AUTHOR ACCEPTED MANUSCRIPT FINAL PUBLICATION INFORMATION The Quest for Subsidies Reforms in the Middle East and North Africa Region A Microsimulation Approach to Policy Making The definitive version of the text was subsequently published in , , 2017 Published by Cham, Switzerland: Springer THE FINAL PUBLISHED VERSION OF THIS MANUSCRIPT IS AVAILABLE ON THE PUBLISHER’S PLATFORM This Author Accepted Manuscript is copyrighted by World Bank and published by Cham, Switzerland: Springer. It is posted here by agreement between them. Changes resulting from the publishing process—such as editing, corrections, structural formatting, and other quality control mechanisms—may not be reflected in this version of the text. You may download, copy, and distribute this Author Accepted Manuscript for noncommercial purposes. 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(3) You must attribute this Author Accepted Manuscript in the following format: This is an Author Accepted Manuscript by Verme, Paolo; Araar, Abdelkrim The Quest for Subsidies Reforms in the Middle East and North Africa Region © World Bank, published in the 2017 CC BY-NC-ND 3.0 IGO http:// creativecommons.org/licenses/by-nc-nd/3.0/igo © 2017 World Bank The Quest for Subsidies Reforms in the Middle East and North Africa Region: A Microsimulation Approach to Policy Making Paolo Verme and Abdelkrim Araar, editors 1 <>Contents Acknowledgments About the Authors Abbreviations Overview Background and Motivation for the Book Structure of the Book Products Considered Data Overview Summary of Simulations SUBSIM as an Analytical Tool Notes Part I Cross-Country Analyses 1. Subsidy Reforms in the Middle East and North Africa Region: A Review Paolo Verme Introduction A Brief History of Subsidies What Triggered Reforms? Who Reformed, When, How, and Why? Policy Options Unfinished Business A Success Story? What Next? Notes References 2. A Comparative Analysis of Subsidies and Subsidy Reforms in the Middle East and North Africa Region Abdelkrim Araar and Paolo Verme Introduction Data and Analytical Approach A Distributional Analysis of Subsidies Simulations of Subsidies Reforms Conclusion Annex 2A Annex 2B Notes References 2 Part II Country Case Studies 3. An Evaluation of the 2014 Subsidy Reforms in Morocco and a Simulation of Further Reforms Paolo Verme and Khalid El-Massnaoui Introduction The Evolution of Subsidies The Political Economy of Reforms Conclusion Annex 3A Major Historical Landmarks of Morocco's Subsidy System Notes References 4. The Socioeconomic Impacts of Energy Reform in Tunisia: A Simulation Approach Jose Cuesta, Abdel Rahmen El-Lahga, and Gabriel Lara Ibarra Introduction Evolution of Energy Subsidies in Tunisia Current Structure of Energy Subsidies in Tunisia Socioeconomic Profile of Energy Subsidies Simulating the Distributional Impacts of a Subsidy-Reducing Reform Conclusion Appendix 4A: Electricity Tariff Structure for Low-Tension Residential Consumers (January 1, 2014) Appendix 4B: Distribution of Monthly Electricity Consumption by Quintile Appendix 4C: Composition of Consumption of Energy Sources by Sector (2012) Notes References 5. The Quest for Subsidy Reforms in Libya Abdelkrim Araar, Nada Choueiri, and Paolo Verme Introduction Evolution of Subsidies Baseline Data, Assumptions, and Limitations Food Subsidies Energy Subsidies The Political Economy of Reforms Summary and Recommendations Notes References 6. Energy Subsidies and the Path Toward Sustainable Reform in the Arab Republic of Egypt Sudeshna Ghosh Banerjee, Heba El-laithy, Peter Griffin, Kieran Clarke, and Mohab Hallouda Introduction Scale of Subsidies How Do the Key Stakeholders Perceive Subsidy Reforms? Household Use of and Spending on Energy Distribution of Direct Subsidies Among Households 3 Impact of Subsidy Reforms on Households Conclusions Notes References 7. Energy Subsidies Reform in Jordan: Welfare Implications of Different Scenarios Aziz Atamanov, Jon Jellema, and Umar Serajuddin Introduction Evolution of Subsidies Direct Impact of Simulation of Subsidies ReformDistribution of Subsidies Electricity Indirect Impact of Simulation of Subsidies Reform The Political Economy of Reforms Conclusions Annex 7A Annex 7B Notes References 8. Energy Subsidies Reform in the Republic of Yemen: Estimating Gains and Losses Aziz Atamanov Introduction Evolution of Subsidies Distribution of Subsidies Simulation of Subsidies Reforms The Political Economy of Reforms Conclusions Annex 8A Notes References 9. Djibouti: Subsidies, Tax Exemptions and Welfare Stefanie Brodmann and Harold Coulombe Introduction Evolution of Subsidies Determination of the Retail Price Distribution of Subsidies Simulation of Subsidies Reforms The Political Economy of Reforms Conclusion Notes References 10. Consumer Subsidies in the Islamic Republic of Iran: Simulations of Further Reforms Mohammadhadi Mostafavi Dehzooei and Djavad Salehi-Isfahani 4 Introduction Evolution of Subsidies Data Distribution of Subsidies Simulations of Subsidy Reform The Political Economy of Reforms Conclusions Annex 10A Notes References Appendix A. SUBSIM: A User Guide Abdelkrim Araar and Paolo Verme Introduction Installation SUBSIM Direct Effects Examples SUBSIM Indirect Effects Launch SUBSIM Comparing SUBSIM Direct and SUBSIM Indirect Effects SUBSIM Basic Formulas Changes in Welfare Changes in Quantities Elasticity Changes in Government Revenues Formulas for Input-Output Simulations References Boxes 4.1: Estimating Shares of Subsidized Prices 7B.1: Construction of Weighted Price Increase on Electricity 8.1: Changes in Fuel Prices and Mitigating Measures from 1995 to 2012 Figures 1.1: U.S. and European Oil Prices, May 1987–May 2014 1.2: Commodities and Oil Prices, January 1992–July 2014 2.1: Distribution of Energy Subsidies, in US$ at PPP/capita/year 2.2: Distribution of Food Subsidies, in US$ at PPP/capita/year 2.3: Expenditure Shares of Subsidized Energy Products across Countries and Quintiles 2.4: Expenditure Shares of Subsidized Food Products across Countries and Quintiles 2.5: Expenditure Shares of LPG versus Subsidies per Capita 2.6: Expenditure Shares of Flour versus Subsidies per Capita 2.7 Welfare Impact of a 30 Percent Reduction in Energy Subsidies, in US$-PPP/capita/year 2.8: Welfare Impact of a 30 Percent Reduction in Food Subsidies, US$-PPP/capita/year 2.9: Inequality Impacts of a 30 Percent Reduction in Subsidies 5 2.10: Governments’ Revenue Impact of a 30 Percent Reduction in Subsidies on Energy 3.1: Share of Total Expenditure on Subsidized Products and Amount of Subsidies per Capita, by percentile 3.2: Sensitivity of Changes in Poverty and Government Revenues to Changes in Prices 3.3: Sensitivity of Changes in Poverty and Government Revenues to Changes in Prices 3.4: Correlations of Subsidies Changes with Oil Prices 3.5: Effects of Subsidies Changes on Budget Deficits, percent of GDP 4.1: Evolution of the Composition and Level of Subsidies by Type, 2005–13 4.2: Public Spending by Sector, Including Subsidies, percent of 2013 GDP 4.3: Household Expenditure on Energy 4.4: Per Capita Expenditures on Energy, in TD 4.5: Impact of Reforms on Households’ Expenditures 5.1: Percentage of Total Household Expenditure on Food Bought at Subsidized Prices (quotas only) 5.2: Per Capita Benefits from Food Subsidies by Product, in LD 5.3: Magnitude of Decline in Government Expenditure under Reform Scenario 2, in LD 5.4: Poverty Impact of Cash Transfers to First Quintile under Food Subsidy Reform Scenario 2 (international poverty line) 5.5: Household Spending on Energy Products, as share of total household expenditure 5.6: Per Capita Benefits Accruing from Subsidies on Energy Products, in LD 5.7: Magnitude of Decline in Government Spending Following Reform Scenario 2, in LD 5.8: Poverty Impact of Cash Transfers to First Quintile under Energy Subsidy Reform S2 6.1: Consumption of Fuels 6.2: Nominal and Real Changes in Energy Prices, 1990–2014 6.3: Evolution of Fuel Subsidies, in LE billion 6.4: Fuel Subsidies, fiscal 2014 6.5: Impact on per Capita Well Being (annual household budget) 6.6: Distribution of Energy Subsidies by Sectors and Energy Products 6.7: Household Perception on Energy Prices and Subsidies (% of sample) 6.8: An Influence-Interest Matrix vis-à-vis Subsidy Reform for Key Egyptian Stakeholders 6.9: Household Annual Average Energy Expenditure 6.10: Household Spending on Energy Items 6.11: Distribution of Household Subsidies among Fuels 6.12: Distribution of Subsidies by Quintiles 6.13: Progressivity in the Distribution of Benefits 7.1: World Energy and Agriculture Price Trends, 1960–2012 7.2: Expenditure on Subsidized Petroleum Products Relative to Total Expenditures, in percent 7.3: Shares of Total Expenditures on Subsidized Petroleum Products by Quintiles, in percent 7.4: Annual Expenditure on Electricity, by Quintile 7.5: Opposition to Reform Consumption Subsidy on Any Product 7.6: Preferred Product for Inevitable Subsidy Removal 8.1: Hydrocarbon Revenues, Subsidies, and Fiscal Deficit, in percent of GDP 8.2: Retail Prices on Fuel Products, 2003 and 2014 8.3. Share of Expenditures and per Capita Subsidies on Fuel Products across the Distribution 8.4. Share of Expenditures and per Capita Subsidies on Electricity across the Distribution 8.5. Impact of Price Increase on Poverty and Government Revenues 6 8.6: Impact of Price Increase on Poverty and Government Revenues 8A.1: Retail Prices on Diesel and Super Gasoline in the Republic of Yemen Compared to the Price of Crude Oil in the World Market, 2012 8A.2: Share of Expenditures on Fuel Products in Total Budget across the Distribution 8A.3: Per Capita Subsidies on Fuel Products across the Distribution Based on August Prices 8A.4: Different Electricity Tariff Structures 8A.5: Distribution of Households by Tariff Brackets 8A.6: Expenditures on Electricity versus Total Consumption per Capita 9.1: Impact on Well-Being, by quintile 9.2: Impact of the Reform on the Government Revenue (DF), by product 10.1: Energy Consumption in the Islamic Republic of Iran, the World, and OECD Countries 10.2: Energy Prices in the Islamic Republic of Iran, 1994–2012 10.3: Natural Gas Price Schedule in 2014, in rials per cubic meter 10.4: Expenditures per Person per Year on Subsidized Goods and Their Share in Total Expenditures in 2013–14, by decile (1,000 rials) 10.5: Price Changes and the Impact on Government Revenue 10.6: Percentage Change in the Poverty Rate by the Size of Price Increases 10.7: Impact of the Level of Transfer to Compensate Indirect Effects on Poverty in the Gradualist Scenario 10.8: Impact of the Level of Transfer to Compensate Indirect Effects on Poverty in the Gradualist Scenario 10.9: Impact of the Level of Transfer to Compensate Indirect Effects on Poverty in the Full Adjustment Scenario 10.10: Impact of the Level of Transfer to Compensate Indirect Effects on Poverty in the Full Adjustment Scenario 10.11: Rates of Inflation and Macroeconomic Shocks from January 2010 to September 2014, 3- month moving averages with annualized rates A.1: Tab Items of SUBSIM Dialog Box A.2: Price Schedule Dialog Box to Set Initial Prices A.3: Tab Table Options of SUBSIM Dialog Box A.4: Tab Graph Options of SUBSIM Dialog Box A.5: Tab Main of SUBSIM Dialog Box A.6: Tab Items and Insertion of information with Editable Fields A.7: Steps to Initialize Prices in SUBSIM A.8: Use of Stata Variables to Declare Information on Items A.9: Tab Items and Insertion of Information with Stata Variables for the Case of Two Simulated Scenarios A.10: Map of Matching between Grouped Consumption Items of Household Surveys and I/O Economic Sectors A.11: Illustrative Example with a fictive Input Output Matrix A.12: Dialog Box of SUBSIM Indirect Effect A.13: Tab Items and Insertion of Information on Items and on Corresponding Matching I/O Sectors A.14: Tab Items and Selection of Indirect Effect Items A.15: Tab Items and Simulation of Several Price's Exogenous Shocks 7 Tables O.1: Summary of Products Considered by Country (direct and indirect effects) O.2: Data Summary O.3: Summary of Simulations by Country 1.1: Pros and Cons of Subsidy Reforms 1.2: Average Regional Prices of Petroleum Products, in US$ 2.1: Baseline Population and Expenditure Statistics, in US$ at PPP 2.2: Energy Unit Prices and Subsidies, in US$ at PPP (2014) 2.3: Food Unit Prices and Subsidies, in US$ at PPP (2014) 2.4 Per Capita Expenditure on Subsidized Products, in US$ at PPP/year 2A.1a: Expenditure Shares in Energy Products (percent) 2A.1b: Expenditure Shares in Food (percent) 2A.2a: Per Capita Subsidies in Energy Products, in US$-PPP 2A.2b: Per Capita Subsidies on Food, in US$-PPP 2A.3a: Impact on Welfare of 30 Percent Reductions in Subsidies on Energy Products, in US$- PPP/capita 2A.3b: Impact on Welfare of 30 Percent Reductions in Subsidies on Food Products, in US$- PPP/capita 2B.1: International Monetary Fund Macrodata 2B.2: Macrodata, Prices, and Subsidies in Local Currency (2014) 3.1: Pre-2013 Reform Selling Price Structure of Liquid Petroleum Products, in DH per unit 3.2: Example of the Selling Price Structure of Liquefied Petroleum Gas, in DH per kilogram 3.3: Domestic Annual Average Prices of Main Petroleum Products 3.4: Reference Statistics, 2007–13 3.5: Baseline Population and Expenditure Data by Quintile 3.6: Subsidized Products (October 1, 2014) 3.7: Baseline Data for the Simulation of Subsidies Reforms, direct effects 3.8: Direct Welfare Effects of the 2014 Reforms, in DH million 3.9 Direct Welfare and Budget Effects of the 2014 Subsidies Reforms 3.10 Indirect Effects of 2014 Reforms: Baseline Data 3.11: Indirect Effects of 2014 Reforms, percent of total effects 3.12: Direct Effects on Welfare of Subsidies Elimination, in DH million 3.13: Direct Effects of Elimination of Subsidies 3.14: Baseline Information of Simulation of Subsidies Removal (indirect effects) 3.15: Indirect Effects of Subsidies Elimination of Selected Products, percent 4.1: Implementation Status of Most Recent Subsidy Reforms in the Middle East and North Africa Region 4.2: Electricity Tariff Structure for Low-Tension Residential Consumers (valid since May 1, 2014) 4.3: Estimated Subsidy Rates for Energy Sources in Tunisia (valid May 2014) 4.4: Total Public Spending on Energy Subsidies, selected energy sources 4.5: Total Residential Energy Consumption, by source and quintiles of household consumption 4.6: Per Capita and Per Household Consumption of Subsidized Energy, in quantity 4.7: Composition of Subsidies Received by Residential Consumers 4.8: Per Capita Energy Subsidy Benefits, in TD 4.9: Energy Subsidy Benefits as Percentage of Total Household Expenditure 8 4.10: Impact of the Reform on Total Per Capita Expenditures (by energy source and quintile of consumption, in TD) 4.11: Poverty and Inequality Impacts of Energy Reform 4.12: Energy Subsidy Savings from the Reform by Source and Quintile of Consumption, in TD 4.13: Simulated Poverty and Inequality Impacts of Compensatory Mechanisms after Energy Subsidy Reform 5.1: Government Expenditure on Food Subsidies, 2001–12 (LD millions) 5.2: Food Subsidies and Quotas, 2008–12 5.3: Energy Prices and Subsidies, 2013 5.4: Parameters Used for the 2008–13 Extrapolations 5.5: Household Statistics Projected to 2013 5.6: Household Expenditure on Subsidized Food Products, in LD million 5.7: Quantities of Subsidized Food Products Consumed, in kilograms or liters 5.8: Percentage of Spending on Subsidized Food in Total Expenditure 5.9: Value of Food Subsidies by Quintile, in LD million 5.10: Prices, Subsidies, and Reform Scenarios 5.11: Aggregate Monetary Impact of Subsidy Reform on Welfare, in LD million 5.12: Per Capita Impact of Subsidy Reform (percent of per-capita expenditure) 5.13: Impact of Subsidy Reform on the Government Budget (Million LD) 5.14: Poverty Impact of Subsidy Reforms 5.15: Impact of Subsidy Reform on Quantities Consumed per Capita (scenario 2 5.16: Household Expenditure on Energy Products, in LD million 5.17: Share of Energy Expenditure in Total Household Expenditure, in percent 5.18: Percentage of Households that Own Cars, by quintile and number of cars 5.19: Household Consumption of Energy Products (in millions of units) 5.20: Energy Subsidies, in LD million 5.21: Two Scenarios of Energy Subsidy Reform, LD per unit 5.22: Welfare Direct Effects, in LD millions 5.23: Per Capita Welfare Direct Effects, as percentage of total welfare (scenario 1 and 2) 5.24: Reduction in Government Expenditure, in LD 5.25: Impact of Energy Subsidy Reform on Poverty (head count index) 5.26: Impact of Energy Subsidy Reform (Scenario 1) on Quantities Consumed 5.27: Summary of Aggregate Results for Cuts in Subsidies 5.28: Per Capita Monetary Value of Food Subsidies, in LD/capita/year 5.29: Summary of Aggregate Results for the Case of Energy Subsidies 6.1: Fuel Prices in July 5, 2014, Subsidy Reforms 6. 2: Electricity Prices in July 5, 2014, Subsidy Reforms 6.3: Impact of Price Change on Well-Being, in percentage of annual household budget 6.4: Impact of Price Change on Poverty 6.5: Impact on per Capita Well−Being (annual household budget) 6.6: Reform, Poverty Head Count, and Gini Index 7.1: Jordan: Changes in Petroleum Subsidies, 2007–12 (in JD million) 7.2: Household Expenditures on Subsidized Petroleum Products, in JD million 7.3: Expenditure on Subsidized Petroleum Products Relative to Total Expenditures, in percent 7.4: Parameters to Calculate Electricity Consumption in Jordan 7.5: Distribution of Households by Tariff Brackets and Consumption per Capita across Quintiles 9 7.6: Pre- and Postreform Prices of Petroleum Products, in Jordanian dinar 7.7: Impact on the per Capita Well-Being of Removing Petroleum Subsidies 7.8: Impact of Petroleum Subsidies Removal on Poverty, Poverty Gap, and Inequality 7.9: Impact of Petroleum Subsidy Reform and Cash Transfer on per Capita Well-Being 7.10: Impact of Petroleum Subsidy Reform and Cash Transfer on Poverty and Inequality 7.11: Impact of Petroleum Subsidy Elimination on Government Revenue, in JD million 7.12: Three Scenarios for Electricity Tariff Reforms 7.13: Impact of 2015 Tariffs on Economic Well-Being 7.14: Different Scenarios for Electricity Tariff Reforms 7.15: Impact of Electricity Subsidy Reform and Cash Transfer on Poverty and Inequality 7.16: Impact of Electricity Subsidy Reform on Government Expenditures, in JD million 7.17: Impact of Electricity Subsidy Reform on Government Expenditures, Correcting for Measures, in JD million 7.18: Expected Producer Price Increase in Jordanian Fuel Sector 7.19: Direct and Indirect Impacts on Well-Being of Removing Petroleum Subsidies 7.20: Direct and Indirect Impacts on Well-Being of Removing Electricity Subsidies B7.1.1: Construction of Electricity Price Increases under Subsidy Reduction Scenarios 8.1: Reference Statistics, 2005–13 8.2. Baseline Population Data and Expenditure by Quintiles, in Yemeni rials 8.3: Subsidized Energy Products, December 2014 8.4: Scenario 1 for Fuel Subsidies Reform, August 2014 reform 8.5. Scenario 2 for Fuel Subsidies Reform, full elimination 8.6. Impact of Fuel Subsidies Reform in August 2014 on Poverty and Inequality 8.7. Impact of Full Elimination of Subsidies on Poverty and Inequality Based on December 2014 Prices 8.8: Old and New Proposed Tariffs for Electricity, by tariff brackets 8.9: Impact of Electricity Subsidies Reform on Poverty and Inequality 8A.1: Annual Per Capita Consumption of Fuel Products, in quantity 8A.2: Annual Per Capita Consumption of Electricity, in kWh 8A.3: Impact on Well-Being of Fuel Subsidies Reform in August 2014, in percent 8A.4: Impact on Well-Being of Full Elimination of Fuel Subsidies , in percent 9.1: Imports and Domestic Consumption of Petroleum Products by Djibouti in 2012 (million liters) 9.2: Prices of Transportation Fuels in 2012 (US$/liter) 9.3: Price Build-up for Retail Gasoline, in DF 9.4: Retail Prices and Discretionary Taxes for Petroleum Products in 2013 (DF/liter) 9.5: Percentage of Households Owning a Car or Motorbike or Using Buses, by quintile and area 9.6: Expenditures per Household (in 2014 DF), by quintile 9.7: Expenditure on Subsidized Products over Total Expenditures (in %), by quintile 9.8: Expenditures per Household (in DF), by quintile 9.9. Expenditure on Subsidized Products over Total Expenditures (in %), by quintile 9.10: Retail Petroleum Product Prices With and Without the Discretionary Tax (December 2013), in DF/liter 9.11: Results of Simulation: Range of Retail Prices (DF/liter) 9.12: Shares of Operating Cost of a Bus Fleet in Developing Countries 9.13: Total Impact on the Population’s Well-Being (in DF millions), by quintile 9.14: Impact on the Per Capita Well-Being (in DF), by quintile 10 9.15: Impact on Well-Being (in %), by quintile 9.16: Impact of the Reform on the Government Revenue (in DF millions), by quintile 9.17: Total Impact on the Population’s Well-Being (in DF, millions), by quintile 9.18: Impact on the Per Capita Well-Being (in DF), by quintile 9.19: Impact on Well-Being (in %), by quintile 9.20: Impact of Reform on Government Revenue (in DF millions), by quintile 9.21: Coverage of Transfer Programs (in %), by quintile 9.22: Distribution of Benefits (Targeting Accuracy), by quintile and area 9.23: Reform, Destitution Head Count, and Gini Index 9.24: Definition of the Different Transfer Schemes 9.25: Effect on Destitution Gap of the Different Transfer Schemes 10.4: Population and Household Expenditures, 2013–14 10.5: Price of Subsidized Items and Free Market 10.6. Expenditures per Capita on Subsidized Products, in thousand rials 10.4: Expenditure on Subsidized Products over Total Expenditures, in percent 10.5: Price of Subsidized Items, in rials 10.6: Direct Effects of the Gradualist Scenario on per Capita Well-Being (thousand rials) 10.7: Direct Effects of Gradualist Scenario on Well-Being, in percentage of household expenditures 10.8: Direct and Indirect Effect of the Gradualist Scenario on Household Welfare 10.9: Direct and Indirect Impacts of Gradualist Subsidy Reform on Poverty and Inequality 10.10: Direct Effects of the Full-Adjustment Scenario on Per Capita Well-Being, (thousand rials) 10.11: Direct Effects of Full Adjustment Scenario on Well-Being, in percentage of household expenditures 10.12: Impact on the Per Capita Consumed Quantities in the Full Adjustment Scenario, direct effects 10.13: Direct Impacts of Full-Adjustment Subsidy Reform on Poverty, Inequality, and Government Budget 10.14: Direct and Indirect Effects of Price Increases on Well-Being in the Full Adjustment Scenario 10.15: Total Impact of Price Increases on expenditures, Poverty and Inequality in the Full Adjustment Scenario 10A.1: Total and per Capita Benefits from Subsidies 10A.2: The Impact on Per Capita Consumed Quantities, Direct Effects, gradualist scenario 10A.3: Impact of the Reform on the Government Revenue, gradualist scenario (billion rials) A.1: Nonlinear Schedule Price for Flour A.2: Example of Alternative Modeling Choices A.3: SUBSIM Indirect: Welfare Impact of Alternative Simulation Options (millions DH) A.4: Summary of Formulas for Alternative Modeling Options 11 <>Acknowledgments This book is the product of a team of nineteen authors including World Bank staff and external consultants. The team was led by Paolo Verme (World Bank) and Abdelkrim Araar (University of Laval), who also edited the book. The book was prepared for the chief economist office of the Middle East and North Africa (MENA) Region under the guidance of Chief Economist Shanta Devarajan and practice manager Benu Bidani. Finance was provided by the MENA Chief Economist Office and the Poverty and Social Impact Analysis (PSIA) Multi-donor Trust Fund. The authors thank the World Bank Country Director Ferid Belhaj, and acting Country Directors Joelle Businger and Poonam Gupta, who at various stages provided comments and cleared the country chapters. Numerous colleagues provided guidance and comments. We wish to thank Jean-Pierre Chauffour, Charles Cormier, Shanta Devarajan, Ferhat Esen, Stafania Fabrizio, Vivien Foster, Gabriela Inchauste, Philippe Leite, Esther Loening, Masami Kojima, Lili Mottaghi, Mustapha Nabli, Lucian Pop, Guido Rurangwa, and Maria Vagliasindi. A special thanks to our copyeditor Carolyn Goldinger. 12 <>About the Authors Abdelkrim Araar received his PhD in economics from Laval University in 1998. He is a World Bank consultant and a resource member at the Partnership for Economic Policy (PEP) network. Abdelkrim has been involved in designing and conducting training activities, developing training material, and conducting fundamental research. He has provided theoretical and technical supports to many researchers, especially those in developing countries. He is the coauthor, with Paolo Verme, of the Stata SUBSIM package. Also he is the coauthor, with Jean-Yves Duclos, of the book Poverty and Equity: Measurement, Policy and Estimation with DAD, the DASP Stata package, and DAD software. Aziz Atamanov is an economist at the World Bank working on poverty and inequality issues in the Middle East and North Africa Region. His areas of interest include poverty and inequality analysis, international migration, and social protection. Aziz is also engaged in regional work on microdata management, harmonization, and visualization. He holds a PhD degree in development economics from Maastricht University. Sudeshna Ghosh Banerjee is a senior economist in the Energy and Extractives Global Practice at the World Bank Group. She has worked on energy and infrastructure issues in the South Asia and Africa departments in both operations and analytic assignments. She focuses on project economics, monitoring, and evaluation, and on a broad range of energy sector issues including energy access, energy subsidies, renewable energy, and sector assessments. She holds a PhD in public policy from the University of North Carolina at Chapel Hill and MA and BA degrees in economics from Delhi University. Stefanie Brodmann is a senior economist at the World Bank’s Social Protection and Labor Global Practice. She has worked on issues related to labor markets, entrepreneurship, safety nets, education- to-work transition, and labor migration. She holds a doctorate from the Universitat Pompeu Fabra in Barcelona, was a visiting PhD student at Harvard University, and a postdoctoral fellow at Princeton University prior to joining the World Bank in 2009. Her current work focuses on, among other topics, social safety nets and targeting in the Middle East and North Africa, including Djibouti. 13 Nada Choueiri is advisor to the deputy managing director/chief administrative officer at the International Monetary Fund. A PhD graduate of the Johns Hopkins University, she joined the IMF in October 1998 and served in various positions in the Research Department, Middle East and Central Asia Department, European Department, and Communications Department before joining the Office of the Deputy Managing Director as an advisor. During 2013–14, while on leave from the IMF, she spent two years at the World Bank’s country office in Rabat, Morocco, where she served as lead economist for Algeria and Libya. Harold Coulombe has been an international freelance consultant for over twenty years, mainly on World Bank projects, but also with other UN organisations (UNDP, UNFPA, UNICEF, and DESA). His most recent mandates have been focused on different applications of the census- based poverty map methodology in collaboration with the World Bank's Research Department and Education Network. He is also collaborating on a series of studies on different poverty and social protection issues. Prior to his current status, he spent five years as a researcher at the University of Warwick where he also obtained his PhD in economics. Kieran Clarke works for the International Institute for Sustainable Development's (IISD) Global Subsidies Initiative, where he manages in-country work programs—chiefly in India, Vietnam, and the Arab Republic of Egypt—promoting energy subsidy reform and supporting governments with this process. Prior to joining IISD, Kieran worked over several years in energy and climate change policy for the Australian federal government, latterly as executive international energy adviser. Kieran has also worked for the Organisation for Economic Co-operation and Development (OECD) in Paris in the International Energy Agency’s South Asia Outreach Program. Kieran has undertaken consultancies on energy policy for the Earth Institute in New York and for Ghana’s Ministry of Environment, among others. His postgraduate studies in applied economics and public administration were undertaken at Columbia University, New York, and Sciences Po College, Paris. Jose Cuesta is a World Bank development economist with a PhD in economics from Oxford University. He is also an affiliated professor at Georgetown University's McCourt School of Public Policy. Cuesta was previously an assistant professor in development economics at the 14 Institute of Social Studies in the Netherlands. He also worked as a research economist and social sector specialist for the Inter-American Development Bank, and as an economist for the UN Development Programme in Honduras. Cuesta's research interests revolve around poverty and conflict economics, specifically the distributive analysis of social policies; intrahousehold allocation; social protection, and labor distortions. He also studies the interaction among poverty, conflict, and culture. A Spanish national, Cuesta has experience from a number of countries in South America, Asia, and Africa. He is currently an associate editor for the European Journal of Development Research and Journal of Economic Policy Reform and the editor of the World Bank's quarterly Food Price Watch. AbdelRahmen El Lahga received his doctoral degree in economics from the University of Louis Pasteur, Strasbourg, France. He is currently Associate Professor of Economics at the University of Tunis, Tunisia. He is also a Research Associate at the Economic Research Forum (ERF, Egypt). His research fields are family economics and the analysis of inequality and poverty in the Arab World. AbdelRahmen is a Tunisian citizen. Peter Griffin is a macroeconomist and modeler. In more than 40 countries, he has developed and implemented CGE (computable general equilibrium) and econometric models for analyzing and demonstrating impacts of energy subsidy reforms as well as other major policy reform initiatives. Currently he is working as a consultant to the World Bank conducting an economy- wide impact assessment of the energy subsidy reforms agenda in the Arab Republic of Egypt. Additionally, he is a consultant for the government of Turkey and World Bank's Public Finance Review, analyzing the impacts and effectiveness of public finance measures undertaken over the last decade, as well as developing proposal for new fiscal measures in support of sustained growth in Turkey. Jon Jellema is an applied policy research economist currently working in Southeast Asia, Africa, and the Middle East. He has led or contributed to reports, publications, and analyses on, among other things, the redistributive effects of fiscal policy, the poverty- and vulnerability- reducing impacts of social assistance and social protection systems, and experimental and quasi- 15 experimental impact evaluations of both community- level and household-level transfers. Jon received his PhD from the University of California, Berkeley. Heba Farida Ahmed Fathy El-laithy is currently a professor of statistics at Cairo University’s Faculty of Economics and Political Science. She is a key expert for microdata analysis and socioeconomic and social impact evaluation for development programs. Dr. El-laithy has a strong background in statistical analysis. She received her PhD degree from Sussex University. She is a key poverty and inequality expert, who has contributed her expertise to several poverty assessments and poverty alleviation program evaluations in the Arab Republic of Egypt, Lebanon, Syria, and the Republic of Yemen, authoring and co-authoring seminal reports on poverty, inequality, poverty alleviation, and social safety net development in the World Bank's MENA Region and the UN's ESCWA Region for governments, research centers, and national and international organizations such as Social Fund for Development, the World Bank, and many others. Dr. El-laithy has published papers on issues including the gender dimension of poverty, social risk management, and monetary poverty, multidimensional poverty, and food security. She designed, prepared manuals, and delivered training course on measuring monetary and nonmonetary poverty, gender statistics, human development indicators, inequality, and targeting mechanisms. She led the team for developing the poverty map for Egypt, using the Household Income, Expenditure, and Consumption Survey 2012–13 and the Population and Housing Census 2006. Recently, she participated in designing targeting mechanisms for new cash transfer programs for the Ministry of Social Solidarity, based on geographical targeting and proxy means testing. Mohab Hallouda is a senior energy specialist in the Energy and Extractives Practice of the World Bank. He graduated from the Faculty of Engineering-Cairo University in 1983, where he also received his MS degree. He received his PhD from North Carolina State University in 1992. He spent two years as visiting faculty in the United States and Germany. He is a professor in the Electric Power and Machines Department, Cairo University, and has worked and conducted research and development programs with industries and utilities on power quality, energy efficiency, motor drives, and renewable energy. He coordinated the work on energy efficiency codes and standards and labels for the Energy Efficiency Improvement and Greenhouse Gas 16 reduction project for five years. He has directed the Information and Communication Technology (ICT) trust fund for development. Hallouba has been with the World Bank since 2007, managing conventional, renewable, and energy efficiency programs as well as energy policies and reform. His primary areas of specialization are clean energy, power quality, and local development. Gabriel Lara Ibarra is an economist in the Poverty and Equity Global Practice. He is working on poverty issues and measurement, currently focusing on the Arab Republic of Egypt, Tunisia, and Djibouti and is collaborating on the data management program in Middle East and North Africa Region. Previously, Gabriel worked as a consultant in the Global Engagement Office, applying the inequality of opportunity methodology in Philippines, Russia, and Morocco, among other countries. His research interests include the welfare and distributional impacts of public policies, analysis and measurement of inequality, and household saving and financial behavior. He received his PhD degree in economics from the University of Maryland. Khalid El Massnaoui has been working with the World Bank since 2003 as a senior economist based in Morocco. He works mainly on macroeconomic, fiscal, and public sector management topics. He has also contributed to the discussions and analytical work on subsidy reform program in Morocco. He is currently the country economist for Libya. Prior to joining the World Bank, Khalid worked in the Ministry of Planning in Morocco since 1980, with a focus on macroeconomic and fiscal policies, modeling, and analysis. Khalid has a MA degree in applied economics from the University of Michigan, Ann Arbor (1989) and holds an engineer degree in statistics and applied economics from the Institut National de Statistiques et d’Economie Appliquée, Rabat, Morocco (1980). Mohammadhadi Mostafavi Dehzooei is a PhD candidate in economics at Virginia Tech. His current research focuses on household labor supply decisions under cash transfers. He has also studied the impacts of the Islamic Republic of Iran's subsidy reform program on household welfare and poverty during his PhD studies. He holds a masters degree in economics and a bachelors degree in electrical engineering from Sharif University of Technology in Tehran. 17 Djavad Salehi-Isfahani received his PhD in economics from Harvard University in 1977. He is currently professor of economics at Virginia Tech and a nonresident senior fellow at the Brookings Institution. He taught at the University of Pennsylvania (1977–84) and was visiting faculty at the University of Oxford (1991–92), the Brookings Institution (2007-08), and the John F. Kennedy School of Government at Harvard (2009–10, and fall 2013). He has served on the Board of Trustees of the Economic Research Forum in Cairo and the Middle East Economic Association and as the associate editor of the Middle East Development Journal. His research has been in energy economics, demographic economics, and the economics of the Middle East. He has coauthored two books, Models of the Oil Market and After the Spring: Economic Transitions in the Arab World, and edited two volumes, Labor and Human Capital in the Middle East and The Production and Diffusion of Public Choice. His articles have appeared in The Economic Journal, Journal of Development Economics, Health Economics, Economic Development and Cultural Change, Journal of Economic Inequality, International Journal of Middle East Studies, Middle East Development Journal, and Iranian Studies, among others. Umar Serajuddin is a senior economist-statistician at the Development Data Group of the World Bank. He currently leads the Development Data Group’s Socio-economic and Demographic data team. His main interests are poverty, inequality, labor markets, and social protection. He has also worked as a poverty expert in the South Asia and the Middle East and North Africa Regions of the World Bank. Paolo Verme is a senior economist at the World Bank. A PhD graduate of the London School of Economics, he was a visiting professor at Bocconi University in Milan (2004–09) and at the University of Turin (2003–10) before joining the World Bank in 2010. For almost two decades, he has served as adviser and project manager for multilateral organizations, private companies, and governments on labor market, welfare, and social protection policies. His research is widely published in international journals, books, and reports, and he has worked extensively on subsidies in the MENA Region and elsewhere. He is the coauthor of the subsidies simulation model SUBSIM (www.subsim.org). 18 <>Abbreviations AIDS Almost Ideal Demand System CGE computable general equilibrium CIF cost, insurance, and freight CNG compressed natural gas CPU consumer price index DP market price FAO Food and Agriculture Organization FDI foreign direct investment (FDI) GDP gross domestic product HBS Household Budget Survey HEIS Household Expenditures and Income Survey HFO heavy fuel oil HH households IBT increasing block tariffs IMF International Monetary Fund IP international reference price kWh kilowatt hours LPG liquefied petroleum gas mbd million barrels per day MENA Middle East and North Africa NP nonsubsidized price OECD Organisation for Economic Co-operation and Development OPEC Organization of the Petroleum Exporting Countries PG price gap PGI poverty gap index PMT proxy means test ppm parts per million PPP purchasing power parity PSIA Poverty and Social Impact Analysis QAIDS Quadratic Almost Ideal Demand System SBA Stand-by Arrangement SMEs small- and medium-size enterprises SR subsidy rate SUBSIM SUBsidy SIMulation VAT value-added tax VDT volume differentiated tariffs WHO World Health Organization Djibouti DF Djibouti franc DISED Department of Statistics and Demographic Studies EBC Enquête de Budget et Consommation (Budget and Consumption Survey) EDAM Enquête Djiboutienne auprès des ménages. 19 Eq. Ad. equivalence adult scale ESMAP Energy Sector Management Assistance Program SDVK La Société de Distribution et de Vente de Kérosène SESN National Solidarity TIC domestic consumption tax Egypt, Arab Republic of CAPMAS Central Agency for Public Mobilization and Statistics GoE Government of Egypt LE Egyptian pound MB Muslim Brotherhood PT/kWh piastre per kilowatt hour SAM social accounting matrix Iran, Islamic Republic of Rl Iranian rial SCI Statistical Center of Iran Jordan DOS Department of Statistics EDCO Electricity Distribution Company EMRC Energy and Minerals Regulatory Commission IDECO Irbid District Electricity Company JD Jordanian dinar JD/kWh Jordanian dinar per kilowatt hour JEPCO Jordan Electric Power Company SPEAKS Social Protection Evaluations of Attitudes, Knowledge and Support Survey NAF National Aid Fund NEPCO National Electricity Power Company NUR National Unified Registry Libya LD Libyan dinar Morocco BARS Bureau d’Approvisionnement des Régions Sahariennes CDC Caisse de Compensation ( DH Moroccan dirham DH/L Moroccan dirham per liter HCP High Commission for the Plan LSS Living Standards Survey ONEE National Electricity Company ONICL Office National Interprofessionnel des Cereales et des Legumineuses RAM Royal Air Maroc SAMIR Societé Anonyme Marocaine de l'Industrie du Raffinage 20 Tunisia BAD Banque Africaine de Développement ENBCV Enquête Nationale sur le Budget, la Consommation et les Conditions de Vie des Ménages INS Institut National de la Statistique PNAFN Programme National d'Aide aux Familles Nécessiteuses TD Tunisian dinars Yemen PDRY People's Democratic Republic of Yemen PEC Public Electricity Corporation SWF Social Welfare Fund YAR Arab Republic of Yemen YRl Yemini rial 21 <>Overview <>Background and Motivation for the Book The past decade saw extraordinary changes in the Middle East and North Africa (MENA) Region and consumers’ subsidies have been at the core of these changes. Oil prices rose to unprecedented levels during the decade that spanned from 2005 to 2014 and this contributed to generate a global rise in food and commodities prices that severely affected poor and middle- income countries. The widespread practice of regulating prices of essential energy and food consumer products in the MENA Region amplified these global shocks in a region already affected by increasing social tensions and in 2011 social tensions erupted into revolutions, regime changes, and political reforms that made subsidy reforms very difficult to implement for the new political establishments. Meanwhile, the economic decline resulting from revolutions and political changes made the budget crisis worse, increasing the urgency for subsidy reforms. On the one hand, the budget pressure for reforms was mounting. On the other hand, the political and social instability rendered these reforms a political hazard. Faced with this dilemma, some governments in the MENA Region decided to push subsidy reforms through while others opted to avoid reforms altogether. These decisions were suffered and came after prolonged periods of discussions and negotiations that saw the World Bank playing an active role. Between 2010 and 2014, several governments in the MENA Region repeatedly called on the World Bank to assist them with the analysis of subsidies and the design of subsidy reforms, and by 2014 the World Bank was working in seven countries1 in collaboration with local ministerial teams. This, in turn, offered to the World Bank a tremendous opportunity to work intensively and continuously on consumers’ subsidies for a prolonged stretch of time and learn firsthand the nuts and bolts of subsidies reforms. It was also an opportunity to develop specific modelling devices that could be deployed quickly and homogenously across countries. The objective of this book is to capitalize on the work undertaken by the World Bank in the MENA Region between 2010 and 2014 using a particular model specifically designed for the distributional analysis of subsidies and the simulation of subsidies reforms. The model is called “SUBSIM” and has been used uniformly in all the seven countries where the World Bank 22 operated. This allowed us to collect the results of the country works into one volume and compare results cross-country in a way that was not possible before. The focus of the book is the distribution of subsidies and the simulation of subsidy reforms in a partial equilibrium framework. The distributional analysis of subsidies provides information on who benefits from existing subsidies, and the simulations of subsidy reforms provide information on the outcomes of the reforms in terms of government budget, household welfare, poverty, inequality, and the trade-offs between these outcomes. It is a partial equilibrium approach in that we focus on the final consumption market only. The countries covered are Djibouti, the Arab Republic of Egypt, the Islamic Republic of Iran,2 Jordan, Libya, Morocco, Tunisia, and the Republic of Yemen. Thus, we have four countries from North Africa and four from the Middle East. We also cover net oil exporters as well as net oil importers and low-income countries and as middle-income countries. This choice provides a certain heterogeneity of experiences that helped us to derive some general lessons for policy. The book covers energy and food subsidies. The coverage of energy subsidies is rather complete, meaning that we cover almost all subsidized products in all countries considered. The coverage of food subsidies is limited to few countries and few products. The reason is that it was difficult to identify with precision the subsidized products in household surveys and in macroeconomic input-output tables. Moreover, information on the unit subsidies of these products was scarce because none of the countries considered undertook subsidies reforms of food items. Where possible, we estimated direct and indirect effects of subsidy reforms. By direct effects, we mean first-round effects or short-term effects of changes in subsidized products on final household consumption via the consumption of subsidized products. By indirect effects, we mean second and higher order long-term effects of subsidy reforms on subsidized products and on nonsubsidized products that are affected by price changes in subsidized products. SUBSIM can estimate direct and indirect effects, but the data necessary for estimating indirect effects were available only for a few countries. The book does not cover some other important aspects of subsidies and subsidies reforms. We do not estimate general equilibrium effects or the effects of subsidy reforms in all markets, such as the financial market or the labor market. We do not estimate the effects on production incentives or consider direct subsidies to enterprises, only final subsidies to consumers. With one exception, 23 we are not making use of qualitative surveys and surveys designed to capture people’s views of subsidies and we do not analyze the role of public information campaigns during subsidies reforms. We also do not attempt to estimate environmental effects, changes in gas emissions, or other social costs and benefits induced by subsidies or subsidy reforms. Further, for the case of energy consumption such as electricity or natural gas, the book does not cover non-residential consumers. This is relevant because in some countries non-residential customers account for a substantial share of energy consumption and removal of subsidies for these types of consumers poses its own challenges. Also, in the case of electricity, a large share of the subsidies burden is explained by the high cost of production. This book does not discuss issues of production costs or efficiency, which for several countries like Jordan are the answer to the subsidies crisis. In these cases, reforming subsidies is strictly related to medium and long- term energy policies that aim at reducing production and environmental costs. Data on energy consumption from residential customers, which are captured in household surveys, have their own limits. For example, in some countries we found evidence of households owing multiple meters for the same property in an effort to exploit the benefits of lower tariffs at low consumption levels. In other cases, we found anecdotal evidence of households illegally attached to other households’ meters and in some other cases small businesses confound voluntarily or involuntarily household and business meters. These phenomena exist and distort the information reported by households on expenditure. The countries observed in this book are mostly middle-income countries with electricity coverage that are close to universal coverage in many countries. Therefore, the phenomena described are less acute than in poor countries. These phenomena can also work in opposite directions, inflating or deflating reported expenditure. As a result, we have not made any attempt to artificially correct this information and for this reason some of the results may be moderately over or under estimated. Finally, electricity or natural gas bills may include payments for previous periods (arrears) or they may relate to different tariffs depending on the type of consumer. For example, some countries apply different tariffs to households who own meters of different power (say 3kW as opposed to 6 kW) while other countries may use regional tariffs. These two factors evidently complicate the accurate estimation of expenditure and consumption for the period or tariff block considered. The book does not attempt to correct for issues related to arrears because proper 24 information was not available. We made an effort instead to use the appropriate tariffs depending on types of consumers and location although this was not always possible. Clearly, the book is narrow in its scope, but it is precisely this focus and the use of the same model in all countries considered that allowed us to be more accurate in our comparisons across countries. <>Structure of the Book The book is organized in two parts and ten chapters. Part I, Cross-Country Analyses, covers the comparative analyses across countries. Chapter 1 provides a synthesis of what we learned about subsidies reforms from a political economy perspective. Chapter 2 provides a comparative analysis of subsidies and subsidies reforms across countries in U.S. dollars at purchasing power parity (PPP) values. Using the same data used by the country studies, this chapter shows the relative importance of subsidies across countries and income groups and the main winners and losers of subsidy reforms. Part II, Country Case Studies, includes the country-specific analyses. All of the chapters in this part were developed along a similar structure with an introduction, followed by a brief history of subsidies, and then the distributional analysis of subsidies, simulations of subsidies reforms, the political economy of reforms, and a conclusion. All chapters are based on primary microdata and macrodata, and each chapter provides two simulations of reforms. The first simulation was chosen based on what was deemed more relevant for the policy dialogue at the time of preparing the chapters. The second simulation is standard across all chapters and includes the full elimination of subsidies. The book includes as an appendix the User Manual for SUBSIM that illustrates the use of the model and provides all formulas used for the estimations throughout the book. <>Products Considered The number of products that remained subsidized at the beginning of the reform process in 2010 is not large. The principal subsidized energy products are gasoline, diesel, liquefied petroleum gas (LPG), kerosene, electricity, and natural gas. Among food products, only bread (or flour) and sugar remained subsidized in several countries, and only one country (Libya) maintained a wide array of subsidies on food products. Egypt and Tunisia also subsidized several food products but these products could not be analyzed for lack of data. 25 Table O.1 reports all the products considered in the country chapters for the distributional analysis and for the simulation of subsidies reforms. We can see, for example, that all case studies consider gasoline and LPG, most case studies consider electricity and diesel, and selected case studies consider kerosene and natural gas. Given our data limitations, only three chapters consider bread and sugar, and two consider flour, vegetable oil, and milk for children. When possible, we have also attempted to provide indirect effects of subsidies reforms in addition to direct effects. Table O.1 shows that we were able to estimate indirect effects in four of the eight countries considered (Morocco, Tunisia, Jordan, and the Islamic Republic of Iran) for all subsidized products considered in these countries. Table O.1: Summary of Products Considered by Country (direct and indirect effects) North Africa Middle East Egypt, Iran, Arab Yemen, Islamic Morocco Tunisia Libya Rep. Jordan Rep. Djibouti Rep. Dir. Ind. Dir. Ind. Dir. Ind. Dir. Ind. Dir. Ind. Dir. Ind. Dir. Ind. Dir. Ind. Energy Gasoline X X X X X - X - X X X - X - X X Diesel X X X X X - - - X X X - X - X X LPG X - X X X - X - X X - - - X X Kerosene X - - - X - - - X - X - X X Electricity X X X X X - X - X X X - - - X X Natural gas - - - - - - X - - - - - - - X X Food Flour - - - - X - - - - - - - X - Flour-bread X X - - - - - - - - - X X Semolina - - - - X - - - - - - - - - - - Rice - - - - X - - - - - - - - - - - Sugar X X - - - - - - - X - - - Tea - - - - X - - - - - - - - - - - Macaroni - - - - X - - - - - - - - - - - Vegetable - - - - X - - - - - - - X - - - oil Paste - - - - X - - - - - - - - - - - tomatoes Milk for - - - - X - - - - - - - X - - - children Milk - - - - X - - - - - - - - - - - (concentrated) [[Typesetter: in table O.1: Change X to check mark.]] 26 <>Data Overview For all countries considered in the book, we were able to obtain and use the latest available household budget survey (HBS) containing information on household expenditure by product, including subsidized products. Because some of these household surveys are not recent, we used the gross domestic product (GDP), the consumer price index (CPI), and population statistics to update monetary and population data to 2014, the baseline year considered in the book. Table O.2 provides the basic statistics from each survey after the update. We can see that some surveys, such as those for Egypt and the Islamic Republic of Iran, were quite recent, while others such as the one for Morocco and the Republic of Yemen were quite old. For all countries, we followed the same approach to update the household survey to the most recent year (2014). Updates were made using published IMF macro indicators for inflation and gross domestic product (GDP) per capita as well as population statistics. These data were taken from the IMF World Economic Outlook database (April 2015) and can be consulted in table 2B.1. Data used to update the household budget surveys to 2014 are provided in table 2B.2. Tables 2B.1 and 2B.2 contain the specific information used for the comparative analysis of chapter 2. The country chapters followed the same approach although some of the primary data may derive from national statistical institutes’ sources. No particular assumptions were made on elasticities between GDP growth and household expenditure growth. We simply applied the same growth rates of GDP to household expenditure. In the short-run, this assumption may not hold for all countries but in the long-run the two growth rates are expected to converge. We did not make any assumption on asymmetric growth rates across the distribution of incomes. The GDP growth rate was applied equally to the expenditure of all households so that the distribution of incomes of the last available survey remained unaltered. In total, we worked with 121,615 household observations with an average size of 4.6 people and representing a population of almost 250 million people, approximately 62 percent of the total population of the MENA Region. 27 Table O.2: Data Summary Country HBS year Obs. Population (m) HH size I/O Tables Djibouti 2012 5,880 0.94 5.6 No Egypt, Arab Rep. 2013 15,057 85.83 5.2 No Iran, Islamic Rep. 2013 38,316 77.97 3.6 Yes Jordan 2010 11,223 6.69 5.4 Yes Libya 2008 19,660 6.21 6.3 No Morocco 2007 7,062 33.18 4.7 Yes Tunisia 2010 11,281 11.06 4.3 Yes Yemen, Rep. 2005 13,136 27.46 7.5 No Total – 121,615 249.35 4.60 – Note: HH = household; HSB = household budget survey; I/O = input-output tables; Obs. = observations. <>Summary of Simulations Each of the eight country chapters provides two alternative simulations of subsidies reforms. One simulation was selected on the basis of its relevance for the current debate on subsidies. For Egypt, Morocco, and the Republic of Yemen, we simulated ex-post the impact of recent reforms, which amounts to an evaluation of these reforms. In Libya and the Islamic Republic of Iran, we considered the partial elimination of subsidies, and in Tunisia and Jordan we considered the total elimination of subsidies with compensation. The other set of simulations we did for all countries was the total elimination of subsidies with no compensation. Table O.3 summarizes the reforms scenario considered with the order of simulations followed in each country (note that the total elimination of subsidies can be the first or second simulation depending on the country). The comparative chapter (chapter 2), where we harmonized data in US$-PPP values across countries, provides a cross-country comparative distributional analysis and an analysis of a 30 percent reduction of subsidies in each country and across all products. Given that the amounts of subsidies and the distribution of expenditure are different across countries and products, results are evidently different. These results are also not directly comparable with the results in the country chapters because of the US$-PPP conversions and other choices made to harmonize 28 variables across countries. However, chapter 2 uses the same price data used in the country chapters. All choices regarding data and conversion factors are reported in annex to chapter 2. Table O.3: Summary of Simulations by Country Country Simulation 1 Simulation 2 October 2014 reforms: Increases in gasoline, diesel, and electricity Morocco Full elimination of subsidies prices; changes in electricity tariffs' blocks Full elimination of subsidies with Tunisia Full elimination of subsidies cash compensation 30% cut in subsidies on all Libya Full elimination of subsidies products July 2014 reforms: price 25% increase in prices of all Egypt, Arab Rep. increases for gasoline, diesel, energy products natural gas, and fuel oil Full elimination of subsidies with Jordan Full elimination of subsidies cash compensation August 2014 reform: Increase in Yemen, Rep. gasoline (50%), diesel (20%), Full elimination of subsidies and kerosene (100%) prices Introduction of consumer tax on Removal of tax benefits on super Djibouti powdered milk, flour, cooking and diesel oil, and sugar. 10% price increase for all Iran, Islamic Rep. Full elimination of subsidies products Simulations of subsidies reforms make also use of own price elasticities. These elasticities vary across products and countries. This question was left to the country teams to decide and is discussed in each chapter. Our recommendation to the teams was to follow the recommendations provided by the SUBSIM manual available in this book. The manual explains that for subsidized prices that are very far from free market prices (unit subsidies are very high) a good approach is to use very low own price local elasticities following a suggested formula provided by the guide. For products with low subsidies, the recommendation was to use known free market price 29 elasticities such as those observed in similar countries. As a result, own price elasticities can vary between 0.1 and 0.5 across products and countries. The exception is the comparative analysis of Chapter 2 where we used the same elasticities for the same products to render results comparable across countries. <>SUBSIM as an Analytical Tool The book uses a single tool for analysis in chapter 2 and across all the eight countries considered. This tool is a subsidy microsimulation model developed by the World Bank called SUBSIM. As already discussed, it was specifically developed to provide rapid distributional analyses of subsidies and simulation of subsidies reforms to respond to the numerous and increasing requests for assistance that the World Bank received starting in 2010. The World Bank has a long tradition in subsidies analyses and has developed over the years several analytical tools that can be used for subsidies analysis, including general equilibrium models, partial equilibrium models, or microsimulation models of various kinds. Before undertaking the project of designing a new model, we reviewed 13 different models that were in use at the World Bank. We concluded that we did not have a dedicated model for subsidies analysis that could provide simple results quickly and accurately, which severely constrained our ability to respond in a timely manner to government requests. As a consequence, we decided to undertake the project of constructing a new model in 2010. Since its first version in 2011, SUBSIM has been used in eight countries in the MENA Region and other countries in other regions, and this experience has contributed to the improvement of the model, which is now in its third version. The model is accompanied by a user manual included in this book and is available free of charge for downloading from our website (www.subsim.org). The website also includes reports and publications based on SUBSIM work and additional useful information for users. SUBSIM is programmed in Stata, is automatically added to the Stata menu when installed, and has an easy-to-use Windows interface. The model estimates the impact of subsidies reforms on household welfare, poverty, and inequality, and on the government budget with or without compensatory cash transfers. It can estimate direct and indirect effects using household budget survey data and input-output matrixes, can be applied to energy and food subsidies, and 30 accommodates linear and nonlinear pricing. It produces 22 tables and 10 graphs of standard output in English or French and allows the user to save input data for future reference. The model comes in two flavors, one that estimates direct effects only and a second that estimates direct and indirect effects. The direct effects module requires at least one household budget survey that contains information on household expenditure on subsidized products. It relies on standard microeconomic theory and uses as measure of welfare the Laspeyers variation formula by default, which is the standard welfare measure used by organizations such as the World Bank or the IMF for policy simulations. However, as explained in the user manual in more detail, the Laspeyers formula becomes inadequate for large price variations and SUBSIM offers users the option to use a Cobb-Douglas utility function to model a standard demand function and provide results accordingly. This is the option used in this book for simulations of large price variations. The direct effects module also provides the option of introducing own price elasticities, a choice left to users. The direct-indirect effects module of SUBSIM requires input-output tables in addition to at least one household budget survey. Users need to prepare the two sources of data in advance in a way that SUBSIM can recognize the same economic sectors and products from the two data sources and match them. Direct and indirect effects are obtained by shocking sectors in the input-output tables and measuring the first order and higher order effects on final prices. These price effects are then applied to household data to measure total effects. Thanks to a specially designed matrix formula for the input-output tables, this last module allows users to present direct and indirect effects separately, an option usually unavailable in other models. Users have also the option of measuring first order or higher order effects for short or long-term estimations. The SUBSIM team was embedded in the governments’ policy reforms teams that designed and implemented reforms in seven of the eight countries we consider in this book. This collaboration gave us privileged access to information that was later used to provide assistance across countries and revise the SUBSIM model to suit subsidy situations in diverse contexts. Our country teams changed over the four years of work, and the authors of the eight country chapters are those who worked on these countries last, but many more people contributed to the SUBSIM effort over the years and we are grateful to them for all inputs received. 31 The use of the same model in all of the case studies provided a unique opportunity to standardize data and results and compare products and reforms across countries. The standard tables and graphs produced by SUBSIM are directly comparable across countries and chapters, and we also developed a separate version of SUBSIM that can compare the same products across countries in U.S. dollars and purchasing power parity. This version of the model was used to prepare the cross-country analysis of chapter 2. <>Notes 1. Djibouti, the Arab Republic of Egypt, Jordan, Libya, Morocco, Tunisia, and the Republic of Yemen. 2. The World Bank did not work in Iran during the period, but it commissioned a chapter on Iran to academics specialists in the field who agreed to use SUBSIM for the analysis. 32 Part I Cross-Country Analyses 33 <>Chapter 1 <> Subsidy Reforms in the Middle East and North Africa Region: A Review Paolo Verme <>Introduction Between 2010 and 2014 MENA, the Middle East and North Africa Region, experienced an extraordinary wave of energy and food subsidies reforms. These reforms did not achieve the objective of removing subsidies completely—far from it, but they were extraordinary in two important respects. They were unprecedented because no other period in the history of the Region had seen such a wave of subsidies reforms and because they occurred during an extremely complex period from a social and political perspective—a period of war, revolutions, and social upheavals. What triggered the reforms? Who reformed, when, how, and why? What are the pros and cons of reforms? What types of reforms can be analyzed with SUBSIM? These are the questions we discuss in this chapter. Using the information contained in the comparative analysis of chapter 2 and eight country case studies, this chapter summarizes events and reflects on some of the choices made by policymakers and emerging (although still unfolding) lessons. A brief history of subsidies will show how their evolution followed a similar pattern across the countries of the Region, a pattern mainly guided by oil prices and shifts in the dominant political views of the time. We then ask what triggered the reforms and try to pinpoint the key factors that eventually forced governments to take action on reforms. Next is a summary of the essential elements of the subsidy reforms in those countries that implemented reforms between 2010 and 2014. Last is a discussion of reforms and the challenges that remain in completing the reforms. <>A Brief History of Subsidies Consumer subsidies are part of the history of the MENA Region. In some countries, subsidies were already present during the colonial period and were part of the colonial heritage when countries became independent. Each case study in this book briefly reviews the origin and evolution of subsidies during the postindependence period, and this section reviews some of the salient features of this history. 34 Consumer subsidies have evolved to serve different purposes depending on the country considered and the historical period. Most of the consumer subsidies systems as we know them today were introduced in the MENA Region between the 1940s and 1970s. Price stabilization was the initial motivation for these subsidies. As countries emerged first from World War II and then from the colonial struggles, one of their main concerns was price instability and rising prices on basic consumer goods. This situation encouraged several governments to experiment with price stabilization mechanisms whereby price increases and decreases would be mitigated via a price adjustment mechanism designed to keep price variations contained within established margins. The initial idea was not to subsidize products, but to contain price fluctuations. In the francophone countries of the Maghreb these mechanisms became known as caisses de compensation (compensation fund) precisely to underline their stabilization role as opposed to a subsidy role. Some of these caisses de compensation, such as the one established in Morocco during World War II, maintained financial stability for fairly long times, while other similar experiments incurred financial constraints early on. All these stabilization mechanisms eventually turned into subsidies systems. The reasons are multiple, but three factors are sufficient to explain the incapacity of these stabilization mechanisms to maintain financial rigor. The first is that nominal prices tend to increase in the long term, so that periods when the stabilization mechanism earned an income were few. The second is that it is politically convenient for a government to keep prices fixed when international prices rise but much harder politically to keep domestic prices high when international prices decrease. There is a behavioral asymmetry here explained by politics and subsidies progressively became a political instrument to buy political consensus. The third factor is related to the businesses and the interest groups that are generated by the very existence of subsidies and that become with time an obstacle to reforms. As price stabilization mechanisms turned into subsidies systems, the rationale for these subsidies also started to change into a system of social protection. This change coincided with the turning of the MENA Region toward socialism and the revolutions that put dictators into power between the 1950s and the 1970s. As the political and economic systems became more centralized, subsidies became instrumental in supporting the regimes. After Muammar Gaddafi’s revolution, Libya quickly introduced in 1971 a national institution to oversee the prices of basic commodities, which contributed to the expansion of subsidies across food and energy items and 35 which became one of the main instruments of the regime to quell discontent. But subsidies fitted well with all other types of regimes in the Region, whether they were monarchies, democracies, pseudodemocracies, or dictatorships. During this period, the state takes a paternalistic role with a mix of socialist and Islamic ideology that sees subsidies as a form of social protection. Populations start to see subsidies as a human right or natural entitlements; governments are happy to use subsidies as a tool to gain consensus and are unprepared to take the risks associated with removing them. Countries that attempted major reforms in the 1970s and 1980s had to backtrack these reforms such as Tunisia in the aftermath of the 1983 reform. The prolonged use of subsidies and the benefits that they provided to some enterprises generated a new rhetoric for their use as enterprise support mechanisms. Import substituting, infant industry protection, or export-oriented growth are some of the terms used to justify subsidies in this context. These terms were used to defend a system of production born and raised with subsidies. Enterprises found themselves in the middle of the subsidy system in two different but connected ways. On the one hand, consumer subsidies covered domestically produced products so that consumer subsidies had first to pass through producers. For example, bread subsidies were and are still administered by subsidizing flour for bakeries. This kind of subsidy evidently creates distortions on the production side and incentives for the creation of shadow markets. Subsidies on liquefied petroleum gas (LPG) are administered by financing the distributors of LPG bottles, which creates an entire distribution system around this product alone. Moreover, some consumer products such as diesel or sugar are widely used as production inputs by enterprises, artificially reducing costs. On the other hand, producer subsidies accompanied consumer subsidies throughout the period. This combination of producer and consumer subsidies generated a much distorted apparatus of production highly dependent on subsidies. Not surprisingly, general equilibrium models often find that when subsidies are removed, the gross domestic product (GDP) declines in the medium term. The reason is that many businesses are expected to survive and export only in the presence of subsidies and they become noncompetitive and go out of business when subsidies are removed. The 1990s were characterized by a structural transformation of the economies, but became somehow a lost decade in terms of subsidies reforms. The socialist period in the MENA Region came to an end during the 1990s when enlightened dictators, presidents, and monarchs started to implement structural reforms, including privatization, liberalization and financial stabilization in 36 the aftermath of the fall of the Berlin Wall. Subsidies were seen as a possible area of reform, but little was accomplished in terms of removing existing subsidies for two good reasons. One is that oil prices were extremely low (around US$ 20 per barrel) and the second is that countries started to grow thanks to the initial reforms. These two factors resulted in subsidies being a relatively small share of GDP decreasing the pressure for reforms. It is, however, a lost decade for subsidies reforms in that low oil prices would have allowed governments to remove price regulation mechanisms and subsidies with a small impact on household welfare as compared to the decade that followed. The 2000s brought about the first urge for reforms but no reforms; rather, it was a period that could characterize subsidies as one of the last instruments for fragile governments to maintain power. The change in attitudes toward subsidies was generated by two concomitant factors. The first follows from the previous period. As countries start to reform their economies, it becomes increasingly clear among international observers that subsidies are an obstacle to further reforms, and this idea starts to generate a debate on subsidies reforms also within countries. The second and most important factor is oil prices. Starting from the beginning of the decade the price of oil rises with a relentless growth process, which drastically changes the weight of subsidies on the economy. Subsidies, for the first time, become an unsustainable burden for the budget. Increasing oil prices have a double cost: they not only increase subsidies but also contribute to higher prices of nonsubsidized products, including food. This general increase in prices, in turn, generates resentments on the part of the population and a wall of adversity toward subsidy reforms. Moreover, through the 2000s none of the countries in the Region goes through political reforms, and rulers continue to use subsidies as a tool to contain discontent. In Libya, for example, Gaddafi implemented a drastic reform of food subsidies in 2008 only to roll it back completely on the eve of the Libyan revolution as one of his last attempts to contain discontent. Hence, subsidies become increasingly a burden for state budgets, but they remain a political hazard for fragile rulers. The incapacity of governments to remove subsidies during a period of hard budget constraints relates to oil prices and government instability but also finds its roots in a combination of factors that, taken individually, may seem reasonable to many observers. Table 1.1 shows ten factors that justify removing subsidies as well as ten factors that would seem to justify subsidies. Subsidies are costly to the government and tax payers; they distort investments, production, and 37 consumption; and they can support nondemocratic institutions. Yet, subsidies are easily portrayed as good policies. Politicians are rightly concerned about the risk of political uprising, various stakeholders benefit indirectly from subsidies thanks to established monopolies or oligopolies. Export-oriented firms benefit from lower input costs and can better compete on international markets. Consumers benefit from reduced prices and reduced volatility on prices, and this applies to all consumers. Subsidies also worked as a social protection mechanism, compensating for the general increase in prices of the late 2000s, and in many countries of the MENA Region, subsidies are perceived as an acquired right. All these reasons for keeping subsidies appear to be legitimate but each of these reasons is linked to a particular interest group and result in a net cost for the economy at large. For example, the risk of social uprising is real, but delaying reforms does not address the problem. Export-oriented firms benefited from increased export competitiveness but only in the short term and at the expense of reduced growth in production and productivity in the medium and long term. Subsidies worked as social protection mechanisms but in a much less efficient way than cash transfers targeted to the poor. In other words, although removing subsidies may result in a positive social outcome overall and in a better allocation of resources in the long run, the potential loss of short-term gains from particular interest groups are a powerful constraint to reforms. This was why it was so difficult to remove subsidies. The voices of the different interest groups were louder than the overall economic rationale of the social planner, a voice that few governments were willing to heed. It is natural to ask next, therefore, what broke this equilibrium and made governments move on with reforms. Table 1.1: Pros and Cons of Subsidy Reforms Ten reasons to remove subsidies Ten reasons to keep subsidies Economic Economic Distort consumption Reduce production costs and increase export competitiveness Distort production Reduce price volatility, financial risks, and Distort investments uncertainty for households Delay important strategic decisions on energy Political 38 Encourage informality and illegality Risk of social uprising Political Buy political consensus Support undemocratic regimes and populists Benefit established monopolies/oligopolies governments related to politicians Nontransparent to the population Social Social Work as social protection mechanism Costly for the tax payers Compensate for general increases in prices Inequitable and prorich Benefit the poor, the middle class, and the rich Costly for the environment Perceived as a basic human right Increased demand for subsidies due to economic decline in the MENA Region <>What Triggered Reforms? The recent wave of subsidies reforms really starts with the 2010 reforms in Iran and progressively expands to other countries of the MENA region in the midst of political turmoil. A combination of factors explains this wave of reform, each of which cannot explain the reforms alone. One possible factor is the extent of the political changes that took the Region by storm. Regime changes in the Arab Republic of Egypt, Libya, Tunisia, and the Republic of Yemen altered the political settings in these countries and had a demonstrative effect on countries that did not experience revolutions first hand. The popular revolutions affected the politics of other countries of the MENA Region, and in some countries political changes occurred without a revolution. The new class of politicians was less averse to subsidies reforms than the previous regimes, perhaps because they were typically less connected than the old regimes to the benefits derived from subsidies. The spirit of change created a new social contract with the populations, who became less averse to reforms although subsidies remained in great demand. But the main factors that explain reforms are economic and relate to the price of oil, regulated prices and the economic decline generated by the political changes. The period considered thus far was exceptional for world energy and food prices. Figure 1.1 shows average monthly oil 39 prices (U.S. and European FOB prices in US$ per barrel, left axis) and the price of gasoline (U.S. FOB price in US$ per gallon, right axis) between May 1987 and April 2016.1 Four distinct periods emerge. The first period, between 1987 and 2003, is characterized by oil prices below 40 US$ per barrel. During this period, U.S. and European prices overlap, and the price of gasoline follows closely the oil price. A second period is characterized by a steep surge in oil prices between 2003 and 2008 when price volatility increases and the price of gasoline follows less closely the oil price. The third period starting in 2009 follows the global financial crisis and is characterized by high and volatile oil prices where the U.S. and European prices and the price of gasoline increasingly diverge. The fourth period shows the most recent decline in oil and gasoline prices and also continued price volatility. The period considered by this book (2010- 2014) is unique in terms of both the level and volatility of oil prices. Figure 1.1: U.S. and European Oil Prices, May 1987–April 2016 160 3.5 140 3 120 2.5 100 2 80 1.5 60 1 40 20 0.5 0 0 May-1996 May-1987 May-1988 May-1989 May-1990 May-1991 May-1992 May-1993 May-1994 May-1995 May-1997 May-1998 May-1999 May-2000 May-2001 May-2002 May-2003 May-2004 May-2005 May-2006 May-2007 May-2008 May-2009 May-2010 May-2011 May-2012 May-2013 May-2014 May-2015 Cushing, OK WTI Spot Price FOB (Dollars per Barrel) Europe Brent Spot Price FOB (Dollars per Barrel) New York Harbor Conventional Gasoline Regular Spot Price FOB (Dollars per Gallon) Source: Elaborated from data available at EIA 2015. [[Typesetter: Left y-axis: Insert label "US$ per barrel"; Right y-axis: Insert label "US$ per gallon"; X-axis: Delete "May-" and make years right reading on a slant.]] Data lines and legend: change colored lines to broken lines. 40 Legend: Delete words following FOB; Background: delete box and gridlines.]] The picture is similar if we consider the commodities indexes for fuel and food (figure 1.2). The fuel energy index, which combines fuel products, shows that its trend overlaps with the oil trend up until the 2008 global financial crisis when we start to see more volatility and a certain divergence between the two trends. The food price index is naturally less associated with changes in the oil price but nevertheless is correlated with it. In particular, during the period that we consider more closely (2010–14) both the food and energy indexes show high levels and high volatility. In their reforms efforts, governments faced increasing fiscal pressure and increasing uncertainty. This aspect is crucial to understanding the political economy of reforms and why most governments in the Region have put subsidies reforms at the top of their agenda in recent years. Figure 1.2: Commodities and Oil Prices, January 1992–May 2016 300 160 140 250 120 200 100 150 80 60 100 40 50 20 0 0 Jan-1992 Jan-1993 Jan-1994 Jan-1995 Jan-1996 Jan-1997 Jan-1998 Jan-1999 Jan-2000 Jan-2001 Jan-2002 Jan-2003 Jan-2004 Jan-2005 Jan-2006 Jan-2007 Jan-2008 Jan-2009 Jan-2010 Jan-2011 Jan-2012 Jan-2013 Jan-2014 Jan-2015 Jan-2016 Commodity Food and Beverage Price Index - Monthly Price (left scale) Commodity Fuel (energy) Index - Monthly Price (left scale) Crude Oil (petroleum); Dated Brent - Monthly Price (right scale) Sources: Elaborated from http://www.indexmundi.com/ and World Bank Commodities Prices database. [[Typesetter: Left y-axis: Insert label "Monthly price"; Right y-axis: Insert label "Monthly price"; X-axis: Delete hyphens and add a space; make years right reading on a slant.]] 41 Data lines and legend: change colored lines to broken lines. Legend: Delete words and hyphens following "Index" and "Brent"]] Background: delete box and gridlines.]] The next issue to consider is the regulated prices that MENA countries were confronted with when they were forced to introduce reforms. Table 1.2 shows the average regional prices for four energy products—gasoline, diesel, kerosene, and LPG—comparing the main regions of the world. It is striking how the MENA Region distinguishes itself from the others by having, by far, the lowest average regional prices. For example, the price of gasoline, on average, was US$ 0.67, about half the price of other regions. The price of LPG was US$ 0.4, which is less than a third of the average price in South Asia and about a third of the price in East Asia and the Pacific. Similarly, for diesel and kerosene, the prices in the MENA Region were a fraction of the prices in other regions. Hence, the worldwide push for subsidies reforms that took place in virtually all regions of the world since 2010–11 was particularly acute in the MENA Region when growth took a negative turn due to political instability. These two factors together with the economic decline generated by the political changes were the driving factors of subsidies reforms that eventually overruled the other logics for maintaining subsidies. Table 1.2: Average Regional Prices of Petroleum Products, in US$ (January 2013) Gasoline Diesel Kerosene LPG East Asia and Pacific 1.25 1.03 1.11 1.20 Europe and Central Asia 1.16 1.23 n.a. n.a. Latin America and the Caribbean 1.24 1.14 1.18 1.01 Middle East and North Africa 0.67 0.44 0.41 0.40 South Asia 1.25 0.91 0.86 1.44 Sub-Saharan Africa 1.24 1.22 0.96 0.97 Source: Elaborated from Kojima 2013. Note: The table is based on a sample of 63 countries. Data on Europe and Central Asia (ECA) countries may not be representative due to the small sample size. <>Who Reformed, When, How, and Why? An overview of reforms undertaken during this period shows that of the eight countries considered in this book, six implemented substantial reforms. In chronological order of reforms, these countries are the Islamic Republic of Iran, Yemen, Jordan, Morocco, Egypt, and Tunisia. 42 The other two countries of Djibouti and Libya did not implement any reforms and will not be covered in this section. In what follows we focus on the key reforms undertaken between 2010 and 2014, summarizing the background, contents, and outcomes of the reforms. <>Islamic Republic of Iran: December 18, 2010 On January 5, 2010, the government of the Islamic Republic of Iran introduced the Targeted Subsidy Reform Act, a major subsidy reform designed to eliminate most subsidies and compensate the population with a cash transfer. Due to political and organizational constraints, the implementation of the act was delayed for almost a year and the reform was finally launched on December 18, 2010. The reform was originally planned to be implemented over a period of five years to coincide with the fifth five-year economic, social, and cultural development plan. The act estimated the expected net gain at 200 trillion rials but did not indicate the price increase to be applied to subsidized products. The reform was preceded by an extensive public relations campaign to educate the population on the costs and benefits of the reform (Guillaume, Zytek, and Farzin 2011). The government also made clear that protests would not be well received. Budget savings deriving from the reforms were expected to be partly redistributed in the form of transfers to the population (50 percent), partly used by the government for administration (20 percent), and for improving the efficiency of the energy, transport, and industry sectors (30 percent). The actual reforms that unfolded in the weeks following December 18, 2010 included major prices increases for all fuel products, electricity, water, transport, and bread. The price of gasoline increased fourfold from the equivalent of US$ 0.10 per liter to US$ 0.40 per liter for quotas2 and from US$ 0.60 per liter to US$ 0.70 per liter for nonquotas. The price of diesel increased tenfold from US$ 0.06 per gallon to US$ 0.6, and the price of natural gas for domestic consumption increased at least fivefold from 1–1.3 cents per cubic meter to 7 cents per cubic meter. Prices for electricity and water also increased by around 300 percent on average, and the reform did not spare public transport or bread, with prices increasing by more than 200 percent.3 The price reform was accompanied by a compensatory cash transfer of 445,000 rials per person per month, an amount equivalent to 28 percent of the median household income and 50 percent of the income of a minimum wage worker with a family of four (see chapter 10). This transfer was quasi-universal. About 80 percent of households were made eligible on the eve of the 43 reform, and more households were added later. The cash transfer was administered via bank accounts. The first transfer was deposited in accounts in advance of the price increases in an effort to minimize protest and distrust for reforms. The reform had a clear impact on prices, which increased during the first half of 2011 across main consumption items, with average increases around 30 percent and peak increases around 100 percent. Consumption of fuel products such as gasoline and liquefied gas decreased by about 10 percent. In January 2012 the government estimated that total savings from the reform amounted to an equivalent of US$ 15 billion. The simulations provided in chapter 10 show that the compensatory cash transfers provided were excessive to compensate for the reforms and that a large part of the transfers accrued to the nonpoor. Perhaps because of these large effects, the government partly rolled back reforms in March 2012 when the parliament amended the Targeted Subsidies Reform Act. The main trigger for reforms was the size of subsidies, which by 2010 were estimated at the equivalent of US$ 100 billion, an amount larger than the total oil revenues and over 20 percent of GDP. The scope and size of the reform was unprecedented not only for Iran but also for any other economy that embarked on subsidy reforms. Indeed, the outcomes of this reform have produced large changes in consumption patterns, inflation, and government revenues and expenditure. However, despite the large increases in prices, the reform did not remove price controls and four years later Iran found itself again with very large subsidies, the second largest provider of subsidies in the MENA Region after Libya, as shown in chapter 2. Therefore, although the reform partly succeeded in readjusting consumption and prices, it failed in its attempt of removing subsidies. Subsidy reforms in Iran have also been carried out in a complex economic environment characterized by international sanctions and large social programs, such as the Maskan Mehr low-cost housing program, which contributed to a prolonged period of stagnation and inflation. The outcomes of these other factors merged with the outcomes of the subsidy reforms and eventually created public resentments against the reforms (see chapter 10). The continuation of reforms during the five-year period that was initially envisioned did not happen as expected, and further subsidy reforms remain as problematic as ever. <> Yemen 2010-2014 44 Recent subsidies reforms in Yemen initiated around 2005 with World Bank and IMF support. Initial reforms included several rounds of price increases that more than doubled prices between 2005 and 2010. In 2010, the government introduced further price increases for fuel products of about 30 percent and for LPG of about 100 percent. This was followed in 2011 and 2012 by further increases of prices of gasoline by 66 percent and diesel and kerosene by about 100 percent. These large price increases were not accompanied by significant public protests. In July 2014, the government decided to remove subsidies and initially increased prices by 60 to 90 percent depending on the product, but this move lacked a proper public information campaign and resulted in violent protests that forced the government to partially reverse reforms in September of the same year. As a result, gasoline and diesel experienced a net increase of 50 and 20 percent respectively. This last round of reforms also foresaw compensatory measures in terms of an expansion of funding and coverage for the social welfare fund. However, these compensatory measures were not clearly explained to the public and they took some time to be enforced, which partly explains why they were not effective in preventing public protests. It is also important to note that these reforms occurred in the midst of high political instability that eventually turned into civil war. If we consider the political climate, the government took bold and risky reforms during the period that could have further compromised the political environment. <>Jordan: November 13, 2012 The government of Jordan introduced a major subsidies reform on November 13, 2012. This move occurred unexpectedly, despite a prolonged period of public discussion about subsidies reforms. The reform reintroduced the automatic pricing adjustment mechanism on petroleum products and thereby discontinued the practice of discretionary adjustments. The liberalization of prices caused immediate increases in the prices of 90 octane gasoline and kerosene (+14.3 percent, from 700 fils per liter to 800 fils per liter for both products), diesel (+33 percent from 515 fils per liter to 684 fils per liter), and LPG (+53.8 percent, from JD 6.5 per cylinder to JD 10 per cylinder of 12.5 kilograms). This rise followed an initial price increase of the other petroleum products, including 95 octane gasoline, introduced during the second quarter of 2012. The reform was accompanied by the precautionary measure of freezing the price of bread, but the Ministry of Transport was instructed to adjust public transport tariffs according to the new fuel prices. 45 The Jordanian reform also included a compensation of JD 70 per person per year with a maximum ceiling per household of JD 420 per year, an amount excluded from any form of taxation or deductions. The only eligibility criteria were Jordanian residency and an annual household income below JD 10,000. An estimated 70 percent of the population were expected to be eligible for the program, and the administrators used several public databases to exclude noneligible households, including the rosters of public sector employees and retirees, military personnel and retirees, and social security subscribers. Beneficiaries of the National Aid Fund (NAF) would receive the compensation without application, but all other eligible citizens (private sector employees, the unemployed, and the inactive) had to apply by filling out a specific form. The start of the compensation was set for November 18, 2012, and payments were scheduled to be made every four months. Payments were also anchored to the average international price of oil with an automatic discontinuation of benefits if the price of oil per barrel fell below US$ 100 in the four months preceding any payment. The generous cash transfer that accompanied the reform probably contributed to quell protest, as the reform did not result in any social backlash. <>Arab Republic of Egypt: July 5, 2014 The Arab Republic of Egypt undertook substantial reforms of fuel prices on July 5, 2014. The government announced increases in prices for all fuels with the sole exception of LPG. Gasoline prices rose from LE 0.9 to LE 1.6 for 80 octane, from LE 1.85 to LE 2.6 for 92 octane, and from LE 5.75 to LE 6.25 for 95 octane; natural gas for cars rose from LE 0.45 to LE 1.1; and diesel from LE 1.1 to LE 1.8. Prices for natural gas and fuel for commercial uses were also increased significantly. Electricity prices for all residential customers rose by about 50 percent on average; smaller increases were applied to commercial customers for whom the initial price had been much higher. These were all major price increases in percentage terms but still insufficient to eliminate subsidies as the starting prices were very low. The government also announced a complete phase out of subsidies over a five-year period, estimated savings of about LE 51 billion and planned to allocate part of these savings to social expenditure—about LE 27 billion on health, education, and social protection programs. The July 2014 reform aimed at addressing the major budget liability stemming from the prolonged growth of subsidies. For example, fuel subsidies had increased at a compound annual 46 growth rate of 26 percent between 2002 and 2013. Their share of the government budget increased from 9 percent in 2002 to 22 percent in 2013, and their share in Egypt’s GDP increased from 3 percent to 7 percent in the same period (see chapter 6). The weight on the budget was already very high in 2011, but the Egyptian revolution stalled any possible reforms. The new government of Mohamed Morsi preferred to delay major reforms and focus instead on administrative adjustments such as the much needed corrections to the LPG distribution system. It is only with the arrival of the government of Abdel Fattah el-Sisi that the political commitment and capacity to implement reforms became stronger. The popularity that this government enjoyed during the first few months in office and the inherited budget deficit contributed to create the conditions for reforms. <>Morocco: September 16, 2013–October 1, 2014 Major reforms to the subsidy system in Morocco began on September 16, 2013, with the decision to reactivate the price indexation mechanism for liquid petroleum products, including gasoline, diesel, and fuel oil. The new system imposed a cap on the unit subsidies with the remaining price differential to be passed through to domestic prices. This first measure helped the government to reduce subsidies by an estimated 1.3 percentage points of GDP. On February 1, 2014, the government stopped supporting prices of gasoline and industrial fuel oil. The price of gasoline in January 2014 was not very far from the nonsubsidized price. As a result, the price increase that occurred in February 2014 was relatively small, from DH 12.02 to DH 12.8. As fuel oil was used for the generation of electricity, the government introduced a lump-sum transfer to the national electricity company to be phased out over a period of three years during which electricity tariffs were to progressively increase starting from August 2014. The August reforms of electricity included an increase of the number of blocks from four to six. Tariffs were adjusted, and starting from the third block, the tariff system changed from increasing block tariffs (IBT) to volume differentiated tariffs (VDT).4 Diesel unit subsidies were also subjected to a gradual dismantling with a progressive phase out from DH 2.15MAD per liter in January 2014 to DH 0.80 per liter in October. Subsequently, the government removed diesel from its list of subsidized products. As of January 2015 the only remaining subsidized products in Morocco were LPG, flour, and sugar. However, the government decided to continue administering prices of liquid petroleum 47 products through the implementation of the indexation mechanism until November 2015, when prices of all liquid petroleum products would be fully liberalized. Prices of these products would thereafter be subject to competition among the distributors (see chapter 3). The political economy of subsidy reforms in Morocco has been driven largely by the global prices of strategic commodities and by the increasing cost of subsidies to the state’s budget. Subsidy reforms were complemented by other fiscal consolidation measures, including a freeze on wages and limits to hiring civil servants to stop the rise of the public wage bill, and improvements to the tax collection system through the extension of the tax base, harmonization of tax rates, and an effort to stop tax evasion. The evaluation of the 2013–14 reforms in chapter 3 shows that the reforms are unlikely to have had any impact on poverty and inequality and they did protect the most vulnerable parts of the population while contributing significantly to reducing the budget deficit. The evaluation of the 2014 subsidy reforms has shown that the government has made a set of proper choices from a distributional and budget perspective. Subsidies have been eliminated on those products, such as gasoline, that were more prorich and affected poverty the least, while the reform of products that would hurt the poor the most, such as LPG, has been delayed. Electricity tariffs have been increased in a sensible way by increasing the number of blocks (and thereby reducing the consumer surplus) and by raising tariffs only on the upper blocks, protecting in this way the poor and the middle class. The 2014 reforms had important indirect effects, particularly for diesel, and these had an impact on poverty but still modest overall. All reforms were implemented without compensatory cash transfers, and the reforms did not provoke any significant social backlash. <>Tunisia: 2012–14 As with the other reformist countries, Tunisia was forced to embark into subsidy reforms because of budget constraints. Between 2005 and 2013, the combined spending on energy, food, and transportation more than tripled, rising from 2 percent of GDP in 2005 to 7 percent in 2013. Energy subsidies, in particular, increased fourfold, reaching 4.7 percent of GDP in 2013. Due to the 2011 revolution and the economic decline and political instability that followed the revolution, reforming subsidies proved difficult between 2011 and 2012. In 2012 the government of Tunisia began implementing a gradual strategy of subsidy reduction and improvement in public spending targeting. As reported by the IMF (2014), the prices of 48 gasoline, diesel, and electricity increased by 7 percent in September 2012, followed by similar increases in March 2013. Energy subsidies to cement companies were halved in January 2014 and fully removed in June of the same year. Electricity tariffs on low and medium voltage consumers were increased in a two-step process, by 10 percent in January 2014 and another 10 percent in May 2014. The government introduced a lifeline electricity tariff for households consuming less than 100 kilowatt hours (kWh) per month in 2014. Also in January 2014 the government established a new automatic price formula for gasoline to align domestic prices to international prices over time, but without a clear calendar (see chapter 4). The government also introduced other social reforms with the potential to mitigate the impact of subsidy reforms, although not designed specifically for that purpose. It launched a new social housing program (which was never really implemented), increased income tax deductions for the poorest households, and committed to creating a unified registry of beneficiaries of social programs and to improving social spending targeting (to be finished in 2015). In addition, the government continued to expand the cash transfer program (PNAFN) while attempting to reduce its exclusion error. <>Policy Options In what follows we discuss the pros and cons of these different approaches to reforms and other important questions and choices that policy makers are called to address when reforming subsidies such as introducing compensatory measures or not, prepare the public with public information campaigns or be silent, follow a product by product approach as opposed to uniform reforms across products, target the poor, the middle class or both, start from energy subsides as opposed to food subsidies or vice-versa, consider direct as opposed to indirect effects, and the choice of the political timing of reforms. Rather than providing recommendations, the following sections review and compare the choices made by the sample of countries we consider in this book. <>Radical versus Gradualist Approach Looking at the contents, duration, and outcomes of the reforms, we can classify the countries observed into four categories. The first category is made of those countries that followed a radical approach to reforms. This category includes Iran and Jordan, the countries that introduced a substantial set of reforms at one particular point in time. The second category is 49 made of those countries that carried out a significant amount of reforms over a period of time using a gradualist approach. This category includes Morocco and Tunisia, but the extent of the reforms and their impact have been quite different, with Morocco implementing much deeper reforms than Tunisia. The third category includes Egypt and Yemen, two countries that stepped up reforms in 2014 after a period of gradual reforms. The fourth category of countries is represented by the nonreformers, which includes Djibouti and Libya. Djibouti had relatively little subsidy in place to start with and distributed it only in the form of tax exemptions. Libya did not reform because of political instability and civil conflict. Were Iran and Jordan more successful than Morocco and Tunisia? The answer is not univocal, but there is something to learn by comparing these two sets of countries. Iran did implement profound reforms in terms of price increases, and these reforms did provide some extra revenues for the government, real benefits to the poor, and reduced energy consumption. However, they also brought about inflation, were costly in terms of compensation, and were carried out in the midst of other important economic changes such as international sanctions and housing reforms. Moreover, these reforms failed to liberalize prices of subsidized items. The result is that four years later subsidies had returned to very large levels, and the population remains confused as to the benefits of the reforms. The job is not done, and pushing further reforms will be more difficult than before. The scale of the reforms in Jordan was much lower, but Jordan managed to liberalize prices of gasoline and diesel in one stroke and to buy support with substantial cash transfers. Jordan solved one problem but has yet to tackle the remaining LPG and electricity subsidies. Electricity subsidies in particular represent the main budget problem in Jordan today and the reforms did not address this problem. Morocco prepared reforms carefully, implemented them in an orderly fashion following an open dialogue with the population, discontinued subsidies altogether for gasoline and diesel, started to implement a clear plan for the removal of electricity subsidies, and designed a plan for discontinuing subsidies on LPG. This country has now eliminated most subsidies and is expected to eliminate all of them within three years. This country started from a relatively low level of subsidies as compared to other countries in the region partly because it was more rigorous in applying the price transfer mechanisms in place and also removed subsidies on other consumers’ products such as edible oil early on in the years 2000s. Tunisia implemented simpler reforms with gradual increases of prices and tariffs every quarter. This approach went well with the 50 population, but the country has failed to remove subsidies altogether for any energy product and, at the end of 2014, still maintained subsidies on several food products. Those countries that did not reform was either because they had low subsidies (Djibouti) or they faced insurmountable political challenges due to internal civil conflict (Libya). Otherwise, these countries too might have gone through reforms during the exceptional convergence of factors of the 2010–14 period. Overall, considering the sample of eight countries and the 2010-2014 period covered by the book, the gradualist approach has been the dominant approach to reforms. <>Compensation versus Noncompensation The more radical approach followed by the Islamic Republic of Iran and Jordan was accompanied by large cash compensations. In both countries these compensations were seen as indispensable to assist the poor and the middle class and discourage any form of social protest. In this sense, compensations were effective. In contrast to the countries that followed a radical approach, neither Morocco nor Tunisia resorted to comprehensive cash compensation although Tunisia expanded the cash transfer program during the period of subsidy reforms; instead, they paired reforms with other mitigating fiscal reforms. These countries not only avoided any form of social unrest but also gained relatively more from reforms than countries that resorted to compensation. The lack of compensation did not result in an overall reduction in poverty, as in the Islamic Republic of Iran and Jordan, but the overall impact on poverty was very low, also because of the initial low level of subsidies. In essence,, the two dominant approaches to reforms have been the radical approach with compensation and the gradualist approach without compensation. However, several other factors can come into play that may affect the decision about compensation such as the political climate, the overall initial level of subsidies or the existence or introduction of other social protection measures in concomitance with subsidies reforms. Depending on these factors, governments may also consider compensation in the course of gradualist reforms. It is important for the social planner to have a good knowledge of the distribution of income and expenditure prior to reforms and simulate the impact on household welfare of alternative compensation strategies. The optimal mix between price increases and cash compensation depends largely on the distribution of household incomes, and the effect of price increases on different households depends on household expenditure on subsidized products. In absolute 51 terms, the cost of price increases for richer households tends to be higher than the cost for poorer households because richer households consume more. But in relative terms (relative to total household expenditure) subsidized products tend to be more important for the poor with the exception of a few products. Chapter 2 and the country chapters have shown how SUBSIM can be used to simulate and evaluate these trade-offs.. Other forms of mitigating measures are also possible. Iran, Morocco, and Tunisia accompanied their reforms with fiscal policies that could mitigate the impact of reforms, even if these reforms were not always explicitly linked to the subsidy reforms. Iran launched a major housing scheme (in addition to cash compensation); Tunisia passed a housing program and tax deductions, and Morocco acted on the macro side with macro stabilization and fiscal policies. These reforms and their relation with subsidies reforms are effectively difficult to evaluate and they cut short of addressing the most challenging task of compensation measures, which is targeting the poor properly. More promising are reforms that aim at improving the targeting capacity of the social protection systems in place. The cost of compensation can be much reduced by passing from quasi- universal systems, such as those implemented by Iran and Jordan, to systems targeting the poor only. Poverty-focused compensations proved difficult to introduce for all countries that moved on with subsidies reforms for the simple reason that these countries did not have proper social protection systems in place. In essence, cash compensation for the poor is the most obvious social policy that would address the poverty question, reduce budget costs and be easy to evaluate in cost-benefit terms. However, this policy remains constrained because the social protection systems in the MENA Region are still underdeveloped and do not guarantee proper targeting of the poor. This contributes to explain why countries that opted for compensation did so using quasi-universal coverage rather than targeting the poor only. <>Public Information versus No Information This is not an aspect that the book has focused on but it is useful to note the contrast between the different approaches followed by the countries considered. Iran is perhaps the only country that implemented a specific public information campaign before launching the reforms. But Jordan and Morocco kept the discussion on subsidies reforms in the news for a long time before implementing reforms and Morocco was rather specific in explaining reforms when it started the 52 process. Egypt introduced reforms in July 2014 quickly, without a proper information campaign by simply exploiting the popularity of the incoming government whereas in Yemen poor communication with the public resulted in social unrest. In essence, the degree of information provided by governments prior to reforms or in the course of reforms varied significantly across countries and it was not necessarily related to the scale or pace of reforms or to social unrest. The only common denominator across countries is that nowhere reforms passed without an interest on the part of the press and some degree of public debate witnessing, once more, the importance of the topic for the region. <>Piecemeal versus wholesale reforms We define “piecemeal” reforms as those carried out product by product, tailoring price increases and product restructuring to each individual product subject to reforms. We define “wholesale” reforms as those carried out uniformly across products: for example, a 20 percent increase in the price of a set of products. All countries considered made an effort to follow a piecemeal approach. However, Tunisia has used in a couple of occasions homogeneous price increases for different products and those countries that followed a radical approach to reforms did so by treating several products at the same time. Gasoline and diesel were the first products to be reformed in all countries, then electricity, and LPG always came later. Reforms were almost never uniform across products with the exception of price increases in Tunisia at one point in time and for only two products. Products are different in their production and distribution processes, they target different types of consumers in different ways, the price structure may be different, and reforms may affect different stakeholders and touch upon different interest groups. Comprehensive wholesale reforms are often tempting because they appear simple in their design and their effect can be better measured in terms of budget outcome. The reality on the ground, however, is much more complex. As shown by the simulations in Chapter 2 and the country chapters, uniform price increases across products result in very different outcomes in terms of budget, welfare effects and effects on the various stakeholders managing subsidized products. This may explain why all governments with few exceptions opted for a piecemeal approach to reforms. <>Poor versus Middle Class 53 Who is really hurt by the reforms and who is most likely to complain? In absolute terms, the answer to both questions is the middle class. The middle class receives more subsidies in dollar amounts than the poor, and the urban middle class has generally more voice when it comes to protests. Political leaders are understandably aware and worried about this fact when it comes to subsidy reforms. The very generous compensation packages designed by Iran and Jordan extended well beyond the middle class, and although the rhetoric may have been around protecting the poor, the real target of quasi-universal cash transfers is the middle class. Egypt, Morocco, and Tunisia, however, did not formally compensate either the poor or the middle class. As already discussed, countries that opted to provide compensation did so with quasi-universal coverage. This is one area where a lot more can be done. If governments opt for compensation and in preparation for the reforms, it is important to simulate reforms and measure the budget cost of compensation under different coverage scenarios as we show throughout the book, and it is equally important to improve the targeting capacity of the social protection systems so as to be able to reach the intended population. <>Energy versus Food Subsidies Reforms In addition to their investigation of energy products, some of the researchers who contributed to this book were able to consider a limited set of food products in selected countries. The list of food products and countries that administer food subsidies is, however, not complete. For example, Egypt and Tunisia are two countries that administer food subsidies, but the case studies dedicated to these countries focused on energy subsidies only. Still, the evidence of asymmetry in reforms between energy and food items is clear. The subsidies reforms we observed have been largely on energy products, and virtually all governments had a clear preference for postponing or avoiding food subsidies reforms. This choice is partly explained by the fact that energy subsidies weigh more on the government budget than food subsidies (but not true for Libya), and the resistance to this type of reform often comes from fear of hurting the poor and the middle class and causing social unrest. Also, food subsidies are thought to work better than energy subsidies as social protection mechanisms because they tend to be allocated to primary food products largely consumed by the poor and there is also a nutrition angle to consider that may be important for the poorest countries. For example, Libya in 2010 and Egypt in 2014 opted to increase food subsidies while trying to reduce energy subsidies. 54 But in other cases countries have successfully removed food subsidies (edible oil in Morocco in the early 2000s and edible oil, tomato paste, tea, and dry yeasts in Libya in the mid-2000s) with marginal impact on welfare, no compensation, and no social implications. Therefore, countries in the MENA region showed a clear preference for reforming energy subsidies as opposed to food subsidies but history shows that it is possible to reform food subsidies. <> Direct versus indirect effects In the country chapters of this book, indirect effects for food products have been estimated only for two products (bread and sugar) in only one country (Morocco) and results show that these effects are negligible. Indirect effects related to energy products have been estimated in four of the eight countries considered (Morocco, Tunisia, Jordan and Iran) and, in the case of Iran, indirect effects are only available for all products aggregated. Therefore, tentative conclusions on the role of indirect effects for energy products can be made comparing three countries (Morocco, Tunisia, Jordan) and three products (electricity, gasoline and diesel). Moreover, in the case of Morocco, gasoline and diesel effects have been estimated jointly and cannot be separated. Comparing available countries and products, we can nevertheless derive three tentative conclusions on the role of indirect effects (see Table 1.3): 1) For electricity, the share of indirect effects on total effects seems quite consistent across countries and estimated around 40 percent; 2) The share of indirect effects of petroleum products is greater than the share of non-petroleum products; and 3) The share of indirect effects of diesel is around 80 percent and generally higher than the share of gasoline. The last two points are expected given the role of petroleum products and diesel in particular in the production processes. Results on electricity are perhaps more interesting and point to a regularity that would call for further research. See also Coady et al. (2015) on indirect subsidies. Table 1.3: Shares of Indirect Effects over total effects (%) Morocco Tunisia Jordan Gasoline 87.8 51 14 Diesel 87.8 89.1 77 Liquefied Petroleum Gas (LPG) n.a. 14.4 n.a. 55 Kerosene n.a. n.a. n.a. Electricity 36.6 40.7 41 <>Political Timing of Reforms It is also instructive to reflect on the timing of reforms in relation to the political context in which they occurred. This chapter has argued that reforms were implemented during an extraordinary period of political and social changes for the Region and that this extraordinary period has been partly responsible for the reforms. But it is also true that not all countries experienced the same political changes and not all countries reformed equally. For example, it is clear that Morocco and Jordan had a comparative advantage in relation to Tunisia,Libya or Yemen in that these countries introduced political changes in a piecemeal manner and managed to avoid a revolution and its economic costs. Political stability evidently provided the government of Morocco with more time and resources to prepare and carry out reforms in an orderly fashion while allowed Jordan to be rather bold with radical reforms. Egypt implemented the first radical reform when El-Sisi came to power and had the political and administrative force to bring about the reforms that had proved difficult to implement under previous political settings. In Libya, Gaddafi brought about radical reforms of food subsidies in the mid-2000s, when he enjoyed political stability and a certain international support, only to backtrack on all reforms when he needed to buy support during the period that preceded the 2011 revolution. Libya has not carried out any reform between 2011 and 2014 despite the size of subsidies in this country because internal civil conflict and political instability made reforms very risky. Although the budget crisis has provided the main impetus for reforming subsidies, the political setting has determined how and when reforms were actually implemented. <>Unfinished Business Chapter 2 offers a comparative analysis of subsidies and simulations of further subsidy reforms. The eight case studies (chapters 3 through 10) also simulate the impact of the total removal of subsidies on welfare, poverty, inequality, and the government budget. The results of these investigations show that subsidy reforms in 2014 were far from complete, not only in the 56 countries that have still to embark on reforms but also in countries that went through deep reforms such as Iran and Jordan. The complete elimination of subsidies is hard to accomplish and requires strong political will as well as a convergence of other elements that facilitate reforms such as favorable international oil prices, a stable social situation and a well-structured reform package. Progress on subsidy reforms also depends on the product considered. By the end of 2014, and with the notable exceptions of Iran and Libya, subsidies on gasoline and diesel were reduced to small amounts. Further reforms on these products will imply ending price regulations or adopt automatic indexation mechanisms that result in zero subsidies Independently of the cost and benefits of this move, this is an epochal change for governments that have controlled prices of these commodities for decades and will require a strong political will. Different is the question of LPG. None of the countries studied carried out comprehensive reforms of this product in a consistent manner. A couple of countries increased the price of LPG, but most did not touch this price, and all now face enormous challenges. Before the fall in oil prices, the elimination of subsidies on LPG entailed price increases from 44 percent (Yemen) to 947 percent (Libya). With the exception of Morocco, none of the countries studied had a clear strategy to eliminate LPG subsidies in 2015 or in the years to come. LPG is a product used by households for cooking and is largely used by the poor, which makes governments reluctant to touch the price of this product. The production and distribution of LPG is mostly in the hands of few entities that may block reforms. Reforming LPG subsidies is, however, possible. Egypt and Tunisia have explored the possibility of combining the expansion of the natural gas network with the reduction in the use of LPG bottles. Natural gas networks are expanding in these countries, and their governments could facilitate the expansion of the network in poorer urban neighborhoods by subsidizing connections to the network. The cost of natural gas for household use is competitive with LPG, and even poor households may be willing to switch to the new system, which was the experience in Europe during the 1960s and 1970s. To encourage this process while reducing subsidies, governments could proceed with small but regular increases in the price of the LPG bottle and use the revenue to expand the natural gas network further or compensate communities that cannot be reached. The other possibility explored by some countries is to introduce quotas and 57 limit consumption in this way. Doing so is possible, although quotas require the introduction of administrative systems such as user cards, which are costly and may generate illegal or informal redistribution systems of the product under quotas. Egypt has struggled with these problems for years and has yet to find a definitive solution for LPG. Electricity subsidies have also their specificities. Most countries have now proceeded with gradual increases, and some countries (Morocco and Jordan) have instituted a reform of the tariff structure. The central problem of electricity subsidies relates to the production of electricity, which in many countries still relies on expensive heavy fuels as opposed to cheaper alternatives such as hydroelectric and natural gas power. The crisis of electricity subsidy of Jordan started when the country had to abandon the production of electricity with natural gas due to the cuts of imports from Egypt. Jordan had to switch to heavy fuels that almost quadrupled the cost of production of electricity. The costs quickly became a major liability for the Jordanian government. In these cases the main solution to the electricity subsidies problem is changing the source of energy used to produce electricity. It is also possible, however, to restructure tariffs in a way that are closer to the consumers' capacity to pay for electricity and reducing the consumer surplus, which is the difference between what consumers are willing to pay for a particular product and what they effectively pay on the market. There are some margins to do that in some countries, as tariffs blocks are obsolete and need to be rethought in the light of current consumption patterns. Small, transparent, and regular increases in the price of electricity is also a viable option that countries such as Morocco and Tunisia have experimented with successfully. Several food subsidies remain in the MENA Region, and they are mostly subsidies on flour, bread, and sugar. The notable exceptions are Libya, which still subsidizes a wide set of food products, and Tunisia and Egypt which maintain food subsidies on essential consumption items. Where they exist, food subsidies can be high and similar in size to energy subsidies. The political will to remove these subsidies is low as these subsidies are important for the poor. Here the unresolved question is how to compensate the poor if subsidies are removed. MENA countries lack developed social protection systems and are unable to target the poor sufficiently well. The result is a tacit consensus between the government and the population for keeping food (mostly bread) subsidies in place. Quotas are already in place in some countries and could work in the direction of reducing subsidies in other countries, but introducing a quota system is administratively complex and may be expensive, especially if this is done for only one product. 58 Where quotas are in place, as in Libya, one possibility is to reduce the quantity amount of the quota. <> A success story? Table A1 in annex summarizes and compares the main features of reforms across the eight countries considered. As already discussed, the MENA region offers a variety of experiences with subsidy reforms (non-reformers, gradual reformers, radical reformers or a mix of the two) in countries with different initial characteristics (net importer or net exporters of energy; upper middle-income or lower middle income) and which experienced different political changes (mild political changes or revolutions) during a relatively short period of time. In addition, the table compares the initial trigger of reforms; content of reforms by year; extent of reforms; the use of cash compensation; other parallel measures; use of indexation mechanisms; significant popular protests and public information campaigns. It is evident that no two countries can be considered similar if we compare all dimensions. In such a context, what is a successful subsidy reform? This is a hard question to answer and, to some extent, it is a country specific question. The difficulty that countries face when making reforms are not equal and the measure of success should we somehow “weighted” by the objective difficulties that countries face. On the other hand, one can also use some objective measures of success such as the degree of subsidies elimination and rank countries according to this parameter alone. It is therefore useful to discuss success from both a relative and an absolute angle. Using a relative perspective, the subsidy reforms that we observed in the MENA region between 2011 and 2014 can be regarded as a success story for several reasons. First, this period saw the major wave of subsidy reforms since independence. If we compare the scale and frequency of subsidy reforms during the 2011-2014 period with that of previous periods, it is evident that the latest period has seen a surge in reforms for the reasons already explained at the outset of this chapter. Second, this surge in reforms has occurred during a very complex period in social, economic and political terms. In 2010, no one predicted the social uprisings of 2011 and these uprisings have complicated subsidy reforms as compared to other world regions that enjoyed social stability. Social tensions resulted in political instability and economic declines that further complicated reforms. Yet, all countries went through some form of reforms with the notable 59 exceptions of Djibouti and Libya. The government that emerged in Libya after the fall of Gaddafi inherited the most extensive and expensive subsidy system in the region and objectively faced a daunting task in reforming subsidies during a very volatile political period. Evidently, we cannot measure success in Libya with the same measure we use for countries like Morocco and Jordan, which managed to maintain internal stability during a difficult political period. Third, reforms occurred after a prolonged period of rising food and commodity prices and a global crisis that made populations very averse to any further price increase. If we consider these three factors alone against the actual reforms implemented, the region can be looked at as a success story overall. There are also objective measures that can be used to measure success and these measures tell a somewhat different story. One of these measures is whether countries have permanently eliminated the use of subsidies for specific products. This implies lifting any kind of price control and leaving markets operating freely, or, for some products, have automatic price adjustment mechanisms that result in no cost for the government budget and no subsidies. Using this meter, only Morocco can claim to have made substantial progress over the past few years. Jordan probably follows in terms of success for petroleum products but in this country electricity subsidies remain extremely high and the major liability for the government budget. Subsidy reforms in Jordan cannot be looked at as a success until the cost of producing electricity will be brought under control. Egypt has made progress on some products like gasoline and LPG but price controls remain a prerogative of the government and subsidies remain very large for strategic products like food products and also LPG. Iran has implemented the largest subsidy reform in the region without lifting price controls, which resulted in a substantial reversal of reforms only four years after their launch. Tunisia implemented only mild reforms for products that did not suffer from major subsidies while did not touch some of the food products where subsidies are large. Djibouti’s reforms are negligible also in the light of the fact that subsidies were very low to start with and administered in terms of tax exemptions. In conclusion and with one exception, objective measure of success show that the region cannot be held as a success story. As the section above has illustrated, the path towards complete elimination of subsidies is still long and we cannot exclude that some of the countries considered will rise subsidies in the future, particularly during periods of low oil prices. 60 Overall, we learned that reforms can occur in lower and upper middle-income countries and in net energy importer or exporter countries. These are not characteristics that distinguish reformers from nonreformers or good reformers from bad reformers, despite the similar global price shocks that these countries were exposed to. Similarly, reforms can occur during periods of high or low political instability, although political stability has clearly helped some countries such as Morocco and Jordan while political instability made reforms impossible in Libya and very difficult in Yemen. In the course of subsidy reforms the countries studied have shown to follow alternative strategies which converged only on selected choices. A piecemeal approach to reforms where products are considered one at the time and reforms are tailored to the characteristics of individual products was the path followed by all reformers. A gradualist approach where reforms are carried out over a period of time has been the dominant approach historically but some countries in particular points in time opted for radical reforms. Cash compensation has been used by some reformist countries but not by others with similar social outcomes. Public information campaigns specifically designed for subsidy reforms have been rare but sustained communication with the public on subsidies reforms has been the path followed by most countries. <> What next? The book focused on a historic period (2010-2014) when oil prices were particularly high and many governments in the MENA region were forced to push through subsidies reforms because of the increasing budget constraints that subsidies entailed. Not surprisingly, the countries that requested support with subsidies reforms were prevalently net oil importers with the exceptions of Libya and Yemen, two countries that faced political instability which led to economic crises. Pressure for reforms was evidently weaker for the GCC countries where political stability was accompanied by higher budget revenues due to high oil prices. Two years after the period covered in this book the situation has reversed. The price of crude oil per barrel declined from about 105 USD in June 2014 to about 28 USD in January 2016. This evidently changes the set of incentives for reforms that net oil exporters and net oil importers may have. Yet, there are good economic reasons for all countries to push through subsidy reforms during low oil prices. For net oil importers, while the budget and political pressure for reforms has diminished, a period of low oil prices is also the ideal period to remove subsidies 61 and price indexation mechanisms because subsidies are low and the impact on prices and household welfare is minimized. For net oil exporters, low oil prices also provide a clear rationale to justify subsidy reforms via-a-vis populations that regard subsidies as an acquired right. Whether these countries will use this window of opportunity is unclear. The recent period has seen a deceleration of subsidies reforms in the countries covered by this book if compared with the previous period. The GCC countries have effectively manifested increased interest for subsidy reforms but have not really moved on with any substantial reform. Moreover, oil prices have now started to rise again and they are currently around 50 USD per barrel (March 2016). This window of opportunity may well come to an end with little progress on the front of subsidy reforms. If we compare the period studied in this book with the most recent period, budget and political pressure seem more powerful incentives to reform than the cost of removing subsidies for the population. While the debate around pros and cons of subsidies reforms is prevalently economic, the impetus for subsidy reforms is driven by few economic factors such as oil prices and is prevalently political revealing the strategic importance that governments attribute to subsidies. In the years to come, we may therefore continue to observe erratic behavior towards subsidy reforms mostly driven by temporary political and budget considerations. <>Notes The author is grateful to Vivien Foster, Gabriela Inchauste, Masami Kojima and Mustapha Nabli for useful comments on earlier drafts. All remaining errors are the sole responsibility of the author. 1. Note that the difference between the Cushing OK WTI Spot price and the Europe Brent price may be due to infrastructure constraints in the United States (the location of oil pipelines relative to that of major refineries exporting refined products, for example) combined with the ban on crude oil exports. The three series are plotted to show that the trends are the same despite differences in absolute values. 2. Since June 2007 gasoline has been subject to a quota system administered with electronic cards. 62 3. See also https://en.wikipedia.org/wiki/Iranian_subsidy_reform_plan. 4. Increasing block tariffs (IBT) apply when the tariff corresponding to a particular block applies only to the latest block of consumption, and tariffs for the previous blocks of consumption apply to the previous blocks. Volume differentiated tariffs (VDT) apply is when the tariffs corresponding to a particular block is applied to all quantities consumed up to that block. <>References Coady, D., Flamini, V. and L. Sears. 2015. The Unequal Benefits of Fuel Subsidies Revisited : Evidence for Developing Countries, IMF working Paper No. 15/250 Devarajan, S., L. Mottaghi, F. Iqbal, G. Mundaca, M. Laursen, M. Vagliasindi, S. Commander, and I. Chaal-Dabi. "Economic Monitor" Corrosive Subsidies." Working Paper 2014, World Bank, Washington, DC. EIA (Energy Information Administration). 2015. Department of Energy, Washington, DC. http://www.eia.gov/dnav/pet/pet_pri_spt_s1_m.htm. Guillaume, D., R. Zytek, and M. R. Farzin. 2011. "Iran–The Chronicles of the Subsidy Reform." IMF Working Paper WP/11/167, International Monetary Fund, Washington, DC. IMF (International Monetary Fund). 2014. Subsidy Reform in the Middle East and North Africa: Recent Progress and Challenges Ahead. Middle East and Central Asia Department, IMF, Washington, DC. IndexMundi. 2015. http://www.indexmundi.com. Kojima, M. 2013. Reforming Fuel pricing in an Age of $100 Oil. The World Bank, Washington D 63 Table A1 – Summary Comparative Table of Subsidy Reforms (2010-2014) North Africa Middle East Morocco Tunisia Libya Egypt Jordan Yemen Djibouti Iran Income level (World Bank Income Lower-middle Upper-middle Upper-middle Lower-middle Upper-middle Lower-middle Lower-middle Upper-middle Data) Net energy importer/exporter Importer Importer Exporter Exporter Importer Exporter Importer Exporter (World Bank Energy Data) Removal of indexation Budget deficit; Political budget deficit; change of budget deficit; pressure budget deficit; IFIs Initial trigger of reforms mechanism, budget Budget deficit n.a. n.a. strategy; International regime from IFIs pressure deficit sanctions Prices on gasoline, diesel, and kerosene gradually increased by Mjor increase in food Reforms 2010 n.a. n.a. no reforms n.a. n.a. no reforms about 30 percent, and and energy prices prices of LPG by 100 percent Diesel prices increased Increase in price of Gasoline prices by 14 percent, gasoline gasoline by 26% (June); Gasoline, Diesel, Increases in gasoline increased by 66 percent minor adjustments to Reforms 2012 by 20 percent, and no reforms Cut in subsidies and no reforms Electricity +7% prices and diesel and kerosene the 2010 reform industrial fuel by 27 introduction of cash prices doubled. percent. program (Nov.) Electricity prices for Reactivation of price Diesel price unified Gasoline, Diesel, households increased by Fuel indexation minor adjustments to Reforms 2013 indexation for no reforms across users, including no reforms Electricity +7% 16 percent; increases in mechanism resumed the 2010 reform petroleum products the electricity sector gasoline prices Gasoline prices from LE 0.9 to LE 1.6 for 80 octane, from LE 1.85 to LE 2.6 for 92 octane, and Full removal of subsidies Indexation of fuel oil; Electricity +10% (2 from LE 5.75 to LE 6.25 for with partial reversal. price increases for rounds); Introduction of 95 octane; natural gas for Electricity tariffs Prices of diesel and minor adjustments to Reforms 2014 no reforms no reforms electricity, water, price indexation formula cars from LE 0.45 to LE increased gasoline increased by a the 2010 reform gasoline and diesel for gasoline 1.1; diesel from LE 1.1 to net 50 percent and 20 LE 1.8. Prices for natural percent gas and fuel for commercial uses also increased significantly. Revolution, new Stable, new constitution Revolution, political Revolution, changes in Stable, changes in Political instability and Political changes (2011-2014) constitution and political Stable Stable and electoral system instability and civil war governments governments civil war system Extent of reform piecemeal piecemeal no reforms piecemeal piecemeal piecemeal no reforms piecemeal Pace of reforms gradual gradual nil gradual/radical radical gradual/radical nil radical Cash compensation no yes, poor no no yes, quasi universal yes, poor no yes, quasi universal yes, introduction of a low electricity tariff for yes, stable low yes, fiscal consolidation poor households; Other parallel measures no electricity tariffs for the no no no yes, housing reforms measures increase in tax poor deductions, new social housing program Use of indexation mechanisms yes yes no no no no yes no Significant popular protests no no no no no yes n.a. no Public information campaign yes no no no no no n.a. yes 64 <>Chapter 2 <>A Comparative Analysis of Subsidies and Subsidy Reforms in the Middle East and North Africa Region Abdelkrim Araar and Paolo Verme <>Introduction As highlighted in Chapter 1, consumer subsidies in the Middle East and North Africa (MENA) Region are widespread. All of the countries in the Region administer energy subsidies, and most countries administer food subsidies on at least a few items. These subsidies are important for households in that they constitute a sizable part of household expenditure and represent an important share of governments’ expenditure or forgone revenues. Consumer subsidies are also larger in this part of the world compared to other regions (Clements et al. 2013; Sdralevich et al. 2014) and they are more heterogeneous in many respects. The initial origins, types, profile, administration, and cost and beneficiaries of subsidies vary significantly across the countries of the MENA Region. This heterogeneity makes comparisons across countries more complex, but also provides an opportunity to derive lessons on subsidies and subsidy reforms. This chapter aims to illustrate how the SUBSIM model can be used to analyze the impacts of consumer subsidies reforms and hence help guide policy reforms. Specifically, the chapter does this offering a standardized analysis of consumer subsidies in 2014. We use household budget survey data for five selected case studies and standardize the key variables for the analysis, including expenditure per capita on individual products and a basic set of household characteristics. We also update all surveys to 2014 using information on production, prices, and population growth and transform all values in purchasing power parity (PPP) using the latest round of the PPP survey (2011). We then use a version of the microsimulation model “SUBSIM,” which is designed to make comparisons across countries, to provide a comparative distributional analysis of subsidies and simulations of subsidies reforms. This version of the software is designed to compare individual products across countries and allows researchers to see how any two countries compare in the distribution of subsidies and in the outcomes of subsidies reforms. In this way, we are able to simulate the same subsidy reforms in different 65 countries and compare the outcomes across countries in terms of household welfare and government revenues. The countries considered are Libya, Morocco, and Tunisia for North Africa and Djibouti and the Islamic Republic of Iran for the Middle East. The combined populations of these countries is 130 million or about 34 percent of the population of the MENA Region. The sample includes net oil exporters such as the Islamic Republic of Iran and Libya and net oil importers such as Morocco and Tunisia. It also includes low-income countries (Djibouti), low-middle-income countries (Morocco and Tunisia), and middle-income countries such as the Islamic Republic of Iran. The products we consider are those that are the most relevant in terms of subsidies and those that are most frequently subsidized in the countries considered. These products are gasoline, diesel, liquefied petroleum gas (LPG), and electricity for energy products, and flour, bread, sugar, and vegetable oil for food products. The comparison of energy products could be done across all countries considered while the comparison of food products was possible only for selected countries. That is because for some countries like Tunisia it was not possible to gather all the necessary information while in other countries such as Djibouti some of the four food products considered were not subsidized. The focus of the analysis is on direct effects only, as it was not possible to collect and standardize a sufficient number of input-output matrixes for a comparative analysis of indirect effects. The relative importance of indirect effects changes across products and income groups. It is high for products like gasoline and for richer quintiles and small for products like bread and for poorer quintiles. Therefore, results on welfare related to reforms on food products capture the greatest share of the total effect, but results on overall welfare related to energy products miss on an important share of the total impact of subsidies reforms. These indirect effects are reported in the country chapters that use input-output tables, but will not be discussed here. Results show that the distribution and effects of subsidies are quite diverse across countries and products. Energy subsidies tend to be pro-rich in terms of absolute amounts (larger amounts accrue to richer households) but tend to be more important for the poor in terms of expenditure shares. Instead, food subsidies can be larger for the poor in absolute and relative terms. These findings do not apply everywhere, and the scale of these phenomena are different across 66 countries and products. The welfare effect of a 30 percent reduction in subsidies can be important, especially if we consider the cumulated effect across products, but the cost of compensating the loss in welfare for the poorest is generally low as compared to the budget benefits of the reform. This leaves governments with some fiscal space for compensation of other groups such as the middle class. The chapter is organized as follows. The next section illustrates the data and methods used for the analysis. The chapter then provides a comparative distributional analysis of subsidies and simulates subsidy reforms comparing the outcomes across countries. <>Data and Analytical Approach In the following sections, we describe the microdata used for the analysis and the baseline prices (subsidized products and unit subsidies) as of 2014, our baseline year. The HBS surveys, prices and methodology employed to update the data to 2014 are the same used for the country chapters. The updates were made using published IMF macroindicators for inflation and gross domestic product (GDP) per capita as well as population statistics (see Tables 2B.1 and 2B.2). The exercise that follows does not draw from the country chapters; rather, it re-estimates the distribution of subsidies and provides new simulations of subsidies reforms using the primary data files for each country and transforming expenditure into U.S. dollars ($) at purchasing power parity (PPP). This allows comparing subsidies and the outcome of subsidies reforms using a common currency. <>Microdata Table 2.1 shows the population statistics estimated directly from the surveys. These numbers are not identical to all country-specific population estimates, but they are very close. We can see that the sample of countries considered amounts to a total population of almost 130 million people, approximately 34 percent of the population in the MENA Region in 2014. The total household expenditure for the countries considered is approximately $0.63 trillion-PPP per year, which amounts to $3,913-PPP per capita, per year, and $17,381-PPP per household, per year. This average hides differences across countries. The Islamic Republic of Iran is by far the country with the highest per capita expenditure ($7,477-PPP). Morocco, and Tunisia follow with approximately $4,000-PPP, and Libya and Djibouti come last with approximately $2,000-PPP. 67 The sample of countries we have is representative of three groups of countries at different levels of economic development. We also have oil-producing countries and net exporters of oil, such as the Islamic Republic of Iran and Libya; non-oil-producing countries with some natural resources, such as Morocco; and non-oil-producing countries, such as Tunisia, which have little in the way of natural resources. Therefore, we have a certain diversity also in terms of natural endowments. Table 2.1: Baseline Population and Expenditure Statistics, in US$ at PPP Number of Total Per capita Household Country Population households expenditures expenditures expenditures Djibouti 939,000 166,966 1,856,869,376 1,977 11,121 Iran, Islamic 77,969,000 21,909 116 582,976,929,792 7,477 26,609 Rep. Libya 6,213,000 991,549 1, 318,968,832 1,983 12,424 Morocco 33,179,000 7,070,798 138,34, 810,176 4,170 19,565 Tunisia 11,060,000 2,548,655 43,800,788,992 3,960 17,186 Total 129,360,000 10,777,968 628,634,588,160 3,913 17,381 Source: World Bank estimations from Household Budget Surveys. Note: PPP = purchasing power parity. Data on household expenditure per capita can be very different from data on GDP per capita and the cross-country ranking made according to these two criteria can be quite different. This is mostly explained by the fact that total household expenditure represents different shares of GDP across countries. <>Baseline Prices and Subsidies As a reference period for the analysis, we use the very early part of 2014 when oil prices and subsidies peaked at their highest levels. A major wave of subsidies reforms occurred in the MENA Region in 2014 but this chapter focuses on the extraordinary situation faced by MENA countries before the reforms. We are interested in the prices and subsidies existing in the MENA countries just before the reforms. Table 2.2 shows the baseline prices and unit subsidies for energy products. For LPG, prices are the lowest for Libya and the Islamic Republic of Iran in that order and the highest for Djibouti. The highest shares of subsidies as a percentage of the free market price are in Libya and the Islamic Republic of Iran, the two oil-producing countries, with Libya’s LPG subsidies reaching 90.4 percent of the full price. The percentage price increases that would be necessary to 68 eliminate subsidies on LPG are remarkable. In Libya the price would have to be increased by 947 percent to eliminate subsidies and in the Islamic Republic of Iran by 500 percent. It is interesting to see that in Djibouti, the poorest of the countries considered, the price of LPG is 15 times the price in the Islamic Republic of Iran, the richest country considered. This divergence is also striking because LPG is a product that is typically consumed by the poor and it is the most important among the poor. The claim that consumers’ subsidies are a form of social protection schemes does not really hold if we observe data for LPG across countries. Prices for electricity appear less diverse, but that can be explained by the way the prices are listed—in kilowatt hours (average across tariffs blocks). As a percentage of the free market price, electricity subsidies are the highest in Tunisia. The lowest subsidies are for Libya (30.6 percent) and Morocco (42.3 percent) but still high. To reach the market price, Libya would have to increase prices by 44 percent, an increase that would not go unnoticed by the population, and Tunisia would have to increase prices by 583 percent, a staggering figure. Prices for gasoline and diesel are closer to the free market price for most countries except the Islamic Republic of Iran and Libya. The Islamic Republic of Iran and Libya in particular would have to raise prices of gasoline fivefold and more than sevenfold, respectively, to reach the free market price. For the Islamic Republic of Iran in 2014 this finding is remarkable given that this country went through a comprehensive reform of the subsidies system in 2010 that supposedly eliminated most subsidies and was costly in terms of cash transfers administered to the population in compensation of the subsidies removal. Table 2.2: Energy Unit Prices and Subsidies, in US$ at PPP (2014) Subs. Increase Subs. Increase Price Subs. Price Subs. (%) (%) (%) (%) LPG (13 kg) Electricity (kWh, av.) Djibouti 28.3 2.8 9.1 10 Iran, Islamic Rep. 1.9 9.7 83.3 500 0.18 0.25 58.5 140.7 Libya 2.9 27.4 90.4 947 0.26 0.11 30.6 44 Morocco 10.4 20.7 66.6 199.8 0.21 0.15 42.3 73.2 Tunisia 9.8 20.9 68 212.7 0.11 0.63 85.4 583 Gasoline (L) Diesel (L) Djibouti 3 -0.1 -2 2.1 0.3 11.1 12.5 69 Iran, Islamic Rep. 0.5 2.3 83.3 500 0.4 2.3 84.8 557.1 Libya 0.2 1.6 87.7 714.7 0.2 1.6 88.1 740 Morocco 3.1 0 0 2.4 0.2 7.5 8.1 Tunisia 2.5 0.2 9.1 10 2.1 0.4 17.4 21.1 Source: World Bank estimations from Household Budget Surveys. Note: PPP = purchasing power parity. For food (table 2.3), the items considered are few, but we can see that subsidies can also be quite high. For flour, subsidies represent 91.3 percent of the free market price in Libya and almost 60 percent in the Islamic Republic of Iran. Libya has also the highest subsidies for bread, sugar, and vegetable oil, and the Islamic Republic of Iran has large subsidies on bread. Therefore, the oil- producing countries seem to be those that maintained the highest food subsidies. However, subsidies are also high in Morocco for flour and sugar, and in this country these products are universally subsidized and not subject to quotas. Table 2.3: Food Unit Prices and Subsidies, in US$ at PPP (2014) Price Subs. Subs. (%) Increase (%) Price Subs. Subs. (%) Increase (%) Flour (kg) Bread (kg) Djibouti 0.759 0.053 6.5 7.0 n.a. n.a. n.a. n.a. Iran, Islamic Rep. 0.689 1.027 59.9 149.2 1.199 1.346 52.9 112.2 Libya 0.130 1.360 91.3 1,044.4 0.054 1.334 96.1 2,491.9 Morocco n.a. n.a. n.a. n.a. Flour1 1.197 0.168 12.3 14.0 % Flour2 Free 0.479 0.342 41.7 71.5 % nat. Sugar (kg) Vegetable oil (liter) Djibouti 0.865 0.061 6.5 7.0 1.422 0.171 10.7 12.0 Iran, Islamic Rep. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. Libya 0.362 1.545 81.0 427.2 0.868 4.054 82.4 467.0 Morocco n.a. n.a. n.a. n.a. Sugar1 1.393 0.682 32.9 49.0 Sugar2 Piece2 1.393 0.682 32.9 49.0 Sugar3 Cub 1.077 0.682 38.8 63.3 Source: World Bank estimations from Household Budget Surveys. Note: Subsidized flour and 3granule sugar in Morocco have different prices depending on varieties and forms; kg = kilogram; PPP = purchasing power parity. 70 <>A Distributional Analysis of Subsidies As indicated in the overview to this book, all country case studies use the microsimulation model SUBSIM to provide a distributional analysis of subsidies and simulations of alternative subsidy reforms. The publicly available version of SUBSIM comes in two flavors, SUBSIM direct, which estimates direct effects using Household Budget Survey (HBS) data only, and SUBSIM indirect, which uses HBS data and input-output matrixes to estimate direct and indirect effects. This chapter uses a third version of SUBSIM, which is not yet publicly available and which is designed to provide comparative analyses of subsidies across countries. This version is similar to the SUBSIM direct version in that it automatically provides a set of results in Excel tables and graphs that can be readily used for analysis. The difference is that this version provides results for individual products across countries instead of results for individual countries across products. As part of the distributional analysis, we look first at the importance of subsidies and subsidized products for households. We then determine who are the main beneficiaries of subsidies, as well as the potential dilemmas for reforming subsidies. When we talk about the importance of subsidized products, we should distinguish between absolute and relative importance. For absolute importance, we refer to the monetary values of subsidies or subsidized products in USD at PPP values. For relative importance, we refer to subsidies or subsidized products as a share of total household expenditure. <> The absolute importance and distribution of subsidies Table 2.4 compares the per capita expenditure of the four main energy and food products considered across countries in US$-PPP values. Looking at energy products and on average, households spend $19.7 per capita, per year on LPG, $85.5 on electricity, $54.2 on gasoline, and $9.5 on diesel. These amounts vary widely across countries. For example, Moroccans spend (in PPP values) the largest amount on LPG, electricity, and diesel. Libya has the lowest expenditure for electricity and one of the lowest for gasoline and diesel. As expected, because Libya has high subsidies and Morocco has low subsidies, it is clear that expenditures for crude oil products are partly driven by the level of subsidies. But other factors must be considered, including the desirability of these products and the exchange rate used in PPP values. 71 Subsidies on food are much less widespread in terms of countries and products. Libya has the largest variety of food subsidies, and a few other countries subsidize flour, bread, sugar, or vegetable oil, which are the four products that we analyze across countries. The largest subsidies go to flour and bread. The distinction between flour and bread is not always clear cut in the data. Some countries subsidize the price of flour for mills and then impose regulated prices on the sale of bread. What we observe in expenditure data are direct purchases of flour or bread on the part of households. Therefore, we need to estimate the flour subsidies received by households via the purchase of bread using conversion factors between these two products. As a consequence, the estimates on bread and flour should be taken with some caution. Sugar is also an important subsidized item in three countries, and vegetable oil remains subsidized in two countries. Table 2.4 Per Capita Expenditure on Subsidized Products, in US$ at PPP/year Energy Food LPG Electricity Gasoline Diesel Flour Bread Sugar Vegetable oil Djibouti 1.8 95.1 36.9 n.a. 35.8 n.a. 51 29.2 Iran, Islamic Rep 10.6 83 102.8 0.6 12.6 163.7 n.a. n.a. Libya 4.4 26.4 26.8 0.5 9 30.1 17.9 46.6 Morocco 42.6 114.9 19.9 26.6 56.7 n.a. 26.8 n.a. Tunisia 38.9 108.1 84.7 10.3 n.a. n.a. n.a. n.a. Average across countries 19.66 85.5 54.22 9.5 28.525 96.9 31.9 37.9 Source: World Bank estimations from Household Budget Surveys. The results on the distribution of subsidies across quintiles are very different depending on the product and the country (Figure 2.1). Consider LPG first. In one country, the Islamic Republic of Iran, subsidies on LPG are progressive, meaning that poorer households get the largest dollar amounts of subsidies. But for all the other countries, subsidies on LPG are clearly regressive, as richer households get the largest amounts. Subsidies for LPG vary between a few dollars for the poorest quintile in Morocco to almost $400 for the rich in Libya. These amounts are significant, particularly for the poorest countries. However, we should not take for granted that subsidies on LPG are always prorich, as shown for the Islamic Republic of Iran. Electricity subsidies are the most important in dollar amounts and exceptionally important in the Islamic Republic of Iran, where subsidies can reach up to $1,000-PPP per capita, per year for the 72 richest quintile. Subsidies are less important in other countries but still nonnegligible, varying between a few dollars and more than $300-PPP per capita, per year. In the case of electricity, subsidies invariably favor the rich in absolute terms, as the largest amounts in dollar equivalents are taken up by the richest quintiles with no exceptions across countries. Clearly, oil-producing countries are those that offer the largest subsidies via electricity, probably because the need to produce electricity with cheaper fuels is less of a priority. Also in the case of gasoline and diesel, subsidies are invariably prorich, with the largest dollar amounts taken up by the richest. The dollar amounts of these two products are relevant only in a few countries - the Islamic Republic of Iran and Libya for gasoline - that are either oil producers or endowed with natural resources. In these countries and for these products, it is evident that the dollar amounts across the distribution increase quickly as we move toward richer households, showing that the regressivity of these subsidies is steep and consistent across countries. Diesel is important only in Morocco and and Tunisia and only for the top quintile. Figure 2.1: Distribution of Energy Subsidies, in US$ at PPP/capita/year Liquefied Petroleum Gas Electricity 400 1,000 Energy subsidies, in US$ at PPP/capita/year Energy subsidies, in US$ at PPP/capita/year 350 900 300 800 250 700 200 600 150 500 100 400 300 50 200 0 Libya Iran, Islamic Djibouti Tunisia Morocco 100 Rep. 0 Iran, Islamic Rep. Libya Tunisia Morocco Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Gasoline Diesel 1,200 140 Energy subsidies, in US$ at Energy subsidies, in US$ at 1,000 120 PPP/capita/year PPP/capita/year 100 800 80 600 60 400 40 200 20 0 0 Iran, Islamic Rep. Libya Tunisia Morocco Tunisia Iran, Islamic Rep. Libya Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Source: World Bank estimations from Household Budget Surveys. 73 [[Typesetter: in figure 2.1, label the panels and move titles flush left: a. Liquefied petroleum gas; b. Electricity; c. Gasoline; d. Diesel; Y-axes: change "Subsidies" to "subsidies"; Chart area and legend: change bar colors to grayscale or patterns]] The variety and amounts of food subsidies are much smaller than energy subsidies (figure 2.2). They are below $40-PPP for flour and oil and below $20-PPP for sugar. The only significant subsidies are for bread in Libya and the Islamic Republic of Iran where the amounts can reach $900-PPP and $200-PPP, respectively, for the richest quintile, and the pattern is regressive. In general, larger subsidies accrue to richer quintiles with monotonic increases across quintiles. This pattern holds for sugar, bread, and oil for all countries and for flour in Libya and Djibouti, but not for Morocco and the Islamic Republic of Iran, where for flour subsidies are larger for poorer quintiles. Therefore, exceptions to the prorichness of subsidies may exist also for food products. Figure 2.2: Distribution of Food Subsidies, in US$ at PPP/capita/year Source: World Bank estimations from Household Budget Surveys. [[Typesetter: for figure 2.2, label the panels and move titles flush left: 74 a. Flour b. Bread c. Sugar d. Vegetable oil Y-axis: change "Subsidies" to "subsidies"; Panel b: y-axis, change 1000 to 1,000; Chart area and legend: change bar colors to grayscale or patterns]] <> The relative importance and distribution of subsidies Figure 2.3 illustrates the share of expenditure on total expenditure for the four energy products by country and by quintile. Starting with LPG, we see that Morocco and Tunisia have the highest shares of expenditure on LPG. These countries spend more in relative terms but less in absolute terms as shown in Figure 2.1. We can also see that these shares decrease as we move toward richer quintiles. The richest quintile in the Islamic Republic of Iran spends less than 0.1 percent of total expenditure on LPG. The shares in other countries are lower than 0.5 percent for all quintiles. With the only exception of Djibouti, the share of expenditure on LPG decreases with richer quintiles. The situation is rather different for electricity. We can see that the share of expenditure in Morocco is the highest for the third quintile whereas it decreases from the poorest to the richest quintiles for all other countries. This result depends on the type of tariff system in place and on the coverage of electricity. The countries that show regular decreasing shares across the distribution tend to have almost universal coverage of electricity and mild progressive pricing, whereby higher blocks of consumption correspond to higher prices applied only to the marginal quantities. In Morocco the hump-shaped distribution could be due to the particular combination of increasing block tariffs (IBT) and volume differentiated tariffs (VDT) tariffs1 and the size of the interblocks price increases. For electricity, therefore, it would be wrong to assume that the share of household expenditure is invariably more important for the poor, particularly because the poor benefit from very low tariffs. For gasoline and diesel the distributional picture is fairly consistent, but opposite to LPG. Gasoline and diesel are disproportionally consumed by richer households. In Morocco car ownership is concentrated among richer households, and the consumption of these products 75 among poorer households is confined to small quantities used for motorcycles or nontransport purposes. We see the shares of household expenditure on gasoline and diesel growing with richer quintiles as shown in figure 2.1 for almost all countries. The exceptions for gasoline are Libya and the Islamic Republic of Iran, two oil-producing countries where subsidies are high, public transport is limited, and the use of private transport is almost universal. Indeed, we can see that the distribution in these two countries are hump-shaped, with the largest expenditure relative to total expenditure borne by the middle class. The consumption of diesel is much smaller in all countries, and in Djibouti the Islamic Republic of Iran, and Libya is negligible. These are the countries where diesel cars are scarcely available or not permitted. In countries that do consume some amounts of diesel, the share of expenditure invariably grows with richer quintiles. Figure 2.3: Expenditure Shares of Subsidized Energy Products across Countries and Quintiles Liquefied Petroleum Gas Electricity 2.5 4 3.5 Expenditure share (in %) 2 Expenditure share (in %) 3 1.5 2.5 2 1 1.5 0.5 1 0.5 0 Morocco Tunisia Libya Iran, Islamic Djibouti 0 Rep. Morocco Tunisia Libya Iran, Islamic Rep. Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Gasoline Diesel 3.5 1.2 3 1 Expenditure share (in %) Expenditure share (in %) 2.5 0.8 2 0.6 1.5 0.4 1 0.5 0.2 0 0 Tunisia Djibouti Iran, Islamic Libya Morocco Morocco Tunisia Libya Iran, Islamic Djibouti Rep. Rep. Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Source: World Bank estimations from Household Budget Surveys. [[Typesetter: in figure 2.3, label the panels and move titles flush left: 76 a. Liquefied petroleum gas b. Electricity c. Gasoline d. Diesel; Chart area and legend: change bar colors to grayscale or patterns]] For food products (figure 2.4), the situation is much simpler. For all products and in all countries, the household budget shares of expenditure on subsidized products is higher for poorer households and progressively lower for richer households, as we should expect. The decrease between quintiles is also very steep in general, particularly for flour and sugar in Djibouti and bread in the Islamic Republic of Iran. These products are evidently very important for the poor in these countries, representing up to 8 percent of total expenditure for the poorest quintile. Figure 2.4: Expenditure Shares of Subsidized Food Products across Countries and Quintiles Flour Bread 7 6 6 5 Expenditure share (in %) Expenditure share (in %) 5 4 4 3 3 2 2 1 1 0 0 Djibouti Morocco Libya Iran, Islamic Rep. Iran, Islamic Rep. Libya Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Sugar Vegetable Oil 9 4 8 3.5 Expenditure share (in %) Expenditure share (in %) 7 3 6 2.5 5 2 4 1.5 3 2 1 1 0.5 0 0 Djibouti Libya Morocco Djibouti Libya Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Source: World Bank estimations from Household Budget Surveys. [[Typesetter: for figure 2.4, label the panels and move titles flush left: a. Flour b. Sugar 77 c. Bread d. Vegetable oil; Chart area and legend: change bar colors to grayscale or patterns]] <>A Policy Dilemma It should be clear by now that there is a certain trade-off between the share of expenditure on subsidized products in total household expenditure and the dollar amounts of subsidies received. To illustrate this trade-off, figure 2.5 plots these two dimensions across population percentiles for LPG in different countries. For most countries, the curves are negatively sloped for the expenditure shares, meaning that poorer households spend a larger share of total expenditure on subsidized products than richer households (figure 2.5, panel a). Also in most countries, richer households receive larger amounts of subsidies in per-capita terms (figure 2.5, panel b). This rule is not, however, always true. For example, the data for LPG in the Islamic Republic of Iran show a negative slope in both graphs, demonstrating not only that this product is more important for poorer households but also that these households receive a larger amount per capita in subsidies than richer households. This is less evident for food products, such as flour (figure 2.6). We can see that although the share of expenditure is higher for poorer households as for energy products, the subsidies per capita are more pro-poor, particularly in the Islamic Republic of Iran. In Djibouti, however, subsidies on flour are prorich. For most countries, this trade-off creates a dilemma. On the one hand, that subsidies are prorich would clearly speak in favor of eliminating subsidies with little consequences on welfare. On the other hand, these subsidized products can be relatively more important for the poor, even if subsidies are in place. The elimination of these subsidies would be felt more by the poor than by the rich with a likely effect on poverty. As we saw, the trade-off does not necessarily apply to all countries; instead, it varies across products, and the size of the trade-off may be different across products and countries. We should also note the structural relation between the values on the y-axes of the two panels in figure 2.5. Let p = unit free market price, s = unit subsidies, q = quantities, and y = total income. The y-axis of the panel a is then (pq-sq)/y and the y-axis of panel b is sq. Income and quantities being equal, the higher the unit subsidy, the lower the expenditure share. Subsidies and quantities 78 being equal, the higher is income, the lower is the share of expenditure. Because the unit market price and subsidy are set by the government and equal for all, the shape of the lines largely depend on the distribution of incomes in each country. Therefore, knowledge of the household income or expenditure distribution is an essential prerequisite to prepare subsidies reforms. Figure 2.5: Expenditure Shares of LPG versus Subsidies per Capita a. Expenditure share b. Benefits per capita .03 150 Djibouti Iran Djibouti Iran Libya Morocco Libya Morocco Tunisia Tunisia LPG expenditure share (in%) .02 100 US$-PPP .01 50 0 0 0 .19 .38 .57 .76 .95 0 .19 .38 .57 .76 .95 Percentiles of population Percentiles of population Source: World Bank estimations from Household Budget Surveys. Figure 2.6: Expenditure Shares of Flour versus Subsidies per Capita a. Expenditure share b. Benefits per capita 8 50 Djibouti Djibouti Iran, Islamic Rep. Iran, Islamic Rep. Libya 40 Libya 6 30 US$-PPP 4 20 2 10 0 0 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 0 .1 .2 .3 .4 .5 .6 .7 .8 .9 Percentiles of population Percentiles of population Source: World Bank estimations from Household Budget Surveys. <>Simulations of Subsidies Reforms In order to simulate comparable reforms across countries, we consider a flat reduction of unit subsidies by 30 percent across all products and all countries. We measure the impact of these 79 reforms on household welfare, inequality, and the government budget in this order. We also consider the cost for the government of compensating the population to reach the prereform level of welfare. The implied changes in prices of the proposed simulations are large for most countries and products, which makes the standard linear approach to subsidies simulations inappropriate. We therefore model the demand function using Cobb-Douglas preferences.2 <>Welfare Figures 2.7 and 2.8 show the impact on household welfare (measured in terms of household expenditure per capita). For each product in the figures we have two panels. The top panel illustrates the welfare impact in annual per capita US$-PPP terms. The bottom panel illustrates the welfare impact in terms of share of total household expenditure. Therefore, the top part of the figures is the absolute welfare effect, and the bottom part is the relative welfare effect. For LPG, the greatest impact of this reform would be in Morocco, with a per capita impact per year of about $20-PPP on average. The smallest impact is in Djibouti, the poorest of the countries considered. It is also instructive to see that the distributions of these impacts can be regressive or progressive depending on the country. In the Islamic Republic of Iran, the impact is regressive all along the distribution, with the highest per capita impact for the poorest quintile and the lowest impact for the richest quintile whereas they are progressive in all other countries. As these are dollar values, it is evident that the relative impact on household welfare is much greater for the poor than for the rich, as can be seen in the bottom part of the LPG figure, where it is clear that the welfare impact in terms of share of total expenditure is regressive in all countries. For electricity, the welfare impact is quite large in all countries, with the Islamic Republic of Iran having by far the highest impact followed by Libya. In the Islamic Republic of Iran, the impact on the richest quintile is very high, about $150-PPP per person, per year. But because the richest quintiles are affected the most in absolute terms, this impact is progressive in all countries. This result is due to the tariff systems in place, which typically include low tariffs for the first or the first two tariffs’ blocks and high tariffs for the last block. As the relation between electricity consumption and household welfare is quite linear in most countries, households in the richer 80 quintiles are also the largest consumers of electricity. This finding is apparent in the difference between the bars for the fourth and fifth quintiles. As for LPG, the welfare impact is progressive in absolute terms, but regressive in relative terms (relatively to total expenditure). As shown in the lower part of the electricity figure, in all countries, the relative welfare impact is regressive. Welfare impacts are also high for gasoline, especially for the oil-producing countries of Libya and the Islamic Republic of Iran. The average cost for households in the richest quintile in the Islamic Republic of Iran is about $200-PPP, a large amount even for a country that is the richest among those considered. For all countries, the welfare impacts are progressive because the poor do not own means of transport and therefore do not consume gasoline. The impacts on household welfare of diesel’s reforms are very small as compared to the impact of other products. They are around $1-PPP per person, per year. Also for diesel, the impact is progressive in all countries considered. Contrary to LPG and electricity, the relative welfare impact is not necessarily regressive but mostly progressive or hump-shaped. Figure 2.7 Welfare Impact of a 30 Percent Reduction in Energy Subsidies, in US$-PPP/capita/ye Liquefied Petroleum Gas Electricity Iran, Islamic Iran, Islamic Rep. Libya Tunisia Morocco Morocco Tunisia Rep. Libya Djibouti 0 0 Impact in US$-PPP -5 -50 Impact in US$-PPP -10 -15 -100 -20 -25 -150 -30 -35 -200 0.00% 0.00% Imapct in % Imapct in % -1.00% -2.00% -2.00% -4.00% Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Gasoline Diesel Iran, Islamic Iran, Islamic Rep. Libya Tunisia Morocco Djibouti Morocco Tunisia Libya Rep. Djibouti 0 0 Impact in US$-PPP -50 0 Impact in US$-PPP -1 -100 -1 -150 -2 -200 -2 -250 -3 0.00% 0.00% Imapct in % Imapct in % -1.00% -0.05% -2.00% -0.10% Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Source: World Bank estimations from Household Budget Surveys. 81 [[Typesetter: in figure 2.7, label the panels and move titles flush left: a. Liquefied petroleum gas b. Electricity c. Gasoline d. Diesel; Y-axes: all panels: change hyphens to minus signs; remove % from the numbers. Chart area and legend: change bar colors to grayscale or patterns]] Figure 2.8 shows the welfare impact for food items. The relative welfare impact is unambiguously regressive for all products and countries. The absolute welfare impact can be progressive or regressive for flour, but is always progressive for bread, sugar, and oil. The largest impacts are observed for bread in Libya with close to $80-PPP per person, per year for the richest quintile. Figure 2.8: Welfare Impact of a 30 Percent Reduction in Food Subsidies, US$-PPP/capita/year Source: World Bank estimations from Household Budget Surveys. [[Typesetter: for figure 2.8, label the panels and move titles flush left: 82 a. Flour b. Bread c. Sugar d. Vegetable oil Y-axes: Remove % signs from numbers; change hyphens to minus signs; Chart area and legend: change bar colors to grayscale or patterns]] <>Inequality A reduction in subsidies implies a loss in welfare, but changes in inequality (measured in terms of changes of household expenditure per capita) can go in any direction depending on the distribution of expenditure and on the parts of the population that are most affected by the reforms. As is apparent in figure 2.9, the reduction in subsidies for energy products does not make much difference for inequality in any of the countries considered, with a maximum impact observed in the Islamic Republic of Iran for only one-third of one percentage point. These changes can also be positive or negative depending on the country, although it is clear that the changes are too small to be significant. The greatest increase in inequality is obtained in Libya if oil, sugar, bread, and flour subsidies are cut by 30 percent, but even in this extreme case, inequality would increase by less than one percentage point. Figure 2.9: Inequality Impacts of a 30 Percent Reduction in Subsidies a. Energy items b. Food items 0.35 0.30 Change in headcount 0.25 0.20 0.15 0.10 0.05 0.00 -0.05 Djibouti Iran, Islamic Libya Morocco Tunisia Rep. Diesel -0.0000 0.0003 0.0041 -0.0059 -0.0030 Gasoline 0.0044 0.0334 0.1098 -0.0000 -0.0158 Electricity 0.2103 0.1255 0.0459 0.0802 LPG -0.0000 0.0724 0.0343 0.1135 0.1385 Source: World Bank estimations from Household Budget Surveys. [[Typesetter: Chart area and legend: use shades of gray; Legend values, change hyphens to minus signs]] <>Government Budget 83 What are the gains in budget revenues? How much is required in cash transfers to offset the increase in the poverty gap determined by the reform? Figure 2.10 shows the increase in per- capita government revenue of a 30 percent reduction in subsidies. The graph also shows the necessary universal transfer required to offset the change in poverty gap resulting from the reforms. This amount can be considered as the minimum universal transfer to keep the poverty gap unchanged. Government revenues are always much larger than the universal cost of compensation to bring the poverty gap back to its prereform level. It is also possible to target compensation and reduce further the cost to the budget, but governments that implemented large reforms in recent years, such as the Islamic Republic of Iran, have not followed that route. On the other hand, governments may want to compensate some of the non-poor, particularly the middle-class, to reduce the risk of political backlash in the aftermath of the reforms. This may rise substantially the cost of compensation but Figure 2.10 shows that the space for maneuver to compensate beyond the poverty gap is quite large. Therefore, unless compensation benefits are extremely large and universal, reforming subsidies with compensation is most likely to reduce the overall cost of subsidies substantially. For food items, in general, we observe that the impact is relatively low for the countries with limited subsidy programs, as is the case for Djibouti and Morocco. The picture is different for Libya, where the food subsidy program is very large. In this country and with a universal transfer designed to offset the poverty gap, the increase in per capita government revenue can be large but still below the overall gains in revenues determined by the reforms. 84 Figure 2.10: Governments’ Revenue Impact of a 30 Percent Reduction in Subsidies on Energy Products, in US$-PPP/capita/year Electricity Liquefied petroleum gas Tunisia Tunisia Morocco Morocco Libya Libya Iran, Islamic Rep. Iran, Islamic Rep. Djibouti Djibouti 0 10 20 30 40 Values in US$-PPP 0 50 150in US$-PPP Values 100 200 250 300 350 400 Per capita equivalent transfer to offset the change in the poverty gap Per capita equivalent transfer to offset the change in the poverty gap Change in the per capita government revenue Change in the per capita government revenue Gasoline Diesel Tunisia Tunisia Morocco Morocco Libya Libya Iran, Islamic Rep. Iran, Islamic Rep. Djibouti Djibouti 0 50 100 150 200 250 300 Values in US$-PPP 0.0 0.5 Values 1.0 in US$-PPP 1.5 2.0 2.5 3.0 Per capita equivalent transfer to offset the change in the poverty gap Per capita equivalent transfer to offset the change in the poverty gap Change in the per capita government revenue Change in the per capita government revenue Source: World Bank estimations from Household Budget Surveys. [[Typesetter: in figure 2.10, label the panels and move titles flush left: a. Liquefied petroleum gas b. Electricity c. Gasoline d. Diesel Legend: Delete "The" and capitalize the next word; change "headcount" to "head-count" in all panels; 85 Chart area and legend: use shades of gray]] <>Conclusion This chapter has provided a comparative analysis of the distribution of subsidies across the MENA Region and a comparative analysis of the welfare and budget effects of subsidies reforms considering a 30 percent reduction in subsidies. We used a special version of SUBSIM designed to make comparative analyses of subsidies reforms across countries in US$-PPP values. The purpose of the chapter was not to provide exact estimates of the impacts of reforms but to compare outcomes across countries and show how SUBSIM can be used for this purpose. The population sample considered is large, almost 130 million people or 34 percent of the total population in the MENA Region in 2014. All data were actualized to 2014, and all expenditures transformed into US$-PPP values using the latest 2011 PPP conversion factor. The total household expenditure considered is approximately $0.63 trillion-PPP or 3,913 US$-PPP per capita, per year on average. The sample of countries covered includes low-income countries, low-middle-income countries and middle-income countries. The sample also includes net oil exporters as well as net oil importers. We found that the size of subsidies does not necessarily relate to the needs of a population. In Djibouti, for example, the poorest of the countries considered in this chapter, the price of LPG is 15 times the price in the Islamic Republic of Iran, the richest country considered. Products such as LPG and electricity tend to have higher subsidies than gasoline. Food subsidies tend to be higher among net oil exporters, as the oil wealth is partly distributed to the population via food subsidies. Subsidized products are quite important for the populations of the MENA Region. LPG can account for more than 2 percent of total expenditure as for the poorest quintile in Tunisia, and electricity can reach 3.5 percent of expenditure as for the poorest quintile in Tunisia. And products such as sugar can reach up to 8 percent for the poorest people in Djibouti. The importance of LPG decreases with welfare, but it increases for gasoline. The consumption pattern of subsidized products partly explains who benefits from subsidies, and it is clear that the main beneficiaries can be very different depending on the product and country 86 considered. For example, in the Islamic Republic of Iran, subsidies are progressive for LPG but regressive in all other countries, and electricity and gasoline subsidies are invariably regressive in that the majority of benefits in absolute terms accrue to richer households. Comparing results on the importance of subsidized products and on the distribution of subsidies leads to an important policy dilemma. Subsidies may be very important for poor households, even though richer households receive the greatest share, which makes subsidy reforms complex from the perspective of public policies. A useful instrument to take decisions on subsidies is to compare the expenditure share curves by percentile of the expenditure distribution with the total subsidies per capita curves. Products and countries where both curves are positively sloped are the most promising for reforms because both the share of these products on household expenditure and the amount of subsidies are larger for the richer households. Simulations of a 30 percent reduction in subsidies for all products showed that the welfare implications are important particularly for electricity and LPG where these reforms can reduce household welfare for the poorest quintiles by up to 2 percent for individual products and can reach 4 percent to 5 percent if we aggregate the impact for all products. Nevertheless, the impact on the poverty gap is small and the impact on inequality is negligible. Instead, the benefits to government budgets are quite large, even if countries decide to compensate households with a universal transfer that would offset the increase in the poverty gap. This result would suggest that countries have some fiscal space for compensating citizens beyond the poor. 87 <>Annex 2A Table 2A.1a: Expenditure Shares in Energy Products (percent) Iran, Djibouti Islamic Libya Morocco Tunisia Rep. LPG Quintile 1 0.06 0.62 0.32 2.02 2.23 Quintile 2 0.09 0.3 0.28 1.58 1.61 Quintile 3 0.12 0.18 0.24 1.41 1.25 Quintile 4 0.08 0.1 0.21 1.12 1.02 Quintile 5 0.09 0.04 0.18 0.63 0.5 Population 0.09 0.14 0.22 1.02 0.98 Electricity Quintile 1 n.a. 1.86 1.66 3.11 3.55 Quintile 2 n.a. 1.53 1.58 3.25 3.27 Quintile 3 n.a. 1.33 1.42 3.34 2.85 Quintile 4 n.a. 1.13 1.28 2.99 2.68 Quintile 5 n.a. 0.8 1.17 2.35 2.44 Population n.a. 1.11 1.33 2.76 2.73 Gasoline Quintile 1 0.03 1.22 1.52 0.01 0.47 Quintile 2 0.05 1.43 1.58 0.04 0.86 Quintile 3 0.08 1.52 1.49 0.12 1.27 Quintile 4 0.4 1.49 1.38 0.23 2.02 Quintile 5 3.16 1.28 1.16 0.83 3.13 Population 1.87 1.37 1.35 0.48 2.14 Diesel Quintile 1 0 0.01 0.04 0.02 0.06 Quintile 2 0 0.01 0.04 0.05 0.15 Quintile 3 0 0 0.03 0.16 0.21 Quintile 4 0 0.01 0.03 0.3 0.22 Quintile 5 0 0.01 0.02 1.11 0.36 Population 0 0.01 0.03 0.64 0.26 Source: World Bank estimations from Household Budget Surveys. 88 Table 2A.1b: Expenditure Shares in Food (percent) Iran, Islamic Djibouti Libya Morocco Rep. Flour Quintile 1 5.95 0.95 0.63 2.29 Quintile 2 3.53 0.35 0.55 2.19 Quintile 3 2.35 0.19 0.48 1.81 Quintile 4 1.96 0.10 0.45 1.74 Quintile 5 1.12 0.03 0.37 0.79 Population 1.81 0.17 0.45 1.36 Bread n.a. Quintile 1 n.a. 5.4 2.85 n.a. Quintile 2 n.a. 3.8 2.22 n.a. Quintile 3 n.a. 2.9 1.80 n.a. Quintile 4 n.a. 2.1 1.40 n.a. Quintile 5 n.a. 1.1 0.94 n.a. Population n.a. 2.2 1.52 n.a. Sugar Quintile 1 7.77 n.a. 1.23 1.68 Quintile 2 4.86 n.a. 1.05 1.16 Quintile 3 3.68 n.a. 0.99 0.86 Quintile 4 2.90 n.a. 0.88 0.67 Quintile 5 1.56 n.a. 0.76 0.34 Population 2.58 n.a. 0.90 0.64 Oil Quintile 1 3.02 n.a. 3.39 n.a. Quintile 2 2.28 n.a. 2.76 n.a. Quintile 3 1.91 n.a. 2.60 n.a. Quintile 4 1.68 n.a. 2.28 n.a. Quintile 5 1.10 n.a. 1.93 n.a. Population 1.48 n.a. 2.35 n.a. Source: World Bank estimations from Household Budget Surveys. 89 Table 2A.2a: Per Capita Subsidies in Energy Products, in US$-PPP Iran, Djibouti Islamic Libya Morocco Tunisia Rep. LPG Quintile 1 66.5 185.1 116 23.3 52.1 Quintile 2 83.2 149.6 169.1 39.1 66.5 Quintile 3 96.9 122 200.5 52.9 76.8 Quintile 4 115.6 99.7 240.7 67.6 91.1 Quintile 5 165.6 73.2 377.5 100.3 125.5 Population 105.6 125.9 220.8 56.6 82.4 Electricity Quintile 1 n.a. 334.15 108.3 20.78 50 Quintile 2 n.a. 449.1 157.91 34.95 63.91 Quintile 3 n.a. 542.06 187.3 47.25 73.78 Quintile 4 n.a. 656.06 224.79 60.35 87.49 Quintile 5 n.a. 946.57 352.57 89.58 120.56 Population n.a. 585.56 206.17 50.58 79.14 Gasoline Quintile 1 0 244.63 97.34 0 0.66 Quintile 2 -0.01 469.19 155.11 0 2.07 Quintile 3 -0.02 693.17 192.81 0 4.23 Quintile 4 -0.16 963.85 238.34 0 9.45 Quintile 5 -3.65 1 685.58 343.1 0 27.76 Population -0.77 811.22 205.33 0 8.83 Diesel Quintile 1 n.a. 0.28 0.31 0.25 0.8 Quintile 2 n.a. 0.32 0.5 1.03 3.48 Quintile 3 n.a. 0.24 0.47 4.67 6.6 Quintile 4 n.a. 1.19 0.58 12.97 9.94 Quintile 5 n.a. 1.11 0.76 114.33 30.43 Population n.a. 0.63 0.52 26.64 10.25 Source: World Bank estimations from Household Budget Surveys. 90 Table 2A.2b: Per Capita Subsidies on Food, in US$-PPP Djibouti Iran, Islamic Rep. Libya Morocco Flour Quintile 1 1.5 36.0 12.3 15.5 Quintile 2 2.0 21.9 14.1 19.5 Quintile 3 2.0 16.5 13.9 18.0 Quintile 4 2.7 12.1 14.9 18.6 Quintile 5 4.3 7.6 14.8 14.9 Population 2.5 18.8 14.0 17.3 Bread Quintile 1 n.a. 152.7 594.9 n.a. Quintile 2 n.a. 175.6 709.3 n.a. Quintile 3 n.a. 190.9 760.4 n.a. Quintile 4 n.a. 193.1 786.3 n.a. Quintile 5 n.a. 205.7 903.1 n.a. Population n.a. 183.6 750.8 n.a. Sugar Quintile 1 1.99 n.a. 14.9 10.9 Quintile 2 2.69 n.a. 15.9 12.7 Quintile 3 3.16 n.a. 16.8 13.4 Quintile 4 3.96 n.a. 17.1 15.0 Quintile 5 6.04 n.a. 17.3 18.2 Population 3.57 n.a. 16.4 14.0 Oil Quintile 1 0.77 n.a. 35.7 n.a. Quintile 2 1.26 n.a. 38.4 n.a. Quintile 3 1.64 n.a. 39.7 n.a. Quintile 4 2.30 n.a. 40.3 n.a. Quintile 5 4.26 n.a. 40.7 n.a. Population 2.05 n.a. 39.0 n.a. Source: World Bank estimations from Household Budget Surveys. 91 Table 2A.3a: Impact on Welfare of 30 Percent Reductions in Subsidies on Energy Products, in US$-PPP/capita Iran, Djibouti Islamic Libya Morocco Tunisia Rep. LPG Quintile 1 0 -14.1 -3.6 -11.8 -14.5 Quintile 2 0 -11.5 -4.7 -15.5 -18 Quintile 3 0 -9.4 -5.5 -19.5 -19.6 Quintile 4 0 -7.7 -6.5 -22.2 -22.3 Quintile 5 -0.1 -5.6 -9.3 -30.5 -20.9 Population -0.1 -9.7 -5.9 -19.9 -19.1 Electricity Quintile 1 n.a. -52.6 -16.3 -5.3 -10.9 Quintile 2 n.a. -71.2 -23.9 -8.7 -14.6 Quintile 3 n.a. -86 -28.4 -11.8 -17.1 Quintile 4 n.a. -104.1 -34.2 -15.1 -20.3 Quintile 5 n.a. -151.1 -53.7 -22.9 -27.6 Population n.a. -93 -31.3 -12.8 -18.1 Gasoline Quintile 1 0 -27.7 -14.3 0 -0.2 Quintile 2 0 -53.3 -22.8 0 -0.6 Quintile 3 0 -78.9 -28.4 0 -1.2 Quintile 4 0 -109.8 -35.2 0 -2.7 Quintile 5 1.1 -192.8 -50.7 0 -7.9 Population 0.2 -92.5 -30.3 0 -2.5 Diesel Quintile 1 n.a. -0.27 -0.35 -0.01 -0.05 Quintile 2 n.a. -0.29 -0.57 -0.02 -0.21 Quintile 3 n.a. -0.22 -0.54 -0.11 -0.4 Quintile 4 n.a. -1.12 -0.67 -0.31 -0.61 Quintile 5 n.a. -1.06 -0.87 -2.74 -1.86 Population n.a. -0.59 -0.6 -0.64 -0.63 Source: World Bank estimations from Household Budget Surveys. 92 Table 2A.3b: Impact on Welfare of 30 Percent Reductions in Subsidies on Food Products, in US$-PPP/capita Iran, Islamic Djibouti Libya Morocco Rep. Flour Quintile 1 −0.5 −8.8 −1.6 −4.2 Quintile 2 −0.6 −5.4 −1.8 −5.4 Quintile 3 −0.6 −4.0 −1.9 −5.0 Quintile 4 −0.8 −3.0 −2.1 −5.2 Quintile 5 −1.3 −1.9 −2.3 −4.3 Population −0.7 −4.6 −1.9 −4.8 Bread Quintile 1 n.a. −39.0 −49.0 n.a. Quintile 2 n.a. −45.1 −59.0 n.a. Quintile 3 n.a. −49.1 −63.6 n.a. Quintile 4 n.a. −49.7 −66.1 n.a. Quintile 5 n.a. −53.1 −76.4 n.a. Population n.a. −47.2 −62.8 n.a. Sugar Quintile 1 −0.6 n.a. −2.3 −3.0 Quintile 2 −0.8 n.a. −2.5 −3.5 Quintile 3 −0.9 n.a. −2.8 −3.7 Quintile 4 −1.2 n.a. −2.9 −4.2 Quintile 5 −1.8 n.a. −3.3 −5.1 Population −1.1 n.a. −2.7 −3.9 Oil Quintile 1 −0.2 n.a. −5.5 n.a. Quintile 2 −0.4 n.a. −6.0 n.a. Quintile 3 −0.5 n.a. −6.6 n.a. Quintile 4 −0.7 n.a. −7.0 n.a. Quintile 5 −1.3 n.a. −7.8 n.a. Population −0.6 n.a. −6.6 n.a. Source: World Bank estimations from Household Budget Surveys. 93 <>Annex 2B Table 2B.1: International Monetary Fund Macrodata Country Subject Descriptor Units Scale 2006 2007 2008 2009 2010 2011 2012 2013 2014 National 110567.4 116269.6 117047.0 118946.3 121307.8 123904.6 127752.0 Djibouti GDP per capita constant prices Units 108169.33 113800.2 currency 8 9 7 9 4 8 4 Inflation end of period consumer Index 116.765 126.303 137.985 140.974 144.918 155.96 159.9 161.7 165.4 prices Million Population Persons 0.753 0.774 0.796 0.818 0.841 0.865 0.889 0.914 0.939 s Iran, Islamic National 25 057 GDP per capita constant prices Units 26360340 26426030 26651480 27983292 28773649 26584071 25743492 25787180 Rep. currency 735.74 Inflation end of period consumer Index 48 58.8 69.2 76.5 91.6 110.4 155.885 186.579 223.894 prices Million Population Persons 70.496 71.278 72.18 73.201 74.339 75.15 76 76.978 77.969 s National Libya GDP per capita constant prices Units 7358.255 7696.338 7774.212 7599.614 7864.235 3037.559 6120.156 5464.247 4963.839 currency Inflation end of period consumer Index 106.629 114.713 125.871 126.284 130.483 165.252 159.18 161.894 174.012 prices Million Population Persons 5.686 5.782 5.877 5.964 6.053 5.943 6.032 6.122 6.213 s National 17961.77 18760.90 19443.46 19938.56 20714.09 21053.16 21787.61 22416.68 Morocco GDP per capita constant prices Units 17680.617 currency 9 8 1 7 5 1 4 4 Inflation end of period consumer Index 101.6 103.618 108 106.3 108.6 109.6 112.446 112.869 115.691 prices Million Population Persons 30.506 30.841 31.177 31.514 31.851 32.187 32.522 32.853 33.179 s National Tunisia GDP per capita constant prices Units 4367.983 4597.276 4756.819 4852.745 4943.176 4789.873 4914.562 4982.483 5066.098 currency Inflation end of period consumer Index 105.331 110.73 115.182 119.882 124.691 129.876 137.603 145.923 153.713 prices Million Population Persons 10.128 10.225 10.329 10.44 10.547 10.674 10.778 10.918 11.06 s Source: IMF World Economic Outlook database April 2014. 94 Table 2B.2: Macrodata, Prices, and Subsidies in Local Currency (2014) Country Year Macrodataa US$-PPPb Price and subsidies in local currencies LPG (13 kg) Gasoline (1 liter) Diesel (1 liter) Population Inflation GDP Price Subsidy Price Subsidy Price Subsidy growth Djibouti 2012 3.40% 5.60% 5.30% 104.104 2,948.4 294.8 315 −6.3 215 26.875 Iran, Islamic Rep. 2013 20.00% 1.30% 0.20% 8,565,406 16,643 83,214.8 4,000 20,000 3,500 19,500 Libya 2008 38.20% 5.70% −36.10% 0.691 2 18.9 0.15 1.072 0.15 1.11 Morocco 2007 7.10% 6.40% 19.50% 4.178 43.3 86.5 12.8 0 9.89 0.8 Tunisia 2010 23.30% 4.90% 2.50% 0.753 7.4 15.7 1.856 0.186 1.584 0.334 Sources: a. IMF World Economic Outlook Database, April 2014, and WDI. b. Updated to 2013 by the World Bank. 95 <>Notes The authors are grateful to Shanta Devarajan and Mustapha Nabli for useful comments on previous versions of the chapter. All remaining errors are responsibility of the authors. 1. IBT = increasing block tariffs, which means that consumers pay the marginal price on marginal quantities, for example, $0.10 on the first 100 kWh of electricity consumed, $0.15 cents on the consumption between 101 and 200 kWh, and so forth. VDT = volume differentiated tariffs, which means that consumers pay the marginal price on all quantities consumed, for example, $0.10 if they consume less or equal to 100 kWh of electricity consumed, $0.15 on all quantities consumed if they fall in the consumption block 101–200, and so forth 2. See www.subsim.org for more details on the SUBSIM model and its use. <>References Arze del Granado, F. J., D. Coady, and R. Gillingham. 2012. "The Unequal Benefits of Fuel Subsidies: A Review of Evidence for Developing Countries." World Development 40 (11): 2234−48. Clements, B., D. Coady, S. Fabrizio, S. Gupta, T. Alleyne, and C. Sdralevich. 2013. Energy Subsidy Reform: Lessons and Implications. International Monetary Fund. Kojima, M. 2013. "Reforming Fuel Pricing in an Age of $100 Oil." Energy Study 79284. World Bank, Washington, DC. http://documents.worldbank.org/curated/en/2013/01/18019602/reforming-fuel-pricing- age-100-oil. OPEC (Organization of Petroleum Exporting Countries). 2014. "Who Gets What from Imported Oil?" September. www.opec.org. Sdralevich, C., R. Sab., Y. Zouhar, and G. Albertin. 2014. Subsidy Reform in the Middle East and North Africa. Recent Progress and Challenges Ahead. International Monetary Fund, Middle East and Central Asia Department. 96 Part II Country Case Studies 97 <>Chapter 3 <>An Evaluation of the 2014 Subsidy Reforms in Morocco and a Simulation of Further Reforms Paolo Verme and Khalid El-Massnaoui <>Introduction Morocco's history with consumers’ subsidies predates World War II. Over the years subsidies have fulfilled different functions, ranging from incentives to promote exports, to price stabilization mechanisms, to social protection policies. Irrespective of their role, consumers’ subsidies continue to exist 73 years after their introduction, but they have been difficult to sustain. The global rise in commodities prices accompanied by the global rise in oil prices has turned consumers’ subsidies in a major liability for the government’s budget, becoming the main constraint to the current fiscal balance. This, in turn, has forced the government to reconsider subsidy policies, first by increasing prices of selected subsidized goods in 2012 and 2013, and then by undertaking a rather comprehensive reform in 2014, leading to a partial dismantling of the subsidy system. This chapter evaluates the 2014 subsidy reforms by simulating the impact of reforms on household welfare, poverty, and the government budget. Using a household consumption survey and input-output tables, we estimate direct effects via changes in prices of subsidized products and indirect effects via changes in prices of nonsubsidized products. We also simulate the impact of the total elimination of subsidies to see the implications of completing the reforms initiated in 2014. In addition, we consider the costs and benefits of possible compensation mechanisms in cash. Two sections of the chapter set the framework for the reforms; first, the evolution of subsidies since their introduction; and second, the political economy of reforms. The latter explains what the major obstacles to further reforms may be. The chapter is organized as follows: the first section covers the evolution of subsidies since their introduction. Following are sections that explain the baseline data, document the distribution of subsidies as of October 2014, describe the results of the simulations, and discuss the political economy of reforms. The final section offers conclusions. 98 <>The Evolution of Subsidies The subsidy system in Morocco was created in 1941 to stabilize prices of consumers’ products that had been rising strongly because of World War II.1 To cope with the war effort, France was importing heavily from Morocco,2 which contributed to higher domestic prices.3 In response, the kingdom introduced a stabilization fund called Caisse de Compensation (CDC).4 After the end of the war, the CDC continued to operate as an instrument to facilitate the entry of various French products into Morocco at competitive prices under the Open Entry regime. After independence in 1956, the government continued to use the CDC to stabilize prices of selected commodities while extending its mission to helping all troubled sectors, mostly the craft, charcoal, cement, and fertilizers industries, along with selected firms exporting strategic products. Before 1974 the CDC was financially autonomous, with its resources coming from fees and taxes levied on sectors benefiting from its support, especially from the oil sector. Its financial balance was maintained through taxation, and the proceeds were used to support troubled sectors and stabilize prices of selected commodities. The second oil shock of 2004–07 would lead the CDC into a fragile financial situation resulting in increasing budget transfers to cover its deficits. In 1986 the government introduced specific taxes on imported petroleum products, but the proceeds of these taxes were directly allocated to the state budget. This decision deprived the CDC from its most important source of revenues. From a financially autonomous instrument of equalization, the CDC turned into a subsidy fund relying mostly on the state budget. Nonetheless, the CDC was able to stabilize the burden on the budget over the period 1986–94 thanks to the removal of subsidies on selected commodities in accordance with the implementation of the structural adjustment programs of the 1980s. Between the 1980s and mid-1990s, the government gradually proceeded with the liberalization of prices of a number of subsidized products, including milk, butter, fertilizers, cement, packaging of oils, and jet fuel. For the remaining products, the government decided to reform subsidies gradually through their partial liberalization and simplification before their full liberalization. Among food products, after the liberalization of the edible oils sector in November 2000, only flour and sugar remained subsidized. For petroleum products, a new pricing system was put in place in 2013 for gasoline, diesel, and fuel oil, allowing the transmission of international price changes to the domestic market. In 2014 the government removed subsidies 99 for gasoline and fuel oil, followed by diesel. As of January 2015 subsidies are limited to flour, sugar, and liquefied petroleum gas (LPG). Annex 3A presents the main measures and reforms of the subsidy system since its creation. The following sections describe in more detail reforms for different sets of products. <>Petroleum Products The first substantial attempt to reform the subsidy system was launched in 1995 for liquid petroleum products. The reform established a price indexation system that linked domestic price changes to the fluctuations of corresponding quotations on the Rotterdam market. The system did not apply to LPG, for which the subsidy system continued to support fully its price differential. The fixing of prices for liquid petroleum products at the producers/importers level complied with the elements of the acquisition price structure set up in agreement with the main national refinery (SAMIR). The selling price to the public was revised monthly on the basis of the acquisition price and in accordance with the structure of the sale price agreed upon with the distributors (tables 3.1 and 3.2).5 In parallel to the implementation of the indexation system, other measures were taken, mostly consisting of the replacement of import duties paid on crude oil by a consumption tax and the exemption from taxes for certain sectors heavily dependent on fuel energy, such as fishing, air and maritime transport, and electricity production. Table 3.1: Pre-2013 Reform Selling Price Structure of Liquid Petroleum Products, in DH per unit Gasoline Diesel Fuel Oil DH/L DH/L DH/t FOB price 5.90 6.64 4,715.58 Transport 0.09 0.10 156.83 Port taxes 0.02 0.02 12.79 Access cost 0.12 0.14 104.30 Parafiscal tax 0.02 0.02 12.21 Stock cost 0.11 0.13 110.00 CIF Border price, including tax and port handling fees 6.26 7.04 5,111.72 CT 3.76 2.42 182.40 VAT 1.00 0.95 529.41 Duty Credit 0.02 0.01 2.92 Acquisition price, including taxes 11.05 10.42 5,826.45 100 Fees and distribution margins 0.38 0.28 90.00 Subtotal 1 11.42 10.70 5,916.45 Subtotal 2 10.42 9.76 5,387.03 Equalization 0.88 0.11 0.00 VAT 1.13 0.99 538.70 Price adjustment account (Unit Subsidy) −0.85 −2.67 −849.11 Wholesale prices, including VAT 11.59 8.19 5076.63 Premium for evaporation losses 0.06 0.04 n.a. Correction for thermal changes in inventories 0.02 0.02 n.a. Retail margin 0.32 0.26 n.a. Retail price to the public, excluding VAT 10.85 7.52 n.a. VAT 1.17 1.02 n.a. Retail price to the public (regulated by govt.) 12.02 8.54 n.a. Source: CDC website. Note: CIF = cost, insurance, and freight; CT = domestic consumption tax; DH/L = Moroccan dirham per liter; DH/t = Moroccan dirham per metric ton; FOB = free on board; n.a. = not applicable (fuel oil is sold on wholesale basis only); VAT = value added tax. Table 3.2: Example of the Selling Price Structure of Liquefied Petroleum Gas, in DH per kilogram Items Container> 5kg Container< = 5kg Acquisition price, taxes not included 8,299.3 8,299.3 Domestic consumption tax 46.0 46.0 VAT 834.5 834.5 Duty credit 3.6 3.6 Price for filling stations 9,183.4 9,183.4 Losses of filling process 183.7 183.7 Filling margin and costs 318.0 318.0 Special premium for inventory financing 30.0 30.0 Bulk transport provision 50.0 50.0 Capping of bottles 20.0 50.0 VAT 60.2 63.2 101 Sale price to distribution companies 9,845.3 9,878.3 Costs and margins of distribution companies 538.0 604.0 Costs and margin for stocking 387.5 450.0 Deduct VAT 894.7 897.7 Subtotal excluding VAT 9,876.1 10,034.6 VAT (max) 987.6 1,003.5 Compensation fund balance −7,726.2 −7,954.7 Wholesale prices, VAT included 3,137.5 3,083.3 Retailers margin 195.8 250.0 Retail price 3,333.3 3,333.3 Source: CDC website. Note: DH = Moroccan dirham; VAT = value added tax. Against the backdrop of increasing global oil prices, in 2000 the government decided to suspend the use of the price indexation system. This decision was due to the increasing political and social cost for the government to continue passing the full changes in the global prices through to the local markets, given the impact on transport services and therefore on prices of basic commodities, and on competitiveness of the domestic enterprises. Together with the suspension of the subsidy system, the government seized the opportunity of the relative easing of global prices between 2001 and mid-2004 to correct some cost items in the price structure of petroleum products that with time had been unduly favorable to the producers, importers, and distributors of fuel products. In 2002 the government revised the price structure of petroleum products to simplify it. The government also reduced the coefficient of adequacy of the local refinery from 6.5 percent to 2.5 percent. This coefficient was reduced in response to the performance of crude oil processing by the local refinery that managed to make the needed investment to enhance its production capacity and efficiency, especially for the production of diesel. Following the modernization of the local refinery in 2009, measures were taken to adapt further the price structure through indexing the freight costs and replacing the coefficient of adequacy by a lump sum for the development of storage capacities. As the global oil price started to rise again strongly by mid-2004 and up until 2012, the government was forced to make several ad hoc partial upward adjustments to local prices of selected liquid petroleum products to reduce 102 the growing pressure on the CDC and the budget. During this period, retail prices of LPG did not change (table 3.3). Table 3.3: Domestic Annual Average Prices of Main Petroleum Products 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Gasoline (DH/L) 9.18 9.85 10.54 10.26 10.75 10.32 10.18 10.18 11.35 12.23 Diesel (DH/L) 7.07 7.71 9.28 9.31 9.63 7.56 7.15 7.15 7.73 8.33 Fuel Oil (industrial) 2,302 2,595 3,233 2,887 3,124 3,032 3,358 3,678 4,254 4,666 (DH/Ton) LPG (DH/12kg 40.00 40.00 40.00 40.00 40.00 40.00 40.00 40.00 40.00 40.00 container) Sources: CDC and World Bank calculation, 2013. Note: DH = Moroccan dirham; kg = kilogram; L = liter; LPG = liquefied petroleum gas. As the global price remained high in 2013, the government decided to reform the subsidy system starting on September 16 by first reactivating the price indexation mechanism to help reverse the deteriorating fiscal trend. The indexation concerned the main liquid petroleum products, namely gasoline, diesel, and fuel oil. The new system imposed a cap on the unit subsidies for the three products to be managed by the CDC, and the remaining price differential was to be passed through to domestic prices. The implementation of the price indexation system, helped by lower global oil prices, allowed reducing subsidies by almost two percentage points of the gross domestic product (GDP) in 2013, resulting in lowering the fiscal deficit to 6 percent of GDP (from 7.3 percent of GDP in 2012). On February 1, 2014, the government stopped supporting prices of gasoline and industrial fuel oil. As a consequence, as June 1, 2014, fuel oil used for the production of electricity has been included in the indexation system, with related subsidies replaced by a direct lump-sum transfer to the National Electricity Company (ONEE) for three years (2014–17). During this period, subsidies for fuel oil used to generate electricity are phased out as established by an agreement signed between the government and the national office for electricity and water. The agreement 103 provides for gradual retail price increases of electricity over three years to match production prices to the sale prices, which will entail operational cost savings in addition to price rises of about 3.5 percent annually. Only the price of the first consumption bracket is maintained unchanged for household using less than 100 kilowatt hours (kWh) per month. Diesel has also been subjected to a gradual dismantling of its subsidies during 2014. To this end, the government decided to phase out unit subsidies to diesel from 2.15 Moroccan dirhams per liter (DH/L) in January to 0.80 DH/L in October 2014. Subsequently, the government removed diesel from its list of subsidized products as of January 2015. However, it decided to continue administering prices of liquid petroleum products through the implementation of the indexation mechanism up to the end of November 2015 when prices of all liquid petroleum products would be fully liberalized. Prices of these products would thereafter be subject to competition among the distributors. These actions have helped keep the subsidy outlays in line with their budgeted amounts while significantly reducing the vulnerability of the budget to international commodity price movements. These measures constitute major steps toward a comprehensive subsidy reform. <>Sugar and Edible Oil Before 1996 the CDC subsidized sugar on the basis of the difference between the unit cost and the selling price declared by each production unit. With this system, the state had been implicitly funding all other operating and capital expenses of the concerned firms. For edible oil, the CDC used a different method based on the average unit costs of the producing firms. This system favored larger producers at the expense of smaller units and led to inefficient use of public funds without necessarily benefiting consumers. In 1996 the government launched the first phase of import liberalization for sugar and edible oil. To keep the consumer prices to their levels before liberalization while encouraging firms to rationalize their production costs, the government introduced a lump-sum subsidy mechanism for the two products in July. The lump-sum subsidy to sugar concerned both local and imported sugar. Under this system, the importation of sugar and edible oil was subjected to tariffs, the proceeds of which allowed the CDC to cover 75 percent of edible oil subsidies and nearly 50 percent of sugar subsidies. The remaining price differential was borne by the state budget. In addition to customs duties, the government imposed other taxes on imports of both products. 104 Taxation on sugar and oil was meant to be an instrument of protection for domestic production, keeping the target border prices fixed. In 2000 prices of edible oil were totally liberalized, leading to the suppression of the related subsidy system. In 1999 the government forced certain industries, such as biscuit, chocolate, and soft drinks producers, to refund the lump-sum subsidy benefiting the sugar used as input in the production process. To maintain competitiveness of sugar-intensive national industries, the refund was abandoned in 2006, except for the soft drinks industry, which benefited from a reduced refund rate starting from 2008. In 2010 sugar exports under all its forms have been subject again to a refund of the allocated subsidy. The CDC continued to support sugar prices both directly through the consumer price, but also to the sugar industries through their main production inputs (beetroot and cane sugar). Sugar subsidies were still in place at the end of 2014. <>Wheat and Flour The government has been subsidizing flour since the creation of the CDC in 1941. It has also been protecting soft wheat produced locally for subsidized flour through high custom duties on imports. As consumption of flour and the associated subsidies started to increase rapidly, the government decided in 1988 to limit the subsidy allocated to soft wheat flour to a quota of 10 million tons per year. The 1996 liberalization phase also concerned soft wheat imports, but subjected the imports to an administered pricing mechanism at the border to protect domestic production. However, due to the surge in the price of wheat on the international market in 2007 and the need to meet the increasing demand for bread, imports of soft wheat for the production of liberalized flours benefited from import subsidies when prices exceeded the target price. The high burden of subsidies stemming from the widening gap between domestic and international prices of wheat persuaded the government to take measures to reduce, albeit marginally, subsidies benefiting the low-cost national flour. To this end, it reduced the quota of subsidized flour to 9 million tons annually, while strengthening the control of production and delivery of subsidized flour and redeploying its distribution to targeted populations, mainly using poverty maps. The government further limited the subsidized flour’s annual quota to 8.5 million tons starting from the second half of 2013. The reduction of the quota was limited to urban areas with a poverty rate below 10 percent. <>Baseline Data 105 The distributional and simulation analyses that follow rely largely on household budget survey data. These data are collected occasionally in Morocco, and the last available survey is the 2007 Living Standards Survey (LSS). The first exercise before undertaking the distributional and simulation analyses that follow requires updating the information available in the 2007 data to 2014, the year we consider for the analysis. The 2007–14 extrapolations are based on demographic and economic estimates. Table 3.4 shows the reference statistics used for the extrapolation. Table 3.4: Reference Statistics, 2007–13 Source Indicator 2007 2008 2009 2010 2011 2012 2013 GDP (current 1 616.3 688.8 732.4 764.3 804.2 850.6 909.4 prices, bn DH) GDP (real 1 prices 1998, bn 554.0 584.9 613.9 636.6 663.8 688.3 718.0 DH) GDP growth 3 (base 2007 = 100.0 105.6 110.8 114.9 119.8 124.3 129.6 100) Govt. spending 1 (current prices, 185.2 219.2 227.7 243.8 277.4 277.0 294.9 bn DH) Population 2 30,841.0 31,177.0 31,514.0 31,851.0 32,187.0 32,522.0 32,853.0 (000) Population 3 growth (base 100.0 101.1 102.2 103.3 104.4 105.5 106.5 2007) CPI (base 1 102.0 106.0 107.0 108.1 109.1 111.3 114.0 2006) CPI (base 3 100.0 103.9 104.9 105.9 106.9 109.0 111.8 2007) 106 Sources: 1. IMF 2014; 2. HCP Morocco; 3. World Bank estimates. Note: bn = billion (1,000 millions); CPI = consumer price index; DH = Moroccan dirham; GDP = gross domestic product. Based on the data presented in table 3.4 and the subsequent update of the information available in the household budget survey, we reconstructed population and expenditure figures for the year 2014 (table 3.5). The population of Morocco is estimated at 33.3 million including about 7.1 million families. Total household expenditure is estimated at 580.2 billion Moroccan dirham (DH), equivalent to DH 81,743 per household and DH 17,420 per capita. The average household size is estimated at 4.7 persons, but higher for poorer households. The first quintile (the poorest) spends about 12 percent of what the fifth quintile (the richest) spends on average. These extrapolations are not the exact figures available in macroeconomic statistics, but they represent good approximations considering that they are derived from household data and a rather old data set. Table 3.5: Baseline Population and Expenditure Data by Quintile Total Number of Total Total Population Household expenditure Quintile households expenditures expenditures (m) size s per (m) (m) per capita household 1 (poorest) 6.66 0.98 6.8 34,789 5,223 35,362 2 6.66 1.19 5.6 58,543 8,789 49,105 3 6.66 1.36 4.9 82,599 12,398 60,946 4 6.66 1.57 4.2 118,540 17,794 75,382 5 (richest) 6.66 1.99 3.3 285,699 42,913 143,304 Total 33.30 7.10 4.7 580,169 17,420 81,743 Source: World Bank estimations from household budget survey data. Note: m = millions. 107 <>A Distributional Analysis of Subsidies (October 2014) The analysis presented in this chapter covers food products (sugar and flour), petroleum products (gasoline, diesel, and LPG), and electricity. The 2014 reforms included a change in the price structure of water for household consumers, and this change has implications for household welfare. However, water is not considered to be subsidized in Morocco, and for this reason water is not considered in this analysis. The prices of subsidized products in October 2014 are described in table 3.6 together with the unit subsidies and the unsubsidized prices. LPG, flour, and electricity are the products with the highest subsidies relative to the unsubsidized price, with LPG reaching 66.6 percent of the unsubsidized price. Households spend more than DH 47 billion on subsidized products, which represents 8.1 percent of total household expenditure. The largest expenditure item among subsidized products is electricity (16 billion ). By far, the largest subsidies are for LPG, which alone costs the government about DH 11.8 billion, followed by electricity (6.4 billion) and flour (2.4 billion). Table 3.6: Subsidized Products (October 1, 2014) Unit HH exp. subs. (% Total Unit Unit Unsub. unit on subs. Unit of subs. (DH price subs. price products unsub. bn.) (DH bn. price) Gas LPG kg 3.330 6.654 9.984 66.6 5.9 11.8 Gasoline L 12.800 0.000 12.800 0.0 2.8 0 Diesel L 9.890 0.800 10.690 7.5 3.7 0.4 Sugar- kg 5.820 2.850 8.670 32.9 2.5 1.2 piece Sugar-cube kg 5.820 2.850 8.670 32.9 0.4 0.2 Sugar- kg 4.500 2.850 7.350 38.8 0.9 0.6 granul. 108 Flour-free kg 5.000 0.700 5.700 12.3 5.6 0.8 Flour-nat. kg 2.000 1.430 3.430 41.7 2.3 1.6 Electricity 16.0 6.4 0–100 kWh 0.9010 0.6600 1.5610 42.3 0.8 0.5 101–150 kWh 0.9689 0.5900 1.5589 37.8 0.8 0.5 151–200 kWh 0.9689 0.5900 1.5589 37.8 2.9 1.8 201–300 kWh 1.0541 0.5100 1.5641 32.6 4.6 2.2 301–500 kWh 1.2474 0.3167 1.5641 20.2 4.4 1.1 501 and kWh 1.4407 0.1200 1.5607 7.7 2.4 0.2 more Sources: Official Bulletins No. 6222, January 16, 2014, and No. 6288, September 4, 2014, and CDC. Note: bn = billion; DH = Moroccan dirham; HH = household; kg = kilogram; kWh = kilowatt- hour; L = liter. Figure 3.1 shows how important subsidized products are for households (panels a, c, and e, representing expenditure on subsidized products as a share of total expenditure) and how important are subsidies in individual terms ( panels b, d, and f, representing subsidies per capita). Starting from the food products (panels a and b), we can see that sugar and flour are both more important for the poor than for the rich (both curves are downward sloped in panel b). The poorest percentiles consume between 2 percent and 3 percent of total expenditure on these products, and the richest percentiles consume a tiny share of total expenditure. However, the data in panel b show that flour subsidies per capita are larger for the middle class than for the poor or the rich, and sugar subsidies favor the rich as higher subsidies per capita go to richer households. The pictures are different for petroleum products (panels c and d). Here the data show that LPG is an important item for the poorest and declines in importance for richer households, and although gasoline and diesel are not particularly relevant for the poor, they become increasingly relevant for the rich (panel d). In terms of subsidies per capita (panel c) the only important 109 product is LPG, and this product is really prorich, meaning that richer households receive higher subsidies. Therefore, LPG is the most important subsidized product for the poor, but subsidies per capita are larger for the rich despite the poor having larger households. This is one example of inequitable distribution of subsidies. The picture changes again if we look at electricity (panels e and f). The share of expenditure on electricity subsidies is declining, with poorer households consuming larger shares than richer households (panel e). Instead, in terms of subsidies per capita, electricity is pro-rich. Similarly to LPG, electricity is another product that appears to be particularly inequitable given the importance of this product for the poor and how the subsidies per capita favor the rich. Figure 3.1: Share of Total Expenditure on Subsidized Products and Amount of Subsidies per Capita, by percentile .03 400 Sugar Sugar Flour Flour 300 The total benefits per capita The expenditure shares .02 200 .01 100 0 0 .2 .4 .6 .8 1 0 Percentiles (p) 0 .2 .4 .6 .8 1 Percentiles (p) 110 .025 Gas LPG Gas LPG Gasoline 4000 Gasoline Diesel Diesel .02 The total benefits per capita 3000 The expenditure shares .015 2000 .01 1000 .005 0 0 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Percentiles (p) Percentiles (p) .035 1000 .03 800 The total benefits per capita The expenditure shares .025 600 .02 400 .015 200 .01 0 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Percentiles (p) Percentiles (p) Source: World Bank estimations from household budget survey data. Note: The y-axes in panels a, c, and e, represent expenditure on subsidized products as a share of total expenditure. The y-axes in panels b, d, and f, represent subsidies per capita. [[Typesetter: Label top left panel "a. Expenditure shares for sugar and flour" Label top right panel "b. Total subsidies per capita for sugar and flour" Label middle left panel "c. Expenditure shares for petroleum products" Label right middle panel "d. Total subsidies per capita for petroleum products" Label bottom left panel "e. Expenditure shares" Label bottom right panel "f. Total subsidies per capita" Y-axes: Use sentence style; delete "The" and capitalize the next word, in panel e, change 1000 to 1,000; Background: delete gridlines.]] 111 <Simulation of Subsidy Reforms This section considers two sets of simulations. The first simulation focuses on the reforms carried out by the government of Morocco between January and October 2014. This simulation can be considered an ex post evaluation of the 2014 subsidy reforms. These reforms include the elimination of subsidies on gasoline in January, progressive increases in the price of diesel implemented between January and October, and changes to the electricity tariffs introduced in August.6 More precisely, the progressive increases in the price of diesel included four successive reductions of the unit subsidy from DH 2.15 per liter in January 2014 to DH 0.8 in October. The August reforms of electricity included an increase of the number of blocks from four to six. Tariffs have been adjusted ,and starting from the third block, the tariffs’ system has changed from increasing block tariffs (IBT) to volume differentiated tariffs (VDT).7 Electricity billing includes a fixed cost for meter use and management. This cost is not included in the simulations for partially compensating underreporting of utilities’ consumption and estimate quantities consumed from household data that are closer to reality. The second set of simulations is the total elimination of subsidies based on October 2014 prices, the latest prices available at the time of writing. Table 3.7 provides initial and final prices for these simulations (October 1 unit price and unsubsidized price, respectively) as well as all price changes implied by the August 2014 reforms. Unit subsidies have been estimated using data on deficits published by the ONEE. For all simulations and products we use an own price-elasticity of 0.2. Table 3.7: Baseline Data for the Simulation of Subsidies Reforms, direct effects 112 January 1st 2014 October 1st 2014 Unsubsi Type of Type of Unit dized Unit Unsubsidize Unit tarificat Unit price tarificat Unit price subsidy unit subsidy d unit price ion ion price Gasoline L Linear 12.020 0.780 12.800 Linear 12.800 0.000 12.800 Diesel L Linear 8.540 2.150 10.690 Linear 9.890 0.800 10.690 Electricity Electricity 0-100 kWh IBT 0.9010 0.6600 1.5610 0-100 IBT 0.9010 0.6600 1.561 101-200 kWh IBT 0.9689 0.5900 1.5589 101-150 IBT 0.9689 0.5900 1.559 201-500 kWh IBT 1.0541 0.5100 1.5641 151-200 VDT 0.9689 0.5900 1.559 501 and more kWh IBT 1.4407 0.1200 1.5607 201-300 VDT 1.0541 0.5100 1.564 301-500 VDT 1.2474 0.3167 1.564 501 and more VDT 1.4407 0.1200 1.561 Sources: Official Bulletins No. 6222, January 16, 2014, and No. 6288, September 4, 2014. Note: IBT = increasing block tariffs; kWh = kilowatt-hour; L = liter; VDT = volume differentiated tariffs. [[Typesetter: in table 3.7, change dates to January 1, 2014 and October 1, 2014; change hyphens in number ranges to en dashes; change "tarification" to "tariff"]] The poverty lines used for all simulations are DH 2,796/capita/year ($US 316) for rural areas and DH 4,266/capita/year (US$ 481) for urban areas. These poverty lines have been estimated by updating the 2007 official poverty line for inflation. As they were in 2007, the poverty lines are quite low for a country like Morocco today and they provide a prereform poverty rate of only 4.15 percent. Keeping this poverty line is important for interpreting our results using the official poverty line. However, what is of interest for the simulations is the relative percentage change in poverty, which gives a better sense of the real impact of reforms on poverty. This percentage change will also be reported in the text. <>Evaluation of the 2014 Subsidy Reforms In this section, we simulate ex post the impact of the subsidies reforms that Morocco implemented between January and October 2014. The reforms include the elimination of the subsidies on gasoline, the progressive increases on the price of diesel, and the changes in electricity tariffs. Table 3.7 detailed the price increases and the restructuring of the electricity tariffs blocks relative to these reforms. These ex post simulations are useful in that Morocco has 113 no new available microdata that can be used to evaluate the actual impact of the reforms. Even if these data were available, it would be difficult to isolate the impact of the reforms from the impact of other shocks, which makes ex post simulations of this kind a useful tool to evaluate reforms. We divide the analysis into direct and indirect effects. Direct effects are estimated using household budget data only and are transmitted to households through price increases of subsidized products. Indirect effects are estimated by combining input-output data with household budget data. The indirect effects capture the impact that price increases on subsidized products have on the prices of nonsubsidized products and, through the latter, on household welfare. <>Direct Effects. The total impact of the 2014 subsidies reforms on households is estimated at DH 3.2 billion or DH 95 per capita, per year. Table 3.8 breaks down the data by quintile and subsidized products. The impact rises with income groups from 0.12 billion for the poorest quintile to 1.84 billion for the richest quintile. The largest contributor is electricity with 2.4 billion. In terms of household welfare, the elimination of subsidies reduces welfare by about 0.5 percent on average, with the impact being larger for the richest quintile (−0.64 percent) as compared to the poorest quintile (−0.34 percent). Table 3.8: Direct Welfare Effects of the 2014 Reforms, in DH million Total Quintile Electricity Gasoline Diesel Total (percentage of expend.) 1 (poorest) −118.0 −0.3 −1.1 −119.4 −0.34% 2 −241.4 −1.4 −4.5 −247.3 −0.42 3 −366.5 −6.3 −20.6 −393.4 −0.48 4 −490.8 −17.6 −57.1 −565.5 −0.48 5 (richest) −1,182.0 −154.1 −502.7 −1,838.8 −0.64 Total −2,398.7 −179.7 −586.0 −3,164.3 −0.5 Source: World Bank estimations using SUBSIM and household budget survey data. These reductions in welfare did not have a significant impact on poverty because the poor are not heavy users of gasoline and diesel, and the tariffs on electricity for this group (structure and prices) changed little. They also had an insignificant effect on inequality (table 3.9). The 2014 reforms saved the government about 3 billion DH, assuming that the benefits of the average 114 increase in prices due to the change in tariffs structure accrues to the government and not to producers or distributors (this is an implicit assumption of the model used for simulations). These savings come for the most part from the richest quintile and progressively less from the other quintiles. As there is no increase in poverty, there is also no need to provide a compensatory cash transfer. Table 3.9 Direct Welfare and Budget Effects of the 2014 Subsidies Reforms Prereform Postreform Change Welfare(per capita) 17,420.404 17,325.391 −95.014 Poverty (percent) 4.155 4.192 0.036 Inequality (percent) 42.433 42.381 −0.052 Subsidies (in millions) 10,371.180 7,366.350 −3,004.830 Source: World Bank estimations using SUBSIM and household budget survey data. The trade-offs between the gain in government revenues and the increase in poverty resulting from subsidies reforms are depicted in figure 3.2. Panel a shows the increase in poverty, and panel b the impact on government revenues of price increases between 1 percent and 100 percent for all products considered. From the standpoint of poverty, the only product that would have a real impact on the poverty head count is electricity for price increases above 30 percent to 40 percent. However, the reforms implemented in 2014 did not reach such price increases and did not affect the lower tariff block, which concerns the poor the most. From the standpoint of government revenues, the most promising product is electricity. This sector results in government savings higher than those resulting from increasing prices on other products. Therefore, the government has taken the right decision in terms of increasing electricity tariffs and changing the type of tariffs (from IBT to VDT) for upper blocks and by increasing the number of blocks. In fact, by increasing the number of blocks, it is possible to achieve savings while respecting the household capacity to pay for electricity (consumer demand). Moreover, prices were increased particularly for those products that are poverty neutral (in terms of direct effects) such as gasoline and diesel. 115 Figure 3.2: Sensitivity of Changes in Poverty and Government Revenues to Changes in Prices 2 1.00e+10 Electricity Electricity Gasoline Gasoline Diesel Diesel The impact on the governement revenue 8.00e+09 1.5 6.00e+09 1 4.00e+09 .5 2.00e+09 0 0 0 20 40 60 80 100 0 20 40 60 80 100 Increase in price in % The increase in prices (in %) Source: World Bank estimations using SUBSIM (subsidy simulation). Note: The y-axis in panel a represents the change in poverty expressed in percentage points. The y-axis in panel b represents the gain in the government budget in local currency. [[Typesetter: Label left panel "a. Impact on poverty head count (percentage change)" Label right panel "b. Impact on government revenue (local currency)" Background: remove box and gridlines.]] <>Indirect Effects. The simulation of direct and indirect effects uses input and output (I/O) tables and household budget survey (HBS) data combined. The baseline data for the price shocks are in table 3.10. With I/O tables it is not possible to simulate price increases by product or by tariff block given that the I/O tables are aggregated by sector. Therefore, we use averages across products belonging to the same sector or across tariffs blocks. As shown in table 3.10, the shock to the petroleum sector is a price increase of 11.15 percent, which is an average of the price shocks applied to diesel and gasoline. The assumption here is that gasoline and diesel have a similar weight in the I/O oil refining sector and that they represent almost the totality of the sector. The price shock applied to electricity is 2.1 percent, which is an average price increase across tariffs blocks weighted by the number of households in each block.8 116 The most accurate estimates for direct effects remain those provided in the previous section, and we will disregard estimates of direct effects using I/O data. What is of interest here is the relative share of indirect effects over total effects. Using this share, one can then derive a better approximation of the real value of indirect effects using the direct effects values of the previous section. Table 3.10 Indirect Effects of 2014 Reforms: Baseline Data Price Price Price Average HBS Corresponding I/O Unit January October increase price sector sector 1, 2014 1, 2014 (percent) increase Gasoline L 12.02 12.80 6.49 11.15 Petroleum D23-Oil refining Diesel L 8.54 9.89 15.81 11.15 Petroleum D23-Oil refining Electricity kWh 1.02 1.04 2.10 2.10 E001 Electric energy Sources: Official Bulletins No. 6222, January 16, 2014, and No. 6288, September 4, 2014, and World Bank estimations based on average prices for electricity. Note: HBS = household budget survey; I/O = input/output; kWh = kilowatt hour; L = liter. Results of the simulations show that the relation between direct and indirect effects varies significantly across products and across quintiles (table 3.11). If we simulate shocks for the two sectors independently we find indirect effects to be 87.79 percent of the total for petroleum products and 36.55 percent for electricity. The relative weight of indirect effects also differs across quintiles. Indirect effects on petroleum products are the quasi-totality of effects for the poorest quintile and they become 81.33 percent for the richest quintile. This is understandable because the poor consume very little gasoline and diesel. Instead, for electricity, indirect effects represent 30.1 percent of total effects for the poorest quintile and this share increases to 42.17 percent for the richest quintile. That is because the coverage of electricity is very large in Morocco and many if not most of the poor consume electricity. Table 3.11: Indirect Effects of 2014 Reforms, percent of total effects Quintile Petroleum Electricity 1 (poorest) 99.55 30.10 117 2 98.87 30.31 3 96.48 30.52 4 93.43 33.89 5 (richest) 81.33 42.17 Total 87.79 36.55 Source: World Bank estimations using SUBSIM. <>Complete Elimination of Subsidies Recall that we are estimating the complete elimination of subsidies as of October 2014, after the 2014 reforms and when subsidies on gasoline had been already removed. Therefore, simulations concern petroleum products that still benefited from some subsidies and the food products that were not affected by the 2014 reforms. The products considered are LPG, diesel, sugar, flour, and electricity. The baseline data for these simulations are those in table 3.6 (October 1, 2014). <>Direct Effects. The total impact of subsidies removal on households is estimated at DH −23.6 billion or DH −707 per capita (table 3.12). The impact rises with income groups from 2.7 billion for the lowest quintile to 7.3 billion for the highest quintile. By far, the largest contributor to this impact is LPG, which alone contributes for 11.8 billion, followed by electricity with 7 billion. In terms of household welfare, the elimination of subsidies reduces welfare by 4 percent on average, with the impact being almost three times as large for the poorest quintile (−7.8 percent) as compared to the richest quintile (−2.6 percent). Table 3.12: Direct Effects on Welfare of Subsidies Elimination, in DH million Quintile Quintile 1 Quintile 3 Quintile 4 Quintile 5 Total 2 LPG −1,405.9 −1,844.9 −2,321.1 −2,641.6 −3,619.3 −11,832.8 Diesel −0.6 −2.3 −10.5 −29.2 −257.2 −299.8 Sugar −232.0 −253.4 −252.5 −254.5 −217.7 −1,210.2 piece cube −0.1 −2.9 −9.6 −36.2 −129.7 −178.6 granulated −70.0 −97.4 −112.0 −125.8 −160.1 −565.4 Flour −33.6 −91.1 −138.0 −233.1 −291.9 −787.6 free natural −397.2 −451.5 −363.1 −285.4 −123.4 −1,620.6 Electricity −579 −974 −1,318 −1,684 −2,501 −7,057 Total −2,719 −3,718 −4,525 −5,290 −7,301 −23,552 Source: World Bank estimations using SUBSIM. 118 Note: LPG = liquefied petroleum gas. This reduction in welfare results, in turn, created a significant increase in the poverty level from an estimated 4.2 percent before the reform to 5.6 percent. It should be noted that the low poverty level observed before the reform is a rough estimate based on the last available survey (2007) inflated to 2014 prices. Therefore, the poverty level datum is probably off. But what is of interest here is the relative change in poverty, which is estimated at more than 34 percent. This is a very large increase as compared to the initial poverty level. About a third of this increase is explained by the removal of subsidies on LPG alone. We can also observe an increase in inequality estimated with the Gini coefficient, from 42.4 to 43.4, a relative increase of about 2 percent. The removal of subsidies on products that are particularly associated with the rich, such as diesel, contributes to less inequality, but, on aggregate, inequality increases. The elimination of subsidies would naturally save the government the equivalent of total subsidies or DH 23.6 billion. However, it is instructive to see what the cost would be to the government of providing a universal cash transfer to all households that would maintain the prereform poverty level unaltered. This amount is estimated at 12.0 billion and would result in government savings of 11.5 billion (table 3.13). This amount should be considered as an upper bound for transfers. If the government is able to target cash transfers to the poor to compensate for their losses in subsidies revenues, the cost for the government would be much lower. Table 3.13: Direct Effects of Elimination of Subsidies Prereform Postreform Change Welfare (per capita) 17,420 16,713 −707 Poverty 4.16% 5.60% 1.44% Inequality 42.43% 43.42% 0.99% Subsidies 23,552 m. 0.000 −23,552 m. Transfers 0 12,044 m. 12,044 m. Total budget 23,552 m. 12,044 m. −11,508 m. Source: World Bank estimations from household budget survey data. To better understand the trade-offs between the gain in terms of government revenues and the losses in terms of poverty increases of subsidies reforms, see figure 3.3. The data show the 119 increase in poverty (panels a, c, and e) and the impact on government revenues (panels b, d, and e) of price increases between 1 percent and 100 percent for all products considered. Note that these price increases may not be realistic and even above the increases necessary to eliminate subsidies. The only purpose of this exercise is to show which product is the most promising in terms of positive impact on government finances while maintaining poverty low. Concerning food products, increasing the prices of flour results in larger poverty increases as compared to sugar, but this is true only up to increases of about 40 percent. After this threshold, it is sugar that increases poverty. In terms of government finances, increases in prices of flour provide more government savings than increases on sugar all along the price increasing spectrum. There is clearly a trade-off here. If the government increases prices of flour, it will gain more than it would by increasing prices of sugar, but the cost for poverty will also be higher than increasing prices for sugar. This is true up to price increases of 40 percent. After that, a good strategy is to continue increasing prices for flour while maintaining prices of sugar as sugar becomes more costly in terms of an increase in poverty and flour continues to be superior in terms of government savings. Petroleum products (panels c and d) are simpler to interpret. The only poverty-increasing product is LPG given that poor households do not use diesel and that gasoline has no subsidies. Because increasing prices of gasoline and diesel further can increase government savings, it would be a good strategy to keep LPG subsidies while financing these subsidies with further increases in gasoline and diesel prices (from a purely poverty-savings perspective). However, we saw that LPG is prorich while panel d shows that the largest savings would be made with the increase in LPG prices. If we consider direct effects only (as we do in this section), increasing gasoline and diesel prices alone is not sufficient to fix government finances, and the government will have to address the large subsidies currently allocated to LPG. The picture is even simpler with electricity (panels e and f). Increases in electricity prices are more promising for government savings than other products but they also have a much greater impact on poverty. What is noticeable here is that price increases of electricity beyond 60 percent bring very little additional government revenues (households start to consume much less), but poverty would continue to increase steadily. The reform of electricity subsidies therefore is quite complex and needs to take into account the elasticity of consumption to price increases as well as 120 the tariffs’ brackets. The price increases that are considered in reality—for example, the 2014 reform of electricity tariffs—are below 20 percent. This is the area of the graphs that is most of interest in Morocco today. Figure 3.3: Sensitivity of Changes in Poverty and Government Revenues to Changes in Prices .3 2.50e+09 Sugar Sugar Flour The impact on the governement revenue Flour 2.00e+09 .2 1.50e+09 1.00e+09 .1 5.00e+08 0 0 0 20 40 60 80 100 0 20 40 60 80 100 Increase in price in % The increase in prices (in %) .2 8.00e+09 Gas LPG Gas LPG Gasoline Gasoline Diesel Diesel The impact on the governement revenue .15 6.00e+09 .1 4.00e+09 .05 2.00e+09 0 0 0 20 40 60 80 100 0 20 40 60 80 100 Increase in price in % The increase in prices (in %) 121 8.00e+09 2.5 The impact on the governement revenue 2 6.00e+09 1.5 4.00e+09 1 2.00e+09 .5 0 0 0 20 40 60 80 100 0 20 40 60 80 100 Increase in price in % The increase in prices (in %) Source: World Bank estimations using SUBSIM. Note: The y-axes in panels a, c, and e represent the change in poverty expressed in percentage points. The y-axes in panels b, d, and f represent the gain in the government budget in local currency. [[Typesetter: Label top left panel "a. Impact of price increases of sugar and flour on poverty head count (percentage change)" Label top right panel "b. Impact of price increases of sugar and flour on government revenues (local currency) Label middle left panel "c. Impact of price increases of petroleum products on poverty head count (percentage change)" Label middle right panel "d. Impact of price increases of petroleum products on government revenues (local currency)" Label bottom left panel "e. Impact of price increases of electricity on poverty head count (percentage change)" Label bottom right panel "f. Impact of price increases of electricity on government revenues (local currency)" In y-axes, delete the word "the" and capitalize the next word. Background: delete boxes and gridlines.]] <>Indirect Effects. As a reminder, what we are considering is the elimination of subsidies in October 2014. By that time the subsidies for gasoline had been already removed, and this product will not be considered here. We also do not consider LPG and flour, assuming that these products do not have indirect effects. Although some enterprises may use LPG bottles and some large industrial bakeries may use subsidized flour, these effects are expected to be small. Household businesses such as small street restaurants and cafés and small bakeries run by households are captured in household consumption and therefore already accounted for in the 122 direct effects. Instead, subsidized sugar, which is used as an intermediary product by the food industry, will be considered as well as diesel, which is used by commercial transport. In addition, we will consider the elimination of subsidies on electricity, as this sector functions as inputs to other sectors. With input-output tables, price shocks can be applied only to sectors rather than individual products. For goods with linear pricing (gasoline and diesel), the price shock for the sector (petroleum) is estimated as an average of the price shocks of gasoline and diesel resulting from the elimination of subsidies. For goods with nonlinear pricing (electricity), the price shock is estimated as the increase in average tariffs weighted by the number of households consuming in each block. Table 3.14 describes the price increases considered for the simulations. Table 3.14: Baseline Information of Simulation of Subsidies Removal (indirect effects) Share Subsidiz Price Unsubsidized in I/O Corresponding I/O Unit ed unit increase HBS sector unit price sector sector price (%) (%) Diesel L 9.89 10.69 38.6 3.12 Petroleum D23-Oil refining A001-2 Sugar kg 5.82 8.67 1.6 0.78 Food Agriculture E001 Electric Electricity kWh 1.04 1.56 100 49.95 Electricity energy Source: World Bank estimates from baseline prices and household data. Note: HBS = household budget survey; I/O = input/output; kg = kilogram; kWh = kilowatt hour; L = liter. Note that it is not possible to compare these simulations with the simulations on direct effects for various reasons: the simulations in this section do not cover all products simulated in the direct effects section; they include both direct and indirect effects; they consider a joint shock to different sectors; the impact is estimated on consumption items that are more aggregated than individual products as in the direct effects section; and for goods like electricity, we cannot simulate price shocks for individual tariffs’ blocks with an I/O table.It is, however, possible to gauge the relative importance of indirect effects if simulations are run one at a time. 123 Consider diesel. This product is mostly consumed by commercial transport and only moderately by households. We should therefore expect shocks to this product to have large indirect effects and small direct effects. The elimination of subsidies on diesel would result in a price increase to the petroleum sector of 3.12 percent, and this increase has indirect effects that account for 87.8 percent of the total effects (table 3.15). As predicted, indirect effects are much greater than direct effects for a product like diesel. If we consider instead a product like sugar, which is mostly consumed by households and we repeat the exercise, we find direct effects for only 2 percent of the total (recall also that industries using sugar as a production input have to reimburse the equivalent of the government subsidy). The ratio of direct and indirect welfare effects changes very significantly across products and also across quintiles (table 3.15). For diesel, indirect effects are almost 88 percent of the total, but for sugar they are only 2 percent. For electricity, indirect effects are estimated at 36.5 percent of total effects. An important difference also exists across quintiles. For diesel, the indirect effects are practically the only effects for the poorest quintile, but they become 93.4 percent for the richest quintile. For sugar, these shares are 1.03 percent and 2.84 percent, respectively, and for electricity they are 30.1 percent and 42.2 percent. These are gross estimates based on the price shocks described in table 3.14. If the government should decide, for example, to change electricity tariffs for the production sector, the effects on household welfare may be very different. Table 3.15: Indirect Effects of Subsidies Elimination of Selected Products, percent Quintile Diesel Sugar Electricity 1 (poorest) 99.55 1.03 30.10 2 98.87 1.22 30.31 3 96.48 1.48 30.52 4 93.43 1.67 33.89 5 (richest) 81.33 2.84 42.17 Total 87.79 2.00 36.55 Source: World Bank estimations using SUBSIM. 124 <>The Political Economy of Reforms The political economy of subsidy reforms in Morocco has been driven largely by the global prices of strategic commodities and by the increasing cost of subsidies to the state’s budget. From an equalization fund with own resources sufficient to conduct its mission of stabilizing prices of basic commodities over short periods of time, the CDC transformed over the years into a permanent subsidy fund relying heavily on budget transfers. With rising world prices of basic commodities, especially of fuels, the burden on the budget of the subsidy system has grown increasingly heavy. Particularly burdensome is the cost of fuels, given that Morocco depends totally on imports. The share of fuels in total subsidies was relatively small before the first oil shock in 1974, but it rose steadily over time to reach almost 90 percent in 2012. With respect to GDP, subsidy outlays rose from less than 0.5 percent over the first decades after independence to almost 2 percent by end of the 1990s. As shown in figure 3.4, the trend in the amount of subsidies followed rather closely the international price of crude oil. Figure 3.4: Correlations of Subsidies Changes with Oil Prices Source: Ministry of Finance, CDC, and World Bank 2015. Note: Oil prices are in DH/bbl (barrel); subsidies are in percentage of GDP. [[Typesetter: in figure 3.4: Turn dates to slant; align with every other tick; Data lines and legend: use two shades of gray or patterns; Background: Remove box and gridlines]] 125 The first experience with the reform of liquid fuel subsidies implemented in 1995 helped to stabilize subsidies around 1.7 percent of GDP until 2000, when the systematic use of the indexation system was suspended. The removal of subsidies on edible oil in 2000 and of jet fuel in 2005, together with the reform of the sugar subsidy system in 2006 and the price increases of liquid fuels, mitigated the impact on the budget between 2001 and 2007, but expenditures on subsidies continued to increase to reach 2.7 percent of GDP in 2007 because of the continued rise in oil prices over the period. The 2008 financial crisis had limited direct effects on Morocco’s economy, but the subsequent food and fuel price crisis had more serious repercussions. Subsidies reached a peak of 6.6 percent of GDP in 2012 when, for the first time, they became higher than budgetary investments. Over this period, subsidies explained most of the deterioration in the budget deficits (figure 3.5). Indeed, after two years of surpluses in 2007 and 2008, the budget experienced rising deficits peaking at 7.4 percent of GDP in 2012, the highest deficit since the early 1980s. The high budget deficits eroded all the budget space accumulated over the years. The resulting rapid increase in public debt was worrisome, jeopardizing the stability of the macroeconomic stance. Over the period 2008–12, public debt worsened by 13 percentage points of GDP, reaching 60.3 percent of GDP in 2012. Figure 3.5: Effects of Subsidies Changes on Budget Deficits, percent of GDP Source: Ministry of Economy and Finance 2009–14. [[Typesetter: in figure 3.5: Y-axis, change hyphens to minus signs; Bars and legend: use two shades of gray; Background: remove box and gridlines.]] 126 It was the sharp fiscal crisis of 2012 that eventually forced the government to reform subsidies. The government reactivated the price indexation mechanism for fuel products, which helped cut subsidies by an impressive 24 percent (or almost 2 percentage points of GDP) in 2013. This move, in turn, helped to reduce the budget deficit by 1.8 percentage points of GDP. The full implementation of the fuel price-indexation mechanism and the subsidies reforms in 2014 contributed to cut further subsidies by almost 20 percent (or 1 percentage point of GDP) by the end of the year. In addition, subsidies reforms were complemented by other fiscal consolidation measures. They included freezing higher wages and limits to new hires of civil servants to stop the rise of the public wage bill and improvements to the tax collection system through the extension of the tax base, harmonization of tax rates, and an effort to stop tax evasion. As a result, the budget deficit for 2014 was less than 5 percent of GDP as targeted by the 2014 budget law. The central government debt increased in 2014, but at a slower pace than in earlier years (66.4 percent of GDP compared to 63.9 percent of GDP in 2013). Despite the government's commitment to deepen the subsidies reforms, addressing the remaining subsidies on LPG and flour seems uncertain over the short term, given the social and political cost. Indeed, unlike gasoline and diesel, which are mostly consumed by the nonpoor, the shares of LPG and flour are important in the consumption baskets of the poor and the low-middle class. Over the medium term, the government might proceed with a progressive reform of LPG subsidies given the weight of these subsidies on the budget. Because subsidies for LPG mostly benefit the nonpoor in absolute terms, the government is trying to find a way to reduce the number of beneficiaries. In this case, the depth of the LPG reform would depend on the size of the targeted population. Until this reform takes place, the government is considering limiting the use of LPG only to households and excluding the agriculture sector. It is also trying to put in place a restitution mechanism like that for sugar to allow recovering the subsidy amounts received by some service activities, such as restaurants and hotels that use LPG. As for flour, the government is trying to further improve its targeting to the poor, especially in rural areas. The most recent decline in oil prices, which is being followed by price declines in major commodities, is both an opportunity and a constraint to further reforms. It is an opportunity because eliminating subsidies on the remaining subsidized petroleum products (LPG and diesel) results in a reduced impact on consumption prices. It is a constraint because low oil prices reduce 127 the amount of subsidies and the pressure on the budget and therefore the political will to reduce subsidies further. The year 2015 will prove which of these two forces will prevail in Morocco. <>Conclusion The subsidy system has a long history in Morocco, dating back to World War II. The system went through several different phases, from an export supporting system, to a price stabilization mechanism, to a pure subsidies system. The most recent evolution of oil and commodities prices forced the government to push through subsidies reforms in 2013 and 2014 with the elimination of subsidies on most products and the increase in prices on the remaining products, except for LPG, sugar, and flour. The 2013 and 2014 reforms have been effective in reducing the budget deficit while protecting the most vulnerable parts of the population. The evaluation of the 2014 subsidy reforms has shown that the government has made a set of proper choices from a distributional and budget perspective. Subsidies have been eliminated on those products, such as gasoline, that favored the rich and affected poverty the least, and the reform of products that would hurt the poor the most, such as LPG, has been delayed. Electricity tariffs have been increased in a sensible way by raising the number of blocks (and therefore reducing the consumers’ surplus) and by raising tariffs only on the upper blocks, protecting the poorest consumers. The 2014 reforms had important indirect effects, particularly for gasoline and diesel, and these reforms had an impact on poverty, although they did not seem to create a significant social backlash. Further reforms, particularly for LPG, require more complex interventions that will probably imply some form of targeting mechanism to protect the poor. Starting from the situation that Morocco faced in October 2014, we modeled the total elimination of subsidies, which implied the removal of subsidies on LPG, electricity, flour, and sugar. Our estimations showed that the government can save an additional DH 23.5 billion in direct subsidies, but they also showed these measures would result in a significant increase in poverty. Some form of compensation to the poor may be necessary to push through the total elimination of all subsidies. This problem is indeed what the government is studying. The latest global decline in oil prices has dramatically reduced the pressure for further reforms, but also provides an opportunity to lift subsidies during a period when doing so would result in minor price increases. Time will tell whether the government of Morocco will continue to push 128 through with the announced gradual reforms for electricity and LPG, therefore exploiting the opportunity provided by low oil prices, or avoid taking any political risk linked to subsidies removal profiting from the decreased budget pressure. <>Annex 3A Major Historical Landmarks of Morocco's Subsidy System Date Measures/reforms Prior to 1941 Six equalization funds (sugar, iron, fuel, eggs, wood, vegetables) 1941 Creation of the subsidy fund (Caisse de Compensation, CDC) 1941 Subsidies for flour, bread, edible oils, fats 1942 Subsidies for coal 1944 Subsidies for transportation of barley and corn 1945 Subsidies for sugar and canned milk, transportation of fresh milk 1946 Removal of subsidies for transportation of barley and corn. Subsidies for farm equipment, seeds and fertilizers. 1947 One-time subsidies for cotton cultivation for one year 1948 One-time subsidies for wheat seed for farmers 1949 One-time subsidies for legume seeds 1949 Decision to cancel the CDC; decision not applied. 1952 Introduction of a policy of encouraging milk production by subsidizing cooperatives 1953 Creation of edible oils equalization fund 1955 Subsidies for petroleum products Premiums paid to the freezing of lamb Subsidies for industries of textiles, glassware, weaponry, tanneries, cold storage. 129 Date Measures/reforms January 1959 Reimbursement of export costs carried by certain handicrafts: slippers, wool carpets, hand-made carpets 1959 Subsidies to cover operating deficits of North African coal company June 30, 1966 Removal of subsidies to export of handicrafts 1967 Creation of the BARS (procurement office of the Sahara) to be responsible for the logistics of administering subsidies for oil, sugar, and flour for the Saharan provinces 1971 Removal of subsidies for operating imbalances of North African coal company August 1972 Subsidies to butter September 1, Subsidy to milk producers 1973 December 1, Subsidies to edible oils 1973 1974 Subsidies to fertilizers Subsidies to packaging of edible oils Subsidies to jet fuel for charters and to the national air companies (RAM) 1975 Removal of subsidies to industries April 28, 1975 Subsidies to cement 1977 Subsidies to jet fuel intended for cargo flights to transport perishable goods 1981 Subsidies on a year of diesel used by farmers 1982 Removal of subsidies for butter 1983 Removal of subsidies for milk, except milk powder 130 Date Measures/reforms 1986 Liberalization of cement prices June 1989 Suppression of subsidies for edible oil packaging July 1, 1990 Liberalization of the fertilizer sector December Suppression of subsidies to jet fuel for the RAM and air transport 1994 companies January 1995 Introduction of a system of price indexation of petroleum products 1999 Introduction of a restitution system for sugar subsidies benefiting industries November 1, Removal of subsidies for edible oils 2000 2000 Suspension of the price indexation system for petroleum products August 8, 2005 Suppression of subsidies allocated to jet fuel intended for cargo flights February 28, Cancellation of the restitution system of sugar subsidies for industries of 2006 chocolate, biscuit, confectionery, ice cream, and milk derivatives, and factory-made pastries March 7, 2006 Introduction of a lump-sum subsidy for raw sugar import August 1, 2006 Suppression of subsidies to kerosene June 1, 2008 Subsidies for diesel used by coastal fishing December 31, Decrease in sugar refund rates for soft drink industries 2008 2008 Subsidies to special fuel oil used in the generation of electricity by ONEE July 2011 Subsidies for diesel used by high-sea fishing July 1, 2012 Removal of subsidies of high-sea fishing January 1, Subsidies to cover VAT on the cost of transportation of butane gas (LPG) 2014 131 Date Measures/reforms September 16, Resumption of the price indexation system for liquid petroleum products 2013 (gasoline, diesel 50 ppm, and industrial fuel oil) February 1, Removal of subsidies to gasoline and industrial fuel oil 2014 February 16, Progressive decrease each quarter of unit subsidy for diesel 2014 May 29, 2014 Removal of subsidies for fuel oil used for generating electricity January 1, Removal of subsidies to diesel 2015 Source: CDC. Note: BARS = Bureau d’Approvisionnement des Régions Sahariennes; ppm = parts per million; RAM = Royal Air Maroc; VAT = value added tax. <>Notes The authors are grateful to Abdoul Gadiry-Barry for preparing the data and to Jean-Pierre Chauffour for useful comments on the final draft. All simulations have been carried out with SUBSIM (see www.subsim.org). 1. Before 1941 there were six equalization funds to stabilize prices of sugar, steel, fuels, eggs, timber, and vegetables. 2. Morocco was a protectorate of France until 1956. 3. The main basic commodities targeted by the CDC during World War II include flour, bread, edible oil, charcoal, sugar, barley, corn, and milk. 4. In the rest of the text, CDC will also be used to include the Office National Interprofessionnel des Cereales et des Legumineuses (ONICL). Created in 1973, the agency administers subsidies for soft wheat and flour. 132 5. Note that the retail price for gasoline and diesel in 2013 were higher than the CIF border price. The difference is mostly explained by taxes. Therefore, subsidies are estimated net of taxes, which is a common practice. See, for example, IMF 2013. 6. The elimination of subsidies on gasoline is based on the unit subsidies estimated by the government at the time of the January 2014 reform. It should be noted that the retail price for gasoline was higher than the import price (see table 3.1) and that the difference is explained mostly by taxes on gasoline. Therefore, subsidies are estimated net of taxes, which is a common practice (IMF 2013). Also, the share of taxes in Morocco is lower than in countries like Italy or Germany where this share is well above 50 percent (OPEC 2014). 7. Increasing block tariffs (IBT) apply when the tariff corresponding to a particular block affects only the latest block of consumption, while tariffs for the previous blocks of consumption apply to the previous blocks. Volume differentiated tariffs (VDT) apply when the tariffs corresponding to a particular block are applied to all quantities consumed up to that block. 8. Note that the share of consumption in each block could also be used for weighting. <>References CDC (Caisse de Compensation). http://cc.gov.ma/. HCP Morocco (High Commission for the Plan). www.hcp.ma. IMF (International Monetary Fund). 2013. Energy Subsidies Reforms: Lessons and Implications. International Monetary Fund, Washington, DC. IMF World Economic Outlook database. October 2014. https://www.imf.org/external/pubs/ft/weo/2014/02/weodata/index.aspx. Ministry of Economy and Finance. 2009–14. "Notes de Conjonctures, 2009-2014, Direction du Trésor et des Finances Exterieures." Morocco OPEC (Organization of the Petroleum Exporting Countries). 2014. Who Gets What from Imported Oil? www.opec.org, September. World Bank. 2014. World Development Indicators. http://data.worldbank.org/data- catalog/world-development-indicators. 133 <>Chapter 4 <>The Socioeconomic Impacts of Energy Reform in Tunisia: A Simulation Approach Jose Cuesta, Abdel Rahmen El-Lahga, and Gabriel Lara Ibarra <>Introduction Tunisia’s improvements in monetary poverty have not translated into substantive reductions in disparities and unequal opportunities across individuals and regions. Poverty incidence declined from 35 percent in 2000 to 15 percent in 2010 (INS, BAD, and World Bank 2012). Rapid growth rates and generous universal subsidies, especially on energy, food, and transport, contributed to that successful poverty reduction, but did not have a similar effect on reducing inequalities. Despite the halving of poverty rates, the Gini coefficient fell only from 0.344 to 0.327 during the same period––a two percentage point effect 10 times smaller than that observed for poverty. Furthermore, drops in inequality were observed within regions, while inequality across regions increased leading to the concentration of extreme poverty in the typically less well-off western regions increased to 70 percent in 2010. In the midst of rapid economic growth and significant poverty reduction, the lack of equal economic opportunities may have contributed to the massive protests that ousted President Ben Ali from power in Tunisia and ignited political uprisings in other parts of North Africa and the Middle East (MENA). Subsidies are integral to the story of growth, poverty, and disparities in the MENA Region, and Tunisia’s tale is no different. IMF (2014) explains that the generalized price subsidies constitute a critical foundation of the social compact in MENA countries, acting as a deliberate cornerstone of social protection. However, those same subsidies can also introduce relative price distortions that typically provoke the following situations: overconsumption and underinvestment in subsidized sectors, the crowding out of more productive investments, delays in economic diversification, weaker current accounts and increasing budget deficits, and adverse effects on health and the environment. In Tunisia subsidies constitute a core aspect of its development model (World Bank 2013). Subsidies are pervasively present in critically productive sectors such as agriculture, energy, and 134 tourism. The current social protection model relies on untargeted food and energy subsidies, which have been proven to be unequitable and increasingly expensive. As noted in the next section, subsidies represented some 7 percent of gross domestic product (GDP) in Tunisia in 2013, but the bottom 40 percent of the distribution captured only 29 percent of energy subsidies and 34 percent of food subsidies (World Bank 2014). This failure to protect the poorest is widely acknowledged in the country, including by the postrevolution government (Government of Tunisia 2014), and is generally believed to have contributed to past social tensions (World Bank 2013). There are also concerns in terms of governance and transparency. As illustration, there are no precise estimates of any hidden subsidies for oil and natural gas generated by the national oil company selling imported crude oil and natural gas at a fraction of international prices to state- owned companies (IMF 2014). Fiscal and equity concerns have prompted the government of Tunisia to consider changes in its subsidy policy, particularly for energy. The new proposal forms part of a larger scheme of social protection reform that aims to improve the targeting of public spending. Detailed proposals have not yet been publicly discussed, but the government has announced its intention to partially remove electricity subsidies and completely eliminate other energy subsidies. In this context of uncertainty regarding subsidy reform by a recently elected administration, this chapter provides an analysis of the distributive impacts of a hypothetical subsidy reform similar to the reform the Tunisian government is considering. This analysis follows an earlier distributional study of energy subsidies in Tunisia using SUBSIM, a subsidy reform simulation methodology developed by Araar and Verme (2012). This chapter, however, makes two contributions to the earlier analysis. First, it updates existing estimates (reported in World Bank 2013) by including the most recent structure of energy prices and the most recent proposal of subsidy changes considered by the Tunisian government. Second, this analysis includes a detailed simulation of the distributional effects of alternative compensating cash transfer schemes financed from the fiscal savings accruing from the subsidy reform. To convey the implications of the reforms, the chapter starts with the evolution of energy subsidies in Tunisia. The next two sections provide an outline of the current structure of energy subsidies and report the most updated information on the socioeconomic patterns of energy 135 subsidies; that is, how consumption, spending, and subsidy benefits of residential energy differ across different socioeconomic groups. Following is an analysis of the distributive impacts of a simulated subsidy reform that partially removes residential electricity subsidies and fully removes those of diesel, gasoline, and liquefied petroleum gas (LPG). It separates direct and indirect effects and reports both distributional and fiscal effects. The impacts of fiscally neutral policies are estimated using current and new targeting mechanisms to compensate for the immediate negative welfare effects following the hypothesized subsidy reform. The final section concludes with a review of the three proposed scenarios and their impacts on poverty and inequalities. <>Evolution of Energy Subsidies in Tunisia Tunisia has a long tradition of generous energy and food subsidies. Subsidies deliberately became the backbone of the country's new social protection strategies of the 1970s. At that time, advocates justified the universal subsidies because of the large size of the informal sector, the high levels of poverty, and the lack of information systems and registries to identify and target the poor. Energy subsidies have not been reformed in depth since that time. In the early 1980s, however, Tunisia went through a painful experience reforming its food subsidies. In 1983 food subsidies reached 3 percent of GDP, with reported significant leaks to the nonpoor. Overnight, the government announced the doubling of prices of cereals and their products, including bread, semolina, pasta, and couscous (IMF 2014). The rushed decision took the public by surprise, and after a month of widespread protests, the reform was abandoned. Later, during the Ali regime, the government did not attempt any in-depth reform of the subsidy systems in place since the 1970s, managing instead to maintain the generous system throughout both difficult and prosperous times. During 1991–93, the government launched a gradual reform on food subsidies, favoring foods largely consumed by the poor—such as lower-quality bread—and phasing out subsidies on foods consumed by the rich (IMF 2014). A well-timed awareness campaign coupled with increases in minimum wages and strengthening of other social protection programs helped improve the targeting and fiscal burden of food subsidies (IMF 2014). During the final years of the Ali regime and the recent postrevolution period, the spending and composition of Tunisia’s subsidies have notably changed (figure 4.1). During the last 10 years, the combined spending on energy, food, and transportation has more than tripled, rising from 2 136 percent of GDP in 2005 to 7 percent in 2013. Energy subsidies, in particular, increased fourfold during that period. Energy subsidies reached 4.7 percent of GDP in 2013, with sustained increases since 2010, reflecting the partial (rather than the full) pass-through of international oil prices to domestic prices sought by the government (IMF 2014). Regarding the composition of subsidies, during the postrevolution period, energy subsidies increased both in absolute and relative terms. As a result, energy subsidies went from one-third of total public subsidies prior to the revolution to about two-thirds in 2013. In contrast, food and other basic needs’ subsidies have lost relative weight in the total subsidy bill despite having notably increased in absolute terms. With respect to other public expenditures, energy subsidies in Tunisia accounted for one- fifth of all public spending, or 7 percent of the GDP in 2013, the latest available figure. Because they are considered the backbone of the social protection strategy, it is not surprising that public spending on subsidies exceeds that of social assistance, health, and education, and individual programs for youth, children, or women (figure 4.2). Figure 4.3: Evolution of the Composition and Level of Subsidies by Type, 2005–13 7.0 6.0 5.0 4.7 4.0 3.3 3.0 3.0 2.4 1.5 2.0 0.9 0.7 0.9 1.2 1.1 1.9 1.7 1.8 1.8 1.9 1.0 1.3 1.4 1.2 0.6 0.7 0.0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2013 Transportation Basic Products Energy (Apr) (Nov*) Source: World Bank calculations using data from Ministère des Finances, October 2013. Note: Basic products refer to food products such as cereals, bread, sugar, and vegetable oil; * = forecast. [[Typesetter: Y-axis: Label: "Percent of GDP"; Remove numbers from the chart area; Bars and legend: use shades of gray; Background: Remove box.]] Figure 4.4: Public Spending by Sector, Including Subsidies, percent of 2013 GDP 137 30 Percentage in Government Budget 24.4 25 18.1 19.2 20 15 12.8 10.6 10 5.2 4.1 5.2 4.9 5.2 5 3.5 1.1 2.2 1.5 1.2 0 Source: World Bank staff calculations using data from Tunisian Ministère des Finances, October 2013. Note: Education includes all levels; subsidies refer to explicit subsidies; social assistance includes cash transfer programs and health cards; other social services includes programs and services of the Ministère des Affaires Sociales, de la Jeunesse, and de la Femme et l’Enfance; health does not include health insurance. Subsidies are further disaggregated into three categories, basic products, transportation, and energy. [[Typesetter: in figure 4.2 Use sentence style for labels. Lower case for "Products" Y-axis: Change to "Percent of govt. budget"; Chart area: Use two shades of gray; remove numbers; Background: remove box.]] The changes in the composition and magnitude of subsidies reflect recent specific changes in the policy of energy subsidies. In effect, after the immediate and deliberate use of subsidies to appease postrevolution social tensions, the government of Tunisia began implementing a gradual strategy of subsidy reduction and improvement in public spending targeting. As reported by the IMF (2014), the prices of gasoline, diesel, and electricity increased by 7 percent in September 2012, followed by similar increases in March 2013. Energy subsidies to cement companies were halved in January 2014 and fully removed in June. Electricity tariffs on low- and medium- voltage consumers were increased in a two-step process, by 10 percent in January 2014 and another 10 percent in May. The government introduced a lifeline electricity tariff for households consuming less than 100 kilowatt hours (kWh) per month in 2014. Also in January 2014 the government established a new automatic price formula for gasoline to align domestic price convergence to international prices over time, but without a smoothing mechanism or a clear 138 calendar. In parallel, the government launched a new social housing program, increased income tax deductions for the poorest households, and committed to creating a unified registry of beneficiaries of social programs and to improving social spending targeting (to be finished in 2015). In addition, plans are also in the works to expand the current cash transfer program (PNAFN) to 250,000 beneficiaries and to reduce its exclusion errors. This brief history of energy subsidies in Tunisia shows that the country is striving to achieve a difficult balance. That balance aims to improve fiscal and equity concerns by reducing subsidies, while also trying to appease social tensions by maintaining subsidies as a cornerstone of its social protection strategy. The transition administration has attempted to maintain that balance through a progressive reduction of subsidies that started well into the postrevolution period and by beginning an expansion of a social protection system less reliant on subsidies. Not pursuing a more ambitious future energy subsidy reform would represent a big missed opportunity for Tunisian development. According to the IMF, Tunisia is the only country in the MENA Region that has made progress in most of the areas necessary for successful reform in both the MENA Region and elsewhere during the last 30 years (table 4.1).1 In effect, IMF (2014) argues that the changes observed in energy subsidies since 2012 have benefited from a gradual pace of adjustment and comprehensive coverage; that is, changes have affected all energy sources and have successively increased all energy prices. Because of fiscal and equity concerns, the Tunisian government supports the reversal of energy subsidies, a position also supported without reservation by international financial institutions. The transition government has included several compensation mechanisms to smooth the effect of the subsidies’ removal. No other country in the MENA Region has initiated subsidy reforms of such breadth. Table 4.7: Implementation Status of Most Recent Subsidy Reforms in the Middle East and North Africa Region Consensus building Gradual pace Breadth of and communication Role of Mitigating Preparation of adjustment reform strategy partners measures Egypt,  – – –   Arab Rep. Jordan       Mauritania    –   Morocco       Sudan  – – –   139 Tunisia       Yemen,  – – –   Rep. Source: IMF 2014, 48. The progress made so far on multiple aspects of a successful reform raises the question of why a more decisive energy subsidy overhaul has not already taken place: the answer is that several factors are in play. First, even though the universal subsidy system was partly justified as a social protection mechanism, it was also designed to protect and strengthen the competitiveness of local firms by providing them with cheap energy sources. These noncompetitive enterprises, which employ unskilled workers and depend largely on government support through energy subsidies and generous tax exemptions, may not survive if subsidies are eliminated. World Bank (2014) provides a detailed account of the complex economic, financial, and governance factors associated with generalized subsidies across noncompetitive sectors of the Tunisian economy. Second, reforms have not only economic, financial, and governance implications, but also marked welfare implications. Whether deliberately sought or not, subsidy reforms generate a pattern of winners and losers. Estimates by World Bank (2013, 17) suggest that a more decisive reform of all energy subsidies—along the lines currently conceived by the government of Tunisia—would have costly and increasing welfare impacts, around 3 percent of household consumption in the short run and about 5 percent in the long run.2 Such impacts—without a careful compensating strategy—do not create a large demand for reform among those currently benefiting from those subsidies. Third, the failed attempt in the early 1980s and the lack of legitimacy of the previous authoritarian regime made an overhaul of subsidies difficult. The generous subsidy system combined with mass recruitment in the public service and periodic revisions of wages were the principal mechanisms for maintaining, at least partially, social peace and stability during the past regime. Similarly, the need to maintain social stability in the onset of the postrevolution period also warned against a profound reform of the subsidy system, even though a national consensus in the face of the economic difficulties of 2011 emerged on the need to streamline subsidies’ costs and ensure their fairness. 140 The final factor is the traditional lack of reliable and transparent estimates of the budgetary costs of subsidies, which further complicates the technical aspects of reforms, particularly a well- informed design of in-depth reform measures. For example, the actual budgetary cost (explicit subsidy) and the cost of inefficiency of refiners and electricity companies (implicit subsidies) are difficult to accurately estimate. According to World Bank (2013), implicit taxes from the generalized practice of the national oil company selling imported crude oil and natural gas at a fraction of international prices to state-owned companies may have exceeded two percentage points of GDP in 2012. In this complex interplay of economic, fiscal, social, and political economy considerations, there is broad agreement on the need to reform the current system of energy subsidies. The next section provides a detailed outline of the current price, consumption, and subsidy structure. <>Current Structure of Energy Subsidies in Tunisia This analysis focuses on residential energy subsidies; that is, subsidies on electricity, gasoline, LPG, and diesel. As already noted, they constitute the lion’s share of the total consumer subsidies funded by the government of Tunisia (two-thirds in 2013) and about 45 percent of the total consumption of energy among Tunisian households. These four energy subsidies are also among those that the government plans to reform. The analysis will simulate the fiscal and distributive effects caused by changes in the current structure of energy prices and subsidies. The current structure was introduced in May 2014 and continues to be in effect at the time of this writing. The analysis uses consumption patterns in 2010 as reference because the household survey reporting households’ energy spending—the 2010 Enquête Nationale sur le Budget, la Consommation et les Conditions de Vie des Ménages (ENBCV)—is the most recent available. The latest input-output matrix (I/O) for Tunisia is also for 2010. This I/O matrix enables estimation of the indirect effects of the reforms; that is, the effects on household consumption and spending accruing from the impacts that energy prices have on other productive sectors of the economy. 141 Household spending on energy and other products is then updated using successive rates of the annual consumer price index (CPI), GDP, and population growth to construct a distribution of energy spending for January 2014. The current energy tariff structures are applied to that distribution of household spending on energy to derive a distribution of household consumption on energy sources. It is on these distributions of spending and consumption constructed for 2014 that the subsidy reform is simulated and its distributive and fiscal effects estimated. The first step before beginning the simulation analysis is to look at a detailed outline of the current system of energy subsidies. <>Structure of Residential Energy Prices The current price structure for residential electricity consumption follows a two-tier system.3 A different structure—the analysis of which is beyond the scope of this chapter—is applied to nonresidential users (which also differentiates between low- and high-tension use). Table 4.2 shows that for households consuming less than 200 kilowatt hours per month, a volume differentiated tariff (VDT) is applied to three consumption blocks and three distinctive prices apply: Tunisian dinar (TD) 0.075 per kilowatt hour, if consumption is 1–50 kilowatt hours; TD 0.108 per kilowatt hour (applied for all kilowatt hours consumed) if consumption is 51–100 kilowatt hours; and TD 0.140 per kilowatt hour if consumption is 101–200 kilowatt hours (also from the first kilowatt hour consumed). Households consuming more than 200 kilowatt hours per month are subject to an increasing blocks tariff (IBT) that includes multiple prices across different blocks of consumption. In this high-volume tier, TD 0.151 per kilowatt hour is charged for each of the initial 200 kilowatt hours consumed; TD 0.158 for each of the subsequent kilowatt hour in the 201–300 kilowatt hour block; TD 0.301 for the next 200 kilowatt hours block; and TD 0.501 per kilowatt hour for each of those kilowatt hours in excess of 500 kilowatt hours per month. Table 4.2: Electricity Tariff Structure for Low-Tension Residential Consumers (valid since May 1, 2014) Voltage Price of energy by monthly consumption bracket Fee (millimes/kVa/month) (millimes/kWh) 142 201– 301– 501 1–50 51–100 101–200 300 500 + 75 Economic (1 and 2 kVa and consumption under 200 500 108 kWh) 140 280 350 Economic (1 and 2 kVa and consumption over 200 500 151 184 kWh); normal (> 2 kVa) 250 295 Source: Societé Tunisienne d’Eletricité et du Gaz 2014. Note: Prices are in TD millimes and before taxes. kWh = kilowatt hour; kVa = kilo-volt-amperes or 1,000 volt amps. Based on this structure, both low-volume consumers—households consuming below 200 kilowatt per month—and high-volume consumers face an increasing marginal cost from usage. High-volume consumers pay more than low-volume users for the first 200 kilowatt and face increasing fees as their consumption rises. In this respect, the tariff structure is progressive: those consuming more pay higher marginal costs per kilowatt consumed. However, the pace at which marginal tariffs increase is not linear. If we take 50 kilowatt increments in consumption, moving from a consumption level of 50 kilowatt to 100 kilowatt, the price of the second 50 kilowatt is 44 percent higher than for the first tranche (from TD 75 to 108 millimes) among low-volume consumers. For those consumers moving toward the highest block of the second tier; that is, moving from 301–500 kilowatt to the 501 plus kilowatt block, the residential tariff increase is TD 25 percent or 70 millimes. In short, nonlinear features (in terms of marginal prices per additional consumption) are combined across different segments of the two-tier system, making the system far from progressive in its entirety. The pro-poor nature of the system depends on the concentration of consumers who are considered poor in the lower price blocks of each tier. In this light, the system falls short in benefiting the less well-off population: the concentration of poor consumers—specifically those in the bottom quintile of per capita household consumption—in the lifeline block is only 48 143 percent (appendix 4B). The share of consumers in the lifeline block rapidly declines for subsequent quintiles of the distribution. In turn, the concentration of consumers from the richest quintile ranges from 35 percent to 60 percent of all users in the high-volume consumption tier. Consumers from the poorest quintile are hardly represented in the high-volume tier: only 3 percent to 6 percent of consumers belong to the poorest quintile. In other words, the poor represent a minimal proportion of consumers of the higher-volume tier, but more surprisingly, they are not the vast majority of beneficiaries of the lifeline price rates either. The prices of other energy sources are not subject to differentiated price segments. The prices of gasoline, LPG, and diesel do not vary across consumption levels. The market price of gasoline is TD 1.67 per liter; the price of 0.2 diesel (containing 0.2 percent of sulfur) is TD 1.25 per liter; and a 13 kilogram cylinder of LPG costs TD 7.4 (or TD 0.57 per kg).4 As indicated already for the case of electricity, the pro-poor measure of the distribution of those energy subsidies is determined by both the price structure and the extent to which these energy products are consumed by the poor. Yet the price structure is not progressive in marginal terms, because the price does not increase as consumption increases. In absolute terms, higher-volume consumers benefit from a higher public subsidy, making those subsidies not pro-poor. <>Estimating Energy Subsidies Most energy sources are publicly subsidized in Tunisia, but to different extents.5 Based on the observed final—market—prices, price structures, international prices (of imported sources), and local production costs, it is possible to calculate shares of subsidized prices for each energy source. Box 4.1 summarizes the methodology used to calculate to such shares. <> Box 4.1: Estimating Shares of Subsidized Prices For energy products consumed by the household—electricity, LPG, gasoline, and diesel—a subsidy level “S” for each product is estimated using the price-gap approach. According to this approach, a first price is calculated by adding to the international reference price (IP) all local taxes and domestic distribution costs. The resulting price is assumed to reflect the cost of efficient market supply, given the conditions and regulations of a given country and international 144 prices. This price is called the nonsubsidized price (NP). Subsidies (S) are calculated as the difference between the estimated NP and the observed domestic sale price, or market price (DP): Si = NPi – DPi, where i refers to each energy source for residential consumption. The subsidy rate SRi for source i is the ratio of Si to NPi. In the case of Tunisia, domestic prices used in this analysis are from the Ministry of Finance, and the IPs were obtained from the Ministry of Industries (Direction Générale de l'Énergie) for electricity, LPG, gasoline, and diesel, respectively. Sources: Araar and Verme 2012; World Bank 2013. <> Table 4.3 presents the rate of subsidized energy prices with respect to the observed market prices since May 2014. The rate of subsidized LPG prices is estimated at 68 percent of the nonsubsidized price. In other words, for every liter of LPG consumed at a final price of TD 0.570, some TD 1.220 have been subsidized from the estimated price of TD 1.790 (reflecting international reference prices). Likewise, a similar calculation shows shares of subsidized prices of 10 percent for gasoline and 21 percent for diesel. In the case of electricity, the subsidized rates for each block decrease with consumption. This is the case for the two-volume tiers. In fact, the two top consumption blocks of the high-volume tier—consumers of more than 300 kilowatt per month—receive negative subsidies; that is, they are net contributors to the subsidies of consumers of lower-volume consumption. Consumers from the two levels of highest consumption end up paying a higher price than the international reference price plus taxes and distribution costs. Table 4.3: Estimated Subsidy Rates for Energy Sources in Tunisia (valid May 2014) Nonsubsidized Subsidy (Si), Subsidy rate Market price, (DPi=NPi- price (NPi), TD TD (SRi=Si/NPi), Si), TD percent Gasoline 1.856 0.186 10 1.670 LPG 1.790 1.220 68 0.570 Diesel 1.584 0.334 21 1.250 Electricity: Households consuming less than 200 kWh per month Electricity 0–50 0.268 0.193 72 0.075 Electricity 0–100 0.268 0.160 60 0.108 145 Electricity 0–200 0.268 0.128 47 0.140 Electricity: Households consuming more than 200 kWh per month Electricity 0–200 0.268 0.117 43 0.151 Electricity 201–300 0.268 0.084 31 0.184 Electricity 301–500 0.268 −0.012 −4 0.280 Electricity > 500 0.268 −0.082 −31 0.350 Source: World Bank staff calculations. Note: DPi = market price of each energy source i; kWh = kilowatt hour; NPi = nonsubsidized price of the energy source i; Si = subsidy of energy source i; SRi = subsidy rate of energy source i; TD = Tunisian dinar. In the case of LPG, the latest available numbers are from 20136 (table 4.4) and show a subsidy rate of 68 percent . In fiscal terms, these subsidies amounted to TD 749 million, 15 percent of all energy subsidies publicly transferred and 1 percent of GDP. Diesels (containing either 0.005 percent or 0.2 percent of sulfur) have subsidies between 16 percent and 26 percent of final prices, respectively, which represented 1.5 percent of GDP, 23 percent of energy subsidies, and TD 1,146 million in 2013. The energy source most highly subsidized in terms of public spending was electricity, with 3.4 percent of GDP, 51 percent of all energy subsidies, and more than TD 2.5 billion a year (in 2013). Its subsidized price share oscillated between 27 percent and 50 percent. The remaining 12 percent of energy subsidies were distributed among gasoline, kerosene, and heavy fuel. At the level of residential spending for energy, other forms commonly utilized by households, such as charcoal, natural gas, or solid biofuels are not subsidized.7 Within the household sector, solid biofuels constitute the main source of energy expenditure (42 percent), followed by LPG (18 percent ), electricity (15 percent ), and natural gas (10 percent ). Diesels and gasoline are very low sources of energy expenditures. Also, as the next section shows, there are marked differences in consumption and spending by socioeconomic groups. Table 4.4: Total Public Spending on Energy Subsidies, selected energy sources 146 Diesel Diesel LPG Gasoline (50 0.2 Electricity Indicator ppm) percent Subsidy rate (percent) 68 15 16 62 27/50 Total consumption at sale price (TD million) 225 884 230 103 2169 Price increase estimated from elimination of subsidies (percent) 214 23 22 165 30 Expenditures Amount (TD million) 483 199 50 170 1671 As a percent of GDP 0.7 0.3 0.07 0.2 2.4 Amount estimated end of 2013 (TD million) 749 321 75 214 2569 As a percent of GDP 1 0.4 0.1 0.3 3.4 Source: World Bank calculations using data from Ministère des Finances and Ministère de l’Industrie. Note: All data are from April 2013 unless otherwise noted. April 2013 GDP in 2012 prices estimated at 70,400 million. TD = Tunisian dinars; GDP = gross domestic product; ppm = parts per million. <>Socioeconomic Profile of Energy Subsidies Previous sections have discussed the complex structure of energy prices (in terms of progressivity) and the estimated subsidy rates underlying current price structures. To determine the extent to which such price and subsidy structures lead to pro-poor welfare outcomes, the consumption of different socioeconomic groups, their expenditures, and their benefits from subsidies all need to be factored in. First, consumption and spending on energy will be disaggregated by socioeconomic group. This socioeconomic analysis covers both Tunisian individuals and households grouped by their consumption levels in quintiles. Quintile 1 refers to the poorest individuals and households, and quintile 5 refers to the richest. <>Residential Consumption and Expenditures on Energy Panels a and b in table 4.5 show that total consumption of energy across quintiles varies by energy sources. Richer quintiles consume more energy, with significantly large differences for gasoline and diesel between these quintiles and the rest. Consumption by the richest two quintiles represents 80 percent and 90 percent of the consumption of diesel and gasoline, respectively. The poorest 40 percent consumes 2 percent and 8 percent of the total consumption of these two sources, respectively. For the other energy sources, the distribution of consumption across quintiles is not so skewed: the share of the poorest two quintiles' consumption of LPG and electricity represents 45–52 percent and 28–34 percent, respectively 147 Table 4.5: Total Residential Energy Consumption, by source and quintiles of household consumption b. Relative terms (in percent ) a. Absolute terms Gasoline LPG Diesel Gasoline LPG Diesel Electricity Electricity (million (1,000s (million Quintile (GWh) Quintile liters) tons) liters) 1 (poorest) 0.3 15.3 1.6 12.5 1 (poorest) 1 80 1 587 2 1.7 18.9 6.8 16.2 2 5 99 4 761 3 6.3 20.5 12.9 18.7 3 18 107 8 881 4 18.7 23.4 19.4 22.0 4 54 122 12 1033 5 5 (richest) 213 114 37 1440 (richest) 73.0 21.9 59.4 30.6 Total 292 521 63 4702 Total 100 100 100 100 Source: World Bank calculations using SUBSIM (subsidy simulations). Note: GWh = Gigawatt hour. Similarly, when it comes to the per capita consumption of energy, the data in table 4.6 unequivocally confirm that the top consumption quintiles, the richest quintiles, consume much more than the poorest quintiles. Consumption differences are largest for gasoline, followed by diesel (panel a). On average, an individual from quintile 5 consumes 200 times more gasoline than someone from the poorest quintile. That ratio is still a whopping 38 to 1 in the case of diesel. Much narrower differences are observed for electricity and LPG. A richer individual consumes 4.5 times more electricity and 1.4 times more LPG than an individual from the poorest household. Individuals from quintile 4 consume more LPG on average than anyone else in the distribution. When the analysis is conducted for households—rather than individuals—(panel b) very similar ratios and distributions are observed, confirming results for individuals. Table 4.6: Per Capita and Per Household Consumption of Subsidized Energy, in quantity 148 a. Consumption per individual b. Consumption per household Gasoline LPG Diesel Electricity Gasoline Diesel Electricity Quintile (liter) (kg) (liter) (kWh) Quintile (liter) LPG (kg) (liter) (kWh) 1 (poorest) 0.46 36.50 0.45 37.41 1 (poorest) 2.53 200.75 2.47 205.75 2 2.30 45.35 1.95 49.59 2 11.5 226.75 9.75 247.95 3 8.45 49.08 3.70 61.23 3 38.02 220.86 16.65 275.53 4 25.02 55.99 5.58 86.58 4 100.08 223.96 22.32 346.32 5 (richest) 97.74 52.39 17.07 167.20 5 (richest) 342.09 183.36 59.74 585.2 Total 26.79 47.86 5.75 80.40 Total 107.16 191.44 23 321.6 Source: World Bank calculations using SUBSIM. 149 In terms of expenditures, figure 4.3 shows that the expenditure of energy represents between 5 percent and 6 percent of households’ total spending. In other words, energy spending as share of household total spending is similar across socioeconomic groups, without marked differences across quintiles. Despite being small, these differences are still interesting. In fact, it is the households in the poorest and richest quintiles that spend a higher proportion of their budgets on energy (just over 6 percent of their total spending). But while the poorest spent its largest share on electricity, the richest does so on gasoline. Figure 4.3: Household Expenditure on Energy 7% 6% 5% 4% 3% 2% 1% 0% Quintile Quintile Quintile Quintile Quintile Total 1 2 3 4 5 Gasoline Diesel LPG Electricity Source: World Bank staff calculations using SUBSIM (subsidy simulations). [[Typesetter: in figure 4.4 Y-axis: remove % marks from the y axis and label the axis "Percentage of household expenditures"; Bars and legend: use grayscale or patterns; Background: Remove box and gridlines.]] Large differences become evident when absolute spending is compared across quintiles of the consumption distribution. Figure 4.4 shows that the richest individual spends more than 200 times per capita than a poor individual. Socioeconomic disparities in spending remain for diesel as well, but are notably reduced for electricity and LPG. In fact, spending on LPG is more uniform across all socioeconomic groups, between TD 20 and 29, and it is the fourth quintile that spends the most. 150 Figure 4.4: Per Capita Expenditures on Energy, in TD 180 160 140 120 100 80 60 40 20 0 Gasoline LPG Diesel Electricity Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Source: World Bank staff calculations using SUBSIM (subsidy simulations). Note: TD = Tunisian dinar. [[Typesetter: in figure 4.4: Y-axis: Insert label "Tunisian dinars"; Bars and legend: grayscale or patterns; Background: Remove box and gridlines.]] <>Socioeconomic Distribution of Energy Subsidy Benefits The distribution of monetized benefits accruing from subsidies is the result of a number of considerations: the degree of price progressivity, the pro-poor nature of the price structure, the share of subsidized price of final price, and the composition and total consumption by socioeconomic group. It is not surprising that energy subsidies are concentrated on LPG and electricity subsidies. Moreover, the concentration of benefits from these two sources is true for all consumption quintiles (table 4.7, panel a). This finding implies that all of the poor, the bottom 40 percent, and richer individuals obtain most of their energy subsidies from LPG and electricity. In relative terms, LPG and electricity represent 53.3 percent and 40.4 percent of total subsidies, shares that for the poorest quintile increase slightly to 54.5 percent and 42.2 percent of their total energy subsidies, respectively. For the rest of the quintiles, subsidies from both sources also capture the lion’s share of total benefits. The distribution of total benefits by socioeconomic group, however, also shows that energy subsidies—either universal or targeted—favor the rich. The poorest quintile captured the lowest share of all benefits associated with energy subsidies, 14.9 percent, and the richest quintile captured 25 percent (table 4.7, panel b). 151 Table 4.7: Composition of Subsidies Received by Residential Consumers b. Distribution over all a. Distribution across each quintile (%) quintiles Total (millimes Total Gasoline Diesel LPG Electricity Total Quintile TD) (%) 1 (poorest) 0.1 0.2 54.5 42.2 100 178 14.9 2 0.4 0.7 56.6 42.3 100 213 17.9 3 1.4 1.1 55.1 42.4 100 237 19.9 4 3.8 1.5 55.7 39.0 100 267 22.4 5 (richest) 13.3 4.2 46.8 35.8 100 298 25.0 Total 4.5 1.8 53.3 40.4 100 1,192 100 Source: World Bank staff calculations using SUBSIM (subsidy simulations). Note: TD = Tunisian dinar. When analyzed in per capita terms, all energy subsidies are found to be regressive. The absolute amount of subsidy benefits increases as individuals and households become richer. Table 4.8 reports the distribution of subsidies benefiting each socioeconomic group. By and large, results reflect inequalities in the consumption of energy sources across quintiles. In fact, differences may not be attributed to the different—universal versus targeted—nature of subsidies. Even though gasoline, diesel, and LPG subsidies are all universal, their distributional effects vary. LPG is the energy source with the largest subsidy benefits in absolute and relative terms for the poorest quintile and the bottom 40 percent: in fact, the LPG subsidies received by the population as a whole represent close to 60 percent of all benefits obtained from energy subsidies. But that is also true for the richer quintiles. So, even though LPG is the most pro-poor—or rather, the least prorich energy source—it is not particularly progressive in terms of subsidy benefits. Moreover, electricity subsidies, with their complex interplay of progressive and regressive features, do not perform differently from the LPG universal subsidy. Electricity subsidies constitute the second largest source of subsidy benefits for Tunisians, around 35 to 45 percent, with shares decreasing as individuals become richer. Table 4.8: Per Capita Energy Subsidy Benefits, in TD Quintile Gasoline Diesel LPG Electricity Total 1 (poorest) 0.09 0.15 44.53 36.99 81.76 2 0.43 0.65 55.33 41.42 97.82 3 1.57 1.24 59.88 46.06 108.74 4 4.65 1.86 68.30 47.85 122.67 5 (richest) 18.18 5.70 63.91 48.89 136.69 152 Total 4.98 1.92 58.39 44.24 109.53 Source: World Bank staff calculations using SUBSIM (subsidy simulations). Note: TD = Tunisian dinar. Table 4.9 reports the shares that energy subsidy benefits represent on total household spending. Consistent with previous results, LPG and electricity subsidies are the largest contributors to household expenditures, which in the case of the poorest quintile represent a substantive 8.8 percent of total expenditures. This share of subsidy benefits over total household spending decreases along with expenditure levels, up to 2.4 percent of total spending for households in the top quintile. Gasoline and diesel do not represent any substantive share of total spending, yet they are larger for the richest rather than for the poorest quintiles. For all households, these two sources of subsidies represent about 0.2 percent of the total 3.9 percent of household expenditures transferred from energy subsidies. Table 4.9: Energy Subsidy Benefits as Percentage of Total Household Expenditure Quintile Gasoline LPG Diesel Electricity Total 1 (poorest) 0.0 4.8 0.0 4.0 8.8 2 0.0 3.4 0.0 2.6 6.0 3 0.1 2.7 0.1 2.1 5.0 4 0.1 2.2 0.1 1.5 3.9 5 (richest) 0.3 1.1 0.1 0.8 2.4 Total 0.2 2.1 0.1 1.6 3.9 Source: World Bank staff calculations using SUBSIM (subsidy simulations). <>Simulating the Distributional Impacts of a Subsidy-Reducing Reform The government of Tunisia has announced its intention to remove all subsidies associated with gasoline, diesel, and LPG, and to increase the prices of each tranche of electricity for residential consumers (Jomaa 2014). As of this writing, however, the specific and detailed proposal on the timing, sequence, and compensatory measures was still being discussed internally. Nevertheless, any reform proposal raises the question of what the expected poverty and distributional effects of such changes might be. This section reports the estimated effects of the simulated subsidy reform, but first explains the methodology to estimate those effects. The discussion then turns to 153 the additional distributional effects of expanding cash transfers using the fiscal savings generated by the subsidy reform. <>A Methodological Note on Simulations Given the preliminary stage of the policy discussion, the estimations consider two effects. One is the direct effect of price increases following the partial or full removal of subsidies. Direct effects have unequivocal impacts on individual and household budgets proportional to the increase in prices. No immediate changes in consumption are assumed, which is consistent with limited substitutability among energy sources in the short run (due to both technical and financial reasons and, presumably, individual preferences). Everyone consumes as before, but at higher prices. This result implies that individuals and households will have fewer resources to purchase other goods and services. For poorer households, these goods and services may include the necessary minimum consumption basket reflected in the poverty line. Changes in prices are therefore equivalent to a proportional increase in the poverty line faced by the household (weighted by its relative composition in the basic consumption basket). The second effect considered is the indirect impact: the changes on prices of goods that result from energy price changes. The indirect effect captures the change in relative prices for the rest of the economy and therefore on the prices of the other components of the consumption basket. Price changes across sectors are estimated by applying the price changes of energy to final products that use energy as an intermediary input. Using the a 2010 I/O table for Tunisia, constructed by the INS (Institut National de la Statistique), a simple approximation of such economy-wide changes following energy price subsidies can be calculated.8 The analysis draws from the distribution of consumption and spending reported in the 2010 Household Budget and Expenditure Survey, the most recent survey. The 2010 structures of consumption and spending are then updated to January 2014 using growth rates, population growth, and the CPI. It is on those distributions that simulations of a hypothetical reform in 2014 are conducted. In other words, the distributive effects of the 2014 reform are applied to the households—and their consumption patterns—existing in 2014. Therefore, the analysis assumes that consumption patterns and their drivers, such as preferences, in 2010 are a good proxy for 2014 consumption patterns. Finally, poverty status is defined in this exercise around the official poverty lines established by the INS (Institut National de la Statistique), BAD (Banque Africaine 154 de Développement), and the World Bank (2012) as the monetized cost of a food basket that ensures minimum caloric needs, further adjusted by nonfood needs.9 <>Spending and Consumption Impacts Table 4.10 applies the described methodology. Panel a presents the monetary impact of price increases resulting from the removal of subsidies for gasoline, LPG, and diesel, and the partial reduction in electricity subsidies. Final results from this simulation are disaggregated between direct and indirect effects. The average total impact of this set of interventions on per capita terms is TD 109. The largest effect on consumption comes from the removal of LPG subsidies, followed by diesel, electricity, and gasoline. In effect, about 62 percent of all the reduction in consumption comes from the elimination of LPG subsidies. By type of effects, direct effects represent two-thirds of the total aggregated effect, and indirect effects, the remaining one-third. By energy source, socioeconomic patterns differ between direct and indirect effects. Among direct effects (panel b), it is the effect of LPG that once again has the largest impact on household consumption (four-fifths of all direct effects), followed by electricity, gasoline, and diesel. In contrast, it is the removal of diesel subsidies that has the largest indirect effect on consumption (43 percent of total indirect effects), followed by LPG, electricity, and gasoline (panel c). Among quintiles, the total impact of the reform increases among richer households, with the largest differences across quintiles observed for gasoline. The differences are less marked for diesel and electricity and relatively close for LPG. The increasing impact on consumption among richer quintiles is also observed for both direct and indirect effects. [[Typesetter: for the 3 panels of table 4.10, change the left column to match table 4.9; change hyphens to minus signs.]] Table 4.10: Impact of the Reform on Total Per Capita Expenditures (by energy source and quintile of consumption, in TD) a. Total effects 155 Quintile Gasoline LPG Diesel Electricity All Quintile 1 -1.9 -47.3 -5.9 -5.5 -60.5 Quintile 2 -3.7 -60.7 -10.3 -8.7 -83.5 Quintile 3 -6.3 -67.7 -14.7 -11.1 -99.7 Quintile 4 -11.1 -79.6 -19.8 -15.0 -125.5 Quintile 5 -28.1 -85.8 -36.2 -27.0 -177.1 Total -10.2 -68.2 -17.4 -13.5 -109.3 b. Direct effects Quintile Gasoline LPG Diesel Electricity All Quintile 1 -0.1 -44.5 -0.1 -3.7 -48.4 Quintile 2 -0.4 -55.3 -0.7 -5.6 -62.0 Quintile 3 -1.6 -59.9 -1.2 -6.8 -69.5 Quintile 4 -4.7 -68.3 -1.9 -8.8 -83.7 Quintile 5 -18.2 -63.9 -5.7 -15.1 -102.9 Total -5.0 -58.4 -1.9 -8.0 -73.3 c. Indirect effects Quintile Gasoline LPG Diesel Electricity All Quintile 1 -1.8 -2.8 -5.7 -1.8 -12.1 Quintile 2 -3.3 -5.4 -9.7 -3.1 -21.5 Quintile 3 -4.7 -7.8 -13.4 -4.4 -30.3 Quintile 4 -6.4 -11.3 -18.0 -6.2 -41.9 Quintile 5 -9.9 -21.9 -30.5 -12.0 -74.3 Total -5.2 -9.8 -15.5 -5.5 -36.0 Source: World Bank staff calculations using SUBSIM (subsidy simulations). In relative terms, the impact of the reforms averages 4.7 percent of households’ expenditures (figure 4.5). The magnitude of the impact decreases with household expenditure levels. It progressively declines from 6.7 percent of the poorest households’ expenditures to 3.1 percent of the richest households’ expenditures. Similar to the case in absolute terms (that is, in TD terms), it is the LPG subsidy reform that brings the largest relative impact on households’ expenditures: some 3.2 percent of all households’ expenditures. Figure 4.5: Impact of Reforms on Households’ Expenditures 156 Gasoline Diesel LPG Electricity Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Average 0 -1 -2 percent of total household -3 -4 -5 -6 -7 -8 Source: World Bank staff calculations using SUBSIM (subsidy simulations). [[Typesetter: Y-axis: change hyphens to minus signs; change "percent" to "Percent"; delete "-8"; Bars and legend: use shades of gray or patterns; Background: remove box and gridlines.]] Estimates of the impacts on poverty and inequality show an increase of 2.69 percentage points in the incidence of poverty, which represents an increase of 17 percent in the incidence of poverty. Table 4.11 shows a Gini coefficient increase of 0.61 percentage points, or a 1.7 percent increase in the prereform levels of inequality. A large portion of those changes in poverty result from direct effects, both in poverty and in inequality, and LPG is the largest contributor to poverty and inequality deterioration. Table 4.11: Poverty and Inequality Impacts of Energy Reform Percentage Change in pp Percentage Change in pp points (pp) w/prereform points (pp) w/prereform Poverty prereform 14.93 – Gini prereform 35.81 – Gasoline 15.02 0.09 Gasoline 35.75 -0.06 LPG 16.84 1.91 LPG 36.43 0.62 Diesel 15.12 0.19 Diesel 35.82 0.01 Electricity 15.13 0.2 Electricity 35.83 0.02 157 Poverty postreform 17.61 2.68 Gini postreform 36.42 0.61 Misc. direct effect – 1.95 Misc. direct effect – 0.58 Source: World Bank staff calculations using SUBSIM (subsidy simulations). Note: The reason that the prereform poverty and inequality rates are not the official rates for 2010 is that prices have all been updated for this specific exercise to 2013 prices, using growth rates and population growth rates. The poverty line has also been updated using CPI trends. Therefore, the starting point of this exercise is a poverty rate of 14.9 in 2013 rather than the 15.4 percent official estimate obtained in the 2010 original household budgetary survey. This adjustment enables comparisons across other countries analyzed in this book. However, the rest of the simulation exercise will be conducted using the 2010 household budgetary survey. A subsample of the 2010 survey is used and not the full sample of the original survey. In effect, it is a subsample of the original sample that is used to capture beneficiaries of the subsidized universal health care card. Even after re-weighting the subsample, the exact official poverty number of 15.4 percent could not be fully replicated—only a slim margin (15.3 percent). Similarly, the estimated prereform Gini of 36.5 percent differs slightly from the official 35.8 percent from the full sample (table 4.13). The increases in poverty and inequality following the reduction of subsidies imply some TD 817.5 million in fiscal savings (table 4.12). Fiscal savings accrue disproportionally from the removal of subsidies in LPG (77 percent of all fiscal savings) and electricity (13 percent). Furthermore, the savings accruing from the removal of subsidies affecting the poorest quintile represent some 13 percent of all fiscal savings, a share that increases across quintiles, so that the savings accruing from removed benefits to the richest group represent 28 percent of the total savings. These shares are very similar to the proportions of benefits from subsidies that each socioeconomic group captured prior to the reform (table 4.7). Given that these simulations do not introduce behavioral effects (only direct and indirect effects are allowed), fiscal savings from the elimination of subsidies for the most part reflect the initial socioeconomic distribution of subsidies. Table 4.12: Energy Subsidy Savings from the Reform by Source and Quintile of Consumption, in TD Quintile Gasoline LPG Diesel Electricity Total 1 (poorest) −186,020 −97,003,152 −325,901 −11,624,507 −109,139,584 2 −929,258 −120,432,824 −1,418,063 −16,163,867 −138,944,016 158 3 −3,420,753 −130,381,216 −2,689,996 −19,003,020 −155,494,992 4 −10,129,942 −148,695,856 −4,054,068 −23,481,422 −186,361,280 5 (richest) −39,575,064 −139,133,344 −12,414,583 −36,451,727 −227,574,720 Total −54,241,036 −635,646,400 −20,902,610 −106,724,543 −817,514,560 Source: World Bank staff calculations using SUBSIM (subsidy simulations). Note: TD = Tunisian dinar. <>Compensating Interventions to Energy Subsidy Reforms The final step is to assess the poverty and distributional effects of spending the total savings from the energy subsidy reform on poverty-reducing purposes. Once again, there is no clear guidance from the government of Tunisia on how these compensation programs will be implemented. For that reason, this analysis considers three hypothetical scenarios. Simulation 1 uses total savings to provide a universal transfer to each Tunisian. This scenario is called “universal transfer” because it includes a transfer to every Tunisian without discrimination. Simulation 2, or “current targeting,” uses the current social assistance program, the subsidized health cards, as the targeting mechanism. This label does not intend to judge the current capacity of subsidized cards to reach the poorest. Instead, it simply indicates that no additional targeting efforts take place and that authorities use existing structures to channel all the savings accruing from energy subsidy reforms. Finally, in simulation 3, “perfect targeting,” all the savings are distributed exactly to those who are poor after the reform. This is an unrealistic and idealistic scenario that describes a situation in which all the poor after the reform are perfectly identified and compensated on a per capita basis. It is idealistic because it assumes perfect and costless targeting; in other words, no additional resources are needed to identify the poor and distribute cash benefits to them. Although these three scenarios vary in terms of implementation feasibility, they are useful in this context where no detailed plans are announced. These results provide information on the boundaries of the distributional effects of the reform—from no compensation following the reform to the complete use of fiscal savings from energy subsidy reform to reduce poverty under perfect targeting. The true impact of the reform and of feasible compensation policies will lie somewhere in between. Table 4.13 summarizes the simulations’ results. Table 4.13: Simulated Poverty and Inequality Impacts of Compensatory Mechanisms after Energy Subsidy Reform 159 Fiscal cost of Average benefit Number of Poverty Inequality (Gini compensation transferred beneficiaries (percent) 0–100 index) (rounded up) Prereform 0 0 0 15.27 36.57 Baseline: subsidy reform 0 0 0 17.84 37.18 with no compensation Simulation 1: universal TD 817.51 TD 75 10.9 million 14.87 36.29 transfer after millimes subsidy reform Simulation 2: TD 817.51 TD 264 3.1 million 13.83 35.46 current targeting millimes Simulation 3: TD 817.51 TD 420 1.9 million 5.25 34.22 perfect targeting millimes Source: World Bank staff calculations using SUBSIM (subsidy simulations). These simulations indicate that the complete use of fiscal savings from the energy reform would not reduce postreform poverty levels by any significant amount with the current targeting mechanism or via universally benefiting the entire population (table 4.13, simulations 2 and 1, respectively).The fiscal savings accruing from a universal transfer reform (simulation 2) would bring down postreform poverty levels by 2.5 percentage points—or some 272,000 persons. Using the current health card targeting mechanism (simulation 1) would reduce postreform poverty by an additional percentage point, to 13.83 percent of the population. A perfect and costless targeting of fiscal savings (simulation 3) would lead to a postreform poverty incidence reduction of 12.5 percentage points, up to 5.25 percent of the population. Despite the slash in poverty incidence, the fiscal resources freed from the current level of energy subsidies would not be sufficient to completely eradicate poverty in Tunisia. Neither would it be sufficient to make a notable dent on consumption inequality as measured by the Gini coefficient. The three compensation initiatives would fully reverse the initial increase in inequality following the subsidy reforms, but the reduction in inequality would by no means be large. The best results, accruing from the perfect targeting scenario, indicate gains of three percentage points in the Gini coefficient with respect to the postreform Gini. In relative terms, the compensation mechanisms simulated after the reform would improve inequality by less than 10 percent.10 <>Conclusion 160 Energy subsidies have played and continue to play a pivotal role in Tunisian social development policy making. Their fiscal implications are substantial, consuming about 5 percent of the country’s GDP, and this analysis shows that their distributional impacts are considerable. But subsidies have also played an important role in appeasing social tensions. An overhaul of energy subsidies in Tunisia must strike a delicate balance to improve fiscal and equity considerations without increasing social tensions. The strategy followed so far has been one of progressive reduction of subsidies coupled with an expansion of the nonsubsidy elements of social protection. This chapter presents an analysis of the fiscal and distributive consequences of the still vaguely defined next step in that strategy: a uniform increase of 10 percent of electricity prices; a total removal of LPG, diesel, and gasoline subsidies; and alternative improvements in the current cash transfer system, which were announced at the end of 2014. A review of Tunisia’s residential energy subsidies helps us to understand the implications of the country’s current strategy. In Tunisia, energy transfers are through a system of universal energy sources plus a complex multiblock price schedule for electricity that mixes progressive and regressive features. All in all, the energy price structure results in a regressive and prorich transfer system that produces a huge fiscal bill. Furthermore, the distributive impact of the system is heterogeneous, with LPG and electricity the most influential among poor (also among the nonpoor) consumers. This has to do with the price and subsidy structure, on the one hand, and differences in the consumption patterns across socioeconomic groups, on the other. Whether the subsidy is universal or targeted does not make much of a distributional difference in the current Tunisian context. Although the Tunisian authorities have announced their intention to reform energy subsidies, policy is still in the planning stages, and final details remained unknown at the time of this writing. Limited information, however, points to a complete elimination of LPG, diesel, and gasoline subsidies, a uniform 10 percent increase in the price of electricity, and the introduction of compensation mechanisms to residential consumers. The present analysis simulates the immediate impacts of the increase in energy prices following the reform of subsidies and constructs several scenarios that simulate the poverty and inequality impacts of increasingly effective targeting mechanisms. Those targeting mechanisms make use of the total fiscal savings freed from the reform in energy subsidies to compensate consumers. In other words, the analyzed 161 simulations of compensatory initiatives postreform are all fiscally neutral. They are also bold and ambitious because they assume that all fiscal savings from the energy reform would be fully invested back into poverty reduction. The scenarios are also unrealistic in that they assume no additional administrative costs. Still, they are useful to set the distributive limits that compensation measures will have after energy subsidies are reformed. Results from simulations underscore two critical results. First, raising electricity prices to consumers and removing subsidies for other energy sources would immediately—that is, without behavioral responses from users—increase poverty by 2.5 points. Second, “easy” compensation mechanisms— that is, either universal or using current structures—will not bring substantive poverty reductions, even if the government channels the entire TD 817.5 million saved from the subsidy reform. Perfect and costless targeting would slash poverty incidence down to five percentage points. Yet while this ideal scenario would imply a huge reduction in poverty, it would still fall short of eradicating poverty, and inequalities would be reduced in more modest terms. Tunisia is still far from having such an ideal targeting system with comprehensive and updated lists of beneficiaries and minimal transaction costs. In addition, it should not be expected that all fiscal savings from the energy subsidy will be invested into poverty reduction. What becomes clear from the proposed simulations results is that bold reforms of energy subsidies need to be accompanied by equally bold improvements to the targeting schemes of public spending if both poverty and disparities are to be substantively reduced. <>Appendix 4A: Electricity Tariff Structure for Low-Tension Residential Consumers (January 1, 2014) Price of energy by monthly consumption bracket Voltage (millimes/kWh) Fee (millimes/kVa/mo nth) 201– 301– 501 1–50 51–100 101–200 300 500 + Economic (1 and 75 2 kVa and 500 108 consumption under 200 kWh) 123 162 Economic (1 and 240 330 2 kVa and consumption 500 136 157 under 200 kWh); 210 270 normal (>2 kVa) Source: Société Tunisienne d’Electricité et du Gaz 2014. Note: kWh = kilowatt hour; kVa = kilo-volt-amperes or 1,000 volt amps. <>Appendix 4B: Distribution of Monthly Electricity Consumption by Quintile Consumer Monthly consumption 1–50 Monthly consumption 51–100 Monthly consumption 101–200 <200 kWh kWh kWh kWh per month Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5 Percent by 48.1 19.2 12.9 11.6 8.2 32 25.5 20.1 13.7 8.7 15.9 20.5 23.2 22.6 17.9 quintile Consumer Monthly consumption Monthly consumption Monthly consumption >200 kWh 1–300 kWh 301–500 kWh + 501 kWh per month Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5 Percent by 6.7 15.2 17.8 25.9 34.4 4.4 12.1 15.2 22.1 46.2 2.8 9.1 9.3 19.4 59.4 quintile Source: World Bank staff calculations using SUBSIM (subsidy simulations). <>Appendix 4C: Composition of Consumption of Energy Sources by Sector (2012) 163 Source: World Bank 2013. Note: In the case of nonresidential sectors, consumption of energy is an input for their production. For households, it is purely consumption. [[Typesetter: Use sentence style for all labels; change ampersand to "and"]] <>Notes 1. IMF (2014) analyzes 25 reforms of fuel and food subsidies in 15 countries across five continents between 1983 and 2012. 2. The increasing effect on household consumption reflects the loss of production among noncompetitive sectors of the economy that lose energy subsidies. See World Bank (2013) for a more detailed explanation. 3. The price structure described here became effective on May 1, 2014. The previous tariff structure, valid between January and April 2014, had slightly lower fees for the highest consumption block of the first tier, as well as for the second tier of residential consumption. Appendix 4A details the previous structure. 4. This type of cylinder is typically used by households. Larger cylinders of 25–35 kilograms are most frequently consumed in the hospitality/tourism industry. 5. From a public finance perspective, the latest data available for both residential and nonresidential consumers in 2013 indicate that some 51 percent of total energy subsidies go to finance electricity subsidies; 23 percent to diesel; 15 percent to LPG; 6 percent to gasoline; 5 percent to crude oil; and 1 percent to kerosene (World Bank 2013). 6. Nevertheless, LPG prices have remained unchanged since February 2010. 164 7. In addition, the consumption of each energy source and, therefore, the ultimate beneficiaries of the subsidized prices vary substantially by sector, as shown in appendix 4C. Figures reported in appendix 4C refer to 2012, the latest available for the composition of consumption within each sector, residential and nonresidential. 8. Due to limits on space, the full set of results is not presented here, but is available from the authors upon request. 9. The monetary cost of the food basket defines the extreme poverty line. This line is also adjusted by differences in cost of living for cities (grandes villes), medium-sized towns (petites communes), and rural areas (zones non-communales). The extreme poverty line based on food needs is further adjusted by adding the average spending of extreme poor households on nonfood items to come up with a “low” poverty line and by adding the average spending of nonextreme poor households on nonfood items for setting the “high” poverty line. This exercise uses the upper poverty lines. INS, BAD, and World Bank (2012) provides a detailed description of the construction of the total consumption aggregate. 10. In effect, the three percentage point reduction in the Gini coefficient in simulation 3 implies an 8 percent reduction in the postreform Gini. The reductions in Gini from the other two simulations render even smaller relative improvements. <>References Araar, A., and P. Verme. 2012. “Reforming Subsidies: A Tool-Kit for Policy Simulations.” Middle East and North Africa Region, Policy Research Working Paper 6148, World Bank, Washington, DC. Government of Tunisia. 2014. Reforme des subventions et du système d’assistance sociale; Organisation et Rôle des Groupes de Travail. IMF (International Monetary Fund). 2014. Subsidy Reform in the Middle East and North Africa: Recent Progress and Challenges Ahead. Middle East and Central Asia Department, IMF, Washington, DC. INS (Institut National de la Statistique), BAD (Banque Africaine de Développement), and World Bank. 2012. “Mesure de la pauvreté, des inégalités et de la polarisation en Tunisie 2000– 2010.” Tunis, l'Institut National de la Statistique. 165 Jomaa, M. 2014. “Personne n'a le droit de bloquer les permis pétroliers.” Kapitalis, September 4, http://www.kapitalis.com/kapital/24453-mehdi-jomaa-personne-n-a-le-droit-de-bloquer- les-permis-petroliers.html. Société Tunisienne d’Electricité et du Gaz. 2014. “Tables des Tarifs.” Direction des Etudes et de la Planification. World Bank. 2013. “Vers une meilleure equité: Les subventions energetiques, le ciblage, et la protection sociales en Tunisie.” Policy Note, Washington, DC. ———. 2014. “The Unfinished Revolution: Bringing Opportunity, Good Jobs, and Greater Wealth to All Tunisians.” Development Policy Review, World Bank, Washington, DC. 166 <>Chapter 5 <>The Quest for Subsidy Reforms in Libya Abdelkrim Araar, Nada Choueiri, and Paolo Verme <>Introduction Libya has a long history with consumers’ subsidies to cover food and energy products. Subsidies were first introduced in the early 1970s and continued with various degrees of coverage until the late 2000s when a first serious attempt to reform the system was launched. The reform process was quickly reversed shortly before the 2011 revolution in an attempt to reduce social discontent. That move could not stop the revolution, and it resulted in a major cost to the state budget during the postrevolution period already characterized by a declining economy and political instability. Subsidies were not the only source of economic distortions in Libya under Muammar Gaddafi’s rule, but the combination of subsidies and other distortionary policies deprived the Libyan economy of the fundamental set of incentives that drives a market economy and made both the population and private firms dependent on the state’s support (Chami 2012; Charap 2013). Functioning markets are among the foundations of functioning democracies, and a reform of the subsidy system is a step forward in the direction of a functioning state. However, subsidy reforms are politically complex and economically costly for the population and cannot be implemented without a preliminary assessment of the reforms’ implications. This chapter provides for the first time a distributional analysis of food and energy subsidies in Libya and simulates the impact of subsidy reforms on household well-being, poverty, and the government budget. We assess the benefit that different population income groups derive from subsidies, the social cost of subsidy reforms for the different segments of the population, and the government gain from increases in prices of subsidized goods. Information on the distributive incidence of subsidies and the social impact of reforms is essential to design compensation mechanisms that may accompany subsidy reforms and alleviate the burden of reforms for the poor. This chapter also provides some tentative estimates of the effect of cash compensations and some considerations on how subsidy reforms could be implemented. 167 Despite the focus on direct effects only, the results indicate that subsidy reforms would have a major impact on household welfare and government revenue. The elimination of food subsidies would reduce household expenditure by about 10 percent, double the poverty rate, and save the equivalent of about 2 percent of the government budget. The elimination of energy subsidies would have a similar effect in terms of household welfare but a larger effect on poverty; government savings would be almost 4 percent of the budget. The size of these effects, the weakness of market institutions, and the current political instability make subsidy reforms extremely complex in Libya. It is also clear that subsidy reforms will call for some sort of compensation in cash, a gradual rather than a radical approach, and a product-by-product sequence of reforms. This chapter offers an initial set of considerations that can be used by policy makers for preparing a reform plan. The chapter is structured as follows: the next section presents an overview of Libya’s food and energy subsidy program and its evolution. Following the overview is an introduction to the baseline data and assumptions made. The next two sections present the results for the distributive incidence of subsidies and reform simulations for food and energy subsidies. The concluding sections discuss the political economy of reforms, summarize the main findings, and consider possible future subsidy reforms. <>Evolution of Subsidies Libya’s ample subsidy program dates back to 1971 when a national institute was created to oversee consumption of essential goods. The system covers a number of food and energy products, as well as public services (water, sanitation, education, and garbage collection), medicines, and animal feed. Subsidies are regulated by a compensation fund that determine prices with the objective of keeping essential consumption items at affordable prices and protect consumers from major global price shocks. Since the early 2000s food subsidies have significantly increased, imposing a toll on the government budget. Data from Libya’s Price Regulation Fund show that the nominal cost of food subsidies has increased from less than LD (Libyan dinar)172 million in 2001 to more than LD 2 billion (1 billion equals 1,000 millions) in 2012. Over the years, the basket of subsidized goods has seen some variation, from a minimum of three products in 2009 to a maximum of 12 168 products after the 2011 revolution, with flour, semolina, and rice consistently subsidized since 2001. A process of subsidy reforms took place between 2005 and 2010, but at the outbreak of the revolution, these reforms were rolled back almost entirely. This move led to a significant increase in the cost of food subsidies from 1.1 percent of gross domestic product (GDP) in 2010 to 2 percent of GDP in 2012 (table 5.1). As a share of government expenditure, food subsidies also doubled from 2 percent to 3.8 percent between 2010 and 2012. Flour, sugar, rice, vegetable oil, and semolina represent the lion’s share of the cost of food subsidies to the government. Table 5.1: Government Expenditure on Food Subsidies, 2001–12 (LD millions) Item 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011* 2012* Wheat 12 99 -31 77 0 0 0 0 0 0 n.a. n.a. Flour 124 151 338 527 491 390 467 925 953 703 n.a. n.a. Sugar 11 22 39 44 55 54 107 0 0 0 n.a. n.a. Rice 8 52 46 104 101 108 97 141 236 187 n.a. n.a. Olive and other vegetable oils -6 5 99 165 120 116 134 0 0 0 n.a. n.a. Tea 18 11 15 31 17 41 34 0 0 0 n.a. n.a. Tomato paste 9 9 16 0 0 0 0 0 0 0 n.a. n.a. Dry yeast 0 1 4 11 10 17 13 0 0 0 n.a. n.a. Evaporated milk -7 3 56 147 0 0 0 0 0 0 n.a. n.a. Semolina 0 4 37 48 37 68 43 50 144 58 n.a. n.a. Miscellaneous 4 2 6 6 7 7 7 0 0 0 n.a. n.a. Pasta 0 0 0 42 0 0 0 0 0 97 n.a. n.a. Total 172 357 625 1,202 839 801 902 1,117 1,333 1,046 1,414 2,046 in percent of GDP 1.1 3.3 2 in percent of government expenditure 2 4.8 3.8 Source: Data provided by Libya’s Price Regulation Fund, obtained from the Central Bank of Libya. Note: *Data for 2011 and 2012 are preliminary. For 2001–10, the breakdown refers to the Price Regulation Fund’s operational balance, a proxy for the cost of subsidies to the government because the fund is responsible for buying the commodities on the international market and distributing them to cooperatives. A negative number therefore indicates an operational surplus for that particular commodity and year, which could be due to accumulated inventories from previous years. [[Typesetter: in table 5.1 replace hyphens with minus signs; Terms under the total row; change "in" to "In"]] 169 Food subsidies vary between 39 percent and 96 percent of the market price, and they are well above 80 percent for most products (table 5.2). They are administered under a system of individual quotas regulated by the Ministry of Economy. Subsidized food products are made available in fixed per capita quantities at cooperatives throughout the country, except for subsidized flour used to bake bread which is distributed to bakeries directly. Quotas are identical for all individuals and have remained unchanged for more than a decade. The quantities are very generous and exceed an individual’s nutritional needs.1 As indicated in table 5.2, these quantities generate about 4,570 calories per person per day—more than double the level recommended by the World Health Organization (WHO) or the Food and Agriculture Organization (FAO). Initially, eight food products were made available under this system: flour, wheat, barley, rice, oil, sugar, tea, and salt. But the list gradually increased over the years to include items such as pasta, coffee, tomato paste, milk for children, and others. Table 5.2: Food Subsidies and Quotas, 2008–12 Subsidy Generated Quota Enforced (per person per month) Subsidized Market Price (in (percent of the calories (per Item Unit price (in LD) LD) free market person per 2008 2009 2010 2011 2012 price) day) 1 Flour for Kg 0.090 1.030 91% 3.00 3.00 3.00 3.00 3.00 407 individuals 2 Flour for bekeries Kg 0.040 0.960 96% 12.00 12.00 12.00 12.00 12.00 1,628 3 Yeast for bekeries Kg 1.345 5.345 75% 0.00 0.00 0.00 0.06 0.06 n.a. 4 Semolina Kg 0.080 0.910 91% 0.00 0.00 0.00 1.00 1.00 137 5 Rice Kg 0.140 1.560 91% 2.50 2.50 2.50 2.50 2.50 347 6 Sugar Kg 0.250 1.320 81% 2.00 2.00 2.00 2.00 2.00 1,067 7 Tea Kg 1.500 5.100 71% 0.00 0.00 0.00 0.20 0.20 13 8 Pasta Kg 0.200 1.390 86% 1.50 1.50 1.50 1.50 1.50 206 9 Vegetable Oil liter 0.600 3.400 82% 0.00 0.00 0.00 1.50 1.50 173 10 Tomato Paste Kg 0.600 2.140 72% 0.00 0.00 0.00 1.00 1.00 433 11 Milk_children Kg 7.500 12.250 39% 0.00 0.00 0.00 3.20 3.20 n.a. 12 Milk_condensed Kg 0.980 2.620 63% 0.00 0.00 0.00 1.23 1.23 159 Sources: Information provided by Libyan Authorities during World Bank missions; FAO (2003); World Bank staff calculations. Note: kg = kilogram; L = liter; LD = Libyan dinar. [[Typesetter: for table 5.2 Use sentence style; In item list, change "bekeries" to "bakeries", change "Milk_children" to "Milk for children", change "Milk_condensed" to "Milk (condensed)"; in unit column, change "liter" to "L"]] 170 Despite some attempts to control the food subsidy system, significant leakages and abuse are believed to occur. Individuals need to be members of a cooperative to be able to shop there. Because individuals are also able to buy these goods on the free market at liberalized prices, not all Libyans are cooperative members, particularly among wealthier households. Although there are no centralized membership records or other mechanisms to control “double-dipping,” Libyan authorities estimate that the total number of cooperative members in the country exceeds the population size, suggesting that abuses of the quota system are widespread. Energy subsidies were also introduced in 1971 and are currently administered by the National Oil Corporation under the authority of the Ministry of Oil. The subsidies cover five products: gasoline, diesel, liquefied petroleum gas (LPG), kerosene, and electricity. Between 1995 and 2000 subsidies on these products were already on the rise, increasing from around 234 million dinars in 1995 to 404 million in 2000 and with the largest subsidies accorded to diesel and electricity (Waniss and Erling 2007). The largest increases occurred during the 2000s before the revolution because of the inability of the regime to increase retail prices during the global rise in oil prices. Energy subsidies continued to increase after the revolution, reaching an estimated peak of LD 6.3 billion in 2012. Energy products are universally subsidized, at rates exceeding 85 percent of the products’ market value (table 5.3), with the highest subsidies provided for LPG and kerosene. Table 5.3: Energy Prices and Subsidies, 2013 Subsidized price Market price Subsidy (LD per unit) (LD unit) (% of market price) Gasoline (L) 0.150 1.072 86 Diesel (L) 0.150 1.110 86 Electricity (kWh) 0.020 0.156 87 LPG (L) 2.000 20.939 90 Kerosene (L) 0.090 1.089 92 Sources: Libyan authorities and World Bank staff calculations. Note: Market prices refer to first quarter of 2013. kWh = kilowatt hour; L = liter; LD = Libyan dinar. 171 It is important to stress that estimates of subsidies in Libya vary significantly across sources. For example, government figures for 2012 indicated that the total amount for food and energy subsidies in 2012 was LD 9.5 billion, equivalent to about 9.2 percent of GDP,2 while the IMF, by including estimates on electricity and other subsidies, reaches an amount of LD 14.8 billion or 13.8 percent of GDP (IMF 2013). These estimates vary in absolute terms and relatively to GDP. Absolute estimates vary partly because what is considered a subsidy is not fixed and partly on whether subsidies include or exclude administrative costs. Estimates of subsidies as percentage of GDP can also vary because GDP figures are themselves volatile estimates in Libya due to weak national accounts and the prominence of oil as a source of revenues. Despite these caveats, it is clear that consumers’ subsidies in Libya are among the highest in the North Africa and Middle East (MENA) Region (Zaptia 2013). <>Baseline Data, Assumptions, and Limitations The analysis provided in this chapter is based on the 2007–08 Libyan Household Expenditure Survey (LHES), with all figures presented in the distributional and simulation analyses estimated at 2013 prices. This survey is the most recent household expenditure survey administered by the national statistical agency and the only survey available in Libya today for this type of analysis. With 2007 as the starting point, data are projected from 2008 to 2013 using official population estimates and IMF estimates for inflation and real GDP growth for the period 2008–13 (table 5.4). Table 5.4: Parameters Used for the 2008–13 Extrapolations 2007 2008 2009 2010 2011 2012 2013 Gross domestic product (in billions of LD/constant prices) 44.5 45.7 45.3 47.6 18.1 36.9 44.4 Inflation (average percent change in CPI; base year 2003) 112.0 123.7 126.7 129.8 150.5 159.6 162.8 Population (in millions) 6.0 6.2 – – – – 6.4 Sources: IMF 2013 and Libyan authorities. Note: CPI = consumer price index; LD =Libyan dinar. The chapter focuses on the direct effects of subsidy reforms.3 This is not a major constraint for the case of food subsidies, but is an important limitation for energy subsidies. Given that food 172 subsidies in Libya are subject to a quota system, the share of subsidized food products that could be used in the production of other goods is likely to be negligible.4 For example, although sugar can be an input to the production of many processed food products, the quota system in place makes it unlikely that sugar used in food production is actually bought at subsidized prices. We will therefore assume that indirect effects for food are relatively small.5 The treatment of bread in the analysis requires a number of assumptions. We have information on subsidized prices and quantities of flour (and yeast) for bakeries, both of which are supposed to be used in making bread, but we only have household expenditure data on bread. We translate the flour subsidy into a bread subsidy as follows. We estimate that 1 kilogram of bread requires 1 kilogram of flour, and given disparate prices of bread across bakeries in Tripoli we assume that a 100 gram baguette is sold for 5 Libyan dirhams. Therefore, the price of a kilogram of bread is LD 0.5. We are therefore able to map the household expenditure on bread first into a quantity of bread (using the 5 dirhams per 100 gram baguette) and then into a quantity of flour, and present these information under the heading “Flour (bread)” in the chapter tables. Although indirect effects are small in the case of food products, they are likely to be significant in the case of energy products. The reason is that energy subsidies in Libya are universal and very large in magnitude, and energy products are an important input in a number of production processes. Therefore, the effect of increasing energy prices on consumer prices is likely large, particularly if producers pass on the associated increases in production costs to consumers. However, input-output data for the Libyan economy were not available, and indirect effects could not be estimated. The survey data suggest that Libyan households are large and their aggregate consumption is a low share of GDP (table 5.5). Libya has a small population, estimated at just below 6.4 million and about 1 million households. Aggregate annual household expenditure is estimated at LD 12.5 billion, implying that annual expenditure per capita is about LD 1,967. Households in the poorest two quintiles are large, at 9.5 and 7.4 members per household, respectively. On average, these household sizes are larger than those in neighboring countries. For example, household size in Morocco is 6.5 for quintile 1 and 5.9 for quintile 2, and in Tunisia these figures are 5.8 and 5.0, respectively. Aggregate household expenditure in Libya is only about 12 percent of GDP.6 This number is atypical of the North African Region, where surveys indicate that household 173 expenditure is usually around two-thirds of GDP; but it is not totally surprising when we look at comparative data for other oil rich countries such as Qatar, Saudi Arabia, and Algeria where household expenditure as percentage of GDP can vary between 11 percent and 35 percent.7 Household final consumption is essentially a small fraction of output as a whole because oil dominates the economy (producing more than two-thirds of GDP). Only a small share of oil proceeds accrues to households via wages and public transfers, while a bigger share accrues through subsidies, which do not appear in actual expenditure. Table 5.5: Household Statistics Projected to 2013 Average Total Average Average Population Number of Quintile household size expenditures expenditures per expenditures per (persons) households (persons) (LD) capita (LD) household (LD) 1 (poorest) 1,936,699 203,399 9.5 1,842,216,192 951 9,057 2 1,512,025 203,373 7.4 2,288,316,928 1,513 11,252 3 1,264,391 203,346 6.2 2,580,271,872 2,041 12,689 4 992,019 203,392 4.9 2,745,245,952 2,767 13,497 5 (richest) 666,346 203,331 3.3 3,077,710,080 4,619 15,136 Total 6,371,480 1,016,842 6.3 12,533,761,024 1,967 12,326 Sources: Libyan Household Expenditure Survey (LHES) 2007–08; Libyan authorities; and World Bank staff calculations. In what follows, the incidence and impact analyses are presented separately for food products and energy products. The analysis is conducted separately because of the different subsidy systems (universal for energy but quota-based for food), which require a different setup for the subsidies simulation model. Also, differences in the relative importance of indirect effects call for a different approach to interpreting the results. The analyses that follow are based on SUBSIM, a subsidies simulation package produced by the World Bank (www.subsim.org). 174 <>Food Subsidies This section provides a distributional analysis of food subsidies to better explain who benefits from subsidies. It also provides a simulation of subsidies reforms to discover who would suffer the most from the partial or total removal of subsidies. <>The Distribution of Food Subsidies Food subsidies are relatively progressive, but a third of them do not reach households. In this section, we quantify the size of subsidies received by households at different income levels. The results suggest that food subsidies are relatively progressive in Libya, mostly thanks to the quota system by which they are administered. However, only about 65 percent of the budgetary costs of subsidies reach households. The difference is probably explained by “leaks” from the subsidy system, including waste from illegal resale of subsidized items outside of the quota system at near market prices and perhaps by administrative costs that cannot be clearly separated and accounted for. Our estimates are an upper bound of the subsidies received by households. The reason is that the analysis is based on the assumption that all households purchase the entire amount of quotas to which they are entitled.8 That assumption may not always be the case as some households may choose not to go to cooperatives to purchase products at subsidized prices—as is reported for a nonnegligible share of Libya's population (mostly middle- and upper-income tranches) In the absence of information on the share of households taking advantage of the quota system in their food purchases, it is more conservative to assume that households take the maximum advantage of the benefit available to them so as not to underestimate the impact of any reform on the population. This assumption also compensates for the nonobservable leakages due to “double dipping.” Households allocate about 9.3 percent (LD 1.2 billion) of their total expenditure on subsidized food products, if we consider the share bought under the quota system and the share bought at market prices (table 5.6). About 22.2 percent of this amount is expenditure on quotas at subsidized prices, and the rest is on the same products bought on the free market. This finding may seem at odds with the fact that quotas provide generous quantities, but richer households are unlikely to shop at cooperatives, which administer quotas. Rich households may opt for better 175 quality and more expensive products, and poorer households may also consume a share of better quality brands not available in the quota system. Indeed, for most of these food products, the market may offer several better quality options that may be preferred by the rich and poor alike. Also and more important, expenditure on quotas is low because prices are low under the quota system as compared to the market prices. For some products, like flour-bread and milk for children, the total expenditure is only on quotas, and there are no purchases of these products at nonsubsidized prices. For products such as bread, which is also sold outside cooperatives, the quota system is not binding. Table 5.6: Household Expenditure on Subsidized Food Products, in LD million Percent at Food products Q1 Q2 Q3 Q4 Q5 Total subsidized prices Flour 11.2 11.6 11.8 11.7 10.5 56.9 15 Flour-bread 3.6 3.3 2.9 2.4 1.9 14.1 100 Semolina 7.6 7.9 7.2 6.3 5.1 34.1 3.7 Rice 18.6 20.6 20.2 20.2 19.3 98.8 15.7 Sugar 21.3 23.5 23.2 23.3 21.8 113.1 21.7 Tea 17.9 20.2 20.0 19.4 19.1 96.6 12.6 Macaroni 33.4 34.8 33.3 32.1 29.8 163.5 11.4 Vegetable oil 58.0 60.9 61.4 59.1 55.4 294.8 18 Paste tomatoes 24.2 25.8 26.2 25.0 24.2 125.3 28.4 Milk for children 4.5 6.8 8.3 9.7 9.0 38.3 99.9 Milk (concentrated) 26.5 29.1 27.9 24.3 23.0 130.8 28.3 Total 227.0 244.5 242.4 233.4 219.0 1,166.2 22.2 Percent of 12.3 10.7 9.4 8.5 7.1 9.3 2.1 total expenditure Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Note: Q = quintile, with 1 being the poorest, and 5, the richest. In terms of quantities, households consume approximately half of the food products via purchases made under the quota system at subsidized prices and buy the other half at market prices (table 5.7). Given the larger size of poorer households and their greater reliance on quotas, the first and second quintiles consume products at subsidized prices in higher quantities than the 176 richer quintiles. The share of products bought via the quota system varies from 30.6 percent for semolina to 100 percent for milk for children and flour for bread. Flour for bread and pasta are the subsidized products with the largest consumption. These products are basic staples for Libyans, and quotas for these products are larger than those for other products. Table 5.7: Quantities of Subsidized Food Products Consumed, in kilograms or liters Percent at subsidized Q1 Q2 Q3 Q4 Q5 Total prices (quotas) Flour (kg) 35.4 31.7 29.2 26.0 19.6 141.9 66.9 Flour-bread (kg) 96.9 89.7 77.9 64.9 51.5 380.9 100 Semolina (kg) 12.8 12.6 10.9 9.0 6.7 52.0 30.6 Rice (kg) 39.1 37.2 34.2 30.0 24.0 164.3 67.5 Sugar (kg) 38.3 37.0 33.9 30.8 25.2 165.2 59.3 Tea (kg) 5.1 5.4 5.1 4.7 4.3 24.6 32.8 Macaroni (kg) 47.1 44.2 40.1 35.9 30.0 197.4 47.4 Vegetable oil (L) 37.8 35.3 33.0 29.2 24.2 159.6 55.5 Paste tomatoes (kg) 23.5 22.3 21.0 18.5 15.9 101.2 58.6 Milk for children (kg) 0.6 0.9 1.1 1.3 1.2 5.1 100 Milk (concentrated) (kg) 16.8 17.1 15.6 13.0 11.2 73.8 51.5 Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Note: kg = kilogram; L = liter; Q = quintile, with 1 being the poorest, and 5, the richest. Poorer households spend a much greater share of total expenditure on subsidized food items than richer households. Indeed, while expenditure on food products at subsidized prices represents 9.3 percent of total household expenditure (table 5.8) on average, this share is higher for the first (12.32 percent) and second (10.68 percent) quintiles and falls to 7.12 for the fifth quintile. The larger size of poorer households explains part of this observation. If we focus on quotas only (the share bought at subsidized prices), the first quintile’share is 3.61 percent against the fifth quintile share of 1.07 percent. Table 5.8: Percentage of Spending on Subsidized Food in Total Expenditure Total Q1 Q2 Q3 Q4 Q5 Total (quotas) Flour 0.61 0.50 0.46 0.43 0.34 0.45 0.07 Flour-bread 0.19 0.15 0.11 0.09 0.06 0.11 0.11 Semolina 0.41 0.35 0.28 0.23 0.16 0.27 0.01 Rice 1.01 0.90 0.78 0.74 0.63 0.79 0.12 177 Sugar 1.16 1.03 0.90 0.85 0.71 0.90 0.2 Tea 0.97 0.88 0.77 0.71 0.62 0.77 0.1 Macaroni 1.81 1.52 1.29 1.17 0.97 1.30 0.15 Vegetable oil 3.15 2.66 2.38 2.15 1.80 2.35 0.42 Paste tomatoes 1.31 1.13 1.01 0.91 0.78 1.00 0.28 Milk for children 0.25 0.30 0.32 0.35 0.29 0.31 0.31 Milk (concentrated) 1.44 1.27 1.08 0.89 0.75 1.04 0.3 Total 12.32 10.68 9.39 8.50 7.12 9.30 2.07 Total (quotas) 3.61 2.63 2.08 1.65 1.07 2.07 – Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Note: Q = quintile, with 1 being the poorest, and 5, the richest. The importance of food subsidies for poorer households is even more apparent when we look at the distribution of expenditure shares by population percentiles. Figure 5.1 plots the share of expenditure on food products at subsidized prices, relative to total expenditure, by population percentiles. The negative slopes indicate that poorer households devote a larger share of their total spending on food bought under the quota system than richer households (for all products except milk for children.) In other words, food is a larger component of the consumption basket of poorer households. Figure 5.1: Percentage of Total Household Expenditure on Food Bought at Subsidized Prices (quotas only) 178 .015 Flour Flour-bread Semolina Rice Sugar .01 Tea Expenditure shares Macaroni Vegetable oil Paste tomatoes Milk for children .005 Milk (concentrated) 0 .01 .198 .386 .574 .762 .95 Household Percentiles Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. The poorest quintiles benefit the most from the monetary value of subsidies (table5. 9), except for milk for children. This result sets Libya apart from other countries in the Region, where food subsidies tend to be slightly regressive because richer households consume more food overall and because subsidies are universal, unconstrained by a quota system. Table 5.9: Value of Food Subsidies by Quintile, in LD million Q1 Q2 Q3 Q4 Q5 Total Flour 25.2 21.1 18.3 15.1 9.6 89.3 Flour-bread 89.4 82.7 71.9 59.8 47.5 351.2 Semolina 4.1 3.5 2.7 1.9 1.0 13.2 Rice 42.3 37.4 33.1 26.5 18.1 157.4 179 Sugar 29.2 25.3 21.4 17.4 11.3 104.6 Tea 8.2 7.2 6.1 4.6 3.0 29.1 Macaroni 32.3 26.9 22.6 17.9 12.0 111.7 Vegetable oil 70.7 59.3 50.9 40.2 27.1 248.3 Paste tomatoes 26.1 22.1 18.7 14.7 9.9 91.4 Milk for children 2.9 4.3 5.2 6.1 5.7 24.2 Milk (concentrated) 17.6 15.8 13.1 9.7 6.4 62.6 Total 348.0 305.6 264.1 213.8 151.6 1,283.0 Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Note: Q = quintile, with 1 being the poorest, and 5, the richest. The per capita data suggest that subsidies benefit all people equally, with the exception of flour used for bread and milk for children.9 Figure 5.2 plots the total monetary value of food subsidies per capita on the y axis and the population percentiles on the x axis. The curves are flat, indicating everyone across the spectrum of the population derives the same monetary value from food subsidies. Again, this result is not surprising given that the quota system is established on a per capita basis, allocating the same quantity of food at subsidized prices to every individual regardless of the income bracket. Figure 5.2: Per Capita Benefits from Food Subsidies by Product, in LD 180 80 Flour Flour-bread Semolina Rice 60 Sugar Total benefits per capita Tea Macaroni Vegetable oil 40 Paste tomatoes Milk for children Milk (concentrated) 20 0 .01 .198 .386 .574 .762 .95 Household Percentiles Sources: Libyan Household Consumption Survey 2007–08 Libyan authorities; and World Bank staff calculations. >Simulation of Food Subsidy Reforms This section simulates subsidy reforms and estimates the impact on household welfare and the government budget. We consider two scenarios: a 30 percent decrease in the subsidy for each product and the total elimination of all subsidies. Note that a 30 percent decrease in the subsidy on each product would result in a different price increase for each product. Table 5.10 reports the current subsidized price for each product under the quota regime, the unit subsidy, the price after a 30 percent reduction in subsidy (final price, scenario 1) and the price after the elimination of all subsidies (final price, scenario 2). The last price is equivalent to the market reference price we consider for each product.10 181 Eliminating all food subsidies (scenario 2) would result in exceptionally high price increases. The price of flour used in making bread would need to increase by almost 26 times to reach the market price, and prices of flour, semolina, and rice would need to increase more than 11 times. Even in the case of milk for children, the product with a price currently the closest to the market price, a 60 percent increase would be needed to match the market price—a significant price increase. Table 5.10: Prices, Subsidies, and Reform Scenarios Final price Final price Final price Initial price Subsidy (scenario 2)/ (scenario 1) (scenario 2) Initial price Flour 0.090 0.940 0.372 1.030 11.4 Flour for bread 0.037 0.922 0.314 0.959 25.9 Semolina 0.080 0.831 0.329 0.911 11.4 Rice 0.140 1.419 0.566 1.559 11.1 Sugar 0.250 1.068 0.570 1.318 5.3 Tea 1.500 3.597 2.579 5.097 3.4 Macaroni 0.200 1.194 0.558 1.394 7.0 Vegetable oil 0.600 2.802 1.441 3.402 5.7 Tomato paste 0.600 1.541 1.062 2.141 3.6 Milk for children 7.500 4.750 8.925 12.250 1.6 Milk 0.975 1.647 1.469 2.622 2.7 Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. These price increases would affect the poor in greater proportion than the rich. The total monetary impact of a complete removal of subsidies (scenario 2) on households would be equivalent in magnitude to the total estimated monetary value of subsidies received by households, namely LD 1.3 billion (table 5.11).11 The total impact of a 30 percent reduction in subsidies (scenario 1) is estimated at LD 385 million. The impact would be regressive in that poorer households would be affected more than richer households, as indicated by the greater loss in per capita spending for lower quintiles (table 5.12). This result is to be expected because food subsidies were shown to benefit the poor in greater proportion. For example, with an elimination of subsidies, the first quintile (the poorest 20 percent of the population) would bear a cost of LD 348 million. And at 18.9 percent, the decline in per capita spending of the lowest 182 quintile if food subsidies were eliminated is nearly four times that of the highest quintile (4.9 percent). This would be a disproportionate cost for poorer households. Table 5.11: Aggregate Monetary Impact of Subsidy Reform on Welfare, in LD million Total Total Q1 Q2 Q3 Q4 Q5 scenario 2 scenario 1 Flour −25.2 −21.1 −18.3 −15.1 −9.6 −89.3 −26.8 Flour−bread −89.4 −82.7 −71.9 −59.8 −47.5 −351.2 −105.4 Semolina −4.1 −3.5 −2.7 −1.9 −1.0 −13.2 −4.0 Rice −42.3 −37.4 −33.1 −26.5 −18.1 −157.4 −47.2 Sugar −29.2 −25.3 −21.4 −17.4 −11.3 −104.6 −31.4 Tea −8.2 −7.2 −6.1 −4.6 −3.0 −29.1 −8.7 Macaroni −32.3 −26.9 −22.6 −17.9 −12.0 −111.7 −33.5 Vegetable oil −70.7 −59.3 −50.9 −40.2 −27.1 −248.3 −74.5 Paste tomatoes −26.1 −22.1 −18.7 −14.7 −9.9 −91.4 −27.4 Milk for children −2.9 −4.3 −5.2 −6.1 −5.7 −24.2 −7.3 Milk (concentrated) −17.6 −15.8 −13.1 −9.7 −6.4 −62.6 −18.8 Total −348.0 −305.6 −264.1 −213.8 −151.6 −1,283.0 −384.9 Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Note: Q = quintile, with 1 being the poorest, and 5, the richest. Table 5.12: Per Capita Impact of Subsidy Reform (percent of per-capita expenditure) Total Total Q1 Q2 Q3 Q4 Q5 scenario 2 scenario 1 Flour −1.37 −0.92 −0.71 −0.55 −0.31 −0.71 −0.21 Flour−bread −4.85 −3.61 −2.78 −2.18 −1.54 −2.80 −0.84 Semolina −0.22 −0.15 −0.10 −0.07 −0.03 −0.11 −0.03 Rice −2.30 −1.63 −1.28 −0.97 −0.59 −1.26 −0.38 Sugar −1.59 −1.10 −0.83 −0.63 −0.37 −0.83 −0.25 Tea −0.44 −0.32 −0.24 −0.17 −0.10 −0.23 −0.07 Macaroni −1.75 −1.18 −0.88 −0.65 −0.39 −0.89 −0.27 Vegetable oil −3.84 −2.59 −1.97 −1.46 −0.88 −1.98 −0.59 Paste tomatoes −1.42 −0.96 −0.73 −0.53 −0.32 −0.73 −0.22 Milk for children −0.16 −0.19 −0.20 −0.22 −0.18 −0.19 −0.06 Milk (concentrated) −0.96 −0.69 −0.51 −0.35 −0.21 −0.50 −0.15 Total −18.89 −13.35 −10.23 −7.79 −4.93 −10.24 −3.07 183 Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Note: Q = quintile, with 1 being the poorest, and 5, the richest. The direct impact on government expenditure from the complete removal of subsidies (scenario 2) would be equivalent to the total impact on household welfare, namely LD 1.3 billion— equivalent to 2.8 percent of government expenditure (table 5.13).12 Under a partial reduction of subsidies (30 percent in the case of scenario 1), the total impact on government expenditure would be greater than the impact on household welfare. Under scenario 1, the total impact on government expenditure would amount to LD 660 million, compared to LD 385 million for the impact on household welfare (table 5.11). This difference is explained by the fact that when subsidies are not totally removed we have two potential causes for lower government expenditure, the first resulting from the increase in subsidized prices (which is equivalent in size to the impact on household welfare) and the second resulting from the reduction in quantities consumed by households at these higher subsidized prices. If subsidies were totally eliminated, this second effect would disappear given that no quantities would be sold at a subsidized price. Table 5.13: Impact of Subsidy Reform on the Government Budget (Million LD) Scenario 1 Scenario 2 Scenario 2 Total Total (percent govt. Q1 Q2 Q3 Q4 Q5 expenditure) Flour 13.7 11.4 9.9 8.2 5.2 48.5 89.3 0.1 Flour-bread 56.4 52.2 45.4 37.8 30.0 221.7 351.2 0.5 Semolina 2.2 1.9 1.5 1.0 0.6 7.2 13.2 0.0 Rice 22.8 20.2 17.9 14.3 9.8 84.9 157.4 0.2 Sugar 13.2 11.5 9.7 7.9 5.1 47.4 104.6 0.2 Tea 3.3 2.9 2.5 1.9 1.2 11.8 29.1 0.0 Macaroni 15.7 13.1 11.0 8.7 5.8 54.2 111.7 0.2 Vegetable oil 32.7 27.4 23.5 18.6 12.5 114.6 248.3 0.4 Paste tomatoes 10.7 9.0 7.7 6.0 4.0 37.5 91.4 0.1 Milk for children 1.0 1.4 1.8 2.1 1.9 8.1 24.2 0.0 Milk (concentrated) 6.7 6.0 5.0 3.7 2.4 23.9 62.6 0.1 Total 178.4 157.1 135.7 110.0 78.6 659.8 1283.0 2.0 184 Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Note: Q = quintile, with 1 being the poorest, and 5, the richest. Should a gradual approach to reform be considered, measuring the government budgetary impact may help with the decision regarding the sequencing and size of subsidy reforms. Figure 5.3 traces, for each product, the impact of a proportional reduction in subsidy (shown in percent on the x axis) on government expenditure in absolute values (measured in LD on the y axis). The impact would differ across products because of different quantities consumed, different initial levels of subsidies, and different price changes associated with a specific subsidy reduction. The fastest decline in government spending would result from first reforming the subsidy on flour used in bread production and then that on vegetable oil. We note that the curves are not linear, implying decreasing marginal returns in terms of lower government spending should prices increase. This result is explained mainly by the importance of the decrease in consumed quantities in response to price increases. Figure 5.3: Magnitude of Decline in Government Expenditure under Reform Scenario 2, in LD 185 4.00e+08 Flour Flour-bread Semolina Rice 3.00e+08 Sugar Tea Macaroni Vegetable oil 2.00e+08 Paste tomatoes Milk for children Milk (concentrated) 1.00e+08 0 0 20 40 60 80 100 Decrease in subsides, in percent Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Removing subsidies on food products would have a significant negative impact on poverty (table 5.14). We estimate poverty in Libya based on both the international poverty line ($1.25 per day)13 and an updated national poverty line (LD 966.26 per person per year).14 Using the national poverty line, poverty is estimated at about 14.4 percent of the population. If food subsidies were eliminated, poverty would rise by about 2.8 percentage points under scenario 1 and by 9.6 percentage points under scenario 2. Price increases of flour (for bread), rice, and vegetable oil would contribute the most to a rise in poverty. Using the international poverty line would lead to a prereform poverty rate of 8.5 percent and a reform impact of 2.0 percentage points for scenario 1 and 8.1 percentage points for scenario 2. 186 Along with greater poverty, income inequality (approximated by expenditure) would rise from 30.2 percent to 33.2 percent following a complete elimination of food subsidies. This prediction is consistent with the finding that food subsidies are pro-poor. Note that inequality in Libya is very low: at 30.2 percent, the Gini coefficient is one of the lowest values in the MENA Region. For example, the latest Gini coefficient for Morocco estimated in 2007 was above 40 percent, and that for the Arab Republic of Egypt, where inequality is believed to be very low, was around 32 percent in 2011. Table 5.14: Poverty Impact of Subsidy Reforms International poverty line National poverty line Poverty Scenario 1 Scenario 2 Poverty Scenario 1 Scenario 2 level poverty poverty level poverty poverty change change change change Prereform 8.48 . . 14.44 . . Flour 8.62 0.15 0.46 14.66 0.22 0.69 Flour-bread 8.91 0.43 1.63 15.06 0.61 2.38 Semolina 8.50 0.03 0.07 14.48 0.04 0.12 Rice 8.73 0.26 0.75 14.77 0.33 0.98 Sugar 8.59 0.11 0.45 14.72 0.28 0.75 Tea 8.53 0.05 0.14 14.50 0.06 0.17 Macaroni 8.64 0.16 0.56 14.72 0.28 0.85 Vegetable oil 8.77 0.29 1.36 14.88 0.44 1.81 Paste tomatoes 8.61 0.14 0.40 14.66 0.22 0.63 Milk for children 8.48 0.00 0.03 14.45 0.01 0.08 Milk (concentrated) 8.57 0.09 0.28 14.59 0.15 0.45 Postreform 2.02 8.11 17.26 2.82 9.58 Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. A cash transfer of LD 175 per capita per year targeted to the poorest quintile would be enough to keep poverty unchanged under the scenario of full subsidy elimination (figure 5.4). An increase in poverty from 8.5 percent to 16.5 percent implies that poverty remains concentrated in the bottom quintile following the price reform. Therefore, targeting that share of the population would be sufficient to maintain poverty unchanged at the prereform level. This targeted transfer system would cost the government LD 340 million per year. Given that savings from the price 187 increases would amount to LD 1.3 billion as calculated, the net gains to the budget from full subsidy elimination and cash compensation to the population in the first quintile of LD 175 per capita would be LD 943 million. Should targeting the first quintile was not possible, extending that level of transfer to the entire population would raise the budgetary cost to LD 1.1 billion per year. In this case, total net gains to the budget from subsidy reform and cash transfers would be much lower, at LD 165 million per year. Figure 5.4: Poverty Impact of Cash Transfers to First Quintile under Food Subsidy Reform Scenario 2 (international poverty line) 20 Initial level of poverty: 8.475 percent Required transfer to maintain poverty at prereform level: 175.406 LD per capita per year 15 10 5 0 0 100 200 300 400 Level of individual transfer (LD per capita per year) Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. [[Typesetter: In the chart and legend, change red and blue lines to broken lines.]] 188 The impact of subsidy reform on quantities consumed would also be significant (table 5.15). It is useful to look at this impact because it gives an idea of the changes required in production and imports of food products bought via the quota system and to better understand the impact on government revenues. When compared to the initial quantities consumed under the quotas, changes would vary from −13.7 percent for milk for children to −62.3 percent for bread flour. The impacts are also quite flat across quintiles, although the impact on the first quintile would be lower for all products.15 Table 5.15: Impact of Subsidy Reform on Quantities Consumed per Capita (scenario 2 Item Unit Q1 Q2 Q3 Q4 Q5 Total Flour Kg −7.19 −7.69 −7.98 −8.37 −7.98 −7.73 Flour-bread Kg −31.19 −36.99 −38.42 −40.76 −48.18 −37.27 Semolina Kg −1.31 −1.45 −1.33 −1.19 −0.97 −1.29 Rice Kg −7.92 −8.97 −9.49 −9.69 −9.85 −8.96 Sugar Kg −5.55 −6.14 −6.23 −6.44 −6.26 −6.04 Tea Kg −0.36 −0.41 −0.41 −0.40 −0.38 −0.39 Pasta Kg −6.16 −6.58 −6.62 −6.67 −6.66 −6.48 Vegetable oil L −5.29 −5.68 −5.84 −5.87 −5.89 −5.64 Paste tomatoes Kg −2.78 −3.00 −3.05 −3.04 −3.04 −2.95 Milk for children Kg −0.04 −0.08 −0.12 −0.18 −0.25 −0.11 Milk (concentrated) Kg −1.42 −1.63 −1.61 −1.52 −1.50 −1.53 Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Note: kg = kilogram; L = liter. <>Energy Subsidies The benefits to households from energy subsidies are multiples of those derived from food subsidies—households in the lowest quintile derive 2.5 times more monetary benefit from energy than from food subsidies, and that ratio increases gradually to 6.5 times for the upper quintile. The analysis in this section covers five energy products: gasoline, diesel, electricity, LPG, and kerosene. Gasoline is the main energy product used by the road transport sector for individuals— both in private cars and taxis, as there are no other means of public transportation. Diesel is 189 consumed mainly by businesses (for transportation) and by the electricity generation company. Electricity and LPG are almost universally consumed. Half of the kerosene sold on the market goes to the air transport sector, and the rest is likely used by lower-income households as a substitute for electricity, but no data are available to corroborate the latter hypothesis. <>The Distribution of Energy Subsidies Gasoline and electricity represent the bulk of energy consumption and, together with other energy products, are heavily consumed by the rich. Gasoline and electricity take up more than 90 percent of household energy consumption, which corresponds to the same share of government spending on subsidies. Subsidies for these two products are clearly regressive in absolute terms. An individual in the upper quintile benefits 3.5 times more from subsidies on electricity and gasoline than an individual in the bottom quintile. That ratio is 2.8 and 2.7 for diesel and LPG, respectively. Households’ direct benefits from energy subsidies are close to LD 2.5 billion, which represents only about a third of the total cost to the budget of energy subsidies.16 Given the extremely low subsidized prices, energy products represent a very small share of household expenditure—about 3 percent of total expenditures, equivalent to LD 370 million (table 5.16). Gasoline and electricity represent the greatest share, while expenditure on kerosene is very low. The share of household spending on energy products is slightly higher for poorer households (3.6 percent) relatively to richer households (2.5 percent). The share of expenditure on LPG shows the largest difference across quintiles (table 5.17), suggesting that it is used more intensily by poorer households. Table 5.16: Household Expenditure on Energy Products, in LD million Quintile Gasoline Diesel Electricity LPG Kerosene Total 1 (poorest) 28.9 0.7 29.9 5.7 0.3 65.4 2 34.9 0.7 34.0 5.9 0.5 76.0 3 36.1 0.6 34.2 5.7 0.5 77.1 4 36.2 0.6 33.1 5.5 0.6 76.0 5 (richest) 33.6 0.7 35.8 5.2 0.6 75.9 Total 169.6 3.3 167.1 28.0 2.5 370.5 190 Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Table 5.17: Share of Energy Expenditure in Total Household Expenditure, in percent Quintile Gasoline Diesel Electricity LPG Kerosene Total 1 (poorest) 1.57 0.04 1.62 0.31 0.01 3.55 2 1.53 0.03 1.49 0.26 0.02 3.32 3 1.40 0.02 1.33 0.22 0.02 2.99 4 1.32 0.02 1.21 0.20 0.02 2.77 5 (richest) 1.09 0.02 1.16 0.17 0.02 2.47 Total 1.35 0.03 1.33 0.22 0.02 2.96 Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Compared to other countries in the North Africa Region, the share of expenditure on energy products in Libya is more homogeneous across quintiles. This finding corroborates the result we found in analyzing food subsidies, namely that the income distribution in Libya is comparatively more flat, with lower inequality, compared to other countries in the Region. Particularly striking is the distribution of gasoline and diesel expenditure. The poorest quintile of households spends on gasoline 85 percent of what the richest quintile spends and twice as much for diesel. Indeed, data on car ownership from the household survey confirm that most households in Libya own at least one car and that the share of nonowners, 25.8 percent (table 5.18), is rather homogeneously distributed across quintiles. This finding, which is atypical for countries at similar levels of per capita income, is likely explained by the very low cost of gasoline and the availability of cheap old cars.17 Table 5.18: Percentage of Households that Own Cars, by quintile and number of cars Quintile 0 car 1 car 2 cars 3 cars 4 cars 5 cars Total 1 (poorest) 6.25 12.17 1.32 0.17 0.08 0.00 20 2 4.64 13.54 1.51 0.29 0.03 0.00 20 3 4.87 13.62 1.26 0.21 0.04 0.00 20 4 4.69 13.86 1.16 0.24 0.04 0.01 20 5 (richest) 5.35 13.63 0.83 0.16 0.03 0.00 20 191 Total 25.8 66.81 6.09 1.06 0.22 0.01 100 Source: Libyan Household Consumption Survey 2007–08; World Bank calculations. Highly subsidized prices have led to excessive consumption of energy products in Libya. The household survey data imply that households consume an estimated 1.13 billion liters of gasoline per year, equivalent to about 177 liters per capita (table 5.19).18 To put that into context, we have extracted comparable data from the World Bank database on energy consumption for Libya and other countries in 2010.19 These data suggest that per capita gasoline consumption in Libya in 2010 was 281 liters, which is far greater than the household survey data imply, much higher than per capita consumption in Italy (225 liters) or France (159 liters) for that year, and far higher than the world average (187 liters). Per capita gasoline consumption in Algeria, another oil producer, is reported at 96 liters in the World Bank’s database. These statistics all point towards significant gasoline overconsumption in Libya. The same conclusion holds when comparing electricity consumption in Libya to that of other countries. Table 5.19: Household Consumption of Energy Products (in millions of units) Gasoline Diesel Electricity LPG Kerosene Quintile (L) (L) (kWh) (15 kg bottle) (L) 1 (poorest) 192.4 4.8 1,496.2 2.8 3.0 2 232.9 4.9 1,700.9 2.9 5.2 3 240.6 3.7 1,710.9 2.9 5.7 4 241.2 4.0 1,654.9 2.8 6.7 5 (richest) 223.7 4.7 1,791.3 2.6 6.9 Total 1,130.8 22.1 8,354.2 14.0 27.4 Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Figure 5.5 confirms that the expenditure share of energy products is low for both the poor and rich, although the share is higher for the poor, which is shown by the negative slope of some of the curves depicted in the figure. The differences between quintiles are not perceptible for diesel and kerosene partly because these products are consumed in very small quantities but also 192 because these products follow a different pattern across quintiles. The share of kerosene expenditure in total expenditure in particular is flat across quintiles. Figure 5.5: Household Spending on Energy Products, as share of total household expenditure .02 Gasoline Diesel Electricity LPG .015 Kerosene Expenditure shares .01 .005 0 .01 .198 .386 .574 .762 .95 Household Percentiles Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Households derive substantial benefits from energy subsidies. We estimated the total value of direct energy subsidies received by households at LD 2.5 billion (table 5.20)—6.7 times higher than total household expenditure on these products. About LD 1 billion of this total derives from gasoline and LD 1.1 billion from electricity. These numbers underscore the significant share of subsidy incorporated in energy prices in Libya: on average, the government should increase energy prices by 670 percent to reach market levels and eliminate subsidies. Table 5.20: Energy Subsidies, in LD million 193 Quintile Gasoline Diesel Electricity LPG Kerosene Total 1 (poorest) 177.4 4.6 203.5 53.6 3.0 442.0 2 214.8 4.7 231.3 55.4 5.2 511.4 3 221.8 3.6 232.7 54.1 5.7 517.8 4 222.4 3.8 225.1 52.5 6.7 510.4 5(richest) 206.3 4.5 243.6 49.5 6.9 510.8 Total 1,042.6 21.2 1,136.2 265.2 27.4 2,492.5 Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Energy subsidies in Libya are regressive (in absolute value), or pro-rich, which can be seen by looking at the distributional analysis on a per capita basis. Figure 5.6 shows per capita subsidies (y axis) across population percentiles (x axis) for each subsidized energy product. All curves are positively sloped, which indicates that richer households receive higher amounts of subsidies per capita. The regressive feature of energy subsidies is less pronounced for the cases of kerosene and diesel, consistent with the proposition that these products are consumed more intensively by the poorer population. This feature is most pronounced for gasoline and electricity, the two products whose subsidies generate the biggest cost to the government budget. Figure 5.6: Per Capita Benefits Accruing from Subsidies on Energy Products, in LD 194 400 Gasoline Diesel Electricity LPG 300 Kerosene 200 100 0 .01 .198 .386 .574 .762 .95 Household Percentiles Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. <>Simulations of Energy Subsidy Reforms Energy subsidy reforms are expected to have a significant direct impact on households. Consistent with gasoline and electricity being the main energy products consumed by households, we find that reducing subsidies on these two items would have a far larger impact on household real income and poverty, as well as on the government budget, than reducing subsidies on other energy products. Presumably, the impact on productive sectors would also be large. Given the considerable price adjustments necessary to eliminate subsidies and the consequent impact on household welfare, a gradual approach to subsidy reform would be preferable, even if a cash compensation scheme is put in place. As in the case of food subsidies, we simulate two scenarios: a 30 percent cut in subsidies for each product and a 100 percent decrease (total elimination) of subsidies. Recall that a 30 percent 195 cut in subsidies would result in a different price increase for each product because prices vary across products. Table 5.21 reports for all energy products considered the initial subsidized price, the unit subsidy, the price following a 30 percent reduction in subsidy (final price, scenario 1) and the price after the elimination of all subsidies (final price, scenario 2). The last price is equivalent to the market reference price that we consider for each product. The elimination of subsidies (scenario 2) would lead to exceptionally large price increases. The price of kerosene would need to rise 12.1 times to match the market price; that of gas LPG would need to rise by a factor of 10.5; and those of gasoline, diesel, and electricity would need to rise by seven or eight times. Gasoline, the product with a price currently the “closest” to market price, would still undergo a price increase of 7.15 times to match the market price. These gaps are the largest observed between subsidized and market prices in North Africa and Middle East Region and represent a real challenge for reform. Table 5.21: Two Scenarios of Energy Subsidy Reform, LD per unit Initial price Subsidy Final price Final market Final price Energy (S1) price (S2) (S2)/initial product price Gasoline 0.15 0.92 0.47 1.07 7.15 Diesel 0.15 0.96 0.48 1.11 7.40 Electricity 0.02 0.14 0.06 0.16 7.80 LPG 2.00 18.94 8.28 20.94 10.47 Kerosene 0.09 1.00 0.42 1.089 12.10 Sources: Libyan authorities and World Bank staff. The direct cost of a complete elimination of subsidies to households is estimated at LD 2.5 billion (table 5. 22), equivalent to the total amount of direct subsidies received by households. This is a very large sum, representing almost 20 percent of total household expenditure. A 30 percent reduction in subsidies on each product would cost households LD 0.75 billion. These costs would be rather evenly distributed across quintiles with the exception of the first quintile, which would bear a much lower cost than the rest. The quintile that would bear the greatest cost is the third. In per capita terms, removing subsidies would cost more to the upper quintiles, as expected given the result that energy subsidies are regressive. Nonetheless, because energy 196 expenditure represents a higher share of total expenditure for the poor, the per capita loss of the lower quintiles represents a larger share of their total per capita spending (table 5.23), although the difference is not as stark as we found it to be in the case of food subsidy reforms. Table 5.22: Welfare Direct Effects, in LD millions Quintile Gasoline Diesel Electricity LPG Kerosene Total 1 (poorest) −53.2 −1.4 −61.0 −16.1 −0.9 −132.6 2 −64.4 −1.4 −69.4 −16.6 −1.5 −153.4 3 −66.5 −1.1 −69.8 −16.2 −1.7 −155.3 4 −66.7 −1.1 −67.5 −15.8 −2.0 −153.1 5 (richest) −61.9 −1.3 −73.1 −14.9 −2.1 −153.3 Total (scenario 1) −312.8 −6.4 −340.9 −79.6 −8.2 −747.7 Total (scenario 2) −1,042.6 −21.2 −1,136.2 −265.2 −27.4 −2,492.5 Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Table 5.23: Per Capita Welfare Direct Effects, as percentage of total welfare (scenario 1 and 2) Quintile Gasoline Diesel Electricity LPG Kerosene Total 1 (poorest) −2.89 −0.07 −3.31 −0.87 −0.05 −7.20 2 −2.82 −0.06 −3.03 −0.73 −0.07 −6.70 3 −2.58 −0.04 −2.71 −0.63 −0.07 −6.02 4 −2.43 −0.04 −2.46 −0.57 −0.07 −5.58 5 (richest) −2.01 −0.04 −2.37 −0.48 −0.07 −4.98 Total scenario 1 −2.50 −0.05 −2.72 −0.63 −0.07 −5.97 Total scenario 2 −8.32 −0.17 −9.06 −2.12 −0.22 −19.89 Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Eliminating all energy subsidies (scenario 2) would create direct savings of LD 2.5 billion to the government budget—the same amount as the total direct value of subsidies to households (table 5.24). This amount is equivalent to 3.83 percent of total government expenditure. The removal of gasoline subsidies alone could create direct savings of 1.6 percent of government expenditure, and the removal of subsidies on electricity about 1.75 percent (table 5.24). A 30 percent 197 reduction in subsidies on all products (scenario 1) would create LD 1.22 billion in direct savings to the government budget, which is more than one-third of the decline in spending under the 100 percent reduction scenario (scenario 2). As explained for the case of food subsidies, with a partial reduction in subsidies we have two sources of reduced government spending, the first resulting from higher subsidized prices and the second resulting from lower quantities consumed by households at these higher prices. If subsidies were totally eliminated, this second effect would disappear given that no quantities would be sold at a subsidized price. Table 5.24: Reduction in Government Expenditure, in LD Quintile Gasoline Diesel Electricity LPG Kerosene Total 1 (poorest) 84.3 2.2 101.4 27.9 1.6 217.4 2 102.0 2.3 115.3 28.8 2.8 251.2 3 105.4 1.7 116.0 28.1 3.0 254.2 4 105.6 1.8 112.2 27.3 3.6 250.5 5 (richest) 98.0 2.1 121.5 25.7 3.7 251.1 Total scenario 1 495.3 10.1 566.4 137.8 14.7 1,224.4 Total scenario 2 1,042.6 21.2 1,136.2 265.2 27.4 2,492.5 Percent of govt. 1.60 0.03 1.75 0.41 0.04 3.83 expenditure (scenario 2) Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Reforming gasoline and electricity prices would bring the greatest savings to the government budget. Figure 5.7 illustrates, for each energy product, the direct impact on government expenditure (measured on the y axis in LD) versus a percentage reduction in subsidy (x axis). The values that correspond to 30 percent and 100 percent reductions are the same as those reported under the two scenarios in table 5.24. For all products, government expenditures are a decreasing function of subsidy reduction. The marginal returns to reducing subsidies would diminish as prices get closer to market levels, because fewer and fewer quantities would be bought at subsidized prices given fixed household expenditure levels. Figure 5.7: Magnitude of Decline in Government Spending Following Reform Scenario 2, in LD 198 Gasoline Diesel 1.00e+09 Electricity LPG Kerosene Government savings 5.00e+08 0 0 20 40 60 80 100 Percentage decrease in subsidies Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Energy subsidy reform could have a substantial impact on poverty. A 30 percent reduction in subsidies, assuming unchanged consumption patterns, would increase poverty (measured by the national poverty line) by four percentage points, from 18.5 percent to 22.5 percent (table 5.25). The increase in poverty following a total elimination of subsidies would be significantly higher, at 17.7 percentage points, resulting in a postreform poverty rate higher than 36 percent. These projections are commensurate with the magnitude of price adjustments that would be needed under either reform scenario. The products that would explain most of the rise in poverty under the two scenarios are gasoline and electricity. The rise in poverty would also be accompanied under scenario 2 by a rise in inequality, estimated at 3.1 percentage points. These estimates are among the highest when compared with those for other countries in the Region such as Morocco, Tunisia, Egypt, or Jordan, in part because of the higher level of subsidies in Libya compared to these countries. 199 Table 5.25: Impact of Energy Subsidy Reform on Poverty (head count index) International poverty line National poverty line Scenario 1 Scenario 2 Scenario 1 Scenario 2 Poverty Poverty poverty poverty poverty poverty level level change change change change Prereform 8.475 n.a. .n.a. 14.44 n.a. n.a. Gasoline 9.306 0.83 4.01 16.16 1.72 6.77 Diesel 8.509 0.03 0.11 14.49 0.05 0.22 Electricity 9.687 1.21 5.25 15.97 1.53 6.47 LPG 8.674 0.20 0.84 14.83 0.39 1.49 Kerosene 8.502 0.03 0.06 14.47 0.03 0.06 Postreform 11.156 2.68 13.19 18.46 4.02 17.67 Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. A number of factors can help attenuate the negative impact of energy subsidy reform. A gradual and sequenced approach to energy subsidy reform, across products and across time, would help to make room for simultaneously working on improving public service delivery, so that households and productive sectors are able to gradually adjust to the new economic realities. Moreover, the poverty impact of energy subsidy reform discussed here is purely monetary and therefore does not take into consideration inevitable substitution patterns that would result when a reform is introduced. Such substitutions would be greatly facilitated if the reform were gradual and accompanied by complementary measures to provide other options for citizens in terms of services, for example, more efficient electricity production or the introduction of public transportation networks. The impact of subsidy reform could also be attenuated through cash transfers. A transfer of LD 243 per capita per year targeted to the first quintile would be sufficient to restore poverty to the prereform level of 8.5 percent under the scenario of full subsidy elimination and using the international poverty line of USD 1.25 per person per day (figure 5.8). This targeted transfer system would cost the government LD 471 million per year. Alternatively, because poverty would jump by almost 18 percentage points if all energy subsidies were eliminated, the government may decide to target the transfers to the first two quintiles. The per capita amount required to bring poverty back to 8.5 percent in this case would be LD 245, costing the government LD 845 million per year. Yet another possibility to restore poverty to the prereform 200 level would be a universal transfer of LD 243 per capita per year, costing the government LD 1.5 billion annually. Given that direct savings from the price increases would amount to LD 2.5 billion (table 5.24), the net gains to the budget from full subsidy elimination and cash compensation to the population in the first quintile of LD 243 per capita would be about LD 2 billion. If targeting the first quintile is not possible, extending a transfer of LD 243 per person per year to the entire population—sufficient to maintain poverty at 8.5 percent—would reduce the net gains to the budget from subsidy reform and cash transfers to about LD 1 billion per year. Figure 5.8: Poverty Impact of Cash Transfers to First Quintile under Energy Subsidy Reform S2 Initial level of poverty: 8.475 percent 20 Required transfer to maintain poverty at prereform leve: 242.995 LD per capita per year 15 10 5 0 0 200 400 600 Level of individual transfer (LD per capita per year) Source: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. 201 [[Typesetter: in chart area and legend, change red and blue lines to broken lines.]] Energy price increases would also be expected to reduce consumption (table 5.26).20 Based on our assumptions, a 30 percent reduction in energy subsidies would reduce the quantities of energy products consumed by 46 percent for electricity, 52.7 percent for kerosene, and 40 percent for gasoline and diesel. The estimated impact on quantities would also vary across quintiles. For kerosene, for example, the impact would be greater for richer households, but for other products such as diesel and LPG the impact would be the greatest for the second quintile. Table 5.26: Impact of Energy Subsidy Reform (Scenario 1) on Quantities Consumed Gasoline Diesel Electricity LPG bottle Kerosene Quintile (liter) (liter) (kWh) (15 kg) (liter) 1 (poorest) −48.1 −1.2 −424.4 −0.9 −1.0 2 −58.3 −1.3 −482.4 −0.9 −1.7 3 −60.2 −1.0 −485.3 −0.9 −1.9 4 −60.3 −1.0 −469.4 −0.9 −2.3 5 (richest) −56.0 −1.2 −508.1 −0.8 −2.3 Total (scenario 1) −282.8 −5.6 −2,369.5 −4.4 −9.3 Total (scenario 2) −454.2 −9.0 −3,843.2 −6.6 −14.4 Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. <>The Political Economy of Reforms Attempts at subsidy reform were made during the decade that preceded the revolution, but they did not last. In the early 2000s, following the removal of international sanctions, Libya embarked on a reform path to modernize and open up its economy (Vandewalle 2011), and cutting subsidies seems to have been an important part of that program (Wahby 2005). Despite widespread opposition among the population, the government proceeded with the reform, raising fuel, diesel, and electricity prices in 2005 and completely liberalizing the price of some food products. By 2006 only four food products were still subsidized: flour, rice, semolina, and pasta. 202 In 2007 the government also eliminated the subsidy on pasta, and to compensate tried to put in place a transfer system of 4 dinars per capita, per month. The government, however, was unable to dispense this cash transfer. Still, subsidies remained restricted to flour, rice, and semolina until early 2011 when Gaddafi, in an attempt to quell the revolutionaries’ demands, extended food subsidies back again to 12 items. The political economy of the Gaddafi period was entirely driven by the leader's decisions, and these decisions served budget interests or short-term political objectives. The post-Gaddafi period has been characterized by internal conflicts among various factions that participated in the revolution and by a very volatile political environment, making reforms difficult to implement and the possibility of a public debate on subsidy reforms almost impossible. High oil and gas prices that characterized the period between the revolution in 2011 and the first half of 2014 helped to boost government revenues, but the internal conflict over natural resources limited the possibility to exploit oil reserves to their full potential. The most recent slump in the price of crude oil, which began in June 2014, and the continued internal instability are contributing to increase the pressure on government finances while keeping subsidy reforms difficult to implement from a political perspective. Libya therefore remains the most extreme of the cases in the MENA Region in terms of the size and variety of subsidies, in terms of weight of subsidies on the government budget, and in terms of lack of reforms, and it will be very unlikely to see a reform of the subsidies system anytime soon. Despite this very complex environment, reforming subsidies remains an important question for the Libyan government. In February 2013 the Ministry of Economy conducted a survey of a sample of 931 adult citizens aged 18 to 95 living in 25 cities. The University of Tripoli analyzed results and found that about 70 percent of the respondents were in favor of a policy that would eliminate subsidies and replace them with cash transfers, although only 28 percent thought that compensation via cash subsidies should be targeted to the poor only. Libyans believed that they are entitled to subsidies as a means to distribute national wealth to most citizens, but they would trade low subsidized prices for a cash benefit. The government announced several times the intention to reform subsidies. In April 2014 it made public the intention to introduce smart cards for the purchase of fuels and stated the intention to eliminate subsidies within three years. In July 2014 it committed to substitute goods 203 and fuel subsidies for cash subsidies by January 2015. According to the Libya Herald it was the first time in Libya’s history that such a move was promised, and this in spite of the political instability(Zaptia 2013). Yet, at the time of this writing, no substantial reform had been implemented, and political instability was deteriorating further. <>Summary and Recommendations This chapter provided a food and energy subsidy incidence analysis as well as an impact analysis for two alternative reform scenarios for Libya. The results provide information for each subsidized good in terms of the subsidy’s impact on household welfare and on poverty. This section briefly reviews the key findings and discusses the main issues that would still need to be addressed for a more comprehensive picture of subsidy incidence and reform analysis. Food subsidies save households some 10 percent of annual expenditure and eliminating them would have a significant effect on poverty. Table 5.27 summarizes the results of the food subsidy analysis. Household expenditure loss would reach 3.1 percent under scenario 1 and 10.2 percent under scenario 2. The incidence of subsidies would drop from 10.2 percent in the prereform scenario to 7.4 percent under scenario 1 and zero under scenario 2. Subsidy reform would reduce government spending by about 1 percent under scenario 1 and 2 percent under scenario 2 (but additional savings from lower administrative costs and less waste/smuggling would also materialize). The poverty impact would be particularly stark: depending on the poverty line used, poverty would rise from 8.5 percent (or 14.4 percent) to 10.5 percent (or 17.3 percent) under scenario 1 and to 16.6 percent (or 24 percent) under scenario 2. Inequality would also rise. Table 5.27: Summary of Aggregate Results for Cuts in Subsidies Scenario 1 (30% Scenario 2 reduction in (elimination Prereform subsidies) of subsidies) Total real household expenditure (LD bn) 12.53 12.15 11.25 Household expenditure loss in real terms (% of prereform) n.a. −3.1% −10.2% Total subsidies(LD bn) 1.28 0.9 0 Incidence of subsidies (% of total expenditure) 10.2% 7.4% 0 Change in govt. spending following reform (LD bn)a n.a. −0.66 −1.28 Savings to the govt. following reform (% of govt. expenditure)a n.a. 1.0% 2.0% 204 Poverty head count (%, international poverty line) 8.5% 10.5% 16.6% Poverty head count (%, national poverty line) 14.4% 17.3% 24.0% Inequality (%, Gini) 30.2% 31.0% 33.2% Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Note: a. Estimates exclude savings from reduced waste, smuggling, and administrative costs. bn = billions. Although food subsidies are relatively progressive, a significant share, about 35 percent of government spending on these subsidies, is wasted, which would support a move to replace them with cash transfers. This chapter's analysis can provide guidance for the size of cash transfers that would compensate for food subsidy reform. One can look for guidance in the estimates of the per capita monetary value of subsidies received by the various quintiles of the population (table 5.28). For example, under a scenario of full subsidy elimination, maintaining the poverty rate constant at 8.5 percent is feasible if a per capita transfer of LD 175 per year is allocated to the population in the first quintile. If the objective is rather to compensate the population falling in the first quintile for the totality of their loss, the transfer could be LD 180 per capita, again granted only to the population in that group. And if the objective is to compensate the average member of the population (a way to address in part the needs of the middle class in a compensation scheme), cash transfers could amount to, for example, 201 LD per year, per person, which is the average monetary value that a Libyan person derives from food subsidies today. Table 5.28: Per Capita Monetary Value of Food Subsidies, in LD/capita/year Q1 Q2 Q3 Q4 Q5 Total Flour 13.0 13.9 14.5 15.2 14.5 14.0 Flour-bread 46.1 54.7 56.8 60.3 71.3 55.1 Semolina 2.1 2.3 2.1 1.9 1.5 2.1 Rice 21.8 24.7 26.2 26.7 27.1 24.7 Sugar 15.1 16.7 16.9 17.5 17.0 16.4 Tea 4.2 4.8 4.8 4.7 4.5 4.6 Macaroni 16.7 17.8 17.9 18.0 18.0 17.5 Vegetable oil 36.5 39.2 40.3 40.5 40.7 39.0 Paste tomatoes 13.5 14.6 14.8 14.8 14.8 14.3 Milk for children 1.5 2.8 4.1 6.2 8.5 3.8 205 Milk (concentrated) 9.1 10.5 10.4 9.7 9.6 9.8 Total 179.7 202.1 208.8 215.5 227.5 201.4 Sources: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Note: Q = quintile, with 1 being the poorest, and 5, the richest. The above examples dealt with eliminating all subsidies in one step but, alternatively, another possibility may be to sequence the reform over products and over time. Price liberalization could start with items, such as semolina, that are likely to have a small impact on households and move onto bigger ticket items over time.21 This approach may be easily followed in Libya because it was implemented in the past between 2007 and 2010 with only three food items subsidized, flour, rice, and semolina. Yet another possibility, given the generous caloric content of the quotas, could be to start reducing the quantities of all food items under the quota system gradually before eliminating subsidies altogether at a later point in time.22 Energy subsidies save households about 26 percent of annual expenditure, and their elimination would also significantly impact poverty. Table 5.29 summarizes the aggregate results for an analysis of energy subsidies. Household expenditure loss would reach 6 percent under scenario 1 and 19.9 percent under scenario 2. These amounts are larger than those for food subsidies, given the larger subsidized component underpinning energy prices in Libya today, compared to that in food prices. Subsidy reform would reduce government spending by about 1.9 percent under scenario 1 and 3.9 percent under scenario 2. The impact would, however, be only a partial impact on the government budget because factors such as indirect effects and effects on productive sectors are not incorporated in the analysis, nor are other factors such as smuggling. The impact on poverty would be high with a rise in poverty from 8.5 percent under the international poverty line (or 14.4 percent under the national line) to 11.2 percent (or 18.2 percent) under scenario 1 and to 21.7 percent (or 30.4 percent) under scenario 2. This rise in poverty would also be accompanied by a rise in inequality of 3.2 percentage points. 206 Table 5.29: Summary of Aggregate Results for the Case of Energy Subsidies Pre−reform Scenario 1 Scenario 2 (30 % reduction (Elimination of in subsidies) subsidies) Total real household expenditure (LD bn) 12.53 11.79 9.29 Household expenditure loss in real terms (% of prereform) n.a. −6% −19.9% Total subsidies (LD bn) 2.49 1.74 0 Incidence of subsidies (% of total expenditure) 19.9% 14.8% 0 Change in govt. spending after reform (LD bn) n.a. −1.22 −2.49 Savings to the govt. after reform (% of govt. expenditure ) a n.a. 1.9% 3.9% Poverty head count (%, internat'l poverty line) 8.5% 11.2% 21.7% Poverty head count (%, nat'l poverty line) 14.4% 18.2% 30.4% Inequality (% Gini) 30.2% 30.8% 33.4% Sourcea: Libyan Household Consumption Survey 2007–08; Libyan authorities; and World Bank staff calculations. Note: a. Estimates exclude savings from reduced waste, smuggling, and administrative costs. bn = billion. Clearly, energy subsidy reform would have a huge impact on the Libyan economy, which calls for gradualism. Full liberalization would imply price increases of between 7 and 10 times the existing prices, in a context where alternatives (such as more efficient production processes for electricity or public means of transportation) are not available. It would therefore seem imperative that energy subsidy reform be planned in stages, with a product-by-product approach, gradually liberalizing them over a number of years, and along with significant improvements in service delivery in related areas (electricity, transport, and so forth.). This approach would help improving efficiency and contributing to lower energy consumption. For the electricity sector in particular, it would be important to first improve performance at all levels of production and distribution while tariffs are slowly increased. Although more analysis is needed to develop a suitable subsidy reform plan, this chapter suggests a number of broad recommendations. The complete elimination of all subsidies in one stroke with no compensation to households could result in a sharp increase in poverty and could affect the middle class severely and lead to social unrest.23 A radical approach to subsidy reforms in Libya during this particular historical period is not advisable. 207 A less drastic approach would be to reduce subsidies in sequential steps over an extended period of time. Morocco and Tunisia have followed this approach, achieving significant budget savings without social unrest. It is also advisable to implement reforms one product at a time starting with the products that affect the poor the least. Other considerations may be important as well, for example, the importance of not delaying reforms where substantial waste is clearly established. Other things being equal, this approach would suggest starting with petroleum products rather than food products and with gasoline rather than LPG. This chapter provides information that helps making choices on priority products based on the importance of each product for different groups of households. The elimination or reduction of subsidies would also call for targeted cash transfers. Compensation could be provided to the bottom 20 percent or 40 percent of households in the form of coupons or cash transfers. Such reforms could result in significant budget savings and no increases in poverty. The difficulty of this approach resides in the better targeting of households, and specific systems would need to be in place to ensure that such targeting is operationally feasible. If the country does not develop such effective systems, targeted subsidies may result in substantial waste of resources. A universal transfer is a second best option, but would still reduce the burden on government expenditure. This chapter provided only part of the information required to put in place subsidy reform. Much more work and preparation will be needed to prepare a feasible reform agenda. In particular, a few areas stand out for further work. First, it will be important to assess, in the context of the existing formal and informal support mechanisms in Libya, whether a new cash transfer system is really needed to compensate for subsidy reform and for what product. Second, if a transfer is needed, the next question is how best to introduce it in the context of existing social safety nets and/or what reforms to these safety nets are needed to support subsidy reforms. Also, actual mechanisms to disburse the transfers might need to be created and may be costly. Third, a strategy for phasing out the transfers may also be needed, particularly if targeting cannot be achieved. Fourth, broad consultation needs to be conducted with all sectors affected by the reform to address any negative impacts. Beyond the impact on households, energy subsidy reforms will probably have significant impact on producers, and such impact will need to be assessed and factored in the reform. Fifth, a communication strategy in Libya would seem to be 208 even more important than in other countries given the size and sensitivity of subsidies and the current political fragility. These aspects are all beyond the scope of this study but need to be tackled in preparing for subsidy reforms. <>Notes The authors thank the Libyan authorities for the information, comments, and advice provided throughout the study. In particular, we thank the staff at the Ministry of Economy, Ministry of Finance, Ministry of Planning, and the Central Bank who provided excellent support during the various missions to Tripoli. The World Bank country and regional teams provided essential logistical support and various World Bank staff contributed with comments and advice. They are Marouane El Abassi, Bernard Funck, Khalid El-Massnaoui, Fanny Missfeldt-Ringius, Maria Vagliasindi, and Heba Elgazzar. Any errors are the sole responsibility of the authors. 1. The quantities provided within the quota system are not negligible. For example, a family of four is entitled to the following quotas at subsidized prices each month: 8 kilograms (kg) of sugar, 800 grams (gr.) of tea, 4 kg of tomato paste, 6 liters of vegetable oil, 10 kg of rice, 12 kg of flour, 4 kg of semolina, and 6 kg of pasta. These quantities are well above the total amount of calories necessary for a family of four for one month. 2. Preliminary data on government spending in 2012 indicated that food, electricity, and other energy subsidies cost, respectively LD 2.1 billion, 1.1 billion, and 6.3 billion to the budget. 3. Direct effects represent the impact of subsidies via subsidized products consumed by households. Indirect effects represent the impact of subsidies via nonsubsidized products consumed by households that use subsidized products as a production input. 4. Anecdotal evidence suggests that because not all households actually take advantage of the quota system for their food purchases, some of the surplus subsidized food ends up being used as cattle feed or input to the production of sweets in bakeries for the case of sugar and flour. No data are available to quantify these observations, and if animal raising and bakeries are household activities, these effects would be captured in the direct effects estimations. A share of subsidized food products is reportedly smuggled and sold illegally in supermarkets, thereby 209 depressing market prices. Some effect from removing subsidies on these products may filter through to market prices, but that effect is likely to be small. 5. We note here that this paper’s analysis does not capture the administrative costs of subsidies, which may be large given the system of quotas administered through cooperatives. 6. Although no data are available, hydrocarbons are believed to constitute about two-thirds of GDP in Libya, suggesting that estimated aggregate expenditure could be about 35 percent of nonoil GDP. 7. See http://data.worldbank.org/indicator/NE.CON.PETC.ZS. 8. We make that assumption when the survey provides no separate expenditure data for subsidized versus nonsubsidized quantities for a given product. 9. Household sizes are different across quintiles, with poorer households also being the largest. It is therefore useful to also look at per capita estimates in addition to per household estimates to assess whether or not food subsidies are progressive. 10. Market prices were obtained from the Ministry of Economy dated for the first quarter of 2013. 11. Note that these are upper bound estimates based on Laspeyers estimations. 12. Estimates of the budgetary impact of alternative reform scenarios do not take into account savings from lower administrative costs of managing the subsidy program and from leakages of the subsidy program (e.g., smuggling). 13. We convert $1.25 to Libyan dinars using the 2009 purchasing power parity (PPP) exchange rate data (1 LD = $0.74-PPP, latest available data) and inflation for the period 2009–13. We find the equivalent universal poverty line for 2013 to be LD 821.42 per person, per year, which is lower than the national poverty line of LD 966.3 per person, per year leading to lower poverty rates. 14. To estimate the national poverty line, we use the 2003 poverty line—which was estimated at LD 593.6 by staff of Libya’s Office of Statistics but not endorsed officially—and CPI inflation 210 between 2003 and 2013. This national poverty line estimate corresponds to LD 2.65 per day, or about $2 at the actual exchange rate. The national poverty line estimate represents 49 percent of the average per capita expenditure of households (LD 1,967). 15. These results are entirely dependent on the choice we made regarding the point elasticity at market price and the shape of the demand curve. Other assumptions would lead to different results, and these findings should be taken with caution. Note, however, that the final results on household welfare are not affected by the choice of elasticity and demand curve as these estimates depend only on the initial expenditure and the price change (relative changes in quantities consumed of subsidized and nonsubsidized products do not affect the overall welfare effects given that we consider a hard budget constraint). 16. The budget data do not include administrative costs associated with the subsidy system. 17. Anecdotal evidence suggests that the stock of cars in Libya is quite old. Many low-income people drive run-down cars and keep doing so because of cheap gasoline and the lack of alternative transportation means. 18. The authorities had budgeted for 4.47 billion liters of gasoline to be sold on the market in Libya in 2013. 19. See http://data.worldbank.org. The data were converted from kilograms to liters on the basis that 1 liter of petrol weighs 0.711 kg. 20. These results are entirely dependent on the choice we made regarding the point elasticity at market price and the shape of the demand curve. Underlying our analysis are demand curves that depict the same elasticity for all households but differ in elasticity across products, with the difference depending on the gap between market price and subsidized price. For energy products, we assumed a point elasticity of −0.5 at the free market price. This estimate and a linear demand curve function are then used to estimate the point elasticity at the subsidized price. 21. A caveat to our analysis is that it does not take into consideration the nutritional consequences of food subsidy reform. Such an analysis may be needed before arriving at a view on how small the impact is on households particularly if the reform is not accompanied by cash transfers. 211 22. The current basket of subsidized products provides more than twice the amount of adult calories intake as recommended by WHO or the FAO. If we consider that children make up the majority of household members in poor households of six to seven people, the amount of calories allocated within the quota system may be between two and three times the calories needed. This finding would justify a reduction in quotas based on the level of individual calorific needs. Quotas could be cut by half, for example, which would be equivalent to reducing food subsidies by half, saving more than 1 percent of government spending. 23. This chapter's analysis does not take into account new transfers enacted by the government in 2013 (such as transfers to heads of households and transfers for minors). A complete picture of the impact of subsidy reform on poverty and the middle class will require including these in the assessment. <>References Alleyne, T., 2013. Energy Subsidy Reform in Sub-Saharan Africa: Experiences and Lessons. Washington, DC: International Monetary Fund. Araar, A., and P. Verme. 2012. "Reforming Subsidies: A Toolkit for Policy Simulations." Policy Research Working Paper 6148, World Bank, Washington, DC. Bacon, R., and M. Kojima. 2006. "Phasing Out Subsidies—Recent Experiences with Fuel in Developing Countries." Public Policy Notes 310, World Bank, Washington, DC. Chami, R., 2012. Libya beyond the Revolution: Challenges and Opportunities. International Monetary Fund. http://www.imf.org/external/pubs/ft/dp/2012/1201mcd.pdf. Charap, J. 2013. “Note on Subsidy Reform in Libya.” IMF Country Report No. 13/151, International Monetary Fund, Washington, DC.. Clements, B. 2013. Energy Subsidy Reform: Lessons and Implications. Washington, DC: International Monetary Fund. ———. 2013. Case Studies on Energy Subsidy Reform: Lessons and Implications. Washington, DC: International Monetary Fund. FAO (Food and Agriculture Organization). 2003. "Food Energy: Methods of Analysis and Conversion Factors." Food and Nutrition Paper 77, ftp://ftp.fao.org/docrep/fao/006/y5022e/y5022e00.pdf. 212 Guillaume, D. 2011. "Iran—The Chronicles of the Subsidy Reform." IMF Working Paper 11/167, International Monetary Fund, Washington, DC. IMF (International Monetary Fund). 2013. "Libya: Selected Issue." IMF Country Report. 13/151, International Monetary Fund, Washington, DC. Vagliasindi, M. 2012. "Implementing Energy Subsidy Reforms: An Overview of the Key Issues." Policy Research Working Paper 6122, World Bank, Washington, DC. ———. 2013. Implementing Energy Subsidy Reforms: Evidence from Developing Countries. Directions in Development. Washington, DC: World Bank. Vandewalle, D. 2011. "Libya: Post-War Challenges." African Development Bank Economic Brief, September. http://www.afdb.org/fileadmin/uploads/afdb/Documents/Publications/Brocure%20Anglai s%20Lybie_North%20Africa%20Quaterly%20Analytical.pdf. Verme, P., K. el-Massnaoui, and A. Araar. 2014. “Reforming Subsidies in Morocco.” Economic Premise 134: 1–5. World Bank PREM Network. Wahby, E. 2005. "Libya: Economic Reforms Anger Citizens." Carnegie Endowment, June 20. http://carnegieendowment.org/files/Wahby.pdf. Waniss, O., and E. Karlberg. 2007. The Libyan Economy: Economic Diversification and International Repositioning. Berlin, London: Springer. World Bank. 2010. "Subsidies in the Energy Sector: An Overview." Background Paper for the World Bank Group Energy Sector Strategy. World Bank, Washington, DC. Zaptia, S. 2013. "The IMF and the Vexing Issue of Reforming Subsidies: Ramifications for Libya,. Libya Herald, Tripoli http://www.libyaherald.com/2013/04/17/the-imf-and-the- vexing-issue-of-reforming-subsidies-ramifications-for-libya/. 213 <>Chapter 6 <>Energy Subsidies and the Path Toward Sustainable Reform in the Arab Republic of Egypt Sudeshna Ghosh Banerjee, Heba El-laithy, Peter Griffin, Kieran Clarke, and Mohab Hallouda <>Introduction Energy subsidies have existed in developing countries for a long while. Traditionally, subsidies were put in place to enhance access to modern energy services, protect the poor against high and fluctuating energy prices, foster industrial development, smooth consumption levels, and contain inflationary pressures. In spite of these intentions, energy subsidies have not fulfilled their purpose in many ways. International experience suggests that such subsidies come with significant economic, social, and environmental costs in the form of a high fiscal burden on government budgets, inequity in subsidy delivery to different income groups, and making fossil fuels more attractive compared to other lower carbon options (Fattuah and El-Katiri 2012). In the Arab Republic of Egypt subsidies, primarily in food items, have been prevalent for many years. Since the British withdrawal in 1956, subsidies were imposed on a large group of items— food, transport, housing, energy, health care, soap, and cigarettes—to create a system of social assistance in the absence of an administrative machinery to transfer wealth. Attempts to reduce or remove the system are politically sensitive and have often met with widespread resistance, for example, the 1977 riots in Egyptian streets following President Anwar Sadat’s decision to cut food subsidies (Rohac 2013). Along with food, energy subsidies have been the mainstay in Egypt’s budget for decades. Following a downward turn in economic performance following the January 2011 revolution, energy subsidies have emerged as a prominent fiscal burden as the country undergoes a historic sociopolitical transition. This chapter presents the evolution of prices and subsidies in the historical context, provides a glimpse of stakeholder views regarding subsidy reforms, and analyzes the direct and indirect impacts of subsidy reforms on one of the most important stakeholders—the households. The analysis presented here draws from work carried out under technical advisory services provided 214 to Egypt’s Ministry of Petroleum in 2013–14 (prior to the comprehensive subsidy reforms announced in July 2014) on two intertwined components: direct and indirect impacts of subsidy reform scenarios and communications strategy to support subsidy reforms. A multisectoral team from the World Bank, supported by consultants, carried out this task. The World Bank- developed software SUBSIM (subsidy simulation) was used to analyze the scenarios of impact of subsidy reforms on households. <>Scale of Subsidies Egypt’s fuel basket contains six items—liquid petroleum gas (LPG), gasoline, diesel, heavy fuel oil (HFO), kerosene, and natural gas. Among them, consumption of natural gas is the highest and has reported the maximum increase between 2002 and 2013 more than four times (figure 6.1). Natural gas is followed by diesel and fuel oil in consumption. Figure 6.1: Consumption of Fuels 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 LPG Gasoline Kerosene Diesel Fuel Oil Natural Gas Source: Ministry of Petroleum 2014. [[Typesetter: in figure 6.1 Y-axis: Remove the percent signs and add "Percent"; Remove the ticks from the bottom of the chart, as the dates align with the bars. Chart area and legend: Use shades of gray or patterns instead of colors; Legend: Use sentence style: change "Fuel Oil" to "Fuel oil"; change "Natural Gas" to "Natural gas"; Background: remove the box.]] 215 Since 1990 the retail price of fuels has been raised incrementally, particularly after 2003. In real terms, with nominal prices deflated by the annual gross domestic product (GDP) deflator, (WDI 2014) prices generally show a declining trend except for fuel oil. In 2012 a whole slew of price measures were implemented, particularly in a group of energy-intensive industries and fuel for electricity generation. Even LPG prices that had remained frozen for 21 years experienced a substantial increase from 4 Egyptian pounds (LE) per cylinder to LE 8 per cylinder in 2013 (figure 6.2). Figure 6.2: Nominal and Real Changes in Energy Prices, 1990–2014 a. Nominal b. Real 3000 3500 3000 2500 2500 2000 2000 LE/Toe LE/toe 1500 1500 1000 1000 500 500 0 0 1996 1990 1992 1994 1998 2000 2002 2004 2006 2008 2010 2012 2014 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Natural Gas LPG Fuel Oil Diesel Natural Gas LPG Gasoline 92 Gasoline 90 Fuel Oil Diesel Gasoline 80 Gasoline 92 Gasoline 90 Source: Ministry of Petroleum 2014. Note: LE = Egyptian pound; TOE = Tonne of oil equivalent. [[Typesetter: in figure 6.2, panels a and b: Chart area and legend: Use broken lines instead of colors; Legend: Use sentence style; X-axis: Turn years on a slant; align with tick marks; Y-axis: Add commas to 4-digit numbers. Background: remove the box.]] On July 5, 2014, the government of Egypt (GoE) took a significant step forward and announced price changes in many categories of fuels and electricity (tables 6.1 and 6.2). Except for LPG, the 216 prices of all fuels increased. The GoE estimated subsidy savings of LE 51 billion of which LE 27 billion will be allocated to health, education, and social protection programs. Around the same time, the GoE announced its intention to phase out subsidies over the next five years. The GoE projected a price path for electricity for annual changes until a minimal cross-subsidy (primarily for households) begins in 2019. Table 6.1: Fuel Prices in July 5, 2014, Subsidy Reforms New Product Unit Sector Old price price Iron, copper, aluminum, glass, ceramics 4 7.00 Fertilizer, petrochemicals 4 4.50 $/mmBtu Cement 6 8.00 Brick, engineering, chemicals, food, medicines, fabric 4 5.00 Electricity, BOOT 1.1 3.00 Natural gas Cars 0.45 1.10 Residential 1 0.4 0.40 LE/M3 Residential 2 1 1.00 Residential 3 1.5 1.50 Bakeries 0.14 0.14 80 0.9 1.60 Gasoline LE/L 92 1.85 2.60 95 5.75 6.25 Food industry 1,000 1,400 Cement 1,600 2,250 Fuel oil LE/Ton Electricity 2,300 2,300 Others 1,500 1,950 All sectors 1.1 1.80 Diesel LE/L 66 percent of tourism sector 1.1 1.80 Residential 8 8 LPG LE/C Commercial 16 16 Source: Ministry of Petroleum 2014. Note: BOOT = Build, Own, Operate, Transfer; C = cylinder; L = liter; LE = Egyptian pound; M3 = cubic meter; mmBtu = 1 million British thermal units. 217 Table 6. 2: Electricity Prices in July 5, 2014, Subsidy Reforms Residential (PT/kWh) Old price Proposed price up to 50 5 7.5 51–100 12 14.5 0–200 – 16 201–350 19 24 351–650 29 34 651–1,000 53 60 above 1,000 67 74 Commercial (PT/kWh) Old price Proposed price 0–100 27 30 0–250 41 44 251–600 53 59 601–1,000 67 78 above 1,000 72 83 Sources: Ministry of Electricity and New and Renewable Energy. Note: kWh = kilowatt hour; PT = piastre. This journey toward price rationalization stems from the ballooning fuel subsidies since 2002, growing at a compound annual growth rate of 26 percent between 2002 and 2013. Their share in the government budget increased from 9 percent in 2002 to 22 percent in 2013, and their share in Egypt’s GDP increased from 3 percent to 7 percent in the same period (figure 6.5). Among the fuel products, diesel subsidies in particular increased dramatically over this period, while the share of LPG and natural gas declined. Fuel subsidies remained a substantial component of the government budget in fiscal 2013/14. Diesel, LPG, and gasoline account for close to four-fifths of fuel subsidies, but represent only a third of the overall fuel consumption. Figure 6.3: Evolution of Fuel Subsidies, in LE billion 218 140000 120000 100000 80000 Billion LE 60000 40000 20000 0 -20000 Axis Title LPG Gasoline Kerosene Diesel Fuel Oil NG Source: Ministry of Petroleum 2014. [[Typesetter: in figure 6.3 Remove the words "Axis Title" from chart area; Chart area and legend: Use shades of gray or patterns instead of colors; X-axis: Delete tick marks; Add commas to 4-digit numbers; Change hyphen in 20,000 to a minus sign; Legend: change "Fuel Oil" to "Fuel oil"; "NG" to "Natural gas"; Background: remove the box.]] Following the July 5 reforms, the average cost recovery rose from 30 percent to 36 percent. Among the fuels, the cost recovery performance of LPG is the worst, standing at 7 percent (figure 6.4, panel a). The mismatch between the cost of LPG and the domestic retail price has been widening. A little more than half of LPG is imported, and the international prices have risen over time. The weighted average cost of LPG, including both the domestic and international quantities, was $756/ton in 2013. The retail price had been frozen at LE 2.5 per cylinder for almost two decades since 1991, but going up in 2013 to LE 8 per cylinder. This change is equivalent to a tripling of the sale price from LE 200 per ton to LE 640 per ton, which is equal to $91 per ton. At the other end is natural gas, where the cost recovery performance is the highest at 85 percent, and it makes up a little more than half of total fuel consumption in Egypt. Figure 6.4: Fuel Subsidies, fiscal 2014 a. Cost recovery performance b. Quantity of fuel use 219 250000 200000 15% 150000 100000 18% 52% 50000 9% 6% 0 Cost Revenue NG LPG Gasoline Diesel Fuel Oil Source: Ministry of Petroleum 2014. [[Typesetter: In figure 6.4, panel a: Bars and legend: use two shades of gray; Y-axis: Add label "LE million"; add commas to 4 or more digit numbers X-axis: Change "NG" to "Natural gas"; In panel b: Use shades of gray; In panels a and b: change "Fuel Oil" to Fuel oil"; Background: delete boxes; delete graph lines from chart a; in b legend, remove the left most box (blue).]] Fuel subsidies, comprising 7 percent of GDP in estimates undertaken in fiscal 2013/14, were greater than the government’s combined estimated expenditures in health and education in the same period, which constituted 5 percent of GDP (figure 6.5). Fuel subsidies also dwarf other elements of Egypt’s social safety net (SSN) system in the budget, which also includes direct cash transfers to the poor; social care services for the disabled, orphaned, and vulnerable persons; skill building and employment services, as well as self-employment training and microlending. In estimates undertaken in fiscal 2013/14, food subsidies corresponded to about 2 percent of GDP, food ration cards reached about 0.5 percent of GDP, and cash transfers to the poor amounted to 0.17 percent of GDP. This allocation between food and fuel subsidies and transfer programs is consistent with trends observed in the Middle East and North Africa Region, but unlike what is practiced in a comparable group of developing countries. These countries' spending on overall 220 SSN, including subsidies, is much lower (around 2 percent of GDP) and is more evenly divided between subsidies and transfer programs (Silva, Levin, and Morgandi 2012). Figure 6.5: Fuel Subsidies, Percentage of GDP, and Percentage of Budget a. Evolution of fuel subsidies b. Budget items 30% 25% 20% % of Budget 15% 10% 5% % of GDP 0% 0 5 10 15 20 25 As % of Total Budget As % of GDP Health Education Fuel subsidies Source: Ministry of Finance, Ministry of Petroleum 2014. [[Typesetter: in figure 6.5: In panel a, remove percent sign (%) from y-axis and label the axis "Percent"; X-axis, change the dates to read, for example: "2001–02". Delete the ticks with no dates; Panel a: change lines and legend to broken lines.\; Panel a legend: use lower case for "total budget"; Panel b, use shades of gray for bars; lower case for "budget".]] Background: remove the boxes.]] The highest volume of subsidies goes to the most energy-intensive sectors. Among them, electricity generation and transportations sectors receive the maximum amount of subsidies, with each receiving around 20 percent of the total energy subsidies in estimates undertaken in fiscal 2013/14 (figure 6.6). Depending on the sector, energy subsidies apply to different energy products. The electricity sector’s subsidies mainly originate from natural gas and fuel oil use, and transportation sector subsidies are from the consumption of subsidized diesel and gasoline.1 Households received about 17 percent of the subsidies directly in the same period, mainly from LPG and to a lesser extent from the consumption of electricity and natural gas. For other sectors, subsidies to diesel are the main sources of energy subsidies, with manufacturing also receiving fuel oil subsidies. Service sectors also received small natural gas subsidies. 221 Figure 6.6: Distribution of Energy Subsidies by Sectors and Energy Products Percent of total energy subsidies Electricity Refining Transportation Tourism Agriculture High Energy Manufacturing Construction Food, beverages and Tobacco Glass, Tiles, and Cement Other Services Other Manufacturing Water and sewage Mining Households Crude petroleum Natural gas LPG Gasoline Diesel Fuel oil Electricity Source: World Bank 2014. [[Typesetter: for figure 6.6: Move row of percent values to the bottom of the chart to create an x-axis, with the label "Percent of total energy subsidies"; change the hyphen in "-3%" to minus sign; Remove the percent signs (%); Use sentence style and serial comma for the products; Chart and legend: 7 values are needed. Shades of gray? Legend: move to the right of the chart and create a list. Background: remove the box.]] <>How Do the Key Stakeholders Perceive Subsidy Reforms? Since the Egyptian revolution in early 2011, various ministers and prime ministers in different governments have discussed the issue of energy pricing and the need for subsidy reform, and they have put forward a number of tentative policy plans. Before the July 2014 announcement of subsidy reform, numerous statements were made emphasizing that current subsidy arrangements are wasteful and a "bad deal" for the poor. These statements have, in turn, started a public discussion on the issue of subsidy reform in traditional media and online. Comprehensive stakeholder analysis was undertaken as part of the advisory services component on communications strategy to understand the knowledge, attitudes, and concerns of Egyptians regarding energy subsidies and the process of subsidy reform, as well as the self-perceived impacts of this process on key stakeholders. Tools employed for this analysis include a large- 222 scale household survey of more than 2,000 households to examine their energy use, knowledge of energy subsidies, attitude toward reform, perceived impacts of reform, and level of information on consumption patterns. The researchers broke down the results by income, age, education, and region. They analyzed focus group discussions on attitudes to and impacts of energy subsidy reform with small transport operators, small agricultural producers, the "youth," and a variety of small- and medium-size enterprises (SMEs), including energy-intensive SMEs. The researchers also conducted structured interviews with policy makers, business leaders, and industry representatives to assess the attitude to and appetite for energy subsidy reform in key sectors and among sectoral leaders. Stakeholder mapping assessed the importance of various stakeholders in Egyptian public life to the debate on energy subsidy reform according to likely power, interest, and influence in this process. Two-thirds of Egyptians believe energy prices are high (figure 6.7). In people disaggregated by age and income, this perception is apparent in about 75 percent of people under age 30, and in about 75 percent of lowest-income group people (earning less than LE 500 per month). Sixty- eight percent of households did not know the extent of subsidy expenditure by the government when presented with options as to the relative size of current subsidies. Only around 20 percent of respondents estimated correctly or overestimated. Knowledge of the size of subsidy expenditure was correlated with education and income: only 29 percent of households in the richest income bracket said they did not know the scale of subsidies, compared to 81 percent of the poorest households. The survey did not disaggregate by age or region on this question. 223 Figure 6.7: Household Perception on Energy Prices and Subsidies (% of sample) a. Perception of energy prices b. Perception of existence of subsidies 68 66 32 11 5 6 7 3 3 government budget 5-14% of budget 15-24% of budget 25-34% of budget 35%+ Don't know Less than 5% of High About right Low Source: World Bank 2014. [[Typesetter: In figure 6.7, panel a and b, change colors to shades of gray; Panel b,y-axis, make the terms right reading and set on a slant; change "government" to "govt."; change hyphen between numbers to en dash. Background: remove the box.]] When respondents were informed of the size of energy subsidy expenditure, however, close to 75 percent said that subsidies were not a good use of public money, with richer, older, and more educated households especially concerned about this use of public funds. This result suggests that it will be more difficult to convince poorer and less-educated households of the wastefulness of energy subsidies, although this task could be easier given the general feeling of the profligacy of subsidy spending. When asked why they thought subsidy expenditure was not a good use of public money, the most popular response among households was that subsidy benefits “go to the wrong people,” suggesting a good knowledge of the limitations of subsidy targeting and that the distributional issues with current subsidy policy should be stressed in communications seeking to build support for reform. 224 When asked how potential subsidy savings should be spent, 55 percent of households listed health as an area in which expenditure should be increased following reform, and 43 percent of households listed education as another. Only 17 percent of respondents listed targeted income support to the poor as a better alternative to energy subsidies. In fact, only 24 percent of the very poorest households said savings from reform should be transferred to targeted income support for the poor. This finding reflects a general lack of support for a redistributive spending policy, which that was also evident in the results of other survey questions. Clear evidence of resistance to reform also emerged in the household survey. Households are suffering under current economic conditions, and they are concerned that they will not be able to cope with significantly higher energy prices. Close to 80 percent of households said that they could afford a maximum 5 percent increase in energy prices. And, despite poor energy service provision, only about half of households were willing to pay higher energy prices for greater reliability of energy supply, and most of these were wealthier households. This theme emerged repeatedly in the focus group discussions. Small businesses are also under severe economic hardship, making energy subsidy reform difficult to manage or support. A preliminary political economy analysis and stakeholder mapping exercise point to the interest and influence of various Egyptian social interest groups on energy subsidy reform. This research will identify key groups and potential sources of opposition and support for reform that will need to be strategically managed through communications. Different social interest groups are divided according to whether they are political entities, businesses, or consumers/civil society and then are subdivided based on the categories most frequently found in the secondary literature. These categories may sometimes overlap, but are still useful for analytical purposes. In creating the matrix, for each social interest group: <>  Interest is scored based on how much the stakeholder is likely to welcome the prospect of fuel subsidy reform, owing to both material and ideological factors, ranging from 1 (strongly opposed) to 5 (largely neutral) and on to 10 (strongly in favor). Some actors may react based less on the issue itself than on the potential it offers to mobilize in pursuit of other goals, which are noted in figure 6.8. 225  Influence is a multidimensional concept, including political influence at the elite level, access to means of mass communication, financial resources, perceived legitimacy, propensity to engage in violence, and raw numbers. These various factors are combined into a rough measure, ranging from 1 (largely sidelined) to 10 (highly influential) (figure 6.8). <> The key social interest groups are those in the "low interest" section of the matrix, especially those with both low interest and high influence, who have the potential to become influential opponents of reform, and a few in the low-influence category who may need special protection and guidance. Because the latter group could easily be manipulated by the former, both categories should be a particular target for communications work. These key groups include: <>  Average-income and low-income households are proportionally the hardest hit by subsidy cuts, and those most able to express their displeasure. It will be vitally important to explain the rationale and the mitigating measures in terms they understand.  Small businesses and farmers are also disproportionately vulnerable. They may need to be advised on how more reliable energy supplies and higher growth will benefit them, as well as what interim support (e.g., microcredit, assistance with a revised business model) is available. Some sectors (e.g., agriculture, microbuses) may be more vulnerable than others, and these could be identified for a tailored approach.  Youth and the unemployed combine to form a nexus of dissatisfied and disempowered people who are the most likely to engage in street protests. Innovative means of communication are likely to be needed to reach them.  Unions and leftists/Nasserists are ideologically predisposed to oppose subsidy reform, in the absence of effective mitigation measures, because of its effect on the poor. That said, the benefits of energy subsidies accrue disproportionally to richer households. A compelling case can be made to leftist advocates and unionists that energy subsidy reform can be a pro-poor policy that seeks to undermine the "rich welfare," which is based on a flawed and untargeted welfare mechanism. 226 <> The emphasis on all these groups, which is suggested by stakeholder mapping, tends to be supported by analysis from the household survey. For example, the youth tend to have much lower confidence in government than older groups. Low- and average-income households tend to have less awareness of the extent of government subsidisation of energy consumption and tend to consider energy prices already too high. The potentially difficult groups will require management and engagement through communications to undermine their opposition to reform, but other groups are natural allies in the process of subsidy reform. Within the influence-interest matrix (figure 6.8), these groups have a high interest in subsidy reform. The business elite, wealthy consumers, the energy sector, and certain parts of the higher levels of the Egyptian government bureaucracy have both high interest and high influence in this process. These social interest groups should be engaged early in the process of subsidy reform to leverage and utilize their energies in building support for reform. Building partnerships with prominent, respected, and influential natural allies will be crucial in communicating the government’s key messages supporting reform in the current context of low government credibility. Figure 6.8: An Influence-Interest Matrix vis-à-vis Subsidy Reform for Key Egyptian Stakeholders 227 Military Higher Higher interest influence Average incomes Poor households Ultras Media SMEs DistributorsFarmersUnemployed Unions Big business Petroleum Ministry MB Finance Ministry Nasserists Youth Other Islamists Cabinet Civil servants Electricity Ministry Public energy firms Foreign investors Microbuses Source: World Bank 2014. Note: The scoring methods used for the indicative matrix are intuitive rather than systematic. MB = Muslim Brotherhood; SMEs = small- and medium-size enterprises. [[Typesetter: The symbols do not signify anything, but keep and change to gray.]] <>Household Use of and Spending on Energy Electricity and LPG are the most commonly used fuels in households, as evinced from the nationally representative Household Income Expenditure and Consumption Survey (HIECS) in 2012. The HIECS contacts 24,000 households covering all governorates to collect information on the annual consumption of 300 different goods and services, including household direct fuel and electricity consumption. Electricity access is universal, but the level of use increases significantly with income. Monthly average consumption of energy in the richest quintile is at least double that of the consumption of households in the poorest quintile.2 The average monthly electricity consumption across the entire population is 234 kilowatt hours. Use of gasoline progressively rises with income quintile, forming one-fourth of their total fuel consumption. For the poorest, electricity and LPG comprise the energy basket, and the use of any other fuel is negligible (figure 6.9). 228 Figure 6.9: Household Annual Average Energy Expenditure a. Total household energy budget b. Disaggregation of household energy budget 1,400 1,400 1,212 1,200 1,200 1,000 1,000 800 LE/year 800 754 685 600 636 574 LE/year 600 400 400 200 200 0 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 0 Quintale 1 Quintale 2 Quintale 3 Quintale 4 Quintale 5 Wood or coal Liquid fuel LPG Natural Gas Electricity Source: HIECS 2012. Note: HIECS = Household Income Expenditure and Consumption Survey. [[Typesetter: in figure 6.9: Panel a: sub in gray for color; Delete the numbers from the graph area; Panel b: 5 values of gray needed for bars and legend; For panels a and b: X-axes: Use "Quintiles" as the label; use the quintile numbers to label the bars (right reading in panel a); remove the tick marks; Background: Remove the boxes.]] LPG is almost universally used for cooking in rural areas and by two-thirds of the households in urban areas. The LPG distribution system is chaotic and informal, which directly affects the quality of service delivery for households. The retail price is artificially depressed at LE 8 per cylinder, but it can go up to LE 50–60 per cylinder during months of shortages. Natural gas, as the alternative to LPG for cooking, is prevalent in the higher-income quintiles and in urban areas. Gasoline and fuel oil, mainly used as transport fuels, are mostly consumed by the higher-income quintiles. Natural gas for cooking and transport fuels has been gaining users. The share of 229 households using natural gas for cooking increased from 10 percent in 2005 to 19 percent in 2013, and the share of households using wood/coal and liquid fuel fell during this period. The share of households using transport fuels grew from 11 percent to 23 percent during the same period. On average, households spend about 3 percent of their budget on energy. Although energy spending increases with income, the share of the budget spent on energy is similar in rural and urban areas and across income quintiles. Electricity represents the largest share, accounting on average for more than 50 percent of the energy budget. Households in the richest quintile spend a larger proportion of their income on transportation fuels compared to households in poorer quintiles. In contrast, households in poorer quintiles spend more of their income on LPG than households in richer quintiles (figure 6.10). Figure 6.10: Household Spending on Energy Items a. Percentage of household budget spent on b. Disaggregation of household energy budget energy 100% 3.5 percent of energy budget Percent of total household budget 3.4 80% 3.3 60% 3.2 40% 3.1 3.0 20% 2.9 0% 2.8 Quintale Quintale Quintale Quintale Quintale 1 2 3 4 5 2.7 wood or coal Liquid Fuel LPG Natural Gas electricity gasoline Source: HIECS 2012. Note: HIECS = Household Income Expenditure and Consumption Survey. [[Typesetter: in figure 6.10: Panel a: sub in gray for color; Panel b: 5 values of gray needed for bars and legend; Y-axis: delete %; use sentence style for legend; For panels a and b: 230 X-axes: Use "Quintiles" as the label; use the quintile numbers to label the bars (right reading in panel a); remove the tick marks; Background: Remove the boxes.]] <>Distribution of Direct Subsidies Among Households Products consumed by richer households, such as diesel and regular gasoline, have traditionally been the most heavily subsidized, followed closely by LPG and electricity. Natural gas subsidies are the lowest per household. Distribution of subsidies is skewed toward the rich, with estimates undertaken in fiscal 2013/14 suggesting that the richest quintile receives 36 percent of the total energy subsidies. In contrast, the poorest quintile receives an estimated 12 percent of total energy subsidies. All types of energy subsidies are regressive: the richest quintile receives the highest benefits, especially for gasoline, diesel, and natural gas. For example, the overall share of energy subsidies accruing to the poorest 20 percent of the households was 12 percent in the 2014 estimates, but was as little as 3 percent for natural gas and 1.6 percent for gasoline. LPG subsidies are the most evenly distributed. The richest quintile receives three times as much subsidy as poorest quintile. Total direct household energy subsidies amounted to LE 1,726 per annum or almost 7 percent of total household annual consumption in fiscal 2013 (figure 6.11). Subsidies are highest for gasoline followed by LPG, and natural gas subsidies are by far the lowest in the household portfolio. The amount of subsidy received by a household increases with expenditure and therefore income quintile: the richest quintile received about LE 690 per capita of energy subsidies, and the poorest quintile received on average LE 232. Nevertheless, as a proportion of total income, subsidies are more important for the poorest quintile, representing 8 percent of household expenditure, but amounting to 6 percent of household expenditure for the richest quintile. Figure 6.11: Distribution of Household Subsidies among Fuels 231 Total Gasoline LPG Electricity Natutal Gas 0 500 1000 1500 2000 2500 3000 LE/year Source: HIECS 2014. Note: HIECS= Household Income Expenditure and Consumption Survey; LE = Egyptian pound. [[Typesetter: in figure 6.11: Y-Axis: change "Natutal Gas" to "Natural gas"; Chart area: change colors to two shades of gray; X-axis: add comma to 4-digit numbers; change label to "LE per year"; Background: remove the box.]] LPG subsidy reduction would directly impact the poorest quintile the most, whereas gasoline subsidies removal would mainly affect the richest quintile. For the poorest quintile, the LPG subsidy accounts for 60 percent of total energy subsidy, followed by electricity with 36 percent. In contrast, the LPG subsidy represents only 25 percent of total energy subsidy received by the richest quintile, and gasoline and electricity account for 41 percent and 31 percent, respectively (figure 6.12). Gasoline subsidies are most inequitably distributed among the fuels (figure 6.13). If gasoline subsidies are eliminated, fuel subsidies will be reduced by 40 percent for the richest quintile and by only 3 percent for the poorest quintile. On the other hand, if the LPG subsidy is eliminated, 60 percent of benefits from fuel subsidies will be removed from the poorest quintile. Figure 6.12: Distribution of Subsidies by Quintiles 232 100 Percent of households 80 Quintile 1 60 Quintile 2 40 Quintile 3 20 Quintile 4 Quintile 5 0 Electricity Natural gas LPG Gasoline All Energy Subsidies Source: World Bank 2014. [[Typesetter: in figure 6.12: Chart area and legend: need 5 values of gray; Use sentence style: change "Energy Subsidies" to lower case; Remove tick marks from bottom of graph; Background: delete box.]] Figure 6.13: Progressivity in the Distribution of Benefits 233 1 ligne de 45° L(p): Lorenz C(p): gasoline .8 C(p): deisel C(p): LPG C(p): Natural gas C(p): electricity .6 .4 .2 0 0 .2 .4 .6 .8 1 The percentiles (p) Source: World Bank 2014. Note: Lorenz curve is a reflection of cumulative percentage of total national income (or some other variable). It is plotted against the cumulative percentage of the corresponding population. [[Typesetter: in figure 6.13: Chart area and legend: Use broken lines instead of colors; keep the black 45 degree line as is; X-axis: Delete "The" and capitalize "percentiles"; Legend: Use sentence style; Background: delete box; delete lines in graph.]] <>Impact of Subsidy Reforms on Households Energy products are consumed directly through household consumption of these products and indirectly through household consumption of other goods and services that use fuel products as inputs. Therefore, the total welfare effect3 of higher fuel prices—or lower fuel subsidies—on household real expenditure depends both on the direct effect of higher prices for energy products consumed by households and on the indirect effect arising from higher prices for other goods and services consumed by households to the extent that higher energy costs are passed on to consumer prices. 234 The analysis of the direct effect on households is estimated through SUBSIM from the 2013 HIECS. The analysis of indirect effect draws from the computable general equilibrium (CGE) model for Egypt underpinned by the social accounting matrix (SAM), representing 56 sectors of the economy, including 11 energy sectors. The SAM has 10 types of households—including five quintiles by urban and rural location—each supplying two types of factors, capital and labor. SAM describes the flow of payments from final demand institutions to production activities and the flow of payments of production factors from activities to institutions, as well as any transfers between institutions. The incidence of the welfare effect can be analyzed by examining how the magnitude of the effect of price change varies across different household groups; in other words, by calculating the average real expenditure loss for each quintile as a percentage of consumption. In addition to the real expenditure effects of the energy price increase, inequality measures, poverty incidence, and the poverty gap are considered. The poverty gap measures how far below the poverty line is the income of the poor on average. At the baseline situation (before the announcement of July 5, 2014, reforms), the total annual expenditure was LE 5,967, the poverty rate was 26.3 percent, the poverty gap was 5.2 percent, and the Gini coefficient4 was 29.8. Any changes in the scenarios presented in this section will be measured from this baseline situation. The scenarios are, first, a 25 percent increase in all fuel prices and, second, the July 5 increase in fuel prices. A situation of cost recovery, particularly for diesel, gasoline, and fuel oil, is also simulated. Considering a 25 percent increase in all fuel prices, the direct impact on per capita consumption would be a reduction by 1.22 percent. The per capita expenditure of the poorest quintile falls by about 1.58 percent, and by 1.12 percent for the richest quintile. For the poorer quintiles, the decline results largely from the removal of subsidies on LPG cylinders. In contrast, for the richest quintile households, most of the decline in per capita expenditure is driven by higher gasoline prices. Price changes in LPG had the largest impact on well-being especially for the poor, resulting in a decline of 1.31 percent for the poorest quintile, but only 0.37 percent for the richest quintile (table 6.3). Table 6.3: Impact of Price Change on Well Being, in percentage of annual household budget 235 Quintile Gasoline Diesel LPG Natural gas Electricity Total 1 (poorest) −0.05 −0.00 −1.31 −0.00 −0.21 −1.58 2 −0.08 −0.00 −1.10 −0.01 −0.18 −1.36 3 −0.12 −0.01 −0.95 −0.01 −0.17 −1.25 4 −0.18 −0.00 −0.77 −0.01 −0.15 −1.11 5 (richest) −0.63 −0.01 −0.37 −0.02 −0.11 −1.12 Total −0.32 −0.00 −0.74 −0.01 −0.15 −1.22 Source: World Bank 2014. Consequently, the direct impact on poverty incidence is an increase of 1.13 percentage points, from 26.3 percent to 27.4 percent of the population (table 6.4). The poverty gap increases by about 6 percent. The largest adverse impact on welfare is driven by LPG price increases (0.9 percentage points), accounting for 82 percent of the overall poverty increase of this scenario, as LPG consumption accounts for a large share of the poor household budget. LPG is followed by electricity, where the subsidy reform contributes to 10 percent of poverty increase. Because natural gas is mainly consumed by well-off households, increased prices of natural gas have minimal impacts on poverty indicators. As a result of consumption patterns of energy products by different quintiles, a rise in LPG prices has an increasing inequality impact as well as electricity (with smaller magnitude), and natural gas, gasoline, and diesel have a decreasing inequality impact. When LPG or electricity prices increase, the poorest quintile exhibited the largest declines in per capita expenditure compared to other quintiles, but these households experienced the smallest deterioration in their well-being when natural gas, gasoline, and diesel increased. To mitigate the adverse impact, the government may compensate the poorest two quintiles for their real expenditure losses. Such compensation amounts to LE 56 per person, per year. In the scenario involving this mitigation transfer, per capita expenditure of households declines by about 0.84 percent on average. It rises by about 0.09 percent for the bottom quintile and declines by more than 1 percent for other quintiles. Consequently, poverty increases only by 0.45 percentage points.5 Table 6.4: Impact of Price Change on Poverty 236 Change to Change to Change to Prereform postreform Prereform postreform Prereform postreform Poverty incidence Poverty gap Gini index Total 26.3 1.13 5.21 0.33 29.82 0.08 Gasoline 26.36 0.07 5.23 0.01 29.69 −0.14 Diesel 26.29 0 5.21 0 29.82 0 LPG 27.23 0.94 5.48 0.27 30.02 0.2 Natural 26.3 0.01 5.22 0.00 29.82 0 gas Electricity 26.4 0.11 5.26 0.04 29.85 0.02 Source: World Bank 2014. Considering the price changes in the July 5 subsidy reforms, this scenario is considered without mitigation. The reason is that the potential recipients of the government's increased funding of health and education are not identifiable. Direct expenditure losses amount to LE 36 per person, per year (table 6.5). This scenario refers to energy products consumed mainly by nonpoor households; therefore, income losses are larger for the richest quintile (LE 97). The poorest quintile also suffers from deterioration in their living standards, mostly resulting from higher electricity prices (LE 11). Table 6.5: Impact on per Capita Well Being (annual household budget) Natural Quintile Gasoline Diesel Electricity Total gas 1 (poorest) −0.97 −0.01 −0.37 −11.16 −12.51 2 −2.20 −0.03 −0.88 −14.53 −17.63 3 −4.13 −0.11 −1.71 −16.99 −22.94 4 −7.98 −0.08 −2.93 −20.35 −31.34 5 (richest) −54.06 −0.26 −9.24 −32.95 −96.51 237 Total −13.87 −0.10 −3.03 −19.20 −36.19 Source: World Bank 2014. As a result of implementation of this scenario, the poverty rate is expected to rise from 26.3 percent to 26.8 percent (table 6.6). As the price reforms do not touch LPG, which constitutes a substantial proportion of the household energy basket, the direct poverty impact is moderate. However, households are affected indirectly, particularly by the rise in the price of transportation fuels. Indirect and substitution impact on poverty are larger than direct impact, as increased gasoline prices are passed through prices of services, especially transportation. All prices are pushed up because of the increase in transportation prices. This scenario exhibited small improvements in inequality resulting from increases of gasoline, diesel, and natural gas, which is mainly consumed by the better-off. Therefore, indirect and substitution impacts on poverty are larger than direct impacts, as increased gasoline prices are passed through services prices, especially transportation. The relatively strong welfare impacts of reform demonstrate the central importance of putting in place social protection and compensation mechanisms to mitigate the impacts of reform on the poorest citizens—mechanisms that can start simple and become more sophisticated and targeted over time as data collection and institutional capacity are enhanced. This approach is especially important if the general public is to accept necessary ongoing price increases in Egypt. To the credit of the government of Egypt, following the 2014 reforms, certain measures were indeed put in place to dampen the immediate effect of higher energy prices on consumers, particularly the poor. To ensure that energy price increases did not translate into higher prices for staple goods, the government has frozen the prices of publicly distributed bread, rice, sugar, tea, flour, and oil. In anticipation of reduced energy subsidies, in June 2014 the government expanded the food subsidy system, discounting the price of 20 new products, including meat, chicken, fish, detergents, pasta, certain staple vegetables, butter, and other dairy products. Nevertheless, these kinds of mitigation measures will need to evolve and be enhanced in advance of further energy price reform. Table 6.6: Reform, Poverty Head Count, and Gini Index 238 Change Poverty Standard Gini Variation Standard p-value in p-value level error index in Gini error poverty Prereform 26.290 – – – 29.82 – – – Gasoline 26.353 0.065 0.025 0.011 29.72 −0.10 0.01 0.00 Diesel 26.290 0.000 0.000 0.000 29.82 −0.00 0.00 0.20 Natural gas 26.309 0.019 0.012 0.103 29.81 −0.01 0.00 0.00 Electricity 26.637 0.426 0.057 0.000 29.85 0.02 0.00 0.00 Post reform 26.801 0.511 0.062 0.000 29.73 -0.09 0.01 0.00 Source: World Bank estimates. A cost recovery scenario is simulated for gasoline, diesel, and fuel oil, allowing these products to trade at market (cost recovery) prices. In this scenario consumption losses amount to LE 243 per person, per year. This scenario involves energy products directly consumed mainly by nonpoor households. Income losses are larger for the richest quintile, but the poorest also suffer from deterioration in their living standards, mostly resulting from the indirect impact of price increases of all goods and services. Poverty rates increase by only 0.3 percent as a result of direct impact. Moreover, income distribution improves (Gini coefficient declines by 1.75 percent) as consumption percentage loss for nonpoor is higher than the poor. <>Conclusions The government of Egypt has embarked on a comprehensive subsidy reform program with an announced price reform trajectory in electricity markets and a similar intention for liquid fuels. This is a bold and welcome first step, but for Egypt’s subsidy burden to become more manageable, further price appreciation will likely be necessary. For example, the price of LPG— the most highly subsidized of energy products in Egypt and used extensively by poorer households—was not revised in the July 2014 reforms. From a political perspective, ongoing price increases may be difficult given the current economic circumstances and that consumers have already expressed some frustration at those already in place. Successful and sustainable energy subsidy reform in Egypt will continue to require three key elements: an effective, gradual, and thoughtful price appreciation strategy for different energy types that consider the user profiles for each energy type; the expansion and creation of social protection mechanisms to 239 mitigate the impacts of reform on the poor; and effective communication to build public support for reform. In terms of pricing, the direct welfare effects of energy subsidy reform on the poor are felt strongly through higher prices for fuels that they consume in large quantities, such as LPG and household electricity, and the indirect effects of reforms on the poor are expressed less through consumption of other fuels and more through their consumption of other goods and services, especially transportation services. This profile of energy consumption and of the direct and indirect impacts of reform has informed, and should continue to inform, energy pricing plans into the future. No matter how well-considered price reform strategies are, there will necessarily be impacts on the poor (and indeed all energy consumers) resulting from reform. Mitigating the impacts of subsidy reforms will likely require a relatively small amount of fiscal resources, but effective targeting to the poor and vulnerable is currently difficult given the limited scope of national social protection systems. Many favor the creation of a national cash transfer system, starting with a universal registry of the poor, which would be the cornerstone of a cash compensation mechanism and should be prioritized. In the meantime, the government should consider other short-term measures that can be rolled out to minimize the impact of energy subsidy reform (if and when this process occurs), as occurred in 2014 with the changes to the food subsidy system. There are a wealth of policy options to achieve this, from the provision of vouchers for key goods consumed by the poor, to price controls for certain nonenergy staple goods. International experience in subsidy reform is illustrative of the interventions that are likely to be successful in this regard. The communications efforts for the July 5 reforms were rather weak. Moving forward with subsidy reforms will require a sustained and consistent communications effort to inform Egyptians about subsidies, help them understand the benefits of moving away from the subsidy regime, and make them aware of the spending on health and education from subsidy savings. The government also needs to continuously monitor the media for public sentiments regarding subsidy reforms, conduct polls to understand the people’s pulse, and build alliances with prominent Egyptians to promote awareness on subsidies and greater consensus on the need for subsidy reforms. 240 Finally, the government will need to deliver tangible results in terms of improved public services provision. The often-repeated rationale for energy subsidy reform is that it will provide the fiscal space to deliver better public services, including investment in education, health, and infrastructure, all of which are sorely needed. The government has stated that LE 21 billion of the total saving of LE 51 billion from the current reforms will be channeled directly into health and education. Egyptian consumers who have been affected by higher energy prices will demand that their sacrifices result in a tangible change in the way the government provides essential services for them. Delivering noticeable, timely improvements in service provision, in the context of general fiscal consolidation, should therefore be a priority of Egypt’s macroeconomic policy in the short to medium term. Communication and transparency will be key to achieving this objective. <>Notes 1. In the CGE model, household consumption of gasoline is treated as a transportation service expense. 2. Households are ranked according to their per capita consumption and grouped into five equal groups from the poorest to the richest. Average per capita consumption for each of the five quintiles are LE 2,795; LE 3,845; LE 4,878; LE 6,216; and LE 11,708, respectively. 3. Welfare is measured by total energy expenditure. 4. Gini coefficient is represented by the area between the Lorenz curve and the line of equality. The coefficient varies between 0, which reflects complete equality and 1, which indicates complete inequality. 5. Direct impact resulted in increase in poverty by 0.19 percentage points. <>References Fattouh, B., and L. El-Katiri. 2012. Energy and Arab Economic Development. Arab Human Development Report, United Nations Development Program. http://www.arab- hdr.org/publications/other/ahdrps/ENGFattouhKatiriV2.pdf. 241 Household Income and Expenditure, and Consumption Survey. 2012, 2014. Available from Central Agency for Public Mobilization and Statistics (CAPMAS), Cairo. Rohac, D. 2013. Solving Egypt’s Subsidy Problem. Cato Institute, Policy Analysis No. 741. http://www.cato.org/publications/policy-analysis/solving-egypts-subsidy-problem. Silva, J., V. Levin, and M. Morgandi. 2012. Inclusion and Resilience: The Way Forward for Social Safety Nets in the Middle East and North Africa. Washington D.C.: World Bank. WDI (World Development Indicators). 2014. Available at http://data.worldbank.org/data- catalog/world-development-indicators. World Bank. 2014. "Policy Brief: Energy Subsidy Reforms in Egypt." Report prepared for technical advisory services to Ministry of Petroleum, Arab Republic of Egypt. Unpublished draft. World Bank, Washington, DC. 242 <>Chapter 7 <>Energy Subsidies Reform in Jordan: Welfare Implications of Different Scenarios Aziz Atamanov, Jon Jellema, and Umar Serajuddin <>Introduction As political unrest spread across the Arab world, Jordan faced an adverse economy as well. Fundamental to the economic challenge was high and rising energy prices, already heavily subsidized for consumers. With the government intent on staving off emerging unrest through a series of measures, buffering consumers from increased energy prices being a key action, fiscal costs mounted. By 2012 subsidies on petroleum products alone were about 2.8 percent of the gross domestic product (GDP) and 8.8 percent of government expenditures. At the same time, political unrest disrupted the supply of natural gas from the Arab Republic of Egypt, and Jordan had to abruptly switch to using imported oil products (heavy fuel oil and diesel) to produce electricity. The cost of producing electricity increased several folds. As the higher cost was not passed on to the consumers, National Electric Power Company (NEPCO), bore all the increases in fuel prices and accumulated debt as a result. At approximately 17 percent of government expenditures and 5.5 percent of GDP in 2011, the new prices doubled the amount of the petroleum subsidies. Even for a country with a history of universal subsidies, the suddenness and immensity of the fiscal burden were remarkable. Facing strong fiscal pressures of the unsustainably large subsidies, in November 2012 the government decided to remove the subsidies for high quality gasoline, diesel, and kerosene and reduce the subsidies on liquefied petroleum gas (LPG). To compensate households for the price increases, the government introduced a large-scale cash transfer program to households earning less than 10,000 Jordanian dinars (JD) a year, covering about two-thirds of households. This major policy decision was carried out in the middle of a volatile political atmosphere. All the same, reform efforts were incomplete, and the government continues to contemplate how to reduce electricity subsidies, which surpass the fiscal burdens imposed by the petroleum subsidies. Much like the 2012 petroleum subsidies reform, the 243 government could implement far-reaching reforms by reducing electricity subsidies and combining the cuts with a targeted cash transfer. Yet, it has been difficult for the government to put in place such a measure, despite the quite successful removal of petroleum subsidies. One reason for the hesitation in further reforms is perhaps that the question of “who gets what, when, and how”1 from reform has no clear answer. The costs and benefits of potential reforms are not well understood, especially for electricity, where the pricing may often appear opaque even to policy makers. This chapter attempts to shed light on the distributional and fiscal impacts of reform options, focusing on petroleum and electricity subsidy reforms. Understanding the impacts of the petroleum subsidy reforms can inform alternative reform options for electricity subsidies. The chapter is organized as follows. It starts with the evolution of subsidies in Jordan since the 2000s. The distributional impacts of reform would depend on how important the subsidized items are to consumers in terms of their expenditures on those items. The next section discusses this question from the perspective of richer and poorer households. The distributional impacts of reform would depend not only on how much consumers spend on the subsidized items but also on the extent of price changes. The following two sections simulate direct and indirect impacts of potential reform scenarios across the income distribution. From this discussion, the chapter moves on to considering how reforms are weighed down by vexing political economy constraints. In Middle East and North Africa (MENA) countries, universal subsidies have been in place as part of the governments' role in ensuring stability in the lives of the people, and doing away with them is not straightforward. <>Evolution of Subsidies As in other countries in the MENA Region, the government of Jordan has traditionally provided universal subsidies to consumers and producers of petroleum products, electricity, water, and food. With the government continuing to insulate the population from spikes in global commodities and food prices, the subsidies experienced sharp increases. In 2005 the government was spending more than JD 600 (British) million on food and oil subsidies alone, about 17 percent of total government expenditures. The magnitude of the subsidies rose and fell with international price changes, but they remained a challenge for the government. 244 Jordan’s consumer subsidies have a long history, with food price subsidies dating back to the 1960s. Starting with wheat and sugar, over time a host of food items were subsidized. By the early 1990s most food prices were liberalized with the exception of wheat, which has continued to be subsidized despite occasional attempts at reform. The government’s attempt to remove the wheat subsidies (with prices almost trebling from JD 0.075 per kilogram to JD 0.25 per kilogram), resulted in widespread social discontent and erupted in "bread riots" in 1996 (Lamis and Schwedler 1996). Although the increase was scaled back, the retail price almost doubled in 1996 and was subsequently accompanied with a cash transfer program to compensate the poor. Since then, wheat prices have remained fixed in nominal terms. Consumers today also receive water at subsidized rates. In this chapter, we focus on petroleum products and electricity because of their relative importance to Jordanian households and the government. <>Subsidies on Petroleum Products Before 2003 Jordan received oil from Iraq at below market prices, and the government passed on part of these savings to consumers. After 2003 Jordan’s savings from this source declined, and at the same time international prices went up (World Bank 2009). Between 2002 and 2008 world energy prices increased by more than threefold, and world food prices doubled (figure 7.1). The government was forced to increase prices on petroleum products in 2005 and again in 2006, but it still kept prices below international levels. Consequently, in 2005 government spending on petroleum subsidies alone reached 5.8 percent of GDP (Coady et al. 2006). Figure 7.1: World Energy and Agriculture Price Trends, 1960–2012 245 Source: Araar et al. 2013; figures based on the World Bank Commodity Prices Database (Index, 2005 = 100 percent). [[Typesetter: in figure 7.1: Chart area and legend: sub in black solid line and black broken line; X-axis: Turn the dates right reading and align every other tick mark with dates ; Y-axis: Label: "Percent"; Legend: change terms to "Energy" and "Agriculture"]] In the face of serious fiscal strain, the government phased out cash subsidies on petroleum products between 2008 and 2010 (table 7.1). For the first time prices were at the international level (LPG was still partially subsidized), and a rapid drop in petroleum subsidies followed— from 2.5 percent of GDP in 2007 to 0.3 percent in 2009. At the same time the government compensated households in the form of salary increases for public and private sector employees and military personnel. At the very end of 2010, however, as oil prices reached US$ 90 a barrel, the government discontinued the monthly petroleum price adjustments and reintroduced petroleum subsidies. By 2012 petroleum subsidies were at 2.8 percent of GDP or close to 9 percent of the government budget. Table 7.1: Jordan: Changes in Petroleum Subsidies, 2007–12 (in JD million) 2007 2008 2009 2010 2011 2012 Budgetary petroleum subsidies 306 197.9 42.9 88.2 571 626 246 Nominal GDP at market prices 12,131 15,593 16,912 18,762 20,477 22,230 Petroleum subsidies (% of GDP) 25 13 0.3 0.5 2.8 2.8 Petroleum subsidies (% of budget expenditures) 6.8 3.8 0.9 1.6 8.4 8.8 Source: Araar et al. 2013. Note: GDP=gross domestic product; JD=Jordanian dinar. Facing fiscal pressure again, in June 2012 the government increased the price of premium octane gasoline (octane 95) by about 26 percent. However, as octane 95 accounted for only about 10 percent of the gasoline consumption of Jordan’s transport sector, this move proved inadequate to address the government’s fiscal burdens. The government then launched the major reforms of November 2012, when subsidies on petroleum products were cut drastically and an extensive cash transfer program was instituted. This program has continued till the present and will be described in more detail. <>Subsidies on Electricity The production and distribution of electricity in Jordan are in the hands of the private sector, and transmission is in the hands of the public sector. Prior to 2006 the entire electricity system was under the public sector. In 2002 a new electricity law was passed to open the system to the private sector. In 2006 the privatization process was initiated, and by 2008 two independent power producers entered the market. Today there are four major private (or almost private) production companies and three main private distribution companies (JEPCO, IDECO, and EDCO). The transmission company, NEPCO, a public shareholding company, purchases all its energy from the producers and resells it to the distributors. Verme (2011) provides a more detailed discussion of this arrangement. The sale price from the production companies to NEPCO is established by bilateral contracts. These contracts specify that NEPCO is responsible for the purchase of the fuel necessary for the functioning of the power stations. The sale price from NEPCO to the distribution companies and the tariffs for consumers are established by the government’s Energy and Minerals Regulatory Commission (EMRC). The existing structure of the electricity system implies that all financial risks are borne by NEPCO. The four private producers companies are insulated from the risks associated with 247 changes in fuel prices, as the cost of fuel is borne by NEPCO as stipulated in the NEPCO- production companies agreements. The three private distribution companies are insulated from price increases by the tariff system in place, which guarantees a positive return to distribution companies. In the 2000s electricity generation in Jordan relied mostly on Egyptian gas and heavy oil, with the former accounting for 80 percent to 85 percent of inputs. Electricity is produced almost entirely with fuels, and alternative sources of production, such as hydro or solar power, are absent. The price of heavy oil almost doubled in February 2008, but Egyptian gas was heavily subsidized at about 50 percent below international market prices (World Bank 2009). Between 2008 and 2009 NEPCO managed to maintain positive balances, but at the end of 2010 the company reported a debt of more than JD 200 million. Then, due to disruptions of gas supply from Egypt in 2011, the cost of producing electricity in Jordan increased several times over. The producers had to switch to expensive diesel and heavy fuel oil, the use of which in the fuel mix reached 80 percent in 2012 from 29 percent in 2010. As the increased costs were not passed onto the final consumers, NEPCO assumed the burden of increases in fuel prices and began running monthly deficits of an estimated JD 100 million, which amounted to JD 1.2 billion annually (5.5 percent of GDP in 2011). This enormous fiscal burden on the government was one of the main reasons the government has stated its intention to follow fiscal consolidation plans in the context of an International Monetary Fund (IMF) program known as the stand-by arrangement (SBA). <>Distribution of Subsidies This section describes the distribution of expenditures on subsidized products and the distribution of subsidies across households in Jordan based on the 2010 Household Expenditures and Income Survey (HEIS), the most recent flagship consumption survey conducted by Jordan's Department of Statistics (DOS). As the survey is outdated, all expenditures were inflated to 2013 prices using nominal GDP per capita growth rates.2 <>Petroleum Products Households in Jordan spent an estimated JD 856 million on subsidized petroleum products such as kerosene, LPG, gasoline (octane 90 only), and diesel in 2013 (table 7.2). Expenditures 248 on gasoline account for about two-thirds of this amount, followed by LPG (24 percent), kerosene (6 percent), and diesel (5 percent). Wealthier households spend larger amounts on subsidized petroleum products than poorer households. Table 7.2: Household Expenditures on Subsidized Petroleum Products, in JD million Quintile Kerosene LPG Gasoline Diesel Total 1 (poorest) 7 27 21 0 55 2 9 33 55 0 98 3 12 38 91 1 141 4 12 45 139 2 199 5 (richest) 14 63 251 35 363 Total 55 206 557 38 856 Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; population quintiles based on spatially adjusted consumption per capita before the reform. Expenditures on gasoline and diesel are relatively more important for wealthier households, and LPG and kerosene are relatively more important for less-affluent households (table 7.3). Households in the wealthiest quintile spend an estimated 4.4 percent of their total expenditures on gasoline, and the poorest quintile spends only 1.9 percent. Conversely, the poorest quintile households spend 2.4 percent of their expenditures on LPG, and the wealthiest quintile spends 1.1 percent. Budget shares of each product can be clearly seen in figure 7.2 plotted over population percentiles ranked by consumption per capita. The positive slope means higher shares of the product in the total budget of the wealthier population. Petroleum products as whole account for an estimated 6.4 percent of total household expenditures, with the poorest quintile households spending 5 percent of their total expenditures on these products and the richest quintile spending 6.4 percent. Table 7.3: Expenditure on Subsidized Petroleum Products Relative to Total Expenditures, in percent Kerosen Gasolin Diese Quintile LPG Total e e l 1 (poorest) 0.7 2.4 1.9 0.0 5.0 2 0.6 2.0 3.4 0.0 6.0 3 0.6 1.8 4.3 0.0 6.6 4 0.4 1.6 4.8 0.1 6.9 5 (richest) 0.2 1.1 4.4 0.6 6.4 Total 0.4 1.5 4.1 0.3 6.4 249 Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; population quintiles based on spatially adjusted consumption per capita before the reform. Figure 7.2: Expenditure on Subsidized Petroleum Products Relative to Total Expenditures, in percent .06 Kerosene LPG Gasoline Diesel .04 Expenditure shares .02 0 0 .2 .4 .6 .8 1 Percentiles (p) Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; population quintiles based on spatially adjusted consumption per capita before the reform. In terms of actual amounts spent on subsidized products, richer households far outspend poorer households. The poorest quintile was spending seven times less on subsidized petroleum products than the richest quintile (6 percent of total national expenditures versus 42 percent as shown in figure 7.3), which indicates that wealthier households received higher per capita subsidies than poorer households. Table 7A.1 shows that for all products, per capita subsidies are lower for poor households, particularly for gasoline and diesel. Figure 7.3: Shares of Total Expenditures on Subsidized Petroleum Products by Quintiles, in percent 250 100 90 80 70 60 Percent 50 40 30 20 10 0 Kerosene LPG Gasoline Diesel Total Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; population quintiles based on spatially adjusted consumption per capita before the reform; Quintile 1 = poorest. [[Typesetter: in figure 7.3, we need 5 values of gray for bars and legend.]] <>Electricity Jordan divides electricity usage—kilowatt hours—into seven tariff brackets. According to the latest revision made in August 2013, electricity tariffs range from JD 0.033 per kilowatt hour for the lowest consumption bracket (1–160 kilowatts per hour, per month) to 0.259 JD per kilowatt hour for the highest consumption bracket (1,000+ per kilowatt hour per month), with households paying progressively higher amounts only on the incremental consumption of the higher brackets. Table 7.4 shows the tariffs, mean annual expenditures on electricity, and the number of households for each tariff bracket. More than half of all households in Jordan consume electricity between 301 and 500 kilowatt hours per month. These households spend an estimated JD 270 on electricity per year. Hardly any households consume in the lowest tariff bracket (of less than 160 kilowatt hours per month), and the same is true for the highest tariff bracket (of more than 1,000 kilowatt hours per month). 251 Table 7.4: Parameters to Calculate Electricity Consumption in Jordan Brackets: 2014 Upper bound Mean annual No. of Percent kWh/month tariff, JD consumption, yearly consumption on HH of HH (JD) electricity, JD 1–160 0.033 63 54 8,967 1 161–300 0.072 184 136 355,443 29 301–500 0.086 391 270 620,619 51 501–600 0.114 528 448 127,452 10 601–750 0.152 801 631 80,494 7 751–1,000 0.181 1344 986 26,901 2 >1,000 0.259 1828 4,673 0 Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; HH = households; JD = Jordanian dinar; kWh = kilowatt hour. Population quintiles based on spatially adjusted consumption per capita before the reform. Household expenditures on electricity in Jordan are substantial and more important for poor households in terms of budget shares. Households spent an estimated JD 359 million on electricity in 2013 (using extrapolated data from HEIS 2010), an amount higher than that spent on LPG, diesel, and kerosene combined, but lower than expenditures on gasoline. Households from the lowest quintiles spend less on electricity in absolute terms. Households from the poorest quintile spend about a little less than a third on electricity than the wealthiest quintile (annually about JD 30 per capita compared to JD 105 for the wealthiest quintile). The budget shares of electricity are higher among the poorest households, who spend about 3.5 percent of their budgets on electricity compared to 2.4 percent for the richest households (figure 7.4). Consequently, poor households can be highly vulnerable to higher tariffs on electricity. Figure 7.4: Annual Expenditure on Electricity, by Quintile 252 120 Yearly electricity expenditure per capita, JD 4.0 Share of electricity in total expenditures, % 3.5 Per capita electricity expenditures, JD 100 Percent of total expenditure 3.0 80 2.5 60 2.0 1.5 40 1.0 20 0.5 0 0.0 Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Consumption per capita quintiles Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; JD = Jordanian dinar; population quintiles based on spatially adjusted consumption per capita before the reform; Quintile 1 = poorest. [[Typesetter: chart area and legend, change to broken lines.]] Table 7.5 shows the distribution of households with different electricity consumption across quintiles. Poor households consume less electricity and as a result pay lower tariffs. Forty-one percent of the poorest households consume 161–300 kilowatt hours per month compared to 15 percent among the wealthiest households. Nevertheless, the relationship between electricity consumption and welfare is not perfect. Some rich households have low electricity consumption, and some poor households have high electricity consumption; this result may be partially attributed to richer households having smaller households. Table 7.5: Distribution of Households by Tariff Brackets and Consumption per Capita across Quintiles Consumption per capita quintiles Brackets: kWh/month 1 2 3 4 5 Average 1–160 1 0 0 1 1 1 253 161–300 41 35 29 25 15 29 301–500 52 55 55 51 40 51 501–600 5 6 10 14 17 10 601–750 1 3 4 7 17 7 751–1,000 0 0 1 2 8 2 >1,000 0 0 0 0 2 0 Total 100 100 100 100 100 100 Source: World Bank calculations based on extrapolated HEIS 2010 data and official information. Note: HEIS = Household Expenditures and Income Survey; kWh = kilowatt hours; household quintiles based on spatially adjusted consumption per capita before the reform. <>Direct Impact of Simulation of Subsidies Reform All simulations in this chapter are based on Jordan’s 2010 HEIS, a nationally representative survey that the DOS used to produce official welfare aggregates and poverty estimates. Even though the reforms chosen for simulation were implemented in 2012, the analysis here refers to 2013.3 Extrapolations between 2010 and 2013 are based on adjustments for economic growth (GDP per capita nominal) and the consumer price index (CPI) for inflation. Household and population weights were updated to reflect population size in 2013.4 Estimates of demand elasticity with respect to price are necessary to model consumer responses to price change. Given limitations of having only cross-sectional household data with no variation in individual petroleum product prices across households, we used an own price elasticity of −0.3 to simulate changes in quantities consumed.5 <>Petroleum Products Simulations for petroleum products are based on price changes largely mimicking the real reform that occurred in November 2012. The price of gasoline (octane 90) rose by 14 percent, and diesel and kerosene prices increased by 33 percent. The price increases were meant to fully eliminate subsidies on these items. The highest increase was for LPG gas cylinders, with a unit price increase from JD 6.5 to JD 10, or by 53.8 percent. Despite this large increase, LPG continued to be subsidized. In this chapter, we decided to simulate the full removal of petroleum subsidies and 254 therefore simulated for the full removal of LPG subsidies as well—the only difference of our simulation from real subsidies reform introduced in November 2012. Using historical data from Saudi Aramco’s contract price on butane and propane, World Bank energy specialists estimated the "efficient" LPG price to be about US$ 1,428 per ton. This estimate implies JD 15.3 per cylinder to be the final LPG unit price without any subsidy (Kojima 2014).6 Two scenarios are used for simulation (table 7.6). In the first scenario, we simulate the full removal of subsidies without any compensating measures by the government. In the second scenario, subsidies reform is combined with the actual cash transfer program that accompanied the petroleum price increases. The cash transfer targets resident Jordanian households (with the households being the unit of reference) with yearly incomes not exceeding JD 10,000. The transfer amounts to JD 70 per person per year, for up to a maximum of six individuals per household (Araar et al. 2013). Table 7.6: Pre- and Postreform Prices of Petroleum Products, in Jordanian dinar Prices after Prereform Unit Increase, removal of pricesa subsidy % subsidiesb Gasoline (octane 90) 0.7 0.1 0.8 14 Kerosene 0.52 0.170 0.685 33 Diesel 0.52 0.170 0.685 33 LPG 6.5 8.8 15.3 135 Source: Araar et al. 2013. Note: a. As of October 2012. b. As of November 2012, except LPG. <>Scenario 1: Subsidy Cuts without Cash Transfers The simulation reveals that the full removal of subsidies on petroleum products would on average lead to an estimated 2.9 percent drop in consumption per capita of households (table 7.7). For the poorest quintiles, the drop will be higher (3.8 percent). The adverse impact on the poor results mainly from increased LPG prices. The increases in gasoline and kerosene prices have tiny impacts, and the increase in diesel price has no impact on consumption. When all 255 households are considered, LPG and gasoline are the two main products to affect household consumption. Table 7.7: Impact on the per Capita Well-Being of Removing Petroleum Subsidies Postreform impact on per capita well- Change in Prereform, JD being, JD per capita Quintiles, Total consumpti keros diese consumption per expenditures LPG gasoline Total on, % ene l capita per capita 1 (poorest) 843 −2 −28 −2 0 −32 −3.8 2 1,240 −2 −34 −6 0 −42 −3.4 3 1,624 −3 −39 −10 0 −52 −3.2 4 2,198 −3 −47 −15 0 −65 −3.0 5 (richest) 4,336 −4 −65 −27 −9 −104 −2.5 Total 2,048 −3 −42 −12 −2 −59 −2.9 Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; JD = Jordanian dinar; population quintiles based on spatially adjusted consumption per capita before the reform. Poverty would be expected to increase by 1.6 percentage points—from 13 percent in 2013 to 14.6 percent after subsidy removal—accompanied by increases in the poverty gap and in inequality. The overwhelming increase in poverty is caused by LPG prices, which is not surprising given its high share in the budget of poorest households and the large increase in its price (figure 7.2 and table 7.8). The poverty gap, measuring how far poor are from the poverty line on average or depth of poverty, would have increased as well, with LPG being the main contributor. Finally, inequality is expected to increase modestly, as reflected by a slightly higher Gini coefficient. Table 7.8: Impact of Petroleum Subsidies Removal on Poverty, Poverty Gap, and Inequality Poverty head count, Gini % Poverty gap coefficient Level Change Level Change Level Change Prereform 13.0 — 2.44 — 33.66 — Kerosene 13.0 0.0 2.47 0.02 33.68 0.03 LPG 14.3 1.3 2.83 0.39 34.00 0.35 Gasoline 13.1 0.1 2.47 0.02 33.61 −0.04 Diesel 13.0 0.0 2.44 0.00 33.61 −0.05 Postreform 14.6 1.6 2.89 0.45 33.94 0.28 Source: World Bank calculations based on extrapolated HEIS 2010 data. 256 Note: HEIS = Household Expenditures and Income Survey. <>Scenario 2: Subsidy Cuts with Cash Transfers In the second scenario we simulate the impact of petroleum price increases on well-being if the government initiates a compensatory cash transfer program to Jordanian households with annual incomes below JD 10,000. Table 7.9: Impact of Petroleum Subsidy Reform and Cash Transfer on per Capita Well-Being Prereform Postreform Change in per Total Total Impact on per capita Quintile expenditures, expenditures, per capita well- consumption, per capita capita being, JD % 1 (poorest) 843 857 14 1.6 2 1,240 1,244 3 0.3 3 1,624 1,611 −13 −0.8 4 2,198 2,166 −32 −1.5 5 (richest) 4,336 4,253 −83 −1.9 Total 2,048 2,026 −22 −1.1 Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; population quintiles based on consumption per capita before the reform. As can be seen in tables 7. 9 and 7.10, if perfectly targeted, the cash transfer offsets the negative impact of higher prices of subsidized products for the bottom 40 percent of the population. Consumption per capita would in fact grow by 1.6 percent for the poorest quintile, although on average consumption per capita would decline by 1.1 percent. Poverty would be expected to fall by 0.6 percentage points from 13 percent to 12.4 percent. The depth of poverty would decline by an impressive 0.2 percentage points, and inequality, as measured by Gini coefficient, would fall by 1.7 percent. Table 7.10: Impact of Petroleum Subsidy Reform and Cash Transfer on Poverty and Inequality Povert Gini Change in Poverty Change Change in Scenario y level, coefficien poverty, pp gap, % in Gini % t 257 poverty coefficient, gap, pp % Prereform 13 2.4 33.66 Postreform: no cash 14.6 1.6 2.9 0.4 33.94 0.8 transfers Postreform: cash transfer perfectly 12.4 −0.6 2.2 -0.2 33.08 −1.7 targeted Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; pp = percentage points. <>Impact of the Petroleum Products Reform on Government Revenue Removing subsidies on petroleum products without compensation would generate an increase in government revenues by JD 389 million per year (table 7.11). More than 70 percent of the increased revenues would come from higher LPG prices, and 20 percent would come from gasoline. Higher revenues from LPG are associated with the much higher increase in prices for LPG compared with that for gasoline (135 percent versus 14 percent). The removal of kerosene and diesel subsidies will generate only modest increases in revenues. As the subsidies were prorich in nature, with their removal, richer households would contribute proportionally more to the increased revenues: the poorest quintile accounts for only an estimated 11 percent of the increase in revenues, compared to 35 percent by the richest quintile. Table 7.11: Impact of Petroleum Subsidy Elimination on Government Revenue, in JD million Quintile Kerosene LPG Gasoline Diesel Total 1 (poorest) 2 37 3 0 42 2 3 45 8 0 56 3 4 51 13 0 68 4 4 61 20 1 86 5 (richest) 5 85 36 12 137 Total 18 279 80 13 389 Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; population quintiles based on consumption per capita before the reform. 258 The cost of the cash transfer program launched by the government was about JD 320 million a year. This cost was in fact higher than the revenues generated to the government from households from the actual reforms the government had carried out in November 2012. Although additional savings to the government were generated from consumers other than households, the cash transfer program appeared costly in the sense that it overcompensated a majority (almost 70 percent) of Jordanian households (Araar et al. 2013). The reform option we simulated in this chapter estimates the revenues/cost savings generated from households’ use of petroleum products (JD 389 million) to be higher than the cash transfer cost but still appear to be quite generous as it overcompensates almost half the population. To put matters in perspective, only JD 206 million are needed to maintain the prereform poverty rate if transfers are universal. If transfers are perfectly targeted to the poorest quintile, only JD 41 million would be needed to bring poverty to its prereform level. The design of the cash transfer program implemented in November 2012, along with a detailed discussion of options for improvement, can be found in Araar et al. (2013). <>Electricity <>Three Scenarios for Electricity Tariffs Reforms Three scenarios are explored in simulating the impact of reforms in electricity tariffs (table 7.12). The first scenario assumes no change in the tariff policy and simply applies tariffs planned for implementation in 2015. According to this scenario, tariffs will increase slightly for consumers from the top fifth, sixth, and seventh brackets. The second scenario lays out the most radical reform, implying a full removal of subsidies. Within this scenario we present two reform options. According to the first one—labeled “flat” reform—tariffs for all consumers become flat, in other words, equal to the cost recovery level at JD 0.164 per kilowatt hour. This option implies a huge burden on the poorer households with the lowest electricity consumption because their prices were the lowest. The second subscenario—labeled “progressive” reform—mimics the first subscenario in terms of the average impact on well-being, but uses a completely different approach to tariff increase.7 Under this subscenario, the burden of subsidies elimination is disproportionately placed on the shoulders of the richest households, who experience the highest increase in electricity tariffs. Given that scenario two is quite severe—leading to a more than doubling of prices for many brackets—and likely very difficult to implement, we simulate a third 259 scenario with a "quasi-progressive" increase in tariffs for all consumers and keeping tariffs on the first two brackets subsidized.8 This scenario, however, does not fully eliminate the electricity subsidies. Table 7.12: Three Scenarios for Electricity Tariff Reforms Scenario 2 Scenario 1 Full elimination Scenario 3 Current 2015 of subsidies Semiprogressive increase kWh tariff Subsidy tariffs in tariffs per month Flat 2014 Progressive Final % Final % Final % Final % 1–160 0.033 0.113 0.033 0.0 0.146 341.5 0.056 70.0 0.036 10 161–300 0.072 0.074 0.072 0.0 0.146 102.3 0.144 100.0 0.09 25 301–500 0.086 0.06 0.086 0.0 0.146 69.4 0.232 170.0 0.146 69 501–600 0.114 0.032 0.114 0.0 0.146 27.8 0.365 220.0 0.228 100 601–750 0.152 0 0.175 15.1 0.146 −3.9 0.502 230.0 0.304 100 751–1,000 0.181 0 0.209 15.5 0.146 −19.3 0.615 240.0 0.362 100 >1,000 0.259 0 0.285 10.0 0.146 −43.6 0.907 250.0 0.518 100 Source: Official tariff instructions replacing electricity tariff instructions, June 17, 2012. Note: Subsidies are calculated based on 2012 cost recovery tariff from NEPCO 2012). Applying 2015 tariffs has little negative impact on the per capita well-being of households. Given small increases in tariffs that are focused mostly on rich consumers, expenditures per capita are expected to decline on average by JD 0.6 or about 0.03 percent (table 7.13). Such a decline would bring no changes in poverty and poverty gap measures. Table 7.13: Impact of 2015 Tariffs on Economic Well-Being Quintile Impact, JD Impact, % 1 (poorest) −0.02 0.00 2 −0.05 0.00 3 −0.15 −0.01 4 −0.31 −0.01 5 (richest) −2.48 −0.06 Total −0.60 −0.03 Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; JD = Jordanian dinar; population quintiles based on consumption per capita before the reform. 260 Full removal of subsidies, however, will have a considerable impact on economic well-being. Replacing subsidies with a flat tariff rate is expected to reduce consumption per capita on average by JD 72.5 or by 3.6 percent. The negative impact is expected to be the strongest for the poorest households, with the bottom quintile experiencing on average a 5.7 percent reduction in per capita consumption. The negative burden on the poorest households can be reduced if a progressive increase of tariffs is applied. In this case, the negative impact would be less pronounced for the poor, even though the average household consumption would drop by the same amount. Nevertheless, both subscenarios are quite severe and would be difficult to implement. A semiprogressive increase in tariffs leading to a smaller reduction in subsidies, as depicted in scenario 3, is perhaps more realistic; the relative impact on households across the distribution would be almost equal, with a 1.2 percent reduction per capita on average (table 7.14). Table 7.14: Different Scenarios for Electricity Tariff Reforms Scenario 2 Scenario 3 Full elimination of subsidies Semiprogressive increase in Total tariffs Quintile consumption Flat Progressive per capita Impact, Impact, Impact, Impact, Impact, Impact, JD % JD % JD % 1 (poorest) 843 −49 −5.8 −33 −3.9 −10 −1.1 2 1,240 −59 −4.7 −42 −3.4 −13 −1.0 3 1,624 −66 −4.1 −54 −3.4 −18 −1.1 4 2,198 − 78 − 3.5 −71 − 3.2 − 24 −1.1 5 (richest) 4,336 −109 −2.5 −157 −3.6 −58 −1.3 Total 2,048 −72 −3.5 −72 −3.5 −24 −1.2 Source: Official tariff instructions replacing electricity tariff instructions, June 17, 2012. Note: JD = Jordanian dinar; population quintiles based on consumption per capita before the reform. Full elimination of subsidies has the strongest negative impact on poverty and inequality. In particular, poverty is expected to increase by 2.4 percentage points, the poverty gap by 0.7 percentage points, and inequality by 1.9 percent (table 7.15). Planned tariffs for 2015 will not have negative impact, but a semiprogressive increase in tariffs will lead to a moderate (0.5 percentage points) increase in poverty. This reform will, however, have a rather equalizing impact on distribution reducing the Gini coefficient by 0.2 percent. 261 Table 7.15: Impact of Electricity Subsidy Reform and Cash Transfer on Poverty and Inequality Povert Change Povert Change Gini Change y level, , pp y gap, , pp coefficie , % % % nt Prereform 13.0 . 2.4 . 33.66 . Postreform: Scenario 1: 2015 tariffs 13.0 0.0 2.4 0.0 33.64 −0.04 Postreform: Scenario 2: full elimination of electricity subsidies, flat 15.4 2.4 3.2 0.7 34.28 1.9 full elimination of electricity 14.7 1.7 2.9 0.5 33.66 0.0 subsidies, progressive Postreform: Scenario 3: semiprogressive increase in tariffs 13.5 0.5 2.6 0.1 33.59 −0.2 Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; pp = percentage points. <>Impact of Electricity Reform on Government Revenue The largest savings from electricity reform will come from the second scenario, assuming full elimination of subsidies. The government can save the largest amount (estimated at JD 473 million) from full removal of subsidies under the scenario of flat tariffs (table 7.16). This reform, however, will also have the largest impact on poverty as shown in table 7.15. To get to the prereform poverty and poverty gap levels, around JD 319 million will be required. Therefore, the net gain will be JD 158 million. Under the progressive subscenario, the costs of the transfer to compensate the poor will be smaller and the government will save about JD 174 million. In the third scenario with semiprogressive increase in tariffs, overall gain from higher tariffs will be JD 162 million. From this amount, JD 70 million have to be transferred back (assuming universal transfer) to bring poverty to prereform level and leaving the government with JD 92 million (table 7.17). 262 Table 7.16: Impact of Electricity Subsidy Reform on Government Expenditures, in JD million Scenario 2, full elimination Scenario 1, Scenario 3, Quintile of subsidies 2015 tariffs semiprogressive Flat Progressive 1 (poorest) −0 −64 −44 −14 2 −0 −77 −55 −19 3 −0 −87 −66 −25 4 −0 −102 −82 −33 5 (richest) −3 −143 −144 −71 Total −4 −473 −391 −162 Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; JD = Jordanian dinar; population quintiles based on consumption per capita before the reform. Table 7.17: Impact of Electricity Subsidy Reform on Government Expenditures, Correcting for Measures, in JD million Postreform Changea Scenario 2 Scenario 2 Scenario Scenario Scenario Progr Scenario Prereform Progre 1 Flat 3 1 Flat essiv 3 ssive e Subsidies 477 473 3 86 315 −4 −473 −391 −162 Transfersb 0 1 316 217 70 1 316 217 70 Total 477 473 319 303 385 −3 −158 −174 −92 budget Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; population quintiles based on consumption per capita before the reform. a. Negative values mean reduction in government expenditures or savings. b. Universal transfers assumed. <>Indirect Impact of Simulation of Subsidies Reform <>Petroleum Products The chapter now turns to the simulation of indirect effects of the rise in petroleum product prices combining a Jordanian input-output (I/O) table with HIES data. The baseline data for the producer price shocks are in table 7.18. The Jordan I/O table (2010) does not have disaggregated-by-type petroleum product statistics. Therefore, to capture the likely impact on economy-wide prices (of petroleum product subsidy removal), we use disaggregated production 263 figures from the state-owned refinery as an expectation proxy of the industry-wide petroleum- product mix. The gasoline shock to the petroleum sector is a price increase of 2.9 percent, which is equal to the change in price in gasoline (from table 7.6) multiplied by gasoline’s expected share (20.6 percent) in industry’s total petroleum product usage. Similarly, the diesel shock—at 10.5 percent—is equal to the change in price in diesel multiplied by diesel’s expected share in industry’s fuel mix.9 Table 7.18: Expected Producer Price Increase in Jordanian Fuel Sector Expected magnitude Price increase, pre- Expected share in of producer price to postreform period total industry fuel increase in fuel (%)a consumption (%) Product sector Gasoline 14 21 2.9 Diesel 33 32 10.5 Sources: Araar et al. 2013; Jordan Petroleum Co. LTD. annual report 2012; World Bank calculations. Note: See table 7.6 for prices. Results of the simulations (table 7.19) show that the relation between direct and indirect effects varies significantly across products and across quintiles. For example, indirect effects are approximately 77 percent of the total for diesel but only 14 percent for gasoline.10 The difference is directly attributable to household consumption patterns. Even though the diesel price increase is more than three times larger than the gasoline price increase and economy-wide prices rise more after the diesel subsidy is eliminated, households purchase so little diesel that they are almost unaffected directly. Any impact from higher diesel prices arrives indirectly through an increase in the price of the household consumption basket. For gasoline, the relative weight of indirect effects is also different across quintiles. The total indirect effect of the gasoline subsidy removal falls from about a third of total effects in the first quintile to about 12 percent for the upper quintile. This is understandable as the wealthiest quintile spends more than 10 times as much on gasoline directly as does the poorest quintile (see figure 7.3). Table 7.19: Direct and Indirect Impacts on Well-Being of Removing Petroleum Subsidies Quintile Diesel Gasoline 264 Total Total Share of Total Total Share of direct indirect indirect in direct indirect indirect (JD) (JD) total (%) (JD) (JD) in total (%) 1 (poorest) 0 3 100 2 0.9 30 2 0 5 100 6 1 17 3 0 6 100 10 2 14 4 0 8 100 15 2 12 5 (richest) 9 13 60 27 4 12 Total 2 7 77 12 2 14 Source: World Bank calculations based on extrapolated HEIS 2010 data and the Jordan 2010 input/output table. Note: HEIS = Household Expenditures and Income Survey; JD = Jordanian dinar. <>Electricity The simulations for indirect effects of electricity subsidy removal, similar to the petroleum product subsidy reform, were carried out by linking the Jordan I/O table to the HIES data.11 In average magnitude, the producer price shocks in the electricity sector are equivalent to a household-consumption–weighted average of the household price shocks (table 7.12).12 Simulation results indicate that the indirect effects of electricity price changes vary significantly by household rank (table 7.20). In absolute magnitude—in other words, in terms of JD—the indirect effects are approximately five times greater for the richest quintile than for the poorest. The reason is primarily that richer households have consumption baskets weighted more heavily with nonfood, electricity-intensive goods and services. Poorer households, in contrast, have consumption baskets weighted toward food, the production of which is not as electricity intensive. Results also indicate that the relation between direct and indirect effects varies significantly by the electricity subsidy elimination scenario. For example, in scenario 2.I, indirect effects are about a third of the total for the poorest households and close to half of the total for the richest households. In this scenario households consuming the highest electricity volumes see the smallest relative postreform electricity price increases, so it makes sense that the direct effect rises slowly across expenditure quintiles. In scenario 3 price increases are higher for higher volume users (richer quintiles), so the quintile-wide relationship between direct and indirect 265 effects is reversed: direct effects rise more quickly across expenditure levels than do indirect effects. In scenario 3, indirect effect shares are smaller for the richest quintile than for the poorest quintile. Table 7.20: Direct and Indirect Impacts on Well-Being of Removing Electricity Subsidies Quintiles, consumption per capita Scenario 2.I, flat Scenario 3 Total Total Share of Total Total Share direct indire indirect direct indire of (JD) ct (JD) in total (JD) ct indirec (%) (JD) t in total (%) 1 (poorest) 49 21 30 10 4 26 2 59 31 34 13 5 29 3 66 41 38 18 7 28 4 78 54 41 24 9 28 5 (richest) 109 102 48 58 17 23 Total 72 50 41 24 8 26 Source: World Bank calculations based on extrapolated HEIS 2010 data and the Jordan 2010 input/output table. Note: HEIS = Household Expenditures and Income Survey. <>The Political Economy of Reforms The simulations indicate that the current subsidy system provides valuable assistance to the poor, but at the same time are prorich and inefficient. Eliminating subsidies and compensating the poor and vulnerable with a direct cash transfer would be a more effective form of social protection. Subsidy reform, however, is a politically sensitive issue. A major reform of the bread subsidy in 1996 involving the complete elimination of the price support and its replacement by a cash transfer was rapidly overturned following widespread social unrest and what came to be known as "food riots." Thus, even as the government is burdened by high subsidy costs, its reform efforts are hampered by political economy considerations. The opposition to subsidy reform appears particularly strong in Jordan and Egypt, especially when compared with Lebanon and Tunisia (figure 7.5). Data from the MENA SPEAKS (Social Protection Evaluations of Attitudes, Knowledge, and Support) survey, indicate that about 56 percent of Jordanians were opposed to subsidy reform on any consumer item, be it electricity, food, petroleum products, or water (Silva, Levin, and Morgandi 2013). In all countries, the (self- 266 identified) lower-middle-income group is slightly less likely to oppose subsidy reform than the upper-middle and wealthy group, and in three of four countries the lower-middle-income group is slightly more willing to consider subsidy reform than the self-identified poor. Figure 7.5: Opposition to Reform Consumption Subsidy on Any Product 70 60 50 Percent 40 30 20 10 0 Poor Lower -middle Upper-middle and rich Egypt, Arab Rep. Lebanon Jordan Tunisia Source: Silva, Levin, and Morgandi 2013 calculations using the MENA SPEAKS survey. Note: MENA SPEAKS = Social Protection Evaluations of Attitudes, Knowledge, and Support. [[Typesetter: in figure 7.5: Chart area and legend: change values to black]] However, of those willing to consider subsidy reform (in the MENA SPEAKS survey’s Jordan sample), diesel was the most frequently cited candidate for reform, followed by subsidy on bread (figure 7.6). Electricity and LPG subsidies, which are much larger, appear to be even more politically sensitive than bread subsidies: only 11 percent of respondents were open to LPG subsidy removals, and a paltry 7 percent were willing to consider electricity reforms. These figures underscore the challenges the government faces. In fact, the government appears to be sensitive to such concerns, and the November 2012 reforms did not fully eliminate LPG 267 subsidies but did eliminate the subsidies on other petroleum products. It is interesting that the opposition to reforming expensive and regressive energy subsidies is stronger than opposition to food subsidies, which tend to be less regressive. A likely explanation for this finding is the relative importance of these energy products in the people's consumption baskets. Figure 7.6: Preferred Product for Inevitable Subsidy Removal 35 30 25 Percent 20 15 10 5 0 Gasoline Water Electricity LPG / gas Diesel Bread / cylinders flour Source: Silva, Levin, and Morgandi 2013 calculations using the MENA SPEAKS survey. Note: SPEAKS = Social Protection Evaluations of Attitudes, Knowledge, and Support. [[Typesetter: change bars to gray.]] These numbers raise the question as to how the November 2012 petroleum reforms went into effect without any significant public unrest. Silva, Levin, and Morgandi (2013) synthesize the vast literature in social protection to summarize the strategies that underscore successful reforms. First and foremost, they mention timing as the key to the success or failure of reforms. More specifically, they argue that it is easier to generate support behind a reform during a crisis, a situation that aptly characterizes Jordan. The population appeared to sense that Jordan was in fiscal crisis and petroleum subsidy removals were inevitable. Moreover, from initial episodes of hope, the social unrest eventually generated fear of violence, heightened by the experiences of neighboring Egypt and the Syrian Arab Republic. The subsidy reforms were likely aided by the strong aversion to the political and social instability that vocal opposition had the potential to generate. 268 Compensation of losers from reform also played a role in the reform’s apparent success. Although fiscal constraints often make it challenging for a government to provide direct compensation, the November 2012 reforms were accompanied by a generous cash transfer designed to fully compensate the bottom 70 percent of Jordanians for the losses suffered from the removal of subsidies. The cash transfer in fact appeared to overcompensate a large portion of the population (Araar et al. 2013). The speed with which the transfer took place is also a factor in the reform’s apparent success. The petroleum price hikes were announced on November 12, and within the next few weeks a large number of people started receiving the cash compensation. In enacting future reforms, the government can learn from its own experience. One concern arose regarding the targeting efficiency of the cash program accompanying the 2012 subsidy reforms (see, e.g., Araar et al. 2013). The government itself has taken measures to improve the targeting, specifically by setting up the National Unified Registry (NUR) database to better target beneficiaries for future cash compensation programs. Tackling electricity subsidy reform, however, appears to be daunting for the government because of its sheer scale. <>Conclusions This chapter examined the distributional and fiscal implications of petroleum and electricity subsidy reforms. Both subsidies are prorich in nature, and in absolute monetary terms, richer households benefit more than poorer households as their consumption levels are higher. These universal subsidies are costly and inefficient because a majority portion of the total subsidies "leaks” to the nonpoor households, and significant amounts actually leak to the richest quintile households. The analysis, however, also suggests that the poorer segments of the population benefit quite substantially from the subsidies and removal of subsidies would impose economic hardship on these groups. Nevertheless, as the government wishes to strike a balance between protecting its population from price increases and ensuring fiscal prudence, a move away from the universal subsidies system appears imperative. This move would require a considered analysis of both technical and political economy considerations. A generous cash transfer can be put in place to help build broad-based public support for reforming universal subsidies, but the government needs to target these transfers well through developing a sound social protection system. 269 Finally, it is important to note that although this chapter has presented several findings, the scope of analysis was necessarily constrained by time and data availability. The focus was limited to a microanalysis of household-level impacts. A more comprehensive analysis would involve broader sectors of the economy (such as nonhousehold users of petroleum products and electricity), and involve a political economy and stakeholder analysis to identify who would gain and who would lose from reform and how. <>Annex 7A Table 7A.1: Per Capita Benefit through Subsidies (in currency) Quintile Kerosene LPG Gasoline Diesel Total 1 (poorest) 2 28 2 0 32 2 2 34 6 0 42 3 3 39 10 0 52 4 3 47 15 0 65 5 (richest) 4 65 27 9 105 Average for all 3 43 12 2 59 products Source: World Bank calculations based on extrapolated HEIS 2010 data. Note: HEIS = Household Expenditures and Income Survey; population quintiles based on consumption per capita before the reform. Table 7A.2: Parameters Used for Extrapolation of Expenditures, Poverty Line, and Weights to Reflect Year 2013 GDP per capita growth CPI index, index, Population (millions) base 2010 Year 2010 base 2010 1.00 1.00 6.05 2011 1.04 1.07 6.18 2012 1.09 1.12 6.32 2013 1.15 1.19 6.46 Source: WDI 2014; and Jordanian Department of Statistics. Note: CPI = consumer price index; GDP = gross domestic product. <>Annex 7B <> 270 Box 7B.1: Construction of Weighted Price Increase on Electricity Construction of kilowatt per hour (kWh)-weighted price increases (table B7B.1) are calculated by multiplying the price increases for a particular bracket (available from table 7.13) by the kilowatt hour electricity consumption in that bracket (available from table 7.3) and then taking a weighted average of those by-bracket price increases. So under Scenario 2.I, for example, a household consuming in the third bracket (at 301–500 kWh per month) would see its expenditure go up by 160* 342 percent for its first 160 kWh; by 140*102 percent for its next 140 kWh consumed; and by 138*69 percent for its next 138 kWh consumed, where 138 kWh is the mean consumption in the third bracket (according to the Jordan HIES 2010) for a household in which total monthly electricity consumption falls into the third bracket range. Taking a kWh-weighted average of those three price increases yields a total price increase of 180 percent for such a household. Consumption-weighted price increases (table B7.1.1) are calculated by multiplying the kWh- weighted price increases for a particular bracket by the share of households whose monthly electricity consumption falls into that bracket’s range (available from table 7.4). So under scenario 2.I, for example, the share of households whose monthly consumption falls in the third bracket is 51 percent; multiplying that share by the total kWh-weighted price increase for consumption in the third bracket yields .91, or a 91 percentage point contribution to the total kWh-weighted, consumption-weighted price change. Total price increases in electricity are a simple sum of the consumption-weighted price increases. As such, total electricity price increases are a kWh-weighted, consumption- weighted average of by-bracket price increases, where the by-bracket price increases are those stated in table 7.13. Note: HEIS = Household Expenditures and Income Survey. Table B7.1.1: Construction of Electricity Price Increases under Subsidy Reduction Scenarios Scenario 2.I Scenario 3 Consumption- Consumption- Brackets, kWh-weighted weighted price kWh-weighted weighted price kWh/month price increase increase price increase increase 1–160 3.4 0.02 0.10 0.00 161–300 2.5 0.72 0.16 0.05 271 301–500 1.8 0.91 0.33 0.17 501–600 1.5 0.15 0.47 0.05 601–750 1.2 0.08 0.57 0.04 751–1,000 0.87 0.02 0.67 0.01 >1,000 0.65 0.00 0.73 0.00 Total 1.89 0.32 Source: Jordanian Department of Statistics. <>Notes 1. Quote from Harold Laswell’s seminal work Politics: Who Gets What, When, and How. 2. WBOPENDATA Stata ado (Azevedo 2013) was used to retrieve information on GDP per capita from the WDI database as of September 3, 2014. 3. SUBSIM simulates short-term effects, and November 2012 reforms were expected to kick in early in 2013. 4. GDP per capita growth and population size are taken from World Development Indicators, while CPI is based on official country numbers if different from WDI numbers. GDP per capita growth is used to inflate consumption, while CPI is used to inflate the poverty line. This procedure gives a poverty incidence of 13 percent for 2013 (lower than the official poverty estimate of 14.4 percent for 2010). Exact numbers used are shown in table 7A.2. 5. SUBSIM calculates quantity using updated expenditures into 2013 prices and prices of similar period. There is a risk of disparity between quantities from the household budget survey and utilities records (Lampietti, Banerjee, and Branczik 2007). Disparity may stem from data quality and usage of the current tariffs instead of effective tariffs applicable to the period of data collection in the survey. However, in case on Jordan this issue does not seem to be very important. First, electricity tariffs changed between 2010 and 2013 only for the top three brackets with less than five percent of population. Second, the consumption pattern changes based on elasticities anyway and the tariffs changes occurred in Jordan are a second order issue. Third, we compared estimated quantities across the HBS and administrative sources and the differences are reasonable and within the range we would expect given the different sources. 6. Masami Kojima is a lead energy specialist at the World Bank. 272 7. Strictly speaking the second subscenario does not fully eliminate subsidies because consumers from the first block continue to be subsidized, and tariffs on others are not raised by enough to offset this subsidy. 8. People in the third bracket also may be subsidized if their consumption in the third bracket is low. 9. The indirect impacts on households of these two producer price changes are calculated separately and independently, and holding fixed all other controlled producer prices—including those of the other petroleum products. Industry is not expected to use significant amounts of LPG or kerosene. 10. The most accurate estimates for direct effects remain those provided in the previous section, and we will disregard estimates of direct effects using I/O data. What is of interest here is the relative share of indirect effects over total effects. 11. The indirect impacts on households of these price changes are calculated holding all other controlled producer prices fixed. 12. See table 7B.1 and accompanying text in box 7B.1 for more details on the construction of the block- and consumption-weighted average electricity tariffs. <>References Araar, A., E. Le Borgne, U. Serajuddin, and P. Verme. 2013. “An Assessment of the Jordan 2012 Petroleum Subsidies Reform and Cash Compensation Program.” World Bank Report 79837. World Bank, Washington, DC. Azevedo, J. P. 2011. "WBOPENDATA: Stata module to access World Bank databases." Statistical Software Components S457234, Boston College Department of Economics. http://ideas.repec.org/c/boc/bocode/s457234.html. Coady, D., M. El-Said, R. Gillingham, K. Kpodar, P. Medas, and D. Newhouse. 2006. “The Magnitude and Distribution of Fuel Subsidies: Evidence from Bolivia, Ghana, Jordan, Mali, and Sri Lanka.” International Monetary Fund Working Paper WP/06/247. Kojima, M. 2014. Personal communication, August 28. 273 Lamis, A., and J. Schwedler. 1996. “Bread Riots in Jordan,” Middle East Report 201: 40–42. Lampietti, A., G. Banerjee, and A. Branczik. 2007. People and Power: Electricity Sector Reforms and the Poor in Europe and Central Asia. Washington, DC: World Bank. NEPCO (National Electricity Company). 2013. Amman, Jordan. Silva, J., V. Levin, and M. Morgandi. 2013. Inclusion and Resilience: The Way Forward for Social Safety Nets in the Middle East and North Africa. MENA Development Report, Washington, DC: World Bank. Verme, P. 2011. “Electricity Subsidies and Household Welfare in Jordan: Can Households Afford to Pay for the Budget Crisis?” Background paper for the Jordan Poverty Reduction Strategy. World Bank. 2009. Hashemite Kingdom of Jordan: Poverty Update. Volume II: Appendices. World Bank Report 47951-JO. World Bank, Washington, DC. WDI (World Development Indicators). 2014. September 3. World Bank, Washington, DC. 274 <>Chapter 8 <>Energy Subsidies Reform in the Republic of Yemen: Estimating Gains and Losses Aziz Atamanov <>Introduction The Republic of Yemen is one the poorest countries in the Middle East and North Africa (MENA) Region, with a gross domestic product (GDP) per capita of around US$ 3,959 in purchasing power parity (PPP) terms in 2013. The country went through a range of internal shocks, including civil war in 1994 and political unrest in 2011. In 2015 President Abd-Rabbu Mansour Hadi and the government resigned after a new spate of violence in the capital San<>a, and at present the country is at high risk of full-fledged sectarian conflict. The average economic growth rates were not exceeding 1.5 percent during the 10 years (2000–10) preceding the crisis in 2011, which led to a huge drop in real GDP by almost 13 percent (IMF 2014). Sluggish economic performance was accompanied by deteriorating social indicators and access to public services. Poverty is estimated to have increased from 35 percent in 2005 to 54 percent in 2011. Unemployment reached an unprecedented high of 35 percent in 2011 (World Bank 2012). Oil production and oil export revenues play a crucial role in the Republic of Yemen and compensate for the underperforming sluggish economy, but at the same time the country has become vulnerable to changes in oil output and oil prices. Oil reserves and products were declining, with severe fiscal implications exacerbated by the presence of generous fuel and electricity subsidies in the form of fixed domestic prices. For illustration, domestic prices on gasoline (super) and diesel were below the price of crude oil in 2012, as shown in figure 8A.1, indicating the high level of subsidies (GIZ 2012–13). Subsidies accounted for 7.2 percent of GDP in 2013 (IMF 2014). They absorbed a large part of fiscal revenues and crowded out urgently needed social expenditures. The government spent on fuel subsidies almost as much as on education, health, and social protection combined in 2009 (Breisinger, Engelke, and Ecker 2011). Subsidies benefited mostly the rich and created incentives for smuggling, corruption, and inefficient use of fuel. 275 Falling hydrocarbon revenues and the increasing fiscal deficit in 2014 urged the government to adjust fuel prices and initiate subsidies reform. Gasoline, kerosene, and diesel prices increased by more than 50 percent in August 2014, leading to mass protests in the capital San<>a. The government had to partially reinstate the fuel subsidies on gasoline and diesel. Currently, official fuel prices are at about 70 percent of the international level, and there is a plan to fully eliminate subsidies in 2015. This chapter explores the distributional and fiscal impacts of different reform options, including the increase in prices in August and focusing on fuel and electricity subsidies. Using the 2005 Household Consumption Survey, updated to 2013 prices, this chapter demonstrates how different groups of the population benefit from subsidies and how the costs of reforms are distributed among the groups. The chapter also discusses the gains to the government from removing subsidies and political economy issues. <>Evolution of Subsidies The state dominates the oil and gas sector in the Republic of Yemen and is involved in all parts of the oil and gas chain, including oil production, refining, distribution, and marketing of petroleum products. Private companies are involved in upstream oil exploration and production activities, the filling and distribution of liquefied petroleum gas (LPG) bottles, and the distribution of petroleum products. The state is also a major player in the electricity market. After unification of the country in 1990, the Public Electricity Corporation (PEC) was established. The PEC is a sole public utility with a mandate for the generation, transmission, distribution, and sale of electricity in the country (World Bank 2005). Subsidizing fuel products and electricity goes back to unification. The size of fuel subsidies has changed over time, reflecting changes in international fuel prices, exchange rates, consumption patterns, and domestic prices. As shown in figure 8.1, the share of government expenditures on subsidies varied from 14 percent in 2008 of GDP to 7.2 percent in 2013. At the same time, the share of revenues from hydrocarbon products was declining steadily from 29 percent in 2006 to 12 percent in 2013 (IMF 2010, 2014). Fuel subsidies put a strain on fiscal balance, accounting for 22 percent of the government budget in 2009.1 Spending on fuel subsidies is almost identical to the overall amount of budget expenditures spent on health, education, and social protection. For example, the share of health 276 in total expenditure was about 3.5 percent, and the share of social protection was about 2.7 percent in 2009. Increasing costs of fuel subsidies crowded out public investment program in infrastructure, which was crucial for long-term growth, economic diversification, and sustainable poverty reduction (Breisinger, Engelke, and Ecker 2011). Figure 8.1: Hydrocarbon Revenues, Subsidies, and Fiscal Deficit, in percent of GDP 35 30 Fiscal deficit 25 Percent of GDP 20 Hydrocarbon 15 revenues 10 5 Subsidies 0 -5 -10 2006 2007 2008 2010 2011 2012 2013 Source: IMF 2010, 2014. Note: GDP = gross domestic product. [[Typesetter: in figure 8.1: Chart area and legend: Use broken lines for the colored lines; gray for bars; X-axis: remove tick marks; Y-axis: change hyphens to minus signs.]] The government made many attempts to increase fuel prices to improve its fiscal position (box 8.1), but the situation did not improve. The fiscal deficit was still high, approaching 7 percent of GDP in 2013 (figure 8.1). With a substantial decline in oil revenues and fuel shortages, in 2014 the situation became unsustainable. The population did not have access to fuel products at subsidized prices, and black market prices outpaced international prices. The government decided to fully eliminate subsidies on three products in August: gasoline, kerosene, and diesel. Kerosene and diesel prices were expected to increase by 100 percent, and gasoline by 60 percent. In the wake of violent public protests, the government was dissolved, and subsidies were partially reinstated on diesel and gasoline. Prices on gasoline increased by 20 percent and diesel 277 by 50 percent (retail prices after the August reform are shown in figure 8.2). The government's plan to fully eliminate subsidies on fuel products, including LPG, in 2015, was stymied by civil war. <> Box 8.1: Changes in Fuel Prices and Mitigating Measures from 1995 to 2012 The government of the Republic of Yemen increased fuel prices by 75 percent in 1994, but benefits from this increase were wiped out by a huge depreciation of the local currency. The second increase in 1995–96 affected gasoline, diesel, kerosene, and LPG prices, but again in dollar terms prices remained at 1994 level. The third increase in prices took place in 2004 and affected only diesel prices. Overall, these reforms did not achieve the intended goal to remove the gap between domestic and international prices on fuel products. Initiated by the IMF and the World Bank, the next subsidies reform started in 2005 to maintain fiscal sustainability in light of falling oil reserves. The government increased fuel prices by about 130 percent on average, and new prices coincided with reforms in the taxation system. The violent protests that followed this reform forced the government to adjust the price increase, but prices still remained higher than they were before the reform. International commodity prices then increased, canceling out the initial success in price adjustments. Prices on gasoline, diesel, and kerosene were gradually increased by about 30 percent, and prices of LPG by 100 percent in 2010. In 2011–12 the government increased the price of gasoline by 66 percent and doubled the prices of diesel and kerosene. These increases in prices were not accompanied by public protests in 2010 and 2011. The most recent reform took place in July and September 2014. This reform, which aimed at fully removing fuel subsides and initially increased prices by 60 percent to 90 percent, was launched earlier (July) than planned (October), without an adequate public campaign as advised by the International Monetary Fund (IMF) and the World Bank (among others). As a result, the reform was partially reversed in September, under the pressure from sectarian groups and popular protests. The country's Social Welfare Fund (SWF) was established in 1996 to provide transfers to the poor. It has expanded from 100,000 beneficiaries in 1996 to 1.5 million in 2013. The fund has 278 the most comprehensive database of the poor and vulnerable population in the Republic of Yemen. The success in compensating the negative impact of subsidies reform was limited. Increasing monthly benefits and streamlining the application process took three years to be approved after the 2005 subsidies reform. In contrast, the coverage of the programs increased by half after the 2010 reforms. No mitigating measures were introduced during the 2011–12 reform episodes. Reforms in 2014 were also launched before a compensation scheme was designed and funded; the operation to help in this endeavor (funded by the World Bank and the U.S. Treasury) was approved in December 2014. In addition to transfers from the SWF, the Republic of Yemen has a Public Works Project that provides short-term employment and support for small-scale contractors through a labor- intensive public works program. Source: Part of this box is based on IMF 2013. <> Figure 8.2: Retail Prices on Fuel Products, 2003 and 2014 250 200 200 YRl per liter 150 150 2003 150 August 100 2014 54.7 50 35 10.2 16 17 0 LPG Gasoline Kerosene Diesel Source: IMF 2010, 2014. Note: GDP = gross domestic product; YRl = Yemeni rial. [[Typesetter: in figure 8.2: Chart area and legend: Use two shades of gray; 279 Delete numbers from the chart area. X-axis: remove tick marks; Background: remove box and gridlines.]] To mitigate potential adverse impacts of higher fuel prices on the poor, the government planned to increase the allocations for the Social Welfare Fund (SWF) by 50 percent starting in the last quarter of 2014 (IMF 2014). The World Bank is helping the government to improve the coverage and targeting of benefits. <>Distribution of Subsidies This section describes distribution of subsidies across households in the Republic of Yemen based on the 2005 Household Budget Survey (HBS), the most recent survey conducted by the country's Central Statistical Office and the World Bank.2 Descriptive and simulation analysis is done using SUBSIM software.3 <>Baseline Data Because the country's household budget survey used in this study is outdated, all information has been updated to 2013 prices.4 In particular, expenditures were inflated using nominal GDP per capita growth rates. The poverty line was inflated by the growth in consumer prices. Weights were also rescaled to reflect the change in the population size between 2005 and 2013. All input data is presented in table 8.1. After updating expenditures and the poverty line, the extrapolated poverty rate turned out to be 49.8 percent in 2013. This number is close to estimates in other studies that also documented substantial increases in poverty in the Republic of Yemen due to the economic and political turmoil in the considered period of time (World Bank, UN, EU, and IDB 2012). Table 8.1: Reference Statistics, 2005–13 Source Indicator 2005 2006 2007 2008 2009 2010 2011 2012 2013 GDP, per 1 capita (YRl billion) 159,313 181,981 240,764 279,782 259,695 298,151 285,127 288,241 316,554 280 GDP growth 1 (base 2005) 100.0 114.2 151.1 175.6 163.0 187.1 179.0 180.9 198.7 Population 2 (000) 20,140 20,662 21,539 22,198 22,864 23,584 24,312 25,066 25,843 Population 2 growth 106.9 110.2 113.5 117.1 120.7 124.5 128.3 (base 2005) 100.0 102.6 CPI (base 2 2005) 100.0 110.8 119.6 142.3 150.0 166.8 199.4 219.1 243.1 Sources: 1 = WDI; 2 = Central Statistical Office. Note: CPI = consumer price index; GDP = gross domestic product; 000 = thousand. Reconstructed population and expenditure figures for 2013 are shown in table 8.2. Total household expenditures are estimated to be around 5.271 billion Yemeni rials (YRls), which is equivalent to YRls 203,976 per capita. Households from the poorest quintiles have larger household sizes, and the richest households spent about six time higher amounts than households from the poorest quintile. Table 8.2. Baseline Population Data and Expenditure by Quintiles, in Yemeni rials Total Total Number of Household Total expenditures Quintile Population expenditures households size expenditures per per capita household 1 5,174,505 577,032 9.0 412,463,398,912 79,711 714,802 (poorest) 2 5,165,212 599,262 8.6 619,873,042,432 120,009 1,034,395 3 5,166,950 648,383 8.0 813,628,260,352 157,468 1,254,857 4 5,167,864 718,895 7.2 1,095,255,457,792 211,936 1,523,526 5 (richest) 5,168,179 897,907 5.8 2,330,065,895,424 450,849 2,594,996 Total 25,842,708 3,441,479 7.5 5,271,286,448,128 203,976 1,531,692 281 Source: World Bank calculation based on extrapolated HBS 2005. Note: HBS = Household Budget Survey. The analysis in this chapter covers four products: liquefied petroleum gas (LPG), gasoline, diesel, and electricity. The December 2014 unit prices and unit subsidies for the four products are shown in table 8.3. From the perspective of total expenditures, households spend almost equal amounts on LPG, gasoline, and electricity. Nevertheless, electricity is the most subsidized product. The unit subsidy accounts for about 80 percent of the unsubsidized unit price (cost recovery price) with households having low electricity consumption being subsidized the most. As a result, the most costly program for the government is associated with electricity subsidies, which is not surprising given that electricity production is based on highly subsidized mazut—a heavy low-quality fuel oil, which can also become diesel.5 In 2014 about YRl 320 billion were spent on electricity subsidies compared to YRl 26.4 billion spent on LPG and YRl 13.8 billion spent on gasoline. Subsidies on diesel are very small, but only because we consider only the diesel and gasoline expenditure spent on private cars. Wealthy farmers spend substantial amounts of gasoline on agriculture and water pumps, but these expenditures are not in included in welfare aggregate and not reflected here. Given the information presented, one may hypothesize that changes in prices on electricity can generate substantial changes in government revenues and have the strongest impact on households’ well-being if fully eliminated. The incidence of subsidies across the distribution can help to clarify this in the next section.6 Table 8.3: Subsidized Energy Products, December 2014 Unit HH Total subsidy Expenditures Unit Unit Unsub. subsidie Product Unit (% of on subs. price subsidy unit price s (YRl unsub. products (YRl billion) price) billion) LPG kg 109.1 47.7 156.8 30.4 60.3 26.4 282 Gasoline L 150.0 32.5 182.5 17.8 63.5 13.8 Diesel L 150.0 40.0 190.0 21.1 0.9 0.2 Electricity 54.7 319.3 0–200 kWh 6.9 57.6 64.5 89.3 201–350 kWh 12 52.5 64.5 81.4 351–700 kWh 14.1 50.4 64.5 78.1 701+ kWh 19 45.5 64.5 70.5 Sources: World Bank calculation based on extrapolated HBS 2005. Unit subsidies and prices are provided by Amir Althibah from the Yemen World Bank country office. Note: HBS = Household Budget Survey; HH = households; kg = kilogram; kWh = kilowatt hour; L = liter. Unit price for electricity is a weighted average for urban and rural areas: 0.7 weight is for urban areas and 0.3 weight is for rural areas. <>Distribution of Subsidies This section describes the importance of subsidies for households across the four products considered. Figures 8.3 and 8.5 show expenditure on subsidized products as shares of total expenditures.7 The household distribution of expenditures (in percentiles) is depicted on the x- axis; the poorest percentiles are on the left and the richer percentiles are on the right of the figures. The y-axis depicts expenditures on subsidized products. The curves with a negative slope imply that expenditures on subsidized products are more important for poor households than for rich households, and a positive slope implies that rich households spend higher shares of their budgets on subsidized products than do the poor. The amounts of subsidies in per capita terms across the distribution are shown in figures 8.4 and 8.6. This information is complementary to the information provided in figures 8.3 and 8.5 showing explicitly which group—rich or poor—receives the highest subsidies. Households spend slightly larger shares of their budgets on fuel products other than electricity (figures 8.3, panel a, and 8.4, panel a). In particular, Yemeni households spend on average 1.04 percent of their budgets on electricity compared to 1.14 percent on LPG and 1.2 percent on gasoline. In terms of the distribution, gasoline and electricity play a more important role in the 283 budgets of rich households. The poorest households spend only 0.2 percent of their expenditures on gasoline compared to 1.7 percent among the richest households. LPG, in contrast, is the only product with a slightly negative slope of the curve, meaning that it plays a slightly more important role for the poor than for rich households Figure 8.3. Share of Expenditures and per Capita Subsidies on Fuel Products across the Distribution a. Share of expenditures on fuel products in total b. Per capita subsidies on fuel products across the budget across the distribution distribution based on December prices, YRl .04 5000 LPG LPG gasoline gasoline diesel 4000 diesel Total benefits per capita .03 Expenditure shares 3000 .02 2000 .01 1000 0 0 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Percentiles (p) Percentiles (p) Source: World Bank calculation based on extrapolated HBS 2005. Note: HSB = Household Budget Survey. Figure 8.4. Share of Expenditures and per Capita Subsidies on Electricity across the Distribution a. Share of expenditures on electricity in total b. Per capita subsidies on electricity across the budget across the distribution distribution, YRl 284 80000 .015 Total benefits per capita 60000 Expenditure shares .01 40000 .005 20000 0 0 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Percentiles (p) Percentiles (p) Source: World Bank calculation based on extrapolated HBS 2005. Note: HBS = Household Budget Survey. [[Typesetter: for figures 8.3, 8.4: Add comma to numbers four digits and larger; Background: delete boxes and gridlines.]] The data on subsidies per capita across the distribution (figures 8.3, panel b, and 8.4, panel b) show that subsidies for all products favor the rich. The subsidies per capita on electricity are seven times higher for the richest households compared to the poorest; for gasoline and diesel the gap is 50 times higher.8 Even for LPG, which is the least prorich among selected products, subsidies per capita for the richest quintile are three times higher than subsidies per capita for the poorest quintile. A final observation from figures 8.3 and 8.4 is that, overall, the electricity subsidies per capita are much higher than the subsidies on fuel products. On average, households in Yemen receive YRl 12,356 in annual electricity subsidies, which is much higher than those they receive from fuel subsidies: YRl 1,020 for LPG and YRl 532 for gasoline. <>Simulation of Subsidies Reforms The purpose of the simulations in this section is to inform the current debate on subsidies in the Republic of Yemen by showing results for different scenarios. The main scenario is common to all chapters of the book: it implies the total elimination of subsidies and is based on December 2014 prices. This scenario provides an upper bound of the effects of this reform on the 285 government budget and on household welfare. Simulations are done separately for fuel products and electricity. In this chapter we focus only on direct effects of subsidy reform, which are the price and quantity changes that apply to the final consumer when subsidies on final products are changed. Simulation of indirect impact on prices of other goods was not possible due to the lack of input- output tables. Estimates of demand elasticity with respect to price are necessary to model consumer responses to price change. Given the limitations of having only cross-sectional household data with no variation in individual petroleum product prices across households, we used an own-price elasticity of −0.2 to simulate changes in quantities consumed. <>Fuel Products Tables 8.4 and 8.5 provide initial and final (unsubsidized) prices of fuel products for two simulation scenarios. The first scenario simulates the impact of the actual reform conducted in August 2014. Under this scenario, unit prices are the August 2014 prices, with the expectation of increasing 100 percent for kerosene, 20 percent for gasoline and 50 percent for diesel. Prices on LPG did not change. For the second scenario we simulate the full removal of subsidies based on December 2014 prices after the August reform. This is the main scenario to inform policy makers about the potential impact of the full removal of subsidies planned for 2015. As can be seen for gasoline and diesel, prices as of December 2014 were not so far from cost recovery. Full elimination of subsidies will imply increase in prices on diesel by 27 percent, on gasoline by 22 percent, and on LPG by 44 percent. Table 8.4: Scenario 1 for Fuel Subsidies Reform, August 2014 reform Unit Scenario 1, August 2014 Cost Product price, reform Unit recovery August price Unit price 2014 change, % Gas LPG kg 109.1 156.8 109.1 0 Gasoline L 100.0 182.5 150.0 50 286 Diesel L 125 190.0 150.0 20 Kerosene L 100 200 200.0 100 Source: Unit subsidies and prices are provided by Amir Althibah from Yemen World Bank country office. Note: kg = kilogram; L = liter. Table 8.5. Scenario 2 for Fuel Subsidies Reform, full elimination Unit price, Scenario 2, full removal Unit December Product Unit price 2014 change, % Gas LPG kg 109.1 156.8 43.7 Gasoline L 150.0 182.5 21.7 Diesel L 150.0 190.0 26.7 Source: Unit subsidies and prices are provided by Amir Althibah from Yemen World Bank country office. Note: Cost recovery prices for this simulation are shown in table 8.3. kg = kilogram; L = liter. Simulated impacts of fuels subsidies reform on poverty, inequality, and government revenues are presented in tables 8.6 and 8.7. Table 8.6 shows the simulated impact of partial subsidies reform conducted in August 2014. Consumption per capita is expected to drop by 0.6 percent on average with the negative impact being again strongest for the poorest households (−1.1 percent) as compared to the richest quintile (−0.5 percent). The increase in poverty will be about 0.4 percentage points, and inequality would increase by 0.1 percent. The most negative impact on the poorest households comes from increasing prices on kerosene, and the richest households are most affected by higher prices on gasoline. For illustration, consumption per capita is supposed to drop by 1.1 percent for the poorest quintile, and 96 percent of this decline comes from increasing prices on kerosene. In contrast, kerosene accounts only for 31 percent of overall decline in consumption for the richest 20 percent of the population, and the rest of the negative impact comes from higher prices of gasoline (table 8A1.3). 287 The August subsidies reform is estimated to save the government about YRl 34.5 billion if the population is not compensated for its losses. If universal subsidies were provided, government savings would shrink to YRl 10 billion. Table 8.6. Impact of Fuel Subsidies Reform in August 2014 on Poverty and Inequality August 2014 reform Prereform Postreform Change Welfare (per capita) 203,976 202,667 −1,309 Poverty (%) 49.8 50.2 0.4 Inequality (%) 35.9 36.0 0.1 Subsidies (in millions) 77,055 42,530 −34,524 Transfers (in millions) 0 24,524 24,524 Total budget (in millions) 77,055 67,054 −10,001 Source: World Bank calculation based on extrapolated HBS 2005. Full elimination of subsidies would reduce consumption per capita by 0.7 percent on average with the impact being relatively equal across quintiles. The poor are more affected by higher prices on LPG, while the negative impact from subsidies removal on gasoline is more pronounced for the richest households (table 8A1.4). This result is consistent with higher role of LPG for budgets of poor households. Poverty will increase by 0.5 percentage points after full elimination of subsidies, which could save the government about YRl 40.4 billion (table 8.7). If universal transfers are provided to keep the prereform level of poverty, most of the savings from subsidies reform would be required for this purpose, and overall savings for the government would be around YRl 9 billion instead of YRl 40.4 billion. If the government is able to target cash transfers to the poor to compensate for their losses in subsidies revenues, the costs would be slightly lower: YRl 29 billion instead of YRl 32 billion. Table 8.7. Impact of Full Elimination of Subsidies on Poverty and Inequality Based on December 2014 Prices 288 Full elimination of subsidies Prereform Postreform Change Welfare (per capita) 203,976 202,414 −1,562 Poverty (%) 49.8 50.3 0.5 Inequality (%) 35.9 35.9 0.0 Subsidies (in millions) 40,356 0 −40,356 Transfers (in millions) 0 31,631 31,631 Total budget (in millions) 40,356 31,631 −8,726 Source: World Bank calculation based on extrapolated HBS 2005. The trade-off between increases in poverty and government revenues for planned subsidies reform can be seen in figure 8.5 across two main fuel products. In particular, figure 8.5, panel a, shows increases in poverty by price increases between 1 percent and 100 percent. Figure 8.5, panel b, shows the impact on government revenues of price increases between 1 percent and 100 percent. Not all price increases are realistic and some can be well above the increases necessary to eliminate subsidies. The only purpose of this exercise is to show which product is the most promising in terms of positive impact on government finances while keeping poverty low. Consistent with larger shares in poor household budgets and high per capita subsidies, increasing prices on LPG have a stronger impact on poverty compared to gasoline, but at the same time they generate higher savings for the government. Government revenues stop growing after the price of gasoline increases by more than 20 percent and on LPG by more than 40 percent because they will reach the cost recovery level. Figure 8.5. Impact of Price Increase on Poverty and Government Revenues 289 a. Poverty impact of price increase of fuel b. Price changes of fuel products and impact on products government revenues 1.5 LPG 2.50e+10 LPG Impact on the governement revenue gasoline gasoline diesel diesel 2.00e+10 1 1.50e+10 .5 1.00e+10 5.00e+09 0 0 0 20 40 60 80 100 0 20 40 60 80 100 Increase in price in % Increase in prices (in %) Source: World Bank calculation based on extrapolated HBS 2005. Note: HBS = Household Budget Survey. [[Typesetter: in figure 8.5: Panel a., y-axis: change "headcount" to "head count"; In panel b: change x-axis to read "Increase in prices in %"; Background: delete boxes and gridlines.]] <>Electricity The Republic of Yemen uses an increasing block tariffs (IBT) system for electricity. This system implies progressive tariffs that charge a higher marginal price per kilowatt hour (kWh) for higher levels of energy usage. The four electricity brackets differ between urban and rural areas. For simulation purposes, an average weighted tariff was constructed (70 percent for urban and 30 percent for rural areas). Three different scenarios have been selected to simulate the impact of electricity subsidies reforms (table 8.8). The first scenario simulates full removal of subsidies. The second scenario simulates the impact on poverty and inequality of a new tariff structure with three brackets and progressive tariffs. The last scenario keeps the same tariff for the lowest bracket as in the second scenario, but extends the number of brackets to six (see also figure 8A.4). Increasing the number of brackets is expected to reduce the consumer surplus and increase revenues for the system without a substantial increase in poverty.9 290 Table 8.8: Old and New Proposed Tariffs for Electricity, by tariff brackets Scenario 1, Scenario 2, gradual Scenario 3, gradual Old tariffs and full increase with three increase with six blocks removal brackets brackets Tariff Unit Tariff Unit Tariff Unit Unit Unit price brackets price brackets price brackets price 0–200 kWh 6.9 64.467 0–200 9 0–200 9 201–350 kWh 12 64.467 201–700 19 201–240 17 351–700 kWh 14.1 64.467 701+ 30 241–280 19 701+ kWh 19 64.467 281–340 35 341–460 40 461+ 55 Source: Current tariffs are provided by Amir Althibah from the Yemen World Bank country office. Note: kWh = kilowatt hour. Unit price for electricity is a weighted average for urban and rural areas: 0.7 for urban and 0.3 for rural areas. Full removal of electricity subsidies leads to a huge increase in tariffs, with the highest increase for households with the lowest consumption of electricity. This result happens because prereform tariff structure was progressive, with the lowest tariffs for households at lower energy usage, and the change means the final price is flat for all households. The overall impact of full elimination of electricity subsidies on poverty is substantial, but still less than one could expect given the magnitude of the increase in prices because of the low share of expenditures on electricity in total household budgets, especially for the poor. Consumption per capita will drop by 6 percent on average, and poverty will increase by 4.8 percent. Inequality will also increase significantly by 0.2 percent because the increase in tariff is the highest for the poorest households with lowest consumption of electricity. 291 Full removal of subsidies is not a feasible option for policy makers to consider; instead, gradual and progressive increases in tariffs can be a more realistic scenario. Progressive electricity tariffs assume a direct relation between household welfare and electricity consumption. Indeed, there is a positive relationship between household expenditures and expenditure on electricity (figure 8A.6). As shown in table 8.9, a progressive increase in tariffs has a weaker negative impact on welfare compared to full removal of subsidies. In particular, having three brackets and progressive increase in tariffs in scenario 2 will increase poverty only by 0.3 percent and will generate about YRl 39 billion in government revenues after universal transfers. If the government wants to increase its gains from reform, the option of having six brackets with more progressive tariff scales will create a slightly higher increase in poverty (0.7 percent) and will bring higher savings—YRl 43 billion. Note that scenarios 2 and 3 will both reduce inequality because the increase in tariffs is highly progressive. 292 Table 8.9: Impact of Electricity Subsidies Reform on Poverty and Inequality Scenario 1, full removal Scenario 2, three brackets Scenario 3, six brackets Prereform Postreform change Postreform change Postreform change Welfare (per 203,976 191,620 −12,356 203,099 −877 201,835 −2,141 capita) Poverty (%) 49.8 54.6 4.8 50.1 0.3 50.4 0.7 Inequality (%) 35.9 36.1 0.2 35.9 0.0 35.7 −0.2 Subsidies 319,314 0 −319,314 263,574 −55,740 237,040 −82,274 (millions) Transfers 0 237,828 237,828 16,820 16,820 39,345 39,345 (millions) Total budget 319,314 237,828 −81,486 280,395 −38,919 276,385 −42,929 (millions) Source: World Bank calculation based on extrapolated HBS 2005. Note: HSB = Household Budget Survey. Compared to the impact of fuels subsidies reform, the negative impact on poverty from higher prices on electricity is comparable to the negative impact of higher prices on LPG (figure 8.6, panel a, versus figure 8.5, panel a). However, the government can save more from electricity subsidies reforms because the amount of electricity subsidies per capita is higher than subsidies on fuel product (figure 8.5, panel b, versus figure 8.6, panel b). Figure 8.6: Impact of Price Increase on Poverty and Government Revenues a. Poverty impact of price increase of electricity b. Price changes of electricity and impact on government revenues 293 1.5 1.00e+11 Impact on the governement revenue 8.00e+10 1 6.00e+10 4.00e+10 .5 2.00e+10 0 0 0 20 40 60 80 100 0 20 40 60 80 100 Increase in price in % Increase in prices (in %) Source: World Bank calculation based on extrapolated HBS 2005. Note: HSB = Household Budget Survey. [[Typesetter: in figure 8.6, panel a, y-axis, change "headcount" to "head count"; panel b, x-axis, delete the parentheses]] <>The Political Economy of Reforms Once adopted, subsidies are hard to remove. Usually countries have to conduct reform by piecemeal changes with constant reversals. Fear of loss of economic rents and political power are common factors behind reluctance to reform subsidies (Commander 2012). The Republic of Yemen was not an exception. In at least two occasions, increases in fuel prices caused violent public protests that led to a reversal of reforms. In this section, we discuss the factors affecting reform paths and try to identify the lessons learned. Modern Republic of Yemen was established in 1990 by uniting the Arab Republic of Yemen (YAR) and the People's Democratic Republic of Yemen (PDRY). The state-society social contract was very different under the two former states. Lack of resources made the population in YAR (north) unite along tribes, while in the PDRY (south) the state was much stronger and controlled by one party. Oil rents and political patronage allowed political powers to unite the country, changing the voice of different religious, regional, and tribal groups. One result was that elite groups captured the key sectors of the economy and less-powerful groups could benefit either from fuel subsidies or from the illegal trade of subsidized products. The patronage system created by petroleum products made the reform of subsidies on these same products politically very complex (World Bank 2005; Salisbury 2011). 294 Falling oil production after 2000 and the poor performance of non-oil sectors shrank the resource base and contributed to the evolving political, social, and economic crises that culminated in the 2011 protests and the departure of President Ali Abdullah Saleh in 2012. The United Nations and the Gulf Cooperation Council have helped to bring about a peaceful transition in the Republic of Yemen, but the situation is still very fragile and has not yet been resolved. The success of subsidies reform depends on timing, institutional capacity, communication campaigns, and the overall micromanagement of reforms. In the Republic of Yemen, the failure of the 2005 subsidies reform seems to be associated with bad timing because it coincided with tax reforms. The compensation scheme designed to accompany price increases could not work because it took almost three years to increase the size of benefits. If the cash transfer program had been implemented on time, it could have reduced the opposition to reforms and increased the likelihood of success. The increase in energy prices in 2010 and 2011 happened in the context of abrupt changes in supply and retail prices in the black market higher than international prices. An effective public campaign kept the public informed the public about the benefits of reforms to ensure adequate supply (IMF 2013). As a result, these episodes of subsidies reforms were not accompanied by public protests and violence. Given that the amount of subsidies depends on international commodity prices and that subsidy is a politicized topic, international organizations proposed a system of automatic fuel prices adjustment. Such a measure may help to depoliticize the process of energy pricing, avoid drastic changes in domestic prices, and allow governments to preserve and increase the savings from a subsidy reform when international prices go up (IMF 2014). <>Conclusions The Republic of Yemen is going through a very difficult political and socioeconomic crisis, and the current level of subsidies makes the fiscal situation unsustainable. The country partially removed subsidies on fuel products in 2014 and planned to fully eliminate subsidies in 2015. This chapter explored the distributional and fiscal implications of fuel and electricity subsidy reforms in Yemen. Electricity is the most subsidized product and accounts for the largest share of overall subsidies. In contrast, in terms of share of total expenditures, gasoline and diesel are relatively more 295 important. The distributional analysis shows that only kerosene subsidies are pro-poor, and that subsidies for other products are prorich, meaning that richer households benefit more from these subsidies compared to poorer households. Nevertheless, poor households still spend substantial shares of their budgets on subsidized products, which implies that the removal of subsidies would impose economic hardship on these households. In particular, the simulation shows that increases in prices on gasoline, kerosene, and diesel in August 2014 are expected to increase poverty by 1.3 percentage points and reduce household consumption by 3 percent. Further removal of the remaining subsidies on LPG, diesel, and gasoline planned for 2015 are expected to generate a slightly less negative impact increasing poverty by 1.1 percentage points. Full removal of subsidies on electricity is not a feasible option to consider. The huge increase in tariffs, especially for poor households, would increase poverty by 4.6 percent. A more realistic reform would be a progressive increase in tariffs partially removing electricity subsidies, which is expected to increase poverty either by 0.4 percentage points (using three brackets) or by 0.7 percentage points (using six brackets). One benefit of having more brackets is higher government revenues, which are estimated to be almost identical to savings from the full removal of subsidies. In terms of the political economy of subsidies reform, several important lessons can be learned from the Republic of Yemen's experience in reforming subsidies. The successful implementation of subsidies reforms depends crucially on the right timing and a sound compensation scheme with targeted benefits. In addition, adequate public campaigns are needed to inform the public about the benefits of reforms. Finally, introducing automatic adjusting mechanisms of domestic prices to international commodities prices by law may reduce the politicians’ ability to manipulate prices. <>Annex 8A Table 8A.1: Annual Per Capita Consumption of Fuel Products, in quantity Quintile LPG (kg) gasoline (liter) diesel (liter) 1 (poorest) 12.15 4.24 4.82 2 17.17 19.42 7.73 3 20.99 28.63 17.60 296 4 24.84 63.60 47.10 5 (richest) 31.78 211.74 152.83 Total 21.39 65.52 46.01 Source: World Bank calculation based on extrapolated HBS 2005. Note: HSB = Household Budget Survey. Table 8A.2: Annual Per Capita Consumption of Electricity, in kWh Quintile Electricity (kWh) 1 (poorest) 72.64 2 127.06 3 174.76 4 247.11 5 (richest) 500.44 Total 224.39 Source: World Bank calculation based on extrapolated HBS 2005. Note: HSB = Household Budget Survey; kWh = kilowatt hour. Table 8A.3: Impact on Well-Being of Fuel Subsidies Reform in August 2014, in percent Quintile Kerosene LPG Gasoline Diesel Total 1 (poorest) −1.0 0.0 0.0 0.0 −1.1 2 −0.7 0.0 −0.1 0.0 −0.8 3 −0.5 0.0 −0.2 0.0 −0.7 4 −0.4 0.0 −0.2 0.0 −0.6 5 (richest) −0.2 0.0 −0.3 0.0 −0.5 Total −0.4 0.0 −0.2 0.0 −0.6 Source: World Bank calculation based on extrapolated HBS 2005. Note: HSB = Household Budget Survey. 297 Table 8A.4: Impact on Well-Being of Full Elimination of Fuel Subsidies , in percent Quintile LPG Gasoline Diesel Total 1 (poorest) −0.73 −0.04 0.00 −0.77 2 −0.69 −0.14 0.00 −0.83 3 −0.62 −0.16 0.00 −0.79 4 −0.56 −0.23 0.00 −0.80 5 (richest) −0.34 −0.38 −0.01 −0.72 Total −0.50 −0.26 0.00 −0.77 Source: World Bank calculation based on extrapolated HBS 2005. Note: HSB = Household Budget Survey. Figure 8A.1: Retail Prices on Diesel and Super Gasoline in the Republic of Yemen Compared to the Price of Crude Oil in the World Market, 2012 80 69 70 60 58 US-cents/liter 50 47 40 30 20 10 0 1998 2000 2002 2004 2006 2008 2010 2012 Diesel, US-cents/liter Super Gasoline, US-cents/liter World crude oil price in 2002 Source: GIZ 2012–13. [[Typesetter: in figure 8A.1: Chart area and legend: Use broken lines instead of colored lines; Y-axis and legend: change "US-cents" to "$0.01"; Remove numbers from chart area. Background: remove box.]] 298 Figure 8A.2: Share of Expenditures on Fuel Figure 8A.3: Per Capita Subsidies on Fuel Products in Total Budget across the Products across the Distribution Based on Distribution August Prices .04 kerosene 10000 kerosene LPG LPG gasoline gasoline Total benefits per capita .03 8000 diesel Expenditure shares diesel 6000 .02 4000 .01 2000 0 0 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Percentiles (p) Percentiles (p) Source: World Bank calculation based on extrapolated HBS 2005. Note: HSB = Household Budget Survey. Figure 8A.4: Different Electricity Tariff Structures, in Yemeni rials 60 50 40 30 YR 20 10 0 1 100 200 270 340 430 510 610 701 kWh per month 6 brackets 3 brackets prereform Source: World Bank compilation. Note: kWh = kilowatt hour; YR = Yemeni rial. [[Typesetter: in figure 8A.4: Chart area and legend: Use patterned lines instead of colored lines; Change "prereform" to "Prereform" Y-axis: change "YR" to "YRls"]] 299 Figure 8A.5: Distribution of Households by Figure 8A.6: Expenditures on Electricity Tariff Brackets versus Total Consumption per Capita 100 100 Expenditure percentiles 80 80 Households (%) 0-200 60 60 201-350 351-700 40 40 20 20 0 0 0 250 500 750 1000 1250 1500 1750 2000 200 400 600 800 kWh per month Mean expenditure on electricity Source: World Bank calculation based on extrapolated HBS 2005. Note: HSB = Household Budget Survey; kWh = kilowatt hour. [[Typesetter: In figure 8A.5: Y-axis: turn the numbers to be right reading; X-axis: add commas to 4-digit or higher numbers; Chart area: change the vertical lines to black; Background: for 8A.5 and 8A.6, delete gridlines and boxes.]] <>Notes The author thanks peer reviewer Guido Rurangwa (senior country officer) and Paolo Verme (task team lead) for their useful comments and suggestions on how to improve the chapter. The author also thanks Lire Ersado, Jianping Zhao, and Amir Mokhtar Althibah for their advice and help. 1. Electricity production benefits from fuel subsidies because the Public Electricity Corporation purchases mazut, diesel, and natural gas at subsidized prices compared to domestic and international prices (Vagliasindi 2014). 2. A new household budget survey is in the field in the Republic of Yemen, and the plan is to have welfare aggregate in the middle of 2015. 3. SUBSIM is freely available to download from www.subsim.org. 300 4. Updating to 2014 prices would be preferable, but would require finalized information on prices, population, and GDP per capita growth, which were not available at this writing. 5. For illustrative purposes, the subsidy on mazut used for electricity was higher than 4.5 times than retail price. Overall, the cost recovery price is about 0.3 cents per kwh, which is much higher than usually considered adequate to cover most of capital costs of 0.08 cents per kwh (Kamives et al. 2005). 6. Expenditures on diesel and gasoline were obtained from data private cars' weekly diaries. To separate them into expenditure on diesel and gasoline we used information on road sector gasoline and diesel consumption in the Republic of Yemen in 2009 from www.tradingeconomics.com. According to this website, diesel consumption in the country was 43 kiloton of oil equivalent, and gasoline consumption was 1,530 kiloton of oil equivalent in 2009. Using information on prices, share of diesel expenditures was about 1.4 percent, and it was applied to fuel expenditure on private cars from household budget survey. 7. Figures 8.3 and 8.5 were replicated for fuel products, including kerosene, and based on August 2014 prices. Results are shown in the annex. The role of fuel products in household budget does not change. The only important addition is that kerosene was more important for the poor than for the rich and subsidies on this product were pro-poor. 8. It is also important to remember that many poor households in the Republic of Yemen do not have access to electricity. 9. Issues with practical implementation of extending the number of brackets are beyond the scope of this paper. <>References Breisinger, C., W. Engelke, and O. Ecker. 2011. "Petroleum Subsidies in Yemen Leveraging Reform for Development." Policy Research Working Paper 5577. World Bank, Washington, DC. Commander, S. 2012. "A Guide to the Political Economy of Reforming Energy Subsidies." IZA (Institute for the Study of Labor) Policy Paper 52, Bonn, Germany. 301 GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit, Federal Ministry for Economic Cooperation and Development). 2012–13. International Fuel Prices 2012/2013. Eighth edition. IMF (International Monetary Fund). 2010. "Republic of Yemen: Request for a Three-Year Arrangement Under the Extended Credit Facility—Staff Report," Press Release on the Executive Board Discussion; and Statement by the Executive Director for Yemen. IMF Country Report 10/300. International Monetary Fund, Washington, DC. ———. 2013. "Case Studies on Energy Subsidy Reform: Lessons and Implications." International Monetary Fund, Washington, DC. ———. 2014. "Republic of Yemen Staff Report for the 2014 Article IV Consultation and Request for a Three-Year Arrangement under the Extended Credit Facility." IMF Country Report 14/276. International Monetary Fund, Washington, DC. Komives, K., V. Foster, J. Halpern, and Q. Wodon. 2005. Water, Electricity, and the Poor: Who Benefits from Utility Subsidies? Directions in Development Series. Washington, DC: World Bank. Salisbury, P. 2011. "Yemen’s Economy: Oil, Imports and Elites." Middle East and North Africa Programme Paper 2011/02. London: Chatham House. Vagliasindi, M. 2014. Implementing Energy Subsidy Reforms: Evidence from Developing Countries. Directions in Development Series. Washington, DC: World Bank. World Bank. 2005. "Household Energy Supply and Use in Yemen." Energy Sector Management Assistance Program Working Paper ESM 315/05. World Bank, Washington, DC. http://documents.worldbank.org/curated/en/2005/12/6743106/household-energy-supply- use-yemen-vol-1-2. ———. 2012. "Republic of Yemen Joint Social and Economic Assessment." Report 69388-YE. World Bank, Washington, DC. World Bank, UN (United Nations), EU (European Union), and IDB (Islamic Development Bank). 2012. Joint Social and Economic Assessment for the Republic of Yemen. Washington, DC: World Bank. 302 303 <>Chapter 9 <>Djibouti: Subsidies, Tax Exemptions and Welfare Stefanie Brodmann and Harold Coulombe <>Introduction Djibouti is one of the smallest countries in Africa. It covers an area of 23,200 square kilometers and is home to a population of fewer than 900,000. The country is almost a city-state with 80 percent of the population living in the capital, Djibouti City. The rural population mainly consists of poor pastoral and nomadic peoples who sparsely occupy the hinterland, an extension of the deserts of Ethiopia and Somalia. As in other small states, the size of Djibouti’s economy limits its ability to diversify production and increases its reliance on foreign markets, making it more vulnerable to external market downturns and hampering access to external capital. With less than 1,000 square kilometers of arable land (4 percent of the country’s total land area) and an average annual rainfall of 130 millimeters, Djibouti depends completely on imports to meet its food needs. Although Djibouti's economic outlook is generally favorable, significant risks to growth remain. Economic growth, which averaged 4.5 percent per year during 2009–12, was projected to reach 5 percent in 2013 (World Bank 2014). Growth is driven by strong foreign direct investment (FDI) inflows and public investment. Transport and logistics, such as transit trade with Ethiopia and transshipment activities, are the backbone of Djibouti’s economy, with port activities contributing almost 20 percent to its gross domestic product (GDP). However, Djibouti is left vulnerable to major risks to growth and macroeconomic stability including fuel and food price shocks and natural disasters such as droughts and floods. Poverty has been exacerbated by drought conditions since 2007—the worst in 60 years. The drought is estimated to have affected at least half the rural population, with annual economic losses of 3.9 percent of GDP over the period 2008–11 and a substantial flow of refugees from neighboring countries that also suffer from drought. With its strategic location in the Horn of Africa and at the southern end of the Red Sea, Djibouti is affected by adverse economic or security developments in neighboring countries. Domestic social and political instability also present potential risks to growth. Djibouti’s external position has deteriorated as a result of a significant increase in the level of 304 imports. The current account deficit is estimated to have widened to about 13.1 percent of GDP in 2013 from 5.1 percent in 2010. Imports grew by 18 percent per year on average, in nominal terms, during 2011–13, as compared to 13 percent for exports. This deficit has been financed in part by significant FDI inflows, which were expected to rise from 2.4 percent of GDP in 2010 to 18.6 percent in 2013. Djibouti requires significant reserves for imports of food, fuel, and manufactured goods. The real effective exchange rate fell by about 4 percent in 2011–12, as declining food and fuel prices led to lower inflation (World Bank 2014). Universal tax exemptions were introduced in response to the food crisis and to shield the population from price shocks on essential food products. Djibouti depends massively on imports to meet its food needs, and a large fraction of the population faces food insecurity. Practically all food items are imported, and increases in international food prices directly affects Djibouti’s poor people, who spend up to three-quarters of their income on food. Due to severe and prolonged droughts, at least 20 percent of the capital’s population and three-quarters of rural households are vulnerable to moderate to severe food insecurity, according the Emergency Food Security Assessment carried out by the World Food Programme in 2013. In response to the stark food price increases, the government has exempted five essential food items from domestic consumption tax since 2008. According to estimates of the International Monetary Fund (IMF), Djibouti forgoes 0.5 percent of GDP (2009) on rice, edible oil, sugar, flour, and powdered milk. Similarly, discretionary price adjustments on certain energy products, such as gasoline (super) kerosene, and diesel, have been in operation since 2009. The government’s Department of Customs and Excise, after consultation with oil companies, operates a monthly adjustment of prices at the pump to minimize the negative impact of fluctuating international prices of super, kerosene, and diesel. According to estimates of the IMF, Djibouti forgoes an estimated 2 percent of GDP (2011) on certain energy products (De Broek, Kangur, and Kpodar 2012). The findings in this chapter are part of a broader dialogue on energy tax reform and the effort to strengthen social safety nets in Djibouti. As part of a possible reform of energy taxes, the government of Djibouti has sought the support of the World Bank to better understand how such a policy reform can be pro-poor.1 Untargeted tax exemptions reach a wider part of the population than targeted programs, but have high benefit leakage and are regressive compared to some targeted transfers that appear generally 305 more progressive. Tax exemptions on basic food items reach the majority of the poor and nonpoor, with close to 95 percent of the population benefiting. In contrast, targeted programs, such as food rations and cash transfers, generally benefit the rural population and the poor. More than half of the transfers for food rations are received by the poor (bottom quintile), and almost 80 percent of beneficiaries are in the bottom two quintiles and live in rural areas (84.2 percent of benefits received). In contrast, the population living in urban areas receive the majority of tax exemptions on food and fuel products, 85 percent and 97 percent, respectively. The majority of these beneficiaries are from the richest two quintiles, 56 percent and 87 percent, respectively, making these programs regressive. Only 15 percent of the tax exemption benefits on food and less than 3 percent on fuel go to beneficiaries living in rural areas, and only 10 percent and less than 1 percent, respectively, are received by those in the poorest quintile. The government of Djibouti is currently considering abandoning the use of the discretionary tax, which can be either positive or negative, on retail prices of fuel. As of December 2013, such a reform would result in a small drop in gasoline and kerosene prices, but an increase of around 13 percent for diesel. Therefore, it is likely that a jump in fuel costs brought about by the abolition of the discretionary tax could lead to higher ticket prices for public transport. Combining the possible increase in diesel prices (12.5 percent), relative to the level in December 2013, with a fuel cost share of 30 percent suggests that an increase in the cost of passenger fares of 4 percent would be justified to allow bus companies to pass on the effects of the higher fuel prices to passengers. In fact, car ownership and utilization of public transport is a strong indication of welfare. One-fourth of the richest quintile owns a car, and car ownership is basically negligible in the other quintiles. In addition, only 10 percent of the poor use public transport (buses, taxis, and school buses) compared with almost 60 percent in the richest two quintiles. The next section provides a short summary of the evolution of subsidies, followed by an overview of the distribution of various fuel and food products by welfare quintiles. The following section presents simulations that eliminate the discretionary tax elements on fuel (super and diesel) and food products and shows the potential impact of this removal on household welfare and government budget. The final sections discuss reform options, show the result of different simulations on the welfare effects of various reform options on poverty head count and poverty gap, and offer conclusions. 306 <>Evolution of Subsidies Djibouti relies entirely on imports for its supply of petroleum products. All imports come through Djibouti port. Of these imports a substantial portion is re-exported, with large volumes in transit to Ethiopia. A large fraction of the net imports are destined for foreign armies with bases in Djibouti, for international airlines, and for maritime transport. Although there are no official figures for imports and consumption of petroleum products, a recent study for the government of Djibouti surveyed all parties involved in the import and sale of petroleum products and produced reconciliation for 2012. The resulting data are shown in table 9.1 and indicate that diesel dominates domestic consumption. The same study also presented a forecast of domestic consumption until 2017. Diesel is expected to reach 91 million liters; kerosene, 17 million liters; gasoline, 9 million liters; and fuel oil, 8 million liters. These figures indicate that the change in taxation of diesel will be particularly important in terms of government revenue. The domestic consumption of petroleum products is divided between households and businesses that pay all taxes and duties and a number of parties, such as certain businesses, embassies, and the Republican Guard, that receive some tax exemptions. Table 9.1: Imports and Domestic Consumption of Petroleum Products by Djibouti in 2012 (million liters) Total imports 530 Re-export 283 Consumption by foreign military, airlines, and shipping 163 Domestic consumption: 84 Diesel (gasoil) 61 Gasoline (super) 6 Kerosene (pétrole lampant) 11 Fuel oil 6 Source: Capgemini Consulting April 2014. Fuel prices, especially of gasoline, are higher in Djibouti than in neighboring countries. Transportation fuel prices in Djibouti can be compared to those from other non-oil-producing countries in the region in 2012. With the exception of Eritrea, prices in Djibouti, especially for gasoline, were higher than neighboring countries (table 9.2). The higher prices are due to the small size of the domestic market, resulting in loss of economies of scale. Diesel prices are 307 nearer to those of neighboring countries, in part due to discretionary tax offsets that have been used for diesel. Table 9.8: Prices of Transportation Fuels in 2012 (US$/liter) Country Gasoline (super) Diesel (gasoil) Djibouti 1.8 1.2 Eritrea 2.5 1.7 Ethiopia 1.1 0.9 Kenya 1.4 1.3 Lebanon 1.1 0.9 Tanzania 1.3 1.3 Source: GIZ: 2012–13. The retail prices of petroleum products in Djibouti are regulated by the Ministry of Budget according to a formula that includes predetermined and discretionary elements (costs and taxes). In 2009 the government signed a memorandum of understanding with the oil companies that allows for a monthly review of the complete price and cost structure. Costs include an import component and various domestic items. The allowable amounts for domestic costs are changed occasionally, and tax rates are fixed except for a discretionary component (ajustement en faveur de l’Etat) that is used to smooth out fluctuations in retail prices that would otherwise be caused by fluctuations in the import cost. This component can be either positive (extra tax) or negative (tax offset). The exact determination of the smoothed retail price is not made according to a formula; rather, it depends on judgments made by the government. In principle, such an approach to smoothing out import cost fluctuations could result in no additional long-run net benefit or cost to the government. At times, however, the discretionary component has been negative (because of the low final retail price set by the government) and produces tax revenues persistently below the amount that would have resulted from the application of the nondiscretionary tax structure. The government is now considering abandoning the discretionary tax component so that retail prices would be predictably linked to the allowable costs and the import cost of the products. This change would mean that the full tax revenue implied by the formula would be collected from 308 retail sales. At present, kerosene is provided through two routes, yielding the same retail price due to a discretionary tax element. In addition to the established marketing of kerosene, the government has made an arrangement with the SDVK (La Société de Distribution et de Vente de Kérosène) to sell and distribute kerosene nationwide (although at present it serves only Djibouti City and suburbs). The government allows the SDVK to include a fee in the price charged to build its network and exempts the price from the domestic consumption tax (TIC) and the value-added tax (VAT). The price does include a discretionary tax element so that the retail price of this kerosene supply is the same as the general retail price of kerosene. <>Determination of the Retail Price The various components of the pricing formula are set by the government in agreement with the oil companies. Table 9.3 illustrates the structure of the gasoline retail price (De Broek, Kangur, and Kpodar 2012). The price for delivery at Djibouti port is set as follows. <>  Free on board (FOB) prices in international markets are collected monthly, as averages of daily FOB prices for the preceding month quoted in Platt’s Oilgram Price Report. An exporter’s margin, cost of shipping and insurance, and port fees are added. The commercial margin is updated every six months based on invoice information about actual FOB prices paid by oil companies in the preceding six months.  Duties and taxes include TIC and VAT at rates set by legislation—currently 26 percent and 7 percent, respectively. Excise duties are set by legislation, and royalties are determined annually in the budget.  The transport, operational, and storage costs and the commercial margins of distributors and service station operators are set by the government. These charges can be changed after discussion with the relevant parties.  A discretionary tax component is used to smooth out retail prices in the face of volatile FOB costs and to reduce inflationary pressure on low-income households in times of rising international prices. This component varies each month and is calculated so as to produce a desired retail price linked to the other costs by the formula. 309 <> Table 9.9: Price Build-up for Retail Gasoline, in DF Category DF PF (FOB price) 137.57 MF (maritime freight) 3.24 EM (exporters margin) 4.36 PF+MF+EM=PC (CIF price) 145.18 SE (extra storage cost) 2.60 FP (port fees) 0.68 PC+SE+FP=PP (price at port) 148.46 TC (domestic consumption tax) = 0.26 * PP 38.60 TE (excise duty) 49.50 TR (royalty) 32.13 TD (discretionary tax adjustment) 5.84 DD (various distribution costs) 11.65 PP+TC+TE+TR+TD+DD=PV (price subject to VAT) 286.18 TV (VAT) = 0.07* PV 20.03 CT (terminal transport cost) 1.76 PV+TV+CT=PS (price received at service station) 307.98 RM (retail margin) 7.02 PS+RM= PR (retail price) 315.00 Source: Ministry of Budget. Note: The price buildup for retail gasoline is illustrated with the case of gasoline (super) for December 2013 (December 11, 2013–January 10, 2014) in Djibouti francs (DF) per liter. The regulated prices for petroleum products sold to special groups also allow for various exemptions on taxes, and these exemptions are expected to continue so that tax revenue from these groups is lower than that from the purely retail market. Such groups include the French military (50 percent exemption on domestic consumption tax and 50 percent exemption on excise duties); exempt businesses (zero domestic consumption tax and zero excise tax); embassies and domestic security forces (zero domestic consumption tax, zero VAT, zero excise tax, and zero royalty). The effect of these exemptions is to forgo tax revenue that would 310 otherwise have accrued to the budget had the products been sold at the same price as to the general public. The government has entered into an arrangement with the SDVK to sell and distribute kerosene to make it more widely available. A service fee was included in the price markup on top of other port and distribution charges. To encourage the company to set up the network required to expand the market for kerosene, the government exempted this kerosene from the TIC, excise duty, and VAT. A royalty was charged, and the discretionary tax was set so as to bring the retail price to the same level as the charge for the traditional method of selling kerosene. Table 9.4 shows the retail prices and discretionary tax elements for 2013. The data for gasoline prices illustrate how the retail price was smoothed by varying the discretionary tax through the year. In January 2013 the adjustment was negative, indicating that the government was holding down retail prices by forgoing a certain amount of tax revenue. By the end of the year, the retail price had risen slightly, but the discretionary tax had become positive, indicating that the government was now collecting some extra tax revenue. For diesel, the government was forgoing a certain amount of tax revenue throughout the year to hold retail prices down. It is important to note that the government during this period was still a net recipient of tax revenue from diesel as “other taxes” were much larger that the negative discretionary tax. For kerosene, the government collected some tax revenue through royalty as well as a small amount from the (positive) discretionary tax. The net effect of this sales arrangement for kerosene was that the total tax revenue per liter was much lower than for gasoline and for diesel. Table 9.4: Retail Prices and Discretionary Taxes for Petroleum Products in 2013 (DF/liter) Month Gasoline Kerosene (SDVK) Diesel Discretionary Tax Discretionary Tax Discretionary Tax Other Taxes Other Taxes Other Taxes Retail Price Retail Price Retail Price FOB Price FOB Price FOB Price January 139.2 310.0 - 141.7 137.6 195.0 8.68 7.00 135.0 210.0 - 75.40 7 0 11.47 0 6 0 8 0 28.47 February 139.2 310.0 - 141.7 142.0 195.0 4.29 7.00 139.7 210.0 - 76.65 7 0 11.47 0 2 0 9 0 34.44 March 139.2 310.0 - 141.7 148.6 200.0 2.61 7.00 146.4 215.0 - 78.69 7 0 11.47 0 5 0 6 0 38.23 311 April 142.5 310.0 -5.90 140.5 136.3 190.0 5.04 7.00 135.4 210.0 - 75.51 8 0 9 1 0 4 0 28.92 May 142.5 310.0 -5.31 141.2 128.2 190.0 13.12 7.00 127.9 210.0 - 73.57 8 0 6 9 0 8 0 19.46 June 137.5 310.0 1.17 139.9 127.8 190.0 13.53 7.00 128.4 210.0 - 73.70 7 0 4 8 0 7 0 20.08 July 137.5 310.0 1.17 139.9 129.5 190.0 11.88 7.00 131.4 212.0 - 74.60 7 0 4 2 0 4 0 21.98 August 137.5 315.0 5.85 140.2 134.8 195.0 11.47 7.00 136.1 215.0 - 76.02 7 0 6 9 0 6 0 25.16 September 137.5 315.0 5.84 140.2 138.3 195.0 7.95 7.00 136.7 215.0 - 76.16 7 0 6 9 0 3 0 25.88 October n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. November 137.5 315.0 5.84 140.2 136.5 195.0 9.85 7.00 136.4 215.0 - 76.08 7 0 6 0 0 2 0 25.49 December 137.5 315.0 5.84 140.2 136.2 195.0 10.01 7.00 136.0 215.0 - 76.00 7 0 6 5 0 9 0 25.07 Source: Ministry of Budget 2013. Note: DF = Djibouti franc; FOB = free on board; SDVK = La Société de Distribution et de Vente de Kérosène. [[Typesetter: Table 9.4 needs to be broadside. Use sentence style for column headings; In column labeled "Discretionary tax": some of the numbers in the gasoline and diesel sections are negative and need minus signs.]] The calculation of the discretionary element is similar for the exempt organizations, but it has to be interpreted differently. The price calculation for the Republican Guard is an illustration. In December 2013 the price at the port (PP) for gasoline was Djibouti francs (DF) 148.46; domestic tax, excise tax, royalty, and VAT were all zero; distribution costs (DD) were DF 11.65; terminal transport cost was DF 1.76; and the retail margin was DF 7.02. The sum of these costs was DF 168.89, and this was the charge to the Republican Guard. Relative to the retail price of DF 315, the charge to the Republican Guard was a tax exemption of DF 146.10, which can be seen as a transfer from one segment of the government to another. <>Distribution of Subsidies Data for this chapter are from the third round of the Enquête Djiboutienne auprès des ménages (EDAM 3), a representative household survey that includes detailed information on household expenditures and receipt of certain cash and in-kind benefits. To ensure consistency across 312 chapters, the analysis uses 2014 prices, with inflation rates of 2.5 percent and 2.9 percent for 2013 and 2014, respectively. The EDAM 3 survey was conducted in 2012 and has a nationally representative sample of the sedentary population composed of 5,880 households with 31,686 individuals. The EDAM 3 questionnaire covers many aspects: demography, education, employment, mortality, governance, housing, access to basic social services, durable goods ownership, and finally, expenditures and revenues. Of particular importance is information on household expenditure on tax-exempt food (flour, rice, oil, sugar, and milk); certain fuel items (kerosene, butane, and fuel expenditure on transport); and electricity, as well as information on cash and in-kind benefits. The EDAM 3 dataset has been used to compute total expenditure aggregates of households, which the Department of Statistics and Demographic Studies (DISED) has used to produce their recent poverty profile, yielding 40.8 percent of poverty and 23 percent of extreme poverty.2 As is common for household surveys, the EDAM 3 data are representative only of the sedentary population. The EDAM 3 sample leaves out the nomad and homeless populations (population flottante) and individuals living in collective households (hotels, prison, military camps, and orphanages). According to the most recent census conducted in 2009, Djibouti’s total population was 818,159 individuals, of which 161,132 were nomads and 149,022 either lived in collective households or were homeless. Having household surveys solely covering the sedentary population is standard practice because surveying nomad and homeless populations creates important conceptual and logistic issues. Five quintiles based on per capita expenditure have been constructed based on the per capita expenditure welfare index. The first quintile includes the poorest 20 percent of the sedentary Djibouti population; the second quintile includes the next 20 percent, and so on up to the top quintile with the richest 20 percent of the population. For the purpose of this study, the destitution3 line is defined as the upper limit of the first quintile. Therefore, the destitution head count rate is de facto set to 20 percent. <>Energy Products The following analysis includes all the tax-exempt fuel products available in the household survey. The survey does not differentiate between diesel and super (lumped together as carburant in the EDAM 3 questionnaire), but data from the Enquête de Budget et Consommation 313 (EBC) survey (an urban-only survey done in 2013) show that around two-thirds of spending by households on carburant is on diesel. Furthermore, the survey shows that almost all direct spending on carburant is by the richest quintile. The simulations of subsidy reforms, discussed n the next section, assume that the price of fuel purchases will increase from DF 215 to DF 242 per liter. Car ownership and utilization of public transport is a strong indication of welfare. Car ownership is not widespread in Djibouti—only 6 percent of households own a car and 1 percent own a motorcycle. One-fourth of the richest quintile owns a car, and car ownership is basically negligible in the other quintiles (table 9.5). Most cars are owned by urbanites, and therefore carburant is essentially consumed by urban households and the richest quintile (table 9.6). Utilization of public transport (buses, taxis, and school buses) is also highest among the richer quintiles. Only 12 percent of the poor (quintile 1) use public transport compared with 60 percent in the richest two quintiles. More than half of the population in urban areas makes use of public transport, but less than 10 percent in rural areas. Utilization of school transportation is also highly skewed toward richer and urban households. Djibouti households spend about DF 7.96 million on subsidized fuel products (that is, fuel at the pump, public transport, and school transport), about 6.75 percent of their total annual expenditure (table 9.7). On an average, households spend DF 25,400 on fuel at the pump, DF 27,400 on public transport, and DF 30,600 on school transport (table 9.6). Tax exemptions on fuel products do not benefit the poorest as they consume little fuel and hardly use public transportation. As shown in table 9.5, possession of cars and motorbikes is essentially limited to the richest quintile, which consumes DF 96,847 per household on fuel at the pump, about 4 percent of the total annual household expenditure. Spending on public and school transport is also considerably lower in the poorest quintile (DF 2,142 and DF 2,381 per household, respectively) than in the richest quintile (DF 49,837 per household). Already the second quintile spends considerably more on public transport than the very poor (table 9.6). For the poor, expenses on fuel and public and school transport amount to less than 2 percent each of the overall household expenses (DF 4,522), whereas the richest quintile spends about 8 percent of total household expenditure (DF 197,643) on these fuel products. 314 Table 9.5: Percentage of Households Owning a Car or Motorbike or Using Buses, by quintile and area Public School Car Motorbike transport transport Quintile 1 (poorest) 0.0 0.1 12.4 6.9 2 0.4 0.5 37.4 21.9 3 1.7 0.6 53.2 37.2 4 3.0 1.3 62.0 47.0 5 (richest) 25.3 3.3 58.0 41.9 Area Urban 7.1 1.3 51.4 36.7 Rural 0.7 0.2 9.7 1.2 Total 6.1 1.2 44.6 31.0 Source: World Bank calculation based on the EDAM 3. Note: EDAM = Enquête Djiboutienne auprès des ménages. Table 9.6: Expenditures per Household (in 2014 DF), by quintile Quintile Fuel Public transport School transport Total 1 (poorest) 0 2,142 2,381 4,523 2 499 13,196 13,192 26,887 3 617 25,352 31,755 57,724 4 4,093 38,002 46,889 88,985 5 (richest) 96,874 49,837 50,932 197,643 Total 25,422 27,381 30,622 83,425 Source: World Bank calculation based on the EDAM 3 (2014 prices). Note: EDAM = Enquête Djiboutienne auprès des ménages. Table 9.7: Expenditure on Subsidized Products over Total Expenditures (in %), by quintile Quintile Fuel Public transport School transport Total 1 (poorest) 0.00 0.79 0.88 1.67 2 0.07 1.89 1.89 3.86 3 0.06 2.57 3.22 5.85 315 Quintile Fuel Public transport School transport Total 4 0.31 2.87 3.54 6.72 5 (richest) 3.93 2.02 2.07 8.02 Total 2.06 2.22 2.48 6.75 Source: World Bank calculation based on the EDAM 3 (2014 prices). Note: EDAM = Enquête Djiboutienne auprès des ménages. <>Food Products Poor households spend relatively more on tax-exempt food products than richer households. Household expenses on tax-exempt food products amount on average to DF 153,629 per household, which is equivalent to 12.4 percent of total household spending. Table 9.8 shows household expenses on tax-exempt food products, and table 9.9 shows the proportion of annual household spending. Of these basic food items, sugar is the most consumed item in terms of expenditure (DF 37,622). Although rice consumption is higher, only a tiny fraction of rice is actually tax exempt and therefore has been excluded from our analysis. Tax-exempt products are relatively more important for the poor, as the expenditure share of these products is much higher for the very poor than for the very rich. In the poorest households, 19 percent of the total expenses correspond to tax-exempt food products, while these products account for less than 7 percent of the richest households’ total expenses. Table 9.8: Expenditures per Household (in DF), by quintile Powdered Cooking Quintile Flour Sugar Total milk oil 1 (poorest) 4,250 17,455 8,262 22,193 52,161 2 17,189 27,000 17,573 36,717 98,480 3 26,579 25,541 20,486 40,253 112,858 4 35,266 28,348 23,782 41,760 129,156 5 (richest) 55,248 31,814 33,213 45,082 165,357 Total 29,529 26,350 21,450 37,622 114,951 Source: World Bank calculation based on the EDAM 3 (2014 prices). Note: DF = Djibouti franc; EDAM = Enquête Djiboutienne auprès des ménages. 316 Table 9.9. Expenditure on Subsidized Products over Total Expenditures (in %), by quintile Powdered Cooking Quintile Flour Sugar Total milk oil 1 (poorest) 1.57 6.46 3.06 8.22 19.31 2 2.47 3.88 2.52 5.27 14.14 3 2.69 2.59 2.08 4.08 11.43 4 2.66 2.14 1.80 3.15 9.75 5 (richest) 2.24 1.29 1.35 1.83 6.71 Total 2.39 2.13 1.74 3.04 9.30 Source: World Bank calculation based on the EDAM 3. Note: EDAM = Enquête Djiboutienne auprès des ménages. <>Simulation of Subsidies Reforms This section presents two simulation scenarios. The first focuses on fuel products and estimates the effects of removing the discretionary tax on retail prices on super and diesel. The survey database used does not differentiate between expenditure on super and diesel, but because it can be shown that by far the largest part of spending on fuel is on diesel, we would assume that all such fuel spending is on diesel. Kerosene would be excluded from such a reform. The second simulation focuses on four basic food items and estimates the effects of introducing a consumer tax. The latter reform is currently not under consideration by the government, and the simulations are for illustrative purposes only. <>Impact of Removing the Discretionary Tax on Fuel Products The proposal to remove the use of discretionary tax on certain fuel products is currently under consideration by the government. Other tax rates could be varied by legislation, as at present, but would normally be stable for lengthy periods. Allowable costs along the supply chain could also be varied if justified by the circumstances of the entities involved. To simulate the effect of removing the discretionary tax element on prices, it is assumed that all other tax rates and costs remain at the levels of December 2013. For gasoline and diesel, the removal of the discretionary tax component has two effects on the retail price that would have to be charged. First, when the discretionary tax is positive, its removal would contribute to lowering of the retail price by this amount. Second, because the VAT at 7 percent is charged on the discretionary tax element, the result would be a further lowering of the retail price. Similarly, when the discretionary tax is negative, its removal would 317 raise retail prices by 1.07 times the amount of the discretionary tax. Table 9.10 illustrates the effects on retail prices if the tax had been removed in December 2013. The removal of discretionary tax would have resulted in a small drop in gasoline price, but an increase of around 13 percent for diesel. The comparison between the before and after prices in December 2013 is possible because the government’s action with respect to the determination of the retail price (and the associated discretionary tax) is a known fact. Simulating the effect of removing the discretionary tax under different circumstances is possible, but it is not possible to give a "before" calculation because it is not known what the government would have decided to do with retail prices had it kept the discretionary tax. Table 9.10: Retail Petroleum Product Prices With and Without the Discretionary Tax (December 2013), in DF/liter Gasoline Diesel Before After % Before After % Change Change 315.00 308.73 −2.0 215.00 241.82 +12.5 Source: World Bank data and calculations. Note: DF = Djibouti franc. To illustrate the range of retail prices that might be experienced if the discretionary tax were abandoned, simulations of the impacts of a 20 percent increase and a 20 percent decrease in the FOB prices (relative to the levels of December 2013) are constructed and the results are shown in table 9.11. It is assumed that all other costs, taxes, and duties remain unchanged, and in all cases there is no discretionary tax element. The results of the calculations show gasoline price varying by between plus or minus 12 percent, and diesel prices by plus or minus 15 percent. The larger fixed elements for gasoline (excise duty and royalty) mean that the percentage swing in the FOB price (which is similar for all three products) is damped down more than is the case for diesel. The substantial fall in crude oil prices is relevant to the calculations shown. In December 2013 Brent crude sold for about $110 a barrel and remained around that level until July 2014. Since 318 then it has steadily declined until falling to around $50 a barrel in September 2015. Considerable uncertainty remains about the price of crude oil. The simulations of the effect of removing the discretionary tax focused on December 2013 actual FOB prices and included a sensitivity analysis of a 20 percent drop of those prices (table 9.11). This drop would have corresponded to a Brent crude price of about $90 a barrel. The actual fall has been almost twice that allowed in the sensitivity analysis. Simple extrapolation indicates that, in the absence of discretionary taxes, a 40 percent fall in FOB prices would result in gasoline prices of 235 DF/liter and diesel prices of 169 DF/liter. Table 9.11: Results of Simulation: Range of Retail Prices (DF/liter) Gasoline Diesel December 2013 FOB 308.7 241.8 December 2013 FOB plus 20% 345.8 278.5 December 2013 FOB minus 20% 271.6 205.1 Source: World Bank data and calculations. Note: DF = Djibouti franc; FOB = free on board. <>Diesel Prices and Transport Costs. The analysis of the impact of removing the discretionary tax element on households proceeds through the use of an expenditure survey, coupled with the calculated changes in petroleum product prices. The shares of total household expenditure allocated to each of the two petroleum products is directly available from the household expenditure survey and can be combined with predicted price changes to estimate the expenditure change required to purchase the same amounts of each product. In addition to the direct effects on household budgets, there are indirect effects caused by the impact of rising petroleum product prices on other goods and therefore on the household budget. Without a detailed input-output table it is not possible to quantify all such links, but the most important link for petroleum products in Djibouti is transport costs. Because the costs of travel by bus or taxi can be a substantial component of household expenditure, we must consider the link between product prices and transport costs. 319 As diesel is used as fuel for commercial transportation vehicles, the key question is the nature of the link between the gas oil price and the price of transportation services. Bus fares are regulated and have changed very little in the last decade. It is likely that a jump in fuel costs brought about by the abolition of the discretionary tax, which was holding down costs by about 12 percent in December 2013, could provide an opportunity for the bus sector to ask for higher ticket prices to cover increased costs. Many factors might enter such a negotiation, including previous loss of profitability caused by the government holding prices steady for a long period. A full justification of an allowable fare increase would require detailed analysis of the economics of the bus and taxi sectors. In the absence of such a detailed study, a first approximation can be obtained by combining the fuel share in total costs with the percentage increase in fuel costs. Evidence from other countries on the share of fuel costs in the total costs of operating a bus fleet can serve as a marker for any assumption that is made for Djibouti. ESMAP (2011) refers to a study in India where the share of fuel cost in Andhra Pradesh amounted to 31 percent of total costs. A World Bank study analyzed factors affecting bus performance in middle- to low-income countries and provided values indicative of the range of cost breakdown as shown in table 9.12. The following remarks from the study are relevant to Djibouti: “In the case of informal small- scale operation using rehabilitated or locally fabricated buses, financed by overseas remittances, depreciation and interest costs are much less (only about 10 percent of total costs), while driver and other staff costs can be relatively more (20–30 percent) due to the higher number of people employed per unit of capacity (often including the owner)” (ESMAP 2011, 10). Table 9.12: Shares of Operating Cost of a Bus Fleet in Developing Countries Cost item Proportion of operating cost (%) Variable costs Fuel 20–30 Lubricating oil 1–5 Tires 5–10 Spares 5–10 Fixed costs Driver and other platform staff 10–15 Other labor About 5 Depreciation and interest 20–30 Overheads and other costs 5–15 Source: IBRD 2015. Fuel costs can range between about 50 percent and 75 percent of variable costs depending on 320 circumstances. A survey carried out by the secretary of state responsible for National Solidarity (SESN) and the Department of Statistics and Demographic Studies (DISED) in Djibouti City in 2014 indicated that averaged over all forms of passenger road transport, fuel accounted for 80 percent of variable costs and that there was little variation in this ratio among the different forms of passenger transport. The closeness of these figures suggests that it is reasonable to assume that fuel costs in Djibouti are about 30 percent of total operating costs (the high end of the range given in table 9.12, corresponding to the 75 percent share of variable costs). Combining the information on the possible increase in diesel prices (12.5 percent) relative to their level in December 2013 with a fuel cost share of 30 percent suggests that an increase of 4 percent in passenger fares would be justified to allow bus companies to overcome the effects of higher fuel prices. If the government decided to permit a larger price rise, perhaps to allow for catching up with previous cost increases, there is more likelihood of public opposition to the change. <>Impact of Fuel Subsidy Reform on Household Welfare, Government Budget, Poverty, and Inequality. Abandoning the discretionary tax on super and diesel retail prices would imply a loss of DF 510.8 million (or 0.2 percent of GDP)4 for the population. Table 9.13 shows the impact of the reform on the welfare of the population for each quintile; table 9.14 shows the impact of the reform on the per capita welfare of each quintile; and table 9.15 shows the impact as the proportion of total household expenditure. For fuel bought directly at pump, the impact of the reform on poor households is negligible, but it increases with welfare and represents the highest loss among rich households (2,734 DF per capita), equivalent to 0.5 percent of total household spending. The poorest two quintiles spend considerably less on public and school transport than the richer quintiles, partly because the poor live in areas with no such transport available, such as the rural areas. The same conclusion, however, holds when restricting the analysis only to urban areas. The impact of the reform on the poorest 40 percent is less than DF 80 per capita on either public or school transport, compared to more than DF 800 (for both public and school transport combined) among the richest quintile. In terms of household spending, this would amount to a loss of 0.06 percent of welfare for the poorest quintile and 0.16 percent for the richest quintile. The middle class would experience the largest reduction in well-being—about 0.22 percent. 321 Table 9.13: Total Impact on the Population’s Well-Being (in DF millions), by quintile Quintile Fuel Public transport School transport Total 1 (poorest) 0.0 −1.5 −1.7 −3.1 2 −1.0 −8.1 −8.1 −17.3 3 −1.3 −16.3 −20.4 −38.0 4 −9.7 −26.8 −33.0 −69.5 5 (richest) −292.7 −44.6 −45.6 −382.8 Total −304.8 −97.3 −108.8 −510.8 Source: World Bank calculation based on the EDAM 3 (2014 prices). Note: EDAM = Enquête Djiboutienne auprès des ménages. Table 9.14: Impact on the Per Capita Well-Being (in DF), by quintile Fuel Public transport School transport Total 1 (poorest) 0 −14 −15 −29 2 −10 −76 −76 −161 3 −12 −152 −190 −354 4 −90 −249 −307 −646 5 (richest) −2,734 −417 −426 −3,576 Total −568 −181 −203 −951 Source: World Bank calculation based on the EDAM 3 (2014 prices). Note: EDAM = Enquête Djiboutienne auprès des ménages. Table 9.15: Impact on Well-Being (in %), by quintile Quintile Fuel Public transport School transport Total 1 (poorest) 0.00 −0.03 −0.03 −0.06 2 −0.01 −0.07 −0.07 −0.15 3 −0.01 −0.10 −0.12 −0.22 4 −0.04 −0.11 −0.13 −0.28 5 richest) −0.49 −0.08 −0.08 −0.65 Total −0.26 −0.08 −0.09 −0.43 Source: World Bank calculation based on the EDAM 3 (2014 prices). Note: EDAM = Enquête Djiboutienne auprès des ménages. The impact of the reform would result in a gain for the government budget, with the highest gain coming from fuel bought directly at the pump. Table 9.16 shows the impact of the reform on the government budget from the different subsidized products. The impact of the reform would 322 result in a total gain of DF 408.6 million (or 0.16 percent of GDP). Sixty percent of that gain would come from fuel sold at the pump (96 percent of the 60 percent will originate from the richest households), and the remaining 40 percent will come from public and school transport. It should be noted that because we assume a price elasticity of minus 0.2, the amount gained by the government is less than the loss incurred by the different households. Table 9.16: Impact of the Reform on the Government Revenue (in DF millions), by quintile Quintile Fuel Public transport School transport Total 1 (poorest) 0.0 1.2 1.3 2.5 2 0.8 6.5 6.5 13.8 3 1.1 13.0 16.3 30.4 4 7.8 21.4 26.4 55.6 5 (richest) 234.1 35.7 36.5 306.3 Total 243.8 77.8 87.0 408.6 Source: World Bank calculation based on the EDAM 3 (2014 prices). Note: EDAM = Enquête Djiboutienne auprès des ménages. Because the poor spend most of their income on food-related products, the elimination of tax exemptions on fuel products would reduce inequality but with no apparent impact on poverty. The elimination of tax exemptions on fuel would not affect the poorest because the consumption of this product is negligible among the poor. On the other hand, the consumption of this product is one of the highest among the subsidized products in rich households, and an elimination of tax exemption would result in a reduction in inequality by 0.12 percentage points. Our results show that an elimination of tax exemption on fuel at the pump offers potential for higher government revenues without impacting poverty. An increase of prices on public transport would increase poverty, but at a lower rate than increases on school transport (see table 9.23). <>Impact of Introducing Consumer Tax on Basic Food Items The government is not considering levying a consumer tax on basic food items, and the next simulations are merely for illustrative purposes. As mentioned, among the basic food items that are tax-exempt, only a certain quality or type is exempt (for example, broken rice). For rice, only 6 percent of the imported rice is exempt, but about 88 percent of flour, about 60 percent of sugar 323 and edible oil, and about 50 percent of powdered milk products are exempt. The implicit subsidy represents 7 percent of the unsubsidized price. Given the minimal proportion of rice being tax- exempt, we exclude it from our analysis. Introducing consumer taxes would imply a loss of DF 558.7 million (or 0.22 percent of GDP) for the population. The per capita values indicate that the loss would be considerably higher for the richest in absolute terms (table 9.17). Overall, the impact of the reform on the poorest quintile would imply a decrease in well-being by DF 500 or 1.06 percent of household spending. For the richest quintile, the loss would be equivalent to DF 1,836 or 0.33 percent of household spending. This comparison shows that the poor spend more in relative terms on tax-exempt food products. Therefore, introducing consumer taxes would affect poverty. Table 9.17: Total Impact on the Population’s Well-Being (in DF, millions), by quintile Powdered Cooking Quintile Flour Sugar Total milk oil 1 (poorest) −3.1 −24.8 −7.3 −18.4 −53.6 2 −11.2 −34.0 −13.8 −27.0 −86.0 3 −18.1 −33.4 −16.7 −30.8 −99.0 4 −26.3 −40.8 −21.3 −35.1 −123.5 5 (richest) −52.4 −58.1 −37.8 −48.2 −196.6 Total −111.2 −191.0 −96.8 −159.6 −558.7 Source: World Bank calculation based on the EDAM 3 (2014 prices). Note: EDAM = Enquête Djiboutienne auprès des ménages. Table 9.18: Impact on the Per Capita Well-Being (in DF), by quintile Powdered Cooking Quintile Flour Sugar Total milk oil 1 (Poorest) −29 −231 −68 −172 −499 2 −104 −316 −128 −251 −800 3 −169 −312 −156 −288 −924 4 −245 −379 −198 −326 −1,148 5 (richest) −490 −543 −353 −450 −1,836 Total −207 −356 −180 −297 −1,041 Source: World Bank calculation based on the EDAM 3 (2014 prices). Note: EDAM = Enquête Djiboutienne auprès des ménages. 324 Table 9.19: Impact on Well-Being (in %), by quintile Powdered Cooking Quintile Flour Sugar Total milk oil 1 (poorest) −0.06 −0.49 −0.14 −0.37 −1.06 2 −0.10 −0.29 −0.12 −0.23 −0.75 3 −0.11 −0.20 −0.10 −0.18 −0.58 4 −0.11 −0.16 −0.08 −0.14 −0.49 5 (richest) −0.09 −0.10 −0.06 −0.08 −0.33 Total −0.09 −0.16 −0.08 −0.14 −0.47 Source: World Bank calculation based on the EDAM 3. Note: EDAM = Enquête Djiboutienne auprès des ménages. Table 9.20: Impact of Reform on Government Revenue (in DF millions), by quintile Powdered Cooking Quintile Flour Sugar Total milk oil 1 (poorest) 2.5 19.8 5.8 14.7 42.9 2 9.0 27.2 11.0 21.6 68.8 3 14.5 26.7 13.4 24.7 79.2 4 21.1 32.6 17.0 28.1 98.8 5 (richest) 42.0 46.5 30.2 38.6 157.2 Total 89.0 152.8 77.5 127.7 447.0 Source: World Bank calculation based on the EDAM 3 (2014 prices). Note: EDAM = Enquête Djiboutienne auprès des ménages. <>The Political Economy of Reforms Following the previous section where we looked at the impacts of the proposed reforms, here we examine the safety nets in place in Djibouti and attempt to estimate the effect of compensating schemes to offset perverse effects on poverty. <>Fuel Subsidies The government is currently considering abandoning the use of the discretionary tax element on certain fuel products (super and diesel) for private consumers, but the privileges for other exempt groups such as the military and embassies would remain. At the time of analysis (based on prices of December 2013), such a reform would have resulted in a small reduction in super prices and an increase of around 13 percent for diesel. The substantial fall of crude oil prices is relevant to the calculations shown. In December 2013, Brent crude sold for about US$ 110 a barrel, and it 325 remained around that level until July 2014. Since then it has steadily declined until falling to around US$ 50 a barrel in January 2015. Before the drop in oil prices, the government had not taken any firm decision, in part due to fears that higher fuel prices would increase inflation. In addition, there are concerns over the impact on the poor, the middle class, and certain sectors, such as transport, fisheries, and bakeries. The impact of fuel subsidy reforms on the transport sector is of particular concern to the government. Ticket prices for public transport are set by the state and have been more or less stable since 2006. The bus and taxi fleet is outdated, and current discussions center on decreasing the cost of transport by updating the fleet. The government is considering financing new vehicles, which the bus and taxi operators would pay back over time, thereby reducing the consumption of fuel. If the government wanted to abandon the discretionary tax, this would be the time for action. With falling oil prices, an elimination of the discretionary tax elements would not necessarily lead to higher prices for consumers. In fact, given the low prices seen in early 2015, removal of discretionary tax on diesel would be small in comparison to the fall in underlying costs—so that the effect of its removal will be negligible and the effect on bus prices will be easily absorbed. If bus operators do not lower their prices at all, their margins will increase. With the elimination of discretionary tax on fuel products, however, the government would relinquish a tool to smooth fuel prices in times of price fluctuations. With falling oil prices, government tax revenues will decrease accordingly. The removal of discretionary tax at this point would lower the tax revenue further. It is likely that the government has adjusted the magnitude of the discretionary tax since January 2014, which would warrant further analysis. Furthermore, an analysis of the optimal tax structure would be warranted. The following analysis based on December 2013 prices confirms that a negative tax on fuel products effectively subsidizes the better-off. Any reform of the current energy tax system should be pro-poor ,and social safety nets would be the channel to reinvest savings in pro-poor policies. <>Social Safety Nets In this subsection we examine first the efficiency of the current safety nets in Djibouti and then look at the impacts of reforming the safety net already in place, including eliminating the tax exemption on a few key items. And finally we estimate the effects on poverty of different compensating schemes following the proposed reforms. 326 <>Role of Social Safety Nets. Currently, untargeted tax exemptions (implicit subsidies) reach a wider part of the population than targeted programs. Table 9.21 shows the percentage of the population (by welfare quintile) receiving seven types of transfers: pensions (private or public), compensation for health care expenditure, food rations, cash transfers from the government or nongovernmental organizations (NGOs), publicly provided food subsidies, publicly provided fuel subsidies, and private transfers received from family and friends. Tax exemptions on basic food items reach the majority of the poor (77.3 percent in the poorest quintile) and almost the totality of individuals in the other four quintiles. Tax exemptions on certain fuel products, on the other hand, benefit only 17 percent of the poorest quintile but more than 82 percent of the richest. About a quarter of the population in the poorest quintile benefits from food rations, making it a program with relatively effective targeting. Compensation for health expenditure disproportionately benefits the richer quintiles. Very few households (less than 10 percent) benefit from pensions. Finally, 21 percent of Djibouti households receive private transfers (international or national), and these transfers benefit the poorest households in a larger proportion. Table 9.21: Coverage of Transfer Programs (in %), by quintile Transfers Compensation Food from Food Fuel Quintile Pensions for health care Remittances rations government subsidies subsidies expenditure or NGOs 1 5.3 1.3 27.0 5.8 77.3 17.1 29.7 (poorest) 2 8.6 3.5 8.6 1.3 98.1 48.2 23.6 3 10.5 4.2 2.5 1.5 99.7 66.9 20.2 4 8.5 5.5 1.3 0.9 99.3 76.2 18.3 5 9.6 6.9 1.1 0.8 99.2 82.5 13.5 (richest) Total 8.5 4.3 8.1 2.1 94.7 58.2 21.0 Source: World Bank calculation based on the EDAM 3. Note: EDAM = Enquête Djiboutienne auprès des ménages. NGO = nongovernmental organization. The intended beneficiaries of social safety net programs should be the poor. Therefore, the performance of such programs can be assessed by estimating program leakage. One way to 327 measure such leakage is by determining the share of total transfers received by nonpoor beneficiaries. In a well-targeted progressive program, the poor receive the highest share of transfers; this share declines as welfare increases. Table 9.22 shows the distribution of benefits by area and welfare quintile. In Djibouti, food rations and cash transfers generally fit this description as the poor receive most of the transfers, in fact, more than half of the transfers for food rations. In contrast, tax exemptions on food and fuel items predominantly benefit the urban population and nonpoor, making these programs regressive. The majority of food and fuel subsidy resources (85 percent and 97 percent, respectively) are received by those living in urban areas and by those from the richest two quintiles (57 percent and 89 percent, respectively). Only 15 percent of food subsidy benefits and less than 3 percent of fuel subsidy benefits go to beneficiaries living in rural areas, and only 10 percent and less than 1 percent, respectively, are received by those in the poorest quintile. Pensions and compensation for health care expenditure transfers are received mainly by nonpoor beneficiaries and the population living in urban areas. Table 9.22: Distribution of Benefits (Targeting Accuracy), by quintile and area Type of benefit Area of residence Quintiles of per capita consumption 5 1 Urban Rural 2 3 4 (richest (poorest) ) Pensions 85.6 14.4 4.5 10.9 17.5 19.3 47.9 Compensation for health care 88.0 12.0 3.5 11.1 17.2 23.4 44.9 expenditure Food rations 15.8 84.2 56.2 21.2 10.7 4.3 7.5 Transfers from government or 44.7 55.3 45.1 16.9 13.6 11.7 12.7 NGOs Food subsidies 84.9 15.1 9.5 15.4 17.8 22.0 35.3 Fuel subsidies 97.2 2.8 0.6 3.4 7.5 13.5 75.0 Remittances 75.6 24.4 20.8 15.4 20.7 15.0 28.1 Source: World Bank calculation based on the EDAM 3. Note: Benefits incidence is the transfer amount received by the group as a percentage of total transfers received by the population. Specifically, benefits incidence is (sum of all transfers received by all individuals in the group)/(sum of all transfers received by all individuals in the population). Aggregated transfer amounts are estimated using household size-weighted expansion factors. EDAM = Enquête Djiboutienne auprès des ménages; NGO = nongovernmental organization. The generosity of social safety net programs in Djibouti is generally very low, which limits the 328 impact on poverty. Only two programs (pensions and private transfers from family and friends, which strictly speaking are not social assistance programs), of the seven types of programs available seem to have an impact on the consumption levels of the population in general. On the contrary, by focusing on the poorest quintile, food rations also have a significant effect even if private transfers are by far the most efficient vehicle. The impact of cash transfers from the government or NGOs and tax exemptions on food on the welfare of the poorest quintile is extremely modest, and that of tax exemptions on fuel items is negligible. <>Impact of Reforming Tax Exemptions and Safety Nets on Poverty. Discretionary energy taxes have benefited the better-off in times of higher fuel prices (the analysis in this study is based on December 2013 prices). An elimination of tax exemptions on fuel products would reduce inequality but would not have any apparent impact on poverty. Savings from a possible tax reform and other funding resources could be rechanneled toward the poor and vulnerable. But the key component of any poverty alleviation program is effective targeting of the poor. The government of Djibouti with the support of the World Bank is currently developing a social registry to increase equity in the distribution of resources and to promote greater social inclusion for the most vulnerable groups. Over the course of the technical assistance provided to the government of Djibouti, a number of policy recommendations have emerged, and some have already been taken into consideration in the design of a stronger social protection system. These recommendations are derived from a poverty and social impact analysis and include:  Savings on energy tax reforms and other funding resources, including those spread over a number of very small safety net programs, should be channeled to a cash-transfer program targeting the poorest;  A proxy means test (PMT) should be used to determine the households’ poverty score, and all safety net programs should target the poorest (as defined by the PMT) rather than targeting rural households based on geography;5  Similarly, current and future safety net programs should first target poor households based on the relative poverty score, and then use other (categorical) factors to determine program eligibility. As the poor spend most of their income on food-related products, the elimination of tax exemptions on such products would have the highest impact on poverty and inequality, while the elimination of tax exemptions on fuel products would reduce inequality but with no apparent 329 impact on poverty. However, these effects would be minimal, almost negligible. Table 9.23 shows the impact of the reform on destitution and inequality. (Recall that the destitution line is defined as the upper limit of Quintile 1.) Globally, a reform of taxes on fuel and food products alone would not have a significant impact on destitution and no impact on inequality. In particular, the destitution rate would increase by 0.17 percentage points from 20.00 to 20.17 percent. The elimination of tax exemptions on flour would increase destitution by 0.05 percentage points (from 20.00 to 20.05 percent), and inequality by 0.05 percentage points (from 45.13 to 45.18 percent). The effect of the elimination of the discretionary tax adjustment on fuel would not affect the poorest as it would result in a reduction of inequality by 0.12 percentage points. The consumption of fuel is negligible among the poor, but it is one of the highest consumed products among the subsidized products in rich households. Table 9.23: Reform, Destitution Head Count, and Gini Index Destitution Change in Variation in Gini index level destitution Gini Prereform 20.00 - 45.13 - Powdered milk 20.00 0.00 45.13 0.00 Flour 20.05 0.05 45.18 0.05 Cooking oil 20.01 0.00 45.15 0.01 Sugar 20.01 0.01 45.17 0.04 Fuel 20.00 0.00 45.01 −0.12 Public transport 20.00 0.00 45.13 0.00 School transport 20.00 0.00 45.14 0.00 Postreform 20.17 0.17 45.13 −0.02 Source: World Bank calculation based on the EDAM 3. Note: EDAM = Enquête Djiboutienne auprès des ménages. <>Likely Impact of Compensation Policies through Social Safety Nets Programs. Reform options based on a number of transfer schemes and budget envelopes were discussed with the government. The different transfer schemes proposed are defined in table 9.24 and could be implemented at an individual or household level. In the latter case, the amount transferred is the same for any household meeting the selection criteria irrespective of the household size. On the other hand, the "individual" schemes depend on household size. For example, a nine-member 330 household would receive three times the amount received by a three-member household. An intermediate measure is based on a calorie-requirement–based equivalence adult scale (Eq.Ad.). Table 9.24: Definition of the Different Transfer Schemes Transfer no. Selection criteria Beneficiary Amount transferred per unit (in DF) 1 Rural + urban outside Individual 6,935 Djibouti City 2 Individual (in 9,268 3 Eq.Ad.) household) 35,826 4 Rural only Individual 11,560 5 Individual (in 15,717 6 Eq.Ad.) household) 54,940 7 Rural + urban in quintile 1 Individual 7,675 8 Individual (in 10,259 9 Eq.Ad.) household) 42,550 10 First quintile with unique Individual 9,306 transfer 11 Individual (in 12,418 12 Eq.Ad.) household) 58,748 13 Quintile 1 with 2 steps Individual Percentile 0–10: 13,960 Percentile 10–20: 4,673 14 Individual (in Eq.Ad. Percentile 0–10: 18,811 Percentile 10–20: 6,176 15 household) Percentile 0–10: 90,133 Percentile 10–20: 28,863 16 Quintile 1 with 4 steps Individual Percentile 0–5: 15,245 Percentile 5–10: 12,670 percentile 10–15: 7,066 percentile 15–20: 2,288 17 Individual (in Eq.Ad. Percentile 0–5: 20,629 Percentile 5–10: 17,001 percentile 10–15: 9,313 percentile 15–20: 3,031 18 household) Percentile 0–5: 110,709 Percentile 5–10: 73,607 Percentile 10–15: 42,777 Percentile 15–20: 14,417 Source: World Bank calculation based on the EDAM 3 (2012 prices). 331 Note: DF = Djibouti franc; EDAM = Enquête Djiboutienne auprès des ménages; Eq. Ad. = equivalence adult scale. The results in table 9.25 show that the largest decline in destitution (poverty) head count is achieved when targeting Quintile 1. The destitution head count (P0) is defined as this quintile. Overall, with a total budget of DF 1 billion, the effect on the destitution head count is limited if we concentrate mainly on rural households without taking into account urban households from Quintile 1. The largest decline in the destitution head count with a budget of DF 1 billion targets that quintile and transfers a uniform amount. Table 9.25: Effect on Destitution Gap of the Different Transfer Schemes Transfer no. Selection criteria Beneficiary DF 1 billion DF 2 billion DF 3 billion 1 Rural + urban outside Individual 5.5 4.3 3.3 Djibouti City 2 Individual (Eq.Ad.) 5.6 4.4 3.4 3 household 5.7 4.6 3.8 4 Rural only Individual 5.0 3.4 2.2 5 Individual (in 5.0 3.5 2.3 6 Eq.Ad.) household 5.3 4.0 3.1 7 Rural + urban in first Individual 5.0 3.4 2.2 quintile 8 Individual (in 5.0 3.5 2.3 9 Eq.Ad.) household 5.1 3.8 2.7 10 Quintile 1 with Individual 4.6 2.9 1.6 unique transfer 11 Individual (in 4.7 3.0 1.7 12 Eq.Ad.) household 4.6 2.9 1.8 13 Quintile 1 with 2 Individual 4.4 2.1 0.6 steps 14 Individual (in 4.5 2.2 0.8 15 Eq.Ad.) household 4.3 2.3 1.1 16 Quintile 1 with 4 Individual 4.4 1.9 0.3 steps 17 Individual (in 4.4 2.0 0.4 18 Eq.Ad.) household 4.2 2.0 0.8 Without transfer 6.9 6.9 6.9 Source: World Bank calculation based on the EDAM 3. Note: DF = Djibouti franc; EDAM = Enquête Djiboutienne auprès des ménages. 332 With a larger budget of DF 3 billion, it would be possible to almost halve the destitution head count using any of the schemes that target Quintile 1. By using such a destitution head count as a measure of efficiency, however, it is not clear whether an individual scheme or a household- based scheme is more efficient at reducing destitution. The main problem in using a destitution head count to assess the different schemes is that no weight is given when an extremely poor household receives an important transfer while remaining below the poverty line. Actually, we can imagine an extreme case where all the poorest households would be better off but still poor if the amount transferred makes them go over the poverty line. Therefore, we should focus on the destitution gap as a measure of destitution. To reduce the destitution gap, targeting Quintile 1 is more efficient than any of the schemes focusing on rural households. The poverty gap index (PGI or P1) estimates the depth of destitution by considering how far, on average, the poor are from that destitution line. It is defined as the average destitution gap in the population as a proportion of the destitution line. In a graph presenting the cumulative welfare function, this is the area below the destitution line and on the left-hand side of the function. Before any transfer, the destitution gap index associated with the destitution line is measured as 6.9 percent (last line in table 9.25). On average, the poor individual has expenditures (as measured by the PMT) 6.9 percent below the destitution line (DF 77,926 per capita in 2012 prices). The preferred transfer scheme to reduce the destitution gap would be to target Quintile 1 with a four-step transfer amount depending on destitution. Schemes 16 or 17 would be by far the best—focusing on Quintile 1 but with the amount transferred being dependent on destitution (as defined by the PMT). In this case, the poorest 5 percent would receive more than the penultimate 5 percent, and so on (see table 9.24). <>Conclusion The government of Djibouti is currently considering abandoning the use of the discretionary tax element on certain fuel products (super and diesel) for private consumers. This chapter shows that the effects of removing tax exemptions on food and fuel globally would have a marginal effect on poverty, but would keep inequality unchanged. Among the poorer quintiles, the loss in welfare as a result of the reform would be the highest on food-related items; among the richer 333 quintiles it would be the highest on fuel products. Figure 9.1 shows the impact of the reform on the welfare of the population as a proportion of the total spending by quintile and for each subsidized product group. In terms of food-related products, the reform would result in a significant loss of welfare among the poorest quintile (1.12 percent of total spending) but this loss decreases as welfare increases. The reform would result in a minimal loss among the richest quintile for fuel products, and this loss decreases as welfare decreases and becomes negligible for the poorest quintile. The impact of the reform on government budget would result in a gain, the highest coming from fuel. The impact of the reform on government budget would result in a total gain of DF 856 million (or 0.33 percent of GDP): 28 percent of that gain would come from fuel (96 percent of the gain from fuel will originate from the richest households), 18 percent from flour, and 15 percent from sugar. The highest gain in the government budget will come from the richest households (54 percent). This gain decreases as welfare decreases to reach the lowest share among poor households (5 percent). This result is consistent with the finding that the highest loss of welfare in the population would come from fuel, and particularly among the rich. Figure 9.5: Impact on Well-Being, by quintile Quintile 1 Quintile 5 (poorest) Quintile 2 Quintile 3 Quintile 4 (richest) Total 0.00 -0.20 Food -0.40 Energy -0.60 Total -0.80 -1.00 -1.20 Source: World Bank calculation based on the EDAM 3. Note: EDAM = Enquête Djiboutienne auprès des ménages. [[Typesetter: In figure 9.1: Y-axis: Use label “Percentage of total household spending”; change hyphens to minus signs; Change colors in chart and legend to grayscale; Background: remove box.]] 334 Figure 9.2 shows the impact on government revenues as the price of each subsidized product increases. The most important revenue gain to the government would come from increasing the price of fuel, while the least would come from increasing the price of cooking oil. Figure 9.6: Impact of the Reform on the Government Revenue (DF), by product 900 856 800 700 600 500 400 300 244 200 153 128 89 77 78 87 100 0 Powdered Flour Cooking oil Sugar Fuel Public School Total milk transport transport Source: World Bank calculation based on the EDAM 3 (2014 prices). Note: DF = Djibouti franc; EDAM = Enquête Djiboutienne auprès des ménages. [[Typesetter: In figure 9.2: X-axis: remove tick marks; Y-axis: Use label “Value in millions of DF”; Change color in chart and legend to gray; Background: remove numbers from the chart area; remove box and gridlines.]] To reduce poverty, savings from a possible tax reform on fuel products and other funding resources could be rechanneled toward the poor and vulnerable. To reduce poverty, however, effective targeting of the poor is important. A key element to strengthening social safety nets in Djibouti is the creation of a social registry of poor and vulnerable households, which will be the single platform used by all social assistance programs. Such a measure would result in significant cost savings and substantial improvements in targeting the poorest households. In addition, the government is considering a targeted cash-transfer system to increase equity in the distribution of resources and promote greater social inclusion for the most vulnerable groups. If the government wanted to abandon the discretionary tax, this would be the time for action. 335 With falling oil prices, an elimination of the discretionary tax elements would not necessarily lead to higher prices for consumers. In fact, given the low prices seen in early 2015, removal of discretionary tax on diesel would be small in comparison to the fall in underlying costs—so that the effect of its removal will be negligible and the effect on transport prices, a key concern to the government, will be easily absorbed. <>Notes We thank Robert Bacon, Ines Rodriguez Caillava, and Angela Elzir for their contributions to this chapter. 1. The study was designed and implemented by a multisectoral committee composed of various stakeholder institutions, including the Ministry of Economy and Finance, the Ministry of Budget, the secretary of state responsible for National Solidarity (SESN), the Department of Statistics and Demographic Studies (DISED), the Ministry of Energy, and the Ministry of Transport, with whom the teams of the World Bank and the International Monetary Fund collaborated throughout the process of preparation of the study. 2. The EDAM 3 sample slightly underestimates the size of households, and the level of average per capita total household expenditure is therefore slightly overvalued in this survey. Because this study focuses primarily on expenditure quintiles, the effect of this general overvaluation is marginal. Furthermore, and in contrast to the recently updated national poverty profile that combines data from EDAM 3 and the Budget and Consumption Survey (EBC), this study uses data from EDAM 3 and its expenditure aggregate only. The aggregate used in this study, however, is highly correlated with that used for the poverty profile produced by the DISED. We do not see any conflict between the analysis in this study and the figures recently approved by the government. 3. In this chapter we try to avoid the terms poverty line and poverty head count in order to differentiate our analysis from the poverty profile produced by the DISED. 4. GDP for 2013 is estimated at US$1.456 billion. 336 5. This functionality will be part of the forthcoming social registry that will be used to identify, classify, and target households that would be considered poor or vulnerable, to improve the delivery of assistance to them. <>References Capgemini Consulting. April 2014. De Broek, M., A. Kangur, and R. Kpodar. 2012. Djibouti: Fuel Price Subsidy Reform. IMF, May 2012. ESMAP (Energy Sector Management Assistance Program). 2011. "Transit Bus Operational and Maintenance Practices to Maximize Fuel Economy." Report 63116–GLB. GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit, Federal Ministry for Economic Cooperation and Development). 2012–13. International Fuel Prices 2012/2013. Eighth edition. https://www.energypedia.info/index.php/International_Fuel_Prices. IBRD (International Bank for Reconstruction and Development). 2015. "Poverty and Social Impact Analysis: Strengthening Safety Nets in Djibouti." Report AUS7544, World Bank, Washington, DC. www.worldbank.org/transport/roads/rdt_docsannex1.pdf. World Bank. 2014. Djibouti Country Partnership Strategy 2014–17. Washington, DC: World Bank. 337 <>Chapter 10 <>Consumer Subsidies in the Islamic Republic of Iran: Simulations of Further Reforms Mohammadhadi Mostafavi Dehzooei and Djavad Salehi-Isfahani <>Introduction The Islamic Republic of Iran is a major producer of oil and gas, and therefore it is not surprising that the country subsidizes energy heavily. In 1995 energy subsidies were estimated at $5 billion or 6 percent of gross domestic product (GDP) (Salehi-Isfahani 1996), and with rising world prices in the following decades, the subsidies rose several times over to reach more than 15 percent of GDP (Jensen and Tarr 2003; Salehi-Isfahani 2014). During the oil boom of the 2000s, when the world price of energy trebled, the country's domestic price failed to keep pace, and subsidies ballooned. Despite several small adjustments in the domestic price of oil and gas since 1995, energy prices in the Islamic Republic of Iran have diverged from their opportunity cost. In January 2010 a bold law was enacted that required the government to raise energy prices to a level equal to 90 percent of the free on board (FOB) price of energy in the Persian Gulf. The law also stipulated that the revenues from the price increases should be divided into three parts: 50 percent to compensate households, 20 percent to compensate firms, and the remaining 30 percent to be added to government revenues. In December 2010 prices of consumer goods were increased, by factors ranging from 2 (for bread) to 9 (for diesel), and monthly cash transfers of 455,000 rials (Rls), or about $90 (U.S. dollars) in purchasing power parity (PPP) per capita started reaching about 95 percent of the population. Although the reform was successful in raising energy and bread prices several times over and the cash transfer scheme allowed the price shock to go forward without any protest, four years later much of the program’s initial gains have been lost to inflation, and opposition to further sharp price adjustments is strong. In the meantime, the collapse of the price of oil in the world markets has narrowed the gap between prices in the Islamic Republic of Iran and the outside world, diminishing the urgency of further subsidy reform. President Hassan Rouhani, who took office in August 2013, introduced the second phase of price increases, raising the average price of energy and bread by about 30 percent. His administration appears determined to follow up with gradual 338 increases in energy prices. This chapter examines the consequences of further price reforms for consumer welfare and the government budget. It presents simulation results that compare the effects of gradual price reform, which is the likely course of action, with a one-time increase that removes all the subsidies, which is similar to the 2010 reform. Although energy subsidies are lower than they were in 2010, the logic of removing them is stronger, especially for the government. Lower world oil prices, which have ostensibly reduced the need to raise domestic prices, have at the same time made it more urgent for the government to seek more revenue from its domestic sale of energy, which is more than three times what it exports. Besides budgetary concerns, energy subsidies raise equity issues because they distribute the national hydrocarbon wealth unequally. This chapter shows that subsidies for energy products accrue mainly to upper-income groups, who use more energy than the poor. Efficiency is another concern. Decades of cheap energy distorted Iranian production to be more dependent on energy and less efficient in its use. As shown in figure 10.1, before 1987 the Islamic Republic of Iran consumed less energy for each dollar of production compared to the world and Organisation for Co-operation and Development (OECD) countries. Since then the country has increased its use of energy per dollar of GDP, and the rest of the world has decreased it. In 2009 the Islamic Republic of Iran consumed 50 percent more energy per unit of GDP than the rest of the world. Moreover, subsidized energy is detrimental to the environment. The country produces more than its share of greenhouse gases, and pollutants have made the air in its major urban centers unbearable. As with snow days in the United States, Tehran's schoolchildren get days off from school because of pollution, which has become a part of normal life. Finally, low energy prices have also encouraged the use of capital-intensive technologies, which limit demand for labor at a time when youth are entering the labor force in record numbers. Figure 10.1: Energy Consumption in the Islamic Republic of Iran, the World, and OECD Countries 339 200 Tons of oil equivalent to $1,000 of 180 160 140 120 GDP Iran, Islamic Rep. 100 World 80 OECD members 60 40 20 0 Source: WDI various years, World Bank calculations. Note: GDP = gross domestic product; OECD = Organisation for Economic Co-operation and Development. [[Typesetter: change data lines and legend to broken lines.]] There is a small literature on the Islamic Republic of Iran’s subsidy reform. Several papers describe the reform. Guillaume, Zytek, and Farzin (2011), Salehi-Isfahani, Stucki, and Deutschmann (2013), Salehi-Isfahani (2014), and Salehi-Isfahani and Mostafavi Dehzooei (2015) evaluate the impact of the cash transfer on household labor supply. Gahvari and Karimi (2013) use an Almost Ideal Demand System (AIDS) model to study the reform and find that cash transfers improve welfare, at least for poor deciles. Gahvari and Taheripour (2011) use prereform data and the Quadratic Almost Ideal Demand System (QAIDS) to predict the impacts of a price reform in the country. In their general equilibrium framework, they find that eliminating subsidies for utilities results in substantial welfare losses. Jensen and Tarr (2003) use a computable general equilibrium (CGE) model to simulate the effect of reform of subsidies and find that “even nontargeted direct income payments to all households (not just the poor) would enormously and progressively increase the incomes of the poor.” The plan of this chapter is as follows. The next section offers a more detailed account of the evolution of subsidies and is followed by a section that explains our sources of data. The next sections derive the distribution of subsidies as they existed in 2013, present the simulations results, and discuss the political economy of subsidy reform. 340 <>Evolution of Subsidies The Islamic Republic of Iran has subsidized a variety of goods besides energy—bread and medicine, in particular—but energy subsidies have been by far the largest part and the part that has increased the fastest in recent decades. One reason for this increase was the rise of global prices. From 1999 to 2008 the price of oil increased tenfold, raising the opportunity cost of oil used domestically and the amount of subsidies to oil-based products. Energy subsidies have also increased because domestic consumption of oil and gas has grown from about 1 million barrels per day (mbd) in the 1970s to about 4 mbd oil and gas in 2013. In oil exporting countries, subsidies tend to rise and fall with the global price of energy. Governments let energy prices stagnate during the periods of rising global oil prices because they are flush with revenue and see no need to charge domestic consumers the world price. Distortions increase further because the expenditure of rising oil revenues leads to inflation, led by the price of nontradable goods and services, which reduces the price of energy products relative to other goods. At the end of an oil boom, as in 2014–15, revenues from exports decline, and governments become more interested in eliminating subsidies. The Iranian government delivers more than 4 million oil equivalent barrels of energy (gasoline, natural gas, and electricity) each day to consumers inside the country. In 2013, before the collapse of oil prices, the total value of this energy reached $100 billion per year. With the domestic price of energy roughly about one-third of the world market, some $66 billion of this can be counted as subsidy. In 2014, as a result of the collapse of oil prices, the amount of the implicit subsidy declined substantially. Given the uncertainty about the future price of oil, it is difficult to define a zero-subsidy price for future years. A major part of subsidies in the Islamic Republic of Iran are implicit and due to the gap between the domestic and world price of energy, but a good part, especially the subsidies for food and medicine, are explicit and are financed from the general budget and therefore compete with other expenditures more directly. The rationale for both types of subsidies is social protection. Protecting the poor was a widely advertised slogan of the 1979 revolution. Although subsidies existed for many of these commodities before the revolution, they took a more essential role as the ethos of the populist state. 341 There were several attempts at energy price reform in the 1990s, but none succeeded in closing the gap between prices in the Islamic Republic of Iran and the world markets to any significant degree. During the administration of President Mohammad Khatami (1997–2005), the conservative political opposition dominated the parliament and stymied any major reduction in subsidies. In 2004 the conservative-dominated parliament passed a law preventing the government from raising energy prices. Figure 10.2 shows the history of energy prices since 1994 in Iranian rials (Rls) and in U.S. dollars ($).1 The impact of fixing the price of energy products is visible in this graph after 2004 when global crude prices doubled. Figure 10.2: Energy Prices in the Islamic Republic of Iran, 1994–2012 a. Prices in rials b. Prices in U.S. dollars 8,000 0.6 0.5 6,000 0.4 Rials US$ 4,000 0.3 0.2 2,000 0.1 0 0 Gasoline Gasoil Natural gas Electricity Source: Ministry of Energy 2013. Note: During much of this period the Islamic Republic of Iran had multiple exchange rates. We use the rial-dollar exchange rate that is reported by the Central Bank of Iran for the parallel or free market. For energy prices with two rates, rationed and free, we use the latter. [[Typesetter: change data lines and legend to broken lines.]] Khatami’s populist successor, Mahmoud Ahmadinejad, had the support of the parliament for energy price reform, but little was done on this during most of his first term (2005–09). In 2008 the government and the parliament started discussions for a major price reform, which eventually became the Targeted Subsidy Reform Act in January 2010, six months after Ahmadinejad’s 342 controversial election to his second term, 2009–13. Subsidy reform was the centerpiece of his economic program, but its implementation was delayed until December 2010, when prices for bread and energy products were raised in one go by factors varying from 2 to 9 times. The decision whether to increase prices in one step or gradually was a difficult one. Gradual increases are preferred if they can be maintained over several years as prices catch up with their intended targets. In the Islamic Republic of Iran the experience with gradual increases had not been encouraging. Getting both the government and the parliament to commit to future increases proved unsuccessful because of the country's fluid politics. Small increases in one year were rarely followed by further increases as the powerful lobbies for low energy prices (such as the petrochemical and auto industries) often mustered enough support in the following year to block further increases. This experience, plus the government’s interest in generating enough revenue for redistribution, provided the impetus for shock therapy. The reform included a massive cash transfer program, which was launched simultaneously with the price hikes. The cash transfer program was efficiently executed, depositing Rls 445,000 per person per month in individual bank accounts. Initially, this amount was 28 percent of the median household income, and 50 percent of the income of a minimum-wage worker with a family of four (Salehi-Isfahani, Stucki, and Deutschmann 2013). According to the government, during the first four months of the program, about 62 million people (about 82 percent of the total population) started to receive cash transfers. This number increased quickly to cover about 95 percent of the population. Survey data indicate that coverage in rural areas where banks are less accessible was lower than in urban areas (Salehi-Isfahani, Stucki, and Deutschmann 2013). <>Data The data used in this chapter are derived from the Household Expenditures and Income Survey (HEIS) collected annually by the Statistical Center of Iran (SCI). The survey is nationally representative and two-stage stratified, at the urban and rural level and by province. The survey is weighted, and the sampling weights are provided by the SCI. This survey includes information on expenditures and incomes of urban and rural Iranian households. We use the most recent sample collected in Iranian year 1392, which corresponds to March 20, 2013, to March 19, 2014, and we refer to it as 2013–14 hereafter. 343 Table 10.1 presents the descriptive statistics for the 2013–14 sample. The survey frequencies have been inflated using sampling weights to reflect population level values. The population of 80 million is divided into ten equal size deciles (with varying number of households). Per capita expenditures is Rls 53 million per year (about $1,664 and $6,200 in PPP). Prices of subsidized items were set through both government control and subsidy. For bread, for example, the government bought domestically produced wheat at Rls 10,150 per kilogram in 2013–14, which was close to international market price. Wheat was then sold at the subsidized price of around Rls 460 to flour producers, who sold it at Rls 5,900 ($0.20) per kilogram to bakers. The government then controls the price of bread sold at bakeries: each kilogram of bread was then sold at Rls 10,274. In rural areas where households bake their own bread, the government sells flour up to a quota at subsidized price. Liquefied petroleum gas (LPG) is also sold at a subsidized price mostly in regions without natural gas pipeline. Alongside bread, LPG and kerosene have linear pricing, but other subsidized items are subject to nonlinear pricing with quotas that vary according to season and a region’s climate (natural gas and electricity) and type of vehicle (gasoline and diesel). LPG sold at Rls 1,800 ($0.06) per kilogram at the time, and the kerosene price was Rls 3,500 ($0.11) per liter. Prices of subsidized goods are given in table 10.2. Table 10.10: Population and Household Expenditures, 2013–14 Number Populatio of Total Expenditures Expenditures Househol Expenditure n househol expenditures per capita per household d size decile (x106) ds (x1012 rials) (x106 rials) (x106 rials) (x106) 1 (poorest) 8.1 1.8 4.5 116.4 14.5 65.4 2 8.0 1.9 4.2 174.9 21.7 92.1 3 8.0 2.0 4.0 217.9 27.1 109.3 4 8.1 2.1 3.8 260.4 32.3 123.9 5 8.0 2.2 3.7 304.2 37.9 140.4 6 8.1 2.3 3.6 358.6 44.5 158.3 7 8.0 2.3 3.4 426.1 53.0 182.2 8 8.0 2.4 3.3 516.0 64.1 213.1 9 8.1 2.6 3.1 671.2 83.4 256.2 10 (richest) 8.1 3.0 2.7 1,242.8 154.4 409.8 Total 80.5 22.6 3.6 4,288.5 53.3 189.6 Source: World Bank calculation using SUBSIM and HEIS 2013. Note: We use the sampling weights provided for the HEIS by the Statistical Center of Iran to inflate sample values to population level. These weights overestimate Iran’s population by about 3 million. HEIS = Household Expenditure and Income Survey; SUBSIM = SUBsidy SIMulation. 344 Gasoline had a two-tier price to begin with: Rls 1,000 per liter for rationed and Rls 4,000 for free market gasoline from 2010, and these prices rose to 4,000 and 7,000, respectively, in 2013. To control the quota, all vehicles have an electronic card that helps the government keep track of their monthly consumption. The quota differs by type of vehicle. Motorcycles had 25 liters per month of the subsidized gasoline in 2013–14. Cars, other than taxis and government vehicles, had 60 liters. In our data, we have the information only on how much gasoline each household bought altogether, but a household may have a car, a motorcycle, or both. In our calculations we assume that all consumed gasoline is used in cars. Natural gas and electricity prices have more tiers, and they also depend on the season and regional climate. The effective national average price of natural gas was Rls 742 per cubic meter (m3) (Ministry of Energy 2013). Prices started at Rls 700 per m3 (about $0.01), increasing to Rls 3,500 (about $0.12) for large users. Similarly, the average price of electricity for households was Rls 337 per kilowatt hour (kWh), with tariffs increasing from Rls 300 to Rls 2,150 per kWh. The rising tariff for natural gas is shown in figure 10.3. Figure 10.3: Natural Gas Price Schedule in 2014, in rials per cubic meter 4,000 3,500 3,000 2,500 Rials 2,000 1,500 1,000 500 0 <45 <95 <145 <195 <245 <295 <345 <395 <445 <495 <545 >546 Consumption level, cubic meter Source: National Iranian Gas Company, 2013. [[Typesetter: change bar color to gray.]] 345 <>Distribution of Subsidies This section describes the distribution of subsidies for bread and energy products in 2013–14. Calculating the exact level of the subsidy is not a trivial task. Many subsidies, such as gasoline sold to households, are direct, while others, such as gasoline used in transportation, are indirect. Here, we are concerned with direct subsidies only. The calculation of direct subsidies is also complicated by two facts. First, most of the subsidies are implicit, so they do not appear in the budget. World market prices serve to estimate the value of implicit subsidies. Second, except for bread, kerosene, diesel, and LPG, other subsidies are nonlinear. Gasoline is sold at two prices—a rationed and a free price—and tariffs for natural gas and electricity are differentiated by volume. In addition, prices for electricity and natural gas vary according to the season and a region’s climate. At the start of the reforms in 2010, gasoline had a two-tier price: Rls 1,000 per liter for rationed and Rls 4,000 for free market gasoline. In December these prices were increased to 4,000 and 7,000, respectively. The new free market price was about $0.70 per liter, which was close to its border price, but by 2014, following the 200 percent depreciation of the rial, it had fallen to about $0.25 per liter, well below the border price. The price of diesel, which had the highest subsidy, was initially set to increase 22 times, but was reduced to 9 times following protests by truck drivers. In 2013–14, the price of diesel was raised again, to Rls 3,500 ($0.11) per liter, which was about one-sixth of its border price. Table 10.2 presents the prices of the main energy products and bread in 2013–14 and their respective free market levels. The prices we use in the calculation of subsidies in this section, as well as in simulations in the next section, are more detailed than appear in table 10.2; in particular, they take into account the nonlinear price structure of energy products in the Islamic Republic of Iran. For example, the effective national average price of natural gas was Rls 742 per cubic meter (Ministry of Energy 2013). In reality, prices started at Rls 300 per m3 (about $0.01) and increased to Rls 3,500 (about $0.12) for big users. Similarly, the average price of electricity for households was Rls 337 per kWh, and tariffs increased from 300 per kWh to 2,150 for the high-end users. Bread prices are set through government control and subsidy. The government buys domestically produced wheat at Rls 10,150 per kilogram, which is close to international market price. Wheat 346 is then sold at the subsidized price of around Rls 460 to flour producers. In 2013–14 flour sold at Rls 5,900 ($0.20), per kilogram to bakers. Each kilogram of bread was then sold at Rls 10,274. Table 10.11: Price of Subsidized Items and Free Market Gasoline Diesel Kerosene Natural gas LPG Electricit Bread Flour y (liter) (liter) (3 ) (3 ) (kg) (kg) (kWh) Up to More than Price in 2013 60 liters 60 liters Iran, Islamic 4,000 7,000 3,500 1,000 742b 1,800 337.5b 10,274 5,900 Rep. Free market 23,811 23,811a 22,986a 22,639a 13,317c 10,800c 4,800d 21,800 14,70 a e 0e Source: Ministry of Energy 2013, except for explicit data in the note. Note: a. Based on FOB Persian Gulf price, Platts.com. b. Effective national average price, Ministry of Energy 2013. c. Average Europe price, FERC and www.cngeurope.com, 2013. d. Price in Turkey, Turkish Statistical Institute 2013. e. Based on international wheat price and authors’ calculations. Using these data from the survey with SUBSIM (SUBsidy SIMulation) enables us to estimate the distribution of subsidies among households. Table 10.3 shows the distribution of per capita expenditures on subsidized goods by deciles of per capita expenditures. Except for bread and kerosene, per capita expenditures on subsidized goods increase sharply with the decile of expenditures. The ratio of expenditures on bread between the richest and poorest deciles is 1.24, compared to 11.1 for gasoline and 3.7 for natural gas (household consumption of diesel is very small, so this ratio is not very informative). The SUBSIM estimates show that the total value of the subsidy paid directly to households (implicit plus explicit subsidies) amounted to Rls 540 trillion per year, or about $18 billion at the market exchange rate (Rls 30,000 = $1.00). This amount is considerably below the $66 billion mentioned at the beginning of this chapter. That calculation was based on the gap between the total value of energy products consumed in the Islamic Republic of Iran evaluated at world and domestic prices. 347 Table 10.12. Expenditures per Capita on Subsidized Products, in thousand rials Expenditu Kerosen Gasolin Electricit Diese Natural Breadb LPG Total re decile e e y la gasc 1,100. 1,966. 1 (poorest) 72.6 166.0 291.9 0.8 213.0 121.3 8 1 1,182. 2,384. 2 112.2 275.8 382.6 3.2 326.1 101.4 9 0 1,187. 2,587. 3 103.0 365.3 416.6 0.0 422.6 92.5 5 3 1,252. 2,944. 4 119.5 481.2 490.0 4.5 509.7 87.5 0 2 1,251. 3,121. 5 125.3 569.6 530.6 3.0 566.0 76.0 9 9 1,331. 3,423. 6 114.7 681.5 563.8 0.4 661.5 70.8 0 2 1,259. 3,691. 7 104.9 836.6 643.5 4.8 776.6 65.4 7 2 1,309. 3,865. 8 98.1 902.6 681.2 12.2 807.0 54.7 4 1 1,321. 4,339. 9 67.7 1,199.5 762.6 3.6 942.8 42.1 3 2 10 1,364. 5,709. 100.5 1,843.0 1,147.8 12.2 1,196.2 45.9 (richest) 3 3 1,256. 3,403. Total 101.8 732.2 591.1 4.5 642.2 75.7 1 3 Ratio of 0.38 richest to poorest decile 1.38 11.10 3.93 15.37 1.24 5.62 2.90 Source: World Bank calculation using HEIS 2013. Note: a. Household consumption of diesel fuel is small compared to its use in transportation, which is included in the indirect effects. b. Bread includes flour. c. Natural gas data included compressed natural gas (CNG) used in cars. HEIS = Household Expenditure and Income Survey. Viewed from the perspective of incidence, the value of subsidies for the poor and the rich is quite different. Defining incidence as the proportion of the subsidies to household expenditures, we 348 can see from table 10.4 that subsidized products matter much more for the poor than for the rich. The poorest decile spends 13.6 percent of its expenditures on subsidized goods compared to 3.7 percent for the richest decile. The poor’s dependence on subsidies was greatest for bread, natural gas, and electricity. Households in the poorest decile spent 7.6 percent of their budget on bread compared to less than 1 percent for those in the richest decile. The gasoline subsidy, which is unequally distributed between the poor and the rich, accounts for similar proportions of the budgets of different deciles. As a result, the poor would sooner agree to a price reform for gasoline, which would not affect them much, than bread, which makes up a larger proportion of their budget. But, with compensation, they would stand to gain from a gasoline price reform. Table 10.4: Expenditure on Subsidized Products over Total Expenditures, in percent Expendit Kerose Gasoli Electrici Diese Brea Natural LPG Total ure decile ne ne ty l d gas 1 0.5 1.1 2.0 0.0 7.6 1.5 0.8 13.6 (poorest) 2 0.5 1.3 1.8 0.0 5.4 1.5 0.5 11.0 3 0.4 1.3 1.5 0.0 4.4 1.6 0.3 9.6 4 0.4 1.5 1.5 0.0 3.9 1.6 0.3 9.1 5 0.3 1.5 1.4 0.0 3.3 1.5 0.2 8.2 6 0.3 1.5 1.3 0.0 3.0 1.5 0.2 7.7 7 0.2 1.6 1.2 0.0 2.4 1.5 0.1 7.0 8 0.2 1.4 1.1 0.0 2.0 1.3 0.1 6.0 9 0.1 1.4 0.9 0.0 1.6 1.1 0.1 5.2 10 0.1 1.2 0.7 0.0 0.9 0.8 0.0 3.7 (richest) Total 0.2 1.4 1.1 0.0 2.4 1.2 0.1 6.4 Source: World Bank calculation using SUBSIM and HEIS 2013. Note: HEIS = Household Expenditure and Income Survey. Figure 10.4 combines the information in tables 10.3 and 10.4 to depict the main dilemma of subsidy reform. The shaded areas are expenditures per person per year, measured in Rls 1,000, on various energy products and bread (left y-axis). Assuming that the subsidies that directly accrue to households (as distinct from the indirect benefits from lower transportation costs, for example) are proportional to expenditures on these items (which is the case with linear prices), this graph also depicts the distribution of the subsidies. The richest decile spent on average more 349 than Rls 5 million per person (about $584 PPP) per year on these subsidized products, compared to Rls 2 million for the poorest decile (about $234 PPP). In a sense, the gasoline subsidy is the most regressive because the richest decile receives about 15 times as much of it as the poorest decile. By contrast, the bread subsidy is almost uniformly distributed. The right y-axis captures the main political economy dilemma in subsidy reform. The solid line shows the share of expenditures on subsidized products in total expenditures for each decile of per capita expenditures. As a proportion of total expenditures, the poorest decile spends nearly four times as much on subsidized goods—13.6 percent compared to 3.7 percent—and therefore stands to lose more if energy prices are increased without compensation. This chart shows that we should expect the direct welfare effects of price reforms to be greater for the poor than the rich. The indirect effects, through higher prices in other goods and services that use energy, are more equally distributed and rise with income. Still, the overall negative effect on the poor is sufficient to justify some form of social protection, either direct compensation or reliance on the existing social protection mechanisms. Figure 10.4: Expenditures per Person per Year on Subsidized Goods and Their Share in Total Expenditures in 2013–14, by decile (1,000 rials) 6,000 16 Share of total expenditures (percent) Expenditures per person per year 14 5,000 12 Gasoline (thousand rials) 4,000 10 Electricity 3,000 8 Natural gas 6 Kerosene 2,000 4 LPG 1,000 2 Bread and flour 0 0 Expenditures share 1 2 3 4 5 6 7 8 9 10 Deciles Source: Data from tables 10.3 and 10.4. [[Typesetter: change data depictions and legend to shades of gray or patterns. The author is concerned about losing the color. What is a good compromise?]] 350 <>Simulations of Subsidy Reform This section presents the simulation results of two hypothetical price reforms. Scenario 1, labeled "gradualist," increases the prices of subsidized goods by 10 percent across the board. Scenario 2, "full adjustment," assumes a much larger adjustment, taking all prices to close to their FOB or European levels (for electricity and natural gas) in 2014. Scenario 1 is interesting because it is the choice likely to be implemented. Scenario 2 is not on the agenda at present, but it is useful to consider because it was adopted in 2010 and serves as a comparison for the gradualist scenario. Since taking office, the Rouhani government has opted for small price adjustments. Following the country’s bad experience with full adjustment in 2010, there is a no public support for a large price increase. The sharp decline in the global price of oil in 2014 has also reduced the need or urgency for raising domestic prices of energy. In spring 2014 all prices for subsidized goods were raised by about 30 percent (the bread price increase came in November), except gasoline, which went up by about 50 percent. In spring 2015 prices were again raised, this time by about 15 percent. Both of these increases are less than our gradualist scenario because the 10 percent increase in our scenario is in real terms, and the price adjustments under Rouhani were hardly enough to correct for inflation in the preceding 12 months, which were 34.5 percent in 2013–14 and 15.5 percent in 2014–15. The price increases that would have matched this scenario would have been 44.5 percent in 2014 and 25.5 percent in 2015. Scenario 2 assumes that global oil prices recover to their average for 2014; that is, it aims for full elimination of subsidies. For bread a 60 percent increase brings its price close to the zero-subsidy level. Bread prices are set by a combination of government control and subsidy. Flour is sold at subsidized prices to bakers, whose prices are monitored. A substantial part of the wheat consumed in the country is imported, which can be considered as opportunity cost. In 2013 the support price set by the government for domestically produced wheat was Rls 10,150 ($0.30) per kilogram, which is close to the world market, so it can be used as the target price. Currently, however, the government sells flour to bakers at Rls 8,490 per kilogram, which would not reach the zero-subsidy level with a 10 percent increase. Determining the energy prices that would fully eliminate the energy subsidies is difficult. Given the volatility in the global price of oil, it is hard to pinpoint the medium-term opportunity cost of 351 Iranian oil and gas. At $50 a barrel, for example, the FOB price of gasoline in the Islamic Republic of Iran is about the free-market price of gasoline. Scenario 2 assumes that the world oil price returns to the average for 2014, $96.30. The list of target prices used in both scenarios is presented in table 10.5. For traded commodities, we set the target price at opportunity costs as implied by the average crude price in 2014. For gasoline, diesel, and kerosene, whose global prices declined by nearly 50 percent during 2014, we take the average FOB Persian Gulf level—Rls 21,950 ($0.69) per liter for gasoline, Rls 21,189 ($0.66) for diesel, and Rls 20,869 ($0.65) for kerosene. These average prices would equal opportunity cost if world oil prices were to return to the level prevailing around September 2014. The price of natural gas varied much less than crude oil during 2014, but has its own complexity because there is no regional market as transparent as the one for gasoline. We set the target price for natural gas at Rls 11,358 per m3 (about $0.35), which is less than the export price of Iranian gas to Turkey (about $0.50), but closer to the export prices charged by Azerbaijan for exports to Turkey. The prices combine compressed natural gas (CNG), used in transportation, with the natural gas supplied to consumers. There is no regional market of any kind for electricity that would guide the setting of the subsidy-free price. The Islamic Republic of Iran does export some electricity to Iraq, but there is no information on pricing for these exports, and in any case may involve a subsidy of its own due to political considerations. We therefore picked the target price of Rls 2,720 ($0.09) per kilowatt hour, which is close to the rate in Turkey but below the average in most middle-income developing countries (EIA 2015). This price is close to the prevailing price in Turkey, India, and Brazil. We use a demand price elasticity of −0.2 to calculate the postreform consumed quantities of subsidized goods and changes in government subsidy payments. Table 10.5: Price of Subsidized Items, in rials Gasoline Diesel Kerosene Natural gas LPG Electricit Bread Flour y (liter) (liter) (3 ) (3 ) (kg) (kg) (kWh) 352 Up to More than Price 60 liters 60 liters 2013 4,000 7,000 3,500 1,000 742.2b 1,800 337.5b 10,274 5,900 Scenario 1 4,400 7,700 3,850 1,100 816.42 1,980 371.25 11,301 6,490 (10 percent increase) Scenario 2 24,000 24,000a 23,000a 22,600a 11,358c 10,800c 2,720d 20,548 13,90 a e (opportunity 0e cost price) Source: Ministry of Energy 2013, except for explicit data in the note. Note: a. Based on FOB Persian Gulf price, Platts.com. b. Effective national average price, Ministry of Energy 2013. c. Average Europe price, FERC and www.cngeurope.com, 2014. d. Price in Turkey, Turkish Statistical Institute, 2014. e. Based on international wheat price and authors’ calculations. <>Scenario 1: Direct Effects This section reports the results of the gradualist scenario, increasing prices by 10 percent. We evaluate the impact of this reform on individual welfare and government revenues, starting with the direct effects of price increases on energy and bread. Direct effects measure the losses in welfare as reductions in real expenditures for households in different deciles of per capita expenditures. The model takes into account consumer responses to the price increases for these products, but ignores indirect or secondary effects caused by increases in prices of other goods and services. These secondary effects are considered in the next section, indirect effects. We present our estimates of the direct effects on well-being in table 10.6 and as proportion of per capita household expenditures in table 10.7. The data show that the largest effect in level and share is due to the increase in the price of bread, an average loss of welfare of Rls 125,600 per person per year and 0.24 percent of expenditures. The second largest average loss is for gasoline at Rls 73,200. The reason bread has a relatively large impact is that the average Iranian spends 67 percent more on bread than gasoline. Expenditures on bread amount to more than one-third of the total expenditures on subsidized goods. 353 The losses due to the increase in the bread price are more uniformly distributed across deciles of per capita expenditures than other commodities, increasing by 24 percent from the poorest to the richest decile. In the case of gasoline this increase is more than 10 times. The total loss on all items is on average Rls 340,300 per person per year (PPP $39.75), which is less than 1 percent of expenditures. The ratio of the overall loss in the richest to poorest decile is 2.9. The loss of welfare is better reflected as proportion of household expenditures (table 10.7). Contrary to the picture obtained from levels in table 10.6, the distributional impact of gasoline seems the least unequal and for bread the most unequal. Losses due to price increases for bread, natural gas, and gasoline figure prominently in the poorest decile’s budgets, but all are less than 1 percent. The overall impact is small because the share of these products in average per capita expenditures is 6.4 percent, so a 10 percent increase in their price does not have a large impact on the average consumer’s budget. Changes in quantities reported in annex table 10A.2 are also modest, showing average reductions of 7 kilowatt hour per person in electricity and 5 m3 of natural gas. Given the elasticity assumptions of −0.2, a 10 percent price increase reduces the quantity consumed by 2 percent. Table 10.6: Direct Effects of the Gradualist Scenario on per Capita Well-Being (thousand rials) Expenditure Kerosene Gasoline Electricity Diesel Bread Natural gas LPG Total decile 1 (poorest) −7.3 −16.6 −29.2 −0.1 −110.0 −21.3 −12.1 −196.6 2 −11.2 −27.6 −38.3 −0.3 −118.2 −32.6 −10.1 −238.4 3 −10.3 −36.5 −41.7 0.0 −118.7 −42.3 −9.2 −258.7 4 −11.9 −48.1 −49.0 −0.4 −125.2 −51.0 −8.7 −294.4 5 −12.5 −57.0 −53.1 −0.3 −125.1 −56.6 −7.6 −312.1 6 −11.5 −68.2 −56.4 0.0 −133.0 −66.1 −7.1 −342.3 7 −10.5 −83.7 −64.3 −0.5 −125.9 −77.7 −6.5 −369.1 8 −9.8 −90.3 −68.1 −1.2 −130.9 −80.7 −5.5 −386.5 9 −6.8 −120.0 −76.3 −0.4 −132.1 −94.3 −4.2 −433.9 10 (richest) −10.1 −184.3 −114.8 −1.2 −136.4 −119.6 −4.6 −570.9 Total −10.2 −73.2 −59.1 −0.4 −125.6 −64.2 −7.6 −340.3 Table 10.7: Direct Effects of Gradualist Scenario on Well-Being, in percentage of household expenditures 354 Expenditure Kerosene Gasoline Electricity Diesel Bread Natural gas LPG Total decile 1 (poorest) −0.05 −0.11 −0.20 −0.00 −0.76 −0.15 −0.08 −1.36 2 −0.05 −0.13 −0.18 −0.00 −0.54 −0.15 −0.05 −1.10 3 −0.04 −0.13 −0.15 −0.00 −0.44 −0.16 −0.03 −0.96 4 −0.04 −0.15 −0.15 −0.00 −0.39 −0.16 −0.03 −0.91 5 −0.03 −0.15 −0.14 −0.00 −0.33 −0.15 −0.02 −0.82 6 −0.03 −0.15 −0.13 −0.00 −0.30 −0.15 −0.02 −0.77 7 −0.02 −0.16 −0.12 −0.00 −0.24 −0.15 −0.01 −0.70 8 −0.02 −0.14 −0.11 −0.00 −0.20 −0.13 −0.01 −0.60 9 −0.01 −0.14 −0.09 −0.00 −0.16 −0.11 −0.01 −0.52 10 (richest) −0.01 −0.12 −0.07 −0.00 −0.09 −0.08 −0.00 −0.37 Total −0.02 −0.14 −0.11 −0.00 −0.24 −0.12 −0.01 −0.64 The sensitivity of the change in government revenue to the size of the price increase of individual subsidized goods is shown in figure 10.5. Government revenue is most sensitive to the size of increase in the prices of bread, natural gas, and gasoline. For example, a 100 percent increase in the price of bread increases government revenues by Rls 100 trillion (PPP $11.7 billion, or 5 percent of total government revenues), compared to Rls 80 trillion for natural gas and Rls 75 trillion for gasoline. In the present scenario, the total amount of subsidies paid out declines from Rls 484 trillion (PPP $56.5 billion) to Rls 447 trillion ($52.2 billion), a savings of Rls 37 trillion ($4 billion) for the government. Figure 10.5: Price Changes and the Impact on Government Revenue 355 Source: World Bank calculation using SUBSIM and HEIS 2013. Note: HEIS = Household Expenditure and Income Survey. We now turn to the impact of the gradualist reform scenario on poverty and inequality. We measure the poverty rate using the poverty lines of Rls 18 million per person per year in urban areas and Rls 12 million in rural areas. Implementing the gradualist price reforms increases the poverty rate from 4.95 percent to 5.30 percent and the poverty gap from 0.98 percent to 1.04 percent. Inequality, as measured by the Gini index, increases slightly from 37.36 to 37.49. These small changes are not surprising given the small price adjustment envisioned in the gradualist scenario. How sensitive are these changes in poverty to the size of the price increase? Figure 10.6 shows the sensitivity of the poverty rate to the size of price increases by commodity. Again, from the point of view of increase in poverty, bread is the most important commodity; a 60 percent 356 increase in its price increases the head-count ratio by 1 percentage point. Energy products have much smaller impacts. Figure 10.6: Percentage Change in the Poverty Rate by the Size of Price Increases Source: Authors’ calculation using SUBSIM and HEIS 2013. Note: HEIS = Household Expenditure and Income Survey. If the government wishes to keep the poverty rate from increasing, it must offer compensation. Figure 10.7 estimates the effect of universal and uniform transfers on the poverty rate. To prevent the poverty rate from increasing as a result of the direct effects of the 10 percent price adjustment, the government needs to pay each person Rls 204,703 per year (about $23.40), which is less than 4 percent of the current level of transfer). Doubling this amount reduces the poverty rate by 0.35 percentage points. 357 Figure 10.7: Impact of the Level of Transfer to Compensate Indirect Effects on Poverty in the Gradualist Scenario Source: World Bank calculation using SUBSIM and HEIS 2013. Note: Direct effects of the reform on well-being are considered only. HEIS = Household Expenditure and Income Survey. [[Typesetter: In figure 10.7: Chart area and legend: change the red and blue lines to broken black lines.]] <>Scenario 1: Indirect Effects The indirect effects are the secondary effects on the consumer budget that result from the increase in prices of energy-using sectors. SUBSIM uses an input/output table to take these secondary effects into account. The quality of the indirect estimates depends crucially on having an up-to-date I/O table. The latest I/O table for the Islamic Republic of Iran is from 2001, when 358 energy prices were very low. SUBSIM uses the rial values of intersector flows as input. We update the rial values of the I/O table to 2013 using the consumer price index (CPI). This calculation underestimates the dependence of other sectors on energy products because energy prices rose by a larger factor than the CPI during 2001–13. The CPI rose by a factor of 7, and energy prices rose by factors ranging from 10 to 20. The country's I/O table does not show individual prices for subsidized products; instead, it combines diesel, gasoline, and kerosene into one group. We include electricity and natural gas as separate items. As with direct effects, we raise the price of the group and individual items by 10 percent in real terms. In Table 10.8 we add the indirect and direct effects to get a more comprehensive picture of the impact on well-being of the gradualist scenario. These results update the direct estimates of impact shown in tables 10.6 and 10.7 (column 1 reproduces the totals column in table 10.6, and column 4 reproduces the totals column in table 10.7). Looking at per capita losses, we note that except for the tenth decile, indirect effects are smaller than the direct effects, but they are less equally distributed. The ratio of the loss suffered by the richest to the poorest decile is 2.9 compared to 5.2. Losses as proportion of household expenditures, shown on the right side, indicate that direct effects, measured relative to household expenditures, are smaller than direct effects and their distribution is more equal. Including the indirect effects does not change our assessment of the impact of the price increase on poverty and inequality by much (table 10.9). Table 10.8: Direct and Indirect Effect of the Gradualist Scenario on Household Welfare Per capita, in rials Percent of total expenditures Expenditure Indirect Direct effects Indirect effects Total Direct effects Total decile effects −196.6 −121.3 −317.9 −1.36 −0.77 −2.13 1 (poorest) 2 −238.4 −169.9 −408.4 −1.10 −0.71 −1.81 3 −258.7 −180.3 −439.0 −0.96 −0.6 −1.56 4 −294.4 −207.5 −501.9 −0.91 −0.58 −1.49 5 −312.1 −234.6 −546.7 −0.82 −0.56 −1.38 6 −342.3 −251.0 −593.3 −0.77 −0.5 −1.27 7 −369.1 −341.8 −710.9 −0.70 −0.58 −1.28 8 −386.5 −333.2 −719.7 −0.60 −0.46 −1.06 9 −433.9 −386.3 −820.2 −0.52 −0.41 −0.93 10 (richest) −570.9 −631.9 −1202.8 −0.37 −0.37 −0.74 359 Total −340.3 −292.6 −632.9 −0.64 −0.48 −1.12 Source: World Bank calculation using SUBSIM and HEIS 2013. Table 10.9: Direct and Indirect Impacts of Gradualist Subsidy Reform on Poverty and Inequality Prerefor Postreform m Change in per capita expenditures (thousand −632.91 rials) Poverty head count 4.95 5.48 (percent) Poverty gap (percent) 0.98 1.072 Gini ( percent) 37.36 37.55 Source: World Bank calculation using SUBSIM and HEIS 2013. As before, we calculate the required transfer to prevent an increase in poverty. To compensate for the indirect effect so that poverty rate remains at 4.95 percent, the government needs to pay Rls 131,824 per person per year (figure 10.8), compared to Rls 204,703 for the direct effects (figure 10.7). Figure 10.8: Impact of the Level of Transfer to Compensate Indirect Effects on Poverty in the Gradualist Scenario 360 Source: World Bank calculation using SUBSIM and HEIS 2013. Note: Indirect effects of the reform on wellbeing are considered only. HEIS = Household Expenditure and Income Survey. [[Typesetter: In figure 10.8: Chart area and legend: change the red and blue lines to broken black lines.]] <>Scenario 2: Direct Effects In the full adjustment scenario we increase prices according to the values in table 10.5 by factors ranging from 2 for bread to 20 for kerosene. We use the Cobb-Douglas routine of SUBSIM because the marginal approach is much less accurate for large price changes. We present the results for this scenario first for the direct effects followed by the indirect effects. As expected, the impact on household welfare in this scenario is much larger than the gradualist scenario. Looking at the impact as a percentage of per capita expenditures (tables 10.10 and 10.11), we note that the average impact is 11.46 percent compared to 0.64 percent in the gradualist scenario, higher by a factor of 17 (compared to a higher average price increase of 7 361 times). The loss for the poorest decile increased from 1.36 percent in the gradualist scenario to 24.06 percent in full adjustment. The richest decile’s loss increased from to 0.37 to 6.61 percent, which is similar to the change in impact for the poor. Table 10.10: Direct Effects of the Full-Adjustment Scenario on per Capita Well-Being, (thousand rials) Expenditure Bread Kerosene Gasoline Electricity Diesel Natural gas LPG Total decile and flour 1 (poorest) −432.4 −390.8 −210.2 −4.0 −1,169.7 −664.0 −606.5 −3,477.5 2 −668.3 −640.8 −260.8 −16.4 −1,236.3 −1,005.3 −507.0 −4,334.9 3 −613.7 −840.2 −282.4 −0.2 −1,227.2 −1,255.2 −462.4 −4,681.3 4 −711.5 −1,094.5 −316.6 −22.7 −1,286.8 −1,481.4 −437.4 −5,351.1 5 −746.4 −1,292.6 −337.1 −15.0 −1,283.6 −1,607.8 −380.2 −5,662.7 6 −683.0 −1,542.0 −353.5 −2.2 −1,355.2 −1,850.8 −353.8 −6,140.6 7 −624.6 −1,885.7 −387.0 −24.2 −1,283.0 −2,114.1 −326.8 −6,645.5 8 −584.6 −2,030.8 −404.1 −61.7 −1,327.3 −2,191.2 −273.5 −6,873.2 9 −403.3 −2,679.6 −451.0 −18.4 −1,335.9 −2,574.4 −210.3 −7,672.9 10 (richest) −598.7 −4,075.1 −596.4 −61.5 −1,375.7 −3,274.2 −229.7 −10,211.2 Total −606.6 −1,647.3 −359.9 −22.6 −1,288.1 −1,801.9 −378.7 −6,105.3 Source: World Bank calculation using SUBSIM and HEIS 2013. Table 10.11: Direct Effects of Full Adjustment Scenario on Well-Being, in percentage of household expenditures Expenditure Bread and Natural Kerosene Gasoline Electricity Diesel LPG Total decile flour gas 1 (poorest) −2.99 −2.70 −1.45 −0.03 −8.09 −4.59 −4.20 −24.06 2 −3.07 −2.95 −1.20 −0.08 −5.68 −4.62 −2.33 −19.93 3 −2.27 −3.10 −1.04 −0.00 −4.53 −4.63 −1.71 −17.28 4 −2.20 −3.39 −0.98 −0.07 −3.98 −4.59 −1.35 −16.56 5 −1.97 −3.41 −0.89 −0.04 −3.39 −4.25 −1.00 −14.96 6 −1.53 −3.46 −0.79 −0.00 −3.04 −4.16 −0.79 −13.79 7 −1.18 −3.56 −0.73 −0.05 −2.42 −3.99 −0.62 −12.55 8 −0.91 −3.17 −0.63 −0.10 −2.07 −3.42 −0.43 −10.72 9 −0.48 −3.21 −0.54 −0.02 −1.60 −3.09 −0.25 −9.21 10 (richest) −0.39 −2.64 −0.39 −0.04 −0.89 −2.12 −0.15 −6.61 Total −1.14 −3.09 −0.68 −0.04 −2.42 −3.38 −0.71 −11.46 Source: World Bank calculation using SUBSIM and HEIS 2013. 362 In contrast to the gradualist scenario, we see a significant quantity adjustment in this case (table 10.12). Average electricity consumption declines by 105.78 kilowatt hours (a decline of 30 percent in consumption), and natural gas by 161.77, which is a decline of less than one-forth. The natural gas consumption by the poorest decile is estimated to decline by about 78 percent, which is unrealistic, and the result of assuming a fixed elasticity for all levels of consumption and income. In this scenario bread continues to have the largest impact on the welfare of the poor, followed by natural gas and kerosene. Table 10.12: Impact on the per Capita Consumed Quantities in the Full Adjustment Scenario, direct effects Bread and LPG Expenditure Kerosene Gasoline Electricity Diesel Natural gas flour (m3) decile (liter) (liter) (kWh) (liter) (m3) (kilogram ) 1 (poorest) −24.20 −12.65 −66.91 −0.23 −26.56 −61.85 −67.39 2 −37.40 −20.43 −81.01 −0.93 −27.00 −94.15 −56.33 3 −34.35 −26.46 −87.46 −0.01 −26.07 −116.68 −51.37 4 −39.82 −34.00 −95.88 −1.29 −26.96 −135.76 −48.61 5 −41.77 −40.05 −101.22 −0.85 −26.73 −146.86 −42.24 6 −38.22 −47.59 −105.48 −0.12 −27.72 −166.70 −39.31 7 −34.96 −57.92 −113.00 −1.37 −26.26 −187.02 −36.31 8 −32.72 −62.23 −117.07 −3.49 −26.82 −195.06 −30.39 9 −22.57 −81.37 −130.44 −1.04 −26.81 −228.62 −23.37 10 (richest) −33.51 −122.11 −159.34 −3.48 −27.40 −284.93 −25.52 Total −33.95 −50.48 −105.78 −1.28 −26.83 −161.77 −42.08 Source: World Bank calculation using SUBSIM and HEIS 2013. Naturally, the impact of full adjustment on poverty and inequality are larger (table 10.13). The poverty rate increases to 11.59 percent, more than doubling, and the poverty gap more than triples, 0.98 percent compared to 3.91 percent. The Gini index increases from 37.36 to 40.70. The Gini index changes because the reform impact is different for each decile. The poor are affected more by the program relative to their total expenditures compared to the rich (see table 10.11). Note that this impact is before any cash transfer is paid to individuals. The cash transfer necessary to keep the poverty rate from increasing is estimated at Rls 4.4 million per person per year, 20 times higher than in the gradualist scenario. However, the savings of the government 363 outweigh this amount of transfer by Rls 139 trillion (PPP $16 billion), which is a substantial amount (about 9 percent of total government revenues). Table 10.13: Direct Impacts of Full-Adjustment Subsidy Reform on Poverty, Inequality, and Government Budget Prereform Postreform Change in per capita expenditures (Rls −6,105.34 thousand) Poverty head count 4.95 11.59 (percent) Poverty gap (percent) 0.98 3.91 Inequality (percent) 37.36 40.70 Subsidies (Rls trillion) 491.41 0 Transfers (Rls trillion)a 0 352.06 Change in total budget(Rls −139.35 trillion) Source: World Bank calculation using SUBSIM and HEIS 2013. Note: HEIS = Household Expenditure and Income Survey. a. The transfer refers to the required amount to offset the change in headcount poverty. Figure 10.9: Impact of the Level of Transfer to Compensate Indirect Effects on Poverty in the Full Adjustment Scenario 364 Source: World Bank calculation using SUBSIM and HEIS 2013. Note: Direct effects of the reform on well-being are considered only. HEIS = Household Expenditure and Income Survey. [[Typesetter: In figure 10.9: Chart area and legend: change the red and blue lines to broken black lines.]] <>Scenario 2: Indirect Effects To implement the price changes according to this scenario we need to find the average price increase for energy products that appear in one group in the I/O table. We use a weighted average of increases for prices of gasoline, diesel, and kerosene, which comes to 600 percent. For individual commodities, we assume a 200 percent increase for natural gas, 100 percent for bread, and 700 percent for electricity. 365 The results are presented in table 10.14. In contrast to the gradualist scenario, for richer deciles the indirect effects are larger than direct effects, though on average the effects of the two types are similar in size. The additional transfer required to maintain the poverty rate at prereform level of 4.95 percent is Rls 3.2 million per person per year (figure 10.10). Thus, the total required compensation for both the direct and indirect effects is Rls 7.5 million (PPP $876), which is about 40 percent larger than the current level of compensation. However, if we compare the same amount paid in 2011, the first year of the 2010 reform, with the estimated compensation here, we learn that the Ahmadinejad compensation plan exceeded what was necessary to keep poverty constant, by some 70 percent.2 Table 10.14: Direct and Indirect Effects of Price Increases on Well-Being in the Full Adjustment Scenario Per capita, thousand rials Percent of total expenditures Expenditure Indirect Direct effects Indirect effects Total Direct effects Total decile effects 1 (poorest) −3,477.5 −2,631.0 −6,108.5 −24.1 −18.2 −42.3 2 −4,334.9 −3,702.1 −8,037.0 −19.9 −17.0 −37.0 3 −4,681.3 −4,372.0 −9,053.3 −17.3 −16.1 −33.4 4 −5,351.1 −4,868.6 −10,219.7 −16.6 −15.1 −31.6 5 −5,662.7 −5,626.8 −11,289.5 −15.0 −14.9 −29.8 6 −6,140.6 −6,284.0 −12,424.6 −13.8 −14.1 −27.9 7 −6,645.5 −7,182.9 −13,828.4 −12.6 −13.6 −26.1 8 −6,873.2 −8,411.0 −15,284.2 −10.7 −13.1 −23.8 9 −7,672.9 −10,318.9 −17,991.8 −9.2 −12.4 −21.6 10 (richest) −10,211.2 −16,333.4 −26,544.6 −6.6 −10.6 −17.2 Total −6,105.3 −6,973.4 −13,078.7 −11.5 −13.1 −24.6 Source: World Bank calculation using SUBSIM and HEIS 2013. Figure 10.10: Impact of the Level of Transfer to Compensate Indirect Effects on Poverty in the Full Adjustment Scenario 366 Source: World Bank calculation using SUBSIM and HEIS 2013. Note: Indirect effects of the reform on wellbeing are considered only. HEIS = Household Expenditure and Income Survey. The value of 1.00e+ is 10,000,000. [[Typesetter: In figure 10.10: Chart area and legend: change the red and blue lines to broken black lines.]] The overall impact on poverty and inequality is reported in table 10.15. As a result of full adjustment, assuming no compensation, the head count ratio jumps fourfold, increasing from 4.95 percent to 20.12 percent, and the poverty gap increases sevenfold, from 0.98 percent to 7.31 percent. The Gini index increases by 5.05 points, which is large and shows that price increases for all the items considered here have a greater effect on the poor than on the rich. Removing subsidies has a large adverse impact on inequality because, as shown in table 10.4, the poor spend a larger proportion of their income on subsidized goods. The share of the expenditures on all subsidized goods to total expenditures is 13.6 percent for the poorest decile and 3.7 percent 367 for the richest decile. The highest disparity is for bread which, in 2013 accounted for 7.6 percent of the poorest decile expenditures compared to 0.9 percent for the richest decile. The next least equally distributed expenditure shares are for electricity, and here the share for the poorest decile is three time higher than for the richest decile. Naturally, any increase in price that is not moderated by a significant decrease in consumption will have a much larger impact on the poor than on the rich, thus increasing the inequality. It appears that the indirect effects are as important in increasing inequality as the direct effects. The change in the Gini coefficient as a result of the direct effects of removing the subsidies (in scenario 2) is from 37.36 to 40.70, which a about half of the change in Gini with the indirect effects added. This result suggests that half of the adverse impact of the removal of subsidies on inequality comes from the indirect effects. Table 10.15: Total Impact of Price Increases on expenditures, Poverty and Inequality in the Full Adjustment Scenario Prereform Postreform Change in per capita −13,078.73 expenditure (Rls thousand) Poverty head count 20.12 4.95 (percent) Poverty gap (percent) 0.98 7.31 Gini (percent) 37.36 42.41 Source: World Bank calculation using SUBSIM and HEIS 2013. Note: HEIS = Household Expenditure and Income Survey. <>The Political Economy of Reforms The most important political economy aspect of subsidy reform in the Islamic Republic of Iran is that much of the subsidies are government forgone earnings rather than cash expenditures. The government delivers daily about 4 million equivalent barrels of oil and gas, about three times as much as it currently exports, to domestic consumers, enterprises, and power companies at very low prices. 368 When oil prices are high the government is flush with revenues and does not feel the need to raise domestic prices of energy in tandem with global prices. When the world price of oil is down, government revenues and household incomes are also down, and that is the worst possible time to raise domestic energy prices. Given such price fluctuations, divergence between local and world prices of energy seems a natural part of the country’s political economy. Another political economy reason that energy subsidies are endemic in the Islamic Republic of Iran (and in other oil-rich countries) is that although energy subsidies are unevenly distributed, with most of it going to higher-income brackets, removing them hurts the poor more than rich. As shown in figure 10.4, as a share of household expenditures subsidies are larger for the poor than the rich. Moreover, the credibility of Iranian governments to remove energy subsidies and promise to spend the proceeds more equitably and efficiently is low, which explains why the large price reforms of 2010 had to include a generous cash transfer program. The unhappy history of energy price reform since 2010 also complicates the political economy of further energy price reform. Since 2010, for reasons unrelated to subsidy reform—sanctions and mismanagement of the economy—Iranians have experienced four years of stagnation and inflation, making them apprehensive of any new government-initiated price reform. A good part of the inflation in the four years following the reform had little to do with energy and bread price increases, but the Iranian media and public opinion believe otherwise. One contributor to inflation was that cash transfers were too generous and as a result the program was not fully funded. The government filled that gap with borrowing from the Central Bank, which fueled inflation. Another contributor to inflation was the low-cost housing Maskan Mehr program. According to the government, 40 percent of the monetary base was created to cover the deficit in this program. In addition to social spending, the country suffered sizable supply shock during 2011–13, as international sanctions tightened and disrupted its oil sale and general trade. As figure 10.11 shows, monthly rates of inflation decreased a few months after the reform but jumped back up with sanctions and devaluation. The much smaller price hikes in 2014, which were not followed up by other shocks, raised the rate of inflation for a few months before declining. Figure 10.11: Rates of Inflation and Macroeconomic Shocks from January 2010 to September 2014, 3-month moving averages with annualized rates 369 Sources: Central Bank of Iran, various years, and World Bank calculations. [[Typesetter: in figure 10.11: Legend: Change "US" to "U.S."; "Rouhani" to "Rouhani elected"; Background: remove box and gridlines. An important solution to the political economy of reform has been the cash transfer scheme that started in December 2010. Unfortunately, it has come under criticism so that it may not be part of any future reform. There have been claims of negative effects of cash transfers on the incentives of the poor to work. Although the evidence does not support such claims, anecdotes of poor agricultural workers abandoning their farms continue to appear in the Iranian media (Salehi-Isfahani and Mostafavi Dehzooei 2015). The cash transfer program has also been criticized for its unsound targeting because even the richest Iranians receive cash transfers every month. Several attempts have been made to limit cash transfers to poor families only. The 2014– 15 budget law required the government to find a way to exclude the richest families from the transfer scheme, but so far the government has avoided the issue because it lacks the necessary mechanism to identify high-income families. 370 Despite setbacks in public support for the continuation of subsidy reform, the government has strong motivation to raise energy prices and replace lost revenues from oil exports with revenues from the domestic sale of energy. The proposed budget for fiscal 2015/16 projects revenues from oil exports to fall by 24 percent in real terms, forcing the government to cut real current expenditures by 3.3 percent. The increased motivation for raising energy prices is, however, tempered by at least two factors. First, the government itself is very apprehensive of rekindling high inflation. Second, its willingness to raise the price of domestic energy is closely related to the outcome of the current nuclear negotiations, which affect the level of oil exports, and the need for more revenues from other sources. Following the July 14, 2015, nuclear accord between Iran and the six world powers, international sanctions against Iran are expected to be gradually lifted, allowing Iran to export more oil. But this may not be enough to close the budget gap if oil prices continue to remain in the low $50 range per barrel. There is considerable uncertainty regarding the future of oil prices, which suggests that budgetary pressures to raise domestic energy prices could continue for the next several years. Furthermore, the pro-market Rouhani government has already demonstrated its willingness to raise energy prices to market levels, so we should expect further adjustments in energy prices in the near future. <>Conclusions Despite the significant reform of subsidies in 2010, the Islamic Republic of Iran still subsidizes energy. The public debate over energy subsidies is lively and largely negative, often emphasizing how reform leads to inflation and stagnation. Given the large role that this public debate plays in the internal politics of the country, especially the parliamentary election in March 2016, knowledge of how energy price reform affects household welfare is key to the future of energy price reform in Iran. In this chapter we evaluate the impacts on household welfare, poverty, and inequality, for two reform scenarios, gradualist and full adjustment. There are important lessons to be learned from each exercise. A simple analysis of household budgets using the country's 2013 household survey shows that although the benefits of the subsidies generally accrue to richer families, they make up a larger proportion of the income of the poor. This result implies that reform without compensation hurts the poor more than the rich and is likely to face serious opposition. Households in the poorest 371 decile on average spend 13.6 percent of their expenditures on subsidized items, compared to 3.7 percent for the richest decile. We then incorporate the same survey data into the SUBSIM model to simulate the direct and indirect effect of energy price increases on household welfare. Several interesting policy implications emerge. First, we find that a gradualist approach to energy price reform, even without compensation, does not increase poverty or inequality significantly. The baseline poverty rate of about 5 percent (using a $5 PPP per day poverty line) increases by less than one percentage point as a result of a 10 percent increase in bread and energy prices. The Gini index increases by about 0.2 Gini points. The price increase simulated in this scenario is larger than what the Rouhani government has managed to push through since March 2014. These price increases have barely adjusted energy prices in real terms. So, our simulations indicate that even without compensation, a larger increase that reduces the subsidies in real terms will not cause a significant increase in poverty or inequality. To keep poverty from increasing, we estimate that about half the savings from price reforms is needed as transfers back to all households. The rest would be added to government revenues, raising them by 0.86 percent. An additional benefit of this scheme is a reduction in inequality of 0.1 Gini points compared to the no-reform case. The necessary amount paid per person is about Rls 28,000 per month, which is quite modest compared to the Rls 445,000 per person per month distributed now. According to this scenario, price increases of 10 percent in real terms (above the rate of inflation) could include modest compensation that insulates the poor and makes further price increases politically easier to implement. We also simulated the results of a larger one-time adjustment in bread and energy prices that would completely eliminate subsidies. This scenario, which is similar to the price hikes of 2010, serves as a comparison for the gradual case. Without compensation, price reforms have a large effect on the poverty rate, which rose fourfold from 4.95 percent to 20.12 percent. This is important to know in view of the widespread criticism of the 2010 cash transfer program. Without it, from a social and political point of view, the price reform would not have been possible. To keep poverty from increasing under this scenario, the necessary monthly transfer is Rls 629,000, which is 29 percent less than the current value of the cash transfer paid in December 2010 (about Rls 875,000). Critics of the implementation of the 2010 cash transfer 372 program have pointed out that the amount paid at the time was too generous and was more than the program’s earnings. The financing of the deficit contributed to inflation and thereby undermined the energy price reform (Salehi-Isfahani 2013). Under this scenario, the government actually ends up with more revenues, about 5.9 percent more, and inequality drops by 1.2 percent Gini points compared to the no-reform case. Finally, our simulations provide evidence of the relative sizes of the direct and indirect effects. The indirect impact on welfare, through energy used in the production of other goods and services, appears quite significant, about 13.1 percent of total expenditures compared to 11.5 percent for the direct effect. For the poor the direct impact is higher, whereas for higher expenditure groups it is the indirect effect that dominates. 373 <>Annex A Table 10A.1: Total and per Capita Benefits from Subsidies Expenditure Natural Kerosene Gasoline Electricity Diesel Bread LPG Total decile gas Total (billion rials) 1 (poorest) 3,826 3,526 1,692 36 9,417 6,546 4,883 29,837 2 5,907 5,779 2,098 145 9,944 9,880 4,078 37,615 3 5,428 7,584 2,272 2 9,876 12,324 3,721 40,959 4 6,304 9,901 2,553 202 10,374 14,575 3,527 47,074 5 6,591 11,654 2,708 133 10,313 15,743 3,054 49,922 6 6,048 13,943 2,848 19 10,919 18,182 2,850 54,441 7 5,524 17,030 3,114 215 10,323 20,734 2,629 59,177 8 5,170 18,343 3,252 547 10,680 21,468 2,201 61,375 9 3,569 24,224 3,631 163 10,756 25,271 1,693 69,049 10 (richest) 5,297 36,847 4,802 546 11,075 32,249 1,849 92,352 Total 53,665 148,831 28,970 2,007 103,678 176,972 30,486 541,802 Per capita (thousand rials) 1 (poorest) 475 438 210 4 1,170 813 607 3,706 2 734 719 261 18 1,236 1,228 507 4,677 3 675 942 282 0 1,227 1,531 462 5,090 4 782 1,228 317 25 1,287 1,808 437 5,839 5 820 1,451 337 17 1,284 1,959 380 6,213 6 751 1,731 353 2 1,355 2,257 354 6,757 7 687 2,117 387 27 1,283 2,577 327 7,355 8 642 2,280 404 68 1,327 2,668 273 7,627 9 443 3,008 451 20 1,336 3,139 210 8,575 10 (richest) 658 4,577 596 68 1,376 4,006 230 11,471 Total 667 1,849 360 25 1,288 2,199 379 6,731 Source: Authors' calculation using SUBSIM, HEIS 2013, and the Statistical Center of Iran. Note: HEIS = Household Expenditure and Income Survey. 374 Table 10A.2: The Impact on per Capita Consumed Quantities, Direct Effects, gradualist scenario Bread LPG Expenditure Kerosene Gasoline Electricity Diesel Natural (kilogram (m3) decile (liter) (liter) (kWh) (liter) gas (m3) ) 1 (poorest) −0.48 −0.51 −3.69 −0.00 −2.42 −1.56 −1.35 2 −0.75 −0.84 −4.73 −0.02 −2.52 −2.40 −1.13 3 −0.69 −1.10 −5.14 −0.00 −2.47 −3.07 −1.03 4 −0.80 −1.44 −5.93 −0.03 −2.58 −3.66 −0.97 5 −0.84 −1.70 −6.38 −0.02 −2.56 −4.04 −0.84 6 −0.76 −2.03 −6.74 −0.00 −2.69 −4.68 −0.79 7 −0.70 −2.48 −7.58 −0.03 −2.55 −5.42 −0.73 8 −0.65 −2.67 −7.98 −0.07 −2.62 −5.66 −0.61 9 −0.45 −3.53 −8.92 −0.02 −2.63 −6.59 −0.47 10 (richest) −0.67 −5.39 −12.83 −0.07 −2.70 −8.23 −0.51 Total −0.68 −2.17 −6.99 −0.03 −2.57 −4.53 −0.84 Table 10A.3: Impact of the Reform on the Government Revenue, gradualist scenario (billion rials) Expenditure Natural Kerosene Gasoline Electricity Diesel Bread LPG Total decile gas 1 (poorest) −127 −194 −264 −1 −1,057 −275 −193 −2,111 2 −196 −320 −343 −5 −1,131 −419 −161 −2,576 3 −180 −423 −374 −0 −1,134 −535 −147 −2,794 4 −209 −557 −438 −7 −1,196 −642 −140 −3,189 5 −219 −656 −472 −5 −1,192 −704 −121 −3,368 6 −201 −787 −502 −1 −1,269 −821 −113 −3,692 7 −183 −963 −570 −8 −1,199 −953 −104 −3,980 8 −171 −1,039 −602 −20 −1,246 −989 −87 −4,154 9 −118 −1,378 −674 −6 −1,257 −1,159 −67 −4,660 10 (richest) −176 −2,110 −1,002 −20 −1,297 −1,471 −73 −6,149 Total −1,780 −8,427 −5,242 −72 −11,977 −7,966 −1,207 −36,671 <>Notes 1. In this chapter we use the market exchange rate for energy prices because we are interested in measuring their opportunity cost in the world market. Elsewhere, when reporting on household expenditures, we use the PPP rates for private consumption taken from World Development Indicators on January 26, 2015. 375 2. The value of the Rls 445,000 per person, per month paid out in 2011 is about Rls 756,000, which is 70 percent higher. <>References CNG Europe 2014. “Map of CNG Stations and Prices by Country in Europe.” http://www.cngeurope.com. EIA (Energy Information Administration). 2015. "Electricity Prices for Households for Selected Countries." http://www.eia.gov/countries/prices/electricity_households.cfm. FERC (Federal Energy Regulatory Commission). 2014. “Market Oversight.” http://www.ferc.gov/oversight. Gahvari, Firouz, and Farzad Taheripour. 2011. "Fiscal Reforms in General Equilibrium:Theory and an Application to the Subsidy Debate in Iran." The B.E. Journal of Economic Analysis and Policy 11 (1): 1–54. Gahvari, Firouz, and Seyed Mohammad Karimi. 2013. "Export Constraint and Domestic Fiscal Reform: Lessons from 2010 Subsidy Reform in Iran." Working Paper, Department of Economics, University of Illinois, Urbana-Champaign, IL. Guillaume, Dominique, Roman Zytek, and Mohammad Reza Farzin. 2011. "Iran–The Chronicles of the Subsidy Reform." IMF Working Paper 11/167, pages 1–28. International Monetary Fund, Washington, DC.. HEIS (Household Expenditures and Income Survey). 2013. Statistical Center of Iran, Tehran. Jensen, Jesper, and David Tarr. 2003. "Trade, Exchange Rate, and Energy Pricing Reform in Iran: Potentially Large Efficiency Effects and Gains to the Poor." Review of Development Economics (4): 543–62. Ministry of Energy. 2013. "Energy Balance Sheet." Tehran, Iran. Platts.com. 2014. "Asia Pacific/Persian Gulf Marketscan," McGraw Hill Financial. Salehi-Isfahani, Djavad. 1996. "Government Subsidies and Demand for Petroleum Products in Iran." Oxford Institute for Energy Studies, Oxford, U.K. 376 ———. 2014. "Iran's Subsidy Reform; From Promise to Disappointment." Policy Perspective 13: 1–11. Economic Research Forum, Cairo, Egypt. Salehi-Isfahani, Djavad, and Mohammadhadi Mostafavi Dehzooei. 2015. "The Impact of Unconditional Cash Transfers on Labor Supply: Evidence from Iran's Energy Subsidy Reform Program." ERF Working paper, Economic Research Forum, Cairo, Egypt. Salehi-Isfahani, Djavad, Bryce Wilson Stucki, and Joshua Deutschmann. 2013. "The Reform of Energy Subsidies in Iran: The Role of Cash Transfers." Emerging Markets Finance and Trade. 377 <>Appendix A <>SUBSIM: A User Guide Abdelkrim Araar and Paolo Verme [[Typesetter: Place note at bottom of page 1.]] SUBSIM is a product of the World Bank. The authors are grateful to the many people who have tested SUBSIM in various countries or provided comments over the past three years. We wish to thank in particular Aziz Atanamov, Shanta Devarajan, Gabriela Inchauste, Michael Lokshin, Jon Jellema, Umar Serajuddin and Quentin Wodon. We are also grateful to the World Bank PSIA Trust Fund and the MENA Chief Economist Office for funding during the preparation of the model and country studies. <>Introduction SUBSIM is an automated subsidies simulation model designed to carry out distributional analyses of subsidies and simulations of subsidies reforms. The model estimates the impact of subsidies reforms on household welfare, poverty, inequality, and the government budget. It can also estimate these impacts in the presence of compensatory cash transfers. SUBSIM currently comes in two flavors: 1. SUBSIM Direct. This version uses only one household budget survey to estimate direct effects of subsidies reforms on household welfare and on the government budget. This version presents results by subsidized products and by quintiles of household expenditure or other group variables indicated by users. 2. SUBSIM Indirect. This version combines data from input-output (I/O) tables and household budget surveys to estimate direct and indirect effects of subsidies reforms. This version presents results by sets of consumption items that match economic sectors and by quntiles of household expenditure or other group variables indicated by users. SUBSIM is a product of the World Bank and has been designed to assist policy makers who need to make rapid decisions on subsidies reforms. For more information about the SUBSIM project, please visit: www.subsim.org. <>Installation To install SUBSIM simply execute the following command in STATA: <> set more off 378 net from http://www.subsim.org/Installer net install subsim_part1, force net install subsim_part2, force cap addSMenu profile.do subsim_menu <> Note: The last Stata command line tries to add the file profile.do automatically or add the command _subsim_menu in the file profile.do if the latter exists already. If this last command does not function, you have to copy the profile.do file in: a. Windows OS system: copy the file in c:/ado/personal/ b. Macintosh system: copy the file in one of the Stata system directories. To find these directories, type the command sysdir. The SUBSIM Automated Simulator: Direct effects is the automated model to run the SUBSIM Direct version. This is complemented by two other tools. The first tool (Initialize the price schedule) is designed for goods priced according to tariffs’ blocks (nonlinear pricing) such as electricity and water wh ere different tariffs correspond to different quantities consumed. This tool is also useful if subsidized goods have a quota system whereby consumers receive the subsidized price only on a limited amount of goods consumed. Note that this tool is also available within the automated simulator and is not normally used independently. The second tool (Describe the price schedule) is designed to graph and compare nonlinear 379 pricing structures. This tool can be useful if users want to compare different tariffs structures for items such as electricity. The SUBSIM Automated Simulator: Indirect effects is the automated model to run the SUBSIM version for direct and indirect effects combining household budget survey and input-output data. This is complemented by one other tool designed to manage and use input-output tables only (I/O Models and Sectoral Price Changes). For example, if users do not have a household budget survey and wish to make simulations of price changes only, they can use this tool working with input-output tables only. Note: By direct effects, we mean the impact of a price change on household well-being via the consumption of subsidized products. By indirect effects, we mean the impact of a price change on household well-being via the consumption of products that are affected indirectly by the change in price of subsidized products. For example, a change in the price of gasoline has direct effects on households who consume gasoline and indirect effects on households that consume products that use gasoline as a production input, such as transportation services. Partial equilibrium models generally provide results for direct effects only. This is the case of SUBSIM Direct for example. General equilibrium models generally provide results for both direct and indirect effects. However, they require lengthy preparation, numerous data sets, several behavioral assumptions, and the convergence of multiple equations toward a general equilibrium. The I/O model can be viewed as a simple general model that can capture the bulk of the welfare effects in the absence of detailed specific behavioral responses for all agents and markets. CGE (computable general equilibrium) and I/O models are expected to reach similar results with moderate exogenous price shocks. SUBSIM Indirect was designed to estimate direct and indirect effects. SUBSIM also provides the SUBSIM package manager to check for updates, read the reference material, or visit the SUBSIM website as shown below. SUBSIM Direct and Indirect versions have similar interfaces organized into four tabs: <> 380  Main  Items  Tables options  Graph options <> The tabs “Main” and “Items” are designed for data inputs and are different between SUBSIM Direct and SUBSIM Indirect. The tabs “Tables options” and “Graphs options” are designed to control outputs options and are identical between the two versions. These last two tabs are described under the SUBSIM Direct version only. Note: Inputs that are compulsory for the simulations are indicated with an asterisk (*). <>SUBSIM Direct Effects <>Tab: “Main” The tab "Main" contains six boxes for data input: Dialog Box Input. This box is used to load and save input data. The box enables the user to load information already saved into the SUBSIM window or to save the information inserted in the dialogue box in a file to be stored for future simulations. This information is stored in text files with the extension "*.prj". You can test this feature by uploading the file “example_1.prj” provided with the toolkit. Note 381 that you can load the file from one directory (“Load the Inputs”) and save it in a different directory with a different name (“Save the Inputs”). General Information. The box General Information enables the user to insert some helpful information, such as the name of the country or the local currency. This information will be saved in the file of results. Remember that the basic background information about the simulation is displayed and saved in the Excel file of results. Variables of Interest. The box Variables of Interest enables the user to insert key variables such as the per capita expenditures or income, the household size, and the poverty line. Note: The key income or expenditure variable should be prepared in advance in per capita terms. Group Variable. The box Group Variable enables the user to insert a population group variable. This variable captures a sociodemographic group, such as gender or urban-rural. By default, results are shown by quintile. When you select a different group variable, the results will be displayed using this variable. Note that only one variable can be chosen for each simulation. If results are needed by more than one variable the user will have to re-run SUBSIM each time. Estimations Methods/Options. The box Estimation Method/Options enables the user to select different modeling estimation options. This concerns the selection of the approach to be adopted to assess the impact on well-being. In addition to the popular marginal approach which uses a Laspeyers variation formula, SUBSIM offers a second option which models the consumer behavior with a Cobb-Douglas function. In this case, the impact on wellbeing is measured with the equivalent variation formula. For more information, see Annex with formulae. <>  The marginal approach (Linear approximation)  The behavioral approach (Cobb-Douglas Utility Function) <> Lump-sum Transfer. The box “Lump-sum Transfer” enables the user to indicate information on cash transfers. In some cases, the government may want to compensate the population affected by subsidies reforms with cash transfers. This box allow users to choose whether this transfer should be allocated to individuals or households (Type of transfer: Individual or household) or whether the transfer should be universal or targeted to particular population groups (Targeting form: Universal or population group). There is no need to indicate the amount of transfers. Results are reported in graphs, and the user can select 382 a range of values of transfers (the min and the max, see graphs options) and see results for all values included in the range specified. The tab “Main” also offers the options of leaving behind the welfare variables of the impact on well-being and the quantities variables before and after simulations for each product. These quantities are estimated by SUBSIM using information on expenditure and unit prices. If these boxes are ticked, users will find these variables in the data set after SUBSIM has finished running. Note: If users want to target a specific population group, the corresponding indicator should be prepared in advance if not already part of the variables set. For example, poor = 1 and non-poor = 0, if the poor only should be targeted. If the group variable is not specified, SUBSIM will produce the graphs on transfers with universal transfers. Note: Survey settings. Remember to set the survey settings before you launch SUBSIM including sampling weights and sampling design information. This can be done with the command “svyset” in Stata or you can use the button “Survey Settings…” located in the bottom right-hand corner of the SUBSIM “Main” tab. For more information on survey settings, see the Stata manual. <>Tab “Items” The tab “Items” is conceived to insert information about the goods concerned in the simulation, including initial prices, final prices, and unit subsidies. Initialize Information: The information on products can be initialized manually by inserting the information for each item (option “parameters values”) or by selecting variables already created and available in the data set (option: “variables”). The “example.dta” contains these special variables. Users would normally input data manually using the parameters values option unless one needs to analyze more than 10 items, which is the limit in the dialogue box. Doing so is usually not recommended because listing more than 10 items makes graphs messy. If you have more than 10 items, divide them in separate simulations, for example, food subsidies and energy subsidies. Number of Items. This is to select the number of items to consider. The maximum number allowed is 10. Option “Parameter Values”: With this option the user can input the information for each item manually including name, quantity, per capita expenditure variables, type of price schedule, initial price, unit subsidy, final price, and elasticity. <> 383 Short names: This is the name of the variable as it should appear in the output files. This is imputed manually. Q. Unit: Used to insert the unit quantity (kg, liters, etc.). This information will be displayed in the results tables. Varnames: These variables are selected from the data set and indicate the variables that contain information on expenditure per capita of the item considered. Price schedules. Users have an option to choose linear and nonlinear prices. The schedule refers to whether the price is equal for all quantities consumed by households or changes according to quantities. This is the case, for example, of electricity or a product with a quota system where households are entitled to subsidized prices only up to a certain quantity (quota). Initial Prices. This is the pre-reform price, usually the subsidized price as found at the time of simulations. Subsidy: This is the unit subsidy. This information is usually provided by ministries or specialized government agencies. Unit prices can also be estimated manually if the total amount of subsidies on a product is known together with information on the quantity of subsidized product consumed. Note that SUBSIM can also be used to simulate price increases or decreases in the absence of subsidies. In this case, unit subsidies are set to zero. Final prices: This is the simulated price. If one wants to remove subsidies completely, this price will be simply the sum of the initial price and the unit subsidy. If one wants to estimate other price increases of reduction in subsidies, this final price will be lower. Elasticity. This is the own-price (quantity/price) elasticity. The user can insert any value, and this is used to estimate changes in quantities consumed and other impacts. See section SUBSIM Basic Formulas for a discussion on how to specify the value of elasticity. <> As an example, assume that the actual initial price is 0.1 monetary unit and the unit subsidy is 0.3. In the absence of subsidies, the price of flour would be 0.4. We can simulate any increase in price, such as an increase in prices of 0.1, which leads to a final price of 0.2. In this case, our inputs will be 0.1 for the initial price, 0.3 for the unit subsidy and 0.2 for the final price. For rice, we can input, as an example, 0.14 for the initial price, 0.4 for the unit subsidy and 0.24 for the final price (figure A.1). Figure A.1: Tab Items of SUBSIM Dialog Box 384 If you are using the nonlinear option, you will have to initialize initial and final prices. If you click on “initialize,” another window will open for this purpose. It will allow you to specify prices by tariffs block and also change the number of blocks if you wish to simulate a reform that implies changing the tariffs structure, not just the prices. Clicking on “Initialize” will open a window as shown in figure A.2. Figure A.2: Price Schedule Dialog Box to Set Initial Prices Tariff Structure. Electricity or water tariffs are generally organized in quantities blocks, where a different tariff corresponds to each block of quantities. These prices can be “marginal,” meaning that they apply only to the block where the consumer is located, or “flat,” meaning that they apply to all quantities consumed up to the block where the consumer is located. The first type of tarification is called increasing 385 block tariffs (IBT), and the second type is called volume differentiated tariffs (VDT). The nonlinear option in SUBSIM can simulate both types (IBT or VDT) and can also simulation combinations of both. Blocks Defined By. Tariffs blocks can be defined by household consumption or by individual consumption. Make sure that you choose the right option. Also check whether your data in the household budget survey report expenditure by month, quarter, year, or other periods. Tariffs blocks are defined in quantities such as kilowatt hours, and these quantities refer to specific period such as a month or a quarter. Number of Brackets. You can set up to 10 tariffs blocks. Subscription Fee. Sometimes, tariffs for electricity or water include an initial fixed cost for the meter or the service. This tariff can also be modeled by including the amount in the "Subscription fee" box. Option “Variables." This applies to the main “Items” tab and to the “Initialize” button. With this option, the user can select the data on products by selecting variables directly from a pre-prepared data set. This option is suitable when the user has a large number of items so that it may be easier to prepare first a spreadsheet with all the key information including names of items, prices, units, and elasticities. SUBSIM allows the user to upload this information and use it for the analysis. Note that the spreadsheet has to contain all the information needed for the analysis in the form of variables. This option will be treated more in detail in Example 3. We usually do not recommend using this option because it is time- consuming to prepare the data and using more than 10 products clogs the output graphs and tables. If you have more than 10 products simply run SUBSIM for different groups of products such as food or energy products. <>Tab “Tables Options” This tab allows the user to select the tables’ options (figure A.3). The default option when you do not select the tables and override options is the production of all tables. Tables: Select the Tables to Be Produced. If the user wishes to have only a selected number of tables, the code of these tables can be indicated in the box. The list of codes with the titles of the tables can be seen by clicking on the question mark button ? . For example, you can type “11 23” to produce tables 1.1 and 2.3 only (no commas, one space between numbers). Join Items. If the user wants to aggregate results for several products, the user can indicate the codes of the products to aggregate and the name of the new aggregated item. For example, you may want to aggregate the results for various types of sugar (items 4, 5, and 6) and various types of flour (items 7 and 386 8). Or you may want to add results for rice and flour. This may be done by adding the option: 4 5 6 : "Sugar" | 7 8 : "Flour." Produce an Excel File of Results. This box allows the user to define the Excel file where all tables should be stored. The user can select an existing file to override or create a new file. The user can either specify the name of the file or not. In the case of an existing file, the user should make sure that this file is closed when the program is launched, otherwise an error message will appear. Language: Users can choose the language for all results. English and French are the two languages currently available. Figure A.3: Tab Table Options of SUBSIM Dialog Box <>Tab: “Graph Options” 387 Graphs: Select the Graphs to Be Produced. This option allows the user to save only selected graphs by indicating the code of each graph. The list of codes with the titles of the graphs can be seen by clicking on the question mark button ?. For example, if the user wishes to produce only Graphs 1, 2, and 4, the user will simply type “1 2 4” (no commas, one space between numbers). Join Items: If the user wants to aggregate results for several products, the user can indicate the codes of the products to aggregate and the name of the new aggregated item. For example, you may want to aggregate the results for various types of sugar (items 4, 5 and 6) and various types of flour (items 7 and 8). This may be done by adding the option: 4 5 6 : "Sugar" | 7 8 : "Flour." Select the Folder of Graphs Results. This option allows the user to select the directory where the saved graphs should be stored. Note that all graph files are saved in three formats: .gph. .pdf, and .wmf. SUBSIM will save a folder with the name “Graphs” in the directory selected. Graph Options. For each graph, the user can select options regarding the y-axis scale (min and max) and other two-way graphs options as indicated in the Stata graph help files. For example, users may want to limit the range of the graphs to a specific interval such as between 10 and 80. This can be done by indicating minimum and maximum values. Or users may want to omit titles of the graphs and add these titles separately in the report. This can be done by adding the stata option “title (“”)” (figure A.4). Note that these options need to be specified separately for each of the 10 graphs produced by SUBSIM. Figure A.4: Tab Graph Options of SUBSIM Dialog Box 388 389 <>Examples For the examples, you will need to download first the data set and the examples files from the following website: http://www.subsim.org/examples/example_dir.rar <>Example 1: Linear Subsidies The following examples are based on the data set “example.dta” provided with the toolkit. To be sure that SUBSIM has been correctly installed, the user should run the example with the data provided before testing SUBSIM with other data. As a first step, load the example.dta data into STATA. Then open SUBSIM Direct and load the pre- prepared example data in .prj format using the load option in the tab “Main” (figure A.5). Then indicate in the “Save the inputs” box the full directory where you want to store the .prj file. Figure A.5: Tab Main of SUBSIM Dialog Box 390 In this example, our country of interest subsidizes two goods, flour and rice. We wish to simulate the impact of a subsidy reform (price increase) on well-being and government revenue. In the example in figure A.6 , the initial prices for flour and rice are 0.10 and 0.14 respectively, the unit subsidies are 0.30 and 0.40, and the final prices to simulate are 0.20 and 0.24. Note that this is not a complete removal of subsidies because the final price is not equal to the initial price plus the subsidy. Figure A.6: Tab Items and Insertion of information with Editable Fields Next, make sure that the directories for the input data, tables, and graphs to save are the correct one that you want to use (see instructions for tabs). Then simply run SUBSIM clicking on “OK” or “Submit” and let the model complete its work. When SUBSIM finishes, the Excel file of results with all tables will open automatically. If you wish to look at the graphs, open the Graphs folder under the graph directory you have indicated. The only difference between the “OK” and “Submit” execution buttons is that “Submit” will keep the SUBSIM window open while “OK” will not. Note: Make sure that you specify directories correctly. SUBSIM does not accept spaces in directories or certain symbols, such as an exclamation point. This may stop SUBSIM from executing the full routine. <>Example 2: Nonlinear Subsidies 391 By nonlinear subsidies we mean to describe subsidies that change according to different levels of quantities consumed by households. The case of nonlinear subsidies is typically of two forms: the quota system and the blocks system. The quota system refers to subsidies administered via allotments. For example, households may be entitled to a subsidized price for bread up to a certain quantity purchased, say 10 kilograms per month. Beyond that quantity, consumers buy bread on the free market at unsubsidized prices. This system usually makes use of quantity cards or vouchers that households can use to purchase certain quantities at subsidized prices. The blocks system is one in which different prices apply to different bundles of quantities consumed. This system is typically used for electricity or water subsidies where the electricity or water prices are set by the regulator at different prices for each quantity block. For example, a price is set for consumption of 0–150 kilowatt hours per month, and a higher price for the consumption of 151–300 kilowatt hours per month, and so on. In this case, the number of blocks can be small or large depending on the choice of the regulator. From an economic and modeling perspective, the quota and blocks systems are equivalent. In fact, the quota system can be considered as a block system with a two-block structure. Therefore, in what follows, we will limit our discussion to the quota system, but the same explanations apply to the blocks system. Suppose now that subsidies are administered through a quota system where all individuals are entitled to fixed quantities at subsidized prices. For example, imagine that the annual per capita quota for flour is 36 kilograms. Assume also that the nonsubsidized market price is equal to 0.4. This implies that the price of flour is nonlinear; it changes with different quantities consumed (table A.1). Consumers pay a subsidized price up to 36 kilograms per person and the unsubsidized price for any additional quantity purchased. Table A.1: Nonlinear Schedule Price for Flour Block By Subsidy Price 0–36 kg individual 0.3 0.1 392 36 kg and more — 0.0 0.4 This nonlinear schedule price must be first declared in SUBSIM. To this end, the user has to perform the following steps (figure A.7): Figure A.7: Steps to Initialize Prices in SUBSIM A. Indicate that the price schedule is nonlinear for the item: flour. B. Click on the button “Initialise.” 393 C. Initialize the opening prices for each block. D. Initialize the final prices for each block. Note that we do not need to indicate the unit subsidy for the final period because SUBSIM estimates it starting from the initial subsidy and the change in prices: ( = −). <>Example 3: Simulation with Large Number of Items If the subsidy reform concerns more than 10 items, the user can insert information on items using variables by selecting the “Variables” option from the “Items” tab. Note that the spreadsheet has to contain all the information needed for the analysis in the form of variables as shown in figure A.8. 394 Figure A.8: Use of Stata Variables to Declare Information on Items Once the data are uploaded into STATA, the user can draw from the spreadsheet by using the items dialogue box as shown in figure A.9. (For this example, load the example_3.prj.) When the information is uploaded through variables, it is possible to ask SUBSIM to perform the computation for up to three scenarios. For example, in scenario 1 the reduction in subsidies is 30 percent, and in scenario 2 it is 100 percent. In this case, the Excel output file will contain estimations for both scenarios. Figure A.9: Tab Items and Insertion of Information with Stata Variables for the Case of Two Simulated Scenarios 395 When you have tested the three examples, you are ready to use SUBSIM Direct with your own data. Don’t forget to prepare your data file in advance following the indications provided. <>SUBSIM Indirect Effects The main objective of SUBSIM Indirect is to estimate the direct and indirect effects of a price change on household well-being combining a Household Budget Survey (HBS) and Input-Output (I/O) tables for a particular country. Note that SUBSIM Indirect focuses only on the goods that are concerned by the exogenous price shocks. Thus, this version is more appropriate to assess the indirect effect rather than the full direct effect of the subsidy reform. Direct effects are better estimated with SUBSIM Direct. <>Data and Methodology SUBSIM Indirect requires at least one Household Budget Survey (HBS) and an Input-Output (I/O) matrix (file). The I/O matrix required is the output matrix expressed in local currency. It is important that the I/O data and the HBS data are expressed in the same currency, in nominal terms, and for the same year. However, it is difficult to obtain I/O tables and HBS data for the same year, which means that either the HBS or the I/O data or both will need to be adjusted for prices to make data in nominal terms comparable and for the same reference year. This work has to be done by users before using SUBSIM Indirect. 396 Note that the last line of the I/O matrix should be the total value added, also called total primary input (total output-total intermediate inputs). For SUBSIM to match HBS data with I/O data, users have to prepare HBS consumption aggregates that mimic the I/O sectors in advance. Because HBS products are much more numerous than I/O sectors, one would want to group sets of HBS products corresponding to I/O sectors so that SUBSIM can do a one-to- one matching between HBS aggregates of products and I/O sectors. In some cases, one HBS product may span across several I/O sectors. SUBSIM can also handle that situation. The user will simply indicate in the dialogue box multiple I/O sectors corresponding to a single aggregate of HBS products (or one product). This is how SUBSIM Indirect operates. Suppose that we want to study the direct and indirect welfare effects of a price increase of gasoline. Because I/O tables are organized by sector, and it is very rare for researchers to have access to I/O tables by individual product, the study of indirect effects can be done only by sector and group of products and not by individual product. In our example, we have one sector called “petroleum products,” which includes gasoline as well as other products. We can shock t his sector with a price increase and study the direct and indirect effects on final consumers. If users have detailed information on the sector structure and want to study the effect of a price change of only one product, it is possible to make the price shock proportionate to the importance of the product within the sector. For example, if gasoline accounts for only 20 percent of the petroleum sector and we wish to increase only the price of gasoline by 10 percent, we can shock the petroleum sector by 2 percent (10 percent of 20 percent ). This is a user’s choice and does not make any difference to how SUBSIM operates. Continuing with the same example, suppose now that we shock the whole petroleum sector with a price increase. Users will have prepared in advance aggregates of consumption products that roughly correspond to I/O sectors. In figure A.10, we have n consumption items present in the HBS represented by the list on the first column and 12 sectors in the I/O matrix represented by the list on the right hand side. Users will aggregate all HBS consumption products that belong to the I/O petroleum sector (e.g., gas, gasoline, and kerosene) into one item and prepare similar aggregates for the other sectors. SUBSIM will first load the HBS and I/O data and then match I/O economic sectors with HBS consumption products following the indications provided in the dialogue box. Note: Some products, such as food in figure A.10, may belong to more than one I/O sectors, and in other cases, such as like gas, gasoline and kerosene, several products belong to one sector. To accommodate simulations for both cases, it is important that users construct in advance HBS aggregates for those 397 products that belong to only one sector. For example, the variable “gas, gasoline, and kerosene” is constructed by users in advance to allow SUBSIM to match products with sectors. Figure A.10: Map of Matching between Grouped Consumption Items of Household Surveys and I/O Economic Sectors HBS final consumption items Matching I/O Economic sectors structure Food S1 Clothes S2 Gas, gasoline, and kerosene S3 (Petroleum products) Transport S4 Etc… S5 S6 S7 S8 S10 S11 S12 The price change of the HBS items is estimated in two steps. In the first step, the price change of the I/O sectors is estimated based on the selected I/O model. In the second step, by using the sectoral price changes, the price change of HBS items are estimated based on the matching information indicated by the user and the importance of each sector. For example, assume that the price change in sector eight is dp_S8 = 0.1 and the one in sector ten is dp_S10 =0.2. Further, assume that the value of total product of the sector eight is S8 = 100 and that of sector ten is S10=400. Then a weighted price change of food is equal to: (100/500)*0.1+ (400/500)*0.2=0.18. SUBSIM Indirect has the same tabs as SUBSIM Direct. The Tables and Graphs tabs are identical but the “Main” and “Items” tabs are different and described below. <>Tab “Main” The “Main” tab window has one choice box in addition to what is available in SUBSIM Direct. This is the box “I/O price change model.” Here users can chose between different types of simulation models: <>  M1: Cost-push prices. The main assumption here is that producers “push” the increase in prices onto consumers via the increase in prices of market products. SUBSIM Indirect offers two sets of options (exogenous/endogenous model and short-term/long-term). 398 Endogenous and exogenous models refer to the sector that is shocked. With the endogenous option, we enable for the price adjustment of the shocked sector after the shock period. With the exogenous option, we assume that the price of the shocked sector does not change after the introduction of the price shock. The selection of the appropriate model will depend on the country context. For example, if the country is a net importer of the shocked good, and we assume that its economy cannot influence the world price, it may be appropriate to select the exogenous model. Short-term or long-term options refer to the time horizon of the price effects measured in terms of successive rounds of price adjustments. The short-term option considers only the first round effects. The long-term option considers infinite rounds.  M2: Marginal profit-push prices. The main assumption here is that markets are competitive and reach full price adjustments and producers maintain their marginal profits in the long term. For the formulas corresponding to this choice see appendix B. <> <>Tab “Items” The new ‘Items” tab window has two panels: Items info and Price shock and I/O matrix info. Remember that items indicated with an asterisk (*) are mandatory. Items Info. This panel is designed to input data from the HBS file. Here you have two options. If you have up to 10 items, you can input the information related to these items directly from the window (option “Parameters value”). If you have more than 10 items, you need to prepare these items in advance in the HBS file (option “Variables”). In this case, the HBS file has to be prepared and loaded in advance and must contain the variables that indicate the item names, the corresponding variables names, and elasticity if required by the user. Look in the example provided to see how the key variables are constructed. Short names. This is the space to indicate the names of items as displayed in results. Varnames. The user should also indicate the variable that contains the items already matched with the I/O economic sectors. This variable will contain the group of HBS products that roughly correspond to I/O sectors. Elasticity. This is the own-price elasticity to use for the simulations. See section "Elasticity" for more information on how to set elasticities. 399 Matching I/O sectors. This is where the I/O sectors matching the HBS variable indicated in “Varnames” are indicated. Because HBS products are more numerous than I/O sectors, one would want to group sets of HBS products under individual I/O sectors so that SUBSIM can do a one-to-one matching between HBS aggregates of products and I/O sectors. However, in some cases, one group of HBS product may span across several I/O sectors. SUBSIM can also handle this. The user will simply indicate multiple I/O sectors corresponding to a single aggregate of HBS products in the box “Matching I/O sectors.” Otherwise, this box will contain only one matching sector. Matching sectors are indicated with numbers as found in the I/O data file. Note: The file directory of the input file should not contain any space and the last line of the I/O matrix data file must contain the added values as shown in figure A.11 for a hypothetical I/O matrix with four sectors. Figure A.11 shows an I/O matrix with four sectors. The last line contains the added values. For example, the first sector uses its product as an input with a cost of 1 unit; it uses the good of sector 2 with cost of 2; and so forth. The total cost of intermediate goods is 9. The added value (labor and capital rents) is 4. The value of the total product of the first sector is 13. Figure A.11: Illustrative Example with a fictive Input Output Matrix As already indicated, the Tabs “Tables options” and “Graphs options” are described under the SUBSIM Direct version. These tabs are the same for both SUBSIM versions. 400 <>Example As an example, load the zipped file below from the Internet and unzip the file in your working directory: http://www.subsim.org/examples/example_ind.rar The zipped file contains data files (.dta) and preloaded input file (.pri). The three data files include a HBS file (“example_ind_eff.dta”), an I/O data file (“iomv.dta”) and a file containing the sectors legends of the I/O file (“sec_info”). The pri files contain information on examples that can be directly loaded into windows. Note: The .pri file extension is used in place of the .prj file extension so as to distinguish between SUBSIM Direct and SUBSIM Indirect input files. As you can see, the I/O file (“iomv.dta”) contains 50 lines and 49 columns (49 sectors plus one line for the value added). The HBS file (“example_ind_eff.dta”) contains the per capita consumption of nine main items: <> 1. food 2. clothes 3. energy (dir_eff) 4. transport 5. electricity 6. travel_tourism 7. telecomunication 8. habits 9. education <> The HBS file also contains the variables with the items full names (“itnames”) and variable names (“nitems”). These are the variables that you would use if you have more than 10 items and cannot create these same variables from SUBSIM windows. The file also contains other information used by SUBSIM, such as total consumption per capita, household size, or the poverty line. 401 In our example, we want to simulate a price shock of 10 percent for the petroleum sector, which is in line 15. Here are the steps to follow: <>  Load the HBS pre-prepared data  Launch “SUBSIM Automated Simulator: Indirect Effects” from the user menu in Stata  Open the “Main” tab and load the *.pri file “myexample.” This will automatically fill all boxes. You should see the window in figure A.12: Figure A.12: Dialog Box of SUBSIM Indirect Effect  Under “Save the inputs” in the “Main” Tab, replace the directory with your directory to make sure that you save the inputs file “myexample” in your working directory, otherwise SUBSIM will produce an error.  Make your choices in the tab “Main” and box “I/O price change model” regarding the options as described in the previous section.  Make sure that the Stata working directory is that where the file iomv.dta is located.  Open the “Items” Tab and check the information loaded. You should see the window in figure A.13. <> 402 Figure A.13: Tab Items and Insertion of Information on Items and on Corresponding Matching I/O Sectors If the user wishes to focus only on the pure indirect effect, the item Energy should be removed from the list of items, as figure A.14 shows. Remember, however, to keep the price shock information (see also the example: myexample_ind.pri). Figure A.14: Tab Items and Selection of Indirect Effect Items 403 As you can see, we are ready to increase the price of sector in line 15 of the I/O file by 10 percent. Doing so will affect the HBS items directly via the increase in price of the consumption products that are included in the petroleum sector and indirectly by increasing the price of nonsubsidized products that are affected by the price change in the petroleum sector. Note that the user can select between two options to insert the information about the aggregated HBS items as already explained (options “Parameters values” for up to ten items and “Variables” for more than 10 items). In this example, we assume that only one economic sector is affected by the exogenous price shock. However, SUBSIM 3.0 enables users to introduce up to six shocks as shown in figure A.15. Figure A.15: Tab Items and Simulation of Several Price's Exogenous Shocks You are now ready to run SUBSIM (click on “ok” or “submit”). Output tables are organized by group of products corresponding to I/O sectors (in columns) and provide totals as sums of all effects (direct and indirect). In this way, you will be able to distinguish between direct effects and indirect effects and also have the total effect, which can be compared with the output of a general equilibrium model. 404 Note: To avoid typical mistakes, make sure that the HBS data have been loaded in advance; the specified directory for the I/O data is correct and without spaces; and the specified directory under “Save the inputs” in the “Main” tab is your directory and not the one preloaded. When you run SUBSIM the program follows the following sequence of actions: <> To give a flavor of the impact of different choices on results, table A.2 provides results for all options under the cost-push framework and using data in example 1. As expected, long-term effects and endogenous shocks produce larger impacts than short-term effects and exogenous shocks. This result is clearly visible if we look at impacts on welfare per capita. As one should expect, however, the differences in impact on poverty is much smaller, and the differences in impact on inequality are nonexistent. Therefore, in applied works, reporting results obtained with different methods may be worthwhile only if differences are large. Table A.2: Example of Alternative Modeling Choices Short term Long term Prerefor Postrefor Postrefor Model m mf Change m Change Welfare(per capita) 3,022 3,002 −19.8 2,999 −23.6 Exogenous Poverty (%) 11.4 11.6 0.2 11.6 0.2 Inequality (%) 39.6 39.6 0.0 39.6 0.0 Welfare(per capita) 3,022 2,994 −28.0 2,984 −38.5 Endogenous Poverty (%) 11.4 11.6 0.2 11.8 0.4 Inequality (%) 39.6 39.6 0.0 39.6 0.0 405 Once you have run the example successfully, inspect the results and try to repeat simulations with your own data and parameters. <>Launch SUBSIM When SUBSIM is launched, it will display all results in the Stata output window. The user can stop the command at any stage of execution by using the Stata “Break” button. If the user has selected to save the table results in an Excel file, this file is automatically opened once the computation ends. The Excel file produced contains one table per sheet and all tables produced by the program. All graphs produced by the program are instead saved in a folder with the name “Graphs,” and in three formats (pdf, gph, and wmf). The complete set of tables and graphs can then be used to prepare a report on the distribution of subsidies, on the impact of subsidies reforms on household welfare and government revenues, and on the impact of compensatory cash transfers on poverty and the government budget. If the user is familiar with SUBSIM and all input information is available, SUBSIM will produce results in a few minutes and a full report can be prepared in a few days. Moreover, all the data input are saved by users in a file with the .prj or .pri files extensions, which allows for an easy update or reproduction of results at any time. <>Comparing SUBSIM Direct and SUBSIM Indirect Effects SUBSIM Direct and SUBSIM Indirect can be used independently depending on data availability and simulation needs. In some cases, users may want to use both versions and compare results. This section explains how to compare and interpret results for direct and indirect effects when both models are used. Recall that SUBSIM Direct produces only direct first-round effects and SUBSIM Indirect produces direct and indirect effects combined for first and higher rounds. As a first rule, SUBSIM Direct will always be more accurate than SUBSIM Indirect to estimate direct effects because results are displayed by individual product and the price shocks can be applied to individual products rather than economic sectors. SUBSIM Direct uses the best available HBS information, and results in SUBSIM Direct should be used as the reference results for direct effects in empirical analyses. It is also possible to separate direct and indirect effects using SUBSIM Indirect by opting for the cost- push model with the exogenous option. The exogenous option is enough to ensure that the introduced price shock in sector X does not affect the same sector in subsequent rounds. For single-products 406 simulations and with the cost-push exogenous option, results of SUBSIM Indirect under the shocked sector are the same as SUBSIM Direct results under the shocked product (see example). Note that comparing SUBSIM Direct and SUBSIM Indirect is possible if one shocks one product at a time. More complex simulations with multiple price shocks will make comparisons between the two SUBSIM versions more complex because of cross-products and cross-sectors effects. Therefore, a good strategy is to analyze one product at a time and see how important direct effects relate to indirect effects. This strategy is also useful because different products typically have different shares of direct and indirect effects. For example, diesel, which is largely used for commercial transport but not by households, has large indirect effects but moderate direct effects. Vice versa, LPG, which is largely consumed by households but not much used as a production input, will have large direct effects but small indirect effects. An analysis that combines simultaneous shocks on diesel and LPG will miss on these important differences. As an example, we compare simulations for a price increase in diesel with SUBSIM Direct with a corresponding price increase in the diesel sector (petroleum) with SUBSIM Indirect. The case study is Morocco and the increase in price of diesel is 11.35 percent. This is the price increase used in SUBSIM Direct. For SUBSIM Indirect we need to multiply this price increase for the share of diesel in the petroleum sector. The result: the price shock to apply in SUBSIM Indirect is [11.35*(57.23/100)] = 6.5 percent. It is important to note here that the share of diesel in the sector is not derived from I/O data but from HBS data. In this particular case, we have only two products that correspond to the oil-refining sector in I/O tables, and these two products are grouped under the HBS sector “Petroleum.” Diesel represents 57.23 percent of the petroleum sector according to HBS data and this is the share (weight) to use for the simulations in SUBSIM Indirect. The baseline data for the simulation are provided below. <> Baseline Data Unit L Subsidized unit price 9.69 Unsubsidized unit price 10.79 Price increase (%) 11.35 Share in HBS sector 57.23 407 I/O sector shock 6.50 HBS sector Petroleum Corresponding I/O sector D23-Oil Refining <> A price increase of 11.35 percent with SUBSIM Direct has a welfare impact of 421 million. We can compare this estimate with those provided by a shock of 6.5 percent of the petroleum sector with SUBSIM Indirect under various modeling options. Table A.3 shows results using the four options provided under the cost-push model. It is evident that the option “Exogenous” in SUBSIM Indirect produces the same results as SUBSIM Direct in correspondence of the Petroleum sector and this is the case whether we use the short-term or long-term option. Therefore, with the option “exogenous,” SUBSIM Indirect provides the same results as SUBSIM Direct in correspondence of the shocked sector, which allows the researcher to separate direct and indirect effects. Table A.3: SUBSIM Indirect: Welfare Impact of Alternative Simulation Options (millions DH) Option Food Housing Electricity Water Petroleum Total Exogenous/short term −695.4 −1,076.9 −145.8 −7.2 −421.0 −2,346.2 Exogenous/long term −904.6 −1,157.9 −155.6 −9.6 −421.0 −2,648.6 Endogenous/short term −1,128.7 −1,277.8 −262.3 −9.4 −463.1 −3,141.3 Endogenous/long term −2,071.1 −1,794.0 −356.2 −21.9 −542.9 −4,786.1 <>SUBSIM Basic Formulas This appendix provides a brief introduction to the basic formulas used by SUBSIM. The first version of SUBSIM (SUBSIM 1.0) was accompanied by a full paper (Araar and Verme 2012), which includes a general section on subsidies simulations, a section on the economic theory behind SUBSIM, and the SUBSIM 1.0 users’ guide. Here, we below integrate and update the theoretical part of the paper for SUBSIM 2.0. <>Changes in Welfare Let e = monetary expenditure; p = price and q = quantities with the superscripts ‘ [[Typesetter: turn the apostrophe.]] representing the postreform values, the subscript 1 representing the subsidized product and the subscript 2 representing the bundle of all other consumed products. It is well known that the total 408 expenditures (e) can be used as a money metric measurement of well-being. The change in welfare, due to an increase in price, depends on the change in consumed quantities. Mainly, we have: e = p1 q1 + p2 q2 ′ ′ e′ = p1 q1 + p2 q′ 2 When prices are normalized at consumer equilibrium, the last consumed units of each of the two goods will generate the same level of utility. With the assumption of marginal or moderate change in prices, the consumer can select any combination of quantities (q′ ′ 1 , q 2 ), but the decrease in well-being is practically the same. Based on this assumption, an easy way to assess the change in well-being is the case where the change in quantities concerns only the first good. ∆ = ∆1 = −1 dp1 Because prices are normalized, we can also write: ∆=−1 dp1 where dp represents the relative price change (∆1 /1). This is the most popular method to estimate changes in welfare subject to changes in prices, and is the same approach proposed by Coady et al. (2006) among others. Note that this formula applies with any behavioral response on the part of households, including changes in quantities consumed of the subsidized products or substitution of the subsidized product with consumption of other products. This means that the use of elasticities in SUBSIM does not affect the estimation of the impact of subsidies reforms on household welfare. Households can reorganize consumption as they wish, but the impact on total household welfare will not change. In the case of multiple pricing of the product considered (for example, electricity with different tariffs for different quantities consumed) the formula for the changes in household welfare is as follows: ∆ℎ = − ∑ 1,ℎ, 1, =1 where b represents the blocks and h households. The sum across households represents the total change in welfare. Note that all of the reported formulas are for the IBT price structure. However, these formulas can be easily generalized for the VDT structure or for the mixed IBT/VDT structure. For example, with the VDT structure, the formula of the impact on household well-being can be written as follows: 409 ∆ℎ = − ∑ 1,ℎ, 1,,|ℎ =1 Where 1,,|ℎ refers to the change in price of good 1 for the consumed quantities within the block , and this is based on the block , which depends on the total consumed quantity of the household (ℎ ). Example 1: Block Initial price (IBT) Final price (VDT) 000–100 0.10 0.10 100–-300 0.20 0.30 >300 0.30 0.40 Note: If the total consumed quantity is 250, then 1,1,2 = 0.2 and 1,2,2 =0.10; If the total consumed quantity is 350, then 1,1,3 = 0.3 and 1,2,3 =0.20. Example 2: Block Initial price Structure Final price Structure 000–100 0.10 IBT 0.10 IBT 100–300 0.20 IBT 0.20 IBT 300–400 0.30 IBT 0.30 VDT >400 0.40 IBT 0.40 VDT Note: If the total consumed quantity is below 300, then 1,1,1 = 0 and 1,1,2 =0; If the total consumed quantity is 350, then 1,1,3 = 0.2 and 1,2,3 =0.10. If the total consumed quantity is 450, then 1,1,4 = 0.3, 1,2,4 =0.2 and 1,3,4 =0.1. 410 SUBSIM also allows researchers to model household behavior using a Cobb-Douglas function. In the case of multiple pricing of the product considered the formula is as follows: 1 ∆ = 1,ℎ ( − 1) ∏ =1 ,ℎ ,ℎ Where ,ℎ is the average weighted postreform price (the postreform price in the linear case) of household ℎ for the good and ,ℎ is the expenditure share of household ℎ for the good . The marginal approach is the most common method and it is usually accurate for small or moderate price increases. For very large price increases, the marginal approach tends to overestimate the welfare impact and it is recommended to use the Cobb-Douglas approach. <>Changes in Quantities Estimates of changes in quantities in the consumption of the subsidized product are useful to have an idea on the impact of the subsidy reforms on quantities consumed and, by consequence, on production of subsidized goods. They are also essential to estimate the impact of reforms on government revenues given that the government reduces expenditure on subsidies when households reduce consumption of subsidized products. Estimates on changes in quantities, in turn, require knowledge of the demand function and the price-quantity elasticity of the subsidized product. SUBSIM assumes a linear demand function and allows for imputing elasticities. The basic formula for the estimation of changes in quantities of the subsidized product is ∆1 = 1 1 1 where the own-price elasticity 1 is typically negative and between 0 and −1. Note that we are assuming that all households behave equally so that the total impact on quantities is just the sum of the changes in quantities consumed across all households. <>Elasticity 411 The formula for the estimation of changes in quantities consumed uses the own-price uncompensated elasticity. One of the main difficulties in subsidies simulations is to specify the value of this elasticity correctly. There are at least three major difficulties. The first difficulty is attempting to estimate elasticities when products are subsidized. When prices are subsidized, and especially when only one price is applied nationally and on all quantities, it is not possible to estimate the own-price elasticity cross-section with a model based on household data (there is no price variation). Sometimes, the subsidized price changes over time, and one may have available several household consumption surveys that cover the period when price changes occurred. However, this occurrence is rare, and it is difficult to isolate the impact of the price change in the subsidized product from other effects on expenditure over time. Therefore, subsidies analysts can rarely estimate elasticities for the country of interest. The second difficulty relates to the use of known elasticities from the literature and other countries. Sometimes, it is possible to derive elasticity parameters from the specific literature on products. For example, the own-price elasticity for gasoline is quite well known and has been estimated widely worldwide, and the user could simply use estimations made for similar countries to the country of interest. However, known elasticities are typically estimated at free market prices, and they are point elasticities that apply to prices that are not subsidized. The point elasticities at subsidized prices may be very different and cannot be assumed to be the same. Therefore, it is difficult for subsidies analysts to simply “borrow” elasticities from elsewhere. The third difficulty is that the formula presented in the previous section is designed for small changes in prices (marginal changes) and does not function well for large price changes. When the product between changes in prices and elasticity (1 1 ) is greater than 1, the postreform quantity can become negative using this formula. Unlike other simulations of price changes, changes in subsidized prices can be very large, especially when governments want to remove subsidies altogether. In these cases, it is not unusual to have price increases of several times over so that 1 can be very large. Therefore, subsidies analysts cannot simply use standard parameters for elasticities like −0.3 or −0.5 but have to consider more specifically the relation between subsidized and unsubsidized prices before specifying elasticities. To overcome these problems, SUBSIM has three main solutions. The first solution is that, by design, SUBSIM does not allow quantities to become negative (−0 ) because the postreform quantity has a lower bound of zero. However, one should be aware that when results on quantities in the Excel output file show zero values, it is most likely that the specified elasticities are too large. Subsidized products are usually essential consumption items, and it is unlikely that households stop consuming these products altogether if the price increases. It is more likely that our specification of elasticity is incorrect. 412 The second solution is to use the value of elasticity at unsubsidized prices from another country and derive from this elasticity the correct elasticity to use for the subsidized price. When the subsidized price is several times lower than the unsubsidized price, this means that the subsidized price is extremely low. But if this price is extremely low and quantity is initially high, we should expect the own-price elasticity to be very low. If prices increase a little around the subsidized price, consumers will tend to reduce quantities by small amounts. On the contrary, if the subsidized price is close to the unsubsidized price then it is more likely that increases in prices will lead to large decreases in quantities and that the elasticity will be large. Therefore, either the elasticity 1 is large or the relative change in price 1 is large, but they should not be both large at the same time. As a rule of thumb, if the new price is three times the current price and the known elasticity at unsubsidized prices is (say) −0.3, then the elasticity to use in the formula may be around a third of that value, say 0.1. With the assumption of a straight linear demand function, it is also possible to calculate precisely the initial elasticity (the elasticity at the subsidized price) using the final elasticity (the elasticity at the unsubsidized price). The formula is as follows: 1 ( ′ (′ − 1) 1 1 − 1 ) (1 − ′ ) 1 1 = ′ 1 (1 − 1 ) The third (and perhaps the most sensible) solution is to run SUBSIM with different assumptions about the elasticity and compare results. In this case, it is useful to use zero as a lower bound and the expected value of elasticity at the unsubsidized price as an upper value. This is what we would recommend especially when price increases are large. <>Changes in Government Revenues Having discussed elasticities and changes in quantities, we can now estimate changes in government revenues. We may face two situations, one where we know the unit subsidy and one where we do not know the unit subsidy in advance. If we know the unit subsidy, the formula is as follows: H ∆ = ∑ ek,h dpk (1 − ( sk − dpk )) h=1 where sk is the unit subsidy for product k. 413 In the case of large price changes and in order to constrain the maximum decrease in quantity to that of the initial quantity, the formula becomes: H ∆r = ∑ ek,h dpk + max(εk ek,h dpk ; −ek,h ) (dpk − sk ) h=1 If we do nott know the unit subsidy in advance, we can then approximate the change in government revenues with the change in producers’ profits as follows: ∆ = ∑ −,ℎ (1 + (1 + )) ℎ=1 SUBSIM will use one or the other formula depending on whether users specify unit subsidies or not in the tab “Items.” <>Formulas for Input-Output Simulations SUBSIM Indirect provides various options for the simulation of indirect effects with input-output tables. The two sets of choices for the cost-push model will select one of four options for the estimation of direct and indirect effects. The formulas of the four options are listed in table A.4. Table A.4: Summary of Formulas for Alternative Modeling Options Short term (t=1) Long term (t=∞) Exogenous model (1) =1 = 0 + (0 ′̅)′ (2) = ( − ̅′)−1 0 Endogenous model (3) =1 = 0 + (0 ′)′ (4) = ( − ′)−1 0 ̄ is similar to by replacing the elements of the ℎ line and Where I is the identity matrix and the matrix the ℎ column of the shocked sector by zeroes. For example, with a three sectors’ matrix and a price shock to the second sector 0.2  0.2 0.3 0.2  0.0 0.3 = [0.0  0.3 0.4] and ̅ = [0.0  0.0 0.0]. 0.5 0.2 0.1 0.5 0.0 0.1 414 If we have an increase of 10 percent in price of sector 2, then: 0.0 1  0 0 = [0.1] and = [0  0 0] 0.0 0 0 1 where S is the vector of initial price shocks and U is the identity matrix with zero in correspondence of the shocked sector. Assume now that denotes the vector of price changes after lapses of time (years or months). Just after the introduction of the price shock, the initial reaction will generate a change in price that is equal to: 0.00 0 = ( ′ ′) + S = [0.10] 0.04 The four cost-push options provide welfare impacts that are ranked in the following order: (1)<(2) and (3)<(4) and (1)<(3) and (2)<(4) so that option 1 is the lower bound and option 4 is the upper bound (see also example in text). Note that the International Monetary Fund (IMF) adopts the cost-push model and the option of choice for this institution is option (4). A good choice is also to model upper and lower bounds and report both bounds in empirical analyses. The formula applied for the marginal profit-push model is the following: 1 = ( − ∗ )−1 Where T is the diagonal matrix of price changes and V is the vector of added values. Example: 1  0 0 = [0  1.1 0] 0 0 1 <>References Araar, A., and P. Verme. 2012. "Reforming Subsidies: A Toolkit for Policy Simulations." World Bank Policy Research Working Paper 6148, World Bank, Washington, DC. Coady, D., M. El-Said, R. Gillingham, K. Kpodar, P. Medas, and D. Newhouse. 2006. “The Magnitude and Distribution of Fuel Subsidies: Evidence from Bolivia, Ghana, Jordan, Mali, and Sri Lanka.” International Monetary Fund Working Paper WP/06/247. 415 416