The Future of Economic Development in the Gulf Cooperation Council States: Evidence-Based Policy Analysis 2022003478, 2022003479, 9781032264332, 9781032264356, 9781003288282, 7280916535

Table of contents :
Cover
Half Title
Series
Title
Copyright
Contents
List of Figures
List of Tables
Preface
1 Introduction
2 Some Stylized Facts
Oil Revenues Dominate
Large Shares of Services
Inefficiency
Declining Marginal Productivity of Labor and Capital
Real Depreciation of the Currency
High Oil Rent
Small Shares of Agriculture
Oil Prices, Domestic Prices, and GDP Highly Correlated
Revenues and Oil Prices Highly Correlated
High Oil Breakeven Prices
Government Expenditures and Oil Prices Highly Correlated
Savings and Oil Prices Highly Correlated
Private Investments, Private Capital Stock, and Oil Prices Correlated
Net Exports and Oil Prices Highly Correlated
External Debt and Oil Prices Negatively Correlated
Young Population
High Literacy Rates, Low-Quality Human Capital, and High Female Achievements
Very Large Foreign Labor Force
High Youth Unemployment Rates
Symmetrical Exogenous Shocks
Monetary Policy Not Independent
Absolute Monarchies
3 The Oil Dependency Dilemma
Estimating the Share of Oil in Real Output
Oil Production – Global Oil Consumption Relationship in the Long Run
The Short-Run Dynamic Relationship and Stress Tests
Technical Appendix 3.1: The VAR
Technical Appendix 3.2: The Solver
Appendix 3.3: The Estimated SVARs
4 The External Debt
The Debt Stylized Facts
Economic Theories
Computing the Fiscal Adjustment Needed to Achieve a Sustainable Debt Target
Appendix 4.1: U.S. Debt Uncorrelated With Real Macroeconomic Variables
Technical Appendix 4.2: Sustainable Debt
5 Is the Level of Government Spending Optimal?
The Growth Model
The Empirical Results of Estimating the Growth Equation
The Current Account Equation
Appendix 5.1: Government Spending Does Not Crowd Out Private Investments
6 Can Taxes Resolve the Economic Problems?
The Model
Empirical Evidence
Appendix 6.1: The Estimated SVAR Without Income Tax
7 Savings, Productivity, and Other Structural Issues
A Case for Personal “Household” Saving
Productivity
Other Research Issues Pertinent to Saving and Productivity
8 Final Remarks
References
Index

Citation preview

The Future of Economic Development in the Gulf Cooperation Council States

The Gulf Cooperation Council (GCC) countries own 30 percent of the world’s proven oil reserves and largely depend on oil for their income. Yet the GCC faces serious challenges. The global demand for oil is expected to continue declining, and the average long-run oil price could become lower than its historical average in the future. This book is a research-based, structural macroeconomic analysis, providing evidence-based and future-facing policy recommendations for GCC governments. First, it analyzes historical data to explain the macroeconomic performance and economic policies of the GCC countries from 1970 to 2019. Then it presents ten-year dynamic stochastic projections from 2020 to 2030. The book examines debt sustainability and optimal fiscal policies – i.e., government spending and taxation. It also analyses structural issues, such as savings and productivity, from an institutional perspective, taking into account education, the labor market, and pension funds, as well as other factors that have a close effect on economic performance. The book is comprehensive and thorough, it relies on extensive econometric analyses, including rigorous time series analysis. The author uses both calibration of theoretical models and estimation, facilitating projections for the next decade of key economic variables under different policy scenarios. The book also assesses what the future of the GCC economies will look like if climate change and the COVID-19 pandemic continue to adversely affect oil supply and demand and the price of oil, given their current policies and institutions. As well as scholars and researchers of economics and finance, the book will engage policymakers in central banks, treasury departments, planning councils, research institutes, and think tanks. Weshah Razzak is Honorary Research Fellow at the School of Economics and Finance, Massey University, Palmerston North, New Zealand.

Routledge Studies in the Modern World Economy

Industrial Development How States Build Capabilities and Deliver Economic Prosperity Greg Clydesdale Ageing and Effecting Long-Term Care in China Sabrina Ching Yuen Luk, Hui Zhang and Peter P. Yuen Asian Trade and Investment in Europe Edited by Prana Krishna Biswas and Robert Dygas Critical Perspectives on Economics of Education Edited by Silvia Mendolia, Martin O’Brien, Alfredo Paloyo and Oleg Yerokhin State-Owned Enterprises in the Global Economy Maciej Bałtowski and Grzegorz Kwiatkowski The Socioeconomics of Nationalism in China Historical and Contemporary Perspectives C. Simon Fan The Future of Economic Development in the Gulf Cooperation Council States Evidence-Based Policy Analysis Weshah Razzak Economic and Political Democracy in Complex Times History, Analysis and Policy Andres Solimano Free Trade and the US-China Trade War A Network Perspective Yoon Heo For more information about this series, please visit: www.routledge.com/ Routledge-Studies-in-the-Modern-World-Economy/book-series/SE0432

The Future of Economic Development in the Gulf Cooperation Council States Evidence-Based Policy Analysis Weshah Razzak

First published 2023 by Routledge 4 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 605 Third Avenue, New York, NY 10158 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2023 Weshah Razzak The right of Weshah Razzak to be identified as author of this work has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data Names: Razzak, Weshah, author. Title: The future of economic development in the gulf cooperation council states : evidence-based policy analysis / Weshah Razzak. Description: Milton Park, Abingdon, Oxon ; New York, NY : Routledge, 2023. | Series: Routledge studies in the modern world economy | Includes bibliographical references and index. Identifiers: LCCN 2022003478 (print) | LCCN 2022003479 (ebook) | ISBN 9781032264332 (hardback) | ISBN 9781032264356 (paperback) | ISBN 9781003288282 (ebook) Subjects: LCSH: Petroleum industry and trade—Persian Gulf Region. | Persian Gulf—Forecasting. | Gulf Cooperation Council. Classification: LCC HD9576.P52 R39 2023 (print) | LCC HD9576.P52 (ebook) | DDC 338.2/7280916535—dc23 LC record available at https://lccn.loc.gov/2022003478 LC ebook record available at https://lccn.loc.gov/2022003479 ISBN: 978-1-032-26433-2 (hbk) ISBN: 978-1-032-26435-6 (pbk) ISBN: 978-1-003-28828-2 (ebk) DOI: 10.4324/9781003288282 Typeset in Times New Roman by Apex CoVantage, LLC

Contents

List of Figures List of Tables Preface

vii x xi

1

Introduction

1

2

Some Stylized Facts Oil Revenues Dominate 11 Large Shares of Services 12 Inefficiency 12 Declining Marginal Productivity of Labor and Capital 14 Real Depreciation of the Currency 14 High Oil Rent 15 Small Shares of Agriculture 16 Oil Prices, Domestic Prices, and GDP Highly Correlated 16 Revenues and Oil Prices Highly Correlated 16 High Oil Breakeven Prices 16 Government Expenditures and Oil Prices Highly Correlated 19 Savings and Oil Prices Highly Correlated 19 Private Investments, Private Capital Stock, and Oil Prices Correlated 20 Net Exports and Oil Prices Highly Correlated 23 External Debt and Oil Prices Negatively Correlated 23 Young Population 23 High Literacy Rates, Low-Quality Human Capital, and High Female Achievements 23 Very Large Foreign Labor Force 25 High Youth Unemployment Rates 26 Symmetrical Exogenous Shocks 26 Monetary Policy Not Independent 27 Absolute Monarchies 28

10

vi

Contents

3

The Oil Dependency Dilemma

32

Estimating the Share of Oil in Real Output 34 Oil Production – Global Oil Consumption Relationship in the Long Run 42 The Short-Run Dynamic Relationship and Stress Tests 46 Technical Appendix 3.1: The VAR 59 Technical Appendix 3.2: The Solver 59 Appendix 3.3: The Estimated SVARs 60 4

The External Debt

72

The Debt Stylized Facts 72 Economic Theories 75 Computing the Fiscal Adjustment Needed to Achieve a Sustainable Debt Target 76 Appendix 4.1: U.S. Debt Uncorrelated With Real Macroeconomic Variables 84 Technical Appendix 4.2: Sustainable Debt 84 5

Is the Level of Government Spending Optimal?

90

The Growth Model 92 The Empirical Results of Estimating the Growth Equation 93 The Current Account Equation 98 Appendix 5.1: Government Spending Does Not Crowd Out Private Investments 102 6

Can Taxes Resolve the Economic Problems?

106

The Model 109 Empirical Evidence 113 Appendix 6.1: The Estimated SVAR Without Income Tax 123 7

Savings, Productivity, and Other Structural Issues

130

A Case for Personal “Household” Saving 130 Productivity 144 Other Research Issues Pertinent to Saving and Productivity 147 8

Final Remarks

153

References Index

158 164

Figures

1.1 1.2 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 2.10 2.11 2.12 2.13 2.14 2.15 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 3.10

Lakes of Oil The Real Price of Oil, Trend, and Trend Growth Rate Proved Oil Reserves in Millions of Barrels Negative TFP Growth Declining Marginal Productivities of Capital and Labor Percentage Change of REER GDP, Domestic Price, and Oil Prices Are Positively Correlated Government Revenues and Oil Prices Are Positively Correlated Government Spending and Oil Prices Are Positively Correlated Savings and Oil Prices Are Positively Correlated Private Investments and Oil Prices Are Positively Correlated Private Capital Stock and Oil Prices Are Positively Correlated Net Exports and Oil Prices Are Positively Correlated External Debt and Oil Prices Are Negatively Correlated The U.S. Real Depreciation Rate and the Growth Rate of Oil Prices Are Negatively Correlated Chi-Squared 95 Percent Confidence Ellipse Percentage Change of the Effective Real Exchange Rate and GDP Growth Negatively Correlated UIP Does Not Hold Time Series Data of Real GDP Time Series Data of the Stock of Capital Time Series Data of Total Employment Time Series Data of Oil Production Time Series Data of Working-Age Population Log Oil Production (Million Barrels/Day (MBD)) and Global Oil Consumption (Exajoules) Deviations of Dynamic Stochastic Projections of Log Real GDP under the Severe Adverse Global Consumption Shock from Baseline Projections Average Real Price of Oil Fell in 2014 Real and Nominal GDP Growth On Average, Real GDP Growth Has Declined after 2014 Oil Price Shock

2 4 11 13 14 15 17 18 19 20 21 22 24 25 28 29 30 35 36 37 38 39 43 48 48 49 50

viii Figures 3.11 3.12 3.13 3.14 3.15 3.16 3.17 3.18 3.3.1 3.3.2 3.3.3 3.3.4 3.3.5 4.1 4.2 4.3 4.4 4.5 4.1.1 4.1.2 4.1.3 4.1.4 5.1s 5.1 5.2 5.3 5.1.1 5.1.2 5.1.3 6.1 6.2 6.3

Fiscal and Primary Balance Deficits Average Fiscal Deficits Higher After 2014 Current Account Balance The Current Accounts in Deficits After 2014 Oil Price Shock External Debt – GDP Ratios On Average, GCC Debt – GDP Ratio Increased After 2014 China and India Economic Growths High U.S. Oil Reserves Increasing Impulse Response Functions Impulse Response Functions Impulse Response Functions Impulse Response Functions Impulse Response Functions The External Debt (Debt – GDP) and the Primary Balance (PB – GDP) Negatively Correlated Bahrain – (1990–2019) VAR Mean Dynamic Stochastic Projections of the Primary Balance – GDP Bahrain Oman – (1990–2019) VAR Mean Dynamic Stochastic Projections of the Primary Balance – GDP Oman U.S. Privately Held Real Public Debt and Real Consumption Growth Rates Annual Data 1950–2020 Confidence Ellipse (95% Chi-Squared) Consumption and Debt Uncorrelated U.S. Privately Held Real Public Debt and Real GDP per Hour Annual Data 1950–2020 Confidence Ellipse (95% Chi-Squared) Real GDP per Hour and Debt Insignificant Negative Correlation BARS Curve The Growth Model With Real Government Expenditures Actual and Fitted Values The Current Account Model with Real Government Expenditures Actual and Fitted Values Actual and the Average Optimal Government Expenditures Billions of Local Currencies The Levels of Private Investments and Public Expenditures Billions of Local Currency Significant Positive (Spurious) Correlation of the 95 Percent Chi-Square Confidence Ellipse Insignificant Positive Correlation Between Growth Rates of Private Investments and Public Expenditures Hypothetical Computed Average Income Tax and Consumption Tax Computed Oman Average Weekly Hours Worked Per Person Growth Rates of Hours Worked and Oil Price

51 52 53 54 55 56 57 58 61 63 65 67 69 74 79 80 81 82 85 86 86 87 91 95 100 101 102 103 104 111 112 112

Figures 6.4 6.5 6.6 6.7 6.8 6.9 6.10 6.11 6.12 6.13 6.14 6.15 7.1 7.2 7.3 7.4 7.5 7.6

Impulse Response Functions of Inflation, the Output Gap, and Labor Supply SVAR1 Baseline Model Without Tax Impulse Response Functions of Inflation, the Output Gap and Labor Supply SVAR 2 Model With an Income Tax Oman – Mean Dynamic Stochastic Projections of Inflation Oman – Mean Dynamic Stochastic Projections of Cyclical Average Weekly Hours Worked Oman – Mean Dynamic Stochastic Projections of the Output Gap Impulse Response Functions of Consumption, Inflation, and Labor Supply to VAT Shock Mean Dynamic Stochastic Projections of Inflation Mean Dynamic Stochastic Projections of Consumption Mean Dynamic Stochastic Projections of Hours Worked The Deviations of Mean Dynamic Stochastic Projections of Inflation From the Baseline Model The Deviations of Mean Dynamic Stochastic Projections of Consumption From the Baseline Model The Deviations of Mean Dynamic Stochastic Projections of Hours Worked From the Baseline Model Saving – GDP Ratios 1995–2019 Net Exports – GDP Ratio Saving Is Not Equal to Investment Saving – Investments Are Equal to the Current Account GCC Countries Are Creditworthy Net Export and Net Foreign Assets Discrepancy

ix 115 116 117 117 118 119 120 120 121 121 122 123 132 133 134 135 136 137

Tables

2.1 2.2 2.3 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 4.1 4.2 5.1 5.2 7.1 7.2

GCC Oil Revenues (2018) GDP by Economic Activity (% at Current Market Prices) – 2019 Percent of Rent – GDP Growth Rates of Real GDP per Employed Person GMM Estimates of the Share of Oil in Output OLS Results of Responsiveness of Oil to Global Oil Consumption, 1970–2019 ADF Test for Unit Root in the Residuals vt – OLS Results OLS t Estimates of the Error Correction Equation ˜lnH = ˙ + ˆ˜lnCtO + ˇ vt −1 + ut Average and Standard Deviation of Real GDP Growth Rates Average Government Balances – GDP Ratios Average the Current Account – GDP Ratio Average and Standard Deviation Debt – GDP Ratio Average Gross Debt – GDP The Fiscal Adjustments Needed for Debt – GDP Target GMM Estimates of the Optimal Government Expenditures Level GMM Estimates of the Optimal Government Expenditures Level Mandatory Savings Scenarios Average Growth Rates of Labor Market Indicators

12 13 16 33 41 44 45 45 50 52 54 56 73 83 94 99 142 146

Preface

I spent nine years of my career as an economic adviser in Kuwait (2007–2012) and Oman (2015–2019) and traveled in the GCC region extensively. I published a number of journal articles and chapters in books about the Middle East and North African Countries (MENA) and the GCC regions; some of that work was done in collaboration with talented economists at the Arab Planning Institute in Kuwait (API). Working at the API was both delightful and fruitful. Most of the thoughts in this book were developed while I was at the Central Bank of Oman (CBO) and the Ministry of Finance. The inspiration to write this book arose from working with Dr. Ahmed Al Kawaz, Dr. Belkacem Laabas, Dr. Riadh Bin Jlili, Dr. Mostafa El Bentour, and Dr. Ali Abelgader at the API. Furthermore, I learned a great deal about the Kuwaiti economy and society from Dr. Mohammed Al Enizi and Dr. Mahmood Boshahri (Kuwait Institute for Scientific Research), Natiq Al Sekouti (chief economist of the Chamber of Commerce), and Tariq Abdul Gahfor (founder and organizer of the value-added Diwaniya), who invited me to meet many Kuwaiti intellectuals. I must pay special acknowledgment to my colleague Dr. Imad Moosa (Royal Melbourne Institute of Technology and the University of Kuwait), whose comments on all my research were very valuable. This book has more to say about Oman, where I sketched memos and technical notes. In the CBO, I learned from Dr. Qais Al Yahai (first deputy governor), Dr. Hatem Al Shanfari (Sultan Qaboos University and the CBO board), Dr. Khalfan Al Barwani (deputy governor), Dr. Mohamed Al Jahwari, and many other talented junior economists, some of whom are working on their doctorate degrees in the United States and the United Kingdom. The most valuable contribution to my understanding of the fiscal side of the Omani economy is from my colleague Dr. Mustapha Rouis (senior economic adviser to the minister of finance and the head of the Fiscal Policy Unit), whom I have known since my days at the World Bank in the early 1990s. Finally, and my critical views notwithstanding, I must say that I also learned from the International Monetary Fund and the World Bank staff missions to Oman, which present the external views that carry significant influence on the GCC countries. The aim of this book is to sum up my thoughts about the GCC and to spell out some policy ideas, which I did not have the chance to write up or discuss

xii Preface publicaly while I was in the Middle East. Many people may find some ideas disagreeable, and I am certain that there are many clever people who will build on this work and move knowledge forward. I wrote this book having in mind mainly the aforementioned economists, but I have been thinking about the new generation of researchers, graduate students, academics, and policymakers in the GCC countries and researchers working on the GCC or other oil-producing economies, such as Iraq and Libya; I hope that they find it useful. Although the main questions of the book were tackled econometrically, I have discussed a number of policy ideas, which need more research and more thoughts; I envisage that researchers in the GCC take them further and provide some empirical support for them. I also identified questions for more research, hoping that graduate students and research economists are inspired to work on these. In a nutshell, the story of the GCC countries is an oil story, beginning with plenty of oil, and should end with less of it at some unknown date in the future because oil is a non-renewable resource. The GCC countries float on lakes of oil; they have 30 percent of the world’s proven oil reserves and depend on oil for their income. This book is an empirical economic study of these countries. To measure oil dependency, first, the shares of oil – gross domestic product (GDP) and oil revenues – total revenues are relatively high. I estimated high elasticity of real GDP with respect to oil (and gas in the case of Qatar) production. Second, oil productions and global oil consumption share a long-run common trend and have a significant economic dynamic relationship. We provide measurements of these shares, elasticities, long-run relationships, and impulse responses. The adverse oil price shock in 2014 resulted in budget and current account deficits because of the GCC governments’ inability to diversify income away from oil to generate more revenues and to reduce spending. Thus, they borrowed externally to bridge the gap. The question is what the future of the GCC economies should look like if climate change and the COVID-19 pandemic continue to adversely affect oil supply and demand, and the price of oil, given their current policies and institutions. This book provides measures of external debt sustainability and required fiscal adjustments, measures the optimal level of government spending that is consistent with maximum growth and balanced current account. It examines counterfactual scenarios of the effects of taxation on the economy. I focus on potential growth and examine the roles of saving, productivity, education, and human capital; the laws; and other potential determinants. The GCC governments, and in particular the central banks and the Ministries of Finance, should lift up their game a little by investing in economic research so the researchers can provide solid evidence-based policy recommendations to policymakers. I am hopeful that the GCC countries endure the future without oil. Weshah Razzak Wellington, New Zealand 2021

1

Introduction

The GCC countries are Bahrain, Kuwait, Oman, Qatar, Kingdom of Saudi Arabia (KSA), and the United Arab Emirates (UAE). The Council was established in 1981 in response to the Iran–Iraq war, which started in September 1980 and lasted eight years. These GCC countries established this Council as a defense pact to provide economic and political stability; although they do not seem to be aspiring to become one, they are theoretically almost consistent with an Optimum Currency Area (OCA; e.g., Mundell, 1961). The OCA is a geographical area where a number of countries could adopt a single currency to maximize efficiency, provided that they share common features, most importantly are (1) a high degree of policy coordination, (2) being affected by symmetrical shocks, and (3) labor mobility across borders. The second and the third conditions seem to be available, the first is weakly available. A sudden oil price shock – terms of trade shock – affects every GCC country similarly, at least qualitatively, although it cannot be guaranteed that every member’s policy reaction to the same shock is the same. All of the GCC countries are hydrocarbon-based economies; they are single-commodity exporters; their populations, though small, are highly mobile across the GCC. Nonetheless, they have not agreed on a single currency and maintain individual hard peg exchange rates to the U.S. dollar (USD). However, a credibly maintained hard-fixed exchange rate to the USD by each member of the Council to the USD is akin to OCA. Among the six countries, Saudi Arabia is the largest in area and in population. It is about 20 percent the size of the United States. Its population is about 35 million. Noticeably, it has the second-largest oil reserves in the world, the wealthiest among GCC, and a member of the organization of the 20 wealthiest nations in the world. It was created in 1932 after a fascinating history of tribal wars that established the Bin Saud dynasty as the sole rulers. The first commercial oil well began production in early 1938. The Sultanate of Oman has an area of about 310,000 sq km. It is strategically located on the Strait of Hormuz, the waterway through which oil and gas tankers sail to the rest of the world. It is part of the oldest civilizations in the world. The Al Said dynasty governed Oman from 1749. In 1798, Oman and Great Britain signed a Treaty of Friendship. Oman became a British protectorate. Under this treaty, Britain guaranteed the Al Said rule. This country has a very interesting history. DOI: 10.4324/9781003288282-1

2

Introduction

Figure 1.1 Lakes of Oil Source: Online – Geological Society, London

The Portuguese occupied Muscat, the current capital city, between 1507 and 1650 because of its strategic location. In the 18th century, the empire extended from present-day Oman to the east coast of Africa, reached Pakistan, and included most of the present-day UAE. Oil was found in 1964, and exporting oil began in 1967. It is not a major oil producer like Saudi Arabia, the UAE, and Kuwait. Total production is slightly less than a million barrels a day. However, it is highly dependent on oil. Oil revenues make up to 85 percent of government revenues. Oman

Introduction 3 is a mercantile maritime trading country whose population today is nearly 4.5 million; half of them are imported unskilled labor. Kuwait is a very small country in area, 17,818 sq km. It has a small population of four million. Two million are foreign workers. On June 19, 1961, Kuwait became independent from Britain when Britain decided to terminate the Anglo-Kuwaiti Treaty of 1899. Oil was found in 1938 at the same time it was found in Saudi Arabia. The other three small GCC countries are Bahrain, the UAE, and Qatar. Just like Kuwait, they were British protectorates; however, they became independent from Britain ten years later in 1971 after Britain announced a policy of ending the treaty relationships with the Persian Gulf sheikdoms in 1968. These three countries have small populations too. Bahrain’s population is about 1.7 million, half are Bahraini; the UAE is slightly less than 10 million, but only 12 percent are considered citizens; and Qatar’s population is 2.8 million, the non-Qataris are about 12 percent only. All of the GCC countries are heavily dependent on foreign labor. The governments and institutions of the GCC countries, except Saudi Arabia and Kuwait, are relatively new and may vary from one country to another. Furthermore, the GCC countries have shared cultural values. They have the same language, religion, and hence the origin of the laws, history, geography, and most importantly blood because the people are descended from a number of known Arabian tribes. Miniaoui (2020) highlights the progress made in the GCC over the period from 1960 and points out the high level of dependency on oil as the primary source of gross domestic product (GDP). They argue that oil made the GCC economies volatile and vulnerable to fluctuations in the global oil price, which is undoubtedly correct. In this book, we provide evidence for such volatility. The authors also argued that the decline in oil price and the threat of depletion of this natural resource has presented subsequent challenges in the economic, environmental, and social spheres in the GCC countries. Consequently, the GCC countries, the authors say, have realized the importance of diversifying their economies away from oil. I agree with this description; however, there is no evidence that the GCC countries did anything significant about it. Repeatedly, whenever the price of oil and oil revenues increase significantly, the GCC governments embark on massive spending programs and forget about their rhetorical diversification plans too quickly. The GCC countries are major oil producers; a single-commodity exporter. They are not industrial nations; they are mercantile societies, where the merchants are very influential politically. It is very conceivable that they gain from oil rent, hence stand against diversification and manufacturing or technological change to advance other industrial objectives. Mokyr (1990, p. 16) argues that there has been a lot of opposition to new technologies throughout history. There are powerful people with entrenched interests in the status quo who would oppose progress. Miniaoui (2020) presents a variety of recommendations for ways in which these states can achieve economic diversification. The book has a rather political flavor. It emphasizes the need for stronger allegiances, particularly so in the wake of the Qatar diplomatic crisis, cooperative relations between the GCC countries in economic, socio-cultural, political, and, to a certain extent, military domains

4

Introduction

have become more pressing. It discusses the alliances between the region and its international partners, specifically Turkey and India. Figure 1.2 plots the log of the real average price of Dubai, Brent, and West Texas Intermediate (WTI) oils in USD (2013 = 100); its trend; and the trend’s growth rate from 1992. The trend is an Hodrick – Prescott (HP) filter. The real price of oil fluctuates around the trend, and its growth rate has been declining since 2004–2005. It is reasonable to argue that the trend itself and its growth rate may decline further in the future because of climate change, future pandemics, and price shocks.1 In a state of the world with zero carbon, one could imagine the price of oil would fluctuate up and down around a permanently lower trend line than it has been historically. Thus, future oil revenues decline too. If oil dependency continues without the urgently needed fiscal adjustments, such as rationalizing public spending and lowering the breakeven price of oil, the twin deficits will persist (both the budget and current account deficits increased significantly after the 2014 oil price shock). Although oil demand forecasts are subject to a number of specific assumptions and high uncertainty, the Organization of the Petroleum Exporting Countries (OPEC) World Oil Outlook – WOO – (2021 p. 23) predicts that energy demand is forecast to flatten in the Organisation for Economic Co-operation and Development (OECD) region in the long term.2 OPEC suggests that global demand may increase during the period 2020–2025, and the main driver of such an increase is the increase in population in Asia, China and India in particular. I agree that the Asian countries are major trading partners with the GCC, and it is quite reasonable to assume that any future increase in the

Figure 1.2 The Real Price of Oil, Trend, and Trend Growth Rate Data Source: BP Statistical Review 2020 The average USD price of Dubai, Brent, and West Texas intermediate (WTI) oils deflated by the U.S. consumer price index (CPI)

Introduction 5 price of oil would be attributed to these two countries; however, forecasts of oil demand and prices are highly uncertain. The WOO report (pp. 99) also states that the annual average growth rate of the demand for oil will be 2.6 mb/d during the first five years of the forecast period. Then, it is expected to slow down significantly during the second five-year period to 0.6 mb/d and to a further 0.3 mb/d during the period of 2030 to 2035. Global oil demand will plateau after 2035. This book is an evidence-based policy analysis of the GCC countries. Policy without continuously updated and revised robust economic theory and empirical evidence often results in errors. Policy errors are highly persistent. The introduction of a certain policy unleashes not well-understood dynamics that could perpetuate deep in the economy over time because people respond to policies, incentives, and non-incentives. It is rather costly to undo policy errors. Hence, the objective of this book is to answer specific questions pertinent to GCC’s fiscal vulnerability. We begin with establishing careful empirical evidence for oil dependency. Oil dependence is the starting point of any discussion about the GCC countries; it makes the GCC countries vulnerable to exogenous shocks, such as oil price shocks, climate change, and pandemics. We argue that the GCC countries are said to be oil dependent if (1) the share of oil in output is relatively large and (2) if oil production depends on global oil demand, both in the long run and over the business cycle. The global addiction to oil provided the GCC countries with an assured stream of income. Thus, they had no or little incentives to produce other goods and services. We estimate the share of oil (and gas in the case of Qatar) in output and the long-run common trend between oil production in the GCC and global oil consumption. Further, we estimate the short-run dynamics between oil production and global oil consumption. Oil dependence may cause more uncertainty about the future of the GCC economies. We will show that almost all macroeconomic variables such as output, prices, government revenues and expenditures, savings, exports, and imports are highly correlated with the price of oil and therefore highly unpredictable – i.e., surrounded by very wide standard errors because the price of oil is highly unpredictable. It is unpredictable because it behaves like asset prices; highly volatile; its Data Generating Process (DGP) is consistent with a unit root process, where the trend is stochastic rather than deterministic, and as the forecasting horizon increases, the forecast error variance does not converge to a fixed value as the time horizon goes to infinity.3 Second, the 2014 negative oil price shock reduced oil revenues significantly. Without a significant reduction in government expenditures, imports, and breakeven oil prices, the GCC countries experienced twin deficits – i.e., a budget deficit and a current account deficit. As a result, the GCC governments decided to borrow in the international capital market – i.e., not from the International Monetary Fund (IMF).4 Although economic theory is unclear about what constitutes a large or unsustainable debt, we test whether the current external debt of the GCC countries is sustainable at any reasonable target level in the future and calculate the

6

Introduction

required fiscal adjustment to maintain that level. It is shown that only Bahrain and Oman have relatively large external debts; hence, significant fiscal adjustments are needed. On average, the fiscal adjustments needed are 5.5 and 10.6 billion USD for Bahrain and Oman, respectively. Third, given the challenges to curtail public spending, we estimate an optimal level of government expenditure. The optimal level is defined as the level that maximizes output growth or balances the current account. The results suggest that actual government expenditures significantly exceed the estimated optimal average levels that maximize real GDP growth or satisfy a balanced current account since 2017 in all GCC countries. Fourth, with regard to the fiscal budget deficits, the IMF’s and the World Bank’s regular missions to the GCC advised the GCC governments to introduce consumption (value-added tax (VAT)) and income taxes to adjust the primary fiscal balance after adverse oil price shocks. Most of the GCC governments heeded the advice and introduced VATs. Oman will introduce an income tax in 2022.5 The important question is how the introduction of VATs and the income tax will affect the economy – i.e., output, labor supply, inflation, consumption, etc, over the period of 2020 to 2030. The analysis is daunted by the lack of historical data of taxes and average weekly hours worked (i.e., the supply of labor). To circumvent the problem, we use a combination of theory-based computational and counterfactual analysis to, empirically, measure the responsiveness of key macroeconomic variables to taxation over the period from 2020 to 2030. An analytical solution of the structural model of leisure-work choice is used to compute hours worked. We also create data for the income tax rate using some economic theories. These data show how taxes affect the GCC plans to stabilize inflation, increase employment, and end the economic slowdown. Further, we study the effects of hypothetical counterfactual policy scenarios under an income tax and a VAT using Vector AutoRegression (VAR) to generate ten-year dynamic stochastic projections under these scenarios. Our empirical results are consistent with the predictions of economic theory. In the VAR with an income tax, an increase in the income tax rate causes the aggregate demand to fall. To clear the good market, therefore, the aggregate supply has to fall too. This reduction in supply comes through a reduction in work efforts, which means fewer hours worked. When comparing the dynamic stochastic projections with the baseline VAR model (without an income tax), significant differences in output, hours worked, and inflation projections are found. The economy with an income tax has sharply declining output and hours worked over the projection horizon from 2017 to 2030. The timing of the introduction of taxes, or increasing existing taxes, does not seem sensible either; the GCC countries have been in an economic slowdown phase since 2014. Policy advice consistent with economic theory would be to lower taxes during bad times and increase them in good times. The IMF’s and the World Bank’s advice to introduce taxations are concerned with the deficits per se. They did not present macroeconomic general equilibrium analysis to support the tax policy proposition.6 To a certain extent, taxes may resolve some public finance problems; however, taxes could have some adverse macro effects on

Introduction 7 employment, output, and inflation. In addition to the macroeconomic effects of taxation, there is evidence, for example, of significant distributional effects. The VAT might affect the low-income people more than the rich, see, for example, Benzarti and Carloni (2017), Benzarti et al. (2017), Kosonen (2015), Carbonnier (2007). The majority of citizens live comfortably in the GCC, especially in Kuwait, Qatar, and the UAE. Fewer citizens in Bahrain, Oman, and Saudi Arabia live relatively less comfortably; nonetheless, distributional effects of taxation seem less important than finance in all GCC countries; however, some officials still care. I had a discussion with the head of the economic committee at the Council of Oman (a bicameral parliament) in 2018, who argued strongly against the introduction of VAT on that basis and raised the matter with the minister of finance at the time. Furthermore, we examine some structural policy and institutional reforms needed and what alternative possible policy options are there to deal with the fiscal challenges. The econometric analyses in this book indicate that the GCC countries experience structural inefficiencies. The most obvious indicator of such inefficiency is that productivity growth has been persistently negative. In growth models, the growth rate of technical progress and savings explain real GDP per capita growth. Technical progress is endogenous; it depends on knowledge, research and development (R&D), and skills in addition to human capital. The GCC countries do not even need to create technology per se; they need to be able to diffuse the globally produced technical progress. Investments in high-quality human capital are important for achieving such objectives. However, unskilled imported labor dominates the labor force in the GCC countries. Furthermore, there is a misallocation of skilled labor manifested in public-sector employment. It is common to find highly educated and trained citizens working in bureaucratic jobs or in the wrong fields. Low-quality human capital is not conducive of productivity growth. Therefore, the GCC must address the productivity issue. We also examine savings. Savings are the source of the stock of capital and the investments needed for growth. However, in the GCC’s low household saving growth rate might be rooted in the system of public spending, which relies on oil rent. The data for household savings are not available. It is highly probable that government savings have historically dominated gross saving; governments save more when the price of oil is high (e.g., sovereign wealth funds (SWF)). In the future, if global demand for oil declines, the price of oil falls, income from oil will decline unless these economies diversify sooner, and savings might decline more. Here is where the issues are tangled and the problem becomes complicated because it is a general, rather than partial, equilibrium problem. A lower oil price than the breakeven price not only results in budget deficits but also foreign-currency reserves decline too. Therefore, defending the exchange rate peg to the USD becomes harder and leads to Balance of Payment problems.7 In addition to fiscal and monetary policy change, a structural change to the social security system might be necessary for the future too. The current payas-you-go pension system, where people pay for the retirement of others, should be replaced sooner than later, with a system of save-as-you-go, whereby every working person is motivated to save for his or her retirement, not someone else’s.

8

Introduction

Such a system could generate the sufficient domestic capital needed for future economic growth, not on oil wealth, and allow the governments to borrow domestically to finance expenditures instead of external borrowing or taxation. The GCC must do more research in this area because it is paramount for survival and progress into the 21st century. Policy without continuously updated and revised robust theoretical and empirical evidence often results in errors. Policy errors are highly persistent. The introduction of a certain policy unleashes not well-understood dynamics that could perpetuate deep in the economy over time because people respond to policies, incentives, and non-incentives. It is rather costly to undo policy errors. Next, we will provide some stylized facts. Chapter 3 provides empirical evidence for oil dependence. Sustainable debt issues are tested in Chapter 4. Chapter 5 provides estimates of the optimal level of government spending. Chapter 6 is a micro-foundation, small, structural, work-leisure model used to compute the equilibrium supply of labor in Oman – i.e., equilibrium average hours worked. Then estimates of a Structural Vector AutoRegression (SVAR) model are used to compare baseline dynamic stochastic projections for key economic variables – i.e., in a system without taxation, with a system under taxations, over the period of 2020 to 2030. Chapter 7 examines savings, productivity, and other structural issues and provides alternative policies. Chapter 8 is a final remark.

Notes 1 Although there are no guarantees that governments will follow through with the climate change commitments to achieve a zero-carbon target by 2050 because of a web of complicated technical issues beyond the words and pledges of treaties. See, for example, a summary of some of the barriers and issues in Nature, “Why Fossil Fuel Subsidies Are so Hard to Kill (20 October 2021). Our assumption is that in a state of the world with zero carbon, global demand for hydrocarbons would be permanently lower than it has been historically. Nonetheless, we have evidence that technological progress will make alternative energy more affordable and more profitable, and there are always the future unknown global pandemics. Hence, the price of oil is expected to be lower than its historical trend. 2 The prediction is that after a short recovery from the impact of COVID-19, the demand for energy in the region will peak in the medium term before declining to around 102 mboe/d by 2045, reaching a level similar to that seen in 2020. 3 The unit root process is one where the moments (the mean, the variance . . .) are functions of time. It could be described as (1 − L)yt = β + ψ(L)et, where L is the lag operator, et is a white noise with a mean of zero and a variance σ 2, and ψ(L) ≠ 0. As the variance of the forecast errors grows linearly with the forecast horizon, the standard deviation of the forecast error grows with the square root of the forecast horizon. The asymptotic distribution for unit root processes can be described in terms of Brownian motion, Hamilton (1994, Chapter 17). Brownain motion W(.) is a continuous-time stochastic process, where each date is associated with a scalar W(t) such that W(0) = 0; for any date 0 ≤ t1 < t2 < . . . < tk ≤ 1, the changes W(t2) − W(t1), . . . W(tk) − W(tk−1) are independent multivariate Gaussian with [W(s) − W(t)] ~ N(0,s−t); and, finally, for any given realization W(t) is continuous in t with probability 1. Razzak (2007) provides a perspective on unit root and cointegration in macroeconomic analysis.

Introduction 9 4 Qatar is a gas producer, so it did not experience a twin deficit, but it also borrowed externally. We suspect that it did so because of the construction needed for the FIFA World Cup, which will be held in Doha in 2022. 5 Interestingly, Kuwaitis do not pay taxes of any kind. Kuwait has two tax laws. One is the Income Tax Rules (Decree no. 3 of 1955), and the second is Law no. 23 of 1961, which regulates company profits. The Kuwait National Assembly passed a law on 26 December 2007, which amends several provisions of the 1955 law. It changed the company tax regulations. It became law upon the publication in the official Gazette on 3 February 2008. The most important change is a substantial reduction in the income tax rate on net profits of foreign entities doing business in Kuwait. The new tax law stipulates a flat rate of 15 percent instead of the old rate of a range between 5 to 55 percent depending on the earnings above a certain threshold. The current 15 percent tax is levied on the income of any entity carrying on a trade or business in Kuwait. The current flat tax rate will result in a significant decrease in the tax liability of such foreign entities. 6 A very recent analysis with the title Economic Prospects and Policy Challenges, by IMF (2021), repeats the same policy propositions without rigorous empirical analysis. 7 I have not seen any serious research in this area in either Kuwait or Oman when I was there for nine years. I also have not heard any discussion about the U.S. peg in public. Most people have money illusion and believe that the current values of their currencies are good. It is not at all clear from a theory standpoint why the GCC governments fix their currencies to the USD. However, there could be some sort of fear of floating phenomena (Calvo and Reinhart, 2002) that the GCC policymakers want to avoid exchange rate swings associated with the float that could make oil revenues unpredictable. Further, a fixed exchange rate system is relatively easier and less costly to manage than a floating system. Floating exchange rate regimes require large human capital investments in a skilled central bank staff. Fixed exchange rate is an easy-to-implement nominal anchor compared with a floating rate. Floating the currency requires another nominal anchor, whether money, inflation, or nominal GDP. Such systems require more central banking skills than the peg.

2

Some Stylized Facts

When coal came into the picture, it took about 50 or 60 years to displace timber. Then, crude oil was found, and it took 60, 70 years, and then natural gas. So it takes 100 years or more for some new breakthrough in energy to become the dominant source. Most people have difficulty coming to grips with the sheer enormity of energy consumption. Rex Tillerson

Abstract Oil price shocks are terms of trade shocks that are highly associated with almost all macroeconomic variables in the GCC. Noticeably, oil prices are highly volatile and unpredictable; therefore, macroeconomic variables are also highly volatile. Climate, pandemics, and oil price shocks are hard to identify, and when combined with uncertain policy reactions, they make the future of the GCC economies more uncertain. Although the literacy rate is high, the GCC has a large unskilled foreign labor force, high youth unemployment, large inefficiencies, real currency depreciations, and high rent. The story of the GCC countries is an oil story, beginning with plenty of oil, that should end with less of it at some unknown date in the future. This is not because oil is a nonrenewable resource, but because we are in a state of the world where we witness a significant change in consumer taste. Today, more people perceive oil as “a bad” not “a good.” The energy of the future is not oil. The GCC governments know that. However, the GCC countries should be concerned about the effects of the expectations of a zero-carbon world on their economies today and over the next decade. The GCC countries produce about 22 percent of the total world crude, and have 30 percent of the world proven oil reserves (BP Statistical Review, 2020). Figure 2.1 plots the proven oil reserves data for 2018 and 2019. The share of oil exports in GDP is not as high as the share of oil revenues in total government revenues; it could be as high as 70 percent, except for the UAE, which has the most diversified income presumably because Dubai is a non-oil producer. Historically, in the GCC, oil revenues have been the main source of governments’ expenditures (consumption and investments). Oil wealth has improved the DOI: 10.4324/9781003288282-2

Some Stylized Facts 11

Figure 2.1 Proved Oil Reserves in Millions of Barrels Data Source: BP Statistical Review (2020)

lives of people tremendously and was used to build modern cities over the past 50 years. Since inception, the GCC governments financed free education; public health; services such as water, electricity, roads, other important infrastructures; and paid pensions, among other free services, to every citizen. In the 1940s and ’50s, the Gulf Arabs went to Baghdad, Beirut, and Cairo to get an education where not many Lebanese, Egyptians, or Iraqis knew what Dubai, Abu Dhabi, and Doha looked like. These cities were flat deserts with no schools. Today, Dubai and Abu Dhabi are international spectacular destinations. The same goes for Doha, which is hosting the FIFA World Cup in 2022. In Oman, families sent all their children to study in Baghdad. Muscat had one road in 1970; today it is a great modern city with so many schools.

Oil Revenues Dominate Table 2.1 reports the oil revenues as a percent of GDP and as a percent of total revenues in 2018. They are relatively high in all GCC countries, except for Bahrain, which is not a major producer of oil, and the UAE most probably because of Dubai and the other four Emirates, which do not produce oil. Abu Dhabi is the main oil producer in the UAE. Put differently, the GCC countries seem to have put “all their eggs” in one basket. This has been the known case for a very long time. Governments have been trying to diversify income away from oil but so far their policies have not really succeeded.

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Table 2.1 GCC Oil Revenues (2018)

Bahrain Kuwait Oman Qatar Saudi Arabia UAE

Oil Revenues a

Nominal GDP b

% of GDP

Total Revenues c

% of Total Revenues

4,775 47,281 21,410 47,563 162,997 44,948

38 142 79 191 787 414

12.7 33.4 27.0 24.9 20.7 10.9

8.22 81.21 29.68 66.76 244.51 120.96

58.1 58.2 72.1 71.2 66.7 37.2

a: Arab Monetary Fund Arabic Consulted Report, 2019, Annex 2/6, pp. 340, million USD b: IMF – World Economic Outlook (WEO) October 2019 (billions of USD) c: IMF – WEO October 2019 (billion national currency converted to USD using fixed exchange rates in terms of USD, one Bahrain Dinar is 2.65, the Kuwaiti Dinar is 3.27, the Omani Rial is 2.60. The Qatari Riyal, the Saudi Riyal, and the Emirati Dirham are 0.270)

Large Shares of Services Table 2.2 reports the shares of sectors in GDP. Note that the highest shares are for mining and querying, which includes oil and gas, and services dominate the economies. It is straightforward to model the GCC economies: oil production and services around it. Bahrain has a relatively large banking sector, and the UAE includes Dubai, which is not an oil-based economy. It is a larger economy relative to the other Emirates and includes Dubai Ports, which is a massive global business. It owns more than 75 ports in more than 40 countries. Measuring output in services sectors, however, is very difficult. Hence, productivity (i.e., output/ input) measurement is imprecise. For all we know, no developing country could jump the development ladder on the backs of mining and querying and services sectors. Oil-rich countries have the lowest economic performances in the world. This is what has been coined the resource curse. All developed countries have gone through an industrialization phase of some sort to get to join the developed nations. China’s industrialization model includes not only manufacturing but also agriculture and services. Korea, Singapore, Taiwan, and Vietnam have industrialized too. The idea is a need to create high value in the production of goods and services. The future, however, may require a different development model; however, comparative advantage and other elements of the economic theory still apply. Absent oil, what comparative advantage do the GCC countries have? There could be many, but the answers are beyond the scope of this book.

Inefficiency Figure 2.2 plots the Conference Board growth rates of total factor productivity (TFP) growth rates. The growth rates are mostly negative. The Conference Board defined it as, TFP growth accounts for the changes in output not caused directly by changes in labor and capital inputs. It represents the effect of technological change, efficiency improvements, innovation, and our inability to measure

Some Stylized Facts 13 the contribution of all other inputs. It is estimated as the residual by subtracting the sum of two-period average labor share weighted input growth rates from the output growth rate. The only way to interpret the data is that the GCC economies are inefficient. Table 2.2 GDP by Economic Activity (% at Current Market Prices) – 2019 Manufacturing Agriculture Mining & Building & Electricity, Services Quarrying Constructions Water & Gas Bahrain 17.9 Kuwait 6.90 Oman 10.5 Qatar 8.60 KSA 12.5 UAE 8.70

0.28 0.43 2.35 0.18 2.23 0.73

15.0 44.8 34.8 34.1 27.8 25.0

8.20 2.80 6.30 13.9 5.50 8.40

1.3 2.4 2.1 1.1 1.6 4.0

56.2 48.6 45.4 42.0 49.6 53.1

Source: The Joint Arab Economic Report, Arab Monetary Fund, Annex Table 2/3 (2020, pp. 42)

Figure 2.2 Negative TFP Growth Data Source: Conference Board

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Some Stylized Facts

Declining Marginal Productivity of Labor and Capital I take the derivatives of a constant return to scale Cobb-Douglas production function with respect to labor and capital – i.e., the marginal productivities. Then I use the labor share and (1-labor share) (Penn World Table), along with real GDP, workingage population, and the stock of capital to calibrate the marginal productivity of labor and capital. Figure 2.3 plots the marginal productivity of labor and capital. The marginal productivities of labor and capital have been falling and are flat in all the GCC countries over the period from 1989. Bahrain, Qatar, and the UAE experienced some positive trends in the marginal productivity of capital in the 1990s and early 2000s, but these trends fell later on. How fast would non-oil GDP grow in the future of a zero-carbon world and a smaller foreign labor force?

Real Depreciation of the Currency Figure 2.4 plots the real effective exchange rate – REER (IMF – International Financial Statistics). The IMF defines it such that an increase in REER implies

Figure 2.3 Declining Marginal Productivities of Capital and Labor Data Source: labor share is from Penn World Table 9.0

Some Stylized Facts 15

Figure 2.4 Percentage Change of REER

that exports become more expensive and imports become cheaper; therefore, an increase indicates a loss in trade competitiveness. The data are available for Bahrain and Saudi Arabia only, but the sample is from 2011 to 2020 for Bahrain. Longer data are available for Saudi Arabia. The volatility is evident in the data. On average, from 2011 to 2014, the REER depreciations were 0.0237 and 0.0241 for Saudi Arabia and Bahrain, respectively. From 2015 to 2020, these averages were 0.0175 and 0.0151, respectively. These are more than a 70 percent decline. Therefore, the exports must have become cheaper and imports become more expensive. The GCC currencies depreciated in real terms after the 2014 oil price shock. On average, the currency has lost real value, and the trade balance deteriorated. Saudi Arabia’s REER jumped up sharply in 2020, and Bahrain’s went negative again. One would expect a similar pattern in the rest of the GCC countries, but unfortunately, the data are unavailable. The U.S. REER is similar to the GCC, more or less, because the difference is mainly in the CPI of these countries.

High Oil Rent Oil dependence, dominant service sectors, and low productivity are the ingredients of the rentier economies. The World Development Indicators data for rent as a percent of GDP show that the GCC countries exhibit relatively high percentages. A rentier economy is one whose income is unrelated to productivity. The data have some gaps. Table 2.3 reports the percentage of rent in GDP in 1975 as a benchmark and then for the 1990s, 2000s, 2010s, and 2011 to 2019. A good sign is that the rent – GDP ratios have declined over time. Relatively, it is significantly lower in the UAE. Nonetheless, they remain relatively high in Kuwait, Oman, and Saudi Arabia.

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Table 2.3 Percent of Rent – GDP

Kuwait Oman Qatar KSA UAE

1975

1981–1990

1991–2000

2001–2010

2011–2019

63.9 59.9 64.2 55.9 41.6

41.4 41.2 38.1 34.3 24.8

35.2 33.4 30.1 30.8 18.6

46.9 37.3 31.2 42.4 20.8

45.4 31.6 21.4 34.2 19.8

Data Source: World Development Indicators

Small Shares of Agriculture Structurally, the GCC countries lack perennial rivers or permanent bodies of freshwater, which explains why they have small agricultural production, although Saudi Arabia has invested heavily in agriculture. Saudi Arabia’s share of agricultural output in GDP was 2.2 percent in 2019, the UAE’s 0.7 percent, Oman’s 2.4 percent, Qatar 0.2 percent, Kuwait 0.4 percent, and Bahrain’s was 0.3 percent. For comparison, the share of agriculture in Sudan is 20.2 percent and in Syria 37.2 percent, according to the Arab Monetary Fund Joint Report (2020, Annex Table 3/10). Food security will be a decisive issue in the non-oil future.

Oil Prices, Domestic Prices, and GDP Highly Correlated Oil prices are very volatile and highly correlated with most of the macroeconomic data. Figure 2.5 plots the growth rates of nominal GDP and the growth rates of the GDP deflator (a measure of domestic price inflation) and the average oil prices (this is the average of Dubai, Brent, and WTI oil prices). Both nominal GDP and domestic prices growth rates are highly correlated with the average price of oil, except for Bahrain, which is not a major oil producer. When the price of oil increases (decreases), output increases (decreases), and domestic prices increase (decrease). The increase (decrease) in the price of oil is a positive (negative) term of trade shock. It shifts up (down) the aggregate demand, where both quantity and price level increase (decrease). This pattern is prevalent in all GCC countries. These shocks are also symmetrical; they affect all of the GCC countries.

Revenues and Oil Prices Highly Correlated Figure 2.6 plots the growth rates of government revenues and the growth rate of the average oil prices. The correlation is even higher than that between GDP and oil prices. It confirms the reliance on oil as the main source of revenues.

High Oil Breakeven Prices Although the IMF forecasts breakeven oil prices to fall in the near future, these forecasts are conditional on the IMF assumptions that the GCC countries’ tax

Some Stylized Facts 17

Figure 2.5 GDP, Domestic Price, and Oil Prices Are Positively Correlated Data Source: IMF – WEO, April (2021)

policies will generate some non-oil revenues. Breakeven oil prices are high in general. These prices balance the fiscal budgets. I argued earlier that the GCC governments did not do anything significant to diversify income away from oil. Given this dependency of revenues on oil, their budgets depend on breakeven prices of oil (the price of oil, which balances the budget). These prices are usually set high in all GCC budgets. When the oil price crashes and the breakeven prices remain unchanged, they get more budget deficits. Evidently, if governments plan to spend more, they will set up the breakeven prices of oil that are required to deliver their budgets. Nevertheless, the breakeven oil prices for

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Some Stylized Facts

Figure 2.6 Government Revenues and Oil Prices Are Positively Correlated Data Source: IMF – WEO, April (2021)

each country often deviate from actual oil prices, especially during crises. The problem is that oil prices are very hard to predict. Oil prices behave like asset prices: they are highly volatile and look like Brownian motions. Statistically, it is impossible to predict the future price of assets traded in organized markets, especially if the markets are efficient.1 For GCC countries, the instability and the unpredictability of the price of oil may persist, and that might be very challenging unless the GCC countries steer away from oil as the main source of revenues.

Some Stylized Facts 19

Government Expenditures and Oil Prices Highly Correlated Figure 2.7 depicts the growth rate of government expenditures and the growth rate of average oil prices. Again, the same patterns observed in other macroeconomic data prevail. There is a strong correlation between these two variables.

Savings and Oil Prices Highly Correlated Figure 2.8 plots the growth rates of savings and the growth rate of average oil prices. There is a very strong correlation between total savings and oil prices. Saving is a function of income. Savings is largely government savings, which

Figure 2.7 Government Spending and Oil Prices Are Positively Correlated Data Source: IMF – WEO, April (2021)

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Some Stylized Facts

Figure 2.8 Savings and Oil Prices Are Positively Correlated Data Source: IMF – WEO, April (2021)

increases with the increase in oil prices. In the non-oil future, savings will decline, and the SWF will shrink. These expected trends, along with declining productivity, will have to reduce real GDP per capita growth.

Private Investments, Private Capital Stock, and Oil Prices Correlated A high correlation with oil prices is also present in private investments and private stock of capital. Figure 2.9 and Figure 2.10 plot the IMF – growth rates of private investments and stock of capital data. Qatar data are missing because they do not

Some Stylized Facts 21

Figure 2.9 Private Investments and Oil Prices Are Positively Correlated Data Source: IMF – Investments and Capital Stock Data Set Qatar data not reported

22

Some Stylized Facts

Figure 2.10 Private Capital Stock and Oil Prices Are Positively Correlated Data Source: IMF – Investments and Capital Stock Data Set Qatar data not reported

Some Stylized Facts 23 report them. These scatter plots are the 95 percent chi-squared tests. In Figure 2.9, the correlations are less significant than those in Figure 2.10 are. Private investments are positively, but not significantly, correlated with oil prices in Oman. This is intriguing because it suggests that private investments in Oman may be able to generate economic growth without oil. The stock of capital, however, is highly significantly correlated with the price of oil.

Net Exports and Oil Prices Highly Correlated Although there are missing data for the growth rates of net exports, net exports growth rates and oil prices are highly correlated. The increase in oil prices increases export and import with occasional spikes in the trade balance. Figure 2.11 plots the data.

External Debt and Oil Prices Negatively Correlated The GCC countries only borrow when the price of oil declines below the breakeven price, and with expenditures unchanged, it causes a budget deficit. We plot the growth rate of external debt and the percentage change of average oil prices. As the price of oil increases (decreases), the debt grows lower (higher). The correlation is negative. Figure 2.12 plots the data.

Young Population Most importantly, they all have young populations; people aged less than 15 years. The Arab Monetary Fund Joint Report Annex Table 2/9 (2020) reports that in 2018, the percentage of population age less than 15 years in the total population was 19.4 percent in Bahrain, 21.7 percent in Kuwait, 22.1 percent in Oman, 14 percent in Qatar (the lowest), 30.1 percent in Saudi Arabia, and 14.6 percent in the UAE.

High Literacy Rates, Low-Quality Human Capital, and High Female Achievements The literacy rate is very high, upper 90th percent, and females are noticeably more eager for educational excellence. Trends in International Mathematics and Science Study (TIMSS) provide standardized tests in math and science to a very large number of countries. They have examined fourth and eighth graders, boys and girls, every four years since 1995. The GCC countries are included in the study. Some GCC countries have been participating since 1995. Although the estimates of the GCC countries are subject to a number of caveats, the TIMSS (2019) report shows that there is a positive gender gap favoring girls in both math and science, and in fourth and eighth graders over time. In more analysis of the TIMSS data, we found that this gender gap is common in a small number of countries in the world, but mostly in Muslim countries. We do not have a rigorous explanation for this intriguing phenomenon.

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Figure 2.11 Net Exports and Oil Prices Are Positively Correlated Data Source: IMF – WEO (April 2021) Net exports data have missing values

The Arab Monetary Fund report (2020), Annex Table 2/10, reports that the enrollment in high education to gross enrollment ratios were 26.7 and 53.2 for males and females, respectively in Bahrain; 35.8 and 76.1 percent in Kuwait; 26.4 and 55.6 percent in Oman; 7 and 54.9 percent in Qatar; and 66.3 and 69.9 percent in Saudi Arabia, respectively. Culturally, however, the GCC countries have maintained male-dominated governments, although it is observed that significant changes have occurred lately in the governance structure in all of them, except Saudi Arabia.

Some Stylized Facts 25

Figure 2.12 External Debt and Oil Prices Are Negatively Correlated Source: IMF – WEO, April (2021)

Very Large Foreign Labor Force Life expectancy at birth is about 73 for men and 77 for women. The labor force is made of largely imported unskilled workers; the labor markets are segmented and have features that are inconsistent with international labor standards. For example, there are no immigration laws. Individual citizens can bring to the country a certain number of foreign workers to work in the GCC by providing Kafalah, which is sort of a guarantee that they are responsible for the foreign worker while they are in the GCC country. Work contracts are not standard. Some of those foreign workers pay the GCC citizens who provide them with employment annual fees in order to stay legally in the country. Foreign workers are not permitted to move

26

Some Stylized Facts

across the GCC borders at will. On the other hand, the vast majority of highly educated citizens are employed in government jobs. These are comfortable, not necessarily productive, jobs in the sense that workers enjoy more benefits, such as fewer hours worked, more leaves, and more security. For example, one could easily find female qualified doctors working as teachers in a kindergarten. Many of the GCC governments, Kuwait in particular, tried to convince the private sector to hire more citizens in vain. Neither the private sector nor the citizens themselves liked the policy. The Kuwaiti constitution guarantees jobs to citizens regardless of their education and skill levels. The governments provide – e.g., Oman – tens of thousands of jobs to citizens every year, most of them in the public sector.

High Youth Unemployment Rates In addition, there is high youth unemployment; graduates are looking for jobs in the bloated public sector. The Arab Monetary Fund Joint Report (2002), Annex Table 2/18 shows that the youth unemployment rates (ages 15–24) in 2019 were 28 percent in the UAE, a whopping 57.1 percent in Bahrain, 29.4 percent in Saudi Arabia, 42.7 percent in Oman and Qatar, and 34 percent in Kuwait. These figures are relatively high indeed. The GCC countries need structural labor market reforms, education reform, and a modern and internationally compatible labor law.

Symmetrical Exogenous Shocks Potentially, the GCC countries might face many adverse external shocks, such as climate change and pandemics, that may reduce the price of oil below the average or reduce the average price level itself, such as a decline in the global consumption of hydrocarbons. There is an expected persistent decline in the global demand for oil mainly because people seem to believe that climate change is highly affected by hydrocarbon production. A government-supported United Nations plan sets a zero-carbon target by 2050: the Paris Accord on Climate Change (2015). This expected downward trend in the production and consumption of fossil fuel, if it persists, is expected to reduce the future average price of oil. In addition, there is an increase in investments in alternative energies (Bloomberg, 2020, 2021). Technical progress has made it possible to produce cheaper alternative energy, such as solar, wind, thermal, nuclear; they seem to be profitable, thus the increase in private and public investments in alternative energy relative to hydrocarbons. This trend would also reduce the future average price of oil. Further to the expected negative oil price shocks and climate change effects on the average long-run price of hydrocarbons, COVID-19 has created another challenge to the GCC. There could be more unpredictable pandemics in the future. At the macroeconomic level, COVID-19 adversely affected certain sectors – for example, the earnings from the vitally important airline industry and tourism, among other sectors. Both the UAE and Qatar are homes for the largest airline fleets in the world. Moreover, the pandemic reduced the demand for oil globally through the negative effect on consumption and spending in general. The shock significantly reduced the consumption of fossil fuels by global transportation networks. It also

Some Stylized Facts 27 disrupted the supply of oil. Furthermore, we do not know for sure how persistent this shock will be, but it is undoubtedly not a temporary shock. COVID-19 directly affected aggregate demand and aggregate supply in the GCC countries. Many projects were either delayed or suspended. COVID-19 disrupted labor markets. It reduced hours worked (the supply of labor). Finally, this shock has threatened fiscal and social stability to the states’ finance investments in health, education, electricity, water, infrastructure, pensions, food, the Internet, etc. No one is certain about future pandemics and their effects, but there is reasonable cause to believe that COVID-19 will not be the last one of such awesome magnitude. IMF and the World Bank data suggest that (1) the GCC governments’ revenues are mainly from oil. (2) The GCC countries are characterized by relatively high-rent GDP ratios. (3) The GCC economies are dominated by mining and querying (oil and gas) and services sectors. The services include restaurants; transport, storage, and communications; finance; insurance and banks; and social services. (4) The dynamics of the GCC macroeconomic data are highly associated with oil price dynamics. (5) The GCC countries are subject to symmetrical “oil price” shocks. (6) There is a strong correlation between the growth rates of macroeconomic variables and oil prices. (7) These correlations also suggest that the volatility of oil prices spilled into the economy too. Furthermore, (8) the correlations imply that the GCC economies share the same degree of volatility because all of them are subject to the volatility of the same oil price shock.

Monetary Policy Not Independent Since the exchange rates are fixed to the USD in all the GCC countries, except Kuwait, which fixes its currency to a basket of currencies, and capital is freely mobile in the GCC countries, we deduce that monetary policies in the GCC countries are not independent, the impossible trinity or the tri-lemma, Mundell (1961) states. Figure 2.13 plots the chi-squared confidence ellipse between the percentage change of the U.S. effective real exchange rate published by the IMF – International Financial Statistics and the growth rate of the average oil prices. The correlation is significantly negative. Oil is priced in USD. Monetary policy and productivity affect the USD directly. When the USD depreciates (appreciates), ceteris paribus, the demand for oil increases (decreases), and the price of oil increases (decreases). It follows that the GDPs of the GCC countries are negatively correlated with the USD real depreciation rate (the percentage rate of change of the effective real exchange rate) because (nominal) GDP growth in the GCC countries is significantly correlated with the average price of oil, as shown earlier. Figure 2.14 plots the data. Kuwait is affected relatively less by the United States because its currency is pegged to a basket of currencies, with the USD having the largest weight. The Uncovered Interest Rate Parity Condition (UIP) given by it* = it + ˛Ste , where it denotes the interest rate, asterisk denotes the United States, and the last term is the expected depreciation rate. This last term is zero if the exchange rate peg systems in the GCC were credible. Examining the data of ∆St – assuming perfect foresight indicates that ∆St is zero. Although the lending rates in the United

28

Some Stylized Facts

Figure 2.13 The U.S. Real Depreciation Rate and the Growth Rate of Oil Prices Are Negatively Correlated Chi-Squared 95 Percent Confidence Ellipse

States and the GCC are correlated, they are not identical. Figure 2.15 plots the GCC and the U.S. lending rates. The lending rates in the GCC are higher than in the United States and higher than Libor. The gap suggests the expected depreciation rate ˜Ste ° 0, or it may reflect measurement errors in interest rates. Note that the GCC central banks maintain the peg by managing reserves and the stock of money not by setting the overnight interest rate. Policymakers do not know about the UIP. The GCC central banks do not have a policy interest rate. Since the commercial banks set the lending rates, the question is how they do that. They do not pay interest on deposits, thus the spread between the lending rate and the deposit rate is very large. Do they add a positive margin to Libor? The deviations would be very large, implying a wide spread of about 4 percent on average bank profits. The determination of the interest rates in the GCC is a good research question, which should interest central banks and research economists. We will briefly discuss monetary policy ineffectiveness in the GCC later in the book.

Absolute Monarchies The political system is also similar in the GCC countries; these countries are absolute monarchies and have no organized, licensed political parties; however, they have limited elections of local bodies and have no free press. Kuwait is the exception, which could be described as a quasi-constitutional monarchy with an elected parliament and reasonably free press. One can describe the GCC

Some Stylized Facts 29

Figure 2.14 Percentage Change of the Effective Real Exchange Rate and GDP Growth Negatively Correlated

30 Some Stylized Facts

Figure 2.15 UIP Does Not Hold

Some Stylized Facts 31 as mercantile economies. The merchants are politically powerful families and individuals who have resisted significant economic changes because they have inherited exclusive rights to import goods and services into the country and sell at a monopoly price. This structure implies a barrier to entry. New companies cannot possibly compete with the existing ones. Thus, competition is highly questionable in the GCC. Finally, and most importantly, the GCC countries are major oil and gas producers, whereby government revenues are highly dependent on oil and gas revenues.

Note 1 This is an implication of the Efficient Market Hypothesis (EMH), Fama (1970), which earned him the Nobel Prize. Also, see Samuelson (2015). The Hypothesis has been tested thoroughly in its weak and strong forms. Some economists believe it to be true; many do not, mostly the behavioral economists have concerns about the validity of rational expectations. That, however, is not the issue here. It is not our objective to defend or criticize the EMH, and we will not cite this voluminous literature here; however, we will argue that most asset prices probably have stochastic trends (unit root). The trend is governed by a stochastic process such as a Random Walk (Brownian motion), which implies that the forecast error variance of the asset approaches infinity as the forecast horizon increases with time. Randomness then reflects the essence of the EMH.

3

The Oil Dependency Dilemma

The inclusion of natural resources in the [work-leisure] model creates a wedge between real wages and the marginal product of labor similar to the wedge that taxes create. The increase in the share of natural resources reduces hours worked. It discourages work and reduces labor supply. This is because the wage rate in the oil-producing countries exceeds the equilibrium wage rate due to rent. Razzak, W and B Laabas (2016)

Abstract In addition to the high share of oil revenues in the GCC, we found that the share of oil in real GDP is high, albeit varies across the GCC countries. The shares are relatively higher in Kuwait and Saudi Arabia than the UAE for example. We also show that the production of oil in the GCC and global oil consumption share a long run common trend. Further, they have a significant short-run dynamic relationship. Oil behaves like a tax. The share of oil in output is akin to the tax rate, which creates a wedge between the marginal productivity of labor and real wages. It distorts the labor market. The GCC data that we presented earlier show that the volatilities in most macroeconomic variables are associated with the volatility of oil prices, and the shares of oil revenues in total revenues are high. In this chapter, we produce some empirical evidence for oil dependence because it is the most significant risk factor for the future of the GCC countries. Interestingly, in a zero-carbon state of the world, one might predict less macroeconomics volatility in the GCC countries. Would the GCC economies be better off in such a world? What would the transitional dynamic to such a state of the world look like? This is a good research question. The GCC economies are mercantile economies with sizable service sectors as shown earlier. The merchants in the GCC countries, however, are a class of very powerful people. They inherit their power and connections with the governments for generations. The governments control the distributions of exclusive import rights of goods and services called Wakala (the plural is Wakalat). These are intergenerational, family-special privileges, which provide monopoly power in the domestic markets. Characteristically, merchants resist change. Manufacturing, for DOI: 10.4324/9781003288282-3

The Oil Dependency Dilemma 33 instance, could represent a threat to the merchants. Mokyr (1990) explains that powerful people with entrenched interests in the status quo opposed progress and change throughout history. Moreover, we would argue that the merchants also represent a barrier to entry; hence, competition is almost absent in the GCC markets. It is very difficult for a new company to enter the market because by definition each one of those wealthy merchants controls vast business conglomerates, which include retails, constructions, imports and exports, petrochemicals, etc. In addition to the low productivity growth and declining marginal productivity of factors presented earlier, Table 3.1 reports the Conference Board’s data of the growth of average real GDP per worker over periods of ten years from 1950 to 2019. Low productivity growth is consistent with the resource curse, rentier economies. Most countries with abundant natural resources have low economic growth rates, fixed exchange rates, monolithic and more authoritarian political systems, and worse development outcomes than countries with fewer natural resources; Japan, Korea, Singapore, Taiwan, and Vietnam are just examples of such countries. Dominant service sectors also contribute to low GDP growth mostly because output of the services sectors is measured imprecisely. There are a number of theories for the resource curse. For evidence in the Arab, oil-producing countries see, for example, Elbadawi and Gelb (2010), Elbadawi and Soto (2012). In this chapter, we provide three pieces of empirical evidence for oil dependency in the GCC countries. First, we estimate the share of oil in output. It is a measure of the responsiveness of real output to oil production. We show that the shares are relatively high in magnitude and statistically significant – i.e., output response to change in oil production is large. Second, we show that oil production in GCC countries is highly associated with global oil consumption in the long run – i.e., cointegrated. Finally, we show that there is a business cycle dynamic between oil production in the GCC and global oil consumption that could be projected into the future. We estimate a Structural Vector AutoRegression (SVAR) to generate baseline dynamic stochastic projections over the period 2020 to 2030. Then we use a counterfactual experiment, whereby the GCC countries cut oil production in response to a severe decline in global oil consumption. We then generate another set of projections over the same period and examine the deviations from the baseline projections. Real output declines significantly, but reactions differ across the GCC. Table 3.1 Growth Rates of Real GDP per Employed Person 1950–1960 1961–1970 1971–1980 1981–1990 1991–2000 2001–2010 2011–2019 Kuwait −0.01 Oman 0.04 Qatar −0.01 KSA 0.05 UAE 0.04

0.03 0.14 −0.02 0.07 −0.04

Source: Conference Board

−0.10 −0.02 −0.01 0.01 −0.01

−0.10 0.01 −0.13 −0.04 −0.07

0.06 0.00 0.04 0.01 −0.02

−0.02 −0.03 −0.03 −0.01 −0.09

−0.02 −0.05 −0.01 −0.02 0.02

34

The Oil Dependency Dilemma

Estimating the Share of Oil in Real Output The Production Function We measure the share of oil in output by estimating a Cobb-Douglas production function with three arguments: capital stock, labor, and oil production. The CobbDouglas production function is consistent with the Statistics of National Account.1 The production function is Yt  H t K t Lt e t,

(3.1)

where Yt . is real GDP, H t is hydrocarbons (oil or gas in the case of Qatar), Kt is the stock of capital, Lt is a measure of labor (either employment or working-age population), and ε t is an error term. The values of the shares of oil, capital, and labor, ω , θ, and γ , are between zero and one. They may sum to one (i.e., constant return to scale production function), less than one (i.e., decreasing return to scale), or greater than one (i.e. increasing return to scale). For H t , Stiglitz (1974), for example, uses the ratio of resource utilization to the stock of natural resources in the production function, while Solow and Wan (1976) only use the flow of oil. We use the production of oil in millions of barrels a day. Estimation Problems Typically, the Cobb-Douglas production function is estimated in a log-linear form. However, a number of daunting specification and estimation problems are associated with this production function. The first problem is endogeneity (i.e., single-equation bias). The second problem is the measurement of factor inputs. Third is an omitted variable problem. All these problems result in biased and inconsistent parameter estimates if not corrected. Fourth is the identification of the nature of trends. Whether the variables are trend-stationary or difference-stationary affects the way we estimate the production function. Fifth, it would be difficult to identify the shares if the regressors are very highly collinear with oil, which is more so in some countries than others. Furthermore, it is hard to predict and identify the nature of the trend (Phillips, 2003). However, looking at the plots of the data one can see trends everywhere. The Data Figures 3.1, 3.2, 3.3, 3.4, and 3.5 plot the data that we will use to estimate the production function. The data are from 1970 to 2019. Real GDP and the stock of capital are from the Penn World Table 10. Labor is measured either by working-age population or ages (15–64) and taken from the World Development Indicators or total employment from the Penn World Table 10 depending on the availability of the data and which fit best. Oil production is from the BP Statistical Review 2020. The oil production data for Bahrain are unavailable because it is a very small oil producer. Qatar is a gas producer; therefore, we use gas instead of oil. The data have trends. Next, we examine the nature of the trends before estimating equation (3.1).

The Oil Dependency Dilemma 35

Figure 3.1 Time Series Data of Real GDP Data Source: Penn World Table 10, 2020

The Time Series Properties of the Data For robustness, we test for trend and unit root using a number of commonly used tests – e.g., the Dickey and Fuller (1979) – Augmented Dickey-Fuller (Said and Dickey, 1984), the generalized least squares (GLS) (Elliot et al., 1996), and Phillips and Perron (1988). We also used the Ng and Perron (2001) test, which is a modified Phillips-Perron, two test statistics Zα and Z t , Bhargava (1986), and finally the augmented Dickey – Fuller (ADF) with breakpoint. We consider a large number of specifications of the trend, the intercept, and break type (additive outlier and innovation outlier) for robustness. In addition, we estimate the unit root regression equations with different specifications: (1) without a constant, (2) with a constant, and (3) with a constant and linear trend. Note that these specifications have different distributions – i.e., the test statistic ˜ ° in each of these specifications has a different tabulated critical value. We also use a variety of

36

The Oil Dependency Dilemma Log Capital Stock Kuwait

Oman

14

13.6 13.2

13

12.8 12.4

12

12.0 11.6

11

11.2 10.8

10 70

75

80

85

90

95

00

05

10

15

10.4 70

75

80

85

90

Qatar

00

05

10

15

00

05

10

15

KSA 16.0

15

15.6

14

15.2

13

14.8

12

14.0

14.4 13.6

11 10 70

95

13.2 75

80

85

90

95

00

05

10

15

12.8 70

75

80

85

90

95

UAE 15.5 15.0 14.5 14.0 13.5 13.0 12.5 70

75

80

85

90

95

00

05

10

15

Figure 3.2 Time Series Data of the Stock of Capital Data Source: Penn World Table 10, 2020

Information Criteria – e.g., the Akaike information criterion (AIC), Schwarz information criterion (SIC), Hannan – Quinn information criterion (HQ) (and some modified versions of these criteria) to determine the lag structure.2 The outputs of these tests are quite large; therefore, they are not reported, but they are available on request. These unit root tests are weak in general – i.e., have low power against stationary alternatives, do not reject the null too often. The econometrics literature on the power of unit root tests is large, and we do not cite them here. Economists are suspicious of the feasibility of these unit root tests. Stock (1991), Cochrane (1991), Rudebusch (1993), and Christiano and Eichenbaum (1990) argued that these tests could not distinguish between a root of one and 0.98 for example. Although it is difficult to predict trends, most economists seem to agree that real GDP, capital, labor, have stochastic, as opposed to deterministic, trends. Therefore, the unit root is a plausible DGP. We find the coefficient of the deterministic trend regressor

The Oil Dependency Dilemma 37

Figure 3.3 Time Series Data of Total Employment Data Source: Penn World Table 10, 2020

only marginally significantly different from zero.3 Hence, these variables are difference-stationary. The next step before we estimate the production function is to test for cointegration among the aforementioned variables – i.e., to test whether these non-stationary unit root variables have a common stationary linear combination or a common long-run trend. We use the Johansen’s Maximum Likelihood Test, Johansen (1988, 1991, 1995) and Johansen and Juselius (1990), λ - max (or maximum eigenvalue test), and the trace statistics to test the null hypothesis that these five variables “do not share” a long-run common trend – i.e., not cointegrated (cointegration represents a stationary linear combination of the five variables). This test is a common test for multivariate analysis. It turned out that these variables do share a common long-run trend, a long-run equilibrium. The null of “no” cointegration is rejected. Although not usually recommended for multivariate analysis, we also tested the residuals from the Ordinary Least Squares (OLS) log-level regression of

38

The Oil Dependency Dilemma

Figure 3.4 Time Series Data of Oil Production Data Source: BP Statistical Review (2020) Kuwait’s production collapsed during the first Gulf war in 1990

equation (2.1) for unit root using the tests for unit root cited earlier. We reject the null of a unit root in the residuals; hence, the variables in the production function are probably cointegrated. The results suggest that there is at least one, and at most two, significant cointegration relationships depending on the assumptions made about the trend in the VAR. For robustness, we tested the data using specifications with (1) no intercept and trend in the cointegration relationship, (2) intercept but no trend in the cointegration relationship, and (3) linear deterministic trend. Cointegration among the variables suggests that one could estimate the production function using an OLS in log-levels, Fully Modified OLS, i.e., FM-OLS (Phillips and Hansen, 1990), and Dynamic OLS (e.g. Phillips and Loretan, 1991; Saikkonen,

The Oil Dependency Dilemma 39

Figure 3.5 Time Series Data of Working-Age Population Data Source: World Development Indicators Kuwait has missing data during the first Gulf war in 1990

1992; Stock and Watson, 1993). These estimators, especially Phillips-Loretan, are very efficient, account for serial correlation in the residuals, and remedy the endogeneity problem (the single-equation problem) of the production function. We begin by estimating the production function in log-linear form for each country separately. Estimation The estimation of the production function is daunting. First, we estimated the production using OLS, FM-OLS, and Dynamic OLS, but we found that the signs of the shares of capital and labor in some cases are incorrect. This is a misspecification problem, which results from not fitting the optimal numbers

40

The Oil Dependency Dilemma

of lags in FM-OLS and the lads and leads in the Dynamic OLS. We could not search for the optimal lags and leads using Information Criteria because the sample is short. Therefore, to remedy this, we estimate the production function using the Generalized Method of Moments (GMM) (Hansen, 1982).4 The instruments are the distribution of the working-age population, ages (20–24), (25–29) . . . and (60– 64) years. These instruments are strictly exogenous, relevant, and uncorrelated with the error term. Moreover, the instruments are consistent with the life-cycle hypothesis, whereby capital stock and labor supply increase with age, peak, and then decline as people approach retirement. In a couple of regressions, we needed to add lags of labor or capital as instruments in addition to the distribution of the working-age population. We also impose a constant return to scale restriction, whereby the shares sum to one, except for the case of Qatar. Qatar is a gas producer, so gas production is used instead of oil as a regressor. However, the stocks of capital and gas production in Qatar are very highly correlated (the correlation coefficient is 0.96); thus the identification of the coefficients was impossible without some additional lags of the stock of capital in the instruments. We needed four lags of the stock of capital as instruments in addition to the population distribution. The data of the distribution of the working-age population are available from 1989 to 2019, except for Kuwait from 1995 because of the Gulf War, where the data were missing. Therefore, the sample is 1980 to 2019, except for Kuwait from 1995 to 2019. Finally, labor input is measured by total employment in Kuwait, Oman, and Qatar and by the working-age population in KSA and the UAE because they fit better. The results are reported in Table 3.2. The shares of oil are 0.56 in Kuwait, 0.29 in Oman, the second largest 0.51 in Saudi Arabia, and 0.23 in the UAE. For Qatar, the share of gas is 0.39. The UAE’s share of oil is relatively small, probably because Dubai is a non-oil producer. Oman is a small producer of oil, but the share is still large. The shares of capital are 0.20 in Kuwait, 0.51 in Oman, 0.23 in Qatar, 0.35 in Saudi Arabia, and 0.31 in the UAE. Oman has the largest share of capital in output. The share of labor in Qatar is 0.11 and estimated freely without any restrictions on the function. For the rest of the GCC countries, the implied shares of labor were computed to be 0.24 in Kuwait, 0.19 in Oman, 0.14 in Saudi Arabia, and a very large 0.46 in the UAE. Razzak and Laabas (2016) show that oil acts as a wedge between the marginal product of labor and the real wage rate just like the tax rate does (i.e., the marginal product of labor = (1− ˝ ) w, where τ is the tax rate, and w is real wages). The increase of the share of oil in the production of output is a tax really, particularly on future generations. It distorts the labor market. They also show that people tend to supply more labor – i.e., work more hours – in periods of low oil price, which is a rational decision. When I was living in Oman, I observed that in 2014 after the crash of the oil market, the Omni people worked more than one job. For example, a low-income (government) employee would have a second or more jobs. Some have private businesses in addition to their daytime jobs in the public

The Oil Dependency Dilemma 41 Table 3.2 GMM Estimates of the Share of Oil in Output

lnYt = ˆlnH t + ˇ lnKt + (1 − ˆ − ˇ ) lnLt + ˘ t

ω θ γ Implied Labor share 2 Rˉ . DW J (vi)

Kuwait (i)

Oman (ii)

Qatar (iii)

KSA (iv)

UAE (v)

1995–2019

1989–2019

1989–2019

1989–2019

1989–2019

0.56 (0.0000) 0.20 (0.0000)

0.30 (0.0000) 0.51 (0.0000)

0.51 (0.0000) 0.35 (0.0000)

0.23 (0.0000) 0.31 (0.0000)

0.24 0.81 0.05 (0.9810)

0.19 0.23 0.09 (0.5961)

0.39 (0.0000) 0.23 (0.0000) 0.11 (0.0000)

0.14 0.99 0.31 0.6948

0.46 0.93 0.15 (0.8175)

0.99 0.06 (0.9370)

(i) The weighting matrix estimation: heteroscedasticity and autocorrelation (HAC), pre-whitening with lag = 1, Bartlett kernel, Newey-West with automatic bandwidth 40.7559, NW automatic lag length = 2. Standard errors and covariance computed using HAC weighting matrix (prewhitening with lags from AIC max lags, Bartlett kernel, Newey-West automatic bandwidth = 1.1908, NW automatic lag length = 2). Convergence was achieved after 293 weight iterations. Instruments are log population distribution ages (20–24), (25–29) . . . (60–64). The equation includes a constant. (ii) The weighting matrix estimation: HAC, pre-whitening with lag = 1, Bartlett kernel with fixed bandwidth = 4. Standard errors and covariance computed using HAC weighting matrix (prewhitening with lag = 1, Bartlett kernel, Newey-West automatic bandwidth = 9.4720, NW automatic lag length = 3). Convergence was achieved after 171 weight iterations. There is a dummy variable that takes a value of 1 during the Gulf War period from 1990 to 1992. Instruments are log population distribution ages (20–24), (25–29) . . . (60–64), and one lagged log employment. (iii) The weighting matrix estimation: HAC, pre-whitening with lag = 1, Bartlett kernel, Newey-West with automatic bandwidth 4.7440NW automatic lag length = 3. Standard errors and covariance computed using HAC weighting matrix (pre-whitening with lags from AIC max lags, Bartlett kernel, Newey-West automatic bandwidth = 4.9435, NW automatic lag length = 3). Convergence was achieved after 293 weight iterations. No restrictions are imposed on the production function. The instruments include log population distribution ages (20–24), (25–29) . . . (60–64) and four lags of the log capital stock because the capital stock and gas production are highly correlated (correlation coefficient is 0.96) therefore the identification of the share of capital was not possible without this specification. The equation includes a constant. (iv) The weighting matrix estimation: HAC, pre-whitening with lag = 1, Bartlett kernel with fixed bandwidth = 4. Standard errors and covariance computed using HAC weighting matrix (prewhitening with lag = 1, Bartlett kernel, Newey-West automatic bandwidth = 2.6157, NW automatic lag length = 3). Convergence was achieved after 67 weight iterations. Labor is measured by the working-age population. The instruments include log population distribution ages (20–24), (25– 29) . . . (60–64). The equation includes a constant. (v) The weighting matrix estimation: HAC, pre-whitening with lag = 1, Bartlett kernel, NeweyWest with automatic bandwidth 4.3952, NW automatic lag length = 3. Standard errors and covariance computed using HAC weighting matrix (pre-whitening with lags from AIC lag = 1, Bartlett kernel, Newey-West automatic bandwidth = 4.3952, NW automatic lag length = 3). Convergence achieved after 93 weight iterations. Labor is measured by working-age population. The instruments include log population distribution ages (20–24), (25–29) . . . (60–64). Equation includes a constant. (vi) The J statistic is a chi-squared test of the null hypothesis that the instruments are over-identified. P-values are in parentheses.

42

The Oil Dependency Dilemma

sector. The same is true in Kuwait. The explanation is that when oil prices fall, governments’ revenues fall too; to deal with the budget deficit, they reduce price and wage subsidies, freeze hiring in public jobs, reduce benefits, and increase fees. People work longer hours in order to smooth out consumption over the business cycle. In other words, people try to keep their consumption unchanged when the economy is contracting.

Oil Production – Global Oil Consumption Relationship in the Long Run So far, the evidence suggests that the share of oil in output is relatively large in the GCC countries, implying that real output is very responsive to oil. The second test for dependency is to examine the association between oil production and global oil consumption. As long as oil is in demand, the GCC countries will continue to supply it for a long time. The responsiveness of the GCC countries to global oil consumption becomes a very important issue as the zero-carbon future draws closer. Unpredictable pandemics would also be a problem. Therefore, we test whether oil production and global oil consumption share a common long-run trend – i.e., cointegrated. The null hypothesis, which we seek to reject, is “no cointegration.” This is a bivariate case; therefore, we test this using the Engle and Granger (1987) method, which consists of three common steps – i.e., the Triangular Representation Theorem. If unit root time series, for example, yt and xt are cointegrated, such that, for example, zt = yt − bxt is a stationary linear combination, then there exists an error correction equation, for example, ˜yt = ˙˜xt + ˆ zt −1 + et . FM-OLS and Dynamic OLS estimators are, more efficient, variants of this error correction equation. First, we regress the log of oil production on the log of global oil consumption using the OLS estimator. Results are reported in Table 3.3. Then we test the null hypothesis that the residuals have a unit root (unit root means no cointegration). In doing so, we follow the same strategy used earlier. For robustness, we use more than one test, and a number of Information Criteria to determine the optimal lag structure. Rejection of the unit root in the residuals is quite convincing evidence of cointegration because these common tests for unit root have low power as we said (i.e., they cannot reject the null of unit root often), thus the power issue becomes irrelevant in case of rejections of the null. Finally, we estimate an error correction equation, whereby we run an OLS regression of the log-difference oil production on the log-difference global oil consumption and the lagged residuals from the first-level regression. This error-correction model (ECM) is a more powerful test for cointegration than testing for the unit root in the residuals from the first regression; if the lagged residuals from the level regression are statistically significant – i.e., ρ in the previous equation has a high t ratio. The distribution of this parameter is not standard but a sufficiently large t would suffice. The BP Statistical Review reports global oil consumption in three different measurements: Exajoules, barrels/day, and tons. They have the same trend, so it does not matter for the regression which one is used. Before we run the regression, Figure 3.6 is a scatterplot of the data.

The Oil Dependency Dilemma 43

Figure 3.6 Log Oil Production (Million Barrels/Day (MBD)) and Global Oil Consumption (Exajoules) Source: Loil is log oil production (for Qatar, gas production) and LGOC is global gas consumption in Exajoules (for Qatar global gas consumption in Exajoules)

44

The Oil Dependency Dilemma

Table 3.3 OLS Results of Responsiveness of Oil to Global Oil Consumption, 1970–2019 ln H t = ˛ lnCtO + vt (i)

β P-value 2 Rˉ . DW

Kuwait (ii)

Oman (iii)

Qatar (iv)

KSA (v)

UAE (vi)

1.53 (0.0000) 0.09 0.59

1.29 (0.0000) 0.59 0.07

0.65 (0.1963) 0.27 0.025

1.81 (0.0000) 0.55 0.34

1.55 (0.0000) 0.85 0.21

(i) CtO , global oil consumption is measured in Exajoules and H t is the production of oil (gas for Qatar). (ii) HAC standard errors and covariance; pre-whitening with lags = 1 from AIC with max lag = 3, Bartlett kernel, Newey-West automatic bandwidth = 6.3001, NW automatic lag length = 3. (iii) HAC standard errors and covariance; pre-whitening with lags = 2 from AIC with max lag = 3, Bartlett kernel, Newey-West automatic bandwidth = 6.9941, NW automatic lag length = 3. (iv) HAC standard errors and covariance; pre-whitening with lags = 3 from AIC with max lag = 3, Bartlett kernel, Newey-West automatic bandwidth = 8.3984, NW automatic lag length = 3. (v) HAC standard errors and covariance; pre-whitening with lags = 3 from AIC with max lag = 3, Bartlett kernel, Newey-West automatic bandwidth = 4.2183 NW automatic lag length = 3. (vi) HAC standard errors and covariance; pre-whitening with lags = 3 from AIC with max lag = 3, Bartlett kernel, Newey-West automatic bandwidth = 5.5289NW automatic lag length = 3.

The Confidence Ellipse is a chi-square test statistic at the 95 percent level. The narrower the Ellipse, the more significant the correlation is. The graphs show very positive significant relationships, more so in the cases of Qatar (gas) and the UAE. Kuwait’s correlation is positive, significant, but relatively less so. The very low values of the Durbin-Watson statistic DW, along with high R2, indicate that oil production and global oil consumption may be cointegrated (Engle and Granger, 1987). We use the same tests we used earlier for testing for unit root, but we do not report the results of all the tests because they are similar, and to save space, we only report the ADF P-values for three specifications, without an intercept, with an intercept, and with an intercept and trend. Also, we report the ADF test for unit root with a break. Table 3.4 reports the results; they suggest that we can reject the null hypothesis of a unit root, which is in favor of the EngleGranger test. Qatar being a gas producer does not seem to have a significant cointegration relationship between gas production and global gas consumption. However, the relationship is especially strong (very small P-values) in Saudi Arabia and the UAE, which implies that the production of oil and global oil consumption share a common long-run trend. Finally, we report the most reliable test for cointegration. We estimate an error correction equation and test the lagged residuals from the level regression. Table 3.5 reports the results. We regress the log-differenced oil production on the log-differenced global oil consumption and one lag of the residuals from the first-level regression. The t value of the coefficient on the lagged residuals and the P-value are reported. We can say with 95 percent confidence that Kuwait and Saudi Arabia’s oil productions share a stable long-run cointegration relationship with global oil consumption. Thus, the production of oil is highly associated with global oil consumption in the long run – i.e., high oil dependency on global demand is quite strong in both countries.

The Oil Dependency Dilemma 45 Table 3.4 ADF Test for Unit Root in the Residuals vt – OLS Results

Kuwait Lags Oman Lags Qatar Lags KSA Lags UAE Lags

No Intercept

Intercept

Intercept & Trend

With Intercept Break (Innovation Outlier)

Beak at

(0.0009) 0 (0.0432) 2 (0.1326) 7 (0.0048) 5 (0.0044) 3

(0.0147) 0 (0.2853) 2 (0.8654) 1 (0.0581) 5 (0.0547) 3

(0.0761) 0 (0.6497) 1 (0.4416) 7 (0.0606) 5 (0.0093) 5

(0.0000) 1 (0.0206) 0 (0.7933) 8 (0.0266) 6 (0.0152) 3

1991 1980 1997 1982 1990

AIC determined the lag length. P-values are in parentheses.

Table 3.5 OLS t Estimates of the Error Correction Equation ΔlnH = α + βΔlnCtO + ρvt–1 + ut

tρ

Kuwait (i)

Oman (ii)

Qatar (iii)

KSA (iv)

UAE (v)

−5.96 (0.0000)

−1.87 (0.0808)

−0.62 (0.5328)

−3.17 (0.0027)

−1.80 (0.0769)

The t values and P-values are in parentheses (i) HAC standard errors and covariance, pre-whitening with lag = 3 from AIC with max lag = 3, Bartlett kernel with Newey-West automatic bandwidth = 11.5187, NW automatic lag = 3. (ii) The regression has a dummy variable = 1 in 1980 and zero elsewhere to capture the break HAC standard errors and covariance, pre-whitening with lag = 3 from AIC with max lag = 3, Bartlett kernel with Newey-West automatic bandwidth = 8.7664, NW automatic lag = 3. (iii) HAC standard errors and covariance, pre-whitening with lag = 3 from AIC with max lag = 3, Bartlett kernel with Newey-West automatic bandwidth = 4.7328, NW automatic lag = 3. (iv) HAC standard errors and covariance, pre-whitening with lag = 3 from AIC with max lag = 3, Bartlett kernel with Newey-West automatic bandwidth = 5.8522, NW automatic lag = 3. (v) HAC standard errors and covariance, pre-whitening with lag = 0 from AIC with max lag = 3, Bartlett kernel with Newey-West automatic bandwidth = 5.3619, NW automatic lag = 3.

Oman and the UAE have significant relationships with production and global oil consumption at the 10 percent level. Qatar is a gas producer. The long-run relationship between gas production and global gas consumption is insignificant, which is consistent with the earlier estimate of the share of gas in output, although not very intuitive. The results reported in the two previous tables show that domestic oil production in the GCC countries and global oil consumption probably share a common long-run (stationary) trend – i.e., they are cointegrated, most certainly in the case of Kuwait and Saudi Arabia, but less so in Oman and the UAE. The results are unrelated to the relative size of production or reserves because the UAE produces more oil than Kuwait, although both have similar reserves. Qatar does not seem to have a long-run connection with global consumption. As a conclusion, I would say that

46

The Oil Dependency Dilemma

there is statistical evidence of the oil dependency of the GCC countries arising from the high share of oil production in output for sure and less so from the longrun association of oil production and global oil consumption. This is probably because the GCC is not the only provider of oil and gas. Global oil consumption may decline in the future because of climate change and pandemics. A natural question to ask is, What are the effects on the GCC economies if their oil production has to be reduced in response to a sudden negative global oil shock.

The Short-Run Dynamic Relationship and Stress Tests Here, we test a counterfactual scenario of an adverse global oil demand shock, whereby global oil consumption declines suddenly because of either climate change policies or another exogenous global demand shock. Recall our earliest results that a 1 percent decline in global consumption reduces oil production by 1.5 percent in Kuwait, 1.3 percent in Oman, 1.81 percent in Saudi Arabia, and 1.5 percent in the UAE. Qatar is a gas producer, so its production falls by 0.65 percent for a 1 percent reduction in global gas consumption. In case of a negative shock to global oil consumption, the GCC countries must reduce oil production in response to the shock to keep the oil price from further declines. Essentially, this is a stress test of the GCC economies. We accomplished this as follows. First, we estimate an SVAR, which includes three variables: global oil consumption, oil production, and real GDP over the sample 1970–2019. Second, we solve the model. Third, we make baseline dynamic stochastic projections for the period 2020 to 2030. The 2030 date is arbitrary. Fourth, we re-estimate the SVAR with a counterfactual shock scenario. We argued in the introduction that there is significant uncertainty about the ability of governments to reach the zero-carbon target by 2050. It is more doubtful that they would reach significant reduction by 2030. The counterfactual scenario that we consider here represents a severe shock. It is assumed that global oil consumption declined suddenly by 50 percent in the year 2014 (recall that the last oil shock was in 2014), and continued to decline by 50 percent every year from 2015 to 2030 tapering toward zero. Oil production is close to zero by the year 2030. Fifth, we solve the model under this shock and make new dynamic stochastic projections for the period 2020–2030. Six, show the deviations of the dynamic stochastic projections under this shock scenario from the baseline projections. For each country, we estimate an SVAR. Essentially, a VAR is a dynamic system of k equations. There is an equation for each variable. In each equation, the dependent variable depends on a constant term, its own lagged values, and the lags of the other variables in the system, and each variable has the same explanatory variables (Sims, 1980). For more, see Hamilton (1994, p. 291). See the Technical Appendix 3.1 for a formal representation. For Kuwait, we estimate an SVAR from 1970 to 2019. Testing the SVAR properties indicates that the variables must be in log-difference rather than in log-level to ensure that all the roots are inside the unit circle – i.e., the SVAR is stable. The following variables enter the SVAR in order: log-difference global oil

The Oil Dependency Dilemma 47 consumption, log-differenced oil production, and log-difference real GDP – i.e., the system has three equations, one for each variable as shown in equation (3). We begin with fitting a general 6 lags SVAR then test for the number of significant lags using a variety of Information Criteria (sequential modified LR tests, final prediction error, AIC, SIC, and HQIC), and a chi-square lag exclusion test. Finally, the SVAR is estimated in log-differences with two lags. The joint chi-square test’s P-values for lag one and lag two exclusions were 0.0000 and 0.0012, thus significant. The residuals are serially uncorrelated and homoscedastic. Second, we solve the model over the period 2020 to 2030 and generate baseline dynamic stochastic projections of the endogenous variables from 2020 to 2030. Third, re-estimate the SVAR under the severe shock scenario described previously. Solve the model, and generate dynamic stochastic projections from 2020–2030 for all the variables in the system.5 (See Appendix 3.2 for the description of the solver). For Oman, testing the properties of the system indicated an SVAR in log-levels is more appropriate, 2 lags, with a sample from 1980 to 2019 instead of 1970 to 2019, which is needed to ensure the stability of the system. For Qatar, we use gas production instead of oil as done earlier. The SVAR is estimated in log-levels from 1980 to 2019 to ensure stability. For Saudi Arabia, we estimate the system in log-levels from 1980 to 2019 too. Finally, the UAE’s SVAR is estimated with 1 lag from 1970 to 2019. The estimation results are reported in Appendix 3.3. Figure 3.7 plots the deviations of log real GDP’s dynamic stochastic projections under severe adverse global oil consumption shock from the baseline projections for each of the GCC countries from 2014 to 2030. Under such a severe decline in global oil consumption, real GDP would fall significantly in the GCC countries. A major adverse oil price shock hit the GCC in March 2014. Oil prices suddenly tumbled by 65 percent. Figure 3.8 plots the spot oil price. This adverse oil shock is a negative term of trade shock. It created a series of economic problems. Figure 3.9 plots the nominal and the real GDP growth from 1990 to 2020 (2020 are IMF estimates). All GCC countries experienced a slow growth after the 2014 oil price shock. Table 3.6 reports the average and the standard deviation of the real GDP growth rates over the periods 1995–2013 and 2014–2019, and the differences. All GCC real GDP growth rates declined significantly after the 2014 oil price shock. Although Qatar is not an oil producer, it has the highest decline in growth rates from 2014 to 2019. Figure 3.10 plots the averages. Qatar experienced a large decline in growth. Figure 3.11 plots the fiscal balance – GDP and the primary fiscal balance – GDP ratios. Table 3.7 reports the averages of the fiscal balance – GDP and the primary balance over different decades over time. Clearly, some deficits are worse than others are. The deficits increased after the oil price shock in 2014 in all countries except Qatar, which, interestingly, did not experience a fiscal deficit even though its GDP growth suffered the most. Figure 3.12 plots the data reported in Table 3.7. All GCC countries experienced current account deficits after 2014. Figure 3.13 plots the current account – GDP ratios.

48

The Oil Dependency Dilemma

Figure 3.7 Deviations of Dynamic Stochastic Projections of Log Real GDP under the Severe Adverse Global Consumption Shock from Baseline Projections

Figure 3.8 Average Real Price of Oil Fell in 2014 Data Source: IMF – WEO, October 2020. The average of Dubai, WTI, and Brent crudes deflated by the U.S. CPI index

The Oil Dependency Dilemma 49

Figure 3.9 Real and Nominal GDP Growth Data Source: IMF World Economic Outlook, October 2020. The GCC average real GDP growth from 1990 to 2013 was 5.4 percent and from 2014 to 2020 was 0.80 percent. The values of 2020 are IMF estimates.

Table 3.8 reports the averages of the current account over the two samples 1995–2013 and 2014–2019. Figure 3.14 plots the averages reported in table (3.8). It is clear that Bahrain and Oman stand out among the GCC; they have current account deficits. Therefore, Bahrain and Oman have twin deficits. The GCC governments hoped that oil prices would rise again to their pre-2014 levels; they did not. The fiscal deficits increased more, and they had to borrow. Most of the GCC countries decided to borrow in the international capital markets rather than the IMF to bridge the gaps in the fiscal balances. It is quite intriguing that the GCC governments, especially Oman as far as I know, did not borrow from the IMF. Oman’s governor of the Central Bank at the time thought about the IMF loan. However, he questioned the credit arrangement and did not follow through

50

The Oil Dependency Dilemma

Figure 3.10 On Average, Real GDP Growth Has Declined after 2014 Oil Price Shock Table 3.6 Average and Standard Deviation of Real GDP Growth Rates 1990–2013

2014–2019

Country

Mean

Std. Dev.

Mean

Std. Dev.

Growth Change

Bahrain Kuwait Oman Qatar KSA UAE GCC

4.75 5.66 4.32 8.63 3.95 5.4 5.45

2.05 21.5 3.03 9.56 5.14 5.42 10.1

3.05 0.16 1.90 2.28 1.91 2.95 2.04

1.18 2.57 2.35 2.60 1.88 1.52 2.16

−1.70 −5.50 −2.42 −6.35 −2.04 −2.45 −3.41

Data Source: IMF, WEO, October 2020

with the idea. Surely, the IMF would have lent to the GCC governments at a much lower interest rate than the international capital market. Oman’s Central Bank knew that Morocco, Egypt, Iraq, and other Arab countries borrowed from the IMF regularly. My understanding is that some Omani economists and policymakers were wary of the IMF’s close and tight supervision that usually accompanies such loans. The current account deficits could threaten the exchange rate peg system, whereby the currencies are fixed to the USD, and it would eventually threaten

The Oil Dependency Dilemma 51 Fiscal and Primary Balances – GDP 1990–2020 Kuwait Bahrain 10 5 0 –5 –10 –15 –20

50 0 –50 –100 –150 90

95

00

05

10

15

20

–200

90

95

00

Oman 30

10

20

0

10

–10

0

–20

–10 90

95

00

05

10

15

20

–20

90

95

00

KSA 40 30 20 10 0 –10 –20 –30

10

15

20

10

15

20

10

15

20

Qatar

20

–30

05

05

UAE 30 20 10 0 –10

90

95

00

05

10

15

20

–20

90

95

00

05

Fiscal Balance – GDP Primary Balance – GDP

Figure 3.11 Fiscal and Primary Balance Deficits Data Source: IMF World Economic Outlook, October 2020. The GCC average of the FB – GDP from 1990 to 2013 is 3.58 percent and the PB – GDP was 2.1 percent. From 2014 to 2020, they are −4 percent and −5.5 for the FB – GDP and PB – GDP, respectively. The values of 2020 are IMF estimates.

financial stability. With declining oil prices and USD reserves at the central banks falling, the GCC countries had to borrow dollars to manage the twin deficits. Some countries needed to borrow more than others did. IMF estimates of 2020 indicate that Bahrain would have a debt – GDP ratio of 128 percent, Oman 81.5 percent, and Qatar 68 percent. Kuwait is less than 20 percent; Saudi Arabia is less than 30 percent; the UAE is 37 percent. Figure 3.15 plots the gross debt-to-GDP ratio. Table 3.9 reports the averages and the standard deviations over the periods 1990–2013 and 2014–2019. Figure 3.16 plots these averages. The average

52

The Oil Dependency Dilemma

Figure 3.12 Average Fiscal Deficits Higher After 2014 Table 3.7 Average Government Balances – GDP Ratios Fiscal Balance – GDP

Primary Fiscal Balance – GDP

1990–2013

1990–2013

2014–2019

Mean Std Dev. Mean Bahrain −2.48 4.20 Kuwait 8.18 40.78 Oman 4.32 7.12 Qatar 3.64 9.45 KSA 2.52 10.75 UAE 5.37 7.01 GCC 3.59 18.26

2014–2019

Std Dev. Change Mean Std Dev. Mean

−12.39 6.12 8.16 7.51 −11.21 7.25 6.78 10.22 −9.36 5.89 −0.84 2.31 −3.14 10.66

−9.91 −1.54 4.23 −0.03 −4.16 45.45 −15.53 3.72 6.88 3.14 6.11 8.95 −11.88 3.64 10.13 −6.21 5.53 6.99 −6.73 2.16 20.02

Std Dev. Change

−9.14 6.00 −4.87 9.32 −10.97 7.40 8.20 10.18 −10.73 6.91 −0.59 2.38 −4.68 9.78

−7.60 −0.71 −14.70 2.09 −14.37 −6.12 −6.84

Data Source: IMF, WEO, October 2020

external debt increased after 2014 oil price shocks in all GCC countries, except in Kuwait and Saudi Arabia. Estimates of 2020 were relatively higher than average GCC in Bahrain, Oman, and Qatar. Typically, forecasters find that the world demand for energy increases because population and economic growth rate projections increase over time. According to the World Bank, the total world population was 7.674 billion in 2019 and projected to be 8.5 billion in 2030 and 9.6 billion in 2050. Populated developing countries such as China and India have been growing fast in the past decade. Figure 3.17 plots real GDP per capita growth rates (official country statistics).

The Oil Dependency Dilemma 53

Figure 3.13 Current Account Balance Source: IMF World Economic Outlook, October 2020. The GCC average from 1990 to 2013 was 6.67 percent, and from 2014 to 2020, it was 1.6 percent. The 2020 values are IMF estimates.

Average growth rates were 8 and 6 percent for China and India, respectively; they are among the highest growth rates in the world. Both countries are expected to increase their oil consumption for years to come. Their demand for fossil fuel has been increasing fast, and they do not seem to satiate. Figure 3.15 BP Statistical Review of World Energy (2020, p. 4) reported that China and India were among the top five countries in the world in terms of oil consumption. It says that China had exceptional energy consumption acceleration in 2019, and that is why China dominated the expansion in the global market. It contributed to the highest increase in demand for every individual type of energy other than natural gas, where the U.S. demand was slightly higher.

54

The Oil Dependency Dilemma

Figure 3.14 The Current Accounts in Deficits After 2014 Oil Price Shock Table 3.8 Average the Current Account – GDP Ratio Mean

Std. Dev.

1990–2013 Bahrain Kuwait Oman Qatar KSA UAE GCC

2.09 14.92 3.48 4.28 6.89 8.40 6.68

Mean

Std. Dev.

Change

3.82 12.86 9.24 9.79 7.38 3.52 10.45

−4.61 −4.22 −12.71 2.81 −4.56 −0.52 −3.97

2014–2019 7.42 56.27 9.35 22.02 14.23 5.84 25.81

−2.52 10.70 −9.23 7.08 2.33 7.87 2.71

Data Source: IMF, WEO, October 2020

On the other hand, climate change has made people demand actions to reduce, or even eliminate the consumption of fossil fuel. The Economist magazine ran a special report on this subject in its 17 September 2020 issue and in “Leaders,” a story under the title, “Is It the End of the Oil Age?” It argued, “The move to a new energy order is vital, but will be messy.” The oil-producing countries, which make up about 8 percent of the world GDP and about one billion people, will be facing an increased risk during the transition to a non-hydrocarbon energy world. The Economist’s article says that as the demand for oil dwindles, countries will fight

The Oil Dependency Dilemma 55

Figure 3.15 External Debt – GDP Ratios Data Source: IMF World Economic Outlook, October 2020. The GCC average from 1990 to 2013 is 31 percent. It is 37.8 percent from 2014 to 2020. The 2020 values are IMF estimates.

viciously for market share. The country with the cheapest and cleanest crude will win. The article also says that the public resources to pay for it may also decrease. Saudi Arabia government revenues fell by 49 percent in the second quarter of 2020. The prediction of the Economist’s article is that a “perilous few decades lie ahead,” which is really a realistic picture as we look at the data. This argument is consistent with expectations regarding the declining demand for oil due to climate change; nonetheless, it requires rigorous testing. The looming global environmental crisis has made people all over the world concerned more about climate change, and they have been vocal and demanding serious and immediate policy change toward greener energy. In addition to climate change problems, recent evidence provides estimates of 10.2 million global excess deaths due to particular matters (PM25) found in fossil fuels (Vohra et al. 2021).

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The Oil Dependency Dilemma

Figure 3.16 On Average, GCC Debt – GDP Ratio Increased After 2014 Table 3.9 Average and Standard Deviation Debt – GDP Ratio Mean

Std. Dev.

1990–2013 Bahrain Kuwait Oman Qatar KSA UAE GCC

20.94 40.61 19.15 38.34 51.75 9.35 31.18

Mean

Std. Dev.

change

2020

21.41 6.38 22.51 11.44 8.14 4.51 27.38

58.83 −29.74 16.80 5.23 −38.52 10.65 2.72

128.28 19.26 81.53 68.06 33.42 36.93 61.25

2014–2019 10.56 40.78 11.11 20.03 35.12 7.05 28.23

79.77 10.87 35.96 43.57 13.23 20.00 33.90

Data Source: IMF, WEO, October 2020

Whether or not policymakers make speedy changes in policy as a response to such alarming environmental crises and when policy changes will take effect is still an open question; nevertheless, we observe changes in statistics now that indicate expected changes in the fossil fuel market. Investments in hydrocarbons and alternative energy sources might tell us more. Bloomberg NEF Clean Energy Investment Trends (2020, 2021) provides data. China is the leading country in investing in alternative renewable energy. The U.S. trend from 2006 to date is nearly flat, however, but data that are more recent may indicate a rise of 20 percent in renewable energy production. Global renewable energy investment in 2020 reached 137 billion USD. The year-on-year change in offshore wind energy between 2019 and

The Oil Dependency Dilemma 57

Figure 3.17 China and India Economic Growths High

2020 was 319 percent. The developed world is slowly but surely moving toward green energy alternatives. The international energy agency (IEA) December 2020 review of the U.S. energy data (Figure 1.3, p. 6) shows that the consumption of renewable energy is equal to that of coal for the first time since 1949. In Europe, the largest program to replace fossil fuel and nuclear energy with green energy is in Germany. The Federal Ministry for Economic Affairs and Energy in Germany reports that the share of green energy in total electricity consumption reached 42.1 percent in 2019. We could see that this trend, reducing fossil fuel and increasing renewable energy, is going to continue in the future. Furthermore, there is evidence of global change in production technology, even in agriculture, for example, Pellegrinia and Fernández (2018) provide empirical evidence from 58 countries. Sustainable production methods are spreading globally. In manufacturing, for example, electric cars have become a reality. The alternative energy scenario reduced the demand for hydrocarbons. It is reasonable to expect a significant decline in the global demand for hydrocarbons if electricity comes from green sources – e.g., wind, geothermal, and solar. The IEA said it now sees global oil demand for 2020 at 91.1 million barrels per day, reflecting a fall of 8.1 million barrels per day year-on-year. We do not know what the price of oil would be in the short run; however, we expect the trend to decline below the historical average in the long run. A below-average price of oil is a serious challenge to GCC countries. The BP Statistical Review of World Energy (2020, p. 5) reports that oil consumption grew by 0.9 million barrels per day (b/d), which is slightly lower than the ten-year average of 1.3 per Annam. The Chinese demand for oil increased by (680,000 b/d), which is the largest increase since 2015. Developing countries’ growth was below average.

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The Oil Dependency Dilemma

On the supply side, however, BP (2020, p. 5) says that the production of oil fell slightly, by 60k b/d in 2019. A strong production growth led by the United States was offset by a sharp decline in OPEC production. The report also showed that OPEC production fell by 2 million b/d, which is the steepest decline since 2009. It was a result of sanctions and what the report described as “economic difficulties” in Iran (−1.3 million b/d) and Venezuela (−560,000 b/d). In addition to these, OPEC+ production cut an agreement that reduced oil production in Saudi Arabia (430,000 b/d). Iraq and Nigeria, however, increased their production by 150,000 and 100,000 b/d, respectively, which is typical cartel (monopoly) behavior in my opinion. Finally, the Net-Zero Carbon by 2025, which is the IEA latest flagship report (2021) says, the roadmap sets out more than 400 milestones to guide the global journey to net-zero by 2050. These include, from today, no investment in new fossil fuel supply projects and no further final investment decisions for new unabated coal plants. By 2035, there will be no sales of new internal combustion engine passenger cars, and by 2040, the global electricity sector will have already reached net-zero emissions. That said, the world’s main energy source is still hydrocarbon-based (Roberts, 2004). We do not know when we will be hydrocarbon-free, and we do not know how much oil is in the ground precisely. Decades after the United States ran out of oil, it discovered a massive amount of Shale oil and discovered the technology to extract it. The United States once again became the largest producer of oil. Figure 3.18 plots the U.S. oil reserve trend. Shale oil is also a threat to GCC; it puts downward pressure on oil prices, and production and investments, although slowed down, are not finished yet. That said, without a doubt, the GCC countries would be facing increasing economic challenges in the next 30 to 50 years just because of the reliance on an uncertain source of income.

Figure 3.18 U.S. Oil Reserves Increasing

The Oil Dependency Dilemma 59

Technical Appendix 3.1: The VAR The SVAR is described by yt = A1yt–1 … Apyt–p + ɛt,

(A3.1)

where yt = (y1, y2t…ykt) is a k × 1 vector of endogenous variables. There is also an exogenous constant term, ɛt = (ɛ1t, ɛ2t ,… ɛkt)' which is a k × 1 vector of white noise residuals with (ɛt) = 0; E (ɛt ɛt' ) = ∑ɛ, and E (ɛt ɛs' ) = 0 for t ≠ s. Let ( pk + d) × 1 vector: '

' ' zt = (yt–1 …yt–p ),

and write the SVAR in a compact form: Yt = BZt + et.

(A3.2)

o Y is (Ct ;Ht,Yt); e is (e1t, e2t, e3t). Both are matrices of the endogenous variables, which are the residuals. The matrices B = (A1, A2, A3, constant) and Z = (Z1t, Z2t, Z3t) are the matrix of coefficients and matrix of regressors, respectively. The short-run restrictions that are imposed on the SVAR to identify these shocks imply that global oil consumption is driven by its own lags. Oil production is a function of its own past and past global oil consumption, and real GDP is driven by its own past, past oil production, and past global oil consumption. We estimate the SVAR for each country.

Technical Appendix 3.2: The Solver The method is described in Eviews 10.0 software. We solve the VAR using the Broyden method, which is a modified Newton’s method. It involves the use of an approximation, rather than the true Jacobian when linearizing the model. We update the approximation at every iteration of the 5,000 iterations we used by comparing the residuals from the new trial values of the endogenous variables with the residuals predicted by the linear model based on the current Jacobian approximation. This method is faster than Newton. See, Dennis and Schnabel (1983). We use analytic derivatives. The starting values are actual values. The model is solved in both directions. We stop solving when we hit a missing value. In a stochastic simulation, we solve the equations of the model such that the residuals match to randomly drawn errors, and the coefficients and exogenous variables of the model change randomly. The solution generates a distribution of outcomes for the endogenous variables in every period. We approximate the distribution by solving the model many times using different draws (1000) or the random components in the model then calculating statistics over all the different outcomes. Only values of the endogenous variables from before the solution sample are used in the dynamic solution of the projections. Lagged endogenous variables are

60

The Oil Dependency Dilemma

calculated using the solutions calculated in previous periods, i.e., not from actual historical values. A series for the mean is calculated. We consider one thousand repetitions reasonable to capture the true values; however, some random variation may be present between adjacent observations. The 95 percent confidence intervals are computed using Jain and Chlamtac (1985) updating algorithm. This updating algorithm provides a reasonable estimate of the tails of the underlying distribution as long as the number of repetitions is not too small. We use bootstrapped innovations; however, bootstrapped innovations drawn from a small sample provides a rough approximation to the true underlying distribution of the innovations. For the diagonal covariance matrix, the diagonal elements are set to zero. We do not scale the variances.

Appendix 3.3: The Estimated SVARs The observed residuals et have a covariance matrix ∑(ee' ). The structural SVAR model is Aet = But, where ut is a matrix of unobserved shocks, which we want to identify. This matrix has an identity covariance matrix ∑(uu' ) = I. Different methods can be used to identify shocks, but the orthogonality of the shocks implies that the identifying restrictions on A and B are of the form A∑A' = BB'. Since the matrices on both sides of the equality sign are symmetrical, we have k(k+1)/2 restrictions on the 2k2 and unknown elements in A and B. To identify A and B, additional 2k2 – (k+1)/2 identifying restrictions are needed. We use short-run restrictions on B. e1 = –α1u1; e2 = –α2e2 + α3u2; e3 = –α4e1 – α5e2 + α6u3.

Kuwait

Source: The standard errors are obtained using 1,000 Monte Carlo repetitions.

The Oil Dependency Dilemma 61

Figure 3.3.1 Impulse Response Functions

62

The Oil Dependency Dilemma

SVAR Estimates Sample (adjusted): 1972 2019 Included observations: 48 after adjustments Estimation method: Maximum likelihood via Newton-Raphson (analytic derivatives) Convergence achieved after 11 iterations SVAR is just identified A=

B=

1 a2 a4

0 1 a5

0 0 1

a1 0 0

0 a3 0

0 0 a6

Coefficient

Std. Error

z-Statistic

Prob.

0.02 −3.68 0.32 −1.18 −0.38 0.05

0.002 2.257 0.033 0.355 0.022 0.005

9.79 −1.63 9.79 −3.32 −17.4 9.79

0.0000 0.1024 0.0000 0.0009 0.0000 0.0000

a1 a2 a3 a4 a5 a6 Log likelihood Estimated A matrix: 1.000000 −3.687668 −1.185022 Estimated B matrix: 0.020745 0.000000 0.000000 Estimated S matrix: 0.020745 0.076500 0.054012 Estimated F matrix: 16.60872 37.42712 50.55117

179.7138 0.000000 1.000000 −0.384686

0.000000 0.000000 1.000000

0.000000 0.324529 0.000000

0.000000 0.000000 0.049786

0.000000 0.324529 0.124842

0.000000 0.000000 0.049786

−0.633266 −0.807510 −1.673331

8.051129 18.46179 24.85424

Oman

Source: The standard errors are obtained using 1,000 Monte Carlo repetitions.

The Oil Dependency Dilemma 63

Figure 3.3.2 Impulse Response Functions

64

The Oil Dependency Dilemma

The SVAR for Oman is estimated in log-levels from 1980 to 2019. The number of lags = 2. All roots are on the unit circle; hence, the VAR is stable. The chi-square P-values for the null hypothesis that there is no serial correlation at lag 1 and lag 2 are 0.1202 and 0.3901. These P-values cannot reject the hypothesis that the residuals are serially uncorrelated. The P-values at lag 1 to lag 2 are 0.1202 and 0.0116 so there is a small amount of serial correlation. The P-value of the joint chi-square test for the null hypothesis of homoscedasticity (in levels) is rather small (0.0248); however, we cannot reject it. For the squares, e12, e22, e33, e22 e12, e32 e12, and e32 e22, the null cannot be rejected with large P-values, 0.0784, 0.0515, 0.1806, 0.2802, 0.3668, 0.4832 respectively.

SVAR Estimates Sample: 1980 2019 Included observations: 40 Estimation method: Maximum likelihood via Newton-Raphson (analytic derivatives) Convergence achieved after 12 iterations SVAR is just identified Coefficient

Std. Error

z-Statistic

Prob.

a1 a2 a3 a4 a5 a6

0.009 1.583 0.037 −0.723 −0.588 0.025

0.001 0.614 0.004 0.443 0.105 0.002

8.94 2.57 8.94 −1.63 −5.56 8.944

0.0000 0.0100 0.0000 0.1029 0.0000 0.0000

Log likelihood

294.3468

Estimated A matrix: 1.000000 1.583510 −0.723446 Estimated B matrix: 0.009633 0.000000 0.000000 Estimated S matrix: 0.009633 −0.015253 −0.002008 Estimated F matrix: 0.298659 −0.073196 0.726247

0.000000 1.000000 −0.588495

0.000000 0.000000 1.000000

0.000000 0.037437 0.000000

0.000000 0.000000 0.025028

0.000000 0.037437 0.022031

0.000000 0.000000 0.025028

0.198127 0.385738 0.667610

0.569683 0.403612 1.729609

Qatar

Source: The standard errors are obtained using 1,000 Monte Carlo repetitions.

The Oil Dependency Dilemma 65

Figure 3.3.3 Impulse Response Functions

66

The Oil Dependency Dilemma

The SVAR for Qatar is estimated in log-levels from 1980 to 2019. The number of lags = 1 according to the various Information Criteria listed earlier. All the roots are on the unit circle; hence, the system is stable. The chi-square P-value for the null hypothesis that there is no serial correlation is 0.3890. The P-value of the joint chi-square test for the null hypothesis of homoscedasticity (in levels) is small (0.0388); however, we cannot reject it. For the squares, e12, e22, e33, e22 e12, e32 e12, and e32 e22 the null cannot be rejected with large P-values, 0.1319, 0.1069, 0.3239, 0.0832, 0.1740, and 0.3815, respectively. SVAR Estimates Sample: 1980 2019 Included observations: 40 Estimation method: Maximum likelihood via Newton-Raphson (analytic derivatives) Convergence achieved after nine iterations SVAR is just identified Coefficient

Std. Error

z-Statistic

Prob.

a1 a2 a3 a4 a5 a6

0.02 −0.43 0.09 0.16 −0.38 0.05

0.002 0.783 0.010 0.392 0.078 0.005

8.94 −0.54 8.94 0.42 −4.86 8.94

0.0000 0.5844 0.0000 0.6695 0.0000 0.0000

Log likelihood

200.8512

Estimated A matrix: 1.000000 −0.428326 0.167370 Estimated B matrix: 0.019693 0.000000 0.000000 Estimated S matrix: 0.019693 0.008435 −5.86E-05 Estimated F matrix: 4.078411 19.21355 13.48052

0.000000 1.000000 −0.383809

0.000000 0.000000 1.000000

0.000000 0.097540 0.000000

0.000000 0.000000 0.048650

0.000000 0.097540 0.037437

0.000000 0.000000 0.048650

2.244594 12.09381 8.372779

−1.605595 −7.820508 −5.268657

KSA

Source: The standard errors are obtained using 1,000 Monte Carlo repetitions.

The Oil Dependency Dilemma 67

Figure 3.3.4 Impulse Response Functions

68

The Oil Dependency Dilemma

The SVAR for Saudi Arabia is estimated in log-differences from 1970 to 2019. The number of lags = 1. All roots are on the unit circle; hence, the system is stable. The chi-squared P-value for the null hypothesis that there is no serial correlation at lag 1 is 0.03035. The P-value of the joint chi-squared test for the null hypothesis of homoscedasticity (in levels) is rather small (0.0276). For the squares, e12, e22 , e33 , e22 e12 , e32 e12 , and e32 e22 the null cannot be rejected with large P-values, 0.0403, 0.0421, 0.1012, 0.2134, 0.4725, and 0.0587, respectively. There is no strong evidence of heteroscedasticity. SVAR Estimates Sample (adjusted): 1972 2019 Included observations: 48 after adjustments Estimation method: Maximum likelihood via Newton-Raphson (analytic derivatives) Convergence achieved after nine iterations SVAR is just identified Coefficient

Std. Error

z-Statistic

Prob.

a1 a2 a3 a4 a5 a6

0.02 −2.34 0.12 −0.19 −0.54 0.02

0.002 0.83 0.012 0.151 0.024 0.002

9.79 −2.80 9.79 −1.28 −22.38 9.797

0.0000 0.0051 0.0000 0.1997 0.0000 0.0000

Log likelihood

272.1843

Estimated A matrix: 1.000000 −2.349753 −0.194459 Estimated B matrix: 0.020512 0.000000 0.000000 Estimated S matrix: 0.020512 0.048199 0.030102 Estimated F matrix: 0.031209 0.134882 0.098059

0.000000 1.000000 −0.541785

0.000000 0.000000 1.000000

0.000000 0.119136 0.000000

0.000000 0.000000 0.019978

0.000000 0.119136 0.064546

0.000000 0.000000 0.019978

−0.007033 0.080773 0.041561

−0.005644 0.005279 0.030052

UAE

Source: The standard errors are obtained using 1,000 Monte Carlo repetitions.

The Oil Dependency Dilemma 69

Figure 3.3.5 Impulse Response Functions

70

The Oil Dependency Dilemma

The SVAR for UAE is estimated in log-levels from 1970 to 2019. The number of lags = 1. All roots are on the unit circle; hence, the system is stable. The chisquare P-value for the null hypothesis that there is no serial correlation at lag 1 is 0.1636 The P-value of the joint chi-square test for the null hypothesis of homoscedasticity (in levels) is rather small (0.0106). For the squares, e12 , e22 , e33 , e22 e12, e32 e12, and e32 e22 the null cannot be rejected with large P-values, 0.0056, 0.1221, 0.2406, 0.1283, 0.0637, and 0.2760, respectively. There is no strong evidence of heteroscedasticity. SVAR Estimates Sample (adjusted): 1972 2019 Included observations: 48 after adjustments Estimation method: Maximum likelihood via Newton-Raphson (analytic derivatives) Convergence achieved after ten iterations SVAR is just identified Coefficient

Std. Error

z-Statistic

Prob.

a1 a2 a3 a4 a5 a6

0.02 −1.63 0.06 0.10 −0.12 0.06

0.002 0.433 0.006 0.540 0.158 0.006

9.79 −3.77 9.79 0.19 −0.76 9.79

0.0000 0.0002 0.0000 0.8432 0.4435 0.0000

Log likelihood

245.5019

Estimated A matrix: 1.000000 −1.636596 0.106973 Estimated B matrix: 0.020504 0.000000 0.000000 Estimated S matrix: 0.020504 0.033557 0.001875 Estimated F matrix: 0.031213 0.076286 0.056159

0.000000 1.000000 −0.121245

0.000000 0.000000 1.000000

0.000000 0.061543 0.000000

0.000000 0.000000 0.067456

0.000000 0.061543 0.007462

0.000000 0.000000 0.067456

0.002939 0.075731 0.013803

−0.009776 −0.029157 0.066510

The Oil Dependency Dilemma 71

Notes 1 The share of labor could be measured directly from SNA data (National Account) the ratio of total compensations to employee – GDP and the share of capital is gross operating surplus – GDP. 2 The bandwidth parameter is l for the kernel-based estimators of f0, which is the NeweyWest (1994). They use AR1. So we choose the lag length p to minimize these criteria

l l    2k / T ); the SIC 2  T   kln T  / T ; HQ 2  T   2kln  ln T  / T .  The modifications add τ to every k and    2 yt21 /  2 . l T

AIC – 2 



t

3 Unlike all other tests for unit root, the KPSS test’s null hypothesis is I(0), not I(1); therefore, we cannot compare the power of the test to others. 4 The GMM estimator minimizes S( ˜ ) = (

N

N

˙ Z ˝° (˜ ))˝W (˙ Z ˝° (˜ )) = g (˜ )˝Wg(˜ ) i

i

i=1

i=1

with respect to the coefficients matrix β for a chosen pxp weighting matrix W, where

˜ i ( ° ) = (Yi − f ( X it , ° )) ; g( ˜ ) =

N

˙ i=1

gi ( ˜ ) =

N

˙ Z ˝° (˜ ) i

i=1

and Z is a Ti xp matrix

of instruments. 5 Stochastic projections are usually considered a remedy to the Lucas critique.

4

The External Debt

Blessed are the young for they shall inherit the national debt

Herbert Hoover

Abstract Historically, the GCC governments have not resorted to debt financing. The 2014 oil price shock caused a budget and current account deficits. They decided to borrow in the international capital market. Bahrain and Oman lead the rest in debt. We derive a sustainable debt measure assuming a target debt – GDP ratio of 30 percent. Then we make dynamic stochastic projections over the period 2020 to 2030. The average ± upper and lower estimate, over the next decade, Bahrain’s fiscal adjustment to achieve the target requires a reduction in the primary balance of about 1.4 < 5.5 < 12.4 billion USD. For Oman, the average adjustment is about double, 0.5 < 10.6 < 34 billion USD.

The Debt Stylized Facts The raw data we presented in previous chapters clearly show that the GCC countries are oil dependent. They also show that the volatility of the price of oil has already spilled into the economy whereby macroeconomic variables fluctuate very closely with oil prices. High (low) oil prices are associated with economic expansions (contractions) and higher (lower) oil revenues with lower (higher) external debts. In states of the world with an expected zero carbon, and with uncertain pandemics, we should anticipate the GCC governments to face lower oil prices, have lower oil revenues, and more external debts, unless some policy and institutional changes take place sooner. Here, we emphasize paying the external debt sooner and increasing private savings for future capital, investments, and growth. Increasing the external debt, conversely, reduces the welfare of future generations. The constancy of the government’s intertemporal budget constraint must be maintained, and that involves hard decisions to be made today. Table 4.1 shows that Bahrain, Oman, and Qatar borrowed the most after the 2014 negative oil price shock. In 2019, Bahrain’s debt – GDP level was 103.36 percent, Oman 63 percent, and Qatar 56 percent. The IMF predictions of the DOI: 10.4324/9781003288282-4

The External Debt 73 Table 4.1 Average Gross Debt – GDP 1990–2013

Bahrain Kuwait Oman Qatar KSA UAE GCC

2014–2019

2020

Mean

Std. Dev.

Mean

Std. Dev.

Change

20.94 40.61 19.15 38.34 51.75 9.35 31.18

10.56 40.78 11.11 20.03 35.12 7.05 28.23

79.77 10.87 35.96 43.57 13.23 20.00 33.90

21.41 6.38 22.51 11.44 8.14 4.51 27.38

58.83 −29.74 16.80 5.23 −38.52 10.65 2.72

128.28 19.26 81.53 68.06 33.42 36.93 61.25

Source: IMF, WEO, October 2020

debt – GDP levels in 2020 are 128, 81, and 68 percent for Bahrain, Oman, and Qatar, respectively. The expected decline in global oil demand because of climate change, the rise in alternative energy demand, and pandemics are expected to increase debt in the future because they would reduce oil revenues and increase the fiscal deficits. Figure 4.1 is a scatter plot showing the negative correlation between the debt – GDP and the primary fiscal balance – GDP ratios. The GCC countries did not borrow when the price of oil was 100 USD or more. The GCC governments resorted to external borrowing to finance fiscal deficits in the aftermath of the 2014 oil price shock, albeit at different levels, with Bahrain and Oman leading the pack in debts. Predictably, both are smaller producers and more oil dependent. Qatar’s fiscal balance and the current account balance are positive. Why would Qatar borrow if the books were not in deficit? We speculate that Qatar borrowed more because of the FIFA World Cup constructions, which she is hosting in 2022. We do not have data for Qatar to examine anyways. Therefore, our sustainable debt analysis will be confined to Bahrain and Oman only. Mirzoev et al. (2020) is an IMF paper. It discusses the future and fiscal sustainability in the GCC region. They presented a number of simulated scenarios, whereby at the current fiscal stance, the region could exhaust its financial wealth in the next 15 years. Holding the current levels of expenditure and non-hydrocarbon revenue constant, projections show a “steady widening of fiscal deficits and a corresponding erosion of the region’s financial wealth at an accelerating pace.” They argued that the region’s current aggregate net financial wealth of approximately 2 trillion USD would turn negative by 2034 as the region becomes a net borrower. Total non-oil wealth would be depleted within another decade; however, it would decrease faster in the alternative scenarios of faster improvement in energy efficiency and introduction of a carbon tax. The timing varies across countries because of differences in their initial conditions. For example, Bahrain and Oman are most vulnerable to this downturn, while Kuwait’s large Sovereign Wealth Fund (SWF) will help keep its net financial wealth positive until about 2052.

74

The External Debt

Figure 4.1 The External Debt (Debt – GDP) and the Primary Balance (PB – GDP) Negatively Correlated

The External Debt 75

Economic Theories The Keynesian Narrative The GCC debt is almost entirely external. It is not a result of declining tax revenues per se, as is usually the case in developed countries because revenues are mostly generated by exporting oil and gas. There are two debt narratives in the economic literature, with limited empirical evidence. One is the Keynesian narrative, and the second is the Ricardian Equivalence. In the typical Keynesian model, when government expenditures exceed tax revenues, thus deficit, the government finances the budget deficit by issuing debt of an equal amount. The assumption here is that the reduction in tax revenues is temporary because (1) the government cannot borrow forever and (2) because tax policy changes when governments change over time. It seems that neither assumption holds for the GCC. Debt affects gross savings (household and government) and capital, which then affects output and factor prices. In theory, it is assumed that the government budget constraint is constant – i.e., holds in the long run; therefore, future taxes will have to increase to satisfy the budget constraint in the long run.1 In other words, the Keynesian theory assumes that debt affects the economy in the short run only. Note that the literature has no credible and careful empirical evidence that debt has real effects. To illustrate this point, we test, for example, the significance of a simple correlation between debt and some real variables in the United States in Appendix 4.1. We find no significant relationships between debt, consumption, and real GDP per capita in the United States to warrant further investigations; however, the plots indicate that running regressions will not reveal anything significant. There is a fundamental difference between the textbook assumption and the situations of the GCC countries in general. First, for the GCC, especially in the case of Oman, the existing fiscal deficit was a result of a sudden significant drop in oil prices in 2014, which reduced revenues. The debt is not a result of a reduction in tax revenues because taxes play an insignificant role in financing the budget deficit in GCC. Second, it is because most of the debt is external. However, the reduction in oil prices or the share of oil in output may not be a temporary shock. Oil price shocks, climate shocks, the evolution of alternative energy markets, and future pandemics shocks such as COVOD-19 are persistent shocks. In Keynesian reasoning, the reduction in taxes increases household disposable income and private wealth. Therefore, private consumption increases, which increases aggregate demand. The increase in aggregate demand increases real national income over the business cycle, which is based either on the assumption of sticky wages or a misperception mechanism (see Elmendorf and Mankiw, 1999).2 Therefore, the Keynesian narrative does not fit the GCC’s current situation because the deficit and the subsequent increase in debt are results of an exogenous reduction in oil prices related to the shocks we described earlier, which reduce future revenues and result in budget and current account deficits. As a result, the GCC aggregate demands will fall. Therefore, the GCC countries are expected to experience a slowdown in economic activity over the business cycle.

76

The External Debt

The Ricardian Equivalence Narrative The second narrative about debt is the Ricardian Equivalence theory, whereby the (domestically held) debt does not have a real effect on the economy in the long run – i.e., the debt is neutral. In other words, there is no correlation between privately held debt and real consumption growth, no correlation between privately held real GDP growth and real interest rate. A reduction in the tax rate today without a change in spending (or only a small reduction in spending) results in a budget deficit. Expectations are rational in the sense that people use all available information to predict the future. You could think of running a regression, where the information set of the explanatory variables includes all available information up to the present time and then make a forecast. The lower tax level (i.e., tax rate) today implies that people anticipate a higher tax level tomorrow because the government wants to maintain the intertemporal budget constraint – i.e., keep the budget constraint unchanged over time. Under the Permanent Income Hypothesis, people do not increase current consumption unless they expect an increase in future (expected) income. Thus, today’s tax cut is a windfall (i.e., temporary increase in income – transitory income). Presumably, they save it (or most of it) in order to pay for future (anticipated) taxes. Therefore, current consumption does not increase and aggregate income remains unchanged. If people, however, anticipate an increase in the future after-tax real income, they would increase their current consumption. It is unclear how the Ricardian story applies to the GCC. However, the share of oil in output in the GCC countries is akin to the marginal income tax rate. Furthermore, there is no exact definition of a “sustainable fiscal position.” The idea of debt sustainability requires having a view – i.e., projections — of the evolution of the debt-financed fiscal balance over time. External debt is also more of a concern than the debt held by the residents, which requires information about the real exchange rate depreciation rate, and net foreign investments are important. Some argue that a debt- GDP ratio of 60 percent is also sustainable, while others suggested 100 percent is still sustainable. See Roubini (2001) for an example.3

Computing the Fiscal Adjustment Needed to Achieve a Sustainable Debt Target The first objective in this chapter is to estimate the fiscal adjustment required to keep a particular “sustainable” debt target, i.e., the percentage change in the primary fiscal balance-to-GDP ratio. Like Roubini (2001), there is no evidence of what level of debt could be considered sustainable. It will be assumed that the average debt – GDP level for the period 1990 to 2013 (the level before the last oil price shock in 2014) is the debt – GDP level every GCC country is happy to have in the future. The fiscal adjustment that is required to achieve a particular debt – GDP target by 2030 is estimated, given the debt – GDP ratio in 2019. Our analysis follows Creedy and Scobie (2015), which is consistent with the European Union (EU) Commission’s approach to debt analysis. See the Technical Appendix 3.2. This approach involves assumptions about a few key variables, such as the initial debt – GDP ratio, the target debt – GDP ratio, the discount rate, and the sum of the discounted expected primary fiscal balance-to-GDP ratio.

The External Debt 77 However, no policy feedback effect is considered because it is difficult to assess the extent and effectiveness of policy reforms in the GCC countries. The GCC governments do not publish detailed fiscal data, and they are not readily available for researchers even if requested. In other words, changes in spending, taxes, or even productivity and risk premium are not considered in this analysis. Such feedback, if assumed, and if the policies and the measures taken by the authority were effective, could reduce the size of the fiscal adjustment. The IMF World Economic Outlook projections might include assumptions about fiscal policy reforms. Here is a description of the model. The solution of the model presented in the appendix gives an equation for PBT* – the changes in revenues, expenditures, or both, that is required to achieve the debt target: PBT* =

r~

(1+ r~ )T

T -1 [ J T i |D~ 0 (1+ r~ ) - D~ T* - PBT - i (1+ r~ ) | -1 |L |] i=0 ,

E

(4.1)

where PBT* is the annual adjustment in the primary fiscal balance – i.e., revenues, expenditures, or both – that are required to achieve a debt – GDP target by the final D projection year. The debt target, which is quite arbitrary, is D~ T* . D~ 0 = 0 , the initial Y0 debt – GDP ratio; the discount rate r~ is typically defined such that 1+ r~ = 1 + g / 1+ r . Essentially, r~ is approximately equal to the difference between the interest rate and real GDP growth rates. The variables required to compute (4.1) are the discount rate, the projections of the primary fiscal balance from 2020 to 2030, the initial debt – GDP level in 2019, and the debt – GDP target. The discount rate, as defined by the difference between the interest rate and real GDP growth rates, is not so straightforward in the case of the GCC countries. The interest rate moves closely with the U.S. interest rate because of the exchange rate peg to the USD. Although the U.S. interest rate might remain low for some time because of the COVID-19 slump, the GCC indebted countries are charged over 6 percent for their external borrowing, and they are expected to pay high rates if they continue to borrow in the international capital markets. The risk premium increases with the increase in debt. The World Bank and the IMF projections of real GDP growth for GCC countries fall between 2 and 3 percent on average for each of the GCC countries. There are only small variations across countries. Forecasts errors notwithstanding, there is an increasing uncertainty around the projections of the growth rates, especially after COVID-19. It is expected that all posted projections, by the IMF or any other agency, will be revised extensively. The strategy to compute equation (4.1) is to avoid making arbitrary assumptions about the interest rate and the growth rate. Sensitivity analysis implies that equation (4.1) is computed using a number of “assumed” different discount rate scenarios. It is assumed that 3 percent is the lower bound, and 9 percent is an upper bound, thus 6 percent would be the average discount rate. Hence, we will have three estimates, one for each interest rate. The correlation between the cost of borrowing, risk, and debt is positive.4 Clearly, the higher the discount rate is

78

The External Debt

the higher the fiscal adjustment and the lower the debt – GDP target is the higher T 1 the required adjustment. Our approach is forward-looking. PBT  i in equation (4.1) with T = 2030 –

 i0

i.e., the sum of the primary balance is the forward dynamic stochastic projections estimated using a standard (unrestricted) VAR. There are significant uncertainties about the projections of the primary fiscal balance. To do so, we estimate the VAR, solve it (the method of solving the system is described in the appendix in the previous chapter), and then make dynamic stochastic projections from 2020 to 2030. Then these projections are used to compute a number of scenarios of primary fiscal balance – GDP to achieve particular debt – GDP targets. Uncertainty is high because oil prices are highly volatile. The innovations ±2σ (two standard errors) of the projections are reported, which provide an upper and lower band around the mean projection of the primary balance. The uncertainty could also arise from the debt – GDP target. A much larger fiscal adjustment would be required to achieve a debt – GDP target lower than 30 percent and a higher initial debt – GDP ratio than the current one. For example, if our sample includes 2020 and the debt – GDP ratio is significantly higher than it was in 2019, the fiscal adjustment would be higher. There are three GCC countries with relatively higher debt – GDP ratios in 2019: Bahrain (about 100 percent) Oman (about 80 percent), and Qatar (about 60 percent). However, Qatar is the only GCC country with a positive primary fiscal balance. Kuwait, Saudi Arabia, and the UAE have relatively smaller debt – GDP ratios. These levels represent the initial debt – GDP levels. For the debt target, the average GCC debt – GDP ratio from 1990 to 2013 (i.e., prior to the 2014 oil price shock) is assumed to be 30 percent. The analysis, therefore, focuses on Bahrain and Oman only because they have high debt – GDP ratios. For these two countries, an unrestricted VAR is estimated from 1990 to 2019 first. These VARs provide a summary of the dynamics of the data and were described earlier. Next, we estimate the VAR for Bahrain. Bahrain The task is to make projections of the primary fiscal balance in order to compute the fiscal adjustments PBt* . To compute the primary fiscal adjustments for Bahrain, a sample from 1989 to 2019 is used to estimate the VAR. The output of the VARs is large; therefore, the statistics are not reported here; however, the output is available upon request. The following steps are in order. First, the variables for Bahrain are plotted in Figure 4.2. Second, before we estimate the VAR, every variable is tested for unit root using the ADF test with various lag structures (using five different Information Criteria as described earlier in Chapter 2) and different specifications for the unit root regressions (no trend, trend, and constant term). As we said before, the ADF test is weak against stationary alternatives when it fails to reject the null hypothesis of the unit root. For robustness, we test for trend and the unit root using the same commonly used tests used earlier (e.g., the ADF, Phillips-Perron, ERS-ADF-GLS, Ng-Perron); the null hypothesis of the unit root in the log price of oil, log real

The External Debt 79

Figure 4.2 Bahrain – (1990–2019) Source: All the data of Bahrain are from the IMF – WEO, October 2020. The long-run U.S. interest rate is from OECD Statistics, deflated by the CPI index from the IMF – WEO, October 2020. The price of oil is from the IMF – WEO, October 2020.

GDP, and real debt – GDP could not be rejected. Note again that the non-rejection may well be due to the weakness of these tests. However, the hypothesis that the long-term real interest rate and the primary fiscal balance – GDP ratio have unit roots is rejected at the 1 and the 10 percent level, respectively.5 Third, these unit root variables are cointegrated. The residual-based Johansen multivariate test rejects the null hypothesis of “no cointegration” in favor of the alternative of more than one cointegrating vector. Therefore, fourth, an unrestricted VAR, in levels, is estimated, whereby the lag length using five different Information Criteria is tested. The U.S. real interest rate is available only from 1991; the optimal lag length is found to be between one and three lags. A VAR with one lag is fitted because the sample is small. A VAR with more than one lag causes great variability in the impulse response functions. The VAR is similar to the one we estimated earlier; however, it includes these five variables

The External Debt

80

P



; rt , Yt , PBt , Dt in this order. PtO is the log of the real price of oil, which is the IMF’s average price of Dubai, Brent, and WTI. rt is the long-term real interest rate measured by the long-term nominal interest rate minus lagged U.S. CPI inflation. Yt is real GDP. PBt is the primary balance – GDP ratio and Dt is the debt – GDP ratio. Fifth, the residuals of the VAR are tested using a number of tests for serial correlation at various lags. The residuals are found to be statistically serially uncorrelated up to the third lag.6 The final step involves making dynamic stochastic projections of the primary fiscal balances–GDP ratio up to the year 2030 in order to compute the fiscal adjustments needed to maintain a 30 percent debt – GDP target, which is the primary objective here in order to calculate the fiscal adjustments required to achieve the debt – GDP target. The model is solved (see the earlier description of the solver) over the period of 2020–2030, and the innovations are generated using 1,000 iterations of Bootstrapping; hence, we have ten-year dynamic stochastic projections. Figure 4.3 plots the mean dynamic stochastic projections of the primary fiscal balance – GDP ratio from 2020 to 2030. Note that there is a very large standard error surrounding the projections as we explained earlier. The same system is estimated for Oman next. t

O

Oman A VAR with the same variables we used in the case of Bahrain is estimated for Oman. Figure 4.4 plots the data used in the VAR. The VAR is estimated for the

Figure 4.3 VAR Mean Dynamic Stochastic Projections of the Primary Balance – GDP Bahrain Source: The SVAR gives exactly the same results, hence not plotted

The External Debt 81

Figure 4.4 Oman – (1990–2019) Source: All the data of Oman are from the IMF – WEO, October 2020. The long-run U.S. interest rate is from OECD Statistics, deflated by the CPI index from the IMF – WEO, October 2020. The price of oil is from the IMF – WEO, October 2020.

period 1990–2019, and the exact diagnosis and procedures that were used in the case of Bahrain are repeated here. The VAR mean dynamic stochastic projections of the primary balance – GDP from 2020 to 2030 are plotted in Figure 4.5. The uncertainty around Oman’s estimates (the standard errors) is higher than Bahrain’s. Oman is highly dependent on oil. Second, for the debt – GDP ratio, the generalized impulse response functions are significant except for the response to the U.S. long-term real interest rate. As expected, a positive shock to the real price of oil reduces the debt – GDP ratio because revenues increase with oil prices. The ratio declines in response to a positive shock to the primary fiscal balance, but it increases in response to a positive shock to real GDP, which is the opposite of the response we observed in the case of Bahrain. Table 4.2 reports the primary fiscal adjustments for Bahrain and Oman in local currencies and in USD. The table is organized into three blocks, where each block

82

The External Debt

Figure 4.5 VAR Mean Dynamic Stochastic Projections of the Primary Balance – GDP Oman

has three rows. Each row reports the elements of equation (4.1) – i.e., the value of the initial debt to GDP, the debt – GDP target, the interest rate, and the discounted sum of the projections of the primary fiscal balance from 2020 to 2030. Because the projections of the primary fiscal balance are surrounded by large standard errors, we report the upper standard error and the lower standard error in two additional rows. Hence, we have three values, the mean, and the upper and lower values. This same pattern is repeated because we assumed three different interest rates, 3, 6, and 9 percent. Therefore, we report nine different scenarios of fiscal adjustments. On average over the period 2020 to 2030, Bahrain’s fiscal adjustment to achieve a debt – GDP target of 30 percent involves a reduction in the primary balance of about 5.54 billion USD. For Oman, the average adjustment is much higher, about double that of Bahrain at 10.61 billion USD. These fiscal adjustments are 13 and 17 percent of GDP for Bahrain and Oman, respectively. We also report the uncertainty, the upper, and lower bounds of the VAR estimates. These estimates vary with the interest rates. For Bahrain, the primary fiscal adjustment could be as high as 12 billion USD (when the interest rate is 9 percent) and as low as 1.4 billion (when the interest rate is 3 percent), so the estimates vary with the interest rate scenarios. For Oman, the primary fiscal adjustments could be as high as 34 billion USD and as low as half a billion; therefore, there is more uncertainty in Oman than Bahrain because Oman produces more oil and is more oil dependent than Bahrain. One can imagine the rise in the primary fiscal adjustment and the uncertainty around it if Bahrain and Oman want to make the target debt – GDP ratio zero. It would be significantly more costly.

Table 4.2 The Fiscal Adjustments Needed for Debt – GDP Target PBT* =

r

(1 + r )T

T −1 ˆ  i ˘ D 0 (1 + r )T − D T* − PBT −i (1 + r )   −1 ˘ˇ i=0 



Bahrain

Oman

Fiscal Adjustments T −1

D 0

D T*

1.00 1.00 1.00

T −1

LCU

USD

˛ PB

−0.04 −0.07 −0.01

0.06 0.09 0.03

0.97 1.45 0.54

2.6 3.9 1.4

Mean i+2 i−2

−0.08 −0.14 −0.03

0.13 0.19 0.08

2.03 2.97 1.18

Mean i+2 i−2

−0.12 −0.21 −0.04

0.20 0.29 0.12 0.13

3.17 4.56 1.93 2.09

D 0 (1 + r )

0.30 0.30 0.30

0.03 0.03 0.03

0.03 0.03 0.03

1.19 1.19 1.19

Mean i+2 i−2

1.00 1.00 1.00

0.30 0.30 0.30

0.06 0.06 0.06

0.04 0.04 0.04

1.42 1.42 1.42

1.00 1.00 1.00

0.30 0.30 0.30

0.09 0.09 0.09

0.06 0.06 0.06

1.68 1.68 1.68

T

PBT −i (1 + r )i

i=0

i

T −i (1 + r )

PB*

LCU

USD

−0.04 −0.16 0.01

0.06 0.18 0.01

1.43 4.33 0.21

3.72 11.2 0.55

5.4 7.9 3.1

−0.08 −0.32 0.03

0.13 0.37 0.02

2.93 8.65 0.58

7.62 22.5 1.50

8.4 12.1 5.1 5.5

−0.11 −0.48 0.03

0.19 0.56 0.05 0.17

4.51 13.0 1.11 4.09

11.7 33.8 2.87 10.6

i=0

i denotes innovations; 2σ is two standard errors; D 0 is the initial debt – GDP ratio in 2019; D T* is the debt – GDP target; r is the discount rate; PBT* is the target primary balance – GDP (%). The fiscal adjustments are in billion. LCU is billions of local currency units. USD is billions US dollars.

The External Debt 83

PB*

˛

r

r (1+r)T − 1

84

The External Debt

Appendix 4.1: U.S. Debt Uncorrelated With Real Macroeconomic Variables There is no correlation between privately held public debt and the real economy. The correlation between the growth rates of real privately held public debt in the United States and real consumption is zero. Figure 4.1.1 plots the data and Figure 4.1.2 is a chi-squared test for the correlation. Figure 4.1.3 plots the real privately held public debt growth rate and the real GDP per hour growth rates. Figure 4.1.4 is a chi-squared test for the correlation.  



Real value of privately held gross federal debt is the market value deflated by the GDP implicit price deflator (1950–2020). Source: Federal Reserve Bank of St. Louis – FRED Labor productivity is real GDP measured by the output-side real GDP at chained purchasing power parity (PPP) (in millions 2017 USD) divided by either population or divided average annual hours worked by persons engaged. Source: World Penn Table 10.0 Real consumption at constant 2017 national prices (in millions 2017 USD). Source: Penn World Table 10.0

Technical Appendix 4.2: Sustainable Debt The long-run government budget constraint under solvency is from Creedy and Scobie (2015): D0 −

t

 ( R − G ) ˙ 1 ˘ = 0, t t ˇ  t=1 ˆ 1+ r 

(4.2.1)

where D0 is the initial debt; Rt is total government revenues. The sources of revenues in Oman are oil, indirect taxes, and corporate taxes. Gt is total government expenditures. The interest rate is 1+r (e.g., 1.05). This long-term interest rate is the world interest rate 1+ r* + a risk premium. All variables are expressed in constant prices. Rewrite the previous equation in terms of ratios to GDP: D0 − Y0

t

 ° Rt − Gt ˙ ° 1+ g ˙ = 0, ˝ ˇ˝ ˇ t=1 ˛ Yt ˆ ˛ 1+ r ˆ

(4.2.2)

where Y is GDP, and g is the growth rate of real GDP. This condition is the strong form budget constraint and usually does not hold in real scenarios. It requires a significant increase in revenues, or significant reduction in expenditures, or both.

The External Debt 85

Figure 4.1.1 U.S. Privately Held Real Public Debt and Real Consumption Growth Rates Annual Data 1950–2020

86

The External Debt

Figure 4.1.2 Confidence Ellipse (95% Chi-Squared) Consumption and Debt Uncorrelated

Figure 4.1.3 U.S. Privately Held Real Public Debt and Real GDP per Hour Annual Data 1950–2020

The External Debt 87

Figure 4.1.4 Confidence Ellipse (95% Chi-Squared) Real GDP per Hour and Debt Insignificant Negative Correlation Source: There is a negative correlation −0.30; it is statistically insignificant

Call the budgetary improvements or adjustments PBt* – i.e., the primary balance (revenues less expenditure adjusted for interest payments); hence, *

*

˙ ° 1+ g ˙t ˇˇ ˝ ˇ = 0, ˆ ˛ 1+ r ˆ

D0 − Y0

° R −G R −G t=1 ˝˝˛ t Yt t − t Yt t

D 0 −

 ˙ ˘ ( PB − PB ) = 0, t=1 ˝ 1+ r ˇ

(4.2.3)

or ˛ 1 ˆ

t

* t

(4.2.4)

D where D 0 = 0 ; the discount rate r is defined such that 1+ r = 1 + g/ 1+ r. EssenY0 tially, r is approximately equal to the difference between the interest rate and real GDP growth rates. PBt =

Rt − Gt R* − Gt* ; and PBt* = t . We solve for PBt*, Yt Yt

88

The External Debt ˝ PBt* = r ˆ D 0 − ˆ ˙

ˇ

t

 ˝ 1 ˇ PB  . t ˆ  t=1  ˙ 1+ r ˘

(4.2.5)

˘

The equation is similar to the EU Commission measure S2 and required very long projections of PSt, as PSt ˜ 0, European Commission (2006). To manage this problem, the EU Commission (2006) assumes a terminal period; thus,

(

D 0 − PB0 − PBt*

 ˙ 1 ˘ −  ˙ 1 ˘ PB ) t=1 ˇ   t=1 ˇˆ 1+ r  ˆ 1+ r 

t

= 0.

(4.2.6)

Solving yields:   0 − PB0 − r PBt* = rD

˝ 1 ˇ

 ˆ  PB t=1 ˙ 1+ r ˘

(4.2.7)

t

To avoid the infinite projection requirement, assume a debt target such that the budget is T

DT = D0 (1+ r ) +

ˆTi=0−1 ( R

− GT −i ) (1+ r ) .

(4.2.8)

ˆTi=0−1PB

(1+ r )i .

(4.2.9)

T −i

i

In terms of ratios, T D T = D 0 (1+ r ) −

T −i

To achieve the debt target, the fiscal authority chooses PB*T such that T D T = D 0 (1+ r ) −

ˆTi=0−1( PB

T −i

i

− PBT* ) (1+ r ) .

(4.2.10)

Notes 1 This is the intertemporal budget constraint. 2 When prices are sticky, an increase in income without an immediate jump in the price level increases real income in the short run until prices adjust. In Lucas and Barro’s model, economic agents increase their output or labor supply in the short run because they misinterpret the shock, and once they realize their mistake, that their real income has not increased, they reduce output and labor supply, and the aggregate demand returns to its equilibrium level before the shock. 3 A stronger sustainability or solvency criterion is that the debt-to-GDP ratio or the debtto-total exports ratio should not be allowed to increase over time. It is unclear which debt indicator (ratio) is the appropriate yardstick. The choice of an indicator is not straightforward and depends on the country’s economic structure. A country could be solvent using

The External Debt 89 one ratio and insolvent using the other. Argentina is a classic example of debt; its debt to GDP was 50 percent, and its debt to exports ratio was 400 percent. 4 Ostry et al. (2010) shows that the cost of borrowing increases with debt. Risk premium slowly increases for a small debt-to-GDP ratio and increases rapidly if the ratio exceeds 1.5 (150 percent of GDP). 5 The power of the ADF test (or any test) is not an issue when the test rejects the null hypothesis of unit root. 6 The order of the variables does not seem to matter. We tested different orders and found that the standard Choleski impulse response functions to be the same. Further, Koop et al. (1996) and Isakin and Ngo (2020) show that when models are linear, traditional impulse response functions (IRFs) and variance decomposition. We do not report the impulse response functions because they are not the primary objective of this analysis; however, the generalized impulse response functions (Pesaran and Yongcheol, 1998), indicate expected responses. The main interest is in the response of the debt – GDP ratio to the other four variables in the VAR. The response is negative to a positive real oil price shock, positive to real interest shock, negative to real GDP shock, and negative to a positive fiscal balance shock. These responses are sensible, and they are statistically significant.

5

Is the Level of Government Spending Optimal?

Increased government spending can provide a temporary stimulus to demand and output but in the longer run higher levels of government spending crowd out private investment or require higher taxes that weaken growth by reducing incentives to save, invest, innovate, and work. Martin Feldstein

Abstract Government expenditures have secular trend. The growth rates are highly correlated with the growth in oil prices. GCC governments played a central role in economic development; they paid for health, education, defense, and the entire infrastructure and social welfare using oil revenues, and without incurring significant debt. However, the future will be unlike the past. Oil revenues will shrink as the world moves into a non-hydrocarbon state at some point in time; when alternative energy becomes affordable; when unexpected future pandemics adversely affect global demand and supply; which will reduce the expected average price of oil. We find the levels of government spending in the GCC to exceed the estimated optimal levels over the period 1989–2019. The data we presented so far suggest that the GCC governments did not borrow externally when they ran budget and current account surpluses. Therefore, we examine government spending in more detail. Theoretically, government spending (which includes consumption and investments) in developing countries in particular, affects real GDP per person growth directly via its effect on infrastructure, education, health, and R&D, which are financed by direct public spending. This is consistent with endogenous growth models. The GCC countries spend a significant amount of money on free education, free health, and infrastructures, such as water, power, water desalinating, roads, transportation, Internet. Although we do not have data to show, there must have been some positive effects of such spending on technical progress; it would be a good research question. Barro (1989, 1990), Armey (1995), Rahn and Fox (1996), and Scully (1994) – hence BARS – estimated an inverted U shape curve to explain the relationship between optimal economic growth and government spending. It is a simple empirical method, which could be useful for policymakers. The BARS curve is depicted in Sketch (5.1). DOI: 10.4324/9781003288282-5

Is the Level of Spending Optimal? 91

Figure Sketch 5.1 BARS Curve

The effect of government expenditures on growth and productivity is non-monotonic. Essentially, the BARS curve illustrates that at a low level of government expenditures, economic growth would be low because the government could not protect property rights, provide law and order, and develop infrastructures, research, education, and health necessary for growth. Further, the increase in government expenditures could boost the marginal productivity of capital. It could also induce technical progress via positive effects of government investments in education and human capital, health, infrastructure, and R&D. Thus, government expenditures and growth are positively correlated. Similarly, a high level of expenditures would crowd out private investments necessary for economic growth, even though there is no evidence for crowding out in GCC countries. However, in the GCC countries, the levels of government expenditures and private investments are highly (positively) correlated, and both are driven by oil prices, as we have shown earlier. The share of private investments, which are a private gross-fixed capital formation, published by the IMF, in total is quite large in the GCC countries. On average from 1990 to 2017, the shares are 0.77, 0.70, 0.66, and 0.58 in Bahrain, Kuwait, Saudi Arabia, and the UAE, respectively. The share in Oman is 0.44, relatively smaller, and the correlation with government expenditures is relatively less significant too. The correlations between growth rates of private investments and government expenditures are insignificant. The IMF does not report the data for Qatar. Appendix 4.1 includes some plots and tests of the data. There is an alternative way to answer the question about optimal government spending. The GCC countries are non-industrial economies. As we showed earlier, the shares of manufacturing and agricultural productions in GDP are small. Historically, the GCC countries have been mercantile societies with large services sectors. Imports licenses are exclusive rights; the governments granted them to certain prominent families and individuals. They import most of the goods including, most

92

Is the Level of Spending Optimal?

importantly, the government’s needed capital goods. This model affects the trade account and the current account directly. When the price of oil is high and covers the breakeven price, the current account is positive and not affected by imports. However, when the oil price falls, oil export revenues decline too, if imports remain high, the trade account, but mostly the current account, slips into a deficit. Persistent current account imbalances are destabilizing under a fixed exchange rate regime like the ones in the GCC countries. The decline in foreign reserves because of the declining price of oil threatens the exchange rate peg. This was the experience of the developed countries, which pegged to the USD in the past – i.e., the Bretton Woods and later the European Exchange Mechanism in the 1990s. Only countries with massive foreign reserves (USD) such as Kuwait, the UAE, Qatar, and Saudi Arabia could maintain the peg longer under current account deficits. So alternatively, the question could be about the optimal level of government spending that maintains the current account balance. We answer these two questions next. The optimal size of government spending, which is consistent with maximum real GDP per capita growth and the balanced current account is estimated for each country. The estimates of the optimal level of government spending, which maximizes real GDP per capita growth vary across countries, large versus small, developed versus developing, commodity exporters or not, etc. Generally, this literature reports estimates of the optimal government expenditures – GDP ratio between 26 and 47 percent. See, for example, Forte and Magazzino (2010). Next, we provide estimates for the GCC.

The Growth Model A variant of the neoclassical Solow (1956, 1957) growth model is estimated, where the main explanatory variable of real GDP per working-age person (i.e., a proxy for productivity) is the investment – GDP ratio, by including the level of real government expenditures, its square, and the production of oil as additional explanatory variables.1 As explained earlier, there is good economic ground to include government expenditures in a growth model for GCC. Governments finance education, health, infrastructure, electricity, etc., which have a direct impact on economic growth. These channels are consistent with endogenous growth models, whereby government expenditures affect technical progress, which in turn affects real GDP growth per worker. Oil production is another factor of production in the GCC. The original Solow (1956, 1957) model is ˜S ˝ ˜Y ˝    + ln ˛ t ˆ = ln ( A 0 ) + gt ln ˛ t ˆ − ln ( n + g +  ) + t , 1−  ° y t ˙ 1−  ° Nt ˙

(5.1)

where Yt is real GDP; Nt is working-age population (age 15–64); St is nominal saving; yt is nominal GDP; n is the growth rate of Nt; g (g, not to be confused with government expenditures) is the growth rate of technology; δ is the rate of depreciation of the stock of capital; A0 is the exogenous level of the stock of technology. Mankiw et al. (1992) argued that human capital should be an

Is the Level of Spending Optimal? 93 additional regressor in (5.1). Human capital is one type of intangible capital, which affects productivity growth. There is a question of whether the level of human capital or its growth rate has to be in the model. It is plausible to argue that the level of human capital increases growth, while the growth of human capital increases the speed of adjustment of growth from one steady state to another. The regression is as follows: ˜ln

( ) =ˆ Yt Nt

0

+ ˆ1lngt + ˆ 2 lngt2 + ˆ 3 ˜ln

( ) + ˆ ˜ln ( H / N ) It yt

4

t

t

+ ˆ 5 ˜ln((ht / Nt ) + ˇ t

(5.2)

The equation is in log-difference specification. Mankiw et al. (1992) use private investments – GDP ratio instead of the saving – GDP ratio in estimating the Solow model, so we follow them, although the results do not change. Our additional regressors are real government expenditures, gt, its square gt, and hydrocarbon production Ht (i.e., oil production in thousands of barrels/day). The human capital denoted ht is an index), which is based on average years of schooling, reported in the Penn Table (except for Oman, which does not report time series data for human capital and average years of schooling.2 Taking the derivative of real GDP per working-age worker with respect to government expenditures gives

°Y ˙ ˜ln ˝ t ˇ ˛ N t ˆ = 0 =  + 2 lng . 1 2 t ˜lngt

(5.3) −°

Therefore, the average optimal level of government spending is g * is 2° 1 . e 2 Next, we provide some empirical evidence.

The Empirical Results of Estimating the Growth Equation There is an endogeneity problem in the regression equation – i.e. a single-equation bias. To remedy this problem, we estimate the equation using the GMM (Hansen, 1982). The instruments have to be highly correlated with the investments and human capital, but not with the errors; be strictly exogenous; and have some relevance. The life-cycle hypothesis suggests that income and spending – i.e., investments and human capital accumulation – should be highly correlated with the distribution of the population by age. They increase with age, reach the max, and then decline at retirement. For this reason, we use the log-difference levels of population age-distribution 20–24, 25–29 . . . 75–79 years as instruments. The orthogonality condition is tested and could not be rejected. Table 5.1 reports the estimation results for all GCC countries except Qatar because it does not publish investment data. The samples vary across countries. Some countries have missing data, either at the beginning of the sample or at the end of it. Kuwait, for example, has missing data after the first Gulf War period

Table 5.1 GMM Estimates of the Optimal Government Expenditures Level (i)

ˇ ˝ ht  + ˜ 5˛ln ˆ ˘ ˙ Nt

Country

Bahrain

Kuwait

Oman

Sample

1991–2017

2000–2017

1991–2017

ˇ  + ° t (ii) ˘ Qatar (vi)

KSA

UAE

1991–2017

1992–2017

Coefficient P- value Coefficient P- value Coefficient P- value Coefficient P- value Coefficient P- value Coefficient P- value α0 0.04 α1 0.05 α2 –0.04 α3 (iii) 0.10 α4 (iv) – α5 1.07 σ 0.05 J P- value (vii) 4.59

0.0000 0.0003 0.0005 0.0000 – 0.0000 0.7095

–1.03 0.89 –0.18 0.07 (v) 0.70 –0.90 0.05 3.72

0.0004 –0.01 0.0002 0.06 0.0001 –0.02 0.0065 0.04 0.0000 0.75 0.0143 – 0.02 0.7136 4.49

0.1246 0.0004 0.0001 0.0178 0.0000 0.8105

– – – – – – – –

– – – – – – – –

–0.57 0.18 –0.01 0.29 0.06 –0.77 0.01 3.29

0.0001 –2.10 0.0001 0.80 0.0001 –0.08 0.0000 0.25 0.0000 1.04 0.0046 0.48 0.05 0.8566 4.48

0.0631 0.0540 0.0503 0.0051 0.0000 0.0055 0.8764

(i) GMM instruments are the log-differenced distribution of population age 20–24, 25–29 . . . 75–79 from the World Development Indicators. The distribution is consistent with the life-cycle hypothesis, where investments increase from low at the early age, peak up in middle age, and then decline after retirement. The distribution of population is strictly exogenous. The estimated weighting matrix HAC uses Bartlett kernel and Newey-West fixed bandwidth because the sample is small, and we could not search for lags. HAC is heteroscedasticity and autocorrelation consistent estimator of the long-run covariance matrix Zt ut ( ˜ ) , and based on an initial estimate of. Convergence occurred just before 30 iterations. (ii) The model is Solow’s (1956, 1957) growth model (with human capital). Yt is real GDP in LCU (IMF-WEO October 2020); Nt is working-age population (age 15–64) from the World Bank Development indicators; gt is real government expenditures, which is the nominal value reported by the IMF-WEO deflated by the government spending price from the Penn World Table 9.0. I t / yt is investments-nominal GDP ratio. The data are from the IMF-WEO. Qatar does not report investments data, but it does run a budget deficit either. Ht is oil production in billion barrels from BP Statistical Review (2020). Oil production data in Bahrain are unavailable. Human capital index is ht and based on average years of schooling and published by the Penn World Table 9.0. Oman does not have data on average years of schooling; hence, they do not report human capital data. (iii) The regressor is ˜ln

( ). I t−1 yt−1

(iv) BP does not report oil and gas production data for Bahrain. (v) The regressor is ˜ln

( ). I t−1 yt−1

(vi) Qatar does not have investments data; therefore, the model is not estimated. (vii) The standard error of the regression is σ , and J is the Sargan test for H0 : over-identification restrictions are valid.w

Is the Level of Spending Optimal?

˝ Ht ˙ ° It ˙ 2 ˇ =  0 + 1lngt +  2lngt +  3˜ln ˝ ˇ + ˜ 4 ˛ln ˆ ˙ Nt ˆ ˛ yt ˆ

94

°Y ˜ln ˝ t ˛ Nt

Is the Level of Spending Optimal? 95 1992–1994. In addition, the price index that we used to deflate the IMF nominal government expenditures is taken from the Penn World Table 9.0 (PI_g) – the price level of government consumption – is available up to 2017; hence, the regressions are up to the year 2017 only.3 Figure 5.1 plots the actual real GDP per worker growth rates and the fitted values of the models. The data fit the model well. In general, the results are consistent with the predictions of the model. The signs of the estimated α1 and α2 are consistent with the theory, both the Solow model and the BARS curve. Investments – GDP ratio is a significant predictor of real GDP per worker growth rate in all countries. The growth rate of oil production per worker is significant in all countries. Bahrain’s regression does not include oil production because the data are unavailable. Finally, the human capital per worker growth rate is significant and positive (1.07) in Bahrain and the UAE (0.48); it is negative in Kuwait (−0.90) and Saudi Arabia (−0.77). Oman does

Figure 5.1 The Growth Model With Real Government Expenditures Actual and Fitted Values Source: Kuwait has missing data for the period 1992–1994 because of the Gulf War

96

Is the Level of Spending Optimal?

not have data on human capital or average years of schooling. The negative coefficients in Kuwait and Saudi Arabia are inconsistent with the prediction of the model, counterintuitive, and interesting. It means that a 1 percent increase in human capital per worker growth rate reduces real GDP per worker growth rate. Why is the effect positive in Bahrain and the UAE?. Before we move on to fit a model for the current account, we ought to make sense of the estimated human capital elasticity. In developed countries, human capital is a significant explanatory variable in the Solow growth model and in all endogenous growth models. The human capital growth rate is insignificant or negative in Kuwait and Saudi Arabia’s regressions. There are a number of possible explanations. There are two hypotheses regarding human capital. One is that the rate of growth of human capital is the explanatory variable in the growth equation, which is what we had in these regressions. The other one is that the level of human capital is what matters for economic growth. These are two different effects, one affects the growth rate of GDP, and the other affects the speed at which human capital affects the GDP growth rate. We re-estimate the growth equations for Kuwait and Saudi Arabia by including the log-level of human capital as an explanatory variable instead of the growth rate. The coefficient of human capital α5 is positive and significant without any effect on the other coefficients. In the case of Kuwait, the coefficient is 0.075 with a P-value of 0.0989, and in Saudi Arabia, it is 0.05 with a P-value 0.1716, which is still significant at 10 percent. Therefore, human capital affects real GDP growth differently in these two countries. Nonetheless, the human capital level is quite low in the GCC because the labor force in the GCC is largely low-skill foreign labor. Human capital is measured by average years of schooling and the rate of return on education as in Mincer (1974). Also, see Bils and Klenow (2000). Reliable data on the quality of human capital is not readily available; therefore, we cannot examine the quality of labor. However, the quality of education could be a proxy for the quality of labor. TIMSS results of standardized tests of fourth- and eighth-year students in math and science, TIMSS (2019), have been showing positive trends over time (TIMSS cycles are four years, i.e., the carryout the tests once every four years since 1995) in all GCC countries; albeit with high volatility. Saudi Arabia, for example, had participated in three studied 2011, 2015, and 2019, with scores going up, sharply down, and up again. The positive trend in the GCC countries, however, favors girls over boys consistently. TIMSS reports a number of caveats, however. One issue is that some of the GCC students’ scores were zeros. TIMSS scores are an unusual statistic. For each student in the sample, five scores per test were reported. Therefore, the zeros complicate the interpretation of the results. Second, the sampling strategy implemented by TIMSS is complex. There is a national research coordinator in every country who is responsible for implementing the sampling strategy. Although the school sampling is random, in some cycles, the GCC countries included more private schools than public schools. The majority of students in private schools are foreigners – expats, which may influence the results. Third, some of the standard errors are noticeably large. Fourth, the GCC countries’ scores are generally

Is the Level of Spending Optimal? 97 significantly lower than the other countries in the samples. Fifth, (TIMSS, 2019, results, Ch. 9, p. 9.2) reported that some countries, including Kuwait and Saudi Arabia, chose to administer the less difficult mathematics assessment at the fourth grade. Sixth, TIMSS allows countries to exclude some students from the population samples – e.g., small remote schools and students with disabilities. For the fourth-year tests, Saudi Arabia, for example, excluded 10.1 percent at the school level and 10.5 percent overall. Dubai excluded 5.6 percent. For the eighth-year tests, Saudi Arabia excluded 10 percent and Dubai 5.5 percent. Al-Mutawa et al. (2021) analyze TIMSS (2019) results for Kuwait. They argued that the performance of Kuwaiti students in both the fourth and eighth grades was extremely low in mathematics in general and in subject areas in particular since Kuwait’s participation in the 1995 cycle. The performance of eighth graders showed a slight improvement in 2015 in all areas. They argued that the results show that the higher the level of thinking that was assessed, the lower the performance of Kuwaiti students was. The data indicate that Kuwaiti girls outperformed boys in all subjects in all TIMSS cycles; however, there was a slight improvement in 2015. However, both female and male performances lagged behind international norms. The authors said that the focus group analysis disclosed that supervisors perceived that students’ low performances are related to a number of reasons, such as the lack of interest in TIMSS tests, unfamiliarity with TIMSS questions, and students’ weakness in the Arabic language, which is quite remarkable really. The paper concludes that there is a need to systematically evaluate the TIMSS results, to intervene to mitigate these problems, and to develop “a competent national curriculum in Kuwait,” as they put it. TIMSS results over the period from 1995 to 2019 show that the GCC standardized tests in math and science for the fourth and eighth graders were significantly lower than the rest of the world. Razzak and Laabas (2011) found that adjusting labor input data for labor quality using TIMSS scores in developed countries shows a positive association with productivity growth, but not in developing countries, which include the GCC. Therefore, we believe that the poor quality of educational outcomes in the absence of data to shed light on the quality of human capital explains why the coefficients of human capital were negative or insignificant. The increase in average years of schooling and the literacy rate in the GCC, on the other hand, do not necessarily imply anything about the quality. Better education must show better quality outcomes, which would help the diffusion of foreign technology and increase the production of skill-intensive goods and services. However, the GCC countries do not produce such goods. So even if all the citizens of GCC are highly educated, the question is, What do they produce? Essentially, what matters is productivity in the non-oil production sector.4 Simon Kuznets (e.g., 1973) argued that economic growth revolves, most importantly, the process of producing useful knowledge. He was strictly talking about the developed countries, where such knowledge is created. He states (italic is our emphasis), “Many production plants in developed countries can be viewed as laboratories for the exploration of natural processes and as centers for research on new tools, both of which are of immense service to basic and applied research

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in science and technology. It is no accident that the last two centuries were also periods of enormous acceleration in the contribution to the stock of useful knowledge by basic and applied research – which provided additional stimulus to new technological innovations. Thus modern economic growth reflects an interrelation that sustains the high rate of advance through the feedback from mass applications to further knowledge.” The GCC countries do not produce useful knowledge. Therefore, research efforts may not lead to higher economic growth under the current economic and institutional structure. Investing in the quantity and quality of human capital might attract foreign technology – i.e., skill-biased technical change. The government should pursue policies that provide incentives for foreign technology to be in the GCC to produce new goods and services in the GCC so they could be counted in the GDP. Changing a mercantile society to a manufacturing society is the key to progress. The Arab Planning Institute in Kuwait produced many annual reports on competitiveness. The reports provided useful information about this issue; alas, they stopped publishing them after 2012. Oman’s National Centre for Statistics and Information (NCSI) reports detailed statistics of the labor force, which gives the reader more clues. Razzak (2020) reports that there is a very large number of expat workers in Oman, and the majority of them do not have an education beyond the elementary level. In Oman, for example, 1.6 million out of 1.8 million expat workers in the private sector are unskilled; they do not have an education higher than a grade school. Kuwait, the UAE, and Saudi Arabia are major oil producers and big employers of unskilled expats. We will revisit this issue later.

The Current Account Equation The second approach to estimating the optimal level of government spending is to estimate a current account (CA) model. The question is what is the optimal level of real government spending necessary for a current account surplus? The following equation is estimated, which is consistent with the theory of investments and the current account in Glick and Rogoff (1995).

˛ It ˆ CAt ˛ CA ˆ 2 =  0 + 1 ˙ ˘ +  2 lngt + 3lngt +  4 ln ˙ ˘ + t yt ˝ y ˇt −1 ˝ yt ˇ

(5.4)

Glick and Rogoff (1995) also make the argument for including domestic and world TFP. TFP data for Oman and the UAE are unavailable in the Penn World Table 10.0. Furthermore, Qatar does not publish data for investment. The equation is estimated using GMM for all countries, with and without TFP, and the instruments are the same instruments used earlier in estimating the growth model, the population distribution. The results are reported in Table 5.2. Figure 5.2 plots the actual and the fitted values. The estimates are consistent with theory and statistically significant. We use the estimates of the parameters of gt and gt2 in

( )

( )

CAt I Table 5.2 GMM Estimates of the Optimal Government Expenditures Level (i) = ˆ0 + ˆ1 CA + ˆ 2lngt + ˆ3lngt2 + ˆ 4 ˘ln t + ˆ5˘lnAt + ˇt y y y t t . (ii) t −1

Bahrain

Kuwait

Oman

Sample

1990–2017

2000–2017

1990–2017

β0

0.02 (0.1085) 0.59 (0.0000) 0.03 (0.1015) -0.03 (0.1377) -0.19 (0.0014) – 0.06 6.62 (0.4692)

– – 0.85 (0.0000) 0.07 (0.0003) -0.02 (0.0017) -0.53 (0.0000) – 0.06 5.03 (0.7538)

β1 β2 β3 β4 β5

σ (iv)

J P-value (v)

0.01 (0.1803) 0.78 .0000) 07 (0.0007) -0.06 (0.0000) 0.06 (0.1683) 0.51(0.0000) 0.06 3.84 (0.6973)

– –

−0.05 (0.0773) 0.93 0.94 (0.0000) (0.0000) 0.08 0.11 (0.0000) (0.0092) -0.03 -0.04 (0.0001) (0.0048) -0.25 -0.31 (0.0000) (0.0000) 0.37(0.0000) – 0.06 0.06 4.83 5.19 (0.6804) (0.7369)

Qatar (iii)

−0.07 (0.1998) 0.97 (0.0009) 0.10 (0.2435) -0.03 (0.2435) -0.47 (0.0000) 2.18(0.0981) 0.11 5.20 (0.6346)

–

–

–

–

–

–

–

–

–

–

– –

– –

KSA

UAE

1990–2017

1991–2017

-5.09 (0.0011) 0.81 (0.0000) 1.71 (0.0010) -0.14 (0.0009) -0.41 (0.0000) – 0.05 4.96 (0.7609)

-1.15 (0.0084) 0.85 (0.0000) 0.44 (0.0077) -0.04 (0.0073) -0.40 (0.0000) – 0.05 4.56 (0.8032)

-2.2 (0.0000) 0.87 (0.0000) 0.75 (0.0000) -0.06 (0.0000) -0.40 (0.0000) 0.66(0.0000) 4.66 (0.7004)

-2.5 (0.0080) 0.79 (0.0000) 0.93 (0.0081) -0.08 (0.0084) -0.27 (0.0349) 0.52(0.0530) 0.05 3.09 (0.8761)

(i) GMM instruments are the log-differenced distribution of population age 20–24, 25–29, . . . 75–79 from the World Development Indicators. The distribution is consistent with the life-cycle hypothesis, where investments increase from low at an early age, peak up in middle age, and then decline after retirement. The distribution of population is strictly exogenous. The estimated weighting matrix HAC uses the Bartlett kernel and Newey-West fixed bandwidth because the sample is small, and we could not search for lags. HAC is heteroscedasticity and autocorrelation consistent estimator of the long-run covariance matrix Ztut(β) and based on an initial estimate of b. P-values are in parentheses. (ii) The current account – GDP ratio is denoted

CAt , and At denotes relative TFP defined by the ratio of the country’s TFP – U.S. TFP. U.S. TFP is a proxy for the world TFP. yt

The Penn World Table 9.0 does not report Oman and the UAE d TFP data. We created them using the stock of capital, working-age population, and the share of labor from the Penn World Table 9.0, which does not report Oman and the UAE data. We computed TFP for Oman and the UAE assuming a Cobb-Douglas constant return to scale production function and using real GDP, the share of labor, working-age population, and the stock of capital that are reported in the Penn Table. The remaining variables are the same variables we defined earlier. The regression is based on Glick and Rogoff (1995) structural model. (iii) Qatar does not have investments data; therefore, the model is not estimated.  (iv) Standard errors of the regression. (v) J is the Sargan test for H0 : over-identification restrictions are valid.

Is the Level of Spending Optimal? 99

Country

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both Tables 5.1 and 5.2 to compute the average optimal government expenditures levels for each country. Figure 5.3 plots the level of the actual real government expenditures and the implied average optimal levels over the sample for the two models: the growth model and the current account model with and without relative TFP growth rate as an additional regressor. The optimal levels of government expenditures required to maximize real GDP per capita growth or the current account balance are the same in the case of Saudi Arabia and the UAE. They are different in the cases of Bahrain, Kuwait, and Oman. In Bahrain, the optimal level of government expenditure that is consistent with the current account is less than the level required to maximize productivity growth; it is significantly smaller in Kuwait

Figure 5.2 The Current Account Model with Real Government Expenditures Actual and Fitted Values Source: Kuwait has missing data for the period 1992–1994 because of the Gulf War

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Figure 5.3 Actual and the Average Optimal Government Expenditures Billions of Local Currencies Source: Kuwait has missing data for the period 1992–1994 because of the Gulf War. We do not plot the optimal values of the CA model with relative TFP growth because they are not significantly different from those plotted here. In addition, we do not plot the 95 and 5 percent upper and lower confidence intervals because the estimates of the optimal values of all three models are very narrow.

and marginally smaller in Oman. All GCC countries increased their government spending over time, and all of them seem to have tried to reduce spending after the increase in the twin deficits after the 2014 oil price collapse. However, the gaps between actual real spending level and average optimal spending remained very significant by 2017, especially with respect to the current account. The GCC countries have been spending significantly more than the implied average optimal levels since the mid-2000s. When the price of oil collapsed in 2014, they all suffered twin deficits, except Qatar. Therefore, a significant reduction in the levels of public spending is needed to make the adjustments in the primary fiscal balances.

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Appendix 5.1: Government Spending Does Not Crowd Out Private Investments

Figure 5.1.1 The Levels of Private Investments and Public Expenditures Billions of Local Currency Source: Source of the data is the IMF Investments and Capital Stock Data

Is the Level of Spending Optimal? 103

Figure 5.1.2 Significant Positive (Spurious) Correlation of the 95 Percent Chi-Square Confidence Ellipse Source: These are the significant positive, however, spurious correlations between the levels

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Figure 5.1.3 Insignificant Positive Correlation Between Growth Rates of Private Investments and Public Expenditures Source: The 95 Percent Chi-Square Confidence Ellipse

Is the Level of Spending Optimal? 105

Notes 1 The Solow model is a textbook model, which most economists know. It is a simple general equilibrium model that combines a neoclassical production function with the assumption of a constant saving rate. The production function is Cobb-Douglas with constant returns to scale. The assumption is that technology grows at constant rates g and population grows at a constant rate n. The number of effective units of labor is AtNt which grows at a rate n + g . The Solow model assumes a fraction of output, s = S / y is saved and I / y is invested. In the closed economy, saving is equal to investment. The capital per effective unit of labor is k = K / AL , and y is the level of output per effective unit of labor Y / AL. The capital-labor ratio evolves according to or kt = syt − ( n + g − ˆ ) kt , where the kt = s ( kt )ˆ − ( n + g − ˇ ) kt depreciation rate is a constant equal . The previous above dynamic equation implies that capital grows and converges to a 1

steady-state number, say k*, which is given by sk*θ = (n + g· − δ)k* or k * = ˆˇ s / ( n + g −  ) ˘ 1−  . The parameter influences the evolution q of capital and the determination of the steadystate value. It also influences TFP. 2 Some use the growth rate of G. Others use the government output ratio as regressors. That is not what matters. What matters is the estimated optimal level of government spending. 3 This analysis was completed before the release of Penn World Table 10.0. 4 Unfortunately, not a lot of data are available. I know that the GCC countries have time series data for non-oil GDP because I have worked with such data, but the regulations prohibits the use of such data by researchers like me. I could not get permission to use such data.

6

Can Taxes Resolve the Economic Problems?

Government spending is taxation. When you look at this, I've never heard of a poor person spending himself into prosperity; let alone I've never heard of a poor person taxing himself into prosperity. Arthur Laffer

Abstract The GCC countries heeded the IMF advice and introduced VAT; they might introduce income tax too. The timing, when the economy has been reeling from major contractions and heavy debts after the 2014 negative oil price shock, might chock the recovery, distributional negative side effects and deadweight losses notwithstanding. Taxation is also inconsistent with the no-representation, no-taxation principle, and there is no evidence that they would lead to democracy either. We use Omani data and a theoretical micro-foundation, work-leisure model to compute time series average weekly hours worked and simulate hypothetical counterfactual scenarios to show the macroeconomic effects of taxes on inflation, hours worked, consumption and output. We find no positive effects from taxes on the economy over the period 2020 to 2030. Historically, the GCC governments have been pursuing expansionary fiscal policies – i.e., government expenditures have positive trends and depend heavily on oil revenues and various fees rather than taxation per se. The governments used oil wealth to build fascinating modern cities, roads, power, communications, and water infrastructures and improved health and education for all citizens among many other infrastructures. These are government investments; they had positive effects on GDP per capita growth rates. The alternative to oil revenues to finance the budget deficits would have been a system based on taxation; however, it never existed for many reasons. (1) It would have very little chance of providing an equitable substitute for oil revenues. (2) Building a functional and efficient tax system is costly; it would have required lots of technical expertise the GCC countries do not have. (3) The income tax base is shallow. In general, the majority of the workforce is foreign labor with low to medium income. The GCC citizens, on the other hand, have multiple sources of income, which might DOI: 10.4324/9781003288282-6

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make the estimation of taxable income more difficult. (4) There is a strong political economy argument. Taxation requires a fully-fledged democracy whereby the people elect their governments. Taxation without representation does not work, and the argument that taxation leads to more democracy is highly questionable econometrically. It is clear that the GCC governments are unwilling to give up absolute power. During the 2011 Arab Spring, very rich Kuwaitis demonstrated every week in front of the parliament building calling for the right to elect the prime minister. In Oman, too, some people wanted jobs. Historically, very rich citizens are usually more politically motivated, and many aspire for more power themselves. After all, the wealthy aristocrats in England and the Netherlands among other European nations were the ones who changed the systems from absolute to constitutional monarchies. Both the people and the governments in the GCC understand this taxation representation requirement. The citizens accepted, without a challenge, a political system of absolute monarchy, which uses the oil wealth to provide for them. We are not quite sure how an income tax would be justified politically and what the reaction of the people would be, however, social unrest or some forms of objections and dissatisfactions would not be an exaggerated prediction. On the other hand, we can imagine a low-income tax rate would be introduced in some GCC countries but at a very high-income level. It seems that the prevalent system is consistent with “no representation and no taxation.” The culture of the GCC is largely in line with the political system. In exchange, the monarchs have not taxed the population so far. However, economic problems such as the budget and current account deficits surface when the price of oil falls significantly below the breakeven price (i.e., the price that balances the fiscal budget) and hinders the government’s ability to provide enough for its citizens. The argument that the introduction of taxes may lead to democracy is hard to prove.1 Ross (2011) argued that no nation with significant oil wealth has ever transformed into democracy. Oil dictators buy off their citizens, presumably, he is referring to “oil rent”; keep their finances secret; and spend wildly on arms. This sounds like a reasonable general description. We showed the data on oil rent in chapter 2. Arms purchases (imports) are easily verifiable by looking up the SIPRI data published by the World Bank, although we are unsure if the GCC countries are totally free to import arms because there might be country-specific defense agreements with the United States and Britain that define the parameters of arms imports. He adds that to prevent the resource curse from destroying the hopes of the Arab Spring, the U.S. government should push for more transparent oil markets and limits on its own addiction to oil. So as long as the GCC countries remain absolute monarchies, imposing taxes on people is not a reasonable proposition. Nonetheless, the IMF and the World Bank consultants who have visited the GCC annually since 2014 often advise the GCC governments to introduce taxes on labor income and consumption, for example, to make up for the shortfall in revenues. They seem oblivious to the political reality of the GCC. Such advice could be questioned on the basis that the GCC citizens do not elect their governments. It is difficult to argue that a vast majority of educated young people would accept paying taxes knowing very well that they cannot elect their prime ministers. Most people agree. Although a few citizens may justify

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a small tax on very high income, they make the argument that modernizing the economy requires a tax system similar to those in Western economies. The GCC governments are aware of the tension between taxation and representation and did not accept such advice immediately. For example, Kuwait, which has a relatively wider margin of civil liberty, went through the process of writing a tax law proposal on paper; however, it never passed as a law. Recently, Saudi Arabia, the UAE, and Oman introduced VAT, not entirely unchallenged, however. Political intricacy notwithstanding, there are other issues with the introduction of taxes in the GCC – e.g., the administrative issues such as collections, public finance issues related to the size of the tax base, and estimation of taxable income. Finally and most importantly are the macroeconomic concerns. The timing of the introduction of taxes matters, for it is irrational to impose taxes or increase taxes during economic downturns or slowdowns. The GCC economies have suffered significantly since the 2014 oil price shock, and may still suffer from COVID-19. Taxes on labor income, consumption, and corporate income have been analyzed extensively in economics and finance. They could generate revenues, no doubt, but they could create distortions too, reduce real income; adversely affect innovations, growth (e.g., Schumpeter, original argument), and welfare (e.g., Prescott, 2004); and increase the deadweight loss (e.g., Feldstein, 1999). In macroeconomic analysis, we are more interested in the effects of taxation on the economy as a whole. Corporate taxes have negative effects on innovation and growth. Akcigit et al. (2021) in a study of the U.S. economy, found that personal and corporate income taxes negatively affect the quantity of innovation; the share of patents produced by firms rather than individual inventors declines when the corporate tax rate is higher, and personal income taxes affect all inventors. Inventors are also significantly less likely to reside in states with higher tax rates. The objective here is beyond the political economy arguments, public finance, and administrative issues.2 We analyze the effects of taxes on some macroeconomic variables empirically. However, there are two problems. First, GCC countries do not have any data on taxes because they have not had taxes before. Second, the macroeconomic data required for the empirical analysis of the macroeconomic effects of taxation are unavailable for the GCC in general, which makes any empirical analysis difficult. However, Oman has some useful data. Thus, our analysis relies on the Omani data only. Although the magnitudes of our estimates might vary across different countries, the result must be qualitatively similar for any other GCC country. I encourage research economists in other GCC countries to do the same analysis if data are available. The main questions are, first, how does an average income tax on labor income affect the labor supply, output, and inflation over the business cycle? Second, would the introduction of a tax on income or on consumption (VAT) reduce hours worked (in the private sector) and output?3 We begin by explaining the relationship between the average income tax and the supply of labor, consumption-output ratio, and production.4 The only model is the familiar work-leisure choice model. In addition to the lack of tax data, there are no data on hours worked in Oman– i.e., the labor supply. We will solve the theoretical structural work-leisure choice model with a typical micro-foundation

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analytically and compute the equilibrium amount of average weekly hours worked in Oman. In this theoretical model, changes in the tax rate influence the decision of current consumption.5 The Permanent Income Hypothesis predicts that anticipated higher future taxes, such as income tax, lead to a lower future real income and lower current consumption. People also make decisions about consuming more today versus tomorrow, as reflected in the consumption-output ratio.6 These expectations have significant effects on the supply of labor (i.e., hours worked) and output; hence, they have policy implications e.g., pension reforms and social security issues. Next, we present the theory and the empirical evidence. The empirical results we present here are consistent with economic theory. In the model with an income tax, an increase in the tax rate causes the aggregate demand to fall, which creates an excess supply. To clear the good market, therefore, the aggregate supply too has to fall. This reduction in supply comes through a reduction in work efforts, which means fewer hours worked as shown earlier. Inflation increases in response to the income tax shock because the aggregate supply curve shifts to the left. When comparing the dynamic stochastic projections with those produced by a baseline model without an income tax, significant differences in output, hours worked, and inflation projections are found. The economy with an income tax has sharply declining output and hours worked over the projection horizon from 2017 to 2030, while the economy without an income tax has a stable and mild increase in output, hours worked, and positive small inflation.

The Model We present a standard structural micro-foundation model of work-leisure choice, which is a modified Prescott (2004), whereby the modification involves adding natural resource endowment to the model. This modified model is Razzak and Laabas (2016). The GCC countries are hydrocarbons rich; therefore, hydrocarbons enter the production function. The solution of this model gives us a computable, equilibrium, labor supply equation – i.e., average weekly hours worked per person. Then, we use this time series, along with GDP and inflation, to estimate an SVAR to examine counterfactual scenarios of the effects of income and consumption (VAT) taxes on labor supply and other macroeconomic variables over the period 2020–2030. The utility function of a stand-in household that faces a work-leisure decision is (| ∞ )| U = E { β )ln Ct + α ln 100 − ht ) }. ( ) |) (| t =0

∑

(

)

(6.1)

The utility function depends on the expected discounted sum of consumption Ct and leisure, where 100 is the number of hours available for individuals to work in a week, and ht is the average weekly hours worked per worker in “market activities.”7 The expectations operator E is the expectation operator, and 0 < β < 1 is the discount factor and specifies the degree of patience, where a high value means more patience for consumption and leisure. The parameter α > 0 denotes

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Can Taxes Resolve the Economic Problems?

the value of the non-market productive time per household.8 It measures the relative value of the time spent working at home or the relative value of leisure. Capital stock evolves as before according to K t +1 = (1 − δ ) K t + I t , where Kt is the stock of capital and I t is gross investments. The depreciation rate is δ. The GCC oil-producing countries have natural resource endowments. Therefore, the production function differs from the typical Cobb-Douglas with capital and labor. Output is produced according to a constant return to scale CobbDouglas production function, and factor inputs include hydrocarbons in addition to capital and labor. This output can be equal to or greater than expenditures (Yt = f (H, Kt, h̅ t) ≥ Y = C + I + G). The production function is Yt = At  Htω Ktθ  h̅ t1–ω–θ,

(6.2)

where Ht denotes the production of hydrocarbons, ω is the share of hydrocarbons Ht in output, and Kt and ht are the stock of capital and hours worked (i.e., the labor supply). See Stiglitz (1974) and Solow and Wan (1976) for the measurement of hydrocarbons in the production function. The household faces a usual budget constraint, whereby consumption and investment (spending) is equal to income from work and interest income. In the case of Oman, the individual also receives income from oil in terms of subsidies and a number of benefits. The government budget constraint holds all the time. The budget constraint is

(1+ τ c ) Ct + (1 + τ I ) It = (1 − τ h )Wt ht + (1 − τ K ) ( rt − δ ) Kt ⎛ Po H + δ Kt + TRt + ⎜ t t ⎜ ˆ ⎝ Pt

⎞ ⎟⎟ , ⎠

(6.3)

where Wt is the real wage, rt is the real interest rate or rental capital, and TRt is transfer payment. The tax rates of consumption, investments, labor, and capital are given by τ with the subscripts C ,. I ,. h, and K, which denote consumption, investments, hours, and capital, respectively. Pto is the international price of the hydrocarbons, H t is the flow or the production of hydrocarbons, and Pˆt is population. The model solves for the equilibrium average weekly hours worked per person. Razzak and Laabas (2106) solve the system to arrive at ht =

1− ω − θ 9 C α . 1− ω − θ + t Yt 1− τ

(6.4)

The equilibrium average weekly hours worked by an individual depends on (1) the shares of labor, which is basically one less the share of oil less the share of capital; (2) the consumption-output ratio; (3) the marginal tax rate, which is given by τ +τ τ = C h , and (4) the relative value of leisure. This equation differs from Prescott’s 1+ τ C (2004) because we include the share of hydrocarbon. Razzak and Laabas (2016)

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argued that the share of hydrocarbon in output is similar to the tax rate in the theoretical model; it creates a wedge between the marginal productivity of labor and the real wages when solving the model. To compute the equilibrium average weekly hours worked per person, equation (6.4), the average marginal tax rate τ, needs to be computed. First, the tax on conITt sumption in Oman τ C is ( ), indirect taxes on consumption (IT)/consumpCt − ITt tion less indirect taxes. Indirect taxes in Oman are approximately the taxes on concessionary use plus custom duties only. Second, the average income tax rate τ h is: DT (6.5) GDP − IT − ° . There are no historical data for direct taxes, of course, so we arbitrarily assume that the direct taxes are 10 percent of total income; we think of this as the initial income tax rate. Figure 6.1 plots our estimated consumption tax and the average income tax. The share ω is set to 0.30, and the share of capital is 0.49, as estimated earlier in Chapter 3.10 The relative value of leisure α is in equation (6.4) is unknown. Prescott (2004) assumed that it is 1.78, which maximizes the fit of equation (6.4) for the G7 countries. In other words, he chose a value for α such that the estimated equilibrium ht is as close as possible to the actual data. However, there are no actual data for average weekly hours per worker in Oman either, or in any other GCC country for that matter. Therefore, as in Razzak and Laabas (2016), sensitivity analysis over three arbitrary values of α, 1.29, 1.55, and 2 is used. The data for total consumption and GDP are readily available, therefore the equation for hours worked could be computed using the aforementioned values of C α, ω, and τ, along with the consumption-output ratio . Figure 6.2 plots the comY puted average weekly hours worked per person. On average from 1998 to 2016,

˜h =

Figure 6.1 Hypothetical Computed Average Income Tax and Consumption Tax

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Can Taxes Resolve the Economic Problems?

Figure 6.2 Computed Oman Average Weekly Hours Worked Per Person

Figure 6.3 Growth Rates of Hours Worked and Oil Price

Omanis work about 18 hours a week. To have a benchmark for comparison, over the same sample, the Americans, who work very long hours, have average actual weekly hours worked of 34 hours.11

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Figure 6.3 plots the percentage changes in average weekly hours worked per person (the average of the three measures plotted earlier), and the oil price – i.e., the growth rates. Although the correlation is high, 0.80, hours worked per person are relatively higher during the period when the price of oil is relatively low. This is clear in the graph for the periods before the Global Financial Crisis and after the collapse of oil prices in 2014. Razzak and Laabas (2016) reported a similar pattern in the data for all GCC. Our interpretation of this correlation is that Omanis work longer hours, or take more than one job, to make up for the decline in income and rent in order to smooth out current consumption. The timing of the introduction of the tax is important too. It is perhaps best to introduce or increase the income tax when the economy is not in a downturn. The Omani economy after March 2014, however, was on a downturn because of the negative terms of trade shock (oil price declined in 2014). It is well understood that there are potential adverse social and political consequences to imposing taxes on income because the majority of workers (75 percent) in Oman are low-income earners. The vast majority of workers in private and public sectors, and 60 percent are in the lower quintile of the distribution making between Omani Rial (henceforth OMR) 325 ($ 845 U.S.) and l OMR 600 ($ 1,560 U.S.) monthly. About 9 percent make between OMR 701–800 ($1,822 to $2,080 U.S.), and 7 percent are between OMR 901–1,000 ($2,343 to $2,600 U.S.) monthly. Therefore, if taxes on income were to be introduced, they should be introduced when the economy is on an upturn. There are other distributional effects, which are not discussed here because they depend on the details of the tax policy, but it is rather obvious that the majority of Omanis will be hurt by the introduction of an income tax, except for a few who are in the top 1 percent of the income distribution. The efficacy of such a policy becomes an important issue if the income tax is imposed on high-income workers only because the tax base would be very small. Next, some empirical evidence is provided.

Empirical Evidence The Effect of an Average Income Tax Rate on Output, Inflation, and Labor Supply We estimate the response of output, inflation, and the labor supply (i.e., average weekly hours worked per worker) to an average income tax shock in Oman. Data from 1998 to 2016 only are available to estimate the dynamic response to an average income tax shock over the business cycle. To illustrate the effect of the introduction of income tax on the economy, two SVAR models (SVAR1 and SVAR2), with additional theoretical restrictions on the parameters, are estimated. SVAR1 model is the baseline model without an average income tax, and SVAR2 is the model with an income tax. The VAR system was described earlier in the appendix of Chapter 3. Usually, the NCSI releases GDP data with a two-year lag, but the data we used to compute the tax rates are only available up to 2016. The small sample influences the specification and the estimation of the model’s dynamic; however, it is a trade-off we have to bear in policy analysis when

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historical data are unavailable. Therefore, no more than five variables could be included in the VAR. We test the lag length using a number of commonly used Information Criteria. Given the sample size, one lag should be suitable.12 The VAR variables include (1) the real price of oil is the average price oil of Dubai, Brent, and WTI, deflated by the U.S. CPI; (2) inflation defined by ˜ln ( CPI t ); (3) the output gap defined as the deviation of log real GDP from an HP trend (Hodrick and Prescott, 1997); (4) the average weekly hours worked is the deviations of the average of the three measures from an HP trend. The structural impulse response functions of the baseline SVAR without an income tax are plotted in Figure 6.4. The estimates are reported in Appendix 6.1. SVAR2 is the model with an assumed income tax rate. This SVAR has five variables. First is the real price of oil. The second is the average income tax, τ h, DT measured by the ratio of the ˜ h = , where DT is direct taxes, IT GDP − IT − ° are indirect taxes, and δ is depreciation. As we mentioned earlier, we arbitrarily assumed that the direct tax is 10 percent of real GDP because there are no data on direct tax. The magnitude should not matter qualitatively because the objective is to compare a system with a tax to another, without a tax on income. The indirect taxes on consumption, IT, are custom duty and taxes on concessionary use. These data are available from the NCSI. The third variable is the inflation rate followed by the output gap and the deviation of the average weekly hours worked from the HP trend. The estimates are reported in Appendix 6.1. Figure 6.5 plots the structural impulse response functions, which are consistent with the theory. The impulse response functions plots are the responses of inflation, the output gap, and the average weekly hours worked to the oil price shock. Inflation increases, the output gap has a small initial decline, then increases and has the typical hump-shaped impulse response function. The supply of labor increases too. Compare these responses to the responses of inflation, the output gap, and the labor supply to the average income tax shock. Inflation increases for about a couple of years before it starts to decline; the output gap dips in response to the tax shock, and the supply of labor falls permanently. These results are consistent with economic theory. Finally, the two models SVAR1 and SVAR2 are solved, and dynamic stochastic projections are made over the period of 2017 to 2030, whereby the innovations are generated with 1,000 Bootstrap iterations (the solution method is in the appendix). Figures (6.6), (6.7), and (6.8) plot the mean dynamic stochastic projections of inflation, the cyclical average weekly hours worked, and the output gap, and of SVAR1 and SVAR2. For the model with the income tax, the mean dynamic projections of inflation are declining throughout the period of 2017 to 2030. Why does inflation fall? The only explanation is that the introduction of income tax reduces aggregate demand by more than aggregate supply in this particular exercise. Figure 6.7 shows that hour worked declines significantly because of the income tax, which is consistent with the theoretical model. Finally, income tax reduces the output gap. Figure 6.8 plots the mean dynamic stochastic projections of the output gap. An economy with an income tax shows that the tax reduced output and the labor supply, and prices.

Can Taxes Resolve the Economic Problems?

Source: Shock 1 is an oil price shock; shock 2 is an inflation shock; shock 3 is an output shock; shock 4 is a labor supply shock (deviations of hours worked from trend)

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Figure 6.4 Impulse Response Functions of Inflation, the Output Gap, and Labor Supply SVAR1 Baseline Model Without Tax

116 Can Taxes Resolve the Economic Problems?

Figure 6.5 Impulse Response Functions of Inflation, the Output Gap and Labor Supply SVAR 2 Model With an Income Tax Source: The model is SVAR 2. Shock 1 is an oil price shock; shock 2 is an average income tax shock; shock 3 is an inflation shock; shock 4 is an output shock; shock 5 is a labor supply shock (deviations of hours worked from trend)

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Figure 6.6 Oman – Mean Dynamic Stochastic Projections of Inflation

Figure 6.7 Oman – Mean Dynamic Stochastic Projections of Cyclical Average Weekly Hours Worked

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Figure 6.8 Oman – Mean Dynamic Stochastic Projections of the Output Gap

The Effect of a Consumption Tax on Consumption, Inflation, and the Supply of Labor Most nations that introduced consumption taxes such as a goods and services tax experienced a temporary one-off spike in the CPI inflation. Australia, New Zealand, and Singapore are examples. For Oman, a VAT is a 5 percent additional increase to the existing indirect taxes, which are custom duties and taxes on conITc cessionary use. The indirect tax is IT = , where ITC is indirect taxes on C + ITC consumption and C is consumption (household plus government consumption). An SVAR similar to the earlier systems includes the log real price of oil, log VAT, inflation, consumption, and the average hours worked per worker. Consumption and hours are deviations from an HP trend. Inflation is ˜ln ( CPI ). The sample is from 1998 to 2016. The dynamic is tested the same way we tested it before in this book, and it is set to one lag. The impulse response functions are plotted in Figure 6.9. Consumption, inflation, and hours worked respond positively to the oil price shock. Consumption responds negatively to a VAT shock, while inflation and hours worked respond positively to a VAT shock. Next, the baseline SVAR with no VAT is solved, and baseline dynamic stochastic projections are computed. Figures (6.10), (6.11), and (6.12) plot the actual and the mean baseline dynamic stochastic projections for consumption, inflation, and hours worked with the standard errors. Initially, inflation rises, consumption, and the supply of labor fall and then slowly stabilize at a higher level. Because the differences between the projections of the baseline model and the 5 percent VAT model are small, Figures 6.13, 6.14, and 6.15 plot the deviations of the mean dynamic stochastic projections of the VAT model from baseline. Clearly, the VAT induces additional volatility in the projections. Inflation, consumption, and hours worked are much more volatile. There are obvious positive macroeconomic effects from the introduction of the 5

Source: The model is SVAR2 with a VAT. Shock 1 is an oil price shock; shock 2 is a VAT shock; shock 3 is an inflation shock; shock 4 is a consumption shock; shock 5 is a labor supply shock (hours worked)

Can Taxes Resolve the Economic Problems?

Figure 6.9 Impulse Response Functions of Consumption, Inflation, and Labor Supply to VAT Shock

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Figure 6.10 Mean Dynamic Stochastic Projections of Inflation

Figure 6.11 Mean Dynamic Stochastic Projections of Consumption

percent VAT; however, the public purse might have a moderate increase in revenues. An important research question is if the VAT increases household savings. The introduction of new taxes or increasing existing taxes will have adverse predicted results on output and the supply of labor. Taxes can increase revenues but only to a certain limit because the tax base is small in Oman. For Oman, as shown earlier, the majority of workers (75 percent) are low-income earners. Further, taxable income is inversely related to the tax rate (the Laffer curve). Furthermore, introducing taxes or increasing them during bad economic times is not a sound macroeconomic policy. It is probably difficult to balance the budget and the current account as long as the price of oil remains below the breakeven price or if the oil price trend declines in the long run. The breakeven price reflects the high government spending. It is equally challenging to reduce government spending

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Figure 6.12 Mean Dynamic Stochastic Projections of Hours Worked

Figure 6.13 The Deviations of Mean Dynamic Stochastic Projections of Inflation From the Baseline Model

to its optimal level, which maximizes real GDP per person growth rate and balances the current account. Taxes are not an optimum solution either because of the deadweight loss and the macroeconomic inefficiencies that they would create, let alone their incompatibility with the political reality in the GCC countries. So what should the GCC government do? Next, we present some policy ideas that have different effects on the macroeconomy.

122 Can Taxes Resolve the Economic Problems?

Figure 6.14 The Deviations of Mean Dynamic Stochastic Projections of Consumption From the Baseline Model

Can Taxes Resolve the Economic Problems?

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Figure 6.15 The Deviations of Mean Dynamic Stochastic Projections of Hours Worked From the Baseline Model

Appendix 6.1: The Estimated SVAR Without Income Tax The model is given by Aet = But , where et is a matrix of the residuals of the estimated VAR, ut is a matrix of unobserved shock, which we want to identify. The short-run restrictions that are imposed on the SVAR to identify these shocks are e1 = −c1u1 ; e2 = −c2 e1 + c3u2 ; e3 = −c4 e1 − c5 e2 + c6u3 ; and e4 = −c7 e1 − c8 e2 − c9 e3 + c10 u4

.

This system is estimated using the Maximum Likelihood with Newton-Raphson analytic derivatives.

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SVAR Estimates Sample (adjusted): 1999 2016 Included observations: 18 after adjustments Estimation method: Maximum likelihood via Newton-Raphson (analytic derivatives) Convergence achieved after ten iterations SVAR is just identified A=

0 1 a5 a8

0 0 1 a9

0 0 0 1

a1 0 0 a3 0 0 0 0 including the restriction(s)

0 0 a6 0

0 0 0 a10

Std. Error

z-Statistic

Prob.

0.043068 0.019643 0.003589 0.027477 0.290360 0.004421 0.057727 0.608151 0.493640 0.009260

5.999999 −2.282221 5.999999 0.336856 −0.048067 5.999999 −5.184832 0.372509 −2.977071 5.999999

0.0000 0.0225 0.0000 0.7362 0.9617 0.0000 0.0000 0.7095 0.0029 0.0000

0.000000 1.000000 −0.013957 0.226542

0.000000 0.000000 1.000000 −1.469602

0.000000 0.000000 0.000000 1.000000

0.000000 0.021535 0.000000 0.000000

0.000000 0.000000 0.026529 0.000000

0.000000 0.000000 0.000000 0.055560

0.000000 0.021535 0.000301 −0.004437

0.000000 0.000000 0.026529 0.038987

0.000000 0.000000 0.000000 0.055560

−0.008556 0.037676 0.015526 −0.075949

−0.622872 −0.041114 0.044550 0.031036

−0.238261 −0.018164 0.005791 0.101836

B=

1 a2 a4 a7

Coefficient a1 a2 a3 a4 a5 a6 a7 a8 a9 a10

0.258406 −0.044830 0.021535 0.009256 −0.013957 0.026529 −0.299305 0.226542 −1.469602 0.055560

Log likelihood

108.6362

Estimated A matrix: 1.000000 −0.044830 0.009256 −0.299305 Estimated B matrix: 0.258406 0.000000 0.000000 0.000000 Estimated S matrix: 0.258406 0.011584 −0.002230 0.071441 Estimated F matrix: 0.749085 0.018871 0.019245 0.085608

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And With Income Tax SVAR Estimates Sample (adjusted): 1999 2016 Included observations: 18 after adjustments Estimation method: Maximum likelihood via Newton-Raphson (analytic derivatives) Convergence achieved after 13 iterations SVAR is just identified A=

B=

1 a2 a4 a7 a11

0 1 a5 a8 a12

0 0 1 a9 a13

0 0 0 1 a14

0 0 0 0 1

a1 0 0 0 0

0 a3 0 0 0

0 0 a6 0 0

0 0 0 a10 0

0 0 0 0 a15

Coefficient

Std. Error

z-Statistic

Prob.

0.041 0.007 0.001 0.013 0.399 0.002 0.025 1.298 0.443 0.004 0.059 3.460 1.141 0.551 0.009

5.99 −1.99 5.99 −0.47 −5.97 6.00 −0.05 2.31 −1.93 5.99 −4.78 −0.62 0.76 −2.98 5.99

0.0000 0.0466 0.0000 0.6332 0.0000 0.0000 0.9589 0.0208 0.0532 0.0000 0.0000 0.5330 0.4417 0.0028 0.0000

0.000000 1.000000 −2.384976 3.000993 −2.157633

0.000000 0.000000 1.000000 −0.857957 0.878173

0.000000 0.000000 0.000000 1.000000 −1.647190

0.000000 0.000000 0.000000 0.000000 1.000000

0.000000 0.007594 0.000000 0.000000 0.000000

0.000000 0.000000 0.012864 0.000000 0.000000

0.000000 0.000000 0.000000 0.024221 0.000000

0.000000 0.000000 0.000000 0.000000 0.056696

a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 a12 a13 a14 a15 Log likelihood Estimated A matrix: 1.000000 −0.014259 −0.006399 −0.001308 −0.284670 Estimated B matrix: 0.249814 0.000000 0.000000 0.000000 0.000000

0.24 −0.01 0.007 −0.006 −2.38 0.013 −0.001 3.00 −0.856 0.02 −0.28 −2.15 0.87 −1.65 0.05 182.0997

(Continued)

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(Continued) Estimated S matrix: 0.249814 0.003562 0.010094 −0.001703 0.067131 Estimated F matrix: 3.673732 0.035638 0.136689 0.103113 0.444054

0.000000 0.007594 0.018112 −0.007251 −0.011463

0.000000 0.000000 0.012864 0.011037 0.006883

0.000000 0.000000 0.000000 0.024221 0.039896

0.000000 0.000000 0.000000 0.000000 0.056696

3.212592 −0.005557 0.166889 0.088776 0.308951

−3.441520 0.019102 −0.123040 −0.065491 −0.438586

−3.170359 −0.018831 −0.144251 −0.033201 −0.281063

0.614447 −0.043096 0.016425 0.030583 0.209249

SVAR Model With 5 Percent VAT The SVAR includes the following variables real price of oil, VAT, consumption, inflation, and average weekly hours worked. The price of oil and the VAT are measured in logs, consumption is the deviation from an HP filter trend, inflation is the log-differenced CPI, and the labor supply is also in deviations from an HP filter trend. SVAR Estimates Sample (adjusted): 1999 2016 Included observations: 18 after adjustments Estimation method: Maximum likelihood via Newton-Raphson (analytic derivatives) Convergence achieved after 13 iterations SVAR is just identified A=

B=

1 a2 a4 a7 a11

0 1 a5 a8 a12

0 0 1 a3 a13

0 0 0 1 a14

0 0 0 0 1

a1 0 0 0 0

0 a3 0 0 0

0 0 a6 0 0

0 0 0 a10 0

0 0 0 0 a15

Can Taxes Resolve the Economic Problems?

Coefficient a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 a12 a13 a14 a15 Log likelihood Estimated A matrix: 1.000000 −0.042462 −0.053659 −0.028418 −0.325833 Estimated B matrix: 0.244569 0.000000 0.000000 0.000000 0.000000 Estimated S matrix: 0.244569 0.010385 0.012119 0.009945 0.084123 Estimated F matrix: 0.004210 −0.040783 −0.026902 −0.019117 0.133734

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Std. Error

z-Statistic

Prob.

0.040 0.088 0.015 0.075 0.197 0.012 0.016 0.042 0.049 0.002 0.030 0.089 0.106 0.415 0.004

5.99 −0.47 5.99 −0.71 0.48 5.99 −1.76 −2.81 −2.92 5.99 −10.60 0.85 7.976 −3.75 6.00

0.0000 0.6331 0.0000 0.4749 0.6249 0.0000 0.0773 0.0049 0.0034 0.0000 0.0000 0.3938 0.0000 0.0002 0.0000

0.000000 1.000000 0.096707 −0.118411 0.075898

0.000000 0.000000 1.000000 −0.145659 0.850750

0.000000 0.000000 0.000000 1.000000 −1.561854

0.000000 0.000000 0.000000 0.000000 1.000000

0.000000 0.092286 0.000000 0.000000 0.000000

0.000000 0.000000 0.077438 0.000000 0.000000

0.000000 0.000000 0.000000 0.016358 0.000000

0.000000 0.000000 0.000000 0.000000 0.028847

0.000000 0.092286 −0.008925 0.009628 0.015625

0.000000 0.000000 0.077438 0.011280 −0.048263

0.000000 0.000000 0.000000 0.016358 0.025549

0.000000 0.000000 0.000000 0.000000 0.028847

−0.344127 0.105635 0.023031 −0.014711 −0.026755

−0.116130 −0.010041 0.141739 0.020164 −0.111754

0.164580 −0.021051 0.044380 0.042111 0.028269

−0.352398 −0.093983 −0.039835 −0.019517 0.055872

0.24 −0.042 0.092 −0.053 0.096 0.077 −0.028 −0.118 −0.145 0.016 −0.325 0.075 0.850 −1.561 0.028 124.4423

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Notes 1 There is a literature on taxation and representation. There is no careful and robust evidence that taxes cause or lead to democracy. See, for example, Ross (2004). Timmons (2010) found some evidence that one-third of the increase in revenues might be due to democracy; however, neither democracy nor voter turnout increases revenues from progressive taxes on income and capital. Herb (2003, 2005) argues that most of the theories about taxation causing democracy have ignored the fact that modern parliamentary institutions do not collect taxes; therefore, taxation has a “modest” effect on democracy. Testing the hypothesis that “taxes cause democracy” is a very difficult task because it involves many measurements, specification, and estimation issues. Bernstein et al. (2000), for example, discusses the Chinese case. For more on democracy in the Arab world see Elbadawi and Makdisi (2011). 2 From a public finance standpoint, a tax on income is a direct tax, which is expected to increase revenues and reduce the deficit, but that depends on the tax base and the total revenues from the tax. For example, Barro (1993, p. 352) explains that if the tax rate is 10 percent, a 10 percent increase means that the new tax rate is 11 percent. The fraction of additional income kept by either producers or workers is one tax rate falling from 90 percent to 89 percent (1.1 percent). Thus, a 10 percent increase in the tax rate means a reduction in real taxable income in the long run by less than 10 percent. The higher the starting value of the tax rate, the larger the proportional reduction of the term one tax rate from a 10 percent increase in the tax rate. This means that the negative response of real taxable income to higher tax rates increases with the tax rate, the Laffer curve. The Laffer curve implies that revenues will increase with the marginal tax rate up-to-a-certain maximum, and then revenues will fall as GDP begins to decline. There is also a literature on optimal taxation. For example, see Scully (2003). 3 We say average income tax and not marginal income tax because we do not have data to compute a marginal income tax. 4 Ideally, we should be examining the effect of the marginal income tax; however, measurement is hindered by the lack of data. 5 The intratemporal substitution. 6 The Intertemporal substitution. 7 Market activity excludes bureaucratic jobs in the public sector. 8 The price of leisure is the after-tax real wage. So small increases in wages, for example, trigger a substitution effect in the short run. People reduce their current consumption of leisure because it becomes expensive, and they work longer hours. When income increases to a certain limit and people feel wealthier, they consume more leisure. The overall effect of a change in wages depends on which effect dominates. There is a large empirical literature that estimates these effects. For Oman’s labor market, which is dominated by a large number of unskilled workers with relatively low income, we expect the income effect to dominate – i.e., less leisure is consumed and hours worked are high. 9 Solving from the time-sequential Lagrange multiplier problems and focusing on the variables, consumption-leisure ratio ct / (100 − Lt), and capital-labor ratio K t / Lt, the ˜ 100 − Lt 1 − ° L Wt = MRS between leisure and consumption is: . To simplify further, 1 1 + ° c Pt ct ˝ +˝L ˜c +˜ L = 1−˝ . = ˜ . Add 1 to both sides, 1 − c we introduce the tax rate τ, let 1+˝c 1+˜c

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10 The share of labor is total compensation to employee / nominal GDP. The share of capita is 1-share of labor. 11 Prescott (2004) and Nickell (2003) estimates of hours worked for the United States using different models and different samples are much smaller than 34 hours. The point is that taxes reduce hours worked. 12 We use LR sequential modified test, FPE final prediction error, Akaike, Schwarz, and Hannan-Quinn.

7

Savings, Productivity, and Other Structural Issues

Fundamentally, the basis of all modern progress is the efficiency of labor. And, the only sure road to restored prosperity is through the thrift and hard work of our people as a whole. Charles M. Schwab

Abstract Expected decline in oil prices, and subsequently GCC incomes in a zero-carbon world, reduces national savings, hence a current account deficit. Persistent current account deficits threaten the currency peg, and induce financial instability. The GCC countries, particularly Oman, have experienced such a deficit after the 2104 oil price shock. There is only one viable policy option to restore the balance, maintain the peg and a sustainable debt level at the same time; savings must increase because reducing investment is not a sensible policy. We present some back-of-the envelope calculations of a number of mandatory saving scenarios to show that Oman could have a minimum household saving of 3 billion Rials and a maximum of about 9 billion Rials a year. Further, productivity is associated with work effort, the education system, public vs. private sector employment choice, the incentive structure, land ownership, the law system, etc. There is a need for evidence-based structural reform to strengthen savings and productivity.

A Case for Personal “Household” Saving It is said that to save something for a rainy day is an idiom that may be traced back to the 1500s. Whether the origin of this idiom is true or not, it makes a lot of sense in economics to save out of income. Paying the external debt is crucial for the future of Oman and Bahrain in particular. It is more important for Oman because it is a relatively larger and has a structurally different economy from Bahrain, which is not a major oil producer. The data on household savings are not readily available. Therefore, gross saving is most probably dominated by government savings. The GCC governments have Sovereign Wealth Funds (SWFs). Little is known about these funds because they are not subject to the transparency rules found elsewhere in the world. There is a general agreement among analysts that these funds are sizable, though have been used to bridge the deficits after the DOI: 10.4324/9781003288282-7

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2014 oil price shock. Finch (2020) rating of these funds in Kuwait, Qatar, and the UAE suggest that they will probably deplete their SWF assets in the long run unless oil prices recover, oil production increases, fiscal adjustments, and higher financial market returns on their investments. The report suggested that although there are structural problems such as the lack of income diversification, they need “a very” strong balance sheet to support their current rating levels. The report clearly says that the deterioration of the fiscal and external balance sheets due to their inability to adjust spending to lower oil prices, which may be low longer because of the negative rating sensitivity in the GCC. Household savings, therefore, are needed in the future states of the world when the demand for hydrocarbons declines, reduces oil prices, and the GCC revenues. Household savings would be the future stock of capital and investments needed for economic growth. Household savings would also be needed to support future pension funds. Finally, household savings would be a domestic source of funds for the government to finance the budget deficits instead of issuing external debt. Two studies stand out and remain as guiding methods to answering this question. Blanchard (1985) argues that debt will reduce capital but not one for one. In a more elaborated general equilibrium overlapping generation model, Auerbach and Kotlikoff (1987) said that debt crowds out capital one for one. According to the Keynesian story, high debt reduces national savings because it reduces GCC government savings and may not increase private savings by the same amount. Therefore, the stock of capital falls, or the share of capital in output declines, and the marginal product of capital increases. The IMF – WEO (April 2021) data show that the gross savings – GDP ratios in the GCC countries are close to those of the rich Asian countries. On average from 1980 to 2020, the GCC countries’ gross savings – GDP ratios were 26.1 percent in Bahrain, 37.4 percent in Kuwait, 23.4 percent in Oman, 41.8 percent in Qatar, 26.7 percent in Saudi Arabia, and 32.8 percent in the UAE. China’s gross savings – GDP ratio is 41.6 percent, Hong Kong 31.2 percent, Korea 34.5 percent, Singapore 44.2 percent, and Taiwan 32.7 percent. Keep in mind that Asian countries do not have oil and gas, and Singapore has a mandatory saving scheme, which we will discuss in more detail. Figure 7.1 plots the level and the growth rate of the saving – GDP ratio (IMF-WEO, October 2020) from 1995 to 2019. Clearly, saving has not been growing. It is highly improbable that savings increase in the future if income remains dependent on hydrocarbons and the global demand for hydrocarbons declines because when income from oil falls so will national savings. Income diversification seems to be important more now than ever. Climate change and pandemics might never bring the demand for hydrocarbon to the old levels; hence, future oil revenues may never recover. The national income identity is Y = C + I + G + X – M, where Y is total output, C is consumption, I is investments, G is government spending, X is exports, and M is imports. Hence, net exports NX = X – M. Figure 7.2 plots NX – GDP ratio – (IMF-WEO, October 2020) from 1995 to 2019. All GCC countries except the UAE experienced a decline in the net exports – GDP ratio after the 2014 oil price shock. It is unclear why the UAE did not experience such decline, but we speculate that Dubai is largely a non-oil exporter.

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Figure 7.1 Saving – GDP Ratios 1995–2019

The previous identity could be rewritten as NX = Y – C – I – G, and NX + I = Y – C – G or NX + I = S, where S is saving. In closed economies, national savings is equal to domestic investment, and the current account is always zero. Any observed increase in national savings is automatically associated with an equal increase in domestic investment. However, the GCC countries are not closed economies. Capital is freely mobile. Therefore, we expect savings to diverge from investments. In bad times, the GCC countries borrow from abroad. Feldstein and Horioka’s (1980) claimed that even in industrial countries, capital mobility does not guarantee saving is equal to investment. Is Saving Equal to Investment? Figure 7.3 plots the investments – GDP and saving – GDP ratios (IMF – WEO, October 2020). There is no evidence that savings equal investment, which is

Savings, Productivity, and Other Issues

133

Figure 7.2 Net Exports – GDP Ratio

consistent with the free capital mobility condition. The three richest countries, Kuwait, Saudi Arabia, and the UAE, have savings that exceed investment over the sample, with a minor fall in savings in Saudi Arabia after the 2014 oil price shock. Qatar does not report investment data. Bahrain and Oman have savings fall and rise above investment but clearly savings fell significantly after the 2014 oil price crash. However, the current account (CA), investments, and savings identity hold well in the data. Figure 7.4 plots the data, S – I = CA. The current account deficit affects the real value of the currency under a fixed exchange rate regime. Deficits tend to put downward pressure on the currency. People in the GCC carefully watch the current account. They know that when the deficits persist, the government thinks about either devaluing or reducing wages. People hedge against devaluation by sending their capital abroad – i.e., keep their money in USD accounts. The current account deficits indicate that the GCC countries borrow externally to finance spending. However, S – I = CA does not hold. Figure 7.5 shows that the trade balances exceed the current accounts.

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Figure 7.3 Saving Is Not Equal to Investment Source: Qatar does not report investment data

Recall that in 1973 the world experienced the largest oil shock in history. A sharp rise in oil prices represents a positive term of trade shock for the oil-producing countries and a negative one for the rest of the world. Back then, the GCC countries ran current accounts surpluses. The rest of the world suffered deficits. Wealth transfer took place from the oil producers to the rest of the world. The opposite was true in 2014. The GCC and most oil producers ran current accounts deficits. They had to borrow. Figure 7.5 implies that the GCC countries are creditworthy countries and could finance their current account deficits by borrowing in the international capital markets obviously because of their oil wealth (the GCC countries have accumulated a huge SWF in USD) and because their output is largely a continuously growing oil production. Creditors were willing to lend without a hitch, at a price, however, higher than the IMF’s. It is reasonable to assume that a country with a flexible exchange rate system and continuously growing economy could

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Figure 7.4 Saving – Investments Are Equal to the Current Account

borrow in the international market to finance its deficit – e.g., Canada, Australia, and New Zealand are examples of very long persistent current account deficits (see Obstfeld and Rogoff, 1994, p. 68; Collins et al., 1998). However, this is not the same for a fixed exchange rate system. In addition, the future might be different with an expected decline in the trend of oil prices because of anticipated global efforts to reach zero carbon by 2050 or even by 2060. Would the GCC be able to finance its current account deficits under such circumstances and a fixed exchange rate regime? It is uncertain because we do not have any precedent in history. Is net export equal to net foreign investment? NX = NFI ? Figure 7.6 plots the data. This identity holds in most developed countries. In Bahrain, net exports > net foreign assets (in local currencies), and the latter is zero since the oil price crash in 2014. For Kuwait, the net foreign investments ratio is above the net export – GDP ratio. Kuwaitis’ investments abroad exceed foreign investments in Kuwait. The gap

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Figure 7.5 GCC Countries Are Creditworthy

between net export and net foreign investment is wide. Oman is in a similar situation to Kuwait. Omanis net foreign investments – GDP ratio is above the net export – GDP ratio, but it is not negative. While the net export – GDP ratio is positive, it is significantly lower than net foreign assets. Positive net foreign assets since the 2014 oil price shock suggest that Omani investments abroad exceed foreign investments in Oman. Qatar’s net export – GDP ratio is above net foreign assets – GDP ratio for an extended period of time, and net foreign assets are negative, thus foreign investments in Qatar exceeds Qataris’ investments abroad. That was unexpected. Saudi Arabia’s net foreign investment is above the net export – GDP ratio over the entire sample from 1989 to 2019. It is about 60 percent of GDP. Saudis’ investments abroad are significantly higher than foreign investments in the Kingdom. The UAE data are from 2001. The Emirates’ investments abroad have been falling over time. Net

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Figure 7.6 Net Export and Net Foreign Assets Discrepancy

foreign investments are still positive, rising since the global financial crisis (GFC), and getting closer to net export – GDP ratio by 2019. Generally, the GCC would benefit more if foreign investments increase. Foreign investment has a positive effect on economic activity. An increase in investment in the GCC increases the growth rate of capital. Increases in the physical capital stock and advances in technology increase the productivity of GCC labor and other resources, pushing up the market value of workers, thereby increasing domestic incomes and wealth overall. However, foreign investments in the GCC are limited to certain sectors, mostly hydrocarbon. Foreign investments are attracted to productive sectors, which guarantee high returns, and to sectors that have highly skilled labor – i.e., skill-biased technical change. Labor, however, is highly unskilled in the GCC. The majority of imported labor is unskilled, and most of the highly skilled

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citizens prefer to work in the public sector, whose productivity growth cannot be positive. See Razzak and Bentour (2013) and Ben Jelili (2020), for example. Replacing External Debt by Domestic Debt Private saving will increase if people realize that future government savings are decreasing, so they react by increasing their own savings; however, it is not clear how people would know if the state’s savings were not fully published. Incentives also increase private savings. None of that is the case in Oman. We advocate a policy to replace external debt with domestic debt, a policy to encourage households to hold more government debt as a form of savings. There is an issue of whether or not sovereign debt issued by the government and held by households is considered net wealth to households. The wealth effect is about a change in the domestic price level such that a lower price level increases aggregate demand directly. In this case, consumption is not only a function of expected (permanent income) but also a function of wealth. Obstfeld and Rogoff (1994) suggested that the GCC’s consumption out of wealth is low. For the wealth effect to work, the stock of real wealth must be allowed to vary with the price level. A fall in the domestic price level increases the real value of the government debt, hence a rise in the economy’s aggregate wealth and consumption. However, there is an issue with treating interest-bearing government debt as net wealth to households. Interest payments on government debt are expected to be met with higher future taxes. The Ricardian Equivalence suggests that when the price level falls, the value of the real debt rises, and people would expect an increase in the present value of future tax liabilities. Barro (1974) argued, based on this argument, that government debt is not net wealth to households. However, (1) Oman does not have an income tax so far, maybe in the future, and (2) we are unsure whether the Ricardian Equivalence operates in an economy without taxes. However, non-interest-bearing government debt could be considered net wealth. Laidler (1985) argued that an increase in the real value of such debt outstanding carries with it no corresponding increase in tax liabilities. Therefore, even if the government institutes an income tax regime; a non-interest-bearing government debt would be considered net wealth. Omanis who save by holding government debt would be wealthier as the domestic price falls. This proposition remains an empirical matter and future research by researchers in the Sultanate, and the GCC countries should consider it. Such policy may well motivate expats to save in government securities rather than sending their savings home (remittances estimated to be in tens of billions of dollars annually.) This structural transformation of the debt implies that domestic debt affects national savings in the long run. Reforming the Pension Funds A good policy is one that motivates the increase in private savings. GCC citizens face a challenge that if the states cannot sell enough hydrocarbons at a breakeven price, the pension funds may not be available for the next generation. The pay-asyou-go system should be replaced with a save-as-you-go system, where everyone

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saves for his/her retirement. Here are the descriptions of the Singaporean and Chilean experiences. The Singaporean Experience Singapore, which is not a wealthy oil producer, but rather a very productive manufacturing small country, saves more than 50 percent of its GDP. The Central Provident Fund (CPF) was established in 1955 as a compulsory tax-exempt savings scheme under which every employee in Singapore is required to maintain a CPF account with the government. Note that in Australia and New Zealand, people hold savings accounts in commercial banks as they please. Singapore was much poorer in 1955 than Oman today. In 1955, Singapore’s GDP per capita (in 2019 USD) was 6,461. Oman’s GDP per capita was estimated to be 29,707 in 2019 (see the Conference Board July 2010 data). When Singapore started the savings scheme, every worker deposited 10 percent of the salary (minimum $50) with the employer (private or public) depositing a matching contribution of 10 percent. Today, the rates are 40 percent for each employee and the employer. It is amazing that the employer contributes 40 percent of the worker’s saving deposit; in New Zealand, it is no more than 4 percent, and in Australia, it could be 17 percent. Why would anyone reject a free contribution from his or her employer? Savings are tax-free. The rate could be age-dependent and income-dependent. The Singaporean government views the CPF as a policy instrument. The CPF contribution rates for employees and employers have been used as instruments for the macro-management of the economy. For example, during recessions, the government could cut the CPF contribution rate to reduce the cost of labor to help employers. It seems that the Singaporean idea that the employer matches the worker’s contribution dollar by dollar is rooted in efficiency wage theory, where higher wages imply more productivity, and more productivity means more profits for the employer. The employers take the contributions they make as increases in wages. We do not have empirical evidence supporting this hypothesis, but the Singaporeans have a successful savings program. The CPF is the most comprehensive centralized savings scheme in the world. It has 2.4 million participants. Each has a number of options: homeownership, health, insurance, stock market, etc. It means that one could save for any of these options. The CPF accumulated saving, with interest, may be withdrawn at the age of 55, or when the employee leaves Singapore permanently (with the exception of leaving for Malaysia). The Singaporean government modified the scheme after independence from Britain. Nevertheless, today, we could argue that the withdrawal age could easily be extended to 67. Variations in the rates of contributions depend on age added later to reduce the cost of hiring people above 55 and other considerations. Out of the current maximum contribution rate of 40 percent, 30 percent goes to the saver’s ordinary account. It could be used to purchase a home, make investments, and pay for education; 6 percent goes to a Medisave account, which could be used to pay for medical expenses; and 4 percent goes to a special account to pay for old age. Therefore, the CPF account holders could borrow from

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these accounts for buying a house, paying a university tuition fee, paying for medical treatment, and investing in Singaporean firms. For healthcare, part of the savings was separated into the Medisave account. Hospitals and government clinics can efficiently access online each patient’s Medisave information and complete the transactions. Today, most of the CPF funds are invested in government bonds. Capital assets provide income and increase the budget surpluses, which are then invested by the government. CPF generates sovereign wealth. The Chilean Experience Chile embarked on pension reform in 1981. The reform was a gradual replacement of the pay-as-you-go system managed by the government with defined but uncertain benefits by a fully funded system managed by the private sector. Corbo and Schmidt-Hebbel (2003) provide a careful empirical evaluation of the new system. They measure the effect on national savings, investments, employment, labor productivity, and TFP over the period 1981 to 2001 and reported a significant increase in national saving as a percent of GDP, investments, employment, labor productivity, and economic growth. Davis and Hu (2005) have a modified Cobb-Douglas production function with pension assets as a shift factor and investigate the direct link between pension assets and economic growth employing a data set covering up to 38 countries using a variety of appropriate econometric methods. They find positive results for both OECD countries and Emerging Market Economies (EMEs), with consistent evidence for a larger effect for EMEs than OECD countries. Bailliu and Reisen (1997) provide statistically significant evidence on the interaction between funded pensions and aggregate savings using international data, after controlling for country-specific effects and for other saving determinants that have been identified in earlier cross-country studies. They use panel data for 11 countries (both OECD and non-OECD). Building several proxies of pension wealth based on internationally comparable pension funds and life insurance data, they estimate the relationship between aggregate saving rates and pension wealth using OLS and 2SLS methods over the 1982–1993 period. The empirical analysis supports the predictions of a simple two-period, life-cycle saving model that incorporates tax treatment of pension returns, population heterogeneity, capital market imperfection, and various features of pension design. They argue that it is crucial to stimulate a positive saving impact of funded pensions from the low-saver group and to limit the negative income effect on savings by the highsaver group that emanates from the higher implicit rates of return on tax-exempt funded pensions. This requires that funded pension schemes are mandatory rather than voluntary, that tax exemptions on pension returns are limited to low savers, and that it is discouraged to borrow against the accumulated mandatory pension assets; otherwise, funded pension schemes will fail to stimulate savings. Birkeland and Prescott (2007) provide some evidence that issuing debt (not external borrowing) is an optimal policy. In the case of early retirement and no population growth, the needed government debt should be large. The idea is that young workers buy the government debt as a form of savings, which they can

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sell when they retire to finance retirement consumption. This form of savings plan replaces the existing pay-as-you-go retirement scheme. Young workers can always set aside x percent of income to finance the government budget deficit, increase their own private savings, and pay for retirement consumption. This policy satisfies the long-run identity we analyzed earlier, deepens the financial market, and restores the government budget constraint. Further, a rising wealth could increase prices and reduce future real debt. Sargent and Wallace (1981) and Woodford (1995), for example, make the argument for the fiscal policy determination of the price level, whereby the increase in debt over time, without a change in the future budget (i.e., a change in taxes or spending), induces a wealth effect, and as a result, the aggregate demand increases. If the aggregate demand shifts up without a change in aggregate supply, the price level increases, and real debt falls to its initial level over time. The NCSI in Oman published a few household surveys, which have useful information about average monthly incomes and income distribution. Unfortunately, the last published survey was for 2011. Scenarios of various compulsory savings plans are shown in Table 7.1. Scenario I assumes that all workers, Omanis, and expats participate in the saving scheme by saving 30 percent of their labor incomes with the employers matching their savings fully. The NCSI reports that the average household monthly income (excluding imputed rent) was OMR 1,024 in 2011. The CBO Annual Report (2014) reports the number of Omani and expats employment in the public and the private sectors. In 2013, the Omanis working in the public sector were 180,737, and expats were 30,392. The total was 211,129 employees in the public sector. The number of Omanis working in the private sector was 181,860, and the number of expats was 1,527,241 workers. The total number was 1,709,101 workers. Thus, the Omanis make up 19 percent of total employment in both the public and the private sectors in Oman while the expats make up the rest, 81 percent. If one assumes that the expat workers do not send remittances abroad, the total additional private compulsory savings scheme yields OMR 9.9 billion a year. If it is assumed that the expat workers continue to transfer 33 percent of their income abroad in remittances, the savings will be about OMR 7.5 billion. Scenario II assumes that the savings rate is 20 percent instead of 30 percent. Under this scenario, the savings would amount to OMR 6.6 billion a year. If expats continue to transfer 33 percent of their income abroad, the saving will be about OMR 4.7 billion a year. Scenario III includes the top earners only – i.e., the workers whose incomes are more than OMR 1,100 a year. The Omanis dominate this population. About 40 percent of earners in this bracket are Omanis. The expats make 16.3 percent. The idea is that workers who make less than that income may find compulsory savings harsh or unjustified. Under this scheme, the savings are OMR 3.1 billion. Again, it is assumed that the expats do not transfer 33 percent of their incomes abroad in remittances. If they do, the savings will be lower. Scenario IV includes workers with income brackets from OMR 500 to +OMR 1,100. Total savings amount to OMR 4.9 billion. This option is problematic because it might give an incentive to employers to fire workers with income above OMR 500, not hire workers with income higher than OMR 500, or both.

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Scenario V permits employers to match up to 50 percent of the employee’s savings. For example, under the 30 percent saving rate scheme, the employer would match 15 percent of the worker’s contribution only. This scenario yields a saving of OMR 7.5 billion a year. The saving scheme is most likely to give incentives to expats to participate and reduce their remittances. Remittances exceed OMR 4 billion a year. The analysis of restructuring saving perhaps requires some analysis of the banking sectors; however, it is not the focus of this book, and the data are not available. There is no rigorous macroeconomic research in this area. There is, however, some banking research, which has a narrow focus. The IMF had one paper on the GCC banking in the aftermath of the Global Financial Crisis – GFC (see Abdullah Al-Hassan et al., 2010), and the other information is taken from the Financial Stability Reports published by the central banks regularly. They show a rosy picture. A household savings scheme requires an efficient banking system to mobilize and direct savings into productive investment projects. The banking system in the GCC in general is conservative and not involved in economic development. The concentration rate is high. A few people own most of the assets. It is a stable sector; however, it is very well capitalized and not engaged in very risky lending and other financial activities. It relies on guaranteed government deposits of oil revenues, and the deposits of the wages of the employees in the public sector. It does not pay any interest on deposits while deposits are the main source of the loans; therefore, the interest spread is wide. Most of the loans Table 7.1 Mandatory Savings Scenarios

1

Total Public Employment1 Omanis Expats

211,129 180,737 30,392

Total private employment Omanis Expats

1,709,101 181,860 1,527,241

Omanis’ average monthly household income – (OMR)2 Expats average monthly household income – (OMR)2

1,024 649.9

All workers participate; saving rate 0.30; employers match all contributions Scenario I Annual income for Omanis3 Annual income for Expats3 Omanis share in total employment Expats share in total employment Omanis’ savings 4 Expats’ savings Average savings (including employer’s share)5 Total savings

12,288 7799 0.19 0.81 3,686.40 2,339.64 5,187.90 9,961,956,105.84

(Continued)

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Table 7.1 Continued 2

All workers participate; saving rate 0.20; employers match all contribution Scenario II Annual income for Omanis Annual income for Expats Omanis share in total employment Expats share in total employment Omanis’ savings Expats’ savings Average savings (including employer’s share) Total savings

3

12,288 7,799 0.19 0.81 2,457.60 1,559,76 1,729.30 6,641,304,070.56

Only top earners (OMR +1100) participate, saving rate 0.30, employers match worker’s Scenario III Annual income Omanis Annual income expats Omani employment share Expat employment share Omani savings Expat savings average saving Total savings6

13,200 13,200 0.19 0.81 3,960.00 3,960.00 3960 3,122,539,833.60

Only workers in the income brackets > 500 OMR a month participate in the savings scheme 4

5

Scenario IV Workers in income bracket 500–599, savings rate 0.30, employers match worker’s Annual income Omanis 6594 Annual income expats 6,594 Omani employment share 0.19 Expat employment share 0.81 Omani share in this bracket 0.074 Expats share in this bracket 0.066 Omani savings 10,085,088.76 Expat savings 164,726,811.25 Total 349,623,800.01 Workers in income bracket 600–599, savings rate 0.30, employers match worker’s Omanis’ employment share 0.078 Expats’ employment share 0.055 Total 349,636,833.93

(Continued)

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Table 7.1 Continued 6

Workers in income bracket 700–799, savings rate 0.30, employers match worker’s Omanis’ employment share 0.127 Expats’ employment share 0.078 Total 616,859,960.26

7

Workers in income bracket 900–1099, savings rate 0.30, employers match worker’s Omanis’ employment share 0.102 Expats’ employment share 0.05 Total 504,548,717.23 Total savings (3 + 4 + 5 + 6 + 7) 4,943,209,145.04

8

Scenario V All workers participate, savings rate 0.30 but the employers match only 0.15 Total 7,476,005,727.92

1. 2. 3. 4. 5.

Data source: CBO Annual Report 2014, Table 2.5 NCSI the household expenditure and income survey (2011), Table 12, page 27 Multiplies monthly income by 12 30 percent of income Average savings times the share of workers for Omanis and expats plus the same amount as the employer’s match contribution 6. Average worker’s savings including the employer’s matching contribution are multiplied by total employment Expats are assumed not to send remittances abroad

support simple businesses and real estate purchases. It is important to note that the GCC banking system withstood the Global Financial Crisis – GFC, not because it is remarkably efficient but because it is highly regulated and conservative. I believe that the evidence is supportive of a mandatory personal savings scheme and a full reform of the pension systems. Most of the advanced countries are moving in this direction. The total reliance on oil revenues will be obsolete within our lifetime. Savings will be needed for economic growth in the zero-carbon world, and the governments of the GCC can borrow domestically to finance its deficits. However, the argument for a mandatory savings scheme has not received attention from the CBO. I speculate that the policymakers are hoping for the price of oil to go back to pre-2014 levels, which would solve the debt and the current account problems. Many policymakers in Oman interpret the current economic difficulty as an “interruption” – i.e., a temporary shock. We know from history that oil price shocks are highly persistent.

Productivity In addition to the declining income from hydrocarbon and declining saving – GDP ratio, and falling savings growth rates, negative productivity growth is a major challenge to the GCC countries. Although the GCC is not a major industrial area, and

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most of its growth is derived from trade, especially in hydrocarbons, TFP growth has been negative over the period 1990–2019, as depicted in Figure 1.3. It is quite reasonable to assume that the GCC countries’ output is measured with errors since half of the economies are services. Constantly understating output reduces productivity. Nonetheless, the implied average growth rate of technical progress, which we estimated from a simple Solow growth model, is negative over the same period. The decline is very large in magnitude in the two super-rich nations, Saudi Arabia and the UAE. These statistics are troubling especially for the zero-carbon future. In addition, the data show that labor quality growth rates are negative, and the marginal productivity of labor has been falling everywhere, but it is stagnant in Saudi Arabia and the UAE. The marginal product of capital has been falling except for the UAE, which remained stagnant. The marginal products of labor and capital are computed from taking the derivatives of real GDP with respect to labor (working-age population ages 15–64) from a Cobb-Douglas production function like the one we used in this book earlier and the derivative with respect to the stock of capital. These are ˜1 YL and ˜ 2 YK , where α1 is the share of labor and α2 is the share of capital, Y is real GDP, L is labor, and K is capital. The share of labor is total compensations to employees/GDP ratio, which is reported by the Penn World Table 10.0. The share of capital α2 is assumed to be 1−α1 for simplicity – i.e., the Cobb-Douglas production function is the constant return to scale. We have already tested this earlier in this book and showed that the constant return to scale assumption holds in the data. Declining productivity, savings, and increasing debt is an unpleasant combination, especially in the non-oil future. Rising debt could reduce the ability of the country to deal with adverse shocks and international crises. Investors may also be less confident in investing in countries with high debt. The real value of the currency is affected by the investors’ view of them – denominated assets; hence, there is an additional concern for a currency crisis.

( )

( )

What Other Policy Increases Labor Productivity and TFP Other Than Tax Policy? In the work-leisure model, which we presented previously, taxes reduce labor supply and labor productivity. Foreign direct investments and trade would have something significant to add to productivity. Razzak (2009) provides evidence for the effect of trade on economic growth in a number of Arab countries. Razzak and Bentour (2013) provide evidence for foreign direct investments’ effects on some Arab countries. Policymakers in the GCC seem to know that very well. However, foreign direct investments are attracted to countries where labor is skilled and able to understand technology in order to produce skilled-intensive goods for the export markets. There are issues with the education systems and skill formation in the GCC, which need to be understood and addressed. The World Bank has studied this particular sector in many GCC countries but it is hard to see that it made a difference. It is unclear what the policies are or, most importantly, what the outcomes are. Education and labor policies are connected, and they could not be separated.

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Table 7.2 Average Growth Rates of Labor Market Indicators 1990–2017

Bahrain Kuwait Oman Qatar KSA UAE

1990–2019

a0

n

0.04 −1.03 −0.01 −0.57 −2.10

0.047 0.044 0.047 0.035 0.065

δ 0.03 0.05 0.03 0.04 0.04

g

Labor Quality

TFP

−0.03 −1.09 −0.09 −0.65 −2.25

0.70 0.00 0.10 −1.50 0.60

−0.90 −1.00 0.20 −2.30 −1.30 0.50

a0 is the estimated constant term in the Solow growth model, which has the right sign (except for Bahrain). ln

   ln  A   gt  Yt Nt

0

 

 ln St   ln n  g     , where Y is real GDP; N is   t t t 1 yt 1

working-age population (age 15–64); St is nominal saving; yt is nominal GDP; n is the growth rate of Nt; ġ is the growth rate of technology;δ is the rate of depreciation of the stock of capital; A0 is exogenous level of the stock of technology. δ is the depreciation rate taken from the Penn World Table 9.0. ġ is the growth rate of technology = α0 – n – δ. Labor quality is a contribution to GDP growth, and TFP data are from the Conference Board.

The GCC countries should reform their labor market institutions, labor laws, and policies to provide incentives for young, educated people to work in private activities and jobs. Without an increase in labor productivity and TFP, the future will be very challenging. Table 7.2 reports some labor market indicators – namely, the estimated constant term in the Solow model, the growth rate of the workingage population, the depreciation rate, the rate of growth of technical progress, labor quality, and the TFP in the GCC countries over the samples 1990–2017 and 1990–2019. These deep parameters are problematic. The growth rate of technology is negative, labor quality growth is poor, and TFP growth is negative. There is an argument for reviewing the financial law and other aspects of Islamic laws (Waqf), which have implications for economic growth. This law goes back to the Ottoman Empire and is widespread in the GCC, Iraq, and other Middle Eastern countries. The amount of money in these funds is unknown, and these funds do not operate under common transparency laws; there could billions. Imagine that this massive fund could not finance any investment project. These funds are set aside for charitable purposes and managed by the government. The legal system has important implications for economic and development growth. We are unsure of whether or not the GCC governments paid attention to this issue from an economic standpoint. There is evidence that a country whose legal system is based on the English common law as opposed to civil law and French law can grow faster. The civil law is also referred to as European continental law. The civil law system is derived mainly from the Roman Corpus Juris Civilus, which is a collection of laws and legal interpretations compiled under the East Roman (Byzantine) Emperor Justinian I between A.D. 528 and 565. In some countries, the civil law systems are based on multiple codes. The main feature of civil law systems is that the laws are organized into systematic written codes.

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In civil law, the sources recognized as authoritative are principally legislation and custom. Common law is a type of legal system often synonymous with “English common law.” It reflects Biblical influences, as well as the law systems of the Romans, Anglo-Saxons, and Normans. The foundation of English common law is “legal precedent” – stare decisis, which means, “Standby things decided.” In this, judges are bound in their decisions in large part by the rules and other doctrines developed – and supplemented over time – by the judges of earlier English courts. French law is a systematic written civil law. Prior to the French Revolution (1789– 1799), France had no single national legal system; the systems varied geographically. Reforms began with the Napoleonic Civil Code during the reign of Napoleon I in the first decade of the 19th century. French law distinguishes between “public law” and “private law.” Public law refers to the government, the French Constitution, public administration, and criminal law. Private law covers issues between private citizens or corporations. The 1980s witnessed some changes, such as the decentralization laws, which transferred authority from centrally appointed government representatives to local representatives. Most of the Arab countries’ civic and commercial law systems are derived from French law. We believe that Oman falls into that category. In addition, there is Islamic law in Oman. It operates in tandem with a civil law system. Islamic law is the Sharia. Research on the effects of the law system on economic development is necessary. These laws might have significant effects on economic growth and need to be reviewed from an economy’s standpoint (see Mahoney, 2000; La Porta et al., 1998). A thorough review of the law, and how it influences the economy, is a potentially important project for researchers. Kuran (2004) is a very important contribution to this literature. We recommend it for students who are interested in the effect of the legal system on economic growth; it provides reasonable arguments for the failure of developments in Middle Eastern countries. He identified three institutions that generated evolutionary bottlenecks. The first is the Islamic law of inheritance, which inhibited capital accumulation. The second is the strict individualism of Islamic law and its lack of a concept of corporation, which hindered organizational development and contributed to keeping civil society weak. The last one was the waqf – Islam’s distinct form of trust, which locked vast resources into organizations likely to become dysfunctional over time. He argued that these three institutions did not necessarily create economic disadvantages at the time, nor did they ever cause an absolute decline in economic activity. However, they became handicaps by perpetuating themselves during the long period when the developed world created modern economic institutions. Essentially, the Islamic countries lagged behind and stuck with old inefficient institutions. We are unaware of any GCC judicial reforms at all.

Other Research Issues Pertinent to Saving and Productivity It has been shown that there are policy concerns regarding the economies of the GCC countries over the business cycle and some longer-term structural challenges. The evidence of rising external debt, which is relatively high in Bahrain and Oman, is alarming. The twin deficits – namely, the budget and the current account deficits – in

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at least five of the GCC countries suggest that the GCC governments need to make some significant and immediate fiscal adjustments. However, they would have to make some structural changes too. The future, although difficult to predict, is not so rosy for oil producers in general. There will be challenges to maintaining a breakeven price of oil. There is a change in consumers’ tastes. More people demand greener and less fossil fuel energy. Climate changes have persuaded consumers and producers of goods and services to change production technology to greener ones. COVID-19 is an alarming bell; it confirmed the fragility of the global economy and indicated that future pandemics could be menacing. These shocks are persistent, and pricing future risks is a daunting task. One could safely predict a decline in the global demand for fossil fuel in the long run, but it is hard to say now by how much demand will fall in the future because the elasticity of the future demand curve for oil is unknown and because of the inability to predict the magnitudes of the decline in prices. Nonetheless, declining future global demand for oil and lower average trend prices are highly probable and beyond the control of OPEC or any oil producer. It is clear that introducing new taxes or increasing current taxes would increase revenues to a certain extent, but that would not be without adverse macroeconomic effects. In fact, new taxes will add more problems. We have provided evidence that taxes would not be good for the economies of the GCC countries, not now at least. We showed using counterfactual scenarios and dynamic stochastic projections over the next ten years that the introduction of an income tax in Oman, for example, reduces output and the supply of labor, and a VAT would increase macroeconomic volatility significantly. Reducing government expenditures to levels consistent with real GDP per person growth or the current account surplus though seems the reasonable thing to do. However, the ultimate question is what public expenditures to cut? Every time the IMF and the World Bank visited Oman, they suggested reducing public-sector wages and defense spending. Arbitrarily reducing the public sector’s wage bill is problematic because the social cost of doing so is very high for obvious reasons. Most importantly, however, public-sector wages are not high after accounting for skill levels. Although we have not empirically studied the taxation of capital and wealth, we should say that it is a long-standing controversial topic in the public debate. The argument centers on equity and efficiency. The literature is vast and complex. To answer questions pertinent to policy such as how to tax different assets owned by different people and with different elasticities, how to account for shifting between capital and labor income, and how to take into account heterogeneity in individual preferences or returns, as well as non-linear taxation and more complex social fairness and equity concerns see, for example, Saez and Stantcheva (2018). No research is available for the GCC countries; therefore, making policies without carefully constructed evidence is problematic. We believe that more research is needed in this area. Let us think about rational spending. Where and what expenditures should the government start with? Increasing savings and reducing the imports bill should be the first variables the government focuses on. The Balance of Payment accounts are hard to maintain under fixed exchange regimes.1 This is challenging though because importers are politically dominant and rich merchants would not like to do

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so. They are the same group that stands against manufacturing or technological change to advance industrial objectives. We always come back to Mokyr (1990, p. 16) who documented the oppositions to new technologies throughout history. There are powerful people with entrenched interests in the status quo who would oppose progress. However, savings would increase if the GCC countries imported generic goods – e.g., import generic medicines rather than original ones – and allow for and provide incentives for parallel imports. Parallel imports are goods that are produced under copyright protection in one market and which are then imported into a second market without the authorization of the local copyright owner – for example, CDs, books, magazines, mobile phones, clothes. There is evidence that Australia and New Zealand, for example, made significant savings in import costs when they allowed for parallel imports. One must wonder why fully subsidized imported medicines could not be replaced by cheaper imported generic brands. Finally, you could imagine that government-imported capital purchases could also be trimmed (trucks, cars, equipment, etc. For example, government departments do not need to have huge fleets of expensive luxury cars and trucks and could do with fewer cars and cheaper brands), and the military purchases, of course, but that has more than a simple economic explanation. The size of the bureaucracy is another structural issue; it must be dealt with more seriously and effectively. A more reasonable policy than cutting public-sector wages is to create incentives for people to seek alternative jobs in the private sector. Kuwait tried, but without a lot of success. Saudi Arabia and Oman have been trying for a decade; however, some jobs remained unoccupied by the locals. The education systems have not supplied all the needed skills. Similarly, a policy to remove the barriers to entry to the markets is essential for the economy to grow. Ending monopoly power and licensing privileges are structural issues. This is again a difficult political reform. The policy should seek to level the playing field. Reducing benefits, not necessarily wages, in the public sector is a reasonable first step. Sensible structural reforms may end the state monopoly on land. Public landownership could be transferred to people who do not work in public-sector jobs as an incentive to leave government jobs. We would also emphasize the use of Active Labor Market Policy in cases where they are effective the most, in modernizing the GCC countries’ labor markets, for example. Although we argued against the introduction of income tax, particularly when the economy is fragile, we know that when all structural wrinkles are ironed out in the future, there should be an argument for income taxation as a policy instrument to alter the after-tax wage rate (income) instead of reducing income itself. The equilibrium condition requires the marginal productivity of labor is equal to the after-tax wage rate – i.e., mpl = (1 − ˙ ) w. In developed countries, the macroeconomic data are fully consistent with this microeconomic condition (see, for example, Razzak, 2015) for an empirical analysis of the U.S. economy). In the future, the government could change the tax rate on labor income t instead of reducing w such that it is higher on public-sector jobs than jobs in the private sector. Thus, people who seek comfortable jobs in the government must pay higher taxes. One would hope that most highly skilled citizens would be motivated to take up jobs in the private sector since the benefits and the after-tax

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wages are better than in the public sector. There are still people who prefer to be civil servants, even though they are financially worse off. This might actually increase the efficiency of the public sector. There are more policy issues, which require some further research, and policymakers should consider carefully. One component of the government’s fiscal adjustment plan to deal with the effects of the oil price shock is the increase in taxes on corporations and the introduction of a consumption tax (VAT). The standard result in the literature is that more taxes imply a higher deadweight loss and greater reduction in welfare. In addition, taxes will have a negative impact on growth, which will make the sustainability of the debt harder because the sustainability gaps are sensitive to the interest rate (the interest rate used for discounting is the ratio of the nominal interest rate/growth rate of GDP). Furthermore, if the level of real GDP falls, tax revenues are likely to fall at some point in time (i.e., the Laffer curve). The question is whether the increase in corporate tax rate and the introduction of consumption tax will worsen the sustainability of the debt or not? Further research in this area is needed. We believe that a reasonable tax on the consumption of luxury goods is fine for the GCC. However, increasing taxes on corporations hinders investments, foreign direct investments, and lowers growth, for example (Akcigit et al., 2021). Taxing labor income reduces labor productivity, which is most needed for the future non-oil economy. Another important policy issue is pertinent to population projections. Adequate sustainability analysis requires long-run population projections in order to assess the government future fiscal position. Future liabilities of the government is a major issue, hence the fiscal gap. The fiscal gap is a measure of all future commitments of the government. For GCC, this is crucial because the role of the state in the economy is significant. The government pays for education, health, infrastructure, and, most importantly for the debt issue, it pays for retirement. For example, the World Bank data for population projections suggest that by 2050 Oman’s birth rate will fall from 19.32 (per 1,000 people) to 17.4 percent. The working-age population (age 15–64) as a percent of the total population will fall from 76.9 percent to 66.07 percent. People aged > 65 years in population will increase from 3.86 percent to 20.43 percent. In addition, life expectancy at birth rises from 77.32 to 84.30. Therefore, Omanis are expected to live longer, but more people will be old and retired, and fewer people are born today. How will the government pay its future liabilities if the price of oil does not increase and productivity does not increase? Similar projections are found for the rest of the GCC countries. Many of the policy issues are tangled, which makes the macroeconomic picture more complicated. Take the question of whether the rising debt affects monetary policy. What happens if the interest rate, the real exchange rate depreciation rate, and the current account change significantly? Would the debt burden increase if the currency depreciates in real terms? GCC countries have to service the debt in USD. Another factor that affects the interest rate and the real exchange rate is risk premium. Risk premium is a non-linear function of the debt level itself. Ostry et al. (2010) show that the cost of borrowing increases with debt. Risk premium slowly increases for a small debt-to-GDP ratio and increases rapidly if the ratio

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exceeds 1.5 (150 percent of GDP). Is a fixed exchange rate system best suited for sustaining an increasing debt level? Bernanke and Blinder (1988) show the effects of a positive term of trade shock (an increase in the price of exports relative to the price of imports) on the economy of a commodity-exporting country. The main assumption of their model is that the interest rate is endogenously determined, so monetary policy is held constant. The term of the trade shock affects aggregate demand through the increase of domestic bank lending, a reduction in the risk premium, and an increase in the money supply. Money increases in order to allow the real exchange rate to increase (real depreciation) and to balance the current account. The results of these changes are that income is higher and the interest rate is lower after the shock. The terms of trade ensure a balanced current account at a higher level of real GDP. Real appreciation leads to an increase in investments associated with more credit. There is a strong reason to believe that the opposite can happen with a negative term of trade shock, such as the recent decline in oil prices. One could expect a shrinking credit supply, a contraction in the money supply, and possibly a higher risk premium. The anticipated reduction in the real value of expected future oil exports reduces the potential collateral of the country, which might make it costly to borrow. This in effect can cause real depreciation of the currency, which could potentially be a very serious policy issue for the GCC countries. As the real exchange rate increases (real depreciation), consumer confidence about future income may fall, and banks become unwilling to lend or increase the price of lending. For GCC, current monetary policy arrangements are unable to deal with these adverse effects, except perhaps through regulations and macro-prudential policies. How much have the GCC countries thought about these issues?2 There is also an issue of crowding out. By how much the debt crowds out private capital in the short and long runs. Modeling this is very complex, requiring data and many assumptions. The analysis requires detailed long-term population projections. The increase in external debt leads to a higher cost of borrowing for everyone. It is a tax on future generations. Suppose that taxes and fees increase (or rent from oil declines) to deal with the government fiscal consolidation plan. The increase in taxes (or the decline in oil rent) would be equally distributed across people of different ages such that each person’s income will decrease by the amount of the interest payments per capita in each period in the future. People will reduce consumption in each period by the same amount (consumption smoothing). Thus, both consumption and income fall equally. Investment spending should also fall; therefore, capital falls with debt one for one – i.e. complete crowding out. Finally, we did not discuss monetary policy and monetary structural institutional arrangement issues because we recognized the Mundell’s Tri-lemma (the Impossible Trinity) when deciding on the monetary arrangement. Under a fixed exchange rate regime and free capital mobility, a monetary policy is not independence. Furthermore, a monetary policy in the GCC countries is ineffective. Put simply, a monetary policy that fixes the exchange rate firmly cannot affect the real economy – i.e., it cannot affect real output, unemployment, domestic inflation, etc. A monetary policy cannot target both foreign and domestic prices at the same time.

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The peg to the USD-induced inflationary spells in the GCC countries in the past via the spillover effect of imported goods. The central banks could not do anything to reduce domestic price inflation. Typical monetary policy instruments are the shortterm overnight interest rate and the quantity of money, neither one could be used in the GCC countries to affect real output. How could the central bank stimulate aggregate demand in case of a recession? Typically, it either lowers the overnight short-term interest rate or increases the supply of money or money growth. However, doing so threatens the peg, which is the monetary policy regime’s sole objective. That is not saying that fixing the exchange rate is not a viable system. It is in fact a very useful nominal anchor. However, in a country that produces a single commodity – i.e., oil – the fixed exchange regime may be inefficient because it ties up the hands of the policymaker. Furthermore, we know from experience that the fixed exchange rate regime could not be maintained forever unless vast foreign reserves are kept in order to deter speculators when the Balance of Payments problems occur and persist. This is the world’s experience with a fixed exchange rate. The Europeans would have kept it, but they simply could not. So far, Saudi Arabia, Qatar, the UAE, and Kuwait have foreign reserves that could protect them from currency speculators who might attack the GCC countries, but Oman is vulnerable. And what would happen in the future when the price of oil plummets permanently because the rest of the world decided to move away from oil? Therefore, a fixed exchange rate to the USD may not be the best system for the 21st century with low oil prices and changing international monetary climate. Research is needed to find out an alternative efficient financial arrangement.

Notes 1 The GCC countries do not publish sufficient budgetary data; however, in general, there are areas where cuts appear logical and maybe doable. The current account imbalances suggest that capital spending exceeds savings, and the trade account shows that imports could exceed exports in some bad times. The capital account in the balance of payment account (BOP) includes a line called “net errors,” which looks significantly high in countries like Saudi Arabia, Qatar, and Oman too. These figures are pluses and negatives and they mean that the account would need that much more or less to be balances. A negative error obviously represents a capital fly. Economists do not usually analyze these errors, but they are peculiarly high in certain times. Most people know the effects of negative oil price shocks. The typical response is waiting and watching for more information to arrive and analyze and maybe hope that the oil price climbs up again. More information suggests that the governments are struggling to keep up with sliding oil revenues. People also anticipate that the governments may consider either devaluing the currency or cutting wages. Therefore, many people send their money out or put it in foreign currency accounts. These figures may be the ones showing in the “net errors” in the BOP account! These net errors in the BOP accounts are smaller in countries with floating exchange rate regimes and inflation targeting. 2 Regulations could be very costly if they are not fully evidence-based. Coffey et al. (2020) estimate the effects of federal regulation on the value added to GDP for a panel of 22 industries in the United States over a period of 35 years (1977–2012). The incidence of regulations on industries is based on a text analysis of federal regulatory code. They showed that regulatory growth since 1980 cost GDP $4 trillion in 2012 or about $13,000 per capita.

8

Final Remarks

People take different roads seeking fulfillment & happiness. Just because they’re not on your road doesn’t mean they’ve gotten lost. H. Jackson Brown, Jr. (1940–) American author

Economic development is endogenous. Every country has its own underlying historical, cultural, and moral drivers that the political and economic institutions rest on. The GCC oil-producing countries are unique. The society is tribal. In exchange for absolute power, the monarchs distribute oil rent to the people and the tribes. Furthermore, the government pays for education, health, pensions, and infrastructure. Everyone benefits. Add to that the very expensive price of Western protection to maintain political and economic stability. In essence, they built and followed their own road to fulfillment and happiness. The future of oil, however, will be different from the past; hence, the trade-offs will change. Expectations matter in macroeconomics. A future scenario of a persistently lower than average expected price of oil, even with temporary fluctuations around a lower price trend is realistic, even if the state of zero carbon is not achieved by 2050. A permanently lower oil price for GCC countries in the long run is not an implausible scenario. The GCC countries are oil dependent. The share of oil in output is large, and its production and global oil consumption share a common long-run trend. The share of oil in revenues is high too. Lower oil prices reduce their oil revenues. With spending not adjusted to reflect the changing reality, persistent future budget and current account deficits remain. Eventually, external debt becomes unsustainable. Further, the increase in the external debt is a tax on future generations. All that means the GCC countries, especially Bahrain and Oman, need current fiscal adjustments and structural changes. However, there are some principles that helped many countries’ economic developments in the past, which the GCC governments may want to consider. In this book, we used readily available data to provide evidence-based policy analysis. We showed that oil production and global oil consumption also have significant short-run dynamics effects. We used counterfactual experiments to show the effects of a counterfactual severe decline in global oil consumption on the GCC economies. Based on these findings, we answered three specific questions. First, DOI: 10.4324/9781003288282-8

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we examined scenarios of debt sustainability for the highest two debtors, Bahrain and Oman. Second, we estimated an optimal level of government spending for all GCC countries. We had two specifications for optimality. One assumes that the optimal level is one that maximizes real GDP per capita growth. The other is the level that balances the current account. Third, we examined counterfactual scenarios of the effects of income and consumption taxes on inflation, output, the labor supply, and inflation. We showed that the GCC government spending is significantly higher than the estimated optimal level. The introduction of an income tax is not a good policy from a macroeconomic perspective, especially when the economy is weak and the political institutions are fragile and subject to many external negative shocks. VAT reduces consumption in general, has an adverse distributional impact on low-income people, and increases the volatility of macroeconomic variables significantly. There is a need to reduce the budgetary breakeven price of oil, reduce public expenditures, and increase revenues by finding another source of income, or all of the above, and start sooner than later. In the long run, however, we strongly emphasize that the problem is not only a public finance problem; fiscal reforms are necessary but not sufficient conditions. There is probably a need for structural and institutional changes such that changes in the incentive structure must be taken more seriously than in the past (Acemoglu and Robinson, 2006a, 2006b). For example, one should not focus on reducing public wages but rather on reducing the size of the public sector relative to the private sector – i.e., smaller bureaucracy. There are indications that there is an overwhelming global desire to replace fossil fuel as the main source of energy in advanced and emerging countries because people seem to believe that the production and consumption of fossil fuel adversely affect the environment. There is an overwhelming belief, whether it is evidence-based or not, that hydrocarbons caused the current adverse climate change. Most of the use of hydrocarbons is in the transport sector. The future is in alternatives such as solar, wind, geothermal, and nuclear powers. It is clear that there is climate change, which has ignited real political and popular issues. Now, climate change has become an economic issue too; people are certain they could make money and profit from alternative energy. Therefore, climate change is a real fixture of the future economy. The implication is that the GCC oil-producing countries would have to make many adjustments now in order to keep going in the long run. The GCC policymakers know that. The GCC problems are numerous, however. In addition to the economic reliance on oil, they have declining household savings, low productivity growth, a large unskilled foreign labor force, inefficient institutions, and a combination of non-evidence-based economic policies. These problems may have negatively affected the incentive structure, which would lower the 21st-century path of income growth relative to the past century. To progress in the 21st century, the GCC governments need structural reform in addition to evidence-based policies. The reform of the economic institutions and the revision of economic policies in any way would not guarantee progress. There is probably a need for political reform to begin with. Take for example the Eastern European countries; their political system changed first after the collapse of the Soviet Union. People agreed on new political institutions, and then they

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subsequently reformed the economic institutions. These changes are endogenous. Every country has its own underlying historical, cultural, and moral drivers that the political and economic institutions rest on. Another example of economic reform is New Zealand, which is a Western democracy with a judicial system based on common law. It reformed its old economic institutions and policies in 1984. In a nutshell, New Zealand removed capital, price, and wage controls; privatized public firms; floated the currency; opened international trade; reduced taxes; and targeted inflation. Its reform process was less disruptive than the Eastern European countries. A good thing is that the GCC is already and largely a market economy, with flourishing international trade, free capital mobility, no price and wage controls. However, the laws are different and monopoly powers are evident. The culture is also different too. The GCC should not underestimate the impact of the laws on economic growth. Endogenous cultural drivers are important for economic development. A tough stance on corruption and the curbing of monopolistic behavior is necessary for well-functioning price and wage mechanisms, free market, and free society. Monopoly (in industry, in labor market, and in government, differences notwithstanding) limits the freedom of exchange, which is the essence of the free-market economy, and distorts domestic prices and wages. Political reform would pave the way to new modern economic institutions. On the fiscal side, a modern tax system to generate revenues could replace the decline in oil revenues; eliminate the reliance on volatile oil prices. However, careful research in taxation is necessary, and it is very unwise to impose taxes on people without a real formula for participation and representation. These reform issues are hard because those who have entrenched interests in the status quo will resist. To ensure progress in the long run, household savings is needed to generate the domestic stock of capital required for growth. We proposed a mandatory savings scheme a la Singapore and Chile because empirical evidence shows that it is an efficient way to accumulate capital and to resolve the anticipated future pension schemes’ problems associated with the aging population and labor market issues. Real GDP per capita growth in the GCC has been negative for a long time. Growth is a function of savings and endogenous technical progress. A system of thrift rather than a system based on consumption, or worse on conspicuous consumption, was essential to building the market economies of the advanced countries. Thrift generates capital and investments needed for growth. The GCC will face a problem if the stock of capital declines because our estimate of the share of capital in output is significant. Thus, capital drives GDP growth. Labor’s contribution is small. Therefore, they need adequate policies to motivate more household savings. The current pay-as-you-go pension system may fail in the future. Many nations decided to move to a save-as-you-go pension system such as Singapore, Chile, and many others because they recognized the impossibility of maintaining the solvency of the pension funds. Productivity growth has to increase too. Technical progress requires skills, research efforts, and the production of useful ideas, useful in the sense that they could be used to produce new goods and services, which have commercial values. It would not be helpful if the GCC countries continue to rely on unskilled imported labor in the 21st century. Labor market reforms are

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essential to begin to produce skilled-intensive goods. That may require significant institutional reforms in addition to activist labor policies to manage employment. New flexible and enforceable labor laws that are consistent with international standards seem necessary for the 21st century. Skill-biased technical change means that foreign direct investments will find the GCC more attractive in the long run. Reforming education is difficult because people believe that education is a privilege, a birthright, and free for everyone, but this is untrue for all types of education. There is no doubt that free education is required to maintain a good society and democracy, elementary and high school for sure, but not tertiary education. People respond to incentives (Easterly, p. 141). Subsidized tertiary education is inefficient because good and bad students are fully equally subsidized. Although spending on education has been increasing, it seems very difficult for the GCC governments to reform the education system to raise the quality of human capital. Human capital growth has either negative or no effect on real GDP per capita growth in the GCC. A policy idea that belongs to the Nobel Laureate Edmund Phelps is that the government could give wage subsidies to highly productive firms and then taper the subsidies down toward zero for less productive firms. Similarly, the subsidy of tertiary education could be linked to performance (grade point average (GPA)) with the education of the top-performing students fully subsidized and those at the bottom not. Students who graduate with a GPA of 4.0 get a full subsidy, and those who graduate with a GPA of 3.0 get less, and so on. The same policy should be applied to universities, where the top performers in terms of ranking are fully subsidized, and those at the bottom are not. In other words, make subsidies a function of productivity, which will change the incentives and make the system more likely to generate useful knowledge. To accommodate the increasing numbers of high school students, massive vocational training institutions, tuition-free, were established to accommodate students who were not accepted in universities, where students would be trained for skills such as carpentry or mechanics. We do not know whether students who undertook vocational education did actually benefit, and we do not know the effect they made on labor market outcomes. Furthermore, the last decade witnessed a significant increase in the number of private universities – e.g., the American University system. The GCC governments spend millions subsidizing these institutions in order to accommodate more students. The outcomes of these universities have not been evaluated yet, but there has been very little to show in terms of labor market outcomes. The World Bank has studied educational and human capital reforms in the GCC. See, for example, El-Saharty et al. (2020), who discuss human capital and proposed strategies to address some of the issues. Another World Bank report (2017) provided an assessment of the challenges facing the education systems in the GCC countries, which included student school readiness, teachers’ qualifications, the curricula, the sector’s management and governance, and the efficiency of financing the education sector. Brixi et al. (2015) discuss how the incentive structure, for all involved in the education system, affects the outcomes.

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More spending on education at this level of economic development would not guarantee good outcomes. Education and human capital accumulation are about getting the incentive structure right, particularly the student’s incentive, and the government’s seriousness about achieving the targets. The data suggest that female students are the better achievers in the GCC, perhaps because they have strong incentives to stand out in a male-dominated society. The GCC countries have a lot to learn from the experiences of the Asian countries, China, Hong Kong, Singapore, Korea, and Taiwan, could they? Free university education for all is certainly problematic from an economic theory standpoint. The returns on such education are private; therefore, taking resources from the rest of the people whether in taxes or subsidies is unfair, to say the least. Free university education in the GCC countries created an excess supply of labor with fewer employment opportunities. For advanced countries, Stantcheva (2017) in a formal life-cycle model argues that an optimal system can be implemented using income-contingent education loans. These are loans given to people throughout life, whenever people need to invest in their skills whether in formal education or training, etc. The repayment depends on income. People who do well and have higher incomes repay a higher share of their income; people with lower incomes repay less. Insurance and redistribution are built into this repayment scheme, as those with high permanent lifetime incomes pay relatively more into the common pool. There already are versions of such income-contingent loans in various countries, but they are typically only available for formal college and only ensure the downside (e.g., student loans can be forgiven in precarious situations) rather than also involving higher payments when things go well. The GCC countries are not advanced economies, but they certainly passed the early stages of development, and a critical review of their educational institutions should take place sooner than later. They simply cannot afford to continue with their institutions and policies of the past in the 21st century. The links between education and labor market policies are evident. The GCC governments struggle to deal with youth unemployment. The young generation of college graduates understands that future job prospects are limited. To absorb the new graduates in government jobs is never a solution to unemployment. However, every country must chart its own future economic prospects. It should find out what it is good at making, what comparative advantages it has, and how it would fit in this world. There is no unique blueprint for development. There are principles. This includes having a functional market economy rather than a non-market economy, whereby the free exchange of goods and ideas takes place. That requires maintenance of the rule of law, especially commercial and property laws, the protection of property rights, and competition. This might look like an uphill struggle against some entrenched monopoly interests, but it is doable. The transitional dynamic from a lower growth path to a higher one is a function of the growth of physical capital (savings), labor, labor quality, human capital and its quality, and the stock of knowledge—all supported with evidencebased policies.

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Index

Page numbers in italics indicate a figure and page numbers in bold indicate a table on the corresponding page. absolute monarchies 28, 107 Active Labor Market Policy 149 agriculture 12, 16, 57, 91 Akaike information criterion (AIC) 36 alternative energies 26, 56–58, 154 Arab Monetary Fund Joint Report 16, 23, 24 Arab Spring 107 arms imports 107 augmented Dickey-Fuller (ADF) test 35, 44 Australia 118, 139, 149 Bahrain: agriculture 16; correlation of government expenditures and private investments 91; debt 6, 49, 51–52, 72–73, 78–80, 130; human capital per worker growth rate 95; loans 72–73; marginal productivities of labor and capital 14; mean dynamic stochastic projections of the primary fiscal balance – GDP ratio 80, 80; as member state of Gulf Cooperation Council 1; net export and net foreign assets discrepancy 135; optimal levels of government expenditures 98; population 3; REER depreciations 14–15; services sectors 12; tax policy 7; VAR data 79; young population 23 barrier to entry 31 BARS Curve 90–92, 91, 95 Bloomberg NEF Clean Energy Investment Trends 56 breakeven oil prices 5, 16–18, 92, 148, 154 Brent oil 4, 80 Bretton Woods 92 Britain 107

Broyden method 59 budget constraint 110 budget deficits 5–6, 7, 23, 147 capital: correlation in private investments 20, 137; correlation of oil prices 19; correlation of productivity growth 145, 155; correlation of savings 7–8, 72, 131–132, 140, 155; external debt 72, 77, 130–131; government expenditures 91; Islamic law of inheritance 147; marginal productivities of labor and 14; marginal productivity of labor and 14; monetary policy 27, 151; oil production 34; rental capital 110; stock 36, 40, 110; taxation 148 Central Provident Fund (CPF) 139 Chile 140–141, 155 China 12, 52–53, 56, 57, 57 chi-square test 44 civil law 146 climate change 4, 5, 26, 46, 54–55, 73, 131, 148, 154 Cobb-Douglas production function 34 common law 146–147 Conference Board 12–13 confidence ellipse 27, 44 constitutional monarchies 107 consumption 120 consumption tax see value-added tax (VAT) corporate taxes 84, 108, 150 COVID-19 26–27, 75, 77, 108, 148 creditworthiness 136 crowding out 151 cultural values 3, 24

Index currency depreciation 14–15, 50–51, 133, 151–152 current accounts 47–50, 53, 54, 54, 98–101, 133–134, 135, 147 direct taxes 111 discount rate 77 diversification 3 domestic debt 138 domestic prices 17 Dubai: services sectors 12; TIMSS scores 97 Dubai oil 4, 80 Dubai Ports 12 Durbin-Watson statistic DW 44 Dynamic OLS 38–40, 42 economic activity 13 economic reform 154–155 economic theories: Keynesian narrative 75, 131; Ricardian Equivalence narrative 76, 138 education 11, 23–24, 26, 27, 90, 91, 92, 96–98, 106, 139, 145, 149, 150, 153, 156–157 efficiency wage theory 139 Egypt 50 Emerging Market Economies (EMEs) 140 employment 37, 40 England 107 Engle-Granger test 42, 44 English common law 146–147 error-correction model (ECM) 42 European Exchange Mechanism 92 exchange rates 27, 33, 92, 134–135, 152 exogenous shocks 4, 5, 26–27 external debt: correlation of oil prices 23, 25, 52; crowding out 151; economic theories 75–76; fiscal adjustment requirement for sustainable target 76–77, 83; replacing with domestic debt 138; sustainable debt 5–6, 84–88, 153; United States 84, 85–87 financial law 146–147 fiscal budget deficits 6 fiscal gap 150 food security 16 foreign direct investments 145 foreign reserves 152 foreign workers 25, 96 French law 146–147 Fully Modified OLS 38, 42

165

gas 40, 44, 53 gender gap 23–24 generalized least squares (GLS) 35 Generalized Method of Moments (GMM) 40, 41, 93, 94, 98, 99 generic medicines 149 Germany 57 Global Financial Crisis (GFC) 142 governance structure 24, 28–31 government debt 140 government expenditures: actual and average optimal 101; BARS Curve 90–92, 91, 95; correlation in private investments 91, 102–104; correlation of economic growth 91; correlation of oil prices 5, 19, 23, 19; correlation of oil revenues 10; correlation of tax revenues 73; current account model with real actual and fitted values 100; financing 8; fiscal gap 150; GMM estimates of optimal level 93, 94, 99; growth model 92–98; optimal level 6, 91–101, 153–154; sustainable debt 77, 84 government revenues 16, 18 gross domestic product (GDP): agriculture 16, 91; average government balances 52, 52; correlation of capital and investments 155; correlation of domestic prices 16, 17; correlation of effective real exchange rate 27, 29; correlation of human capital growth 156; correlation of labor productivity growth 144–146; correlation of net exports 131, 135–138; correlation of oil prices 16, 17, 47, 48, 50, 51, 54; correlation of savings growth rates 7, 19, 131–132, 132, 132, 139, 140, 144; current accounts 54; debt 55, 56, 72–73, 73, 74, 76–82, 84, 85–87, 150–151; declining marginal productivity of labor and capital 14; economic activity 13; government expenditures 6, 90–96, 98, 148; growth of average per worker 33, 33, 93; growth rates 50, 50; growth rates in China and India 52–53; oil dependence 3; oil production 34; oil revenues 10–11; real and nominal 49, 155; rent 15, 16, 27; stress test 46; sustainable 153; tax policy 106, 109, 111, 113, 114, 121, 150; time series data 35 growth model 92–98 Gulf War 40, 93

166

Index

Hannan – Quinn information criterion (HQ) 36 high education enrollment 24 household savings 7, 130–144, 154, 155 human capital 7, 23, 92–97, 156–157 import costs 149 imports licenses 91 impossible trinity 27 income tax 6 income taxes 6, 106–113, 123, 148, 149, 150 India 4, 52–53, 57 indirect taxes 84, 111, 118 inefficiency 12–13 inflation 118, 119 Information Criteria 79 information criteria 36 inheritance 147 interest rates 28, 76, 77, 151 international energy agency (IEA) 57, 58 International Financial Statistics 27 International Monetary Fund (IMF) 5, 6, 14, 27, 49–50, 77, 107, 134 Iran 58 Iran–Iraq war 1 Iraq 50 Islamic laws 146, 147 Japan 33 Johansen Maximum Likelihood test 37 Johansen multivariate test 79 Keynesian narrative 75, 131 Kingdom of Saudi Arabia (KSA): agriculture 16; capital shares 40; correlation of government expenditures and private investments 91–92; debt 51–52, 78; foreign reserves 152; governance structure 24; government revenues 55; human capital per worker growth rate 93–96; impulse response functions 67–68; labor shares 40; as member state of Gulf Cooperation Council 1; net export and net foreign assets discrepancy 136; oil production 1, 2, 44–45; oil shares 40; optimal levels of government expenditures 98; public-sector jobs/wages 149; REER depreciations 14–15; rent 15; savings 133; tax policy 7; TIMSS scores 96–97; value-added tax 108; young population 23 Korea 12, 33

Kuwait: agriculture 16; capital shares 40; correlation of government expenditures and private investments 91–92; debt 51–52, 78; employment 40; foreign reserves 152; history 3; human capital per worker growth rate 93–96; impulse response functions 61–62; labor force 26; labor shares 40; as member state of Gulf Cooperation Council 1; net export and net foreign assets discrepancy 135–136; oil production 2, 44–45; oil shares 40; optimal levels of government expenditures 98; population 3; private sector jobs 26; public-sector jobs/wages 149; quasi-constitutional monarchy 28; rent 15; savings 133; Sovereign Wealth Fund 73; SVAR estimates 46–47; tax law proposal 108; tax policy 7; TIMSS scores 96–97; working-age population 40; young population 23 labor: force 7, 25–26, 96, 137; marginal productivity of capital and 14, 14; market indicators 146; reform 155–156 landownership 149 life-cycle hypothesis 93 life expectancy 150 literacy rate 23–24 loans 49–52, 142, 157 manufacturing 3, 12, 32, 57, 91, 98, 139, 148 mercantile economies 2, 3, 31, 32, 91, 98 monetary policy 27–28, 151–152 monopoly 155 Morocco 50 Napoleonic Civil Code 147 National Centre for Statistics and Information (NCSI) 98 net exports 23, 24, 133, 135–138, 137 net foreign assets 135–138, 137 Netherlands 107 Net-Zero Carbon 58 Newton’s method 59 New Zealand 118, 139, 149, 155 Ng and Perron test 35 offshore wind energy 56–57 oil: consumption 42–46, 43, 44, 48, 53, 57, 153; demand 4–5; estimates of share in output 34–42, 41; production 1–3, 12, 38, 41, 42–46, 43, 44, 58, 153; rent 3,

Index 15, 107; reserves 11, 58; revenues 4, 5, 10–11, 12, 27, 106, 131, 153, 155 oil dependence 3, 4, 5, 15 oil prices: average real price 48; breakeven oil prices 5, 16–18, 92, 147, 154; correlation in private capital stock 20, 22; correlation in private investments 20, 21; correlation of external debt 23, 25, 52; correlation of GDP and domestic prices growth rates 16, 17; correlation of government expenditures growth rates 5, 19, 19; correlation of government revenues 16, 18, 153; correlation of macroeconomic variable growth rates 27; correlation of net exports 23, 24; correlation of savings growth rates 19, 20; growth rate 4, 4, 28, 48; volatility 27, 32, 78 oil price shock: currency depreciation 15; impact on economies of Gulf Cooperation Council countries 47, 108, 114, 118, 131, 133, 136; impact on oil revenues 4, 5, 26–27, 72–73; impact on tax revenues 150 Oman: agriculture 16; capital shares 40; computed average weekly hours worked per person 112; correlation of government expenditures and private investments 91; correlation of oil prices and private investments 20; debt 6, 49, 51–52, 72–73, 80–83, 130, 138; employment 40; growth rates of hours worked and oil price 112; history 1–2; human capital per worker growth rate 95–96; hypothetical computed average income tax and consumption tax 111; impulse response functions 63–64; indirect taxes 111; Islamic law 147; labor force 98; labor shares 40; life expectancy 150; loans 49–50, 72–73; mean dynamic stochastic projections of cyclical average weekly hours worked 117; mean dynamic stochastic projections of inflation 117; mean dynamic stochastic projections of the output gap 118; mean dynamic stochastic projections of the primary fiscal balance – GDP ratio 82; as member state of Gulf Cooperation Council 1; net export and net foreign assets discrepancy 136; oil production 6, 45; oil shares 40; optimal levels of government expenditures 98–101; population 3; rent 15; savings 133, 138, 141; SVAR estimates 47; tax analysis 8,

167

108–121; tax policy 7, 108–123, 138; value-added tax 108, 118–121; VAR data 81; young population 23 Optimum Currency Area (OCA) 2 Ordinary Least Squares (OLS) 37–40, 42 Organisation for Economic Cooperation and Development (OECD) 4 Organisation of the Petroleum Exporting Countries (OPEC) 4, 58 pandemics 4, 5, 26–27, 42, 46, 72–73, 75, 131, 148 parallel imports 149 Paris Accord on Climate Change 26 pay-as-you-go pension system 7 pension funds: Chile 140–141; Singapore 139 Permanent Income Hypothesis 76, 109 Phillips and Perron test 35 political reform 154–155 private capital stock 20, 22 private investments 20, 21, 91, 102–104, 132–138, 134, 135 private law 147 private sector jobs 26 productivity: of capital 91; correlation of capital 145, 155; declining marginal productivity of capital and labor 14, 33; government expenditures 98; human capital 92–93; impact of taxes 145, 148; impact of wage increases 139; monetary policy 27; negative growth 7, 15, 20, 33, 126, 144–145; non-oil production sector 97; reform 155–156; role of financial law 145–147; total factor productivity growth rates 12–13, 145 public law 147 public-sector jobs/wages 149–150 public spending 6 Qatar: agriculture 16; capital shares 40; correlation of government expenditures and private investments 91; debt 51–52, 72–73, 78, 101; employment 40; foreign reserves 152; gas production 44–45, 46, 47; gas shares 40; impact of COVID-19 26; impulse response functions 65–66; labor shares 40; loans 72–73; marginal productivities of labor and capital 14; as member state of Gulf Cooperation Council 1; net export and net foreign assets discrepancy 136; population 3; savings 133; SVAR estimates 47; tax policy 7; young population 23

168

Index

rational spending 148 real effective exchange rate (REER) 14–15, 15, 29 real wage rate 40 regression equation 93 rentier economies 15, 27, 33 resource curse 12 Ricardian Equivalence narrative 76, 138 risk premium 77, 84, 150–151 save-as-you-go pension system 7–8 savings: correlation in private investments 132–138, 134; correlation of capital 7–8, 72, 130–132, 140, 155; correlation of debt 75; correlation of GDP 7, 19–20, 131–132, 132, 135, 139, 140, 144; correlation of oil prices 19–20, 20; government debt 140; household savings 7, 130–144, 154, 155; import costs 149; incentives 138; mandatory savings scenarios 142–144, 144; pension funds 138–144 Schwarz information criterion (SIC) 36 sensitivity analysis 77 services sectors 12, 91 Shale oil 58 Sharia 147 Singapore 12, 33, 118, 139, 155 social security system 7 Solow growth model 92–93, 96, 145 solver 59–60 Sovereign Wealth Fund (SWF) 73 Soviet Union 154 Statistics of National Account 34 Structural Vector AutoRegression (SVAR) 33, 46–47, 59, 60, 114, 118, 123 sustainable debt 84–88 Taiwan 12, 33 taxation: of capital and wealth 148; corporate taxes 84, 108, 150; hypothetical computed average income tax and consumption tax 111; income taxes 6, 106–113, 123–126, 148, 149, 150; indirect taxes 84, 111, 118; rates 40; reform 155; representation requirement 106–107; tax policy 6–8, 17, 75–76, 106–122; value-added tax 6–7, 126–127, 148, 154 technology 7, 145, 148–149 total factor productivity (TFP) growth rates 12–13, 13, 145

Trends in International Mathematics and Science Study (TIMSS) 23, 96–97 Triangular Representation Theorem 42 tri-lemma 27, 151 Turkey 4 twin deficit 5 Uncovered Interest Rate Parity Condition (UIP) 27–28, 30 unemployment 26 United Arab Emirates (UAE): agriculture 16; capital shares 40; correlation of government expenditures and private investments 91; debt 51, 78; foreign reserves 152; human capital per worker growth rate 95; impact of COVID-19 26; impulse response functions 69–70; marginal productivities of labor and capital 14; as member state of Gulf Cooperation Council 1; net export and net foreign assets discrepancy 136; oil production 2, 45; oil shares 40; optimal levels of government expenditures 98; rent 15; savings 133; services sectors 12; tax policy 7; value-added tax 108; young population 23 United Nations 26 United States 53, 58, 58, 75, 84, 85–87, 107 United States dollar (USD) 2, 27, 50–51, 73, 92, 150, 152 U.S. dollar (USD) 7 useful knowledge 97–98 value-added tax (VAT) 6–7, 108, 118–121, 119, 126–127, 148, 154 Vector AutoRegression (VAR) 6 Vietnam 12, 33 wages 40, 75, 111, 133, 139, 142, 148–149, 154, 155 wage subsidies 42, 156 waqf 146, 147 West Texas Intermediate (WTI) oil 4, 80 working-age population 39, 40, 93, 120, 150 work-leisure choice model 8, 108–113, 145 World Bank 6, 27, 77, 107, 150, 156 World Oil Outlook (WOO) 4–5 world population 52 young populations 23 youth unemployment 26