 In the 2007/2008 crisis, many states had to face billions of dollar in budget deficits. Governors and state lawmakers had to work with less revenue as sales and taxes declined. Consequently, they had to explore ways to generate higher local taxes. A plea for federal assistance had only little effect because the

44

IWAN J. AZIS

federal government was also cash-strapped. This added to the list of policy trade-offs and conflicts. The importance of understanding policy conflicts in a crisis situation cannot be over-emphasized. It is necessary to think of a counterfactual policy analysis to derive important implications of different policy response. Even given the success of a particular policy in the past, selecting same policy measure in a different crisis situation may not be the right thing to do. The selection process needs to take into account the specific conditions and institutional environment in the crisis country. This is even more critical when we are presented with difficult policy trade-offs. One may recall episodes of financial crisis around the world where the standard policy response was a pro-cyclical type, for example, raise the interest rates, tighten the budget, and avoid a bailing out scheme to avoid a moral hazard problem. A case in point was the Mexico’s tequila crisis in 1994 and the Asian crisis in 1997, during which the IMF and the U.S. Treasury were adamant to impose such a pro-cyclical policy. It worked in Mexico, but mostly failed in Asia. Ironically, everything what the U.S. administration and the Fed had been doing during the 2007/2008 crisis was exactly the opposite of what they preached: lower the interest rates, expand the fiscal deficit, and bail out some of the troubled financial institutions. And the IMF supported them. A financial crisis could also spark conflicts beyond policy disputes. Political and diplomatic conflicts arise when parties in two or more countries are involved in lending transactions, and borrowers in the country hit by financial crisis has a difficulty to repay. A conflict flared up between the United Kingdom and a Nordic country, Iceland, as a result of the 2007/2008 crisis. After being privatized, many banks in Iceland used substantial wholesale funding to finance their entry into the local mortgage market and acquire foreign financial firms, mainly in Britain and Scandinavia (e.g., Iceland’s Baugur Group owned a vast swath of Britain’s retail industry).18 The financial interlink between the two countries got deeper as many British investors, attracted by high interest rates put their money in Iceland banks.19 One Internet bank, Icesave, owned by the second largest bank in the country Landbanki, managed to attract $7 billion in deposits from 300,000 British retail investors. The problem began in the Fall of 2008 when the Icelandic economy and its financial sector got into trouble.20 When credit rating agencies downgraded Icelandic state and banks, foreign investors tried to get rid of Icelandic assets. The currency (Krona) fell sharply, posing difficulties for banks to repay due to a classic balance sheet effect. Icelandic banks operating in United Kingdom also suffered from

Financial Crisis

45

mass withdrawal of funds. This brought the country’s largest bank, Kaupthing, into collapse, and the effect reverberated throughout the entire economy. Realizing that many British retail investors invested in Icelandic banks, U.K. government stepped in by pledging to guarantee the deposits of all British retail investors in Landsbanki and its subsidiaries. At the same time, however, it sued Iceland to recoup at least some part of the savings of British customers in Icesave, and decided to freeze all assets of the collapsed Icelandic banks under anti-terrorism laws, to protect British depositors.21 A full-blown diplomatic spat erupted as the Nordic nation protested Britain’s decision. The then Prime Minister Geir H. Haarde called the move a ‘‘completely unfriendly act’’ and blamed Britain in part for Iceland’s decision to take control of the country’s largest bank. Concerned that money had been transferred from the accounts out of London to Iceland, Gordon Brown refused to apologize for his actions and claimed that the attitude of Icelandic government was ‘‘totally unacceptable.’’ He went on to say ‘‘ . . . the responsibility is on the Icelandic authorities . . . they should pay back that money, they are liable for it. We expect them to honor their obligations.’’ Trade conflict is another common form that arises because of a financial crisis. Suffering from a credit crunch, automakers in Detroit argued that government loan was needed to deal with their immediate cash crisis and allow them to complete the restructuring plans. After long debates, they got the loan.22 Automakers from other countries filed a complaint against the move. Pascal Lamy, the director-general of the World Trade Organization (WTO), sounded a warning about state aid intended to mitigate the economic crisis. He argued that any policy response to a crisis must not break the WTO rules or discriminate against foreign companies. He believed that rich countries’ support for their car industries, not likely to create systemic threats like in the case of banks, could discriminate against rivals in developing countries. Concerns were also expressed that bailout programs for banks could distort competition (the list of countries offering relief and the receiving financial institutions got longer and longer). However, many believed that without relief programs there would not be an end to the crisis. Another serious conflict is when the Sovereign Wealth Fund (SWF) aggressively acted as dealmaker in some countries and industries. In the past few years, the trend was triggered by the growing size of accumulated foreign reserves in surplus countries such as China, and the falling asset prices in crisis countries. As the 2007/2008 crisis unfolded, several SWFs quickly announced their intention to increase the values of M&A (left part

46

IWAN J. AZIS

of Fig. 6), the largest share of which was intended to flow into Western industrial countries (right part of Fig. 6).23 Governments, lawmakers, regulators, and analysts in the United States and other crisis countries argued whether greater safeguards were warranted. They feared that the ‘‘invasion’’ of SWF in Wall Street could pose a national security threat and pigeonhole U.S. policy makers into taking a certain policy when the acquired institutions will face some problems in the future.24 This was despite the fact that most deals made by SWFs involved only small stakes, that is, between 5 and 10 percent with no voting rights. The biggest target of criticism was SWFs from China, because suspicion was strong that they will support Chinese government’s strategy of selling bonds domestically to sterilize its excess reserves and then buying U.S. Treasury bonds at a loss, to keep the inflation rate low and the currency undervalued. Although simple economics justifies an acquisition by any legitimate investors, domestic and foreign alike, negative sentiments against SWF and the resulting political pressure can be indeed significant. In early 2008, the then President Bush expanded the mandate of a group charged with investigating SWF interested to buy some U.S. banks and companies,25 and a congressional committee threatened to scuttle one high-profile transaction backed by the Chinese government (Financial Weeks, 2008). From the

Fig. 6. Total Values of M&A Announced by SWF and the Share Going To Western Financial Institutions. Note: For the Left and the Right Figures, 2008 Data are as of January 23, and January 31, respectively. Source: Financial Weeks, February 11, 2008.

Financial Crisis

47

perspectives of the governments that SWF represented, this was seen as protectionist fervor. A potential conflict heightened. Fearful of the future repercussions of the deal, some SWFs decided to take its money elsewhere. National Oil Corp., Libyan government’s SWF, decided to invest in European stocks, real estate, and banks because they viewed that in Europe politics did not interfere too much in trade and financial transactions. The concept of SWF being large concentrated holdings of international assets owned and managed by governments, is essentially in conflict with the conventional notion of a market-based international financial system managed by individual private investors. There is a potential for conflicts of interest on the part of private firms that compete for investments by SWF, as these firms may exploit inside information and do not feel compelled to adhere to international norms because those norms are not necessarily embraced by the SWF-establishing government. More seriously, the murky motives of governments in managing their international investments through SWF can lead to conflicts fueled by national security concerns and economic nationalism. The increase in financial protectionism in host countries as a result of SWF’s aggressive purchase can lead to a counter-measure in home countries. The overall effect and the resulting conflict can be more destabilizing than in trade disputes, because in crossborder financial flows there are no generally accepted rules of the game that can deter a country to use protection. Controversy and potential conflicts related to SWF operations were nonexistent in the past crisis episodes. This time, however, the sheer magnitude of surplus, and the accumulated reserves by some countries allowing SWFs to move more aggressively made the scheme more conflictprone. As discussed in the preceding chapter, the increased surplus in some emerging economies was closely linked with global imbalances. But the trigger was the financial crisis that led to the falling asset prices in the United States and other industrial countries. It is estimated that in 2007 alone SWF from countries of Asia and the Middle East had spent more than 43 billion Euros to invest in European and U.S. business groups. The IMF estimated that more than 20 SWF financed by petrodollars and foreign exchange reserves managed between $1.9 trillion and $2.9 trillion around the world. The number of SWF and amount of assets managed by them grew exponentially, expected to grow by $1 trillion a year. When it collides with the growing sentiments and political pressures against foreign acquisition, conflicts arise. Any economic crisis will always have undesirable impacts on the most disadvantaged group of society. Even if the magnitude of negative effect is

48

IWAN J. AZIS

smaller for this group than for the wealthy, the real impact is always more devastating for the poor. This applies not only within a country but also between countries. For emerging markets and other developing countries, even without the global financial crisis their position in 2007–2008 had already been weakened by the cumulative effects of the food and fuel price surges that peaked in mid-2008.26 As the credit crisis in the United States spread around the world, private capital flows declined, and export markets shrink, many of them had to face serious setbacks through no fault of their own. Gains in poverty reduction and improvements in living standards achieved during the past years were in jeopardy. Income inequality is another problem that could be worsened by the global financial meltdown. As the benefits from growth failed to trickle down to the low-income segments, especially in rural areas, income inequality worsened. Tighter credit conditions and weaker growth exacerbated the worsening trend, because private sector investment shriveled, and governments’ abilities to spend more on social overhead capital declined (e.g., for education, health, and other public services). Rising poverty and inequality pose a threat to political and social stability. In China, where the Communist Party used economic reforms as a source of legitimacy for its rule, the decline in growth due to the global financial crisis could threaten the party if the social unrest spiked.27 The government was so far able to prevent labor protest from developing into uncontrolled situation by keeping the protests separate from one another. However, if the global financial crisis turns into a prolonged recession, and the downturn in the Chinese economy becomes more severe, the ruling party may face a serious threat. A widespread conflict can arise. This is the reason why China is among those active in providing a series of stimulus package during the 2007/2008 crisis. Although it is hoped that such a policy will mitigate the downward pressure on the economy, the more important goal is to maintain social stability through employment creation, especially for those migrating from rural to urban areas. In some countries, the economic and financial crisis had already led to social unrest. From Greece to India, from Argentina to China, riots erupted. Even in oil-rich Middle East countries social unrest was inevitable. It was reported that a group of Kuwaiti equity traders marched on the emir’s office in October 2008 to demand the closing of the stock exchange to stem losses. In United States cities many predict that a civil disorder is ‘‘conceivable’’ if unemployment rises above 10 percent. Russia saw an increasing number of unrest due to crisis measures, as growth in protests increased, arising from the frustration of workers over the nonpayment of wages or those

Financial Crisis

49

threatened with dismissal. In Iceland, where the economic contraction took the country back to the income levels of five or 10 years ago, households owed more than double their disposable income at the end of 2006, almost twice the level in the United States. Protests in that country came out of nowhere. At Reykjavik’s concert hall, a symbol of the good times, the center’s marketing director commented, ‘‘Iceland right now is like Chernobyl after the blast. It looks normal, but there’s radiation.’’ Policy response to a crisis taken by one country can also spark a conflict when other countries feel disadvantaged by it. In the early 1990s, when Germany raised the interest rates to counter the increased inflationary pressure due to a surge in government spending related to the unification, other European countries especially those with slow growth and high unemployment faced a serious policy dilemma: not to raise their own rates risking massive capital outflows, or follow Germany step risking a further downturn in their economy. Many criticisms by other European countries were thrown at Bonn’s decision at the time. In the 2007/2008 crisis, the table was turned. Germany felt that Britain’s policy of cutting the rate of valueadded tax (VAT) in order to stimulate the economy could hurt German economy. Peer Steinbruck, German finance minister, accused Britain of ‘‘a breathtaking switch from decades of supply-side economics to a crass Keynesianism’’ (although responding immediately with its own fiscal stimulus package). To diminish the appearance of a more serious AngloGermany dispute, Gordon Brown brushed it off as the fallout of German politics. He declared that the 27 EU nations were united in agreeing that a suitable fiscal stimulus was needed to tackle the recession. Enduring the same pressure, other European countries did not seem to agree. Dutch finance minister, Wouter Bos, openly said that the VAT cut in Britain was ‘‘not a very wise thing to do.’’ He further made a remark reflecting what was felt by other countries ‘‘I don’t believe it will contribute to a recovery of the economy, whereas it does put pressure on other countries to do the same.’’ But no harsher words than those coming from the Elysee Palace. President Nicolas Sarkozy said that a cut in VAT would not encourage people to buy more if ‘‘they are scared of their future’’. He argued that targeted investments were a better approach than consumer spending measures ‘‘Britain is cutting taxes. That will bring them nothing. Consumption continues to decrease in Britain . . . In France, we chose investment because when we put France into debt by taking money to invest, in return we have assets, infrastructure. When you put your country into debt to pay for operating costs, you have nothing in return for your debt and you ruin the country.’’ He then continued saying, ‘‘If the English did that it’s because they don’t

50

IWAN J. AZIS

have any industry left. Gordon Brown cannot do what I am doing with carmakers giving them 6 billion euros . . . in construction and other industries, because they haven’t got any left.’’ Ironically, the exchange of harsh attacks due to conflicting opinions about policy response to the crisis happened when European countries badly needed a coordinated effort to rescue their tattered economy. If anything, the disputes stalled the EU rescue efforts. The disputes among European countries did not stop there. Under severe domestic strain, President Sarkozy also suggested that French car companies should move production back home from countries like the Czech Republic. The response from Prague was predicted. Prime Minister Mirek Topolanek pointed out that Sarkozy’s comments could jeopardized ratification of the European Union’s Lisbon Treaty ‘‘What Nicolas Sarkozy said is unbelievable . . . If somebody wanted to seriously threaten ratification of the Lisbon Treaty, they couldn’t have picked a better means or time.’’ It is not difficult to predict that instability and conflict will arise when the economy is in a gloomy state of affair resulting from a crisis and its policy response. The depressing condition is particularly discernable in rising bankruptcy, foreclosure, inequality, poverty, and unemployment. The 2007/2008 crisis also brought up a fundamental question about the role of market and capitalism, similar to what happened in the late 19th century and in the 1930s. People began to question whether free market or unfettered capitalism was the best form of organizing society. The proponents who continue to believe that one cannot beat the market as a system for distribution and exchange of goods, argue that there is going to be an adjustment with more interventionist state. The fact that market could not train workers, create infrastructure, protect the environment, and failed to regulate itself, was the mistake of politicians, not the system. Thus, free markets system should be subject to civil regulation, asset distribution, and persistent intervention. A crisis or recession reflects the need for such an adjustment. The opponents, however, would go straight to the point. Looking around the world where massive need coexists with massive wealth shows that market is massively inefficient. The fact that financial crisis occurred so frequently proves that market is also unstable and turbulent. In the 2007/ 2008 crisis, monolithic investment banks and securitization emerged because the system allowed profit rather than product-driven incentive system, financialization of the economy based on pretend earnings and pretend values, and also because it embraced a greed-is-good philosophy. Critics contend that there is nothing inherently efficient about free markets when

51

Financial Crisis

they are conceived wholly in terms of price and return. The system will create nothing other than gambling masking itself as sound investment. They made a point by raising the irony that the very people and institutions for whom it was a sacred orthodoxy that there should be a fully market system with no government intervention came to the government during the crisis begging for assistance. Injecting uncertainty into the analysis of any system including capitalism and free market system makes good theoretical and practical sense. It is in line with the ability to act correctly and rapidly in the face of disconcerting events such as an economic crisis. After the elongated Great Depression that called for state interventions, capitalism survived. Following the wreckage of unsuccessful central plan, state plan, and top down system, the development thinking post-1980s also favored free markets and capitalist system. It remains to be seen what happens after the 2007/2008 financial meltdown. What seems clear is that, the dominant economic system will go through some serious adjustments and corrections. It will not happen quickly because it is a process, not a single event. But it is not unlikely that in the process some sections of the capitalist economy will collapse or completely altered. Looking from this perspective, although the 2007/2008 crisis poses an enormous threat to the global economy and human welfare, it also provides an opportunity for a real change.

NOTES 1. LTCM (Long Term capital management) is a hedge fund founded in 1994 with $1.3 billion investment at inception. It made huge profits during a few years of operation. By early 1998, the fund had a leverage factor of roughly thirty to one, that is, holding $5 billion equity and over $125 billion borrowing. The key reason investors were attracted to its strategy was the belief that the long and short positions were highly correlated so that the net risk was small (this is based on the complex computer models that LTCM used). Long story short, in September 1998, the LTCM lost substantial amounts of investors’ equity capital, and was on the brink of default. To avoid the threat of a systemic crisis, the Federal Reserve orchestrated a $3.5 billion rescue package from leading U.S. investment and commercial banks, in exchange for 90% LTCM’s equity. 2. The 1997 tax break proposed by the then President Clinton and approved by Congress in 1997 also played role in the creation of a housing bubble. Under the law, people do not pay tax on most of the profit obtained from selling a house. In essence, it allowed home sales to become tax-free windfalls. A study by the Federal Reserve suggested that the number of homes sold was almost 17% higher over the decade before than it would have been without the law.

52

IWAN J. AZIS

3. The good time spread out across the Atlantic. In Europe, asset-backed bonds (also known as ‘‘covered bonds’’) are the most well-known. The key difference from the U.S. mortgage-backed securities is that, in Europe banks that make loans and package them keep those loans on their books. This means that when a company with mortgage assets on its books issue the covered bond, its balance sheet grows. 4. The Act stipulates, among others, that interest deductions on mortgage debt remain intact, whereas deductions for consumer and auto loans are eliminated. To deal with the high-risk borrowers (low-income households who want to take mortgage), the legislative reform also enables lenders to deliver risk-adjusted pricing rather than shut the door on them altogether. This served the early growth of credits of the subprime type, that is, loans offered at a rate above prime because the low credit ratings of the recipients did not qualify them for the prime rate loans. 5. Take the case of a real estate finance company Countrywide that aggressively made $470 billion in loans in 2006. In its website the company’s efforts to lure borrowers was obvious: ‘‘We offer you products and services at a lower cost or with greater convenience by sharing limited information within our Countrywide family of companies and with carefully selected business partners.’’ 6. When the U.S. second-biggest home lender American Home Mortgage Investment Corp filed for bankruptcy in early August 2007, the market of commercial paper felt the shockwaves. As other lenders fell into a similar situation, many of them took the option of delaying payment for the money they borrowed from investors (there was a clause allowing such a practice in the unlikely event lenders could not refinance). All of sudden, the 30-day notes you bought became, say, 240-day notes. Who would not shun such commercial paper? 7. When LIBOR-OIS spread increases, it indicates that banks think that other banks they are lending to have a higher risk of defaulting on the loans. Consequently, they charge a higher interest rate to offset this risk. This usually happens when credit markets are not functioning as smoothly as they could be, as the mid 2007 case has shown. 8. Using US$30 billion credit line provided by the U.S. Federal Reserve Bank, JP Morgan took those MBSs at a fraction of their market value. 9. Housing expenditures account for more than one-fifth of U.S. GDP. When housing wealth and capital gains from home sales increase, consumers spend more. Interestingly, the housing sector tends to be strong no matter what happens with the stock market. If the stock market is strong (e.g., during a bubble), home prices receive a lift from investors’ decision to shift the stock gains into real estate. When stock values fall, home prices also receive a boost as investors pull money out of the stock market and put it into real estate in search of positive returns. According to Belsky and Prakken (2004), the effects of changes in housing and stock wealth on consumer spending are different in timing. It takes only about one year for spending from housing wealth to reach four-fifths of a long-run effect, compared with several years for stock wealth. That is, the effect of housing wealth is more immediate. An important reason for it is that, consumers are more cautious about changing their consumption behavior based on near-term movements in stock prices that can well prove unsustainable. Although liquidation of home equity and realization of capital gains from home sales can add significantly to growth in consumer spending, the impacts are only temporary. Thus, an increase in home prices imparts more lasting benefits. This explains why historically the correlation between home prices and economic growth has been stronger.

Financial Crisis

53

10. As expected, the search for scapegoats intensified as a plethora of investigations by prosecutors and regulators was launched. By the end of 2008, Federal officials had opened investigations into at least 25 large companies, including Lehman Brothers. The Securities and Exchange Commission (SEC) tried to determine whether managers of those firms misled the public about the financial condition of their companies. However, defence attorneys argued that companies, as well as their individual directors and executives, could not be blamed for the unprecedented market turmoil. 11. The National Bureau of Economic Research (NBER) does not define recession as two consecutive quarters of decline in real GDP, as is the rule of thumb used by many people in many countries. Instead, it looks at whether ‘‘a significant decline in economic activity spread across the economy, lasting more than a few months, normally visible in production, employment, real income, and other indicators.’’ For the 2007 recession, the particular data that declined after reaching the peak in December 2007 was on payrolls. 12. The new financial transactions were so complex that many terms were not well understood. It was reported that even the former Treasury secretary and current Citigroup executive, Robert Rubin, had difficulty in explaining ‘‘liquidity put,’’ a new and obscure kind of financial contract that eventually hit Citigroup. 13. It is also important to understand what really prevented regulators from adopting stricter rules on financial institutions like the hedge funds. 14. Much of the current tax burden on investment stems from the 1986 Tax Reform Act. 15. Some studies show that if the United States had switched in 1991 to a consumption tax system, instead of taxing investment heavily, the real GDP would have been around 5 percent higher by 2004, and business capital spending would have been more than 30 percent higher. 16. Take the case of New York State. From a survey conducted by The Business Council of New York State, Inc in March 2006, employers overwhelmingly agree that the state taxes undermine their ability to compete and prosper. More than half of respondents said they had considered leaving New York State, closing operations here, or putting growth in other states. 17. States usually handle big-ticket programs (e.g., health-care funding, socialservices programs), whereas municipalities are responsible for other services (e.g., fire and police protection). 18. The aggressive company also built up an equity stake in Saks Fifth Avenue, viewed by many as a takeover attempt (Business Week, 2008). 19. In just five years, the Icelandic banks went from being almost entirely domestic lenders to becoming major international financial intermediaries. 20. Traced back to the origin of the Iceland economic problems, the inflation targeting policy was to blame. The policy led to high interest rates, and encouraged domestic firms and households to borrow in foreign currency, as well as attracted currency speculators. With massive capital inflows, the exchange rate appreciated sharply, giving the Icelanders an illusion of wealth. These effects encouraged economic growth, higher inflation, and a further rise in the interest rates, exacerbating the already high leverage problem. At one point, Icelandic banks had foreign assets worth around 10 times the country’s GDP. Even when Icelandic banks were better capitalized and had lower exposure to high-risk assets than many of their European counterparts,

54

IWAN J. AZIS

they could not survive with such worsening conditions. The financial sector bankruptcy damaged the economy further, and a contagion to the economy of the United Kingdom and other European countries was inevitable. 21. The collapse of Iceland’s three major banks had a serious impact in Britain, where tens of thousands of private savers held accounts worth millions of pounds with branches or subsidiaries of those banks. Also, some 82 British local governments invested hundreds of millions of pounds worth of taxpayers’ money in Icelandic banks, taking advantage of relatively high interest rates compared to other countries’ A-rated banks. 22. Auto-parts suppliers, the supporting industries for automakers, also asked for government aid, arguing that they had to struggle with losses as sales dwindled. 23. Note, however, that due to the deep crisis the financing difficulties, the volatility in valuations and widespread risk aversion caused the overall value of M&A to fall in 2008 (down by 30 percent compared to the 2007 level). The declining trend is expected to last as long as the financing difficulties continue. 24. Former Treasury Secretary, Lawrence Summer, was reported saying, ‘‘What about the day when a country joins some ‘coalition of the willing’ and asks the U.S. president to support a tax break for a company in which it has invested? Or when a decision has to be made about whether to bail out a company, much of whose debt is held by an ally’s central bank?’’ Ironically, the IMF along with the U.S. Treasury where Mr. Summer was the Deputy during the Asian Financial Crisis supported the idea of acquisition by foreign banks and institutions in Asia. Facing the influx of SWF following the 2007/2008 crisis, the United States and European countries put pressures on the IMF to draft a set of transparency practices and a voluntary code of conduct for deals involving SWF. 25. Through an executive order, the then President Bush raised the workload of a committee that scrutinizes cross-border transactions. Known as CFIUS, made up of eight cabinet officers and four presidential advisers, the main task of the committee is to suggest denials or approvals. 26. The impact of oil price surge is discussed in Chapter 4. According to the World Bank estimate, the number of poor increased by at least 100 million as a result of the food and fuel crises. Many of poor households were forced to switch to less nutritional (cheaper) foodstuffs, or cut back on total caloric intake, causing weight loss and severe malnutrition. This also occurred in two most populated developing countries, China and India. It was reported in the 2008 Global Hunger Index (IFPRI, International Food Policy Research Institute) that India is one ofthree countries with the highest prevalence of underweight children under five (more than 40 percent). 27. To create enough new jobs to absorb new labor force entrants, China’s annual growth rate must reach higher than 8 percent.

CHAPTER 4 REGIONAL FINANCIAL ARRANGEMENT INTRODUCTION As discussed in the preceding chapter, the impact of a financial crisis can be very severe, creating conflicts of various types. We have also learned that formulating an appropriate policy response to a crisis is not easy, involving many trade-offs and complex chains of reaction, especially when numerous institutions get involved in business deals that have only a few same underlying transactions. The longer a crisis lasts, the more difficult to find policies that will work effectively. The experience of Japan with her long recession since early 1990s is a notable example. No one knows exactly how long the 2007/2008 crisis will last. It is quite expected that after experiencing a crisis, countries tend to search for appropriate policy response and alternative strategy that will minimize the chance for another crisis in the future. This has been the case in East Asia in the aftermath of the 1997 Asian Financial Crisis (AFC). The failure of the IMF-style policy response spawned a strong desire among East Asian countries to develop a regional self-help financial networking to stabilize the region’s financial sector. What these countries looked for were ways to minimize the likelihood of another crisis and more effective policies to manage the crisis should it hit again in the future. The early proposal to set up an Asian Monetary Fund (AMF) was shelved because of the rejection of the United States and the IMF who argued that it would be an unnecessary duplication since the IMF can continue functioning as a lender of last resort through its Supplementary Reserve Facility (SRF) and Contingent Credit Line (CCL). The counter-argument, however, pointed to the fact that the severity of Asian crisis required fast and large amount of disbursement of liquidity support that put serious constraints on the IMF to act in a timely manner with sufficient financial resources.1 There was clearly a conflict of opinion in

55

56

IWAN J. AZIS

terms of what to do if there is another crisis. China was also not supportive of AMF simply because it did not have the lead role in the concept. The episode, however, did not stop governments in the region from pursuing its efforts to strengthen the cooperation. In May 2000, they declared the Chiang Mai Initiative (CMI) that effectively expanded the swap arrangements among Association of Southeast Asian Nations (ASEAN) countries to include Japan, China and Korea (hence the term ASEANþ3).2 Intended to focus on closer cooperation and concrete regional financial arrangement, the proposal stipulated the importance of regional surveillance and monitoring, particularly of capital flows, and the need to complete a network of bilateral swap arrangements (BSA) that would provide liquidity support for member countries when needed. Although, the name AMF was no longer used to avoid a further conflict, all the above components are essentially the same with what constitutes the IMF’s standard tasks. In the context of growing global imbalances, as already discussed in Chapter 2 Asian countries should take a prominent role in the adjustment process since they are ‘‘major contributors’’ to the imbalances. The necessary adjustments, ranging from fiscal support of domestic demand to monetary and exchange rate policy, will be more effective if coordinated within the region (collective policy adjustments) since the costs and risks associated with the imbalances and the adjustments are perceived differently by individual countries, that is, the attractiveness of adjustments is less if the burden is not shared by others. Absence of coordination can cause the policy adjustments undersupplied. Although some progress in cooperation and coordination had been made, intensified by the need of some countries to utilize the currency swap facility during the 2007/2008 crisis, concrete actions remained constrained by the details to be worked out, the limited political will, and the vicissitudes of domestic political climate. These numerous challenges and the choice of exchange rate system still need to be overcome as and when concrete moves are made toward establishing a formal Regional Financial Arrangement (RFA). One of the ideas being proposed was the use of a currency basket exchange rate system that could, in the long run, lead to a common currency area (CCA) and the establishment of a Currency Union (CU). Supports for this idea rested on a fundamental argument that countries in the region need to have a stable exchange rate to stimulate trade and attract foreign investment. Although there have been signs of de facto managed-floating system in the region, in which the U.S. dollar is no longer the only currency with a substantial weight in the region’s exchange rate movement (Azis & Puttanapong, 2008), there are still many sticking points preventing the

Regional Financial Arrangement

57

region from declaring the use of a basket system. Some of these points are political or noneconomic in nature, making them very difficult to resolve. If RFA with a basket system is pushed without considering these factors, a conflict can easily arise, and the whole idea of regional cooperation can falter. What are those sticking points, and how to analyze them in tandem with standard economic considerations such that a conflict can be averted? How can a compromised solution be reached on the exchange rate system? The bulk of this chapter is devoted to this subject matter. In particular, it is shown how numerous factors – tangibles and intangibles – that reflect the existing and emerging sources of conflicts associated with regional cooperation can be analyzed. These conflicts have caused a delay in the establishment of a formal RFA. It is subsequently shown how the conflicting elements are analyzed and prioritized such that a resolution can be reached. Since the choice of the exchange rate system is at the center of the problem, we begin with the discussions on this subject.

EXCHANGE RATE FLUCTUATIONS Why the choice of exchange rate system matters in RFA? For one thing, every country wants to avoid excessive fluctuations in her exchange rate because they are not compatible with sustainable competitiveness and resource allocation. Excessive fluctuations will also create uncertainty that can affect business plan and investment unfavorably. A fully flexible exchange rate may not be the most preferred system (Kawai & Takagi, 2000). But economists also have long recognized the impossibility of simultaneously pursuing a fixed exchange rate regime, along with independent monetary policy and open capital accounts (the ‘‘impossible trinity’’). Before the crisis in 1997, many emerging market economies in Asia effectively pegged their currencies to the U.S. dollar, pursued independent monetary policies, and liberalized their capital accounts. When the crisis struck, many of these countries scrambled to drop one of the three objectives. Under the pressure from the IMF, they abandoned the fixed exchange rate system, despite the fact that a floating system could pose problems of excessive fluctuations. Only Malaysia chose to impose capital controls and fix the exchange rate, albeit temporarily. Although Singapore and Taipei (China) maintained their managed float currency, Hong Kong (China) kept its currency board system. As a result, a diverse set of exchange rate regimes exists in East Asia. Fluctuations of exchange rate can also be detrimental to growth and macroeconomic stability. Using vector autoregression (VAR) technique

58

IWAN J. AZIS

based on the following equations and the data set for 1993:Q1 to 2007:Q1 with four-quarter lag, we can measure the extent to which such detrimental effect occurred in East Asia 3 D ln Y t ¼ c1 þ

4 X

b1 D ln Y tj þ

j¼1

D ln E t ¼ c2 þ

4 X

4 X j¼1

b2 D ln E tj þ

j¼1

y1 D ln Y tj þ

j¼1

D ln Pt ¼ c3 þ

4 X

4 X

4 X j¼1

b3 D ln Ptj þ e1t

j¼1

y2 D ln E tj þ

j¼1

f1 D ln Y tj þ

4 X

4 X

y3 D ln Ptj þ e2t

j¼1

f2 D ln E tj þ

4 X

f3 D ln Ptj þ e3t

j¼1

where DlnYt is the GDP real growth rate; DlnEt the difference of log exchange rate of local currency against the U.S. dollar; and DlnPt the log difference in consumer price index (CPI) – i.e. inflation; e1t, e2t, and e3t are, respectively, the shocks to GDP growth rate, exchange rate, and inflation rate.4 The set of impulse response functions shown in Fig. 1 are obtained from using Cholesky orthogonalization. With the exception of Taipei (China), Singapore, the Philippines, and Hong Kong (China) (the results are insignificant), fluctuations of the regional exchange rates produce a fairly strong inflationary effect to the regional economy. In the case of Indonesia, the inflationary pressure has been the largest- and longest lasting. The time required for the pressure to subside varies, ranging from three (Korea) to six quarters (Indonesia). A sharp fluctuation (depreciation) of exchange rates has thus been detrimental to the region’s macroeconomic stability.5 The second set of impulse response functions shows the reaction of GDP growth to one standard deviation of exchange rate. Most cases suggest that GDP growth has been adversely affected by the depreciation (only the VAR results for Taipei (China) and Hong Kong (China) are insignificant). Thus, an exchange rate depreciation has not only created an inflationary pressure but also slowed the economic growth. The latter reflects the working of a balance-sheet effect, that is, damage on the balance sheets of corporate and banking sector due to exchange rate depreciation. Under such circumstances, business sector could not expand and banks would have a difficulty to lend. This caused investment and GDP to fall. Many Asian countries were in such a position during the 1997 crisis.

Regional Financial Arrangement

Fig. 1.

Impulse Responses to 1 SD Exchange Rate Shock.

59

60

(Continued)

IWAN J. AZIS

Fig. 1.

Regional Financial Arrangement

61

On the issue of basket system, market seemed to signal that there had been a change in the patterns of influence of major currencies on the regional exchange rates’ movement. Consider the following model: þ b2 DeYen þ b3 DeEuro þ ut Dejt ¼ a þ b1 DeUSD t t t where D ejt is the daily change in the log exchange rate of currency j on date t and ut the disturbances. All exchange rates are measured against the neutral currency (Swiss Franc is used in the current study).6 Applying the model to daily exchange rates data for January 1994–September 2007 reveals that the sum of the statistically significant coefficients is very close to unity.7 As expected, for currencies with a fixed system, that is, the Malaysian ringgit and the Hong Kong dollar, the regression coefficients of the U.S. dollar are close to unity. Note that the regression fit during the crisis is generally lower than during the noncrisis period (regression for the Indonesian rupiah during the second half of 1998 is the only one that produces insignificant coefficients). Normalizing the statistically significant coefficients from the earlier regressions, a set of tables is obtained (excluding the fixers) and shown in Appendix A. It is clear from the Tables that the weights of the U.S. dollar, the yen, and the euro had been changing over the observation period. In most cases, during the post-AFC the weight of the U.S. dollar declined. In the first half of 1998, currency fluctuations in Indonesia, Thailand, and the Philippines were exclusively influenced by the yen movement. Since then, the weights fluctuated. Movements of the Korean won shortly after the country fell into crisis had also been influenced by the yen fluctuation. Since early 2001 the role of the yen generally increased, and during the second half of 2005 all three major currencies influenced the won movement. In general, the role of the yen increased during the post-crisis period, and in some periods the role of the euro also emerged prominently. In Singapore, the Philippines, and Indonesia the weight of the euro reached higher than 40 percent by 2007. The influence of the euro in the Indonesian rupiah movement was even larger than that of the U.S. dollar in that year. After being jointly influenced by the U.S. dollar and the yen, in 2007 the movement of the Thai baht was determined entirely by the U.S. dollar movement, a pattern similar to that during the pre-crisis period. This may be seen as reaffirmation on the claim made by those who predict that the region’s currencies will return to a dollar-standard (e.g., McKinnon, 2000; Ogawa, 2001). Such a claim, however, is premature and is based on only the short-term trend after the crisis. As the tables in Appendix A show, the

62

IWAN J. AZIS

post-crisis role of the euro and especially the yen had generally been prominent in influencing the movements of currencies in the region. One may argue that the sharp fluctuations of regional exchange rates, especially during the AFC, may distort the results. Thus, a series of rolling regressions are conducted by dividing the whole sample into several small subsamples with equal numbers of observation. The daily exchange rate data from January 4, 1994 to September 5, 2007 are divided into subsamples, each having 90 observations. For example, the first sub-sample (daily exchange rates from January 4 to May 12, 1994) is followed by the next sub-sample through shifting the 90-day window by one day (from January 5 to May 13, 1994). In this way, points from the series of each iteration can be added, and the parametric variability can be accommodated. The results of the rolling regressions are displayed in Appendix B.8 It is shown from the results that the basket composition changed quite considerably. Take the case of Indonesia where the weight shifted from a U.S. dollar-dominated to a combined currency-dominated system.9 The trend in other countries also points to a changing weight, that is, the role of the yen and the euro increased, particularly during and after the crisis. During April 1994–May 1998, the Singaporean dollar was mainly based on the U.S. dollar (around 65%–100% of the currency basket), but the pattern changed during May 1998–May 1999; the role of the yen and the euro increased considerably during this period. Although from June 1999 the U.S. dollar recouped the influence, its weight to the basket decreased as the weights of the yen and the euro increased (Appendix B). Thus, the role of the U.S. dollar in the movements of regional currencies (except the fixers) had changed considerably during and after the crisis. In most cases, its role declined. The next question is, did regional exchange rates perform as a shock absorber to a symmetric shock? If they did, the idea of setting the rates through a common basket system could be detrimental to the economy. Based on VAR analysis, it is revealed that the response of regional exchange rates to a symmetric shock was insignificant. The only exception was the Indonesian case, in which a symmetric shock represented by a decline (an increase) in real GDP caused the exchange rate to depreciate (appreciate). However, the rate reverted to the pre-shock level fairly quickly, that is, within three quarters. The case of Hong Kong dollar also showed significant results, but the magnitudes of response were very low, ranging from 0.05 to 0.03 of the rate’s standard deviation. Thus, there is an indication that regional exchange rates did not really perform as a shock absorber to a symmetric shock. For the proponents of a

Regional Financial Arrangement

63

basket peg system, this strengthens their arguments. But as revealed in the next two sections, things are not one-sided. Even if the benefits of such a system can be strongly demonstrated, there are plenty of costs and risks that will prevent those benefits from being realized. Another case of policy conflict therefore arises.

ARTICULATING MAJOR COMPONENTS OF REGIONAL FINANCIAL ARRANGEMENT The framework of analysis to be used to evaluate alternative forms of RFA and the exchange rate system is based on the Analytic Network Process (ANP), which is a generalized version of the Analytic Hierarchy Process (AHP).10 The three alternative forms of RFA to be considered are: (1) RFA with a basket peg system, labeled RFA Basket; (2) RFA with a common exchange rate but not using a basket system, labeled RFA With ER; and (3) RFA without a common exchange rate system (RFA Without ER). In the latter case, each member country is allowed to adopt any system deemed appropriate.11 Note that in all three alternatives there is a sort of exchange rate coordination. In searching for the preferred form, three strategic criteria are set out: securing financial stability (Fin Stability), enabling each country to better manage a crisis (Crisis Management), and strengthening the regional interdependence among ASEANþ3 countries (Interdependence) (Fig. 2). Based on formal documents and statements issued by officials in the region, securing financial stability to prevent a crisis and strengthening the management of a crisis are the most important strategic criteria. To fulfill each of those three criteria, the selected form of RFA will have to be evaluated based on its strengths and weaknesses. Some strengths and benefits can be felt in the short-run (relatively immediately), others may be reaped only in the longer run. Similarly, each alternative of RFA may have short-term weaknesses and long-term costs. In the model framework, the short-term and future benefits are denoted by Benefit (B) and Opportunity (O), respectively, and the short-term and future costs are represented by Cost (C) and Risk (R). Each of the benefits, opportunities, costs, and risks (BOCR) forms a cluster, within which a relevant model for finding the preferred form of RFA is specified. In the Benefit cluster (Fig. 3), there are two-level sub-nets: the first consists of the types of short-term benefits, and the second contains the detailed

64

IWAN J. AZIS

Goal Search For RFA Form

Strategic Criteria

Fin Stability

Crisis Mgt

Interdependence

Model

Benefit

Fig. 2.

Opportunity

Cost

Risk

Searching for Preferred Form of RFA: Model Framework.

network model in each of those types.12 The four types of short-run benefits are: providing greater latitude for risk sharing among member countries (labeled Risk Sharing), making macro and exchange rate coordination more possible (Macro & ER Coordination), strengthening the capacity of each country to avert a potential contagion from others (Contagion), and enabling investors in each country to avoid a double Mismatch, that is, in currency and maturity mismatch. In the benefit of Risk Sharing network, the choice of RFA will influence – and be influenced by – the opportunity for each country to activate and strengthen the swap facility (Reserve Pool). In line with the CMI, the swap arrangement can eventually be multilateralized by earmarking a portion of foreign exchange reserves held by ASEANþ3 countries for financing members’ short-term liquidity needs.

65

Regional Financial Arrangement Benefit Risk Sharing

Goal

Macro & ER Coordination

Goal

RFA Basket

RFA Basket

RFA With ER

RFA With ER

RFA Without ER

RFA Without ER Smoothing

Reserve Pool Consumption

Macro

Speed Investment

Investment Growth

Uncertainty

Overheating

Size GDP

Mismatch

Goal

Contagion

Goal

RFA Basket

RFA Basket

RFA With ER

RFA With ER

RFA Without ER

RFA Without ER ER

Surveilance Safeguard

Monitoring

Financing

ER Stability ABM

ADF

Fig. 3.

Searching for Preferred Form of RFA: Benefit Model.

Slow disbursements and a relatively small size of IMF’s support during the AFC may have deepened the confidence problem that has led to a rapid fall in regional currencies. Under the selected RFA, these problems can be overcome. Thus, in the Reserve Pool cluster there are two nodes: Speed and Size (Fig. 3). Another type of benefits related to the risk sharing is to have a greater scope for smoothing of Consumption, Investment, and GDP. The degree of risk sharing in Asia has been low, in contrast to the continually growing regional integration especially in the trade area. Once RFA is formally established, the level of smoothing is expected to increase, allowing member counties to benefit from the risk sharing.

66

IWAN J. AZIS

Another benefit of RFA is to allow members to conduct macroeconomic and exchange rate coordination (recall that all three forms of RFA involve some degrees of exchange rate coordination). This will contribute directly to stabilization and growth by reducing the uncertainty.13 Making the exchange rate coordination explicit and formal could also rule out forestalling cascading speculation. This will contribute to the results for the Asian Bond Market (ABM) and the Asian Development Fund (ADF). Such coordination, however, should be approached cautiously. More so than the one in surveillance and reserves pooling because it requires substantial trust-building and political consensus. In the context of reducing the global imbalances, given the region’s saving–investment gap the most important and realistic outcome expected from the coordination is a more favorable environment for Investment Growth and lowering Uncertainty. Macroeconomic coordination can also provide a basis for surveillance, from which each country can safeguard from a possible contagion. Thus, another benefit cluster is to avoid Contagion. Since contagion effects of financial troubles can affect countries within a region more severely, and a regional mechanism will respond more quickly to a financial crisis, providing Safeguard is ranked the highest, followed by Monitoring. Having learned the hard lesson from holding a double mismatch that led to a financial collapse in 1997, the benefit of reducing such a possibility is also notable. On the one hand, with or without an exchange rate arrangement the RFA can still stabilize the exchange rate (ER Stability); on the other hand, the possibility of a maturity mismatch can be drastically reduced by enhancing the ABM and the ADF. Fig. 3 displays all four clusters under the benefit of RFA. Whatever form of RFA being selected, another set of benefits may also be reaped albeit not in the short-run; it is a kind of Opportunity. Two clusters for these long-run benefits are: improvements in the Capital Market and a larger scope for stronger Supervision. The development of capital market can provide an opportunity for agents to diversify risks (Risk Diversity) and to raise capital from sources other than banks. In some member countries, post-crisis disintermediation had become a binding constraint to lending and investment growth. With a stronger capital market, problems in Intermediation can be partly solved. Meanwhile, the stability provided by RFA is likely to attract Capital Inflow (Fig. 4). If ABM and ADF can be strengthened, regional and Local Capital can also be channeled toward investment within the region, narrowing down the saving–investment gap and contributing to the rotation of demand away from exports (especially to the United State) in favor of regional sources.

67

Regional Financial Arrangement Opportinity Goal

Capital Market

RFA Basket RFA With ER RFA Without ER Source of Financing

Function Risk Diversity

Capital Inflows

Intermediation

Supervision

Local Capital

Goal

RFA Basket RFA With ER RFA Without ER

Challenges Credibility

Fig. 4.

Best Practice

Searching for Preferred Form of RFA: Opportunity Model.

68

IWAN J. AZIS

Along with the completion of the Asian free trade area, this will help reduce the global imbalances. However, it will take some time before these benefits can take effect.14 Establishing RFA will also provide an opportunity for the region to strengthen the Supervision function needed to secure financial stability. The choice of RFA, in this context, will depend on the extent to which the region can meet the formidable challenges in terms of maintaining good Credibility of the supervision and keeping it up with the international standard (Best Practice).15 Although the two are equally important, maintaining credibility is considered more critical in the longer run. Of course, credibility has to be grounded on a reliable judicial system, transparency, and well-defined institutional responsibilities. Strong and reliable legal and regulatory frameworks are the foundations on which the credibility of supervision and financial stability (or of any policy for that matter) rests.16 The Cost cluster in the model contains two subnets: Coordination and Moral Hazard (Fig. 5). One of the worst scenarios is if the selected RFA fails to coordinate members such that the outcome leaves all member countries worse off. This Coordination Failure is the most important node within Coordination subnet. Asia is a complex and heterogeneous entity. When benchmarked to the United States and Japan, the region’s two important trade and investment partners, the differences are equally striking. This Heterogeneity problem is likely to create difficulties in coordination. In the Moral Hazard subnet, ineffectiveness of adopting the agreed Criteria (e.g., for reserve swap) is most costly to the RFA. Without a Cost Moral

Goal

Coordination

Goal

Hazard RFA Basket

RFA Basket

RFA With ER

RFA With ER

RFA Without ER

RFA Without ER Ineffectiveness

Problems Coordination Failure

Fig. 5.

Problem Source

Criteria

Political Pressure

Conditionality

Complacency

Heterogeneity

Searching for Preferred Form of RFA: Cost Model.

Regional Financial Arrangement

69

sufficient degree of compliance, the criteria are ineffective. The same applies to the agreed Conditionality (Fig. 5). Lack of criteria adoption and low degree of compliance to conditionality will not only cause a credibility problem but more seriously it can lead to a total break down of the system, for example, reserve-surplus countries cease to participate. Even if this can be prevented, moral hazard can still be widespread no matter what form of RFA being selected. Since 1997, member countries have been moving away from fixed exchange rates and making some progress toward reform of their financial infrastructure. With the recovery process in place, the next greatest danger is complacency. In a similar manner, there is a risk that Complacency will emerge once the RFA is established. Having many agreements reached during the process of establishing RFA, it may be tempted to say that no further work needs to be done. Domestic Political Pressure, especially when combined with the region’s tradition of no-intervention, can also derail the process by which each member country and the RFA will have no opportunity to gain from acting contrary to the principles laid out by the agreement. Host government policies toward different types of foreign capital, for example, can shape the environment in which foreign capital participates in domestic policy process. Domestic sensitivity and sentiments against foreign capital can determine the political strength of foreign capital, including the strength of traditional policy networks, the presence of domestic allies (e.g., NGOs), and the quality of idea markets (e.g., media and think tanks). When RFA rules are considered too stringent, some agents may not see the strong need to meet the terms because they can get away by hiding behind these domestic forces. Thus, strong domestic political pressures can exacerbate the moral hazard problem (Fig. 5). Even if intensive efforts are made to avoid the presence of moral hazard, there remain some risks of no compliance for reasons ranging from lack of enforcing institution to absence of strong political will. Thus, in the Risk cluster there is a node representing Compliance (Fig. 6). The relevant institution under RFA must promote, among others, the development of private markets, which has been hindered by problems of coordination, lack of credibility, and problems of surveillance. Looking at the experience of ASEAN, despite the existence of a formal secretariat (strengthened in 1992), the region still does not have a central institution to call member states to always account for noncompliance (e.g., on rules for reserve composition disclosure to facilitate the coordination of reserve diversification and avoid destabilizing policy shifts). There is no reason that a similar faith will not

70

IWAN J. AZIS Risk Goal

Compliance

Synchronized

Goal

RFA Basket

RFA Basket

RFA With ER

RFA With ER

RFA Without ER

RFA Without ER Constraints

Institution Potential Conflict Asymmetry Multilateral

Central Institution

Domestic

Political Will

Fig. 6.

Searching for Preferred Form of RFA: Risk Model.

happen with the planned RFA. Yet, it is extremely difficult to expect a wellfunctioning arrangement without strong Central Institution (Fig. 6). Asymmetry can also create a serious problem. RFA typically involves an asymmetrical distribution of costs and benefits across member countries. In view of significant externalities in the provision of RFA services (e.g., reserve swap, surveillance, and monitoring), it is important that countries coordinate in the design and implementation of the programs from a regional perspective. After all, this is one of the important reasons for setting up a financial arrangement at the regional level. But it is also the same reason for which member countries may fall short of compliance. If, due to Asymmetry in the cost and benefit distribution some members cannot exploit economies of scale and externalities in a way that will overcome their original weaknesses, there will not be enough incentives for them to comply with the RFA agreements. Some argue that a major hindrance to an effective RFA in Asia is the area’s lack of historical experience in regionalism. Whatever economic benefits the RFA may bring, they are unlikely to be realized if each member country is unwilling to cooperate in the political arena. China and Japan need to play a key role in developing a common Political Will in the region.17 This author has argued elsewhere that ‘‘most serious risk is the lack of a concrete political integration . . . As long as there is no willingness to pool political sovereignty to make room for the creation of regional political institution with real power, any forms of RFA would not be effective. The absence of clear regional leadership and consensus only

Regional Financial Arrangement

71

worsens the situation . . . ’’ (Azis, 2005c). Thus, lack of Political Will can derail the process of securing a well functioning RFA (Fig. 6).18 The last Risk subnet is related to the difficulty of the system to be Synchronized with other standards, rules, and regulations imposed either by Multilateral institutions (e.g., the IMF) or sovereign governments. Potential conflicts may arise, for example, when the standard of surveillance is not the same, and consequently the assessment over the state of the economy is also different. At the multilateral level, this will raise concerns about the possibility that some member countries receiving IMF support and RFA swap facility might bypass the IMF conditionality and receive easy money from the RFA because of differences in the assessment. Conflicts can also arise due to the inaptness of RFA rules with Domestic standards (Fig. 6). Although, the extent of the potential conflict may not be as great as that caused by the sharply different views about the causes of – and appropriate policy response to – a crisis, the problem of domestic standards not being synchronized with RFA rules can have significant consequences on the sustainability of the RFA.19

PRIORITIZING BENEFITS, OPPORTUNITIES, COSTS, AND RISKS Having ranked the importance of each node in each cluster and subnet, and using the pairwise-comparisons to generate ratio scales, results of the calculation are as follow. Of the three strategic criteria, securing financial stability and managing crisis are the highest-ranked. As indicated earlier, this is consistent with formal documents and official statements supporting the establishment of a regional arrangement. In the Benefit cluster under Risk Sharing subnet, RFA with a basket exchange rate system (RFA Basket) is ranked the highest with respect to both speedy disbursement and consumption smoothing. Looking at the feedback effect, the speedy disbursement of fund through reserve pool and swap arrangement is perceived to be most important under RFA Basket.20 Despite the limited risk sharing among Asian countries, the benefits of risk sharing through consumption smoothing are still considered most important under the RFA. Thus, from this viewpoint a basket system is superior. However, that is not the case with the benefits of having a greater scope for macro and exchange rate coordination. The ANP calculation under this scenario shows that boosting investment growth in each country is

72

IWAN J. AZIS

considered most important, and is consistent with the efforts to mitigate the problem of global imbalances. Consequently, the preferred RFA is the one without any exchange rate arrangement (RFA Without ER). Neither a basket system nor any other imposed exchange rate arrangement is preferred. That is, the established RFA should allow each country to adopt whatever exchange rate regime deemed appropriate. It is the stability – not a particular regime – of exchange rate that matters in this scenario. The same is true for the benefits of avoiding contagion, in which safeguarding member country is ranked the highest. As financial openness increases, and financial integration deepens, external shocks can be easily transmitted to the region from which a contagion may result. This calls for even greater efforts to strengthen the regional financial safeguards by allowing each member country to make necessary adjustments. Thus, RFA Without ER is even more preferred (the normalized eigenvalue is higher than under Macro & ER Coordination subnet, that is, 0.5802 versus 0.4696; see Appendix D for the details). From the perspective of benefits to avoid a double mismatch, the currency mismatch part can be prevented if the selected RFA is able to make the exchange rate more stable. The part on the maturity mismatch, however, is preventable if the RFA can strengthen the ABM and expand the ADF. To effectively avoid the double mismatch, an exchange rate system based on a basket of major currencies (RFA Basket) is more preferred than the other two alternatives. Thus, viewed from the two types of benefit, Risk Sharing and Mismatch, RFA with a basket system is ranked at the top. For the other two types (Macro & ER Coordination and Contagion) RFA without imposing and targeting an exchange rate system is ranked the highest (Table 1). Note that these outcomes are based on a network – not a hierarchical – system. Thus, the feedback effects from different forms of RFA to each subnet have been taken into account. The outcomes are therefore more Table 1. Graphic

Net Results (Ranking) of the Benefits Cluster with Feedback Effects. Alternatives

Total

Normal

Ideal

Ranking

RFA basket

0.7999

0.3848

1.0000

1

RFA with ER

0.5064

0.2437

0.6331

3

RFA without ER

0.7721

0.3715

0.9653

2

73

Regional Financial Arrangement

stable. After weighting the priority of the four subnets, the net result indicates that given all the information and considerations, the region will be better off if the RFA is established with neither imposing a basket system nor targeting any common currency regime. As discussed earlier, the earlier benefits can take effect relatively immediately after the RFA is formed. But there are two other potential benefits (opportunities) that can be reaped after the arrangement operates for some time, that is, enhancing the capital market and strengthening the supervision. With improved capital market, there is a greater scope for member countries to diversify risks and attract capital inflows, especially if the exchange rate stability can be maintained. Since the latter is more probable with a basket system, RFA Basket is ranked the highest. This alternative is also preferred under a scenario where member countries will have an opportunity to strengthen the financial supervisions. With stronger supervisions, the basket system will be more credible. Therefore, similar to the earlier analysis on the possible immediate benefits, viewed from the future benefits (opportunities) a basket system is also most preferred (Table 2).21 The earlier analysis, however, still neglects the costs and potential risks that may arise in RFA Basket. Results of the calculation for the Cost cluster show that the difficulty to coordinate and the undesirable effect of moral hazard put RFA Basket in the most costly category. Coordination failure and the fact that the region is not homogenous tend to create a serious problem with RFA coordination especially under a basket system.22 However, the difficulty to meet the agreed criteria combined with the presence of a strong domestic political pressure is likely to derail the process of achieving the benefits from such a system. Thus, while RFA Basket is preferred under the Benefit cluster, it is least preferred under the Cost cluster (Table 3). The European experience demonstrates how expensive it is to defend and maintain such a system. Table 2. Graphic

Net Results (Ranking) of the Opportunity Cluster with Feedback Effects. Alternatives

Total

Normal

Ideal

Ranking

RFA basket

1.0000

0.4935

1.0000

1

RFA with ER

0.5494

0.2711

0.5494

2

RFA without ER

0.4771

0.2354

0.4771

3

74

IWAN J. AZIS

Table 3. Graphic

Alternatives

Table 4. Graphic

Net Results (Ranking) of the Cost Cluster with Feedback Effects. Total

Normal

Ideal

Ranking

RFA basket

1.0000

0.6925

1.0000

1

RFA with ER

0.2891

0.2002

0.2891

2

RFA without ER

0.1550

0.1073

0.1550

3

Net Results (Ranking) of the Risk Cluster with Feedback Effects. Alternatives

Total

Normal

Ideal

Ranking

RFA basket

1.0000

0.6389

1.0000

1

RFA with ER

0.3220

0.2057

0.3220

2

RFA without ER

0.2433

0.1554

0.2433

3

Not only short-term costs that make RFA Basket least preferred. The longer-term costs also make it very risky (Table 4). This is particularly true for the risks of noncompliance that may be caused by a lack of effective central institution to call member-states to always account for deviating from agreements, and by the asymmetrical distribution of costs and benefits across member countries.23 A slightly less pronounced is the risk that RFA standards are not matched with those set out by the multilateral institutions or sovereign governments (e.g., different standards of surveillance lead to different assessments about the state of the economy). To sum up, while establishing RFA with a basket exchange rate system can provide many short- and long-run benefits, it may also entail high costs and large risks. It is, therefore, important to weigh all costs and benefits before deriving any conclusion and making any recommendation. By assigning equal rating to the benefit (B), the opportunity (O), the cost (C), and the risk (R), there is a number of ways BOCR can be combined.24 Using ‘‘Additive-Negative’’ approach, the final ranking is: 0.2352, 0.5226, and 1.0 for, respectively, RFA Basket, RFA With ER, and RFA Without ER.25 That is, RFA without imposing and targeting any exchange rate system is the most preferred. Thus, this observation makes clear that

75

Regional Financial Arrangement

an attempt to suppress intraregional exchange rate movements will be counterproductive. In the context of making adjustments to reduce the global imbalances, it is a recipe for inaction to minimize the risk of a disorderly correction. Under what circumstances will a basket system be ranked the highest? Looking carefully at the results of calculation, such a scenario can occur when preferences for the benefit and opportunity are set higher than for the cost and risk. An unequal BOCR rating is not entirely impossible if the interest and optimism toward regional arrangement gets very strong, for example due to the growing concerns over another meltdown associated with the 2007/2008 crisis. Only with such a sanguine view toward regional arrangement that a basket system will be chosen. Fig. 7 shows the results from two scenarios of different BOCR ratings. Another interesting comparison is with the case without feedback effects, that is, the influence from criteria (Risk Sharing, Contagion, etc.) to alternatives (the forms of RFA) flows only downward. This is a hierarchical setting that can be solved using AHP, where the arrows in Figs. 3–6 are all set to point only to downward direction. Although, in general, the results are less stable than the case with feedback effects, it is not uncommon that policy and decision makers view the problem in this fashion. Results of the calculation using AHP show that, regardless of the BOCR rating the preferred RFA is always the one without imposing or targeting any exchange rate regime (Fig. 8).26 How sensitive are the earlier results to BOCR ratings? The unequal rating used in Figs. 7 and 8 is only one of the many combinations. To synthesize

Equal Rating Unequal Rating

RFA Without ER

RFA With ER

RFA Basket

-0.4

Fig. 7.

-0.2

0

0.2

0.4

0.6

0.8

1

Results with Feedback Effects (Network) under Different BOCR Ratings.

76

IWAN J. AZIS

Equal Rating

RFA Without ER

Unequal Rating

RFA With ER

RFA Basket

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Fig. 8. Results without Feedback Effects (Hierarchy) under Different BOCR Ratings.

Fig. 9.

Sensitivity with Respect to Benefit and Opportunity.

77

Regional Financial Arrangement

Fig. 10.

Sensitivity with Respect to Cost and Risk.

the whole range of BOCR combinations, a sensitivity analysis is conducted, the results of which are shown in Fig. 9. It is clear that the adoption of a basket-based exchange rate system is preferred only when the weight assigned to the benefit and opportunity is set high, that is, greater than 0.90 for benefit and larger than .45 for opportunity. However, evaluating the sensitivity with respect to cost and risk makes virtually impossible for RFA Basket to be ranked highest (Fig. 10). This is the reason why under an equal BOCR rating discussed earlier the basket system is not preferred.

NOTES 1. A case in point was the far too small supplementary support from the IMF to Thailand and Indonesia during the 1997 crisis. The disbursement of financial support was also not timely, because it was done in several tranches. 2. The Association of Southeast Asian Nations (ASEAN) was founded on August 8, 1967. It is geo-political and economic organization of 10 countries located in Southeast Asia. 3. VAR quantifies the reaction of every single variable in the model (i.e., GDP growth and inflation) on an exogenous shock (i.e., exchange rate fluctuation).

78

IWAN J. AZIS

The imposed shock mirrors the residual covariance structure of the model, and the idea is how to investigate the orthogonalized impulse responses. The reaction is measured for every variable in a certain time period (i.e., a number of quarters) after shocking the system. In the calculation, the optimal lag length was selected using Akaike Information Criterion (AIC). To ensure the robustness of lag length selection, the impulse responses obtained from using a lag length of 3–7 quarters are compared. Results show that they are very similar in both response-to-shock patterns and levels of significance. 4. Macrodata are obtained from the International Financial Statistics (IFS) and CEIC database. All log-difference time series pass the unit-root test except that of Hong Kong’s (China) CPI. Thus, we use the second log-difference for Hong Kong’s (China) CPI. 5. Studies confirming the importance of demand shocks in explaining exchange rate fluctuations are usually based on industrial countries cases. 6. Daily exchange rate data are from PACIFIC Exchange Service, University of British Columbia (http://fx.sauder.ubc.ca/data.html). 7. Data on the Indonesian rupiah and the Philippines peso are from January 2, 1996–September 2007, whereas those on other currencies cover the period of January 3, 1994–September 5, 2007 (the last period is January 2, 2007–September 5, 2007). 8. As each new observation is acquired, another observation may be removed so that at any instant the estimator comprises only n points. Such an estimator is the result of rolling regression. 9. It should be noted, however, that the results of the rupiah-rolling regressions for some periods are insignificant. For example, no comovements of the rupiah and other major currencies are detected during January 16, 1998–February 11, 1998, September 11, 1998–October 20, 1998, and December 17, 1998–January 12, 1999. 10. A summary of AHP can be found in Azis and Isard (1996), and brief descriptions of ANP are given in Appendix C. 11. Note that RFA Basket may take a less rigid form, that is, a basket system but not pegged or fixed. A noted example is a basket-band-crawl (BBC) system. 12. Unlike in a hierarchy, in a network system the feedback effects are taken into account. Thus, the alternatives can depend on the criteria as in a hierarchy but they may also depend on each other. The criteria themselves can depend on the alternatives and on each other as well. It has been proven that the results of such a network model are more stable because one can consider the influence on and survival in the face of other influences. Thus, the arrows at the bottom level of each block in Figs. 4–7 point to both directions (a network system). 13. Take the case of currency realignment. Individual countries may be reluctant to allow their currencies to appreciate if this will damage their competitiveness in other Asian markets as well as in markets outside the region. Thus, in the absence of an agreement on concerted action, the willingness to appreciate the currency is limited (free rider problem). A scenario of joint appreciation is therefore preferable, and it can be bolstered by the adoption of a particular exchange rate system, for example, common basket peg, or a common basket, band and crawl (BBC) regime. In such a case, the coordination efforts can focus only on monitoring the behavior of

Regional Financial Arrangement

79

exchange rates themselves, as opposed to ascertaining the consistency of the entire range of national policies (Eichengreen, 2006). 14. The benefits for the region are not the same with the narrowing of global imbalances. The latter may take a longer time because it depends not only on the response of the Asian countries but, more importantly, on the U.S. policy reaction. 15. One of the principal tools for strengthening supervision, domestic policies, and institutions is international best-practiced information in financial sector regulation and supervision, and capital market infrastructure. 16. Malaysia’s capital control imposed immediately after the crisis is a case in point. The controls had a salutary effect not only because they were temporary and supported by a strong macroeconomic framework and accompanied by bank and corporate restructuring, but more importantly they were implemented with credible supervision. 17. In 2003, the then Japanese vice minister of finance Sakakibara argued that the role of China and Japan in Asia’s integration process is synonymous with that of France and Germany in Europe’s integration process. In the report submitted to the fourth gathering of the finance ministers of the Asia-Europe Meeting (ASEM) held in Copenhagen in July 2002, the so-called Kobe Research Project states that ‘‘It is essential for the Japan-China cooperation, as a core in East Asia, to lead the process of economic and financial integration, as the France-German alliance played a central role in the integration and cooperation process in Europe.’’ 18. Lack of political will can also arise from a lack of trust. This is particularly true when a proposal floated by one country, for example, designating the location of RFA head quarter, is viewed with suspicion by other member countries. 19. Detailed analysis on the differences between the IMF perspectives and the alternative views about the causes of, and the policy response to, the Asian crisis can be found in Azis (2005a). 20. The typical question in this case is: to obtain the benefit of speedy disbursement, which of three alternative forms of RFA has greater relevance (or is more preferred)? An example of the question for the feedback channel is: under RFA Basket, which of the two benefit criteria is more likely to be achieved (Speed or Size)? 21. The complete ranking for each subnet in the benefit, opportunity, cost, and risk clusters derived from the ANP calculation is shown in Appendix D. 22. The fact that the Asian identity, economic and cultural wise, remains strange to many Asians, may worsen the heterogeneity problem. 23. It is worth noted that Asia has benefited considerably from the interactions with the global market. Thus, greater regional integration should not – and need not – come at the expense of the region’s increased engagement with the rest of the world. 24. Rating the BOCR is necessary because in real world the importance of each component of the BOCR is often weighted differently (Saaty, 1996). The standard benefit/cost approach (Multiplicative) is to take the ratio of benefit (B) times opportunity (O) over costs (C) times risk (R) (see, e.g., Azis, 2005c). In the current study, however, ‘‘Additive-Negative’’ method is used where the results can be validated under any circumstances for any scales (e.g., can be compared with negative numbers).

80

IWAN J. AZIS

25. Note that the ideal – instead of the normal – ranking is used because negative numbers are present. I thank Thomas and Rozann Saaty for explaining the main rationale why ‘‘Additive-Negative’’ approach is superior than others. As it turns out, the final ranking based on the ‘‘Multiplicative’’ approach is: 0.8000, 2.9900, and 9.7709 for RFA Basket, RFA With ER, and RFA Without ER, respectively. Thus, while the priority numbers are different, the resulting ranking from the two approaches is the same. 26. In applying AHP, here it is specified that all subnets under each cluster of the BOCR are weighted equally.

APPENDIX A Table A1. Period 1994/01–1994/06 1994/07–1994/12 1995/01–1995/06 1995/07–1995/12 1996/01–1996/06 1996/07–1996/12 1997/01–1997/06 1997/07–1997/12 1998/01–1998/06 1998/07–1998/12 1999/01–1999/06 1999/07–1999/12 2000/01–2000/06 2000/07–2000/12 2001/01–2001/06 2001/07–2001/12 2002/01–2002/06 2002/07–2002/12 2003/01–2003/06 2003/07–2003/12 2004/01–2004/06 2004/07–2004/12 2005/01–2005/06 2005/07–2005/12 2006/01–2006/06 2006/07–2006/12 2007/01–2007/09

Hong Kong (China) Dollar.

US Dollar (%) 100.00 100.00 100.00 100.00 98.02 100.00 100.00 100.00 100.00 96.55 100.00 96.79 100.00 100.00 100.00 100.00 100.00 100.00 100.00 96.16 95.88 98.15 96.29 98.57 99.08 97.62 100.00

Euro(%)

Yen (%)

1.98

3.45 3.21

3.36 2.34

3.84 0.76 1.85 1.37 1.43 0.92 2.38

81

Regional Financial Arrangement

Table A2. Period 1996/01–1996/06 1996/07–1996/12 1997/01–1997/06 1997/07–1997/12 1998/01–1998/06 1998/07–1998/12 1999/01–1999/06 1999/07–1999/12 2000/01–2000/06 2000/07–2000/12 2001/01–2001/06 2001/07–2001/12 2002/01–2002/06 2002/07–2002/12 2003/01–2003/06 2003/07–2003/12 2004/01–2004/06 2004/07–2004/12 2005/01–2005/06 2005/07–2005/12 2006/01–2006/06 2006/07–2006/12 2007/01–2007/09

US Dollar (%)

1994/01–1994/06 1994/07–1994/12 1995/01–1995/06 1995/07–1995/12 1996/01–1996/06 1996/07–1996/12 1997/01–1997/06 1997/07–1997/12 1998/01–1998/06 1998/07–1998/12 1999/01–1999/06 1999/07–1999/12 2000/01–2000/06

Euro (%)

Yen (%)

100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 84.50 77.20 59.63 100.00 100.00 69.13 48.40 40.31

Table A3. Period

Indonesian Rupiah.

15.50 22.80 40.37

30.87 51.60 59.69

Malaysian Ringgit.

US Dollar (%) 100.00 89.38 69.56 87.55 100.00 95.23 100.00 100.00 72.33 100.00 100.00 100.00

Euro (%)

Yen (%)

10.62 30.44 12.45 0.00 4.77

100.00 27.67

82

IWAN J. AZIS

Table A3. Period 2000/07–2000/12 2001/01–2001/06 2001/07–2001/12 2002/01–2002/06 2002/07–2002/12 2003/01–2003/06 2003/07–2003/12 2004/01–2004/06 2004/07–2004/12 2005/01–2005/06 2005/07–2005/12 2006/01–2006/06 2006/07–2006/12 2007/01–2007/09

US Dollar (%) 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 90.58 80.94 65.97

Table A4. Period 1996/01–1996/06 1996/07–1996/12 1997/01–1997/06 1997/07–1997/12 1998/01–1998/06 1998/07–1998/12 1999/01–1999/06 1999/07–1999/12 2000/01–2000/06 2000/07–2000/12 2001/01–2001/06 2001/07–2001/12 2002/01–2002/06 2002/07–2002/12 2003/01–2003/06 2003/07–2003/12 2004/01–2004/06 2004/07–2004/12 2005/01–2005/06 2005/07–2005/12 2006/01–2006/06 2006/07–2006/12 2007/01–2007/09

(Continued ) Euro (%)

Yen (%)

9.42 19.06 34.03

Philippines Peso.

US Dollar (%)

Euro (%)

Yen (%)

100.00 100.00 100.00 100.00 80.60 78.48 100.00 100.00 100.00 100.00 100.00 100.00 100.00 84.60 100.00 93.53 100.00 100.00 77.95 100.00 84.08 56.11

100.00 19.40 21.52

15.40 6.47

22.05 15.92 42.89

83

Regional Financial Arrangement

Singapore Dollar.

Table A5. Period 1994/01–1994/06 1994/07–1994/12 1995/01–1995/06 1995/07–1995/12 1996/01–1996/06 1996/07–1996/12 1997/01–1997/06 1997/07–1997/12 1998/01–1998/06 1998/07–1998/12 1999/01–1999/06 1999/07–1999/12 2000/01–2000/06 2000/07–2000/12 2001/01–2001/06 2001/07–2001/12 2002/01–2002/06 2002/07–2002/12 2003/01–2003/06 2003/07–2003/12 2004/01–2004/06 2004/07–2004/12 2005/01–2005/06 2005/07–2005/12 2006/01–2006/06 2006/07–2006/12 2007/01–2007/09

US Dollar (%)

Euro (%)

Yen (%)

57.98 100.00 100.00 78.09 84.24 91.18 85.76 85.31 18.14 67.66 61.55 100.00 86.70 87.80 81.67 73.56 77.63 65.30 69.25 77.95 47.13 73.09 63.91 66.39 68.56 50.61 57.35

32.47

9.55

Table A6. Period 1994/01–1994/06 1994/07–1994/12 1995/01–1995/06 1995/07–1995/12 1996/01–1996/06 1996/07–1996/12 1997/01–1997/06 1997/07–1997/12 1998/01–1998/06

35.80 26.72

26.79

31.31 42.65

21.91 15.76 8.78 14.24 14.69 46.16 32.34 11.73 13.30 12.20 18.34 26.44 22.37 34.70 30.75 22.05 26.09 26.91 36.09 33.61 31.44 18.08

South Korea Won.

US Dollar (%)

Euro (%)

88.41 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00

11.60

Yen (%)

84

IWAN J. AZIS

Table A6. Period 1998/07–1998/12 1999/01–1999/06 1999/07–1999/12 2000/01–2000/06 2000/07–2000/12 2001/01–2001/06 2001/07–2001/12 2002/01–2002/06 2002/07–2002/12 2003/01–2003/06 2003/07–2003/12 2004/01–2004/06 2004/07–2004/12 2005/01–2005/06 2005/07–2005/12 2006/01–2006/06 2006/07–2006/12 2007/01–2007/09

US Dollar (%) 88.50 87.48 100.00 100.00 100.00 60.57 79.87 77.79 60.38 66.00 72.18 78.15 75.88 68.66 51.04 73.86 71.62 71.58

Table A7. Period 1994/01–1994/06 1994/07–1994/12 1995/01–1995/06 1995/07–1995/12 1996/01–1996/06 1996/07–1996/12 1997/01–1997/06 1997/07–1997/12 1998/01–1998/06 1998/07–1998/12 1999/01–1999/06 1999/07–1999/12 2000/01–2000/06 2000/07–2000/12 2001/01–2001/06 2001/07–2001/12 2002/01–2002/06 2002/07–2002/12

(Continued ) Euro (%)

Yen (%) 11.50 12.52

34.95

39.43 20.13 22.21 39.62 34.00 27.82 21.85 24.12 31.34 14.01 26.14 28.38

28.42

Taipei (China) Dollar.

US Dollar (%) 100.00 100.00 67.75 100.00 100.00 100.00 100.00 75.60 77.68 73.98 100.00 100.00 100.00 100.00 100.00 100.00 91.04 100.00

Euro (%)

Yen (%)

14.30

17.95

24.40 17.84

22.32 8.18

8.96

85

Regional Financial Arrangement

Table A7. Period 2003/01–2003/06 2003/07–2003/12 2004/01–2004/06 2004/07–2004/12 2005/01–2005/06 2005/07–2005/12 2006/01–2006/06 2006/07–2006/12

(Continued )

US Dollar (%) 100.00 90.83 89.25 88.16 67.17 100.00 83.42 84.07

Table A8. Period 1994/01–1994/06 1994/07–1994/12 1995/01–1995/06 1995/07–1995/12 1996/01–1996/06 1996/07–1996/12 1997/01–1997/06 1997/07–1997/12 1998/01–1998/06 1998/07–1998/12 1999/01–1999/06 1999/07–1999/12 2000/01–2000/06 2000/07–2000/12 2001/01–2001/06 2001/07–2001/12 2002/01–2002/06 2002/07–2002/12 2003/01–2003/06 2003/07–2003/12 2004/01–2004/06 2004/07–2004/12 2005/01–2005/06 2005/07–2005/12 2006/01–2006/06 2006/07–2006/12 2007/01–2007/09

Euro (%)

US Dollar (%) 100.00 100.00 100.00 86.02 100.00 100.00 73.91 100.00 40.76 59.85 100.00 90.41 71.78 76.00 86.63 79.82 64.69 76.81 80.36 61.71 65.94 64.83 66.93 66.79 77.30 100.00

Yen (%)

9.17 10.75 11.84 32.83 16.58 15.93

Thai Baht. Euro (%)

5.60

Yen (%)

8.38

26.09

41.38 24.20

19.46

100.00 17.84 15.95 9.59 28.22 24.00 13.27 20.18 35.31 23.19 19.64 18.83 34.06 35.17 33.07 33.21 22.70

86

IWAN J. AZIS

APPENDIX B

Fig. B1.

Hong Kong (China) Dollar.

Currency Basket: Indonesian Rupiah 100% 90% 80%

60% 50% 40% US Dollar Euro Yen

20% 10%

Fig. B2. Indonesian Rupiah.

3/26/2007

3/26/2006

3/26/2005

3/26/2004

3/26/2003

3/26/2002

3/26/2001

3/26/2000

3/26/1999

3/26/1998

3/26/1997

0% 3/26/1996

Proportion

70%

87

Regional Financial Arrangement Currency Basket: Malaysian Ringgit 100% 90% 80%

Proportion

70% 60% US Dollar Euro Yen

50% 40% 30% 20% 10%

Fig. B3.

5/9/2007

5/9/2006

5/9/2005

5/9/2004

5/9/2003

5/9/2002

5/9/2001

5/9/2000

5/9/1999

5/9/1998

5/9/1997

5/9/1996

5/9/1995

5/9/1994

0%

Malaysian Ringgit.

Currency Basket: Philippines Peso 100% 90% 80%

60% 50%

US Dollar Euro Yen

40% 30% 20% 10%

Fig. B4. Philippines Peso.

3/26/2007

3/26/2006

3/26/2005

3/26/2004

3/26/2003

3/26/2002

3/26/2001

3/26/2000

3/26/1999

3/26/1998

3/26/1997

0% 3/26/1996

Proportion

70%

Fig. B6.

South Korea Won.

5/9/2007

5/9/2006

5/9/2005

5/9/2004

5/9/2003

5/9/2002

5/9/2001

5/9/2000

5/9/1999

40%

5/9/1998

50%

5/9/1997

5/9/2007

5/9/2006

5/9/2005

5/9/2004

5/9/2003

5/9/2002

5/9/2001

5/9/2000

5/9/1999

5/9/1998

5/9/1997

40%

5/9/1996

5/9/1995

5/9/1994

Proportion 50%

5/9/1996

5/9/1995

5/9/1994

Proportion

88 IWAN J. AZIS

100% Currency Basket: Singapore Dollar

90%

80%

70%

60%

US Dollar Euro Yen

30%

20%

10%

0%

Fig. B5. Singapore Dollar.

100% Currency Basket: South Korean Won

90%

80%

70%

60%

US Dollar Euro Yen

30%

20%

10%

0%

5/9/2007

5/9/2006

5/9/2005

5/9/2004

90%

80%

70%

60%

89

Fig. B7. Taipei (China) Dollar. 5/9/2003

5/9/2002

5/9/2001

5/9/2000

5/9/1999

5/9/1998

40%

5/9/1997

50%

5/9/1996

5/9/1995

5/9/1994

Proportion

Currency Basket: Taipei-China Dollar Regional Financial Arrangement

100%

US Dollar

Euro

Yen

30%

20%

10%

0%

Fig. B8. 5/9/2007

5/9/2006

5/9/2005

5/9/2004

5/9/2003

90%

IWAN J. AZIS

Thai Baht.

5/9/2002

5/9/2001

5/9/2000

5/9/1999

5/9/1998

5/9/1997

5/9/1996

5/9/1995

5/9/1994

Proportion

90

100%

Currency Basket: Thai Baht US Dollar

Euro

80% Yen

70%

60%

50%

40%

30%

20%

10%

0%

91

Regional Financial Arrangement

APPENDIX C. FROM HIERARCHY (AHP) TO NETWORK MODEL (ANP) A hierarchical model does not recognize two-way dependence relationships that exist among variables, or how to compensate for those conditions in a decision-making model. Consequently, an alternative model that allows one to deal systematically with dependence and feedback (i.e., counterpart of the influence diagram in statistical decision analysis based on Bayes theorem) is needed. With feedback, the alternatives can depend on the criteria as in a hierarchy but they may also depend on each other. The criteria themselves can depend on the alternatives and on each other as well. Hence, it involves a network rather than a hierarchy. With such a feature, it is expected that the results from a network model is more stable because one can consider the influence on and survival in the face of other influences (Saaty, 2001). Figs. C1 and C2 show the difference between a hierarchy and a network. Note that the term ‘‘level’’ is to be substituted by ‘‘cluster’’ in a network, and the terms ‘‘elements’’ and ‘‘nodes’’ are interchangeable. In Fig. C2, the

Fig. C1.

Fig. C2.

Linear Hierarchy.

Feedback Network.

92

IWAN J. AZIS

parent node (or element) and the nodes to be compared can be in different clusters; for example, a link originates in the parent node cluster C4 to the other clusters (C2 and C3). This is the case of outer dependence. In other cases, the parent node and the nodes to be compared can be in the same cluster, in which case the cluster is linked to itself and a loop link appears. This is called inner dependence. Although in a hierarchy-based model (AHP) a set of pair-wise comparison matrices are used, the presence of feedback influences in a network model requires a large matrix known as supermatrix containing a set of submatrices. This supermatrix should capture the influence of elements in a network on other elements in that network. Denoting a cluster by Ch, h ¼ 1, . . . m, and assuming that it has nh elements eh1, eh2, eh3 . . . , ehmh, Fig. C3 shows the supermatrix of such a hierarchy. When the bottom level affects the top level of the hierarchy, a form of network known as holarchy is formed, the supermatrix of which will look like the one displayed in Fig. C4. Notice that the entry in the last row and column of the supermatrix in Fig. C3 is the identity matrix I corresponding to a loop at the bottom level of the hierarchy. This is a necessary aspect of a

Fig. C3.

Supermatrix of a Hierarchy.

Fig. C4.

Supermatrix of a Holarchy.

93

Regional Financial Arrangement

hierarchy viewed within the context of the supermatrix. However, the entry in the first row and last column of a holarchy in Fig. C4 is nonzero, indicating that the top level depends on the bottom level. The entries of submatrices in Wij are the ratio scales derived from paired comparisons performed on the elements within the clusters themselves according to their influence on each element in another cluster (outer dependence) or elements in their own cluster (inner dependence). The resulting unweighted supermatrix is then transformed into a matrix each of whose columns sums to unity to generate a stochastic supermatrix. The derived weights are used to weight the elements of the corresponding column blocks (cluster) of the supermatrix, resulting in a weighted supermatrix which is also stochastic. The stochastic nature is required for the reasons described later. The typical entry of the Fig. C5 supermatrix is therefore shown in Fig. C6. Since an element can influence the second element directly and indirectly through its influence on some third element and then by the influence of the latter on the second, every such possibility of a third element must be considered. This is captured by squaring the weighted matrix. But the third element also influences the fourth, which in turn influences the second.

Fig. C5.

Fig. C6.

Supermatrix of a Network.

Entry in the Supermatrix of a Network.

94

IWAN J. AZIS

These influences can be obtained from the cubic power of the weighted supermatrix. As the process is performed continuously, one will have an infinite sequence of influence matrices denoted by Wk, k ¼ 1, 2, . . . The question is, if one takes the limit of the average of a sequence of N of these powers of the supermatrix, will the result converge, and, is the limit unique? It has been shown that such a limit exists given the stochastic nature of the weighted supermatrix (Saaty, 2001). There are 3 cases to consider in deriving Wk: (1) lmax ¼ 1 is a simple root and there are no other roots of unity in which case given the nonnegative matrix W is primitive, we have limk-N Wk ¼ weT, implying that it is sufficient to raise the primitive stochastic matrix W to large powers to yield the limit outcome; (2) there are other roots of unity that cause cycling, in which case Cesaro sum is applied; and (3) lmax ¼ 1 is a multiple root, in which case the Sylvester’s formula with lmax ¼ 1 is applied. For further details see Saaty (2001) and Azis (2005a). In practice, however, one simply needs to raise the stochastic supermatrix to large powers to read off the final priorities in which all the columns of the matrix are identical and each gives the relative priorities of the elements from which the priorities of the elements in each cluster are normalized to one. The powers of the supermatrix do not converge unless it is stochastic, because then its largest eigenvalue is one. When a convergence is failed to achieve (a cyclic case) the average of the successive matrices of the entire cycle gives the final priorities (Cesaro sum), in which the limit cycles in blocks and the different limits are summed and averaged and again normalized to one for each cluster. At any rate, raising the stochastic supermatrix to large powers gives what is known as limiting supermatrix. Hence, there are three supermatrices to be used: (1) the original unweighted supermatrix of column eigenvectors obtained from pair-wise comparison matrices of elements; (2) the weighted supermatrix in which each block of column eigenvectors belonging to a cluster is weighted by the priority of influence of that cluster, rendering the weighted supermatrix column stochastic; and (3) the limiting supermatrix obtained by raising the weighted supermatrix to large powers.

95

Regional Financial Arrangement

APPENDIX D. RESULTS FROM USING A NETWORK MODEL Benefit-Risk Sharing Graphic

Alternatives

Total

Normal

Ideal

Ranking

RFA basket

0.2308

0.4615

1.0000

1

RFA with ER

0.1141

0.2283

0.4946

3

RFA without ER

0.1551

0.3102

0.6721

2

Total

Normal

Ideal

Ranking

RFA basket

0.1218

0.2437

0.5189

3

RFA with ER

0.1434

0.2868

0.6108

2

RFA without ER

0.2348

0.4696

1.0000

1

Total

Normal

Ideal

Ranking

RFA basket

0.1147

0.2293

0.3952

2

RFA with ER

0.0953

0.1905

0.3284

3

RFA without ER

0.2901

0.5802

1.0000

1

Total

Normal

Ideal

Ranking

RFA basket

0.3203

0.6406

1.0000

1

RFA with ER

0.1247

0.2494

0.3893

2

RFA without ER

0.0550

0.1100

0.1718

3

Benefit-Macro & ER Coordination Graphic

Alternatives

Benefit-Contagion Graphic

Alternatives

Benefit-Mismatch Graphic

Alternatives

96

IWAN J. AZIS

Opportunity-Capital Market Graphic

Alternatives

Total

Normal

Ideal

Ranking

RFA basket

0.2292

0.4584

1.0000

1

RFA with ER

0.1389

0.2778

0.6060

2

RFA without ER

0.1319

0.2639

0.5756

3

Total

Normal

Ideal

Ranking

RFA basket

0.3203

0.6405

1.0000

1

RFA with ER

0.1216

0.2432

0.3797

2

RFA without ER

0.0581

0.1162

0.1814

3

Total

Normal

Ideal

Ranking

RFA basket

0.3481

0.6962

1.0000

1

RFA with ER

0.0985

0.1970

0.2829

2

RFA without ER

0.0534

0.1069

0.1535

3

Total

Normal

Ideal

Ranking

RFA basket

0.3409

0.6817

1.0000

1

RFA with ER

0.1048

0.2097

0.3076

2

RFA without ER

0.0543

0.1086

0.1593

3

Total

Normal

Ideal

Ranking

RFA basket

0.3334

0.6668

1.0000

1

RFA with ER

0.0941

0.1882

0.2823

2

RFA without ER

0.0725

0.1450

0.2174

3

Opportunity-Supervision Graphic

Alternatives

Cost-Coordination Graphic

Alternatives

Cost-Moral Hazard Graphic

Alternatives

Risk-Compliance Graphic

Alternatives

97

Regional Financial Arrangement

Risk-Synchronized Graphic

Alternatives

Total

Normal

Ideal

Ranking

RFA basket

0.2736

0.5472

1.0000

1

RFA with ER

0.1315

0.2631

0.4807

2

RFA without ER

0.0949

0.1897

0.3467

3

This page intentionally left blank

CHAPTER 5 OIL PRICE INCREASE INTRODUCTION Global imbalances and financial crisis discussed in the preceding chapters were not the only contemporary issues that shaped the current and future landscape of the world economy. Since 2004, many countries also felt a significant shock prompted by a surge in the oil price, forcing them to look for the appropriate policy response that would produce least pain and minimum impact on welfare. The fact that oil remains an important source of energy for many countries, developed and developing alike, a price surge can trigger a new round of global conflicts. Indeed, from the hording of grain in Neolithic times to rivalry over resources in the interimperial wars of the 16th–19th centuries that laid the groundwork for World War I, and to modern nations warring over oil, competition and the desire to have a control over the possession of critical sources of vital materials had always been at the center of conflicts from the very beginning of human story. To prop up their industrialization, for a long period of time developed countries had relied on a stable supply of oil, making their political and strategic relations with oil-producing countries so critical, yet fragile and crisis prone. Conflicts and wars over oil were fought among the oil-producing countries as well.1 Although it was not admitted by the U.S. administration, at least not publicly, the desire to have greater control over oil was also the primary reason for the 2003 U.S. invasion of Iraq. During the past decades, we have seen several episodes of oil price increase and its impact on the world economy. The recent oil price surge, began in the fall of 2004, looked like just another example. Unlike in the past episodes, however, this time it had not resulted in a major economic slowdown. The demand-driven nature of the price shock mitigated the adverse repercussions especially in the oil-importing countries. Although many of these countries were intensive and relatively inefficient in energy use, the share of oil in total energy use in some of these countries was not

99

100

IWAN J. AZIS

that large (China is a notable example). All these explain why the 2004 price increase did not cause a global recession. There is no deficit of conflicts in the policy response to an oil price shock. Maintaining the domestic fuel price level to prevent the welfare of majority from declining is likely in conflict with the efforts to keep government’s fiscal position from deteriorating due to increased fuel subsidy. On the other hand, removing subsidy will be in contradiction with the goal to control inflation, and presumably also in conflict with the efforts to reduce poverty. Although conflicts between countries over the control of oil have been widely documented, the focus of the discussions in this chapter is on the impact of oil price shock and the potential conflicts that can arise from the policy response to the shock. The challenge to strike a balance between maintaining macro stability and helping the most vulnerable segment of society is particularly highlighted. The difficulty of finding such a balance compels one to go back to the essence of development goal, and look more carefully at the transmission mechanisms through which the oil price increase affects such a goal.

IMPACT OF OIL PRICE SURGE Spurred by robust economic growth in many countries, particularly China, India, and the Unites States, the world’s oil price began to surge in 2004 (Fig. 1). By March 2004, the level reached over $10 per barrel higher than in 2000. The Hurricane Katrina in August 2005 accelerated the trend.2 The continued widening gap between strong consumption and lagging supply, especially from the non-OPEC producing countries, kept the price acceleration until the mid-2008. Given its heterogeneity and being a surplus region that played an important role in the global imbalances, Asia went through an episode that may reflect the diverse experience of other regions in terms of how the oil price surge affected the economy. Despite the oil price disruptions beginning in the Fall of 2004, the Asian economy continued to expand at a reasonably good pace. Although the energy intensity was high, that is, over three times more than in the average G7 countries, the share of oil in total energy use had been relatively small, that is, approximately 34 percent on average. In China, where the domestic demand for oil continued to exceed supply because of strong economic growth, the government took action by rationing the distribution of oil in some regions. Though countries in the region seemed able to mitigate the upward pressure on the domestic price

Oil Price Increase

Fig. 1.

101

Average CIF Cost of Imported Crude Oil (IEA Total). Source: IEA (2008), Oil Market Report, December.

level, however, individual countries with large subsidy for the domestic fuels had to face a serious policy conflict: removing the subsidy that would be in contradiction with the goal to control inflation and lower the poverty rate, or keeping the subsidy that would deteriorate the government’s fiscal position and sustainability. Theoretically, an oil price increase affects economic activity through output (GDP) and the price level. The potential reduction in economic growth will influence incomes of different households, and the increase in the general price level will determine the poverty line. Given the resulting household incomes and poverty line, the incidence of poverty can be estimated. In a simple term, this is how oil price increase affects poverty. However, the precise mechanisms and the intensity of each relation are more complex. As shown in Fig. 2, any policy intervention will eventually determine the outcome. The domestic oil price is determined by the extent of subsidy (price policy), the general price level is influenced by the interest rates (monetary policy), and household incomes is affected by public expenditures on social overhead capital (SOC) (fiscal policy). In a classic supply shock also known as the ‘‘real business cycle’’ (RBC) model, an oil price increase reflects a growing scarcity of energy as a basic

102

IWAN J. AZIS

Fig. 2.

How Oil Price Increase Affects Poverty.

input to production. Output and labor productivity are consequently dampened, and the growth of real wages and employment will slow down (Abeysinghe, 2001; Aguiar-Conraria & Wen, 2005). From this channel alone household incomes and expenditures can be adversely affected. Whether consumers smooth out the expenditures or not depend on their expectation. Only if consumers expect that the short-run effects of output fall are greater than the long-run effects, that is, if the price increase is only temporary will they smooth their expenditures, reducing saving and increasing borrowing. The demand for real cash balance will fall, as the real interest rates tend to rise, output falls, and price level increases. From the theory of real balance, agents raise the demand for money to rebalance their portfolio, and this will raise the interest rates and lower the output level. To restore output equilibrium, prices have to adjust downward, not upward as postulated in the RBC model. An oil price increase can also be viewed as income transfers from oilimporting to oil-exporting countries. The net effect on expenditures, however, is not proportional: the fall of consumption expenditures in oilimporting countries is greater than the increase in oil-exporting countries, because the costs associated with indirect impacts on exports due to lower growth in the trading partners outweighs the benefits accruing to the oil exporters. If this is the case, the resulting higher saving tends to reduce the interest rates, although the net effect on aggregate demand is likely negative. A loose monetary policy will have to allow the unexpected inflation to restore aggregate demand and output. Partly because of the fact that most

103

Oil Price Increase

countries often tightened their monetary policy in response to an oil price increase, the past episodes of oil price shocks did not seem to conform to this postulate. Obviously, monetary policy has a key role in each of the above hypotheses. Some even suggested that a recession following an oil price shock could be due to the tight monetary policy as a response to the shock, rather than the shock itself (Bernanke, Gertler, & Watson, 1997). With a strongly tight monetary policy, the recession price level could be lower than before the policy was implemented. Although the historical record following the oil price shocks in the past did not seem to conform to such a prediction (i.e., rising interest rates, slower GDP growth, and lower inflation rate), it is important to realize that in evaluating the effect of rising oil prices on household welfare, the risks of a monetary policy shock need to be analyzed carefully. A tighter-than-necessary policy will have a deleterious effect on growth and household incomes. The fact that the historical record conforms to the supply shock and RBC more than to the other hypotheses does not necessarily mean that the same conclusion applies to all cases of oil price increase. One of the most important factors to look at is the source of the price increase. As indicated earlier, the surge in oil prices that began in 2004 was not entirely exogenous. Strong demand due to a robust economic growth particularly in the United States, China, and India contributed to the price surge (see Fig. 3).3 The nonexogenous rise of oil prices was less disruptive because the dampening effect was counter-balanced by the rising trade of nonoil sector. It is therefore important to evaluate the extent to which the rising demand for nonoil exports may offset the downward pressure to the economy 12 10

United States India

World China

8 6 4 2 0 2003

Fig. 3.

2004

2005

Real GDP Growth Rates (2003–2006).

2006

104

IWAN J. AZIS

and the rising import bills following the oil price increase. In general, an oil price increase affects the economy through higher input costs and greater uncertainty. What is unclear is, whether the reduction in real money balances or the costly resource reallocation among sectors that will eventually slow down the economic activity. The subsequent effects on unemployment and real output gap (the difference between actual and potential output) may vary between countries. Nonetheless, since oil is not only important in production activity but also used to transport a wide range of goods and services, changes in its prices should be incorporated in the analysis of a trade-off between inflation and unemployment (Phillips curve). The second most important channel pertains to the effect of oil price changes on the general price level. It is through this channel that the poverty line is determined. The most obvious indicator of a price shock is the change (increase) in the nominal price. With rising nominal price of oil, firms’ costs will increase, so will the prices they charge for their products. Holding nonenergy prices constant, this pushes up the inflation rate. Holding aggregate demand constant, the probability of a recession will increase. But the actual effect on inflation is often influenced by the policy response, particularly monetary and fiscal policies. The monetary authority has a choice between implementing a contractionary monetary policy to fight inflation, and an expansionary policy to fight recession. Obviously, the inflation impact also depends in part on how big is the role of energy sector in the economy, and to what extent institutional factors (e.g., wage setting institutions) plays a role in the process. Stronger labor unions may make the economy more prone to wage-price spirals since the unions are more likely to extract higher wage concessions in response to rising consumer prices for energy. Higher wages will subsequently lead to higher unemployment. On the fiscal front, to avoid recession government can raise public expenditures. But this will widen the fiscal deficit. Along with the long-run effect on inflation, the rising deficit may weaken the economic fundamentals and macro stability that could potentially worsen the prospects of investment, capital inflows, and overall growth. On the other hand, the short-run effect on low-income groups and poverty condition could be favorable, provided that the increased public expenditures are mostly directed to the low-income groups. The dynamics of the effect, however, are more complex. Since many governments subsidize the domestic fuel price, when the world oil price increases the options regarding public expenditure will be constrained by the

Oil Price Increase

105

size of subsidy the government is willing to spend. Thus, the real policy choices are: maintain the subsidy (in effect letting the domestic fuel price to increase), raise the subsidy (leaving the domestic fuel price unaffected), or reduce the subsidy (allowing domestic price to adjust to the world price). The impact of each option on growth, inflation, and unemployment, that will eventually determine the resulting poverty rate, depends on what happens with the aggregate supply and the aggregate demand. Take the case where domestic fuel price is allowed to move according to the international market price. This will raise the domestic fuel price. Since the increase will shift the aggregate supply curve leftward, potential output tends to decline along with falling real balance and higher general price level. If the resulting increase in general price persists and no effective expansionary policy is in place, output will fall. When wages go up, added by inflation expectation and deteriorating confidence, the fall of output and the increase in prices may lead to a cost-price spiral that can bring the economy into recession or stagflation. For net oil-importers, they may suffer more because the aggregate demand may also shift leftward. On the other hand, an expansionary policy to counter the aggregate supply shift can be inflationary, reducing the real balance and hence lowering the aggregate demand. If oil price continues to rise, output falls again, making the expansionary policy ineffective. Higher price level also weakens the exchange rate competitiveness.4 Even for oil-exporting countries, rising world prices may cause the exchange rate to appreciate. Since exporting sectors in many countries tend to have high import content with low elasticity of substitution, this can worsen the balance-of-payment position. A depreciation of exchange rate is unlikely to help because it can fuel further inflation. There is an asymmetry in the effect of oil price changes: oil price increase matters more than oil price decline (Mork, 1994), and price increase that occurs after a period of stable price matters more than an increase that simply reverses an earlier decline (Hamilton, 2003).5 Since an accurate measure of the shocks depends on how the price of oil affects the economy, an alternative measure is to use the ‘‘net oil price increase.’’ It distinguishes rising prices that establish new highs relative to the recent experience, and price increases that simply reverse the recent decreases (Hamilton, 1996). What are the empirical evidences of policy conflicts discussed above? The remaining sections deal with this question. We begin with the empirical evidence in some countries showing the transmission mechanisms through which an oil price shock affects the economy.

106

IWAN J. AZIS

TRANSMISSION MECHANISMS AND SECTORAL EFFECTS The strand of studies emphasizing the positive relation between growth and poverty tends to emphasize the importance of raising incomes – economic growth – to reduce poverty.6 However, many of these studies were conducted within a cross-sectional setting, undermining the unique characteristics of individual countries. They suffered from a lack of detailed mechanisms linking economic activity and poverty. Even the most careful cross-country analysis has to be treated with lots of caution. In identifying the transmission mechanisms, one needs to take into account the direct, indirect, and feedback effects of a price shock. The model used in the analysis below is able to incorporate those effects, utilizing the economy-wide data system known as the social accounting matrix (SAM). The analysis is based on multiplier analysis and structural path analysis (SPA) (see Appendix A for further descriptions). Having a robust economic growth, India was one of the sources of strong demand for energy. About 80 percent of the country’s crude oil was imported. As shown in Table 1, the following sectors were the most oilintensive in India: rubber–petroleum–plastic, chemical, other services, other manufacturing, and food products. In the case of China, the most oilintensive sectors were: transport and telecommunication, utilities, refined petroleum, quarrying, and metal. When the oil price surged, these sectors were the first to be affected. As the rising energy costs led to a fall in output, the value-added also declined. Even if the level of output was maintained at the same level as before the oil price increase, the rising energy costs would have lowered the value added. As shown on the left panel of Fig. 4, based on India’s SAM multipliers any fall in the production of oil-intensive rubber–petroleum–plastic industries will adversely impact the following sectors (through lower demand for their products): crude petroleum and natural gas, trade, construction, other transport services, and other services. But the actual impact can be bigger. The value-added fall of the rubber–petroleum–plastic industries will also create some problems to other sectors that use their products. On the basis of SAM multipliers, the most affected by such forward linkages are: other mineral, petroleum, electricity, other manufacturing, and machinery (see Table 1; values in the parentheses indicate the multipliers). Fig. 4 shows the complete mechanisms from the production fall in the affected sectors to household incomes. Thus, the effect of oil price increase on India’s rubber–petroleum–plastic industries will subsequently lower the

Backward and Forward Multipliers of Oil-Intensive Sectors in China, India, Indonesia, and Thailand.

Table 1.

Transport and Telecom (7.81%) Backward linkage China

OthServ Chem Food Cmmrce OthCrop

Utilities (4.97%)

Forward linkage

0.347 0.244 0.222 0.198 0.133

Quarrying Construc OthServ BldMtrial MetalProd

0.187 0.169 0.164 0.163 0.16

Backward linkage OthServ Chem Cmmrce Food CoalMin

Rubber–Petroleum–Plastic (42.55%) Backward linkage India

PETRO TRADE CONSTRUCT OTHTRNS OTHSRVICE

OTHMINRAL PETRO ELECTRNIC OTHMANU MACHINE

Backward linkage

0.094 0.11 0.201 0.231 0.234

TRADE CONSTRUCT OTHTRNS OTHSRVICE OCROP

Chemical (43.40%) Backward linkage Indonesia

ACoal_Petro AFoodBev APaper ATrade APublicAd

AChem AWood ATrade APersonal AConstructic

Thailand

GASFUEL AGMANU TXTAPP RESHOT CTRADE

0.283 0.223 0.212 0.171 0.165

0.152 0.152 0.139 0.138 0.134

CrudeOil OthServ Chem Cmmrce Food

0.791 0.749 0.596 0.561 0.470

Forward linkage OTHMINRAL PETRO ELECTRNIC MACHINE OTHMANU

1.11 0.067 0.063 0.059 0.047

0.484 0.284 0.204 0.17 0.16

0.136 0.153 0.266 0.306 0.339

Backward linkage TRADE CONSTRUCT OTHTRNS OCROP CHEM

ACoal_Petro AFoodBev ATrade APublicAd AFarmCrop

0.322 0.275 0.196 0.174 0.132

CCONSTR CLIVSTK CBEVER CNONPRF AGMANU

Apaper AElecGasWate AWood ATransport_R AAirWaterTra

0.281 0.218 0.215 0.212 0.21

CTRADE AGMANU GASFUEL TRANS TXTAPP

0.262 0.235 0.226 0.183 0.148

0.127 0.104 0.1 0.098 0.091

Forward linkage

0.836 0.812 0.63 0.476 0.46

1.306 0.46 0.367 0.33 0.322

Backward linkage AFoodBev APublicAd ATrade APaper AFarmCrop

Plastic &Rubber (14.52%) Backward linkage

Trns Tele Util Metal Construc Qyarrying

OTHMINRAL PETRO ELECTRNIC RUBBER OTHMANU

0.19 0.225 0.36 0.416 0.428

Coal_Petro (10.48%)

Forward linkage Backward linkage Forward linkage

Forward linkage

Forward linkage

Other Services (1.93%)

Backward linkage

Transport (17.44%) Backward linkage

MetalMin Metal BldMtrial MetalProd CoalMin

Backward linkage

Paper (25.25%)

Forward linkage

0.504 0.251 0.239 0.175 0.167

Forward linkage

Chemical (4.24%)

Forward linkage

0.586 0.569 0.55 0.432 0.416

0.352 0.248 0.238 0.217 0.214

Refined Petroleum (3.95%)

Acoal_Petro Achem APaper AElecGasWate AWood

1.146 0.504 0.322 0.124 0.115

Electricity (12.58%)

Forward linkage CFISHIN WOODFU CRPAIRS CTRANEQ TRANS

0.276 0.183 0.175 0.158 0.133

Forward linkage

0.035 0.03 0.026 0.025 0.023

Backward linkage AGMANU GASFUEL TXTAPP MINING TRANS

0.245 0.221 0.194 0.188 0.188

Forward linkage TXTAPP CRCREAT CNONMTL CWATER WOODFU

0.08 0.079 0.078 0.077 0.073

(Continued )

Table 1. Quarrying (3.49%)

Metal (3.32%)

Backward linkage China

OthServ Chem Food Cmmrce Trns Tele

Forward linkage

0.333 0.329 0.221 0.221 0.187

BldMtrial Construc CoalMin Furniture Chem

Backward linkage 0.104 0.069 0.066 0.06 0.034

OthServ Chem Cmmrce Food MetalMin

0.313 0.253 0.218 0.195 0.181

Other Manufacturing (0.70%) Backward linkage India

TRADE CONSTRUCT METAL OTHTRNS OTHSRVICE

OTHMINRAL PETRO ELECTRNIC RUBBER MACHINE

Backward linkage

Indonesia

AFoodBev ATrade APaper AForestry APublicAd

0.33 0.304 0.288 0.248 0.189

0.54 0.377 0.292 0.265 0.264

0.051 0.062 0.105 0.114 0.121

TRADE CONSTRUCT OTHTRNS OCROP OTHSRVICE

Forward linkage 1.0190 0.9530 0.7590 0.7290 0.7080

Textile (0.24%) Backward linkage

MetalProd ElecMch Machin Car OthTrEq

Food (0.31%)

Forward linkage 0.598 0.547 0.528 0.437 0.428

Forward linkage

OTHMINRAL PETRO ELECTNIC RUBBER OTHMANU

0.135 0.162 0.242 0.291 0.293

Construction (0.14%) Forward linkage

APersonal AElecGasWate Atransport_R AAirWaterTra APublicAd

Backward linkage 0.303 0.219 0.213 0.205 0.192

AFoodBev ATrade APaper AForestry APublicAd

0.33 0.304 0.288 0.248 0.189

Forward linkage AConstuctio ATextile AElecGasWate Amining ATrade

1.191 1.191 0.049 0.013 0.013

Fishery (12.18%) Backward linkage Thailand

AGMANU TXTAPP GASFUEL CTRADE TRANS

Gas Fuel (8.80%) Forward linkage

0.386 0.224 0.221 0.219 0.186

CLIVSTK AGMANU RESHOT CTOBACO CPUBADM

Backward linkage 0.119 0.112 0.093 0.06 0.049

MINING AGMANU TXTAPP TRANS CMACHIN

Forward linkage 0.534 0.173 0.132 0.126 0.114

TRANS CPLASRB CFISHIN CELCITY CBUSISR

0.283 0.226 0.221 0.221 0.123

Notes: OthServ, other services; Chem, chemical; Cmmrce, commerce; OthCrop, other crops; Construc, construction; BldMtrial, build material; MetalProd, metal product; CoalMin, coal mining; Trns Tele, transport and telecom; Util, utilities; ElecMch, electrical machinery; OthTrEq, other transport equipment; PETRO, crude petroleum and natural gas; CONSTRUCT, construction; OTHTRNS, other transportation equipment; OTHSRVICE, other services; OCROP, other crops; OTHMINIRAL, other minerals; ELECTRNIC, electronics; MACHINE, machinery; OTHMANU, other manufacturing; CHEM, chemical; RUBBER, rubber, petroleum, and plastic; ACoal_Petro, coal and metal ore, petroleum and natural gas mining activity; AfoodBev, food, beverages, and tobacco manufacturing activity; Apaper, paper and printing activity; Atrade, whole sale and retail trade, services allied to transport, storage, warehousing activity; ApbulicAd, public administration activity; Achem, chemical activity; Awood, wood activity; Apersonal, personal, household and other service activity; Aconstruction, construction activity; AfarmCrop, farm crop activity; AelecGasWate, electricity, gas and water supply; ATransport_R, rail transportation activity; AairWaterTra, air and water transportation; Aforestry, forestry and hunting activity; GASFUEL, gas and fuel; AGMANU, agricultural manufacturing; TXTAPP, textile and apparel; RESHOT, restaurant and hotel; CTRADE, trade; CCONSTR, construction; CLIVSTK, livestock; CBEVER, beverage; CNONPRF, non-profit activity; CFISHIN, fishery; WOODFU, wood and furniture; CRPAIRS, repair services; CTRANEQ, transportation equipment; TRANS, transports; MININIG, mining; CRCREAT, recreation; CNONMTL, non-metal product; CWATER, water supply; CTOBACO, tobacco; CPUBADM, public administration; CMACHIN, machinery; CELECITY, electricity; CBUSISR, business service.

110

IWAN J. AZIS

Rubber, Petroleum, and Plastic

Capital Labor

Petroluem

Rural Mid-High Income Household Urban Mid-Low Income Household

Trade Construction

Urban Low Income Household

Other Transports

Rural Mid-Low Income Household

Other Services

Rural Low Income Household Rural High Income Household Urban Mid-High Income Household Rural Mid-Low Income Household Urban High Income Household

Fig. 4.

Structural Path of Oil-Intensive Rubber–Petroleum–Plastic Industries in India.

demand for labor and capital. All these eventually affect wages and incomes of different households. Most affected households are rural middle-high-income and urban middle-high-income categories. That is, India’s middle-high-income group is the most affected by the adverse impact of oil price increase on rubber– petroleum–plastic industries. This is consistent with the finding of most studies that indicate rich households generally benefit more from fuel price subsidies than poor households. The mechanism works through various paths. Take the case of rural medium-high-income households (receiving highest global influence, i.e., 0.891). As shown in Table 2, the most important channel with largest total influence (0.159) is the one that works through a lower demand for capital. The second most important channel (with total influence equals to 0.105) works through a lower demand for petroleum sector before transmitted to lower capital requirement and eventually lower income of rural medium-high-income groups.

Origin (I )

Rubber– Petroleum– Plastic

Destination ( j)

Global Influence (GI)

Rural MidHigh-Income HH

0.891

Urban LowMid-Income HH

0.784

Elementary Path i - j

Rubber–Petroleum–Plastic - Labor - Rural Mid-High-Income HH Rubber–Petroleum–Plastic - Capital - Rural Mid-High-Income HH Rubber–Petroleum–Plastic - Plantation Crop - Capital - Rural Mid-High-Income HH Rubber–Petroleum–Plastic - Coal - Capital - Rural Mid-High-Income HH Rubber–Petroleum–Plastic - Petroleum - Labor Rural Mid-High-Income HH Rubber–Petroleum–Plastic - Petroleum - Capital Rural Mid-High-Income HH Rubber–Petroleum–Plastic - Chemical - Capital Rural Mid-High-Income HH Rubber–Petroleum–Plastic - Trade - Labor Rural Mid-High-Income HH Rubber–Petroleum–Plastic - Trade - Capital Rural Mid-High-Income HH Rubber–Petroleum–Plastic - Bank- Capital Rural Mid-High-Income HH Rubber–Petroleum–Plastic - Indirect Taxes Government-Rural Mid-High-Income HH Rubber–Petroleum–Plastic - Labor - Urban Low-Mid-Income HH Rubber–Petroleum–Plastic - Capital - Urban Low-Mid-Income HH Rubber–Petroleum–Plastic - Plantation Crop Capital - Urban Low-Mid-Income HH

Direct Influence (DI)

Path Multiplier (Mp)

Total Influence (TI)

TI/GI (%)

0.006

5.400

0.032

3.6

0.035

4.574

0.159

17.9

0.001

4.608

0.006

0.6

0.002

4.649

0.007

0.8

0.005

5.431

0.026

2.9

0.023

4.588

0.105

11.8

0.004

6.175

0.023

2.6

0.001

5.866

0.007

0.8

0.005

4.948

0.025

2.8

0.004

4.986

0.019

2.1

0.008

3.369

0.029

3.2

0.016

4.590

0.073

9.4

0.003

5.177

0.016

2.0

0.002

4.623

0.009

1.1

Oil Price Increase

Table 2. How India’s Oil-Intensive Rubber–Petroleum–Plastic Industries Affect Household Incomes.

111

112

Table 2. (Continued ) Origin (I )

Destination ( j)

Global Influence (GI)

Elementary Path i - j

Rubber–Petroleum–Plastic - Petroleum - Labor Urban Low-Mid-Income HH Rubber–Petroleum–Plastic - Petroleum- Capital Urban Low-Mid-Income HH Rubber–Petroleum–Plastic - Chemical - Capital Urban Low-Mid-Income HH Rubber–Petroleum–Plastic - Other Transports Capital - Urban Low-Mid-Income HH Rubber–Petroleum–Plastic - Trade - Capital Urban Low-Mid-Income HH Rubber–Petroleum–Plastic - Bank - Capital Urban Low-Mid-Income HH Rubber–Petroleum–Plastic - Indirect Taxes Government - Urban Low-Mid-Income HH

Direct Influence (DI)

Path Multiplier (Mp)

Total Influence (TI)

TI/GI (%)

0.013

4.625

0.059

7.6

0.002

5.189

0.010

1.3

0.002

6.275

0.011

1.4

0.002

5.013

0.008

1.0

0.003

5.215

0.016

2.1

0.002

5.149

0.010

1.2

0.006

3.208

0.020

2.6

IWAN J. AZIS

Oil Price Increase

113

The influence on incomes of the second most affected households (urban low-middle-income category with global influence equals to 0.784) is not through capital demand. As seen in the lower part of Table 2, the two most important channels, receiving total influence of 0.073 and 0.059, work through labor demand. The patterns for other oil-intensive sectors (chemical, other services, other manufacturing, and food products) are similar. It is always the middle-income households in both urban and rural areas that are most affected by the changing structure of the economy. China is another source of strong demand for energy. The most oilintensive sectors in that country are transport and telecommunication, utilities, refined petroleum, quarrying, and metal (see Table 1). The backward and forward multipliers of each of these sectors are listed in Table 1. The effect of oil price increase on China’s transport and telecommunication sector generates further ramifications on other services, chemical, food, commerce, and other crops sectors through backward linkages, and on quarrying, construction, other services, building materials, and metal products through forward linkages. The most affected factor of production is capital, followed by production worker, agricultural labor, and professional labor. The adverse effect of oil price increase will be felt in terms of lower demand for these factors. Interestingly, the same ranking also applies to other oil-intensive sectors. Through this channel the effect of oil price increase on transport and telecommunication sector eventually determines the level and distribution of household incomes. Looking closely at the results of SPA, the ranking of most impacted households is the same for all oil-intensive sectors. That is, the urban high-income, rural high-income, and urban middle high-income are the most affected. The complete ranking is shown in the right panel of Fig. 5. The difference between the case of China and that of India is that, in China the urban households tend to benefit more than the rural residents when the oil price increases. Interestingly enough, although the top most important channel connecting China’s production sector and household incomes is through the demand for capital, in tracing the source of the effect on urban high-income, the most important path is through a lower demand for production workers (the total influence is 0.044), followed by demand for professional worker (0.014). The path through demand for capital is only ranked third (0.006; see Table 3).7 For the effect on the rural high-income households, the most important path is also through demand for production workers. Similar to China case, the sector with the highest oil-intensity in Thailand is also transportation. Other oil-intensive sectors are plastic and rubber,

114

IWAN J. AZIS

Transports & Telecom

Capital

Urban High Income Household

Production Worker

Rural High Income Household

Agri Labor Professional Other Services Chemical Food Commerce Other Crops

Land

Urban Mid-High Income Household Urban Mid Income Household Urban Mid-Low Income Household Rural Mid-High Income Household Urban Low Income Household Rural Mid Income Household Rural Mid-Low Income Household Rural Low Income Household

Fig. 5.

Structural Path of Oil-Intensive Transport and Telecommunication Sector in China.

electricity, fishery, and gas and fuel. Some of these sectors also have strong interactions among themselves. For example, the negative effect of oil price increase on the transport sector will have a largest repercussion on the gas fuel sector, whereas the latter is also classified as oil-intensive with large backward and forward linkage multipliers on transport sector (Table 4). The transmission mechanisms from transport sector to household incomes are displayed in Fig. 6. In the factor market, if oil-intensive sectors fall, the most adversely affected will be the demand for nonagricultural capital and labor. When the demand for capital declines, output falls, and when the demand for labor declines, unemployment increases. The net effect on household incomes is, nonagricultural households are most adversely affected, especially the high-income category. Incomes of the top seven deciles decline. A similar pattern also applies to the case of other oil-intensive sectors. The only case where the fall in the demand for agricultural capital is larger than the fall in nonagricultural capital is in the oil-intensive fishery sector. As far as the effect on incomes is concerned, similar to the case of India and China the high-income category is more affected than the lower income groups.

Origin of Shock (i)

How China’s Oil-Intensive Transport and Telecommunication Sector Affects Household Incomes. Destination (j)

Transport and Urban HighTelecom Income HH

Rural HighIncome HH

Global Influence (GI) 0.204

0.196

Elementary Path i-j Transport and Telecom - Prod Workers - Urban High-Income HH Transport and Telecom- Professional - Urban High-Income HH Transport and Telecom - Capital - Urban High-Income HH Transport and Telecom - Other services Professional - Urban High-Income HH Transport and Telecom - Capital - Companies Urban High-Income HH Transport and Telecom - Prod. Workers - Rural High-Income HH Transport and Telecom - Capital - Rural High Low-Income HH Transport and Telecom - Capital - Companies Rural High-Income HH

Direct Influence (DI)

Path Multiplier (Mp)

Total Influence (TI)

TI/GI (%)

0.031

1.451

0.044

21.8

0.01

1.33

0.014

6.7

0.004

1.384

0.006

3

0.002

1.699

0.004

2

0.01

1.446

0.014

6.9

0.027

1.556

0.042

21.3

0.006

1.493

0.01

4.9

0.009

1.56

0.014

6.9

Oil Price Increase

Table 3.

115

Origin (i)

Destination (j)

Transports

NonAgri HH10

NonAgri HH9

116

Table 4.

How Thailand’s Oil-Intensive Transport Sector Affects Household Incomes. Elementary Path i-j

Direct Influence (DI)

Path Multiplier (Mp)

Total Influence (TI)

TI/GI (%)

0.392

Transports - Labor - NonAgri HH10 Transports - NonAgri Capital - NonAgri HH10 Transports - Textile - Labor- NonAgri HH10 Transports - Textile- NonAgri Capital - NonAgri HH10 Transports -Gas Fuel - Labor- NonAgri HH10 Transports - Gas Fuel- NonAgri Capital - NonAgri HH10 Transports - Trade - NonAgri Capital - NonAgri HH10 Transports - Restaurant and Hotel - Labor NonAgri HH10 Transports - Restaurant and Hotel - NonAgri Capital NonAgri HH10 Transports - Banking and Insurance - Labor - NonAgri HH10 Transports - Banking and Insurance - NonAgri Capital - NonAgri HH10 Transports - Repair Services- Labor- NonAgri HH10 Transports - Repair Services- NonAgri Capital - NonAgri HH10 Transports - Labor- NonAgri HH9 Transports - NonAgri Capital - NonAgri HH9 Transports - Gas Fuel - Labor- NonAgri HH9 Transports - Trade - NonAgri Capital - NonAgri HH9 Transports - Restaurant and Hotel - NonAgri Capital - NonAgri HH9 Transports - Banking and Insurance- NonAgri Capital - NonAgri HH9

0.035 0.069 0.002 0.001 0.006 0.005 0.004 0.003

1.779 1.8 2.356 2.376 2.002 2.025 1.867 1.863

0.062 0.124 0.004 0.003 0.012 0.009 0.008 0.005

15.9 31.7 0.9 0.7 2.9 2.4 2.1 1.3

0.002

1.888

0.004

1.1

0.002

1.907

0.003

0.9

0.003

1.92

0.005

1.4

0.001

1.809

0.003

0.7

0.001

1.828

0.002

0.5

0.016 0.025 0.003 0.002 0.002

1.72 1.746 1.937 1.965 1.814

0.027 0.043 0.005 0.003 0.003

16.9 27 3.1 2 1.8

0.001

1.811

0.002

1.4

0.16

IWAN J. AZIS

Global Influence (GI)

117

Oil Price Increase

NonAgri Capital

Transports

NonAgri Household 10 Labor NonAgri Household 9 Agri Capital

Gas Fuel

NonAgri Household 8

Agri Manufacturing

NonAgri Household 7

Textile

NonAgri Household 6

Restaurant & Hotel

NonAgri Household 5

Trade

NonAgri Household 4 Agri Household 10 NonAgri Household 3 Agri Household 5 Agri Household 4 Agri Household 3 Agri Household 6 Agri Household 7 Agri Household 8 Agri Household 2 Agri Household 9 NonAgri Household 2 Agri Household 1 NonAgri Household 1

Fig. 6.

Structural Path of Oil-Intensive Transport Sector in Thailand.

118

IWAN J. AZIS

As shown in Table 4, the channel that starts from transport sector to nonagricultural capital and then to nonagricultural highest income households is the most significant one. It constitutes almost 32 percent of the entire transport sector’s global influence (last column). Similarly, the most important channel that reaches the next richest nonagricultural households also passes through the demand for nonagricultural capital. In the case of Indonesia, the most oil-intensive sectors are chemical, paper, coal petroleum, textile, and construction. They interact closely among themselves. For example, paper industry generates the largest multiplier on coal petroleum (0.322), and the latter also generates a relatively high multiplier on paper industry (0.158). Like in the Indian case, the adverse effect of oil price increase on Indonesia’s chemical industry generates largest direct and indirect impact on the demand for capital (Fig. 7). Even for the laborintensive textile industry, the largest total effect in factor market is on the demand for capital. The most affected households by the adverse consequence of oil price increase on chemical industry are those in the urban areas, both the highand the low-income categories. For the urban high-income groups, the most important channel involves intersectoral linkages through a lower demand for coal and petroleum products that adversely impacts the demand for unincorporated capital, and eventually lowers the household incomes. Incorporated Capital

AChemical

Unincorporated Capital CCoal&Petro

ACoal&Petro

Service Labor

CFood & Beverage

AFood & Beverage

Manufacturing Labor

NonAgri Urban High Income Household

CPaper

APaper

Agri Labor

NonAgri Urban Low Income Household

CTrade

ATrade

Professional

NonAgri Rural Low Income Household

CPublic Administration

APublic Administration

NonAgri Rural High Income Household Agri Small Land Household Agri Employee Household NonAgri Urban Mid Income Household Agri Large Land Household NonAgri Rural Mid Income Household Agri Med Land Household

Fig. 7.

Structural Path of Oil-Intensive Chemical Industry in Indonesia.

Oil Price Increase

119

The total influence of this channel is 0.027, or 13.2 percent of the industry’s global influence. The second most important channel does not involve intersectoral linkages; it goes directly to urban high-income households through a lower demand for unincorporated capital (Table 5). A similar pattern occurs in the channel that reaches the urban low-income households. The most important one is through the demand for coal and petroleum sector. However, the second most important channel is through a lower demand for manufacturing labor. This explains why the unemployment rate in Indonesia’s manufacturing sector was on the rise when the oil price increased, especially since the government raised drastically the domestic fuel prices in October 2005. Looking at only the size of the decline in all the preceding cases, incomes of wealthy households fall more than incomes of the poor households, consistent with the common assertion that the rich benefits more from the fuel price subsidy. But this does not imply that those households experiencing a larger income fall also suffer more. For the poor households, a small decline of income can easily push them into deeper poverty with far worse human conditions. Since in most cases their budget shares for fuel products (e.g., kerosene) and food expenditure are higher than the share for the wealthier households (see Appendix B), and the fuels they use are much less efficient than modern fuels, they are actually more adversely affected. Thus, low-income households are clearly more vulnerable than the high-income groups when the domestic fuel price is raised. It is also important to note that the impact of increased prices of different fuel products on the poor is not the same. Fuel products directly consumed by households are typically kerosene and gasoline, whereas diesel and other energy sources are consumed more by industries. Thus, the direct effects on the poor are largely due to kerosene and gasoline price increases. However, in some cases, the indirect effects can be larger than the direct effects, especially when they involve activities intensively using other fuel products (e.g., food requires transportation). It is also important to emphasize that the preceding analysis is based on the transmission mechanisms with no policy response to the oil price shock. The implicit assumption is that, the cost increases due to higher oil prices are fully passed through to output prices except for the prices of some sectors that were controlled by the government (reflected in the initial SAM). The actual consequences on poverty will depend on the government’s policy response, and these consequences bring about policy conflicts. This subject is discussed next.

Origin (i)

AChemical

How Indonesia’s Oil-Intensive Chemical Industry Affects Household Incomes.

Destination (j)

Global Influence (GI)

HHNonAg Urban High Income

0.204

Elementary Path i-j

Direct Influence (DI)

Path Multiplier (Mp)

Total Influence (TI)

TI/GI (%)

0.002

1.508

0.003

1.4

0.009

1.567

0.014

6.8

0.006

1.395

0.008

3.9

0.01

1.45

0.015

7.1

0.001

1.527

0.002

1

0.001

1.685

0.002

1

0.005

1.753

0.008

4

0.004

1.565

0.006

2.9

0.001

1.624

0.002

1.1

0.016

1.691

0.027

13.2

0.001

1.877

0.003

1.4

0.004

2.051

0.008

6.9

0.003

1.875

0.006

5

0.002

1.826

0.003

2.5

IWAN J. AZIS

AChemical - Manufacturing Labor - HHNonAg Urban High Income AChemical - Service Labor - HHNonAg Urban High Income AChemical - Professional - HHNonAg Urban High Income AChemical - Unincorporated Capital - HHNonAg Urban High Income AChemical - Incorporated Capital - HHNonAg Urban High Income AChemical - ACoal&Petro - CCoal&Petro Manufacturing Labor - HHNonAg Urban High Income AChemical - ACoal&Petro - CCoal&Petro Service Labor - HHNonAg Urban High Income AChemical - ACoal&Petro - CCoal&Petro Profess - HHNonAg Urban High Income AChemical - ACoal&Petro - CCoal&Petro Unincorporated Capital - HHNonAg Urban High Income AChemical - ACoal&Petro - CCoal&Petro Incorporated Capital - HHNonAg Urban High Income AChemical - Apaper - Cpaper - Incorporated Capital - HHNonAg Urban High Income APaper - Incorporated Capital - Companies Government - HHAgSmllLand APaper - CfarmNonCrop - AfarmNonCrop AgLabor - HHAgSmallLand APaper - CCoal&Petro - ACoal&Petro Incorporated Capital - HHAgSmallLand

120

Table 5.

0.183

AChemical - Manufacturing Labor - HHNonAg Urban Low Income AChemical - Service Labor - HHNonAg Urban Low Income AChemical - Professional - HHNonAg Urban Low Income AChemical - Incorporated Capital - HHNonAg Urban Low Income AChemical - Unincorporated Capital - Companies - Government - HHNonAg Urban Low Income AChemical - ACoal&Petro - CCoal&Petro Manufacturing Labor - HHNonAg Urban Low Income AChemical - ACoal&Petro - CCoal&Petro Service Labor - HHNonAg Urban Low Income AChemical - ACoal&Petro - CCoal&Petro Incorporated Capital - HHNonAg Urban Low Income AChemical -ACoal&Petro - CCoal&Petro Manufacturing Labor - HHNonAg Urban Low Income AChemical - ACoal&Petro - CCoal&Petro Incorporated Capital - HHNonAg Urban Low Income

0.014

1.424

0.02

10.9

0.005

1.582

0.008

4.6

0.005

1.435

0.007

3.7

0.001

1.506

0.002

1

0.001

1.801

0.002

1.3

0.009

1.595

0.015

8

0.003

1.769

0.005

2.7

0.015

1.667

0.025

13.9

0.002

1.799

0.003

1.9

0.001

1.849

0.003

1.4

Oil Price Increase

HHNonAg Urban Low Income

121

122

IWAN J. AZIS

POLICY RESPONSE On the basis of the general premise that ‘‘growth lowers poverty,’’ the concept of growth elasticity of poverty is often used because it reflects the distributional pattern of growth as well as the level of initial inequality and the level of economic development in the countries under study (Bourguignon, 2002–2003; Ravallion, 1997). The policy implication includes elements beyond just growth itself to reduce poverty. It should include distributional changes, initial income inequality, asset inequality, and some control variables (e.g., education, infrastructure, and macroeconomic stability). An oil price shock always posed difficult policy choices for oil importers and exporters alike. Traditionally, surging oil prices would have caused import bills to rise (affecting the trade balance) and put a burden on the government budget through higher subsidies (fiscal balance). The latter holds the key to the problems of how monetary authority in each country responds to the inflationary pressure. The selected policy will determine the economic activity, hence incomes of different households, and eventually the price level that will influence the poverty line. In reality, however, it is hardly the case that policy makers take a single policy. Instead, they adopt a set of policies (policy mix). It is the interactions among these policies that will fundamentally determine the macroeconomic outcomes, income distribution, and poverty. Empirical evidence from five countries (China, India, Korea, Thailand, and Indonesia) are used to highlight the policy dynamics and policy conflicts that emerge when the international price of oil increases. The analysis is conducted by using VAR technique, a brief description of which is shown in Appendix C. The basic causality in the model is running from fuel subsidy to the domestic price. The monetary policy response to the inflationary pressure is represented by higher interest rates, whereas government expenditures on SOC reflect the policy response from the fiscal front. When the interest rates are raised, inflation and poverty line are expected to decline. When SOC expenditures are increased, incomes of the poor are expected to increase. Subsidy reduction in China caused the domestic fuel prices to increase. Between January 1, 2003 and March 28, 2006, China’s gasoline and diesel retail price rose by 46 and 40 percent, respectively. In May 2006, China raised gasoline and diesel prices again by 9.6 and 11.1 percent, respectively. Although the government announced that eventually subsidies would be eliminated, it would take several years to accomplish such a goal considering the dependency of vulnerable segments of the population on cheap fuels,

Oil Price Increase

123

particularly for agricultural activities.8 The 2007/2008 crisis also postponed the plan. The VAR results show that changes in China’s CPI significantly affect the country’s poverty line. When inflation moves up with domestic fuel price, the poverty line tends to increase. Meanwhile, incomes of the poor households in rural areas are significantly influenced by the growth of valueadded in the agricultural sector. This causality holds for both changes in domestic kerosene price and in diesel price. Efforts to reduce poverty should therefore focus on inflation control and agricultural sector development (see Figs. D1 and D2 in Appendix D). Although in the medium run, higher fuel prices tend to lower manufacturing output, in the short run, it may not be so because of strong demand, both domestic and export demand, for China’s manufacturing products. Thus, given the positive impact of manufacturing on agricultural output, there is no negative short-run effect on the latter and hence on the incomes of the poor. But if the cut is on kerosene subsidy, manufacturing output tends to fall in the short-run and so does agricultural output. Consequently, incomes of the poor in rural and urban areas are affected negatively. Therefore, in the short run, a higher price of kerosene would hurt the rural poor more (see Figs. D3 and D4 in Appendix D). This is the reason why a policy to reduce subsidy often differentiates fuel products; for example, subsidy for those that affect the poor more (e.g., kerosene) are reduced less. The mechanisms of subsidy provision also differ between countries. There is also a question whether the potential negative effect of the price increase on the poor can be compensated by other forms of subsidies and income transfers. In response to the world oil price increase, in 2005, the Chinese government gave $1.25 billion to the oil company Sinopec to offset its refining losses. On May 2006, however, the government introduced a mechanism to offer subsidies to disadvantaged communities and public service sectors as well as to collect special fees from oil producers that sell domestically produced crude oil. This new mechanism included a series of simultaneous measures to shield lower-income farmers by giving direct cash compensation, as well as to protect the public transport sector and taxi drivers from higher fuel costs. Subsidies were also handed out to the fishing and forestry sectors, and to rural transport and urban bus companies. As a way to make oil companies shouldered their social responsibilities, beginning in March 2006 if prices of domestically produced crude oil exceeded US$30 per barrel the government imposed a special profit tax on these companies.9

124

IWAN J. AZIS

Looking at the VAR results, SOC spending in China does not seem to be tightly related to what happens with the domestic prices of fuels in general, although the relation with the kerosene price is rather significant. Although the fuel price may be one element to consider, other factors are more dominant in determining the SOC spending in China. But the VAR results also show that SOC has a positive and significant impact on the incomes of the poor, especially those living in the rural areas (see Figs. D5 and D6 in Appendix D).10 Thus, China’s fiscal policy can be effective in combating poverty if it is combined with monetary policy that prevents the poverty line from rising (see Figs. D7 and D8 in Appendix D). In the Indian case, a significant amount of subsidy was maintained even after the surge in the world oil price. The Petroleum Ministry announced in May 2006 that state oil companies subsidized 393 billion rupees ($8.7 billion) worth of liquefied petroleum gas (LPG), kerosene, diesel, and petrol during the fiscal year (2005–2006) ended March 31.11 In total, India issued $2.6 billion in bonds to compensate the companies. The government allowed state-run refiners to raise fuel prices by approximately 7% since January 2006. The VAR results show that a higher price of kerosene does not seem to cause an immediate inflationary concern. Only if the higher price continues for five or six months will the interest rates increase. This is different from the case of higher diesel price in which the interest rates will respond immediately, and effectively lower the inflation rate (see Figs. D9 and D10 in Appendix D). Thus, similar to the China case, an increase in nonkerosene price is more inflationary, and keeping inflation low is consistent with protecting the poor by lowering the poverty line. Household incomes are determined by what happens with the real sector if oil price increases. As shown in Figs. D11 and D12 (Appendix D), a higher kerosene or diesel price can hold off India’s economic growth. But the two generate different effects on the pattern of relation between GDP and poor household incomes. If the kerosene price increases, GDP growth falls, and the adverse impact on the income of rural poor happens instantly. But if the diesel price increases, it will take sometime for such a shock to affect incomes of the rural poor.12 If the fall of income occurs along with the increase of poverty line, the poverty incidence is likely higher. Thus, as predicted, poor households are more sensitive to changes in kerosene price than in diesel price. Broken down the GDP by sectors, the effect through agricultural sector holds a similar pattern as above, except that it will take some time for the increased price of both kerosene and diesel to affect negatively the incomes of the poor. In contrast, the effects through the manufacturing sector works

125

Oil Price Increase

more immediately. The VAR results also indicate that if the growth of India’s services sector falls due to kerosene price increase, the effect on the rural poor is only short term but immediate. For urban poor, on the other hand, the effect is not immediate but will last longer. Interestingly, almost an opposite pattern applies to the effect of diesel price that works through services sector: it is immediate and lasting longer for rural poor, whereas for urban poor it is not immediate and lasting only for a short term (see Figs. D13 and D14 in Appendix D). The positive effect of SOC expenditure on urban poor is immediate and significant, whereas it takes almost two years for the effect to be felt by the rural poor. However, what happens with the fuel prices does not seem to affect significantly the government’s decision on expenditures for SOC (see Figs. D15 and D16 in Appendix D). One of the striking results from the case study of India is that, in general, kerosene price is less sensitive than diesel price in response to changes in subsidy policy. Indeed, as shown in Fig. 8, over the period the kerosene price is relatively more stable. The Indian government seems determined not to hurt the poor by not allowing the kerosene price to fluctuate too much. In Korea, higher inflation rate leads to higher poverty line. But unlike in China and India, the role of fiscal policy, that is, government expenditures on SOC, is influenced by what happens with the domestic fuel price. As shown in Fig. D17 (Appendix D), a higher diesel price prompts higher expenditures on SOC, and this has a stimulating effect on the incomes of poor households. The VAR results associated with this channel are all statistically significant. For the increase of gasoline price, the results are

Fig. 8.

India: Kerosene and Diesel Wholesale Price Index.

126

IWAN J. AZIS

similar (see Fig. D18 in Appendix D). Thus, the role of SOC in raising the incomes of the poor is quite significant in Korea. The impact of higher diesel price on the overall growth of the economy should be more of a concern than the impact on inflation. This explains why the interest rates tend to be lowered when the diesel price increases (see Fig. D19 in Appendix D). Such a policy does not lead to higher inflation or higher poverty line. The case of gasoline price is slightly different. A higher price leads to an inflationary pressure that led Bank of Korea to raise the interest rates. But the VAR results also show that in the short run the intended effect on inflation is difficult to achieve (see Fig. D20 in Appendix D). Thus, as far as the effect of price changes on inflation in Korea is concerned, gasoline matters more than diesel. The latter is considered more critical in influencing the real sector (output growth). Gasoline and diesel price increase generates a dampening effect on manufacturing output. In turn, this creates an adverse impact on Korea’s agricultural sector. Since the welfare of poor households is influenced by this sector, the poverty condition tends to worsen unless the income effect of SOC expenditures is significant and the poverty line does not increase (see Figs. D21 and D22 in Appendix D). The net effect on poverty is determined by the interplay of these factors. Thailand imports 90 percent of its crude oil. It consumed approximately baht 701 billion worth of energy or 11 percent of GDP in 2004. As the world oil price surged, the government introduced a subsidy program in January 2004. It spent baht 92 billion to subsidize retail fuel prices since its introduction, most of it was used to curb diesel price to protect millions of farmers who made Thailand the world’s biggest rice exporter. With mounting fiscal pressure, however, the subsidy program for petrol was terminated in October 2004, and for diesel in May 2005 (subsidy for LPG retail prices through the State Oil Fund continued). Since then, retail oil prices had been allowed to float. There had been a sign of declining demand as a result (e.g., diesel demand dropped by more than 10%). Between mid-August and mid-September 2006, the diesel price was reduced four times and gasoline prices nine times. Those reductions resulted in falling food and beverage prices. The Energy Fund Administration Institute (EFAI) cut cooking gas subsidies by half in preparation for a delay in the price flotation of cooking gas. But the public bus fare was not reduced, as the diesel price remained high. Oil companies were considering further cut for the fuel prices assuming the world oil prices would continue to soften in the near future. To understand the dynamics of fuel prices, the VAR is conducted separately for kerosene and diesel prices.

Oil Price Increase

127

Subsidy reduction in Thailand does not seem to have a short-run effect on the kerosene price. But when the price goes up, the fear of inflation is countered by higher interest rates. As the inflationary pressure is contained by such a policy, after a certain time lag the poverty line declines. A similar outcome is derived for the case of diesel price (see Figs. D23 and D24 in Appendix D). Incomes of the poor are influenced by what happens in the agricultural sector and the extent of SOC spending. Manufacturing output is affected negatively by higher fuel prices; so are agricultural output and incomes of the poor. This applies to both kerosene and diesel (see Figs. D25 and D26 in Appendix D). The only difference is, while the effect of a higher kerosene price on agricultural output is felt only after four months, the effect of a higher diesel price is felt immediately. Indeed, Thailand’s farming activities, including the rice sector, relied heavily on diesel fuel. On the other hand, the causal relation from inflation to household incomes is more significant under the kerosene price shock. The effect of a higher fuel price on SOC spending is significant and immediate, suggesting that the government of Thailand tends to respond to higher fuel price by raising the SOC expenditures to mitigate the potential adverse consequence of the general price increase. Such a policy works effectively as the VAR results show that SOC spending has a positive and significant impact on the incomes of the poor. This causality holds for both, kerosene and diesel (see Figs. D27 and D28 in Appendix D). Among the five cases analyzed, the size of fuel subsidy in Indonesia was the largest. In 2004 and 2005, it amounted to $7.4 billion and $7.8 billion, or approximately 3–4 percent of GDP, respectively. The subsidy was given to the oil company responsible for distributing and selling the fuel products for transportation and household use. Following the surge in the world’s oil price, the government implemented a very sharp rollback of subsidies in October 2005, causing the retail prices of gasoline and diesel to jump dramatically (i.e., by 125 percent). Realizing the potential devastating impact on the poor, the government began allocating budget for cash subsidy for the poor, the amount of which was estimated at Rp 18 trillion for 15.5 million poor families between October 2005 and September 2006. Promising not to raise fuel prices again in 2006, the government then attempted to cut fuel consumption by replacing fuel for power generation with coal, and lowering fuel imports to ease fuel subsidy.13 Other subsidies were maintained, in some cases even raised. In addition, the government raised the electricity subsidy to Rp 32.2 trillion from Rp 17 trillion.

128

IWAN J. AZIS

Even with the price supports above, the drastic and sudden cut of fuel subsidy in October 2005 that caused a sharp increase in domestic fuel prices took a heavy toll on the economy, especially on poor households. The poverty incidence rose almost immediately in 2006, reversing the declining trend that had taken place since 2002. Much of the increase was due to a higher poverty line. As shown in the VAR results in Figs. D29 and D30 (Appendix D), higher kerosene price due to the subsidy cut leads to higher interest rates. However, the price pressure is too strong to be contained by the monetary policy. The resulting inflation rate continues to rise, and with only two-month lag the poverty lines in the rural and urban areas also increased. In the case of diesel price, higher inflation rate immediately raised the two poverty lines (see Figs. D31 and D32 in Appendix D). As the kerosene price goes up, the negative effect on the real side of the economy is felt immediately. In the case of diesel price increase, the effect is significant only few months after the price shock. Under both cases, the effect on the incomes of the poor in urban and rural areas takes place instantly and significantly (see Figs. D33–D36 in Appendix D). Thus, like in other countries, the poor’s welfare in Indonesia is also more sensitive to kerosene price than to diesel price. Similar to China and India, fluctuations of SOC expenditures in Indonesia have been influenced by factors other than fuel prices. However, surprised by the extent of the detrimental effects of subsidy cut on poverty and other social conditions, the government raised SOC-related subsidies in the following year. Indeed, in preparing for the cut the government argued aggressively that the inflationary pressure would be modest, and that the number of the poor could decline because a compensating income policy would be implemented after the subsidy cut. Both predictions turned out to be incorrect. As shown in Fig. 9, the surge of domestic fuel prices due to world oil price increase differed in the five countries under study. The largest and most dramatic increase occurred in Indonesia, due to the drastic cut of the fuel subsidy. When the compensating income policy failed due to poor preparation and weak administrative capacity, the poverty conditions worsened. It is clear from the preceding analysis that policy conflicts abound when a government has to respond to an oil price increase. The most important policy conflict is not only between maintaining macro stability and lowering poverty, but also between achieving short-run and long-run goals. Only by analyzing the intricate mechanisms through which an oil price shock affects the rest of the economy, we can find comprehensive resolutions to the policy conflicts. Although the analysis in this chapter does not directly take into

129

Oil Price Increase 1300 1200

China Fuel Index India_high speed diesel Indonesia_ADO Korea Diesel India_light speed diesel Indonesia_IDO Thailand_high speed diesel

1100 1000 900 800 700 600 500 400 300 200

Fig. 9.

M5 2006

M12 2005

M7 2005

M2 2005

M9 2004

M4 2004

M11 2003

M6 2003

M1 2003

M8 2002

M3 2002

M5 2001

M10 2001

M7 2000

M12 2000

M2 2000

M9 1999

M4 1999

M6 1998

M11 1998

0

M1 1998

100

Domestic Fuel Price Increases in Some Countries.

account the changes in the prices of other goods, it demonstrates the complexity of interrelations between production sectors, factors, households, and other institutions, that policy makers should consider in selecting the appropriate policy response in line with the development goals.

NOTES 1. Iraq–Iran war in the 1980s, and Iraq’s occupation of Kuwait in 1991 were two recent examples. 2. The disaster caused the U.S. oil production to fall. At its peak, approximately 1.4 mb/d of production in Gulf of Mexico was shut in, affecting 14 refineries. Key pipelines were closed, with problems spilling over to shipping and other forms of oil transportation. The International Energy Agency (IEA) estimated that the storm had reduced U.S. product supply by close to 38 million barrels over September (IEA, 2005). The effect quickly spread to the rest of the world. Gasoline prices jumped by 30 and 13 percent in Europe and Asia, respectively. Although several measures were taken, that is, cargoes already on water were diverted, clean tanker rates for medium range vessels between Europe and the U.S. doubled, and the obligation to hold 90 days of net import demand was removed by the IEA, the oil price continued to surge. 3. A case in point was the U.S. experience during the 1990s. The positive relation between unemployment and oil prices gradually weakened. In addition to less

130

IWAN J. AZIS

accommodative monetary policy and declining energy-to-GDP ratio, a robust world economy and strong demand, not the supply shock, played an important role in the weakening of the relation. 4. It is important to distinguish the different impacts when using a world real oil price (in $US) and a local real oil price (local currency), due to the role of exchange rates or national price variations. A test is also needed to check whether oil price shocks are Granger cause economic activities, and whether there is a co-integrating long-run relationship between oil prices and economic activity. This is important to ensure that the impacts of oil shocks on output, household incomes, and poverty line prices are limited to the short run. As far as the effect on price level is concerned, studies on the past episodes of oil price shocks show that when the shocks are expressed in local currencies the effect on domestic inflation is more significant and short run in nature (Cunado & de Gracia, 2004). 5. The relation between increases in the nominal price of oil and economic activity has been shown rather unstable. Hence, it requires more complicated specifications of the ‘‘true’’ relation. 6. Dollar and Kray (2000) is probably the most quoted study of this type. They used data from 80 countries over four decades, concluding that income of the poor rises one-for-one with overall growth. Accordingly, policy-induced growth is as good for the poor as it is for the overall economy, and that the effect of growth on income of the poor is no different in poor countries than in rich ones. More surprisingly, according to the study, reducing government spending is even better for the poor than for the rest of the population and that neither democracy nor spending on health or education makes any difference to growth. 7. Note that in Table 3, the total influence of the following path (transport and telecommunication - capital - companies - urban high-income) is also 0.014. However, since there are more nodes in this path (4 versus 3), its total influence cannot be compared with the three-node case. 8. The country has been facing a serious challenge in terms of closing the gap between urban and rural population. 9. This energy price reform plays a vital role in the implementation of China’s 11th Five-Year Plan for 2006–2010. 10. The VAR results for the urban poor are similar. 11. Note that India’s fuel subsidies were absorbed in the balance sheet of state owned petroleum companies. 12. A similar pattern is found for the effect on incomes of the urban poor. 13. On March 2006, for example, the government issued a regulation to allow retailers to blend 10 percent of bio-fuels into fuel products, part of a drive to cut oilbased energy consumption from 50–55 percent in 2005 to 10–15 percent of total energy by 2020.

131

Oil Price Increase

APPENDIX A Consider the following SAM multiplier: yn ¼ An yn þ x ¼ ðI  An Þ1 x ¼ M a x where yn is the vector of endogenous receipts, An the matrix of average expenditure propensities, and x the vector of exogenous receipts. Although useful, this multiplier does not reveal the network of paths through which an oil price shock is transmitted. Decomposing it into individual paths of transmission, the essence of SPA, one yields more useful insights (see Defourny & Thorbecke, 1984). SPA recognizes three types of ‘‘influences’’: (1) direct influence (DI), (2) total influence (TI), and (3) global influence (GI). The starting point in a SPA is to equate the intensity of an ‘‘influence’’ traveling from pole i to pole j as the SAM average propensity aji (an ‘‘influence’’ is the metaphor in the literature for an additional flow of income or output, which can be either positive or negative). Define an arc (i, j) as the link between the pole of origin and that of destination. Define a path as a sequence of consecutive arcs – the length of which is the number of arcs between the origin and destination poles. For example, arc (i, j) is a path with unit length, whereas path (i, x, y, j) has length equal to three. An elementary path is a path that does not pass more than once through the same pole. In contrast, a circuit is a path for which the starting pole of an influence is also its destination pole. For example, the path (x, y, z, x) is a circuit. The DI(i-j) travels through the elementary path that connects two poles i and j: DI(i-j) ¼ aji. But DI(i-j) can also travel along a path (i, . . . , j) with length greater than one, in which case its magnitude is the product of the intensities of the arcs connecting the path. TI(i-j) along the path (i, . . . , j) is defined as DI(i-j) plus all of the indirect effects of the circuits formed along that path. For example, the DI axi ayx is transmitted back from y to x, creating a circuit with the magnitude (axi ayx) (axyþazy axz), which in turn is transmitted back to y. Hence, a series of feedback impulses are generated along that circuit, yielding a new set of multipliers: axi ayx [I – ayx (axyþazy axz)] 1. To compute total influence, all terms in the equation are multiplied by ajy because an influence has to traverse the arc (y, j) before reaching the final destination at pole j. The resulting TI(i-j) is therefore TI(i-j) ¼ axi ayx ajy [I – ayx (axyþazy axz)] 1. The GI is derived by taking the cumulative impact of all total influences (see Fig. A1 which is taken from Defourny & Thorbecke, 1984, p. 122).

132

Fig. A1.

IWAN J. AZIS

Global Influence: All Elementary Paths and Circuits Linking i and j.

Consider the original node i as the value-added of oil-intensive sector, say, transportation. When oil price increases, this sector’s value-added will be adversely affected. If the increased oil prices lead to higher production costs, the sector’s output and value-added may fall. This creates ripple effects on other sectors, captured by nodes x, s, and v (e.g., fuel and gas, electricity, and food products, respectively). What happens with the transportation sector will in turn influence labor wages (represented by node y). Combined with other nonwage incomes, these will eventually determine the incomes of households, say, rural poor households (node j). Notice the two-way interactions between y and x. The reverse relation occurs because lower wage may generate lower demand for fuel and gas, in such that the dampening effect on fuel and gas is multiplied, turning higher than simply the effect that was caused by lower transport activities. But lower wages may also affect other sectors, say trade sector (node z), and this will lower the demand for fuel and gas further. Through these series of impulses, we will finally be able to measure the net-effect on each sector’s value-added, wages, and household incomes (mathematical derivations and the formulas for different types of influences are shown in Appendix A). (A decline in the value-added of food product (say, canned fish), that is, node v in Fig. A1, may result in a reduced demand for the output of fish processing industry (say, fish storage), which also falls under v category. This explains the loop from v back to v at the bottom of Fig. A1.) In applying SPA, we begin by identifying activities most affected by the oil price increase. This is done by ranking the sectors based on their oil-intensity, the information of which is taken from the respective country’s SAM.

133

Oil Price Increase

APPENDIX B Table B1. What Poor and Rich Households Spend on Their Additional Incomes. Rural Low Income China

Food Livestock Rice OthCrop Wheat

0.2041 0.1234 0.1168 0.0823 0.0698

Rural Low Income India

Food Trade Animal FCROP OTHTRNS

0.0660 0.0632 0.0600 0.0582 0.0539

Ag Employee Indonesia

FoodBev FarmCrop PublicAd Livestock Textile

0.32994 0.11753 0.10477 0.06292 0.04838

Ag Low Income Thailand

RESHOT TXTAPP CBEVER TRANS AGMAHU

0.39544 0.34757 0.23083 0.22815 0.22074

Urban High Income Food OthServ Apparel Commerce Livestock

0.0857 0.0688 0.0482 0.0468 0.0394

Urban High Income OWNRSHIP MEDIC TRADE OTHTRNS OTHSRVICE

0.1427 0.0802 0.0763 0.0651 0.0517

Non-Ag Urban High FoodBev Textile PublicAd Restaurant Paper

0.1771 0.0958 0.0705 0.0679 0.0583

Non-Ag High Income TXTAPP RESHOT TRANS CRESTAT CHLTHMD

0.0817 0.0690 0.0497 0.0459 0.0429

Notes: OthServ, other services; OthCrop, other crop; FCROP, food crop; FarmCrop, farm crop products; Livestock, livestock products; FoodBev, food, beverages, and tobacco manufacturing product; AGMANU, agricultural processing.

APPENDIX C As argued throughout the study, in determining the resulting poverty, the policy response matters more than the oil price increase itself. The relevant

134

IWAN J. AZIS

policies in this case are fuel subsidy, interest rates, and government expenditures for SOC. But these variables are endogenous, because they are implemented in response to the oil price shock. This makes it difficult to infer how changes in these variables affect poverty line and household incomes. To solve this simultaneous causality problem, it is necessary to find components of the preceding policy variables that are exogenous to the state of the economy. These can be obtained by employing a VAR. A VAR is a regression of an n by 1 vector of endogenous variables, yt, on lagged values of itself: X yt ¼ A1 yt1 þ    þ Ap ytp þ t ; Eðt 0t Þ ¼ This equation can be inverted and represented as an infinite-vector moving average process yt ¼ t þ C 1 t1 þ C2 t2 þ C 3 t3 þ    One problem with the preceding equation is that the individual error terms in et may be contemporaneously correlated. The Cholesky factorization can be used to obtain orthogonalized innovations. This approach involves finding a lower triangular matrix P such that S ¼ PPu, where S is the variance– covariance matrix of et. In this case, the preceding equation can be rewritten as yt ¼ PP1 t þ C1 PP1 t1 þ C2 PP1 t2 þ    ¼ G0 ut þ G1 ut1 þ G2 ut2 þ    where Gi ¼ CiP, ut ¼ P1et, and E[ututu] ¼ I. This last equation represents the macroeconomic variables (yt) as functions of the orthogonalized residuals (ut). If components of ut represent shocks to fuel subsidy, interest rates, or expenditures for SOC, impulse-response functions can trace out the dynamic responses of world oil price to household incomes, or to poverty line. The variables used include the first difference of fuel subsidy, domestic fuel prices, SOC expenditures, real activity (GDP and sectoral value-added), interest rates, inflation, poverty line, and household incomes. An unrestricted VAR is used since there is no evidence of cointegration between variables. In calculating impulse-response functions, the ordering of the variables matters. The variables ordered prior are assumed to affect within the month the variables ordered later but not to be affected within the month by them. For example, to determine the poverty line, the world oil price is placed first as the original shock, then it is assumed that changes in the fuel subsidy are causally before the other variables. The size of fuel subsidy is determined by government’s decision (exogenous) during the sample period. It is then assumed that interest rates respond to the domestic fuel prices, and the inflation rate is influenced by the interest rates, thus they are placed after

135

Oil Price Increase

these variables in the recursive ordering. After inflation, data on poverty line is placed the last. For the model to determine the incomes of poor households, following the world oil price shock it is assumed that changes in the fuel subsidy are causally before real activity (e.g., GDP, manufacturing, and agricultural value-added). The scenario of capturing government’s policy response is done by inserting SOC expenditure before sectoral value-added, particularly value-added of agricultural sector, before ending it with incomes of the poor households. The sample period (monthly data) extends from January 1999 to December 2005. Thus, there are 84 observations for each equation. Different time lags are used depending on the best statistical results.

APPENDIX D

Fig. D1.

China Impulse Response: Fuel Subsidy - Fuel Price - Interest Rate Inflation - Poverty Line.

136

IWAN J. AZIS

Fig. D2.

China Impulse Response: Fuel Subsidy - Kerosene Price - Interest Rate - Inflation - Poverty Line.

Fig. D3.

China Impulse Response: Fuel Subsidy - Fuel Price - Manufacturing - Agriculture - Rural Poor.

Oil Price Increase

137

Fig. D4.

China Impulse Response: Fuel Subsidy - Fuel Price - Manufacturing - Agriculture - Urban Poor.

Fig. D5.

China Impulse Response: Fuel Subsidy - Kerosene Price Manufacturing - Agriculture - Rural Poor.

138

Fig. D6.

IWAN J. AZIS

China Impulse Response: Fuel Subsidy - Kerosene Price Manufacturing - Agriculture - Urban Poor.

Fig. D7. China Impulse Response: Fuel Subsidy - Fuel Price - SOC - Rural Poor.

139

Oil Price Increase

Fig. D8. China Impulse Response: Fuel Subsidy - Kerosene Price - SOC Rural Poor.

Fig. D9. India Impulse Response: Fuel Subsidy - Kerosene Price - Interest Rate - Inflation - Poverty Line.

140

Fig. D10.

IWAN J. AZIS

India Impulse Response: Fuel Subsidy - Diesel Price - Interest Rate - Inflation - Poverty Line.

Fig. D11. India Impulse Response: Fuel Subsidy - Kerosene Price - GDP Rural Poor.

Oil Price Increase

141

Fig. D12.

India Impulse Response: Fuel Subsidy - Diesel Price - GDP Rural Poor.

Fig. D13.

India Impulse Response: Fuel Subsidy - Kerosene Price - Services - Rural Poor.

142

IWAN J. AZIS

Fig. D14.

India Impulse Response: Fuel Subsidy - Kerosene Price - Services - Urban Poor.

Fig. D15.

India Impulse Response: Fuel Subsidy - Diesel Price - Services Rural Poor.

Oil Price Increase

143

Fig. D16.

India Impulse Response: Fuel Subsidy - Diesel Price - Services Urban Poor.

Fig. D17.

Korea Impulse Response: Diesel Price - SOC - Poor Households.

144

IWAN J. AZIS

Fig. D18. Korea Impulse Response: Gasoline Price - SOC - Poor Households.

Fig. D19.

Korea Impulse Response: Diesel Price - Interest Rates - Inflation Poverty Line.

145

Oil Price Increase

Fig. D20.

Korea Impulse Response: Gasoline Price - Interest Rates - Inflation - Poverty Line.

Fig. D21. Korea Impulse Response: Gasoline Price - Manufacturing Agriculture - Poor Households.

146

IWAN J. AZIS

Fig. D22. Korea Impulse Response: Diesel Price - Manufacturing Agriculture - Poor Households.

Fig. D23.

Thailand Impulse Response: Fuel Subsidy - Kerosene Price Interest Rates - Inflation - Poverty Line.

Oil Price Increase

147

Fig. D24.

Thailand Impulse Response: Fuel Subsidy - Diesel Price - Interest Rates - Inflation - Poverty Line.

Fig. D25.

Thailand Impulse Response: Fuel Subsidy - Kerosene Price Manufacturing - Agriculture - Poor Households.

148

IWAN J. AZIS

Fig. D26. Thailand Impulse Response: Fuel Subsidy - Diesel Price Manufacturing - Agriculture - Poor Households.

Fig. D27. Thailand Impulse Response: Fuel Subsidy - Kerosene Price - SOC - Poor Households.

Oil Price Increase

Fig. D28.

149

Thailand Impulse Response: Fuel Subsidy - Diesel Price - SOC Poor Households.

Fig. D29. Indonesia Impulse Response: Fuel Subsidy - Kerosene Price Interest Rates - Inflation - Rural Poverty Line.

150

IWAN J. AZIS

Fig. D30. Indonesia Impulse Response: Fuel Subsidy - Kerosene Price Interest Rates - Inflation - Urban Poverty Line.

Fig. D31.

Indonesia Impulse Response: Fuel Subsidy - Diesel Price - Interest Rates - Inflation - Rural Poverty Line.

Oil Price Increase

151

Fig. D32.

Indonesia Impulse Response: Fuel Subsidy - Diesel Price - Interest Rates - Inflation - Urban Poverty Line.

Fig. D33.

Indonesia Impulse Response: Fuel Subsidy - Kerosene Price - GDP - Rural Poor.

152

Fig. D34.

IWAN J. AZIS

Indonesia Impulse Response: Fuel Subsidy - Kerosene Price - GDP - Urban Poor.

Fig. D35. Indonesia Impulse Response: Fuel Subsidy - Diesel Price - GDP Rural Poor.

153

Oil Price Increase

Fig. D36. Indonesia Impulse Response: Fuel Subsidy - Diesel Price - GDP Urban Poor.

This page intentionally left blank

CHAPTER 6 MITIGATING CLIMATE CHANGE INTRODUCTION The proportion of long-distance migrant birds at the border of Germany, Austria, and Switzerland decreased between 1980 and 1992 because winter temperature increased. Deterioration in the Amazon, observed in the Xingu National Park, has become more serious during the past few years. The melting of Glazier in many places, especially in the European Alps and in the United States, is another classic example of changing ecosystem caused by the climate change. One prediction indicates that the glaciers in Mount Kilimanjaro will be gone by 2020. Natural disasters, also associated with climate change, are predicted to increase not only in terms of the frequency but also in the size of damages they can cause. From Bangladesh to Vietnam, from Pacific Islands to Latin America, scientists predict that hectares and hectares of mangroves will be flooded due to the rise of the sea level. People in some countries suffered from undrinkable water because of the saltwater intrusion caused by climate change–related hurricanes. In the other extreme, some places experienced drought that caused serious water shortages and loss of biodiversity and agricultural products (e.g., Australia, in 2002, and India, in 2003). Disappearance of habitats and ecosystems caused by climate change are serious, but a short-term challenge in terms of declining productivity in many farm areas are equally serious, if not more so. Concentration of carbon dioxide in the atmosphere is one of the sources of climate change. Its level is influenced by the level of carbon dioxide emissions that can be caused by natural as well as human sources.1 While the impact of the two sources on the climate is the same, the focus of policy debates has been on what is the most efficient way to reduce the emissions from human sources. Since there is already warming in the system from the long history of previous emissions, mostly by industrialized economies, the analysis of climate change tends to be directed toward mitigating the change in future climate and adapting climate change that is uncontrolled by current policy. The problem is that climate system is complex. The level of 155

156

IWAN J. AZIS

our understanding about how it works is still limited, albeit improving. The availability of data is also inadequate. This explains why climate models are still imperfect and incomplete; there remain disagreements as to the actual climate trends, the underlying causes, and their future developments. Indeed, there is a large uncertainty in any climate projection. The impact of climate change, however, is more certain.2 Central to the impact analysis is what happens with the productivity of each sector. In the agricultural sector, there is a strong relation between weather and productivity or yields, for example, crops have become weaker at withstanding extreme heat above the optimal temperature. Some studies have confirmed that the relation is robust and consistent across space, time, and type of crops. Schlenker and Roberts (2008) also found that the relation tends to be nonlinear: the slope of the decline above (below) the optimal temperature is much steeper (flatter).3 Since each sector’s productivity is affected differently by climate change, and its influences on carbon emissions and poverty depend on where the change in productivity occurs, one needs to distinguish the effect of productivity change in different sector. For developing countries, the effect is likely greater since many of them are at a geographic disadvantage; they are already warmer and suffer from high rainfall variability, and typically primary sector-dependent and very climate-sensitive. Adaptation to climate change is also more difficult because incomes are low, health provision is inadequate, and the quality of public services is generally poor. In its news release, February 24, 2009, the Asian Development Bank (ADB) described the seriousness of the challenge faced by Asian countries: ‘‘Even if carbon emissions are capped at current levels the region faces a 10% reduction in crop yields by 2020, and rising sea levels that could displace millions of people living in coastal areas in Bangladesh, India, the Maldives and the Pacific Islands. In addition, about 1.2 billion people could face freshwater shortages by 2020, and up to 34% of the region’s coral reefs are likely to be lost by 2050.’’ Thus, concerns toward poverty in developing countries take a central stage. Scarcities of food, water, and health are all closely related to poverty, and they are the outcome of various factors, an important one of which is the decline in productivity. These scarcities can intensify the competition and create conflict between communities, societies, regions, and countries. Increased poverty can also affect migration patterns, which, in turn, can exacerbate the conflict. What the analysis in this chapter intends to show is that the economic effect of climate change and its repercussions on the potential policy conflict is not easy to predict. They are complex, involving numerous variables that

157

Mitigating Climate Change

interact with each other, and some of the interrelations are highly nonlinear. One of the most important questions regarding the policy conflict is whether the likely outcomes of policies to mitigate the climate change are in conflict with other socio-economic objectives. In many countries, resources needed for such policies are scarce and might otherwise be devoted to tackling other pressing issues such as unemployment and poverty. It is shown in this chapter that by simulating a model applied to a resource-rich country, conflicts between mitigation policies and improvements in socioeconomic conditions do not have to arise if appropriate policies that can lead to productivity improvements are implemented effectively. After discussing the concept of discount rate and the potentials of conflict associated with it, the subsequent section demonstrates how the impact of climate change is estimated by simulating an economy-wide model under different mitigation scenarios.

DISCOUNT RATE One of the critiques against the Kyoto Protocol points to the absence of a clear link between climate change policies and economic and environmental objectives. Yet, such a link is necessary if any proposed policy is to be effective. The role of market and prices is indispensable. Reducing carbon emissions at low cost and large quantities will involve a portfolio of policies based on markets and incentives system that can ultimately generate the necessary technological change. There is a need to have price signals consistent with a carbon goal that will encourage the emergence, adoption, and diffusion of existing and new technologies. One of the relevant questions in this regard is should one use fixed prices and let the quantity be determined by the market or should quantities be fixed and prices be determined by the market? The analogy in the financial market is to use fixed prices in the short run and fixed quantities in the long run. There is a wide disagreement about the extent of needed cuts in the emissions. Some argue that huge cuts are needed from where they are now if we are to have a meaningful effect on global warming. The Stern Review on the Economics of Climate Change is of such an opinion. Others contend that since there are too many intractable uncertainties surrounding the estimates of costs associated with climate change, making sharp and immediate reductions now would be irresponsible.4 In effect, it is a situation where we are compelled to make current decisions about highly uncertain and speculative events in the far distant future.

158

IWAN J. AZIS

Central to these contrasting views are the rate of time preference (social discount rate) and the elasticity of marginal utility. As it turns out, the two cannot be chosen independently to match observable variables (refer Heal, 2008). A low curvature (e.g., the logarithmic utility function) implies a relatively high social discount rate, whereas a strong risk aversion to intergenerational inequality – as represented by a high curvature – implies a low social discount rate. Implementing the derived policies, let alone coordinating them, is difficult, since these policies likely cross many jurisdictions – international organizations, national, state, and local governments, and they also lead to winners and losers (distributional issues within and between countries). What is discounting? It is a factor in investment decisions which involves the relative weight of future and present payoffs. The discount factor will generally depend on growth, that is, consumption level in the future relative to that now, and on the social utility or welfare function used to evaluate consumption (i.e., marginal utility of consumption). The importance of discounting in the analysis of climate change cannot be over-emphasized. As stated in the Stern Review: ‘‘discounting and the ethics from which it is derived is of great importance for the analysis of climate change.’’ In a climate change analysis, what is relevant is not discounting consumption or dollars, but more on using the social discount rate (calculated in percent per year), that is, discounting future welfare. In this case, relative weights are assigned to different generations or people. A zero (positive) social discount rate means that future generations are treated equally (less equally or discounted) as compared to the present or nearer generations. Consider a case where there are two arguments in a constant elasticity of substitution (CES) utility function: the environmental stock that produces a flow of services (ES) and produced consumption (CS): U ¼ ½dCSa þ ð1  dÞ ESa 1=a If the two are complementary (there are technological limits to the possibility of substituting consumption goods for environmental goods), a tends to be close to zero. Thus, if the consumption of the environmental good rises, the consumption discount rate on the consumption declines as the marginal utility of the consumption good will increase. The question is what discounting to use? Opinion varies, conflicts of perception arise. The discounting rate used in the Stern Review is very small (0.1), essentially close to zero (refer Nordhaus, 2008). Such intergenerational neutrality assumption produced magnified impacts in the distant future, suggesting that deep cuts in today’s emissions and all consumption are

Mitigating Climate Change

159

necessary. An alternative stance is to believe that each generation should leave at least as much total societal capital as it inherited. Both cases imply an intergenerational conflict, as the present and future generations utilize resources and protect environment to pursue their own interests. The conflict occurs especially when consumption implies the exhaustion of resources, both renewable and non-renewable, as well as the degradation of environmental resources such as soil, water, and air. When the consumption produces some wastes, for example, radioactive waste, the persistent toxic substances will last for a long time, exacerbating the intergenerational equity problems as it will produce a negative impact on the health of future generations. That is, another type of conflict may also arise, that is, between intergenerational equity and intra-generational equity (Okrent, 1999). An alternative view holds that societies maximize the minimum consumption along the riskiest path (e.g., stockpiling medicines, water, and food to contemplate for possible drastic events). Then, there is the Rawlsian view that claims societies should maximize the economic well-being of the poorest generation, suggesting that there should be a sharp increase in the current consumption. Obviously, a different ethical stance suggests different conclusion. However, if the discount rate is treated as being uncertain in the long run, one should theoretically work with the lowest of all the possible rates (Weitzman, 2007; Heal, 2008). Another type of intergenerational conflict related to the issue of discount rate concerns investment, particularly government investment as part of the mitigation policy. The question of interest is how much spending should be made to mitigate the climate change given different interest of different generations, that is, young versus old population. As people have become increasingly aware of the consequences of the aging population and growing costs of pensions and health care, they may feel that their pensions may be less secure in the future. In such a case, the current young population is likely to reduce the net present value of their expected income due to lower expectations. Hence, a relatively low discount rate is used. Take another scenario with a similar outcome. Due to either high savings in the past or generous pensions, the current older population is in a relatively well-off position, suggesting more spending should be made for the current young population. However, the budget allocation for mitigation policy may have to be tightly controlled if the number of elderly have increased fast and is expected to continue in the near future. Otherwise, they have to pay for the program through higher taxes, while they may not be able to benefit from the averted productivity decline due to the policy. Thus, the choice of discount factor may also have to be linked with this type of intergenerational conflict.

160

IWAN J. AZIS

IMPACT ANALYSIS AND POTENTIAL CONFLICTS The impact of climate stress on the probability of conflict is complicated and not easy to predict. Scarcities of various resources can become the seed for violent conflict, as in the case of the dispute over water access between India and Pakistan and between neighboring countries in Latin America. Lower productivity and falling production can shred job opportunities for millions of farmers and raise poverty, both of which are capable of inciting conflicts through competition over food and ‘‘environmental refugees’’ or through dispute over land. The intensity of conflict is likely to increase further should there be draught, floods, or other types of climate change–induced natural disasters. The difficulty to make a precise estimate arises because these factors interact with political and other governance issues. They may also interact with ethnic problems. On the contrary, a natural disaster or any factors causing environmental stress can also produce a peace agreement or useful collaboration instead of conflict or violence. Post-tsunami Aceh in Indonesia is a case in point. Negotiations to end a conflict in the region that lasted for almost 30 years and led to widespread violence and displacement were kick-started after the tsunami disaster in December 2004.5 Memorandum of Understanding (MoU) and Peace Agreement were finally reached in Helsinki in 2005. Indeed, when conflicting parties suffer from environmental stress or other disputes over resources, generally dialogues will build trust and prompt negotiation. The dispute over water access between India and Pakistan is another notable example, where the multiyear conflict had served as an important feature of conflict resolution negotiations that culminated in 2004. At any rate, while the effect of climate change on conflict seems obvious, estimating it is a different story. Many factors can influence the effect, where the interactions of those factors with climate stress and socio-economic variables can determine the extent of the potential conflicts. The key challenge is how to minimize the risk of a conflict. For this purpose, we need to analyze the effect of a climate change on socio-economic variables (e.g., output, productivity, inequality, and poverty) by exploring alternative mitigation policies. To the extent that it is not the amount of emissions in any year but the concentrations in the atmosphere that matters for the climate, any climate models should deal directly with the stock measure (i.e., the emissions over a long period of time that cumulate into concentrations). The problem is that climate system is so complex. It is difficult to trace the transmission mechanisms that will eventually impinge on the socio-economic variables.

Mitigating Climate Change

161

For countries with rich natural resources, another challenge may arise. In many of these countries, natural resources and land had been degraded and depleted. In the process, rapid emissions of carbon dioxide drove changes in global climate. The latter poses a grave threat, and it has become a major obstacle for welfare improvements and poverty reduction across many dimensions. It also lowers the future growth capacity by way of reducing the productivity in many sectors. The standard principle to follow is that the use of non-renewable resources must proceed at a rate that is declining faster than or equal to the rate of depletion (the percentage amount of resources being extracted and used during a specified time interval). In the case of renewable resources, the use must proceed at a rate that is less than or equal to the rate of natural replenishment. For developing countries, however, the principle cannot be detached from what will be the implications on poverty and other backwardness. This suggests that income and prices invoked by productivity changes are among the important variables to evaluate. The economy-wide effects of several scenarios associated with productivity declines driven by climate change and resource depletion are explored to get a better understanding of the numerous linkages between activities, poverty, and the rest of the economy including monetary and financial variables. This is done by way of simulating recursive dynamic computable financial general equilibrium (CFGE) model.6 A brief feature of the model is discussed in the appendix. The version of the model used here has a simple recursive dynamic structure, where the dynamics in the model originate in three sources: (i) accumulation of productive capital and labor growth; (ii) shifts in production technology; and (iii) the putty/semi-putty specification of technology. In the aggregate, the basic capital accumulation function equates the current capital stock to the depreciated stock inherited from the previous period plus gross investment. However, at the sectoral level, the specific accumulation functions may differ because the demand for (old and new) capital can be less than the depreciated stock of old capital. In this case, the sector contracts over time by releasing old capital goods. Consequently, in each period, the new capital vintage available to expanding industries is equal to the sum of disinvested capital in contracting industries plus total saving generated by the economy, consistent with the closure rule of the model.7 No matter how comprehensive the model is, the application in each country must take into account the unique characteristics of the country under study. To account for the role of natural resources and efforts to resolve the conflicting development goals, Indonesia is used as a case study.

162

IWAN J. AZIS

The model is simulated by concentrating on three primary activities considered resource-depleting and sensitive to the climate change (food, mining, and primary non-food products that consist of forestry and fisheries). In each of the aforementioned activities, the country has been facing substantial challenges, that is, declining productivities due to climate change, and reconciling past and current resource use with sustainable growth objectives. One of the approaches to use is to ask what happens if the resource-based activities proceed in an unsustainable way that can cause not only a climate stress but also a serious problem of resource depletion. For the purpose of the analysis, three scenarios of resource depletion are generated. These scenarios are based on the premise that the primary sector will continue to be an important component of gross domestic product (GDP) in the foreseeable future and that there is a critical link between climate change, resource depletion/degradation, and the growth patterns that works through changes in the productivity of different sectors.8 The consequences of each scenario are analyzed by comparing the simulation results with those generated under a baseline scenario during the period of 2005–2050. The model is calibrated on exogenous growth rates of population and labor force. It is important to note that the simulation results shown later should not be seen as long-term forecast; it is intended only to illustrate the economic mechanisms at work.

BASELINE VERSUS ALTERNATIVE SCENARIOS In the baseline scenario, the past trend is assumed to continue in the future. More importantly, it essentially assumes that there is no climate change or the effect of it is negligible. The capital efficiency continues to improve, in such that the GDP under this scenario is estimated to grow at 6 percent annually. The resulting inflation rate is around 7 percent per annum, the exchange rate is relatively stable with an annual rate of depreciation of 1 percent, the agriculture share in GDP will decline to reach 12 percent by 2050, and the employment generation is slow, mimicking what has occurred in the past few years (Table 1). Assuming no significant changes in the development strategy, it is expected that a worsening income inequality will persist.9 When alternative scenarios around the baseline are simulated, the technical efficiency parameter is held constant, and the saving/investment relation endogenously determines the growth of capital. Given the current

163

Mitigating Climate Change

Table 1.

Baseline BAU SCI SC2

Average Growth Rates, 2005–2050.

GDP (percent)

Inflation (percent)

Exchange rate index

6.00 5.32 4.99 6.20

7 7.30 7.20 6.90

1.00 1.25 1.17 0.60

Source: Results of the author’s CFGE model simulations.

rate of depletion, economic and technological constraints, and information related to climate change, in the so-called Business-as-Usual (BAU) scenario, the dynamics are calibrated by assuming a much slower growth of productivity in the climate-sensitive primary sectors (food, fishery, forestry, and mining).10 This scenario reflects a trend with climate change but with limited efforts for mitigation. The loss of GDP when the policy response is limited can grow rapidly, reflecting the increased risks associated with climate change.11 The average annual growth rate is around 5.3 percent or 0.7 percent lower than under the baseline. As a result, the labor absorption is persistently smaller, reaching 30 percent lower than in the baseline by 2050. This implies that the country will have to face a serious unemployment problem. The inflation rate is slightly higher than in the baseline (7.3 percent annual average), and the exchange rate will depreciate faster at 1.3 percent per annum (Table 1). The poverty impact tends to be unfavorable as the deviation of the poor household’s income from the baseline is larger than the deviation for the poverty line (Fig. 1). This is despite the fact that the price and output of agricultural food will not be much different from the baseline, as also the case with the domestic and export demand for food (no additional food surplus is assumed). The share of the agricultural value added in GDP is consequently similar (Fig. 2). An alternative scenario (SC1) is developed to demonstrate the devastating effect of the high-climate setting with catastrophic and non-market impacts when no efforts of mitigation and adaptation are made.12 A balanced growth path is specified, in which the ratio between labor and capital (in efficiency units) is held constant over time.13 No productivity improvement is assumed in this scenario. That is, given degrading environmental inputs in some sectors due to climate change and resource depletion, the output level will be lower. Thus, the results should capture the long-term expense of neglecting climate change and the cost of resource depletion.

164

Fig. 1.

IWAN J. AZIS

Incomes, Poverty Line, Food Output, and Prices. Source: Results of the Author’s CFGE Model Simulations.

Even if the country maintains a conservative target of 6 percent growth, in this scenario such a goal will be undermined significantly due to no productivity improvements especially in the resource-based sector. The resulting GDP growth rate is less than 5 percent per annum with a rapidly growing GDP gap in this scenario compared to the baseline. The effect of a slower GDP growth on employment is devastating. The annual rate of inflation is the worst among all scenarios, such that by 2050 the price of the poverty line reaches 10 percent higher than in the baseline. Combined with the income of the poor being the lowest among all scenarios (Fig. 1), this suggests that the poverty incidence will increase significantly. As the output of food declines (at 0.2 percent annually), its price will increase and consumption will decline. The welfare of food consumers will consequently deteriorate. The resulting agriculture share in GDP falls rapidly to reach 11.4 percent by 2050. With a large number of employment in the agricultural sector, the income share of the poor falls by more than 0.1 percent each year. Clearly, this scenario depicts the opportunity cost of government failure to recognize the effect of climate change and resource sustainability as a generalized policy objective over the next 50 years.

Mitigating Climate Change

Fig. 2.

165

Demand for Food, Exports, Agriculture Share, and Gini Index. Source: Results of the Author’s CFGE Model Simulations.

In the last scenario (SC2), it is assumed that serious attempts are made to foster a more integrated development of biological resources and alternative energy sources to mitigate the climate change and avoid further resource depletion. To the extent that concerns over the effect of climate change coincide with the trepidation over the growing food crisis, it is further assumed that the country is compelled to do all-out efforts to adapt the effect of climate change on this sector. This is presumably done by introducing an environmentally friendly agricultural policy that will improve productivity of the sector.14 The same is assumed for the mining sector. More specifically, the country is assumed to recognize the value created when trees store carbon dioxide and prevent global warming; it is actively engaged in the trading of carbon credits to prevent existing forest from destruction and get paid for doing so such that the sector’s productivity will continue to improve.15 In the fishery sector, an emphasis is put on promoting investment, developing coastal fisheries, and undertaking innovative activities designed to use the country’s tropical habitats in a sustainable manner, for example, aquaculture. The adverse effects of resource depletion in the mining sector are also recognized, although their precise nature varies

166

IWAN J. AZIS

according to demand responses. For example, progressively higher extraction costs undermine profits and output to a relatively greater extent because of more elastic export demands than in the food, forestry, and fishery sectors, which have large sales shares in the domestic market and are therefore less severely affected. Since weather shocks typically destroy capital investment and disrupt production, it is further assumed in this scenario that a steady improvement in the capital productivity across all sectors can be maintained (at 0.5 percent per annum). Thus, all sectors and agents will gain under this scenario, although some may gain more than others. The results show that the GDP growth rate will reach 6.20 percent per annum throughout 2050. This is despite the fact that a rather conservative estimate of productivity improvements in resource-based activities is used. It demonstrates how Indonesia’s enormous biological potential can be realized through innovative approaches to resource development and use, including the use of new technologies. It appears that there is no trade-off between mitigating climate change and maintaining macroeconomic stability. As shown in the consumers price index (CPI) trajectories, the general price level is likely lower, suggesting that the GDP growth associated with sustaining productivity increase as a result of appropriate policy response to climate change is non-inflationary. While more sustainable resource utilization has a neutral impact on exports, partly because the exchange rate tends to appreciate, the higher GDP growth is stimulated mostly by higher investment and consumption, including food consumption. Indeed, the food production is much more favorable under this scenario, causing food prices to fall faster than under any other scenario. With more affordable food products, consumption steadily grows, that is, at 1.8 percent per annum. This helps lower the poverty incidence. With a lower general price level than in any other scenario, the resulting poverty line also has a similar pattern. Combined with a higher income of the poor (see Fig. 1 under SC2), the poverty condition tends to improve. Thus, there is no trade-off between growth, stability, and poverty reduction if appropriate policies are fostered to mitigate the climate change and maintain productivity improvements. The ‘‘win-win’’ situation delivered by the carbon credit scheme, where most financial revenue goes directly to the poor living in the villages and forest area, is a noted example of how the devastating impact of climate change can be mitigated while at the same time welfare of the poor is improved.16 However, since all agents gain from productivity improvements, and given the country’s socio-economic structure, the additional gain is likely higher for the more modern and

167

Mitigating Climate Change

technologically advanced sector.17 This explains why the Gini index does not change much in spite of a reduction in the poverty incidence.

NOTES 1. Carbon can be stored in soil and biomass, but it can be released back into the atmosphere through fire, excessive drought, overgrazing, and so on. It is a greenhouse gas that contributes to global climate change. The World Bank’s figure shows that the rate of global carbon emissions from burning fossil fuels and manufacturing cement rose by 4 billion metric tons between 1990 and 2003, where most of the increase came from high-income countries (2.09 billion metric tons) and East Asia and the Pacific (2.07 billion metric tons). 2. Impacts of climate change are typically represented by a damage function that can take a simple form dependent on regional temperature increases and the damage exponent. The latter, critical in determining the scale of the estimated impacts, can be defined by a probability distribution based on the results from existing studies (IPCC Third Assessment Report). 3. In the U.S. farm case, it is found that yields increasing in temperature up to a critical threshold of 291C for corn, 301C for soybeans, and 321C for cotton, temperatures higher than these will significantly harm yields. 4. The uncertainties range from the extent of economic damages and economic benefits in different regions at different times, the timing and extent of temperature change, future emission levels, to the impacts of temperature changes on ecological systems. The difficulties are also due to the fact that the time scales for climate policy are much longer than most other policy problems. 5. The long-standing conflict in Aceh was basically prompted by a disagreement between the Indonesian government’s insistence on central control and Acehnese’ aspiration for independence. This led to a series of rebellious movements in early 1950s. By mid-1970s, the Free Aceh Movement (GAM) was founded with the express goal of seceding from Indonesia. Although there is no clear consensus as to the number of casualties, most believe that it was in the hundreds. 6. Unlike in a one-sector model (e.g., Nordhaus & Boyer, 2000) that ignores the possibility that productivity will increase if production is shifted from low-productivity/ highly climate-sensitive sectors to high-productivity/low-sensitivity sectors, in the multisector CFGE model, such a possibility is allowed (refer also Jorgenson, Ho, & Stiroh, 2005). 7. Given the details captured in the model, a fully endogenous or ‘‘closed-loop’’ dynamic specification is not feasible. Instead, a sequential static approach is taken, computing equilibria using a five-year interval. 8. In each of the primary sector, the extent to which resource depletion and climate change will prevent sustainable economic development and increased poverty will generally depend on the relative size of the sector and its linkages to the rest of the economy. 9. The reason why income distribution is more closely watched in developing countries has more to do with politics than altruism. Yet, it is essential to recognize that

168

IWAN J. AZIS

political sustainability is a necessary condition for economic sustainability. Acute and chronic income disparities can undermine economic stability in countless ways, and effective policies for long-term development must anticipate distributional consequences. 10. It is well known that many estimates of the rate of productivity growth are biased upward since the growth accounts on which they are based do not take into account the depletion of resources or the degradation of natural capital. 11. The direct impact of climate change is generally felt slowly at the beginning before the full direct and indirect impacts take place. 12. On the non-market impact, it is reported that in the past decade, Indonesia has lost one species a day and that 70 percent of the original habitat of those species has been destroyed. Unless urgent action is taken, these losses in biodiversity will continue at the same rate in the future. Obviously, there are still many other nonmarket impacts that are difficult to quantify. 13. This involves computing in each period a measure of Harrod-neutral technical progress in the capital–labor bundle as a residual. This is a standard calibration procedure in dynamic CGE modeling – refer Ballard, Fullerton, Shoven, and Whalley (1985). 14. I have shown elsewhere that by far the most important area for resource sustainability and renewal is the food sector: an annual productivity growth of 3 percent can double food output and contribute more than 10 percent to annual GDP growth within 20 years (Azis & Salim, 2004). 15. Consistent with the 1997 Kyoto Protocol to limit carbon emissions, polluters can ‘‘offset’’ some carbon production by planting forests. This raises the possibility of countries, regions, or corporations in one country compensating for their carbon emissions by planting forests in another. Such a possibility turned into reality in Aceh, Indonesia, in 2008 when Merrill Lynch announced that it will invest $9 million (pay $4 per credit for 500,000 credits per year over the next four years and buy $1 million as an option to acquire more credits) to help save a 1.9-million acre tropical in Aceh, called Ulu Masen. Merrill will pay villagers in Aceh to stop logging their forests; the money will be used to train the villagers in alternative livelihoods such as growing coffee, cocoa, or palm trees for oil. In exchange, Merrill will get carbon credits (carbon offsets, the ‘‘crop’’ in carbon farming) that will meet quality standards set by CCBA (Climate, Community and Biodiversity Alliance). The latter, whose members include Conservation International, the Nature Conservancy and the Rainforest Alliance, and companies as BP, Intel and SC Johnson, acts as a regulator. 16. Such a conclusion, however, cannot be generalized; the ultimate outcome depends on the country’s level of development, economic structure, and development policy in general. 17. Since technology requirements for this sector are also high, imports will likely increase under this scenario.

APPENDIX In the CFGE model, the general price level is endogenously determined through the interactions between supply and demand of both domestic and

169

Mitigating Climate Change

foreign goods, in which the demand consists of domestic and import demand (PD  DþPM  M): PQp ¼

PDp  Dp þ PMp  M p , Qp

where Q, D, and M refer to total supply of goods available, goods produced and sold domestically, and imported goods, respectively, and subscript p denotes the economic sector. PQ, PD, and PM are the corresponding prices. A similar notion applies to the prices of domestic output, PX:   PDp  Dp  1  tdomp  ttdp þ PEp  E p , PXp ¼ Xp where tdom and ttd are indirect tax rates on domestic goods and trade and transport margin rate on domestic goods, respectively. The above specification is based on a production structure that is modeled as a set of nested CES function. In the first stage, the production function (expressed as value-added) is determined, in which primary inputs are the right-hand-side variables. Since a considerable portion of intermediate inputs are imported, the composite intermediate inputs INTM are modeled as a CES function of domestic and imported inputs (DOMINTM and FORINTM). In the second stage, the domestic output is specified as a CES function of the value-added VA and the composite intermediate inputs. It is this separation of value added and intermediate inputs that holds the key in the climate change–driven productivity analysis. It reflects changes in the input–output proportion, hence the sectoral productivity. The model simulations discussed in the text are conducted by focusing on this factor and the technological parameters in the production functions. The resulting price of value-added PV is as follows: PVp ¼

PXp  X p  PINTMp  INTMp , VAp

where PINTM is the price of intermediate inputs. The unit price of imported and domestically produced intermediate inputs (PDINTM and PFINTM) are, respectively, X faadpp;p  PDpp g, PDINTMp ¼ pp

PFINTMp ¼

X pp

faampp;p  PMpp g

170

IWAN J. AZIS

where aad and aam are the share parameters, and subscripts p and pp refer to the production sector. From these two equations, the price of composite intermediate inputs is derived: PINTMp ¼

PDINTMp  DOMINTMp þ PFINTMp  FORINTMp INTMp

The value-added price PV determines the nominal value added. After taking into account the indirect tax (INDTAX), TARIFF, and subsidy (SUB), the nominal GDP (GDP at current price or GDPCUR) can be derived: X GDPCUR ¼ VAp  PVAp þ INDTAXp þ TARIFFp  SUBp  SUBMp The general price level (PINDEX) is derived as the GDP deflator X PINDEX ¼ GDPCUR=GDP, where the GDP at constant prices is derived from the expenditure side. To link the climate change–driven productivity with the poverty analysis, prices of basic commodities that form the poverty line and incomes of poor households are derived endogenously in the model. To arrive at the prices of basic needs presumably consumed by the poor, distinctions between urban and rural and formal and informal are made. Thus, the rural poverty line prices are distinguished from prices in urban areas, and so are the consumption patterns. Hence, the relation between P and PL is as follows:   X P r;u  ar;u PL ¼ p  PDp , PDAVG where apr,u is the sectoral consumption parameter that captures different consumption patterns between rural and urban. Next is to estimate the incomes of poor households. Income of different households consists of factor income (wages), transfers, and income from the financial assets. Given the labor market segmentation (wages being strongly sector-specific), the labor income is specified as follows: P 0 1 X p = FACDEMp;fl pp  ð1rÞ PV p p A , @ WAGESp ¼ PINDEXr  PV0p PDL0p where PDL0 and FACDEM are, respectively, labor productivity before the shock and factor (labor) demand. Note that r, the price electivity of wages, can play a critical role in determining the effect of a policy shock that cause

171

Mitigating Climate Change

changes in prices on wage income. The average wage rates for each labor category are arrived at on the basis of the above sectoral wage rates and the wage shares of each type of labor in each sector (wsharep,fl): X WFfl ¼ WF0fl  WAGESp  wsharep;fl p

The unemployment and rural–urban migration reflect the slack in the labor market as such that the total supply of labor equals the demand for labor plus the unemployed labor force. Household income from sources other than factor income is denoted by ITRAN. It consists of transfers among households, firms, and rest of the world (OTRAN), government subsidy (GTRAN), and returns on financial assets (RTRAN): ITRANi;j ¼ GTRANi;j þ OTRANi;j þ RTRANi;j; where i, j reflect different institutions. The inclusion of financial assets, which is the core feature of CFGE model, is particularly important amid what has been happening during the past few years in the country under study (Indonesia), where there exists an excess liquidity (saving) characterized by a faster growth of investment in financial assets than in real sector. This phenomenon is noticeable from the Flow-ofFund table showing total saving being greater than total investment in the real sector (most excess saving goes to the financial investments). Unlike in a standard non-financial CGE model, investment is endogenously determined by the investment function and the institutional portfolio allocations (the ‘‘fixed’’ asset investment). The institutional savings will also be a part of the institutional balance sheet as they represent the changes in wealth ((Asset ¼ LiabilityþWealth) is the core balance in the financial module). While in general the rate of return for each asset is determined based on the supply and demand of financial assets, some returns determine the supply, for example, the supply of time deposit follows the demand and the given deposit rates, and others determine the demand, for example, the demand for government bonds is determined by how much is offered and at what rate. The saving-investment closure in the model departs drastically from the neo-classical specifications. Investment in sector p is specified as a function of value added VA (output accelerator), the interest rates rn, and the exchange rate EXR: INVp ¼ lp VAlp1p ð1 þ rnðcÞÞl2p ðEXRÞl3p ,

172

IWAN J. AZIS

where rn(c) is the loan interest rate, and ls are constant; the size of l3 depends on the sensitivity of investment on the exchange rate fluctuations. This specification reflects the financing behavior (i.e., bank-dependent) of agents and the balance sheet constraint (Bernanke & Gertler, 1989; Krugman, 2001; Aghion, Bacchetta, & Banerjee, 2001). When the exchange rate is stable, few firms are constrained by their balance sheets: the direct effect of EXR on AD is minor. On the contrary, if the exchange rate depreciates sharply, agents’ ability to expand is adversely affected. The portfolio allocation of institutions is specified based on the assumption that there is no perfect substitutability, as suggested by Tobin (1970), Brunner and Meltzer (1972), and Bernanke and Blinder (1988) and used in Bouguignon, Branson, and De Melo (1989), and Thorbecke (1992). Incomes received by household h from institution j are determined as follows: X rns LiablGj;s , RTRANhh;j ¼ AssetsHhh s

where rns is the return on asset type s, LiablGj,s is the stock of asset type s transferred from institution j in the beginning of the period, and AssetsHhh is the share of total asset held by household j. For institution i, the latter is defined as: X X AssetsHi ¼ ðrns AssetlGs;i Þ= ðrns AssetlGs;j Þ, s

s;j

where AssetlGs,i and AssetlGs,j are, respectively, the stock of asset type s in the beginning period held by institution i and the stock of asset type s transferred from institution j. For example, if i is urban rich household and s is the time deposit, the above equation indicates the ratio of time deposit held by urban rich household over the time deposit of all households. Thus, the ratio shows how much of the total time deposit is held by the urban rich.

CHAPTER 7 LESSONS AND CONCLUSIONS Conflict in various forms is a natural consequence of the power of one party to take actions and decisions that affect others. It can be studied from many different standpoints. In policy conflict, the relative complexity or simplicity depends very much on whose interests are being considered as new measures are debated. Many policy issues are more complex than most people thought. They are simplified for public debate. Some interests are marginalized while others remain central to the discussion. Realizing the inherent trade-offs, knowing what elements of debate are present and absent, and what are the causes of the policy structure that we observe are all central to understanding the representative nature of policy conflicts. This is what the book is all about. When the 2007/2008 financial crisis hit the United States and the rest of the world, much interest was directed toward policy response and the consequent conflicts of ideas to deal with the meltdown. Yet, our understanding will not be complete without recognizing the fundamental role of global imbalances in making the crisis possible by pushing down the global interest rates and driving investors toward riskier assets.1 The meltdown actually reflected the unwinding of the global imbalances. The interplay of the U.S. accommodative policy in response to the deflationary pressure emerged from a series of financial crisis during the 1990s – reinforced by the Iraq war, and the resulting strong demand that led to a higher oil price contributed to the widening of global imbalances. The size of the U.S. current account deficit (CAD) was unprecedented, almost two-third of the entire global deficits, while on the surplus side, close to half of global surpluses originated in East Asia. The oil price surge also made oil-producing countries becoming major players in the surplus camp. While the U.S. investment-saving gap was negative, that in East Asia was large positive. These imbalances led to various types of conflict, for example, trade, interpretations of law, multinationals versus domestic industries, and conflict of interest regarding the value of the exchange rate. The focus of discussions in Chapter 2, however, is on the emerging policy conflicts faced by policy makers. 173

174

IWAN J. AZIS

As the largest contributor to the world deficit, the United States and European Union (EU) tend to believe that making the currencies in East Asia (especially China) more flexible would have been the answer, and lowering the saving rate in Asia would have reduced the imbalances and averted the crisis. They reasoned that super-abundant savings (saving glut) from fast-growing emerging nations such as China and oil-exporting countries put downward pressure on yields and risk spreads everywhere. As one member of the Executive Board of the ECB argued: ‘‘there has been an insufficient production of alternative assets around the world, compared to the large amount of savings available’’ (Smaghi, 2008). The Fed Chairman Ben Bernanke was even more unabashed, blaming everyone but the Fed for the housing and credit bubbles. In his speech at the International Monetary Conference, Barcelona, June 3, 2008, he put the fault on foreign investors and the global savings glut, without mentioning easy money created by the U.S. low interest rate policy. In contrast, surplus countries tend to believe that fiscal deficit, excess consumption, and low saving rate in the United States hold the key to the problem.2 They argued that the U.S. CAD, the most striking feature of global imbalances, had been caused by the U.S. fiscal deficit since 2000 (the ‘‘twin deficits’’). There was clearly a fundamental difference in opinion about what caused the imbalances, and it consequently posed a conflict in terms of what policy response should be in place. Although the 2007/2008 crisis was largely caused by the excesses of the U.S. financial system with excessive debt creation and risk mispricing, most of the toxic assets were distributed not only in the United States but also in the emerging markets where market participants bought assets without fully understanding their risk profile. Nonetheless, everyone agreed that global imbalances had a lot to contribute to the crisis. Selecting the most effective policy to mitigate the imbalances was where things were unclear. Raising interest rates seemingly makes sense, but if one takes into account the longterm dynamics of the process, the resulting initial dollar appreciation could widen the U.S. CAD further due to lower competitiveness. The eventual currency depreciation could also be large and less orderly. The shift in the preferences toward U.S. assets as a result of higher interest rates would be manifested in the anticipated large depreciation due to higher net debt position, hence higher interest payment. By specifying the relations between current account and portfolio balances, it is argued in Chapter 2 that a policy mix of lowering the interest rates and reducing U.S. fiscal deficit would be the right thing to do to help lower the global imbalances. Each of these policies should not be taken

Lessons and Conclusions

175

as a stand-alone measure; a drastic reduction of fiscal deficit alone might bring the economy into recession, and lowering the interest rates without correcting the fiscal deficit could create an easy money environment and a bubble in the economy. With the financial crisis in place, however, lowering the deficit is no longer a feasible option. Even if the fiscal deficit can be eventually reduced, an orderly adjustment remains hard to come by unless other countries also take action simultaneously. Indeed, resolving global imbalances requires commitments and cooperation from all countries. International institutions such as the International Monetary Fund (IMF), the World Bank, and the Regional Development Banks should play a role. But being the world’s largest economy and at the same time holding almost two-third of the entire global CADs, the United States, along with the surplus countries of Asia, hold the key to the resolution.3 Easy money and massive capital inflows from abroad fueled borrowing spree including in the housing market. With the growing financial innovation and the wish to fulfill the ‘‘American Dream,’’ subprime lending thrived since late 1990s. Believing that housing prices would always go north, such lending attracted mortgage companies, banks, homebuyers, and investors alike. Because banks sold off the underlying mortgages to investors, and the rating agencies assigned good rating to many of those debts, no one thought about the risk. Risk sharing was also ascertained by credit default swap (CDS), which essentially covered investors against losses from a default. When homeowners began to find it difficult to pay the mortgage, lenders got hit, and the complex web of trades started to disintegrate, creating multiple losses and logistical headache for many parties. Like house of cards, the shaky structure was blown by negative financial forces. Since banks were also involved in mortgage debts, financial contagion kicked in. The entire financial market suffered from huge losses. The resulting liquidity crisis spread to consumption and investment credits, causing a major slowdown in the economy. As many firms went bust, insolvency problems set in. This injured market confidence including confidence on the dollar. From a bigger picture, the whole episode was quite predictable if we look at the experience of other countries that suffered from similar crises before. Influenced by the neoliberal view of the ostensible benefits that financial deregulation would bestow, many countries adopted financial liberalization throughout the 1980s and 1990s by reducing or abolishing restrictions on financial sector and capital movements. This was the analogy of relaxing regulations limiting U.S. domestic banks to the role of financial intermediaries and not engaging in more speculative activities. For a while the policy produced stronger growth and capital inflows. But it also created

176

IWAN J. AZIS

a destabilizing force that eventually led to a whole series of financial and economic crises in Latin America, East Asia, Russia, and more recently, Europe and the United States. In emerging markets, financial liberalization and deregulation increased the number of banks, creating easy credits and reckless loans. In the United States, commercial banks were no longer obliged to evaluate risk and creditworthiness of borrowers since the loans they issued could be sold as collateralized assets to the secondary bond markets, and if necessary re-packaged them into other classes of yield bearing financial assets (securitization). This implied that the U.S. banks’ primary concern was to sell collateralized assets that were selected based on yield rather than on credit profile of borrowers. Banks transferred illiquid assets into their affiliates and sold them to secondary bond markets. The secondary market would then convert the collateralized assets into mortgage-based securities (MBSs) issued according to their yield (interest and principal payments from the underlying pool of mortgage debt). These MBSs, which represent new classes of engineered financial assets known as CDOs (collateralized debt obligation, or derivatives of derivatives) grew rapidly to become one of the largest pools of financial assets traded in capital markets. Through this Ponzi scheme, the traditional role of banks to evaluate risk was transferred to credit agencies. Ownership of assets and risks were separated when other players such as mortgage companies and real estate developers entered the market. This was due to the off-balance sheet position of the securitized loans. Everybody benefited from the system, everyone was having a party. No one talked about risks, let alone regulating the market, because no one wanted to be party pooper. But when defaults mounted, contagion hit, home prices fell, and the entire structure of debt collapsed. Falling home prices made it harder for homeowners to refinance, causing foreclosures to surge and consumers to lower spending. Party’s over. The potential of such chain-reaction effects was clearly overlooked by both investors and policy makers-cum-regulators.4 Thus, financial institutions that were supposed to manage risks, evaluate credit worthiness, and allocate capital did not do a good job. The crisis reflects gross mismanagement, greed, and wrong kinds of regulatory rules, from which bubbles in housing and credit markets have developed (e.g., funds raised in U.S. credit markets nearly doubled during 2002–2007). In December 2008, the National Bureau of Economic Research (NBER) made it official that the U.S. recession began in December 2007. The conclusion was made after they looked at three key monthly economic indicators, including employment, industrial output, and sales.

Lessons and Conclusions

177

Monetary expansion alone failed to provide the solution. It might have averted a bigger fall of output, but it could also weaken the dollar value. More seriously, with very low interest rates and low inflation, the economy entered a dangerous territory of becoming ensnared in a deflation cycle and liquidity trap.5 Consumers delayed purchases, and household debt burdens became heavier (remember Japan?). Should that happen, the only choice for the policy makers and the Fed is to use the unconventional policy, for example, buy up bonds, securities and anything whose price shows signs of going down. Judging from the costs to the economy (credit loss was estimated around US$ 2 trillion for 2009 and 2010), monetary expansion ought to be combined with fiscal stimulus. The latter had to be huge and targeted.6 This is a drastic departure from conventional thinking and is outside the theoretical boundaries of mainstream economics that advocates low taxes, fewer regulations, and less public spending. Keynesian economics is back, and free market ideology that assumes people behave rationally and do the right thing is seriously challenged. A standard anti-crisis policy a-la IMF is also challenged. In most crisis situations, the IMF policy has been always leaning toward tightening both the fiscal policy and the monetary policy. Cut the fiscal expenditures and raise the interest rates. During the Asian Financial Crisis, for example, the IMF demanded that fiscal deficit was slashed and interest rates raised to an exorbitant level. When the Asian governments wanted to inject public money to support the capital of ailing financial institutions, the IMF strongly opposed the idea. All this was in a stark contrast with the even-handedness of the IMF’s endorsement of the U.S. Federal Reserve’s decision to sharply lower the interest rates, and the U.S. government’s huge fiscal stimulus and preference for massive bailouts during the 2007/2008 crisis. It is a mind-boggling volte-face! Only years after the Asian crisis was over, the IMF admitted that it made mistakes in Asia by putting a spin on the likely economic downturn and misjudging the market’s response.7 The damage was done. Few would doubt that had Asian countries not followed the IMF policies, the situation could have been more tumultuous. While the needed policy response to the 2007/2008 crisis may be clear, the length of the recession is not. Take the case of fiscal stimulus. This is always one area where economics and politics collide. Delayed expenditure tends to lower its effectiveness. Timing is everything, especially when market confidence deteriorates. As long as confidence is not restored, all remaining options are bad solutions. Some believe that the crisis will end only after the end of the housing bust. Yet, as argued in Chapter 3, the housing excess

178

IWAN J. AZIS

supply is expected to remain for some time, implying that the recession is likely to last long. The bottom line is that there is a great deal of uncertainty about almost everything associated with a financial meltdown of this epic proportion. The arising policy conflicts cannot be more severe as the shortterm objective (recovery) clashes with the longer term and more structural goals (governance, regulations, infrastructure, competitiveness, Social Security and Medicare, etc.). What should rise from the ashes? So many mistakes had been made, one of them was to allow investment banks that grew fast after the repeal of the Glass-Steagall Act in 1999 to conduct risky lending. They originally focused on client businesses such as merger and acquisition advice. But lured by profit, they shifted the main activity to trading. Some did it on a large scale. Discussed in Chapter 3, this led to the meltdown. Making them to return to their original role is warranted if future crisis is to be averted. Better (stricter) rules on liquidity for banks, especially during stressed markets, may also be needed. Since CDS played a prominent role in the crisis, regulators must insist that banks hold on to a significant portion of credit risk when they package loans into securities before selling them. On the hedge fund operation, it is long overdue for regulators to impose rules that would make hedge fund’s leverage be disclosed and controlled. Some sort of capital and liquidity standards must be met by these financial firms. Given the increased complexity of financial instruments, some accounting principles exacerbating the 2007/2008 crisis also need to be reviewed and, when necessary, replaced. Will the crisis worsen or mitigate the global imbalances? Given the severity of the crisis that shock consumers, a change in the U.S. consumers’ behavior is likely to happen. The prospect of higher savings is now better than ever. Borrowing by households and business sector also tends to decline, and so does import. That means economies around the world will have to find new markets for their products or sell less. This will gradually shrink the imbalances, although the speed of the change depends on how fast the adjustments in other countries will take place. But if the U.S. debt continues to be viewed as the safest investment, not much change will happen in the imbalances. A scenario of worsening imbalances is also possible, that is, if American consumers continue to spend beyond its means, and foreign investors shift their perception and keep their assets in their own countries or elsewhere outside the United States. While this may reduce capital inflows and force the U.S. deficit to shrink, it can also raise savings worldwide. This will complicate the policy to mitigate saving glut. If this is followed by currency devaluation everywhere, the U.S. trade imbalances will

Lessons and Conclusions

179

remain large, if not larger. Only if the effects of a further decline in the dollar on U.S. exports exceed those of other countries’ devaluation will trade imbalances get smaller. Thus, there is an uncertainty on the effect of the crisis on global imbalances. The best way to help unwind global imbalances once the crisis is over is for the United States to adjust its excessive consumption habit and save more, and for surplus countries to bolster the domestic demand. Given the fact that economic interdependence have increased dramatically following trade and financial liberalization in the 1980s and 1990s, and economic links have deepened as companies set up worldwide production networks and financial firms operate around the world, it was quickly realized that any efforts to avert and resolve a crisis will not be effective if implemented unilaterally without the cooperation from other countries. The world is too interconnected for countries to go it alone in their policies. International cooperation is important. But many countries have also learned another lesson, that is, relying on the help of international organizations such as the IMF always comes with a price (e.g., conditionality). For some countries, the price was so high that the whole program of external support failed, and in some cases exacerbated the effect of the crisis. Countries in Asia learned this in a hard way during the 1997 crisis. This explains why there has been an increased proliferation of regional cooperation not only in trade but also in the financial sector. But any trade and financial cooperation between countries always involves some noneconomic factors, including political and institutional constraints. If unattended, these constraints can result in various forms of conflict. This is discussed in Chapter 4, using the case of the efforts of Asian countries to establish a Regional Financial Arrangement (RFA). RFA can potentially help to stabilize macroeconomic and financial sector commensurate with the attempts to prevent and manage another crisis. It can integrate the region’s financial markets to secure and strengthen the existing interdependence. It is also an attractive concept to internalize the intraregional spillovers associated with policies to reduce the global imbalances. One of the most critical issues in RFA is to determine the exchange rate regime to adopt. Ideas were floated that the 10 countries in ASEAN, China, Korea, and Japan should consider moving toward a basket system, in which U.S. dollar, Yen, and Euro are the potential currencies to be used in the basket. To fulfill the above potentials and to select the preferred exchange rate system, it is argued that member countries must recognize and weigh the prospective benefits as well as the costs and risks of each alternative, given economic and non-economic considerations.

180

IWAN J. AZIS

It is shown that when those factors are taken into account with equal rating for the benefits, opportunities, costs, and risks (BOCR), an exchange rate system based on a basket peg does not augur well with the region’s current conditions. While the system may bring short- and long-term benefits, the costs and risks of adopting it are too high. True, that a basket peg can offer some cushions against third-party exchange rate misalignment. When applied in a band system, it can also provide some flexibility to deal with asymmetric shocks. A basket system may also accommodate a certain degree of independence in the conduct of monetary policy. However, policies must be predicated not on an ideal world, instead on the world as it is. In reality, flexibility can be limited, defending the band at the margin may fail, and unless compliance is high the system can suffer from a credibility problem. The quantitative analysis in Chapter 4 clearly shows that while the potential benefits and opportunities of adopting a basket peg may be there, the costs and risks of it outweigh those benefits. A basket peg can be also problematic when viewed from the efforts to reduce global imbalances. If regional currencies are expected to appreciate to reduce the global CAD, then requiring all countries to adjust their exchange rates by the same amount against a multicurrency basket will have different repercussions to different countries, because U.S. trade shares are not the same for all countries. The needed compensatory fiscal policy may also differ because each country’s capacity to conduct such a policy is not the same. At the early stage, the IMF was against the idea of Asia having its own RFA, because it might be duplicative with the IMF programs. It could also create moral hazards. The choice of name, Asian Monetary Fund, seen as a substitute to IMF, was not helpful either. Thus, a serious conflict already appeared at the early stage. If the standard of surveillance and assessment over the state of the economy in RFA are not the same with those of the IMF, another problem may arise. A potential dispute can also set in if RFA rules are not in line with the domestic standards in each member country. The analysis finally shows that establishing a closer financial cooperation with exchange rate coordination without imposing a common exchange rate system, let alone a basket peg, bodes better for Asia at this stage of development. Only when the benefits and opportunities are rated disproportionally higher than the costs and risks will the basket system be superior. Imposing a common exchange rate system or a basket peg forcefully without considering its costs and risks will surely create policy conflicts that can vacillate the whole idea of regional cooperation. While the analysis in Chapter 4 has already scrutinized the important merits and costs of RFA, it shies away from assessing the dynamics of the

Lessons and Conclusions

181

arrangement under different stages and time horizon. It discusses neither a scenario where a centralized reserve pool can, in the later stage, support a common basket peg, nor a scenario where the issuance of Asian Currency Unit (ACU) may eventually make it the sole legal tender. But as far as the current stage is concerned, in searching for regional financial cooperation, countries should not rush into altering the exchange rate system without considering other non-economic forces at play. There are many other important policy issues that require higher priority. For Asian countries in particular, one of the issues that has already created a policy conflict is how to respond to an external shock such as an oil price surge, since many Asian countries are oil-importing. Given the oil price increase, the impact of financial crisis is likely more devastating in countries that consume and import a lot of energy sources. This happened in 2007 and the first half of 2008. During that time, the world economy was hit by both an oil price surge and a financial crisis at the same time. The two forces pushed the economy in the unfavorable direction, creating a lot of policy conflicts. For oil-importing countries, the pressures came from two fronts, rising dollar price of oil itself and higher cost in local currency per dollar value. For oil-exporting countries, the rising oil price led to a trade surplus, making the process of mitigating the global imbalances even more difficult. But the policy conflict faced by all countries were more or less the same, that is, what to do with subsidy to prevent a worsening condition particularly of the low-income groups, and at the same time to maintain fiscal sustainability. The analysis in Chapter 5 focuses on this policy conflict using examples from selected emerging markets.8 The oil price increase, began in the fall of 2004, did not slow down the world economy. The overall impact was relatively mild, largely due to the fact that the price surge was mainly caused by stronger demand from some countries, the Unites States, China, and India in particular. The downward pressure created by the oil price increase was counterbalanced by stronger demand for non-oil products. Another reason was that, although most countries in the region were net-oil importers, intensive in energy use, and relatively inefficient in energy use, the share of oil in total energy use was not always high (e.g., China). The fact that the economic system in many countries had become more flexible than before also explains why the effect of recent oil price surge was mild. The impact on poverty and social conditions had been modest too. However, when government’s policy response was misguided, focusing entirely on the government’s fiscal position, not on the welfare of majority population, the poverty conditions worsened. Most governments in

182

IWAN J. AZIS

emerging markets extended fuel price subsidy to prevent a full pass-through of the fluctuations in the world price. Wanting to relieve from subsidy burden, some countries opted to let the domestic fuel price move freely according to the world’s market. Yet, history has shown that in almost any policy issue, the poor segment of society needs to be helped first to get above the survival threshold before policy makers can let markets to start functioning. By utilizing an economy-wide model – with and without endogenous prices – the analysis in Chapter 5 shows that it was the policy response, not the oil price surge itself, that played a critical role in determining the impact on the economy and poverty. The main policy question was not whether to cut the subsidy or not, but how much reduction was necessary. Should it be done at once or gradually, and if done gradually at what pace? What alternative items to cut other than fuel subsidy? The latter was important given the fact that misallocation of resources continued to plague government budget in many countries. This is shown to be true in one of the countries used in the case study. The pro-market proponents tend to argue that allowing fuel price to move freely may hurt the poor in the short run but not in the long run. They also typically argued that it was the high-income group who benefitted more from the lower subsidized fuel price. Differentiating short-run and longrun period may have some use for analytical purposes, but it is deceptive and even dangerous when seen from the real-life condition of the poor. When households fell into poverty either because of declining income or due to higher prices, they became vulnerable to all kinds of malady (e.g., malnutrition, diseases, and low productivity). Even if their incomes and expenditures will, after some years, return to the level before subsidy cut, the effect of the misery can be longer and irreversible. It is not rare that human physical and intellectual impairments, developmental deficiencies, or even death are associated with malnutrition during early childhood. For these vulnerable households, the distinction between short-run and long-run impact is totally meaningless and absurd. Lack of early education caused by poverty also has long-term and irreversible effects on productivity. The argument that fuel subsidy benefited the non-poor is equally problematic. It may be true that transportation users, mostly non-poor, are the largest direct beneficiaries of the subsidy. But as shown in the analysis in Chapter 5, such a claim overlooks the multiplier effects, including the indirect and feedback effects of the policy. Once the multiplier effects and the differential in marginal utility are taken into account, the adverse impact of the policy is more severe for the poor.

Lessons and Conclusions

183

The subsequent analysis goes one step further by asking the following question: On which sector should the saved money from reduced subsidy be spent? By conducting counterfactual simulations, it is shown that if the money was spent on agricultural-related infrastructure, not only growth and other macroeconomic indicators would improve, but social indicators (e.g., employment, income distribution, and poverty condition) would have been also better. Supported by stronger linkages and greater accessibility and affordability of infrastructure, the benefits to the poor could easily be multiplied. Another important policy conflict is with respect to the monetary policy response to the oil price surge. It is common to argue that to control inflation and protect the low-income groups, a tighter monetary policy is needed. But this is a misguided generalization. A higher interest rate may lower the inflation rate but not necessarily the poverty rate, because the fall of inflation rate may not be accompanied by a proportional decline in the poverty line. On the contrary, slower growth due to higher interest rates may lead to falling incomes of the poor. The net outcome can therefore be a rising poverty rate. The mechanisms through which macro policy in response to a higher oil price affects poverty are too complex to be generalized. The effects of the policy on poverty line and income of the poor hold the key to the problem, and such effects can vary according to the types of policy, the structure of the economy, the price elasticity, and the mechanisms through which financial sector is linked with prices and household income. Unfortunately, this particular type of policy conflict receives little attention among economists. Indeed, the study of the link between macroeconomic policy and poverty has been held in a relatively low esteem by mainstream economists. The issue was considered relevant only at the early stage of development. As countries began to reach a higher level of welfare, the topic was disparaged as a type of antiquarianism. The renewed interest on the issue has been triggered among others by the poverty impact of macro policy response to the crisis that spread across the globe during the 1990s and the rising oil price in 2004–2008. It is no secret that energy prices and consumption are closely related to environmental issues. One of such issues discussed in Chapter 6 is about the climate change. Potentially, climate change can create conflicts by way of intense competition for food and resources, massive migration, and dispute over land. Since estimating the precise effect of a climate change on conflict is difficult (interactions with other factors can play an important role), the analysis is based on the premise that to reduce the risk of a conflict we should understand better the relationship between climate change,

184

IWAN J. AZIS

environmental degradation, and socio-economic variables. The model used in Chapter 6 is intended precisely to explore such a relationship by evaluating different scenarios of mitigating climate change and to show what would have happened with the socio-economic conditions under those scenarios. This should help enable policy makers to design an effective risk management, appropriate conflict prevention, and resolution mechanisms. The analysis begins with the discussions on the role of discount factor. It is argued that the disagreement over what discounting factor to use leaves the central question about global warming policy remains open. A small (large) social discount rate requires much deeper (smaller) cuts in emissions and consumption today. While it may be indefensible to make long-term decisions with a large positive social discount rate, adopting a strict intergenerational neutrality in developing countries may pose a risk that the cost of action exceeds the expected benefit of taking action because there are many other urgent problems they need to address (e.g., poverty, poor infrastructure, and weak socio-economic conditions). Dealing with these problems requires scarce resources that otherwise might be devoted to tackling climate change. A policy conflict is inevitable. The resolution to such a conflict may require an even more complex analysis than the ones for the financial crisis and oil price surge. With the help of a general equilibrium model, it is shown that the efforts to mitigate climate change do not have to be in conflict with the goal of raising welfare of the majority and lowering the poverty rate. Using the case of a resource-rich country as an example and by simulating a dynamic model, the analysis shows that as long as the focus of the policy is on productivity improvements the two objectives can be attained simultaneously. Another principal lesson emerging from the analysis is the need to realize the importance of systemic linkages and indirect effects of a policy, the sum total of which routinely exceed (and sometimes contradict) the direct effects that motivate policies. When such linkages are taken into account, the long-term expense of neglecting climate change and the cost of resource depletion can be substantial. The growth target will be undermined significantly if the productivity decline caused by climate change is being considered. Policies that not only mitigate climate change but also reduce resource exploitation through investment in resources that can increase their long-term productivity are essential to sustaining the transition from a low-income primary exporter to a mature and diversified economy. The simulation result also highlights the need for economic diversification and the development of nonprimary resources in resource-rich countries. The promotion of such a policy, however, is not without a challenge, especially from the world trading

185

Lessons and Conclusions

system. Developed countries tend to continue imposing high import duties on processed products and low import duties on raw materials. In reality, the political will to deal with climate change may not be as strong as expected. Climate system is too complex to understand, and to some policy makers it is too uncertain to be used as the basis for a policy. The level of our understanding about how it works is still limited, and the available data remain inadequate. Disagreements abound as to the actual climate trends, the underlying causes, and their future developments. They reflect in large uncertainty in any climate projection. But the adverse impact of climate change is more certain. For many farm activities, there is a strong (non-linear) relation between weather and productivity or yields, and this applies across space, time, and type of crops. Even if we do not like to paint a gloomy picture, the clear and devastating impact of climate change will not make the reality less pessimistic. To surmise, the different cases analyzed throughout the book clearly show that the nature and intensity of policy conflicts are important to understand because they can influence the quality of policy debate. They can also determine the extent to which outcome of the policy is in accordance with the goals. In cases where policy conflict is sharp (e.g., oil price increase and climate change), it is important to be consistent with the ultimate and fundamental goal of development, that is, raising the welfare of the poor and majority. Distinguishing short run and long run is important for some cases (e.g., global imbalances, climate change, and regional cooperation), maybe less so for others (e.g., financial crisis), but completely nonsensical for impact analysis on poverty. It is also imperative to recognize that indirect effects can be as important as direct ones, especially the two may not move in the same direction. For the purpose of policy intervention, it is essential to identify the precise mechanisms of the impact. When done properly, what seems to be in conflict may not necessarily be the case (e.g., mitigating climate change). It is also clear from the discussions that many policy issues often simplified in public debates are actually more complex than most people thought.

NOTES 1. In explaining the crisis, the then U.S. Treasury Secretary, Hank Paulson, admitted before leaving his job: ‘‘A lot more needs to be learned about global imbalances.’’ 2. A low saving rate in the United States and most industrial countries was caused primarily by low weight placed by the current generation, particularly contemporaneous older generations, on the welfare of the current generation, indicative of growing intergenerational selfishness.

186

IWAN J. AZIS

3. Until 2008, the IMF’s traditional role of crisis-fighting faded with the absence of financial crises. This raised questions about the Fund’s relevance, especially that middle-income countries in Asia, Eastern Europe, and Latin America owned a large amount of foreign reserves, in some cases exceeded the IMF’s $227 billion (before the injection from some member countries following the 2008 crisis). The emerging problem of global imbalances might come to a rescue, by letting the IMF to return to center stage through its multilateral surveillance. 4. In his testimony before the House Committee on Oversight and Government Reform in October 2008, former Federal Reserve Chairman Alan Greenspan called for imposing some of the same sorts of regulations on mortgage securities he resisted when he was in office. He acknowledged that the financial crisis had exposed ‘‘a flaw’’ in his view of how the world and markets function. Robert Rubin, former Treasury Secretary in the Clinton Administration, wrote in a letter before leaving Citigroup on January 2009: ‘‘My great regret is that I and so many of us who have been involved in this industry for so long did not recognize the serious possibility of the extreme circumstances that the financial system faces today.’’ 5. A deflationary economic cycle is when output, prices, and wages all fall, even after repeated interest-rate cuts drive the interest rates close to zero. This happened in Japan during the 1990s and in the United States during the 2007/2008 crisis. In both cases, central bank joined with the government in unprecedented steps to revive credit. Indeed, in a major crisis, the lines between central banks and governments can become fuzzier. 6. Obviously, this is in contradiction with the argument made in Chapter 2, in which a policy mix of low interest rates and reduced fiscal deficit was suggested. Such was applicable if reducing the global imbalances was the only goal. 7. Speaking about mistakes, months before the 2007/2008 crisis began, the IMF’s World Economic Outlook (WEO) gave a glowing prognosis for the world’s economy. It continued to maintain such a prognosis in late July, even as the U.S. housing market was unraveling and Bear Stearns hedge funds went bust. Interestingly, one year since taking the job, the IMF Managing Director, Dominique Strass-Kahn, had never given a speech in the United States on the U.S.-led crisis. 8. With more than 700 million people live on less than $1 a day, more than 100 million children are undernourished, and over 120 million people still live below the minimum level of dietary energy requirement – Asia has a unique position in the global efforts to lower world’s poverty.

REFERENCES Abeysinghe, T. (2001). Estimation of direct and indirect impact of oil price on growth. Economics Letters, 73, 147–153. Aghion, P., Bacchetta, P., & Banerjee, A. (2001). Currency crises and monetary policy in an economy with credit constraints. European Economic Review, 45, 1121–1150. Aguiar-Conraria, L., & Wen, Y. (2005). Asian development outlook 2005 update, Manila: Asian Development Bank. Azis, I. J. (2005a). IMF perspectives and alternative views on the Asian crisis. In: P. Gangopadhyay & M. Chatterji (Eds), Economics of globalisation. England: Ashgate. Azis, I. J. (2005b). Indonesia’s external liberalization: Policy dynamics and socio-economic impact. In: L. Taylor (Ed.), External liberalization in Asia, post-socialist Europe, and Brazil. New York: Oxford University Press. Azis, I. J. (2005c). A regional cooperation to support financial crisis management and prevention: An application of a model with uncertainty and feedback influences. International Journal of Organizational Analysis, 13(3), 196–215. Azis, I. J. (2008). From subprime crisis to a possible recession. Current Topics in Management, 13, 15–33. Azis, I. J., & Isard, W. (1996). The use of the analytic hierarchy process in conflict analysis and an extension. Peace Economics, Peace Science and Public Policy, 3(3), 15–27. Azis, I. J., & Puttanapong, N. (2008). A regional trend towards a basket peg system. International Journal of Trade and Global Markets, 1(1), 1–19. Azis, I. J., & Salim, E. (2004). Development performance and future scenarios in the context of sustainable utilization of natural resources. In: P. R. Budy (Ed.), The politics and economics of Indonesia’s natural resources. Singapore: Institute of Southeast Asian Studies. Ballard, C. L., Fullerton, D., Shoven, J., & Whalley, J. (1985). A general equilibrium model for tax policy evaluation. Chicago, IL: The University of Chicago Press. Belsky, E., & Prakken, J. (2004). Housing wealth effects: Housing’s impact on wealth accumulation, wealth distribution and consumer spending. Joint Center for Housing Studies’ Report of a study commissioned and supported by the National Association of Realtors, Harvard University (W04–13). Cambridge, MA: National Center for Real Estate Research. Bernanke, B. S., & Blinder, A. S. (1988). Credit, money and aggregate demand. American Economic Review, 78(2), 435–439. Bernanke, B. S., & Gertler, M. (1989). Agency costs, net worth, and economic fluctuations. American Economic Review, 79, 14–31. Bernanke, B. S., Gertler, M., & Watson, M. (1997). Systematic monetary policy and the effects of oil price shocks. Brookings Papers on Economic Activity (1), 91–157. Blanchard, O., Francesco, G., & Filipasa, F. (2005). International investors, U.S. current account, and the dollar. Brookings papers on economic activity (1), 1–49.

187

188

REFERENCES

Bordo, M. D. (2005). Historical perspective on global imbalances, NBER Working Paper no. 11383, Cambridge, MA . Bourguignon, F. (2002). The growth elasticity of poverty reduction: Explaining heterogeneity across countries and time periods. In: T. Eichler & S. Turnovsky (Eds), Growth and inequality. Cambridge, MA: MIT Press. Bouguignon, F., Branson, W. H., & De Melo, J. (1989). Adjustment and income distribution, May. Working Paper. World Bank, Washington, DC. Brunner, K., & Meltzer, A. H. (1972). Money, debt, and economic activity. Journal of Political Economy, 80, 951–977. Business Week. (2008). The stunning collapse of Iceland. Available at http://www.businessweek. com. Accessed on October 9. Caballero, R. J., Farhi, E., & Gourinchas, P.-O. (2006). An equilibrium model of global imbalances and low interest rates, NBER Working Paper no. 11996, Cambridge, MA. Cunado, J., & de Gracia, F. P. (2004). Oil prices, economic activity and inflation: Evidence for some Asian countries, April. Working Paper no. 06/04. Facultad de Ciencias Econo´micas y Empresariales, Universidad de Navarra, Pamplona, Spain. Defourny, J., & Thorbecke, E. (1984). Structural path analysis and multiplier decomposition within a social accounting matrix framework. Economic Journal, 94, 111–136. De Gregorio, J. (2005). Global imbalances and exchange rate adjustment. Comments to ‘‘From World Banker to World Venture Capitalist: The US External Adjustment and the Exorbitant Privilege’’ by Pierre-Olivier Gourinchas and He´le`ne Rey, June. Paper presented at the NBER Conference on G7 Current Account Imbalances: Sustainability and Adjustment, Newport, RI. Dollar, D., & Kray, A. (2000). Growth is good for the poor, March. Development Research Group, The World Bank. Eichengreen, B. (2006). Global imbalances and the Asian economies: Implications for regional cooperation, August. ADB Working Paper Series on Regional Economic Integration, no. 4, Asian Development Bank, Manila. Feldstein, M. (2006). Taxes on investment income remain too high and lead to multiple distortions. Economists’ Voice, 1–6. Financial Weeks. (2008). Regulators target sovereign wealth funds. Financial Weeks, February 11. Gray, S., & Stella, P. (2008). IMF assesses central banks’ reaction. IMF Survey Magazine, 37(2), 22–23. Greenspan, A. (2003). Remarks at the annual convention of the Independent Community Bankers of America, Orlando, Florida (via satellite). Hamilton, J. D. (1996). This is what happened to the oil price-macroeconomy relationship. Journal of Monetary Economics, 38(2), 215–220. Hamilton, J. D. (2003). What is an oil shock? Journal of Econometrics, 113(2), 363–398. Heal, G. (2008). Climate economics: A meta-review and some suggestions. NBER Working Papers 13927. Cambridge, MA. International Energy Agency (IEA). (2005). Oil market report, various issues. International Energy Agency (IEA). (2008). Oil market report, various issues. IMF – International Monetary Fund. (2005a). World economic outlook. Washington, DC. IMF – International Monetary Fund. (2005b). World economic outlook: Building institutions, September, Washington, DC. Jorgenson, D. W., Ho, M. S., & Stiroh, K. J. (2005). Productivity, information technology and the American growth resurgence. Cambridge, MA: MIT Press.

References

189

Kawai, M., & Takagi, S. (2000). Proposed strategy for a regional exchange rate arrangement in post-crisis East Asia, Working Paper, World Bank, Washington, DC. Krugman, P. (2001). Analytical afterthoughts on the Asian crisis. In: T. Negishi, R. Ramachandran & K. Mino (Eds), Economic theory, dynamics, and markets (pp. 243–256). London, UK: Kluwer Academic Publishers. McKinnon, R. (2005). Exchange rates under the East Asian dollar standard: Living with conflicted virtue. Cambridge, MA: MIT Press. McKinnon, R., & Schnabl, G. (2004). A return to soft dollar pegging in East Asia? Mitigating conflicted virtue. International Finance, 7(2), 169–201. McKinnon, R. M. (2000). After the crisis, the East Asian dollar standard revisited. Mimeograph, Stanford University, CA. Mork, K. A. (1994). Business cycles and the oil market. The Energy Journal, 15, 15–38. Nordhaus, W. (2008). A question of balance: Weighing the options on global warming policies. New Haven: Yale University Press. Nordhaus, W., & Boyer, J. (2000). Warming the world: Economic modeling of global warming. Cambridge, MA: MIT Press. Ogawa, E. (2001). Causes, effects and lessons from the Asian crisis: From a viewpoint of exchange rate system. Mimeograph, Hitotsubashi University, Japan. Okrent, D. (1999). On intergenerational equity and its clash with intergenerational equity and on the need for policies to guide the regulation of disposal of wastes and other activities posing very long-term risks. Risk Analysis, 19(5), 877–901. Rajan, R. G. (2005). Global imbalances: An assessment. Paper presented at the Ronald Reagan International Conference Center, Washington, DC, October 25. Ravallion, M. (1997). Can high inequality development countries escape absolute poverty? Economics Letters, 56, 51–57. Roubini, N., & Menegatti, C. (2007). The US housing recession is still far from bottoming out. RGE Monitor, 1–22. Saaty, T. L. (1996). Fundamentals of decision making and priority theory with the analytic hierarchy process. Pittsburgh, PA: RWS Publication. Saaty, T. L. (2001). Decision making with dependence and feedback: The analytic network process. Pittsburgh, PA: RWS Publication. Schlenker, W., & Roberts, M. (2008). Estimating the impact of climate change on crop yields: The importance of non-linear temperature effects. NBER Working Paper, 13799. Cambridge, MA. Smaghi, L. B. (2008). The Financial Crisis and Global Imbalances – Two Sides of the Same Coin. Speech delivered at the Asia Europe Economic Forum conference The Global Financial Crisis: Policy choices in Asia and Europe, Beijing, December 9. Thorbecke, E., (1992). Adjustment and equity in Indonesia. Development Center Studies, Paris, Organisation for Economic Co-operation and Development. Tobin, J. (1970). A general equilibrium approach to monetary theory. Journal of Money, Credit and Banking, 2(November), 461–472. Weitzman, M. (2007). Structural uncertainty and the value of statistical life in the economics of catastrophic climate change. NBER Working Paper No. W13490, MA.

This page intentionally left blank

INDEX ABM. See Asian Bond Market (ABM) ABS. See Asset-backed securities (ABS) Accommodative policy, of US, 9–10, 20–21, 39, 43 reasons to adopt, 10 ADB. See Asian Development Bank (ADB) ADF. See Asian Development Fund (ADF) AFC. See Asian Financial Crisis (AFC) Aggregate demand (AD) shock curve, 39–40, 41f Aggregate supply (AS) shock curve, 39–40, 41f Analytic Network Process (ANP), 63, 91–94 ANP. See Analytic Network Process (ANP) ASEAN. See Association of Southeast Asian Nations (ASEAN) Asian Bond Market (ABM), 66 Asian Development Bank (ADB), 156 Asian Development Fund (ADF), 66 Asian Financial Crisis (AFC), 8, 55 Asian Monetary Fund (AMF), 55 Asset-backed securities (ABS), 28 Assets emerging market, 10 Japan, 14 US, 7, 16, 18–20, 21f

Bear Stearns Co Inc, 33 Benefit cluster, RFA, 63, 64–66, 65f, 72f with basket system, 71, 72 contagion, 66, 95t macro & ER coordination, 66, 95t mismatch, 66, 95t risk sharing, 64–65, 95t without ER, 71–72 Bernanke, Ben, 36 Bilateral swap arrangements (BSA), 56 BNP Paribas, 31 Bos, Wouter, 49 Britain. See United Kingdom (UK) Brown, Gordon, 45, 49 BSA. See Bilateral swap arrangements (BSA) Bundesbank, 31 Bush, George, 25 CAD. See Current account deficit (CAD), US Capitalism, and financial crisis, 50–51 Capital market, RFA opportunity cluster, 66, 68 Carbon credit scheme, 166 Carbon emissions, 161 mitigation, 157 CDS. See Credit default swap (CDS) CFGE model simulation. See Computable financial general equilibrium (CFGE) model simulation

Bank of America, 33 Barclays, 32 Baugur Group, 44 Bayh, Evan, 26–27 191

192 CFIUS. See Committee on Foreign Investment in the United States (CFIUS) Chiang Mai Initiative (CMI), 56 China bilateral imbalances with US and Europe, 12–13 currency manipulation, 12 oil price increase, 135f–139f household incomes, 113, 115t, 123, 133t oil demand in, 100 oil-intensive sectors, 113 poverty, 123, 124 SOC expenditures, 124 subsidies, 122–124 Cholesky factorization, 134 Citigroup, 32 Climate change CFGE model simulation. See Computable financial general equilibrium (CFGE) model simulation discount rate, 157–159 impact analysis, 160–162 overview, 155–157 Collateralized debt obligations (CDO), 28, 29 Commercial paper, 28 Committee on Foreign Investment in the United States (CFIUS), 26 Compliance, RFA risk cluster, 69–71 asymmetry, 70 central institution, 70 political will, 70–71 Computable financial general equilibrium (CFGE) model simulation, 161–166 in baseline scenario, 162, 163t in BAU scenario, 162–163, 163t in SC1 scenario, 163–164, 163t in SC2 scenario, 163t, 164–166, 165f

INDEX Conduits, 30 Conflicted virtue, 14 Contagion, RFA benefit cluster, 66 without exchange rate (ER), 72 Contingent Credit Line (CCL), 55 Coordination, RFA cost cluster, 68 Cost cluster, RFA, 68–69, 68f with basket system, 73, 74f coordination, 68, 96t moral hazard, 68–69, 96t Countrywide, 33 Credit default swap (CDS), 29, 33, 34 Currency appreciation, and CAD in Asian economies, 11–12, 14 in net-creditor countries, 14 Currency basket. See also Regional Financial Arrangement (RFA) Hong-Kong dollar, 86f Indonesian rupiah, 86f Malaysian ringgit, 87f Philippines peso, 87f Singapore dollar, 88f South Korea won, 88f Taipei (China) dollar, 89f Thai baht, 90f Current account deficit, US, 37 Current account deficit (CAD), US accommodative policy, 9–10, 20–21, 20f China and bilateral imbalances, 12–13 foreign reserves, 11, 14 manipulation of currency, 12, 14 currency appreciation and in Asian economies, 11–12, 14 in net-creditor countries, 14 debt and, 15–16 and dollar value, 16 and domestic and multinational companies, 13 equilibrium of, 18–19

193

Index and interest rates, 16, 22 and internal conflicts by contradictory interpretations of law, 14–15 investment-saving imbalance, 8, 8f–9f oil-exporting countries, 6, 7, 7f policy measures and, 17–22 and trade conflict, 13 valuation effect, 7 Debt, and CAD, 15–16 Discounting, defined, 158. See also Discount rate Discount rate, 157–159 intergenerational conflict, 159 investment, 159 resources exhaustion, 159 use, 158–159 zero (positive), 158 Dollar, 5–6 depreciation, 18 in Latin America, 5 Dubai Ports World, 26–27 Emerging markets, 6 and financial crisis, 48 reforms and liberalization, 10 US accommodative policy, 10 ER. See Exchange rate (ER) Exchange rate (ER) in baseline scenario, 162, 163t in BAU scenario, 163, 163t fluctuations, 57–63 currency basket system, 61–63 in different countries, 80t–85t GDP growth, 58 inflationary impact, 58 VAR technique, 57–58 in SC1 scenario, 163t in SC2 scenario, 163t, 166

Fannie Mae, 31 Financial crisis and capitalism, 50–51 and diplomatic conflicts, 44–45 and disadvantaged group, 47–48 and European disputes, 49–50 and free market, 50–51 and income inequality, 48 overview, 25–27 and poverty, 48 and social unrest, 48–49 subprime lending. See Subprime mortgage crisis and SWF. See Sovereign Wealth Fund (SWF) and trade conflict, 45 Foreclosures, 32, 34, 35. See also Financial crisis France, and UK, 49–50 Freddie Mac, 31 Free market, and financial crisis, 50–51 GDP. See Gross domestic product (GDP) Geithner, Timothy, 12 Germany, interest rates hike, 49 Gini index, 165f, 167 Government investment, mitigation policy, 159 Gross domestic product (GDP), 58, 103f in baseline scenario, 162, 163t in BAU scenario, 163, 163t current account balances, 6f oil price increase and, 103f in India, 125 in Indonesia, 127 in Thailand, 126 in SC1 scenario, 163t, 164 in SC2 scenario, 163t, 166 US, 6, 16, 29, 35, 37

194 Haarde, Geir H., 45 Hierarchy-based model, 91–94 Holarchy, 92–93 supermatrix of, 92f Hongkong, ER fluctuation, 80t Household incomes, oil price increase and, 101, 102 in China, 113, 115t, 123, 133t in India, 106, 110–113, 111t–112t, 124, 133t in Indonesia, 118–119, 118f, 120t–121t, 127, 133t in Korea, 125–126 in Thailand, 114, 116t, 117f, 118, 127, 133t Housing market. See Subprime mortgage crisis Hurricane Katrina, and oil price surge, 100 Iceland and United Kingdom, 44–45 Icesave, 44, 45 IKB Deutsche Industriebank, 31 Income inequality, and financial crisis, 48 India, oil price increase, 139f–143f household incomes, 106, 110–113, 111t–112t, 124, 133t oil-intensive sectors, 106, 110–113 poverty, 124 SOC expenditures, 125 subsidies, 124–125 Indonesia CFGE model simulation. See Computable financial general equilibrium (CFGE) model simulation ER fluctuation, 81t oil price increase, 149f–153f household incomes, 118–119, 118f, 120t–121t, 127, 133t oil-intensive sectors, 118–121 poverty, 128

INDEX SOC expenditures, 128 subsidies, 127–128 Inequality, and financial crisis, 48 Inflation, 10, 16, 46, 102–103 in baseline scenario, 162, 163t in BAU scenario, 163, 163t CAD, 37 ER fluctuation, 58 factors in declining, 27 oil prices changes and, 102–103, 104, 105, 134–135 in China, 123 in India, 124 in Indonesia, 128 in Korea, 125, 126 in Thailand, 127 in SC1 scenario, 163t, 164 in SC2 scenario, 163t upward pressure on, 39–40, 42f Information technology (IT) bubble, 9 Interest rates, CAD, 16, 22 International Monetary Fund (IMF) policy failure, 55 Investment banks, subprime mortgage crisis and, 28–29 margin calls, 31 Investment-saving imbalance, 8, 8f–9f Investment-saving imbalance, 8 Japan, bilateral imbalances, 12 JP Morgan Chase & Co, 33 Korea, oil price increase, 143f–146f household incomes, 125–126 poverty, 125, 126 SOC expenditures, 125, 126 Kyoto Protocol, 157 Lamy, Pascal, on economic crisis, 45 Landbanki, 44, 45 Lehman Brothers, bankruptcy, 35–36 Liquidity, 33 London inter-bank rate (LIBOR), 33

Index Long Term Capital Management (LTCM), 28 LTCM. See Long Term Capital Management (LTCM) Macroeconomic & ER coordination, RFA benefit cluster, 66 without exchange rate (ER), 71–72 Madoff, Bernard L., 28 arrest, 36 Malaysia, ER fluctuation, 81t–82t MBS. See Mortgage-backed securities (MBS) Mismatch, RFA benefit cluster, 66 with basket system, 66 Mitsubishi UFJ, 32 Moral hazard, RFA cost cluster, 68–69 complacency, 69 conditionality, 69 political pressure, 69 Mortgage-backed securities (MBS), 28 investors and, 29 selling, 29 Mortgage lending. See Subprime mortgage crisis National Oil Corp., 47 Net international reserves, 11f Non-renewable resources, use of, 161 Oil-exporting countries, and US CAD, 6, 7, 7f Oil-intensive sectors, 108–121 in China, 113 in India, 106, 110–113 in Indonesia, 118–121 in Thailand, 113, 114, 118 Oil price increase household incomes and, 101 income transfers and, 102 inflation and, 103, 104 monetary policy and, 102–103

195 oil-intensive sectors. See Oil-intensive sectors overview, 99–100 policy response to, 122–128 recession and, 103, 104 Opportunity cluster, RFA, 66–68, 67f with basket system, 73, 73f capital market, 66, 68, 96t supervision, 68, 96t Output growth, downward pressures, 40, 42f Philippines, ER fluctuation, 82t Plaza Accord, 12 Policy trade-offs, and financial crisis, 37–51 aggregate demand (AD) shock, 39–40, 41f aggregate supply (AS) shock, 39–40, 41f dollar value, 38–39, 38f inflation shock, 41, 42f institutional losses, 40 interest rates, 38–39 output growth shock, 41, 42f and policy conflicts, 44–51 taxes, 43–44 Ponzi scheme, 35, 36 Poor. See Poverty Poverty and climate change, 155 in developing countries, 156, 161 simulation model analysis, 163, 164, 164f, 166 and financial crisis, 48 oil price increase and, 101, 102f in China, 123, 124 growth elasticity concept, 122 in India, 124 in Indonesia, 128 in Korea, 125, 126 in Thailand, 127

196 Real business cycle (RBC) model, oil price increase in, 101–102 Recession, 36 Regional Financial Arrangement (RFA), 55–97 benefit cluster, 63, 64–66, 65f contagion, 66, 95t macro & ER coordination, 66, 95t mismatch, 66, 95t risk sharing, 64–65, 95t cost cluster, 68–69, 68f with basket system, 73, 74f coordination, 68, 96t moral hazard, 68–69, 96t currency basket. See Currency basket exchange rate (ER) fluctuations, 57–63, 59f–60f opportunity cluster, 66–68, 67f with basket system, 73, 73f capital market, 66, 68, 96t supervision, 68, 96t overview, 56–57 risk cluster, 69–71, 70f with basket system, 74, 74f compliance, 69–71, 96t synchronized, 71, 97t Renewable resources, use of, 161 Reserve pool cluster, RFA, 64, 65 RFA. See Regional Financial Arrangement (RFA) Risk cluster, RFA, 69–71, 70f with basket system, 74, 74f compliance, 69–71, 96t synchronized, 71, 97t Risk sharing, of RFA benefit cluster, 64–65 with basket system, 71 SAM. See Social accounting matrix (SAM) Sarkozy, Nicolas, 50 on SWF, 26 on VAT cut, 49

INDEX Singapore, ER fluctuation, 83t Social accounting matrix (SAM), 106, 131 Social discount rate. See Discount rate Social overhead capital (SOC), government expenditures on in China, 124 in India, 125 in Indonesia, 128 in Korea, 125, 126 in Thailand, 127 Social unrest, and financial crisis, 48–49 Socie´te´ Ge´ne´rale, 32 Solvency, 33 South Africa Chinese imports in, 5 job loss in, 5 South Korea, ER fluctuation, 83t–84t Sovereign Wealth Fund (SWF), 26, 45–47 values of M&A by, 45–46, 46f SPA. See Structural path analysis (SPA), of transmission mechanism Steinbruck, Peer, 49 Stern Review on the Economics of Climate Change, 157, 158 Structural path analysis (SPA), of transmission mechanism, 131–132, 132f Subprime mortgage crisis ABS, 28 background, 27–30 CDO, 34 CDS, 34 commercial papers issuers, 28 high-risk portfolios, 32 investment banks and, 28–29 Lehman Brothers bankruptcy, 35–36 liquidity problem, 33 margin calls, 31

197

Index risky investments, 31–32 solvency problem, 33 Subsidies, oil price increase and, 101, 104–105 in China, 122–124 in India, 124–125 in Indonesia, 127–128 in Thailand, 126–127 Supervision, RFA opportunity cluster, 68 Supplementary Reserve Facility (SRF), 55 SWF. See Sovereign Wealth Fund (SWF) Synchronized risk cluster, RFA, 71 Taipei (China), ER fluctuation, 84t–85t Taxes, and financial crisis, 43–44 Tax Reform Act, 30 Thailand ER fluctuation, 85t oil price increase, 146f–149f household incomes, 114, 116t, 117f, 118, 127, 133t oil-intensive sectors, 113, 114, 118 poverty, 127 SOC expenditures, 127 subsidies, 126–127 Trade conflict, 45 and CAD, 13

Transmission mechanism. See also Oil-intensive sectors SAM multiplier, 106, 131 SPA analysis, 131–132, 132f UBS, 32 United Kingdom (UK) and France, 49–50 and Germany, 49 and Iceland, 44–45 and VAT policy, 49–50 United States (US) accommodative policy, 9–10, 20–21, 39, 43 assets, 7, 16, 18–20, 21f current account deficit (CAD). See Current account deficit (CAD), US GDP, 6, 16, 29, 35, 37 subprime crisis. See Subprime mortgage crisis Value added tax (VAT), cut in Britain, 49–50 VAR model, 122, 133–135. See also Oil price increase, policy response to Zero (positive) social discount rate, 158. See also Discount rate