61390 DIREC TIONS IN DE VELOPMENT Infrastructure Africa’s Power Infrastructure Investment, Integration, Efficiency Anton Eberhard Orvika Rosnes Maria Shkaratan Haakon Vennemo Africa’s Power Infrastructure Africa’s Power Infrastructure Investment, Integration, Efficiency Anton Eberhard Orvika Rosnes Maria Shkaratan Haakon Vennemo Vivien Foster and Cecilia Briceño-Garmendia, Series Editors © 2011 The International Bank for Reconstruction and Development/The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org All rights reserved 1 2 3 4 14 13 12 11 This volume is a product of the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. 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All other queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2422; e-mail: pubrights@worldbank.org. ISBN: 978-0-8213-8455-8 eISBN: 978-0-8213-8652-1 DOI: 10.1596/978-0-8213-8455-8 Library of Congress Cataloging-in-Publication Data Africa’s power infrastructure : investment, integration, efficiency / Anton Eberhard ... [et al.]. p. cm. Includes bibliographical references. ISBN 978-0-8213-8455-8 — ISBN 978-0-8213-8652-1 (electronic) 1. Rural electrification—Government policy—Africa, Sub-Saharan. 2. Energy policy—Social aspects—Africa, Sub-Saharan. 3. Capital investments—Africa, Sub-Saharan. I. Eberhard, Anton A. HD9688.S832.A37 2011 333.793'20967—dc22 2011002973 Cover photograph: Arne Hoel/The World Bank Cover design: Naylor Design Contents About the AICD xvii Series Foreword xix Acknowledgments xxi Abbreviations xxvii Chapter 1 Africa Unplugged 1 The Region’s Underdeveloped Energy Resources 1 The Lag in Installed Generation Capacity 2 Stagnant and Inequitable Access to Electricity Services 5 Unreliable Electricity Supply 7 The Prevalence of Backup Generators 7 Increasing Use of Leased Emergency Power 10 A Power Crisis Exacerbated by Drought, Conflict, and High Oil Prices 12 High Power Prices That Generally Do Not Cover Costs 12 Deficient Power Infrastructure Constrains Social and Economic Development 16 Notes 19 References 19 v vi Contents Chapter 2 The Promise of Regional Power Trade 23 Uneven Distribution and Poor Economies of Scale 24 Despite Power Pools, Low Regional Power Trade 26 The Potential Benefits of Expanded Regional Power Trading 28 What Regional Patterns of Trade Would Emerge? 31 Water Resources Management and Hydropower Development 33 Who Gains Most from Power Trade? 33 How Will Less Hydropower Development Influence Trade Flows? 38 What Are the Environmental Impacts of Trading Power? 39 Technology Choices and the Clean Development Mechanism 39 How Might Climate Change Affect Power Investment Patterns? 40 Meeting the Challenges of Regional Integration of Infrastructure 40 Conclusion 50 Note 50 Bibliography 50 Chapter 3 Investment Requirements 53 Modeling Investment Needs 54 Estimating Supply Needs 55 Overall Cost Requirements 58 The SAPP 64 The EAPP/Nile Basin 67 WAPP 70 CAPP 74 Notes 77 Reference 78 Chapter 4 Strengthening Sector Reform and Planning 79 Power Sector Reform in Sub-Saharan Africa 80 Private Management Contracts: Winning the Battle, Losing the War 85 Sector Reform, Sector Performance 87 The Search for Effective Hybrid Markets 88 Contents vii The Possible Need to Redesign Regulatory Institutions 94 Notes 100 Bibliography 101 Chapter 5 Widening Connectivity and Reducing Inequality 103 Low Electricity Connection Rates 104 Mixed Progress, despite Many Agencies and Funds 105 Inequitable Access to Electricity 110 Affordability of Electricity—Subsidizing the Well-Off 112 Policy Challenges for Accelerating Service Expansion 119 References 129 Chapter 6 Recommitting to the Reform of State-Owned Enterprises 133 Hidden Costs in Underperforming State-Owned Enterprises 134 Driving Down Operational Inefficiencies and Hidden Costs 135 Effect of Better Governance on Performance of State-Owned Utilities 136 Making State-Owned Enterprises More Effective 137 Conclusion 147 References 148 Chapter 7 Closing Africa’s Power Funding Gap 149 Existing Spending in the Power Sector 151 How Much More Can Be Done within the Existing Resource Envelope? 157 Increasing Cost Recovery 158 On Budget Spending: Raising Capital Budget Execution 160 Improving Utility Performance 161 Savings from Efficiency-Oriented Reforms 162 Annual Funding Gap 164 How Much Additional Finance Can Be Raised? 166 Costs of Capital from Different Sources 178 viii Contents The Most Promising Ways to Increase Funds 180 What Else Can Be Done? 180 Taking More Time 180 Lowering Costs through Regional Integration 181 The Way Forward 182 Note 183 References 183 Appendix 1 Africa Unplugged 187 Appendix 2 The Promise of Regional Power Trade 199 Appendix 3 Investment Requirements 213 Appendix 4 Strengthening Sector Reform and Planning 239 Appendix 5 Widening Connectivity and Reducing Inequality 267 Appendix 6 Recommitting to the Reform of State-Owned Enterprises 291 Appendix 7 Closing Africa’s Power Funding Gap 299 Index 305 Boxes 2.1 The Difficulties in Forging Political Consensus: The Case of Westcor 42 2.2 The West African Power Pool (WAPP) and New Investment 45 2.3 Difficulties in Setting Priorities in SAPP 46 3.1 Definitions 61 4.1 Kenya’s Success with Private Sector Participation in Power 83 4.2 Côte d’Ivoire’s Independent Power Projects Survive Civil War 84 4.3 Power Sector Planning Dilemmas in South Africa 90 5.1 Ghana’s Electrification Program 106 5.2 Residential Electricity Tariff Structures in Sub-Saharan Africa 116 Contents ix 5.3 Rural Electrification in Mali 127 6.1 Kenya’s Success in Driving Down Hidden Costs 138 6.2 Botswana’s Success with a State-Owned Power Utility 139 6.3 The Combination of Governance Reforms That Improved Eskom’s Performance 142 7.1 Introducing a Country Typology 152 Figures 1.1 Power Generation Capacity by Region, 1980–2005 3 1.2 Power Generation Capacity in Sub-Saharan Africa by Country, 2006 4 1.3 Household Electrification Rate in World Regions, 1990–2005 5 1.4 Per Capita Electricity Consumption and GDP in Selected Countries of Sub-Saharan Africa and World Regions, 2004 6 1.5 Power Outages, Days per Year, 2007–08 8 1.6 Generator Ownership by Firm Size 9 1.7 Own Generation as Share of Total Installed Capacity by Subregion, 2006 9 1.8 Economic Cost of Power Outages as Share of GDP, 2005 10 1.9 Average Residential Electricity Prices in Sub-Saharan Africa and Other Regions, 2005 13 1.10 Average Cost of Grid and Backup Power in Sub-Saharan Africa 13 1.11 Average Power Sector Revenue Compared with Costs 14 1.12 Contribution of Infrastructure to Total Factor Productivity (TFP) of Firms 17 2.1 Profile of Power Generation Capacity in Sub-Saharan Africa 25 2.2 Disaggregated Operating Costs for Power Systems in Sub-Saharan Africa, 2005 26 2.3 Electricity Exports and Imports in Sub-Saharan Africa, 2005 27 2.4 Savings Generated by Regional Power Trade among Major Importers under Trade Expansion Scenario 30 2.5 Cross-Border Power Trading in Africa in Trade Expansion Scenario (TWh in 2015) 34 3.1 Overall Power Spending by Country in Each Region 63 4.1 Prevalence of Power Sector Reform in 24 AICD Countries 81 x Contents 4.2 Effect of Management Contracts on Performance in the Power Sector in Sub-Saharan Africa 88 4.3 Power Sector Performance in Countries with and without Regulation 95 4.4 Coexistence of Various Regulatory Options 99 4.5 Choice of Regulatory Model Based on the Country Context 100 5.1 Patterns of Electricity Service Coverage in Sub-Saharan Africa 104 5.2 Electrification Rates in the Countries of Sub-Saharan Africa, Latest Year Available 107 5.3 Rural Electrification Agencies, Funds, and Rates in Sub-Saharan Africa 108 5.4 Countries’ Rural Electrification Rates by Percentage of Urban Population 109 5.5 For the Poorest 40 Percent of Households, Coverage of Modern Infrastructure Services Is below 10 Percent 111 5.6 Infrastructure Services Absorb More of Household Budgets as Incomes Rise 113 5.7 About 40 Percent of Households Connected Do Not Pay 114 5.8 Subsistence Consumption Priced at Cost Recovery Levels Ranges from $2 to $8 115 5.9 Electricity Subsidies Do Not Reach the Poor 117 5.10 Subsidy Needed to Maintain Affordability of Electricity 118 5.11 Prepayment Metering 123 5.12 Potential Rural Access: Distribution of Population by Distance from Substation 126 6.1 Overall Magnitude of Utility Inefficiencies as a Percentage of Revenue 135 6.2 Effect of Utility Inefficiency on Electrification and Suppressed Demand 136 6.3 Impact of Reform on Hidden Costs in the Power Sector in Sub-Saharan Africa 137 6.4 Incidence of Good-Governance Characteristics among State-Owned Utilities 140 6.5 Effect of Governance on Utility Performance in State-Owned Power Utilities 141 7.1 Power Spending from All Sources as a Percentage of GDP 155 Contents xi 7.2 Sources of Financing for Power Sector Capital Investment 158 7.3 Power Prices and Costs, Sub-Saharan Africa Average 159 7.4 Potential Efficiency Gains from Different Sources 163 7.5 Power Infrastructure Funding Gap 165 7.6 Overview of Private Investment to African Power Infrastructure 172 7.7 Costs of Capital by Funding Source 179 7.8 Spreading Investment over Time 181 Tables 1.1 Overview of Emergency Power Generation in Sub-Saharan Africa (Up to 2007) 11 2.1 Regional Trade in Electricity, 2005 28 2.2 Top Six Power Exporting Countries in Trade Expansion Scenario 31 2.3 Power Exports by Region in Trade Expansion Scenario 32 2.4 Long-Term Marginal Costs of Power under Trade Expansion and Trade Stagnation 36 3.1 Blackout Data for Selected Countries 56 3.2 Projected Market, Social, and Total Net Electricity Demand in Four African Regions 56 3.3 Projected Generation Capacity in Sub-Saharan Africa in 2015 in Various Scenarios 57 3.4 New Household Connections to Meet National Electrification Targets, 2005–15 59 3.5 Required Spending for the Power Sector in Africa, 2005–15 60 3.6 Estimated Cost of Meeting Power Needs of Sub-Saharan Africa under Two Trade Scenarios 62 3.7 Generation Capacity and Capacity Mix in SAPP, 2015 64 3.8 Overnight Investment Costs in SAPP, 2005–15 65 3.9 Generation Capacity and Capacity Mix in EAPP/Nile Basin, 2015 68 3.10 Overnight Investment Costs in the EAPP/Nile Basin, 2015 69 3.11 Generation Capacity and Capacity Mix in WAPP, 2015 71 3.12 Overnight Investment Costs in WAPP, 2005–15 72 3.13 Generation Capacity and Capacity Mix in CAPP, 2015 74 3.14 Overnight Investment Costs in CAPP, 2005–15 75 xii Contents 4.1 Overview of Public-Private Transactions in the Power Sector in Sub-Saharan Africa 82 4.2 Common Questions in Hybrid Power Markets and Their Policy Solutions 93 5.1 Proportion of Infrastructure Electricity Coverage Gap in Urban Africa Attributable to Demand and Supply Factors 111 5.2 Monthly Household Budget 112 5.3 Potential Targeting Performance of Electricity Connection Subsidies under Various Scenarios 124 6.1 Governance Reforms to Improve State-Owned Utility Performance 142 7.1 Sectoral Composition of Investment, by Financing Source 151 7.2 Power Sector Spending in Sub-Saharan Africa, Annualized Flows 154 7.3 Annual Budgetary Flows to Power Sector 160 7.4 Average Budget Variation Ratios for Capital Spending 161 7.5 Potential Gains from Higher Operational Efficiency 162 7.6 Annual Power Funding Gap 164 7.7 Net Change in Central Government Budgets, by Economic Use, 1995–2004 167 7.8 Financial Instruments for Locally Sourced Infrastructure Financing 174 7.9 Outstanding Financing for Power Infrastructure, 2006 175 7.10 Syndicated Loan Transactions for Power Sector in 2006 176 7.11 Details of Corporate Equity Issues by Power Sector Companies by End of 2006 177 7.12 Details of Corporate Bonds Issued by Telecom Operators by End of 2006 178 A1.1 National Power System Characteristics 188 A1.2 Electricity Production and Consumption 190 A1.3 Outages and Own Generation: Statistics from the Enterprise Survey 192 A1.4 Emergency, Short-Term, Leased Generation 193 A1.5 Distribution of Installed Electrical Generating Capacity between Network and Private Sector Self-Generation 193 A1.6 Effect of Own Generation on Marginal Cost of Electricity 195 Contents xiii A1.7 Losses Due to Outages (“Lost Load”) for Firms with and without Their Own Generator 195 A1.8 Operating Costs of Own Generation 196 A2.1 Projected Trading Patterns in 10 Years under Alternative Trading Scenarios, by Region 200 A2.2 Projected Long-Run Marginal Cost in 10 Years under Alternative Trading Scenarios 202 A2.3 Projected Composition of Generation Portfolio in 10 Years under Alternative Trading Scenarios 206 A2.4 Projected Physical Infrastructure Requirements in 10 Years under Alternative Trading Scenarios 208 A2.5 Estimated Annualized 10-Year Spending Needs to Meet Infrastructure Requirements under Alternative Trading Scenarios 210 A3.1 Power Demand, Projected Average Annual Growth Rate 214 A3.2 Suppressed Demand for Power 215 A3.3 Target Access to Electricity, by Percentage of Population 218 A3.4 Target Access to Electricity, by Number of New Connections 220 A3.5 Total Electricity Demand 223 A3.6 Generating Capacity in 2015 under Various Trade, Access, and Growth Scenarios 224 A3.7a Annualized Costs of Capacity Expansion, Constant Access Rates, Trade Expansion 226 A3.7b Annualized Costs of Capacity Expansion, 35% Access Rates, Trade Expansion 228 A3.7c Annualized Costs of Capacity Expansion, National Targets for Access Rates, Trade Expansion 230 A3.7d Annualized Costs of Capacity Expansion, Low Growth Scenario, National Targets for Access Rates, Trade Expansion 232 A3.7e Annualized Costs of Capacity Expansion, Trade Stagnation 234 A3.8 Annualized Costs of Capacity Expansion under Different Access Rate Scenarios, Trade Expansion 236 A4.1 Institutional Indicators: Summary Scores by Group of Indicators 239 xiv Contents A4.2a Institutional Indicators: Description of Reform Indicators 240 A4.2b Institutional Indicators: Reform, 2007 242 A4.3a Institutional Indicators: Description of Reform Sector–Specific Indicators 244 A4.3b Institutional Indicators: Reform Sector Specific, 2007 245 A4.4a Institutional Indicators: Description of Regulation Indicators 246 A4.4b Institutional Indicators: Regulation, 2007 248 A4.5a Institutional Indicators: Description of Regulation Sector-Specific Indicators 250 A4.5b Institutional Indicators: Regulation Sector Specific, 2007 251 A4.6a Institutional Indicators: Description of SOE Governance Indicators 252 A4.6b Institutional Indicators: SOE Governance, 2007 255 A4.7 Private Participation: Greenfield Projects, 1990–2006 259 A4.8 Private Participation: Concessions, Management and Lease Contracts, Divestitures, 1990–2006 261 A5.1 Access to Electricity 268 A5.2 Adjusted Access, Hook-Up, Coverage of Electricity, Latest Available Year, Urban Areas 270 A5.3 Electricity Expenditure and Its Share in Household Budget 272 A5.4 Kerosene Expenditure and Its Share in Household Budget 274 A5.5 Liquefied Propane Gasoline (LPG) Expenditure and Its Share in Household Budget 276 A5.6 Wood/Charcoal Expenditure and Its Share in Household Budget 278 A5.7 Rural Access to Power, Off-Grid Power, and Rural Electrification Agency and Fund 280 A5.8 Share of Urban Households Whose Utility Bill Would Exceed 5 Percent of the Monthly Household Budget at Various Prices 282 A5.9 Overall Targeting Performance (Ω) of Utility Subsidies 283 A5.10 Potential Targeting Performance of Connection Subsidies under Different Subsidy Scenarios 284 A5.11 Value of Cost Recovery Bill at Consumption of 50 kWh/Month 285 Contents xv A5.12 Residential Tariff Schedules 286 A5.13 Social Tariff Schedules 287 A5.14 Industrial Tariff Schedules 288 A5.15 Commercial Tariff Schedules 289 A5.16 Value and Volume of Sales to Residential Customers as Percentage of Total Sales 290 A6.1 Electricity Sector Tariffs and Costs 292 A6.2 Residential Effective Tariffs at Different Consumption Level 294 A6.3 Electricity Sector Efficiency 295 A6.4 Hidden Costs of Power Utilities as a Percentage of GDP and Utility Revenue 296 A7.1 Existing Spending on the Power Sector 300 A7.2 Size and Composition of the Power Sector Funding Gap 302 A7.3 Sources of Potential Efficiency Gains, by Component 303 About the AICD This study is a product of the Africa Infrastructure Country Diagnostic (AICD), a project designed to expand the world’s knowledge of physical infrastruc- ture in Africa. The AICD provides a baseline against which future improvements in infrastructure services can be measured, making it possible to monitor the results achieved from donor support. It also offers a more solid empirical foundation for prioritizing invest- ments and designing policy reforms in the infrastructure sectors in Africa. The AICD was based on an unprecedented effort to collect detailed economic and technical data on the infrastructure sectors in Africa. The project produced a series of original reports on public expenditure, spend- ing needs, and sector performance in each of the main infrastructure sectors, including energy, information and communication technologies, irrigation, transport, and water and sanitation. The most significant findings were synthesized in a flagship report titled Africa’s Infrastructure: A Time for Transformation. All the under- lying data and models are available to the public through a Web portal (http://www.infrastructureafrica .org), allowing users to download customized data reports and perform various simulation exercises. The AICD was commissioned by the Infrastructure Consortium for Africa following the 2005 G-8 Summit at Gleneagles, which flagged the importance of scaling up donor finance to infrastructure in support of Africa’s development. The first phase of the AICD focused on 24 coun- tries that together account for 85 percent of the gross domestic product, population, and infrastruc- ture aid flows of Sub-Saharan Africa. The countries were Benin, Burkina Faso, Cape Verde, Cameroon, Chad, Democratic Republic of Congo, Côte d’Ivoire, xvii xviii About the AICD Ethiopia, Ghana, Kenya, Lesotho, Madagascar, Malawi, Mozambique, Namibia, Niger, Nigeria, Rwanda, Senegal, South Africa, Sudan, Tanzania, Uganda, and Zambia. Under a second phase of the project, coverage was expanded to include the remaining countries on the African continent. Consistent with the genesis of the project, the main focus was on the 48 countries south of the Sahara that face the most severe infrastructure chal- lenges. Some components of the study also covered North African countries to provide a broader point of reference. Unless otherwise stated, therefore, the term “Africa” is used throughout this report as a shorthand for “Sub-Saharan Africa.” The AICD was implemented by the World Bank on behalf of a steering committee that represents the African Union, the New Partnership for Africa’s Development (NEPAD), Africa’s regional eco- nomic communities, the African Development Bank, and major infrastructure donors. Financing for the AICD was provided by a multidonor trust fund to which the main contributors were the Department for International Development (United Kingdom), the Public Private Infrastructure Advisory Facility, Agence Française de Développement, the European Commission, and Germany’s Kreditanstalt für Wiederaufbau (KfW). The Sub-Saharan Africa Transport Policy Program and the Water and Sanitation Program provided technical support on data collection and analysis pertaining to their respec- tive sectors. A group of distinguished peer reviewers from policy-making and academic circles in Africa and beyond reviewed all of the major outputs of the study to ensure the technical quality of the work. Following the completion of the AICD project, long- term responsibility for ongoing collection and analysis of African infrastructure statistics was transferred to the African Development Bank under the Africa Infrastructure Knowledge Program (AIKP). A second wave of data collection of the infrastructure indicators analyzed in this volume was initiated in 2011. Series Foreword The Africa Infrastructure Country Diagnostic (AICD) has produced continent-wide analysis of many aspects of Africa’s infrastructure chal- lenge. The main findings were synthesized in a flagship report titled Africa’s Infrastructure: A Time for Transformation, published in November 2009. Meant for policy makers, that report necessarily focused on the high-level conclusions. It attracted widespread media coverage feeding directly into discussions at the 2009 African Union Commission Heads of State Summit on Infrastructure. Although the flagship report served a valuable role in highlighting the main findings of the project, it could not do full justice to the richness of the data collected and technical analysis undertaken. There was clearly a need to make this more detailed material available to a wider audience of infrastructure practitioners. Hence the idea of producing four technical monographs, such as this one, to provide detailed results on each of the major infrastructure sectors—information and communication technologies (ICT), power, transport, and water—as companions to the flagship report. These technical volumes are intended as reference books on each of the infrastructure sectors. They cover all aspects of the AICD project relevant to each sector, including sector performance, gaps in financing and efficiency, and estimates of the need for additional spending on xix xx Series Foreword investment, operations, and maintenance. Each volume also comes with a detailed data appendix—providing easy access to all the relevant infrastructure indicators at the country level—which is a resource in and of itself. In addition to these sector volumes, the AICD has produced a series of country reports that weave together all the findings relevant to one par- ticular country to provide an integral picture of the infrastructure situa- tion at the national level. Yet another set of reports provides an overall picture of the state of regional integration of infrastructure networks for each of the major regional economic communities of Sub-Saharan Africa. All of these papers are available through the project web portal, http://www.infrastructureafrica.org, or through the World Bank’s Policy Research Working Paper series. With the completion of this full range of analytical products, we hope to place the findings of the AICD effort at the fingertips of all interested policy makers, development partners, and infrastructure practitioners. Vivien Foster and Cecilia Briceño-Garmendia Acknowledgments This book was co-authored by Anton Eberhard, Orvika Rosnes, Maria Shkaratan, and Haakon Vennemo, under the overall guidance of series editors Vivien Foster and Cecilia Briceño-Garmendia. The book draws upon a number of background papers that were pre- pared by World Bank staff and consultants, under the auspices of the Africa Infrastructure Country Diagnostic (AICD). Key contributors to the book on a chapter-by-chapter basis were as follows. Chapter 1 Contributors Anton Eberhard, Vivien Foster, Cecilia Briceño-Garmendia, Maria Shkaratan, Fatimata Ouedraogo, Daniel Camos. Key Source Document Eberhard, Anton, Vivien Foster, Cecilia Briceño-Garmendia, Fatimata Ouedraogo, Daniel Camos, and Maria Shkaratan. 2008. “Underpowered: The State of the Power Sector in Sub-Saharan Africa.” Background Paper 6, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. xxi xxii Acknowledgments Chapter 2 Contributors Orvika Rosnes, Haakon Vennemo, Anton Eberhard, Vivien Foster, Cecilia Briceño-Garmendia, Maria Shkaratan, Fatimata Ouedraogo, Daniel Camos. Key Source Documents Rosnes, Orvika, and Haakon Vennemo. 2008. “Powering Up: Costing Power Infrastructure Spending Needs in Sub-Saharan Africa.” Background Paper 5, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Eberhard, Anton, Vivien Foster, Cecilia Briceño-Garmendia, Fatimata Ouedraogo, Daniel Camos, and Maria Shkaratan. 2008. “Underpowered: The State of the Power Sector in Sub-Saharan Africa.” Background Paper 6, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Chapter 3 Contributors Orvika Rosnes, Haakon Vennemo, Anton Eberhard. Key Source Document Rosnes, Orvika, and Haakon Vennemo. 2008. “Powering Up: Costing Power Infrastructure Spending Needs in Sub-Saharan Africa.” Background Paper 5, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Chapter 4 Contributors Anton Eberhard, Vivien Foster, Cecilia Briceño-Garmendia, Maria Shkaratan, Maria Vagliasindi, John Nellis, Fatimata Ouedraogo, Daniel Camos. Key Source Documents Eberhard, Anton, Vivien Foster, Cecilia Briceño-Garmendia, Fatimata Ouedraogo, Daniel Camos, and Maria Shkaratan. 2008. “Underpowered: The State of the Power Sector in Sub-Saharan Africa.” Background Paper 6, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Vagliasindi, Maria, and John Nellis. 2010. “Evaluating Africa’s Experience with Institutional Reform for the Infrastructure Sectors.” Working Paper 23, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Acknowledgments xxiii Chapter 5 Contributors Anton Eberhard, Vivien Foster, Cecilia Briceño-Garmendia, Sudeshna Ghosh Banerjee, Maria Shkaratan, Quentin Wodon, Amadou Diallo, Taras Pushak, Hellal Uddin, Clarence Tsimpo. Key Source Document Banerjee, Sudeshna, Quentin Wodon, Amadou Diallo, Taras Pushak, Hellal Uddin, Clarence Tsimpo, and Vivien Foster. 2008. “Access, Affordability and Alternatives: Modern Infrastructure Services in Sub- Saharan Africa.” Background Paper 2, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Chapter 6 Contributors Anton Eberhard, Vivien Foster, Cecilia Briceño-Garmendia, Maria Shkaratan, Fatimata Ouedraogo, Daniel Camos. Key Source Documents Eberhard, Anton, Vivien Foster, Cecilia Briceño-Garmendia, Fatimata Ouedraogo, Daniel Camos, and Maria Shkaratan. 2008. “Underpowered: The State of the Power Sector in Sub-Saharan Africa.” Background Paper 6, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Briceño-Garmendia, Cecilia, and Maria Shkaratan. 2010. “Power Tariffs: Caught Between Cost Recovery and Affordability.” Working Paper 8, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Chapter 7 Contributors Maria Shkaratan, Cecilia Briceño-Garmendia, Karlis Smits, Vivien Foster, Nataliya Pushak, Jacqueline Irving, Astrid Manroth. Key Source Documents Briceño-Garmendia, Cecilia, Karlis Smits, and Vivien Foster. 2008. “Financing Public Infrastructure in Sub-Saharan Africa: Patterns and Emerging Issues.” Background Paper 15, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Irving, Jacqueline, and Astrid Manroth. 2009. “Local Sources of Financing for Infrastructure in Africa: A Cross-Country Analysis.” Policy Research Working Paper 4878, World Bank, Washington, DC. xxiv Acknowledgments Substantial sections of this book were derived from the above-listed background papers, as well as from the text of the AICD flagship report, Africa’s Infrastructure: A Time of Transformation, edited by Vivien Foster and Cecilia Briceño-Garmendia. The work benefited from widespread peer review from colleagues within the World Bank, notably Rob Mills, Dana Rysankova, Reto Thoenen, and Fabrice Karl Bertholet. The external peer reviewer for this volume, Mark Davis, provided constructive and thoughtful comments. The comprehensive editorial effort of Steven Kennedy is much appreciated. Philippe Benoit, David Donaldson, Gabriel Goddard, S. Vijay Iyer, Luiz Maurer, Rob Mills, Fanny Missfeldt-Ringius, Lucio Monari, Kyran O’Sullivan, Prasad Tallapragada V.S.N., Clemencia Torres, and Tjaarda P. Storm van Leeuwen contributed significantly to the technical analysis and policy recommendations for the AICD power sector work, which formed the basis of this book. None of this research would have been possible without the generous collaboration of government officials in the key sector institutions of each country, as well as the arduous work of local consultants who assembled this information in a standardized format. Key contributors to the book on a country-by-country basis were as follows. Country Local consultants or other partners Angola Fares Khoury (Etude Economique Conseil, Canada) Benin Jean-Marie Fansi (Pricewaterhouse Coopers) Botswana Adam Vickers, Nelson Mokgethi Burkina Faso Maxime Kabore Cameroon Kenneth Simo (Pricewaterhouse Coopers) Cape Verde Sandro de Brito Central African Republic Ibrahim Mamame Chad Kenneth Simo (Pricewaterhouse Coopers) Congo, Dem. Rep. Henri Kabeya Congo, Rep. Mantsie Rufin-Willy Côte d’Ivoire Jean-Phillipe Gogua, Roland Amehou Ethiopia Yemarshet Yemane Gabon Fares Khoury (Etude Economique Conseil, Canada) Ghana Afua Sarkodie Kenya Ayub Osman (Pricewaterhouse Coopers) Lesotho Peter Ramsden Madagascar Gerald Razafinjato Mali Ibrahim Mamame Acknowledgments xxv Country Local consultants or other partners Mauritania Fares Khoury (Etude Economique Conseil, Canada) Mauritius Boopen Seetanah Mozambique Manuel Ruas Namibia Peter Ramsden Niger Oumar Abdou Moulaye Nigeria Abiodun Momodu Rwanda Charles Uramutse Sierra Leone Adam Vickers, Nelson Mokgethi with the support of Alusine Kamara in SL Statistical Office Senegal Alioune Fall South Africa Peter Ramsden Swaziland Adam Vickers, Nelson Mokgethi Tanzania Adson Cheyo (Pricewaterhouse Coopers) Uganda Adson Cheyo (Pricewaterhouse Coopers) Zambia Mainza Milimo, Natasha Chansa (Pricewaterhouse Coopers) Zimbabwe Eliah Tafangombe Abbreviations All currency denominations are in U.S. dollars unless noted. AICD Africa Infrastructure Country Diagnostic AIM alternative investment market AMADER Agence Malienne pour le Developpement de l’Energie Domestique et d’Electrification Rurale AU African Union BPC Botswana Power Corporation BRVM Bourse Régionale des Valeurs Mobilières capex capital expenditures CAPP Central African Power Pool CDM Clean Development Mechanism CER certified emission reduction credit CIE Compagnie Ivoirienne d’Electricité CIPREL Compagnie Ivoirienne de Production d’Electricité CREST Commercial Reorientation of the Electricity Sector Toolkit DBT decreasing block tariff EAPP East African Power Pool ECOWAS Economic Community of West African States EDF Electricité de France xxvii xxviii Abbreviations EDM Electricidade de Moçambique ESMAP Energy Sector Management Assistance Program FR fixed rate GDP gross domestic product GW gigawatt HFO heavy fuel oil IBT increasing block tariff ICT information and communication technology IDA International Development Association IFRS International Financial Reporting Standards IPP independent power project KenGen Kenya Electricity Generating Company KPLC Kenya Power and Lighting Company kVA kilovolt-ampere kWh kilowatt-hour LRMC long-run marginal cost LuSE Lusaka Stock Exchange MW megawatt NEPAD New Partnership for Africa’s Development NES National Electrification Scheme NGO nongovernmental organization O&M operations and maintenance ODA official development assistance OECD Organisation for Economic Co-operation and Development opex operational expenses PPA power-purchase agreement PPI private participation in infrastructure PPIAF Public-Private Infrastructure Advisory Facility Q quintile REA rural electrification agency REF rural electrification fund RERA Regional Electricity Regulators Association ROR rate of return SADC Southern African Development Community SAPP Southern African Power Pool SHEP Self-Help Electrification Programme SOE state-owned enterprise SSA Sub-Saharan Africa T&D transmission and distribution Abbreviations xxix tcf trillion cubic feet TFP total factor productivity TOU time of use TPA third-party access TW terawatt TWh terawatt-hour UCLF unplanned capability loss factor USO universal service obligation WAPP West African Power Pool Wh watt-hour WSS water supply and sanitation CHAPTER 1 Africa Unplugged Sub-Saharan Africa is in the midst of a power crisis. The region’s power generation capacity is lower than that of any other world region, and capacity growth has stagnated compared with other developing regions. Household connections to the power grid are scarcer in Sub-Saharan Africa than in any other developing region. The average price of power in Sub-Saharan Africa is double that in other developing regions, but the supply of electrical power is unreliable throughout the continent. The situation is so dire that countries increas- ingly rely on emergency power to cope with electricity shortages.1 The weakness of the power sector has constrained economic growth and development in the region. The Region’s Underdeveloped Energy Resources An estimated 93 percent of Africa’s economically viable hydropower potential—or 937 terawatt-hours (TWh) per year, about one-tenth of the world’s total—remains unexploited. Much of that is located in the Democratic Republic of Congo, Ethiopia, Cameroon, Angola, Madagascar, Gabon, Mozambique, and Nigeria (in descending order by capacity). Some of the largest operating hydropower installations are in 1 2 Africa’s Power Infrastructure the Democratic Republic of Congo, Mozambique, Nigeria, Zambia, and Ghana. Burundi, Lesotho, Malawi, Rwanda, and Uganda also rely heavily on hydroelectricity. Although most Sub-Saharan African countries have some thermal power stations, only a few use local petroleum and gas resources. Instead, most countries rely on imports. There are a few exceptions: proven oil reserves are concentrated in Nigeria (36 billion barrels), Angola (9 billion barrels), and Sudan (6.4 billion barrels). A number of smaller deposits have been found in Gabon, the Republic of Congo, Chad, Equatorial Guinea, Cameroon, the Democratic Republic of Congo, and Côte d’Ivoire.2 Overall, Sub-Saharan Africa accounts for less than 5 percent of global oil reserves. Actual oil production follows a similar pattern (BP 2007). Natural gas reserves are concentrated primarily in Nigeria (5.2 trillion cubic feet [tcf]). Significant natural gas discoveries have also been made in Mozambique, Namibia, and Angola, with reserves of 4.5 tcf, 2.2 tcf, and 2.0 tcf, respectively. Small amounts have been discovered in Tanzania. Gas reserves in Sub-Saharan Africa make up less than 4 percent of the world’s total proven reserves, and actual gas production is an even smaller proportion of the world’s total production (BP 2007). Only one nuclear power plant has been built on the continent: the 1,800 megawatt (MW) Koeberg station in South Africa. Africa’s natural uranium reserves account for approximately one-fifth of the world’s total and are located mainly in South Africa, Namibia, and Niger. Geothermal power looks economically attractive in the Rift Valley, and Kenya has several geothermal plants in operation. The continent has abun- dant renewable energy resources, particularly solar and wind, although these are often costly to develop and mostly provide off-grid power in remote areas where alternatives such as diesel generators are expensive. The Lag in Installed Generation Capacity The combined power generation capacity of the 48 countries of Sub- Saharan Africa is 68 gigawatts (GW)—no more than that of Spain. Excluding South Africa, the total falls to 28 GW, equivalent to the installed capacity of Argentina (data for 2005; EIA 2007). Moreover, as much as 25 percent of installed capacity is not operational for various rea- sons, including aging plants and lack of maintenance. The installed capacity per capita in Sub-Saharan Africa (excluding South Africa) is a little more than one-third of South Asia’s (the two regions were equal in 1980) and about one-tenth of that of Latin America Africa Unplugged 3 (figure 1.1). Capacity growth has been largely stagnant during the past three decades, with growth rates of barely half those found in other devel- oping regions. This has widened the gap between Sub-Saharan Africa and the rest of the developing world, even compared with other country groups in the same income bracket (Yepes, Pierce, and Foster 2008). South Africa’s power infrastructure stands in stark contrast to that of the region as a whole. With a population of 47 million people, South Africa has a total generation capacity of about 40,000 MW. Nigeria comes in second, with less than 4,000 MW, despite its much larger population of 140 million. A handful of countries have intermediate capacity: the Democratic Republic of Congo (2,443 MW), Zimbabwe (2,099 MW), Zambia (1,778 MW), Ghana (1,490 MW), Kenya (1,211 MW), and Côte d’Ivoire (1,084 MW)—although not all of their capacity is operational. Capacity is much lower in other countries: Mali (280 MW), Burkina Faso (180 MW), Rwanda (31 MW), and Togo (21 MW) (EIA 2007). Per capita generation capacity also varies widely among countries (figure 1.2). In 2004, the power plants of Sub-Saharan Africa generated 339 TWh of electricity—approximately 2 percent of the world’s total. South African power plants generated about 71 percent of that total (Eberhard and others 2008). Coal-fired plants generate 93 percent of South Africa’s electricity, and coal is therefore the dominant fuel in the region. Most of Figure 1.1 Power Generation Capacity by Region, 1980–2005 600 500 MW / million people 400 300 200 100 0 1980 1985 1990 1995 2000 2005 East Asia and Pacific Latin America and the Caribbean Middle East and North Africa South Asia Sub-Saharan Africa Sub-Saharan Africa without South Africa Source: Derived by authors from AICD 2008 and EIA 2007. Note: MW = megawatt. 4 Africa’s Power Infrastructure Figure 1.2 Power Generation Capacity in Sub-Saharan Africa by Country, 2006 Gabon Zimbabwe Cape Verde Zambia Namibia Mozambique Swaziland Botswana Ghana São Tomé and Príncipe Côte d’Ivoire Angola Cameroon Senegal Nigeria Congo, Dem. Rep. Lesotho Kenya Congo, Rep. Eritrea Guinea Sudan Equatorial Guinea Mali Tanzania Malawi Gambia, The Burkina Faso Togo Guinea-Bissau Madagascar Ethiopia Uganda Sierra Leone Central African Republic Comoros Niger Somalia Benin Rwanda Burundi Chad 0 20 40 60 80 100 120 140 160 180 200 MW per million people Source: EIA 2007. Note: By comparison, South Africa’s figure is 855 MW per million people. MW = megawatt. Africa Unplugged 5 the region’s coal reserves are located in the south, mainly in South Africa, which has the fifth-largest reserves globally and ranks fifth in annual global production (BP 2007). Few other countries in the region rely on coal, but Botswana and Zimbabwe are among the exceptions.3 Coal reserves in Africa constitute just 5.6 percent of the global total. Power generation in Sub-Saharan Africa is much different outside of South Africa. Hydropower accounts for close to 70 percent of electricity generation (and about 50 percent of installed generation capacity), with the remainder divided almost evenly between oil and natural gas generators. Stagnant and Inequitable Access to Electricity Services Sub-Saharan Africa has low rates of electrification. Less than 30 percent of the population of Sub-Saharan Africa has access to electricity, com- pared with about 65 percent in South Asia and more than 90 percent in East Asia (figure 1.3). Based on current trends, fewer than 40 percent of Figure 1.3 Household Electrification Rate in World Regions, 1990–2005 100 90 80 % households with access 70 60 50 40 30 20 10 0 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 19 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 East Asia and Pacific Europe and Central Asia Latin America and the Caribbean South Asia Sub-Saharan Africa IDA total Source: Eberhard and others 2008. Note: IDA = International Development Association. 6 Africa’s Power Infrastructure African countries will achieve universal access to electricity by 2050 (Banerjee and others 2008). Per capita consumption of electricity averages just 457 kilowatt-hour (kWh) annually in the region, and that figure falls to 124 kWh if South Africa is excluded (Eberhard and others 2008). By contrast, the annual average per capita consumption in the developing world is 1,155 KWh and 10,198 kWh. If South Africa is excluded, Sub-Saharan Africa is the only world region in which per capita consumption of electricity is falling. Figure 1.4 shows the relationship between electricity consumption and economic development in world regions. All countries in Sub-Saharan Africa (except South Africa) lag far behind other regions in per capita power consumption and gross domestic product (GDP). Because of its low electricity consumption, Sub-Saharan Africa is an insignificant contributor to carbon dioxide emissions and climate change. It has the lowest per capita emissions among all world regions and has some of the lowest emissions in terms of GDP output. Excluding South Africa, the power sector in Sub-Saharan Africa accounts for less than 1 percent of global carbon dioxide emissions. Figure 1.4 Per Capita Electricity Consumption and GDP in Selected Countries of Sub-Saharan Africa and World Regions, 2004 3.8 3.6 Latin America & Caribbean 3.4 South Africa Europe & Central Asia Middle East & North Africa log (GDP per capita) 3.2 East Asia & Pacific 3.0 Cameroon 2.8 Côte d’Ivoire Sub-Saharan Africa Senegal South Asia 2.6 Kenya Zambia 2.4 Ghana 2.2 2.0 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 3.6 3.8 log (electricity consumption per capita) Source: Eberhard and others 2008. Note: GDP = gross domestic product. Africa Unplugged 7 Unreliable Electricity Supply Power supply in Sub-Saharan Africa is notoriously unreliable. Conventional measures of the reliability of power systems include the unplanned capability loss factor (UCLF)4 of generators, the number of transmission interruptions, and indexes of the frequency and duration of interruptions. Yet most African countries still do not systematically collect or report these data. The World Bank enterprise surveys, which provide a useful alternative measure of the reliability of grid-supplied power, indi- cate that most African enterprises experience frequent outages. In 2007, for example, firms in Senegal, Tanzania, and Burundi experienced power outages for an average of 45, 63, and 144 days, respectively (figure 1.5). The Prevalence of Backup Generators In countries that report more than 60 days of power outages per year, firms identify power as a major constraint to doing business and are more likely to own backup generators. The size, sector, and export orientation of the firm also influence the likelihood of the firm having its own generation facilities (hereafter own generation). Larger firms are more likely to own backup generators (figure 1.6). Own generation constitutes a significant proportion of total installed power capacity in the region—as much as 19 percent in West Africa (fig- ure 1.7). In the Democratic Republic of Congo, Equatorial Guinea, and Mauritania, backup generators account for half of total installed capacity. The share is much lower in southern Africa, but it is likely to increase as the region experiences further power outages. South Africa—which for many years maintained surplus capacity—recently experienced acute power shortages. The value of in-house generating capacity in Sub- Saharan Africa as a percentage of gross fixed capital formation ranges from 2 percent to as high as 35 percent (Foster and Steinbuks 2008). Frequent power outages result in forgone sales and damaged equip- ment for businesses, which result in significant losses. These losses are equivalent to 6 percent of turnover on average for firms in the formal sec- tor and as much as 16 percent of turnover for informal sector enterprises that lack a backup generator (Foster and Steinbuks 2008). The overall economic costs of power outages are substantial. Based on outage data from the World Bank’s Investment Climate Assessments (ICA), utility load-shedding data,5 and the estimates of the value of lost load or unserved energy, power outages in the countries in Sub-Saharan Africa constitute an average of 2.1 percent of GDP. In those Africa 8 Africa’s Power Infrastructure Figure 1.5 Power Outages, Days per Year, 2007–08 Congo, Dem. Rep. Burundi Guinea Angola Kenya Madagascar Gambia, The Guinea-Bissau Ethiopia Rwanda Sudan Malawi Uganda Tanzania Ghana Mozambique Zimbabwe Mauritius Côte d’Ivoire Nigeria Sierra Leone Togo Senegal Central African Rep. Chad Equatorial Guinea Gabon Zambia Congo Cape Verde Cameroon Lesotho Benin Botswana Namibia Mali Burkina Faso South Africa Mauritania Niger 0 20 40 60 80 100 120 140 160 180 200 Source: Enterprise Survey database; World Bank 2008. Africa Unplugged 9 Figure 1.6 Generator Ownership by Firm Size 60 50 % of generator owners 40 30 20 10 0 oy 10 oy 50 oy 00 oy 50 oy an pl 10– pl 0–1 pl 0–2 pl e th s s s s s pl an ee ee ee ee ee em r th em 5 em 10 em or M e w em Fe 0 25 firm size Source: Foster and Steinbuks 2008. Figure 1.7 Own Generation as Share of Total Installed Capacity by Subregion, 2006 20 18 16 % of installed capacity 14 12 10 8 6 4 2 0 ca a ca a ric ric fri fri Af Af lA tA st rn ra es Ea he nt W Ce ut So Source: Foster and Steinbuks 2008. Infrastructure Country Diagnostic (AICD) countries for which we were able to make our own calculations (about half of the countries), the costs ranged from less than 1 percent of GDP in countries such as Niger to 4 percent of GDP and higher in countries such as Tanzania (figure 1.8). 10 Africa’s Power Infrastructure Figure 1.8 Economic Cost of Power Outages as Share of GDP, 2005 7 6 percentage of GDP 5 4 3 2 1 0 n o r e r n l a a da a i ga aw ge ca ny ni ric rd as ni oo an as za ne Be Ni Ve aF al Af Ke er Ug ag M n Se m in h pe Ta ut ad Ca rk Ca So Bu M Source: Briceño-Garmendia 2008 and authors’ calculations of own-generation costs based on Foster and Steinbuks 2008. Note: GDP = gross domestic product. Increasing Use of Leased Emergency Power The increasing use of grid-connected emergency power in the region reflects the gravity of the power crisis (table 1.1). Countries experiencing pressing power shortages can enter into short-term leases with specialized operators who install new capacity (typically in shipping containers) within a few weeks, which is much faster than a traditional power-generation proj- ect. The country leases the equipment for a few months to a few years, after which the private operator removes the power plant. Temporary emergency generators now account for an estimated 750 MW of capac- ity in Sub-Saharan Africa, and they constitute a significant proportion of total capacity in some countries. Emergency power is relatively expensive—typically around $0.20–0.30 per kWh. In some countries, the cost of emergency power is a considerable percentage of GDP.6 Procurement has also been tainted by corruption and bribery. For exam- ple, the Tanzanian prime minister and energy minister resigned in February 2008 after a parliamentary investigation revealed that lucrative contracts for emergency power had been placed with a company with no power generation experience. Despite the high cost of leased power, a multi-megawatt emergency power installation can be large enough to achieve economies of scale, and it is a better option than individual backup generators. The cost of Table 1.1 Overview of Emergency Power Generation in Sub-Saharan Africa (Up to 2007) Contract Emergency Percent of total Estimated annual Country Date duration (years) capacity (MW) installed capacity cost (% GDP) Angola 2006 2 150 18.1 1.04 Gabon — — 14 3.4 0.45 Ghana 2007 1 80 5.4 1.90 Kenya 2006 1 100 8.3 1.45 Madagascar 2004 Several years 50 35.7 2.79 Rwanda 2005 2 15 48.4 1.84 Senegal 2005 2 40 16.5 1.37 Sierra Leone 2007 1 20 100 4.25 Tanzania 2006 2 180 20.4 0.96 Uganda 2006 2 100 41.7 3.29 Source: Eberhard and others 2008. Note: Leases for emergency power are generally short term. Therefore, installed capacities in individual countries change from year to year. — = Not available. 11 12 Africa’s Power Infrastructure emergency power also far exceeds the value of lost load. Countries that have entered into these expensive, short-term contracts understand the potentially greater economic cost of power shortages. A Power Crisis Exacerbated by Drought, Conflict, and High Oil Prices In recent years, external factors have exacerbated the already precarious power situation in Sub-Saharan Africa. Drought has seriously reduced the power available to hydro-dependent countries in western and eastern Africa. Countries with significant hydropower installations in affected catchments—Burundi, Ghana, Kenya, Madagascar, Rwanda, Tanzania, and Uganda—have had to switch to expensive diesel power. High inter- national oil prices have also put enormous pressure on all of the oil- importing countries of Sub-Saharan Africa, especially those dependent on diesel and heavy fuel oil for their power-generation needs. Furthermore, war has seriously damaged power infrastructure in the Central African Republic, the Democratic Republic of Congo, Liberia, Sierra Leone, and Somalia. In Zimbabwe, political conflict and economic contraction have undermined the power system as investment resources have dried up. Overall, countries in conflict perform worse in the development of infra- structure than do countries at peace (Yepes, Pierce, and Foster 2008). Other countries, such as Nigeria and South Africa, are experiencing a power crisis induced by rapid growth in electricity demand coupled with prolonged underinvestment in new generation capacity. Both of those countries have experienced blackouts in recent years. High Power Prices That Generally Do Not Cover Costs Power in Sub-Saharan Africa is generally expensive by international stan- dards (figure 1.9). The average power tariff in Sub-Saharan Africa is $0.12 per kWh, which is about twice the tariff in other parts of the devel- oping world, and almost as high as in the high-income countries of the Organisation for Economic Co-operation and Development. There are exceptions: Angola, Malawi, South Africa, Zambia, and Zimbabwe have maintained low prices that are well below costs (Sadelec 2006). Power from backup generators is much more expensive than grid power (figure 1.10), which increases the weighted average cost of power to consumers above the figures quoted previously. Africa Unplugged 13 Figure 1.9 Average Residential Electricity Prices in Sub-Saharan Africa and Other Regions, 2005 0.20 0.16 0.12 $/kWh 0.08 0.04 0.00 a ia sia c CD ea d ric i As cif Su ribb an lA OE Af n Pa h a ra ut n Ca ic nt d ra e er So an Ce ha th Am ia Sa d As an tin b- st La pe Ea ro Eu Source: Briceño-Garmendia and Shkaratan 2010. Note: OECD = Organisation for Economic Co-operation and Development. Figure 1.10 Average Cost of Grid and Backup Power in Sub-Saharan Africa 0.8 0.7 0.6 0.5 $/kWh 0.4 0.3 0.2 0.1 0.0 o, am a m ia M Eth ep. bi a M ue Ni wi Ug ria Cô Les da d’ o Na oire Gh ia a ts d nz a M Ke ia ag ya Rw ina Ca er a Ve n Co B e o, n ne . Ni l i Bu car r Se ep ga al ge ng Z fric am pi an Ta an m d rd te oth pe oo ng eni Bo Cha De b ib an M ad n a ge an Ca an q as rk .R R oz io al m w Iv A h ut So Co grid power unit cost of self-generation Source: Briceño-Garmendia 2008 and authors’ calculations of own-generation costs based on Foster and Steinbuks 2008. 14 Africa’s Power Infrastructure Although electricity in the region is relatively expensive, most Sub- Saharan Africa countries are doing little more than covering their average operating costs (figure 1.11). The close correlation between average effec- tive tariff7 and average cost across the countries of Sub-Saharan Africa (as high as 58 percent) indicates that for the most part they price their power with the intent of breaking even. Countries with average operating costs in excess of $0.15 per kWh tend to set prices somewhat below this level. Figure 1.11 Average Power Sector Revenue Compared with Costs a. Against average operating cost ($ per kWh) 0.5 0.4 average revenue ($/kWh) 0.3 0.2 0.1 0.1 0.2 0.3 0.4 0.5 average operating cost ($ per kWh) b. Against average incremental cost ($ per kWh) 0.5 average effective tariff ($/kWh) 0.4 0.3 0.2 0.1 0.1 0.2 0.3 0.4 0.5 average incremental cost ($ per kWh) Source: Briceño-Garmendia and Shkaratan 2010. Africa Unplugged 15 A simple comparison of average revenues and average operating costs misrepresents the prospects for long-term cost recovery for two reasons. First, owing to major failures in utility revenue collection, operators col- lect far less per unit of electricity from customers than they charge. Second, for many countries in Sub-Saharan Africa, the average total cost associated with power developments in the past is actually higher than the average incremental cost of producing new power in the future. This is because historically, power development has been done using small- scale and inefficient generation technologies, which could be superseded as countries become able to trade power with one another, thereby har- nessing larger-scale and more efficient forms of production. Thus, a com- parison of the average tariff that operators charge (but do not necessarily collect) with the average incremental cost of generating power provides a more accurate picture of the situation. Regardless, in some countries, rev- enues would cover costs only if tariffs were fully collected and if the power system moved toward a more efficient production structure. In the past the state or donors have subsidized the share of capital investment that tariffs could not cover.8 Households account for the majority of power utility sales in many African countries but only about 50 percent of sales revenue because of poor collections and underpricing. Thus, tariffs charged to commercial and industrial consumers are impor- tant sources of revenue for the utility. It is more difficult to assess whether tariffs for commercial and industrial customers are high enough to cover costs. The limited evidence available suggests that the average revenue raised from low- and medium-voltage customers does cover costs, whereas high-voltage customers tend to pay less. This relative price dif- ferential, which is not uncommon around the world, reflects the fact that high-voltage customers take their supply directly from the transmission grid. They do not make use of the distribution network and hence do not create such high costs for the power utility. Nevertheless, it is unclear whether these lower tariffs for large, high-voltage customers are actually covering costs. Numerous countries have historically charged highly discounted tariffs of just a few cents per kWh to large-scale industrial and mining cus- tomers, such as the aluminum smelting industry in Cameroon, Ghana, and South Africa and the mining industry in Zambia. These arrangements were intended to secure base-load demand to support the development of large-scale power projects that went beyond the immediate demands of the country. Growing demand has begun to absorb excess capacity, however, which makes the relevance of the discounts dubious. 16 Africa’s Power Infrastructure Deficient Power Infrastructure Constrains Social and Economic Development Based on panel data analysis, Calderón (2008) provides a comprehensive assessment of the impact of infrastructure stocks on growth in Sub- Saharan Africa between the early 1990s and the early 2000s. Calderón finds that if African countries were to catch up with the regional leader, Mauritius, in terms of infrastructure stock and quality, their per capita economic growth rates would increase by an average of 2.2 percent per year. Catching up with the East Asian median country, the Republic of Korea, would bring gains of 2.6 percent per year. In several countries— including Côte d’Ivoire, the Democratic Republic of Congo, and Senegal—the effect would be even greater. Deficient power infrastructure and power outages dampen economic growth, especially through their detrimental effect on firm productiv- ity. Using enterprise survey data collected through the World Bank’s Investment Climate Assessments, Escribano, Guasch, and Peña (2008) find that in most countries of Sub-Saharan Africa, infrastructure accounts for 30–60 percent of the effect of investment climate on firm productivity—well ahead of most other factors, including red tape and corruption. In half of the countries analyzed, the power sector accounted for 40–80 percent of the infrastructure effect (figure 1.12). Infrastructure is also an important input into human development. Better provision of electricity improves health care because vaccines and medications can be safely stored in hospitals and food can be preserved at home (Jimenez and Olson 1998). Electricity also improves literacy and primary school completion rates because students can read and study when there is no natural light (Barnes 1988; Brodman 1982; Foley 1990; Venkataraman 1990). Similarly, better access to electricity lowers costs for businesses and increases investment, driving economic growth (Reinikka and Svensson 1999). In summary, chronic power problems—including insufficient invest- ment in generation capacity and networks, stagnant or declining connec- tivity, poor reliability, and high costs and prices (which further hinders maintenance, refurbishment, and system expansion)—have created a power crisis in Sub-Saharan Africa. Drought, conflict, and high oil prices have exacerbated the crisis. The overall deficiency of the power sector has constrained economic and social development. Although the extent of the problems and challenges differs across regions and countries, Sub-Saharan Africa has generally lagged behind other regions of the world in terms of infrastructure and power sector investment and performance. This book investigates how these problems and challenges might be addressed. Africa Unplugged 17 Figure 1.12 Contribution of Infrastructure to Total Factor Productivity (TFP) of Firms a. Overall contribution of infrastructure Namibia Botswana Swaziland Mauritius South Africa Kenya Madagascar Tanzania Niger Burkina Faso Mauritania Cameroon Mali Eritrea Zambia Ethiopia Uganda Senegal Benin Malawi 0 20 40 60 80 100 percentage contribution to TFP infrastructure others (continued next page) 18 Africa’s Power Infrastructure Figure 1.12 (continued) b. Infrastructure contribution by sector Eritrea Ethiopia Botswana Swaziland Namibia Mali Uganda Zambia Kenya Senegal Madagascar South Africa Malawi Mauritania Niger Burkina Faso Cameroon Benin Tanzania Mauritius 0% 20% 40% 60% 80% 100% percentage contribution to TFP electricity customs clearance transportation ICT water Source: Escribano, Guasch, and Peña 2008. Note: ICT = information and communication technology. Africa Unplugged 19 Notes 1. Emergency power is a term for expensive, short-term leases for generation capacity. 2. Small deposits were also recently discovered in countries such as Ghana and Uganda. 3. Mauritius, Namibia, Niger, and Tanzania also have small coal-generation plants. Mozambique is planning investments in coal power stations. 4. The UCLF is the percentage of time over a year that the generation plant is not producing power, excluding the time that the plant was shut down for routine, planned maintenance. 5. Load shedding occurs when the power grid is unable to meet demand, and customers’ supply is cut off. 6. Spending on emergency power can displace expenditures on social services such as health and education. For example, Sierra Leone has a population of 6 million but only 28,000 electricity customers. The country relies heavily on an overpriced emergency diesel-based power supply contract for its electric- ity needs. As a result, the government of Sierra Leone has not been able to meet the minimum targets for expenditures in health and education that are required for continued budget support by the European Union and other donors. 7. Effective tariffs are prices per kWh at typical monthly consumption levels calculated using tariff schedules applicable to typical customers within each customer group. 8. One of the casualties of insufficient revenue is maintenance expenditure. Utility managers often have to choose between paying salaries, buying fuel, or purchasing spares (often resorting to cannibalizing parts from functional equipment). For example, in Sierra Leone, the overhead distribution network for the low-income eastern part of Freetown has been cannibalized for spare parts to repair the network of the high-income western part of the town. Thus, even with the advent of emergency generators, many former customers in the eastern districts remain without power. References AICD (Africa Infrastructure Country Diagnostic). 2008. AICD Power Sector Database. Washington, DC: World Bank. Banerjee, Sudeshna, Quentin Wodon, Amadou Diallo, Taras Pushak, Hellal Uddin, Clarence Tsimpo, and Vivien Foster. 2008. “Access, Affordability and Alternatives: Modern Infrastructure Services in Sub-Saharan Africa.” Background Paper 2, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. 20 Africa’s Power Infrastructure Barnes, Douglas F. 1988. Electric Power for Rural Growth: How Electricity Affects Rural Life in Developing Countries. Boulder: Westview Press. BP (British Petroleum). 2007. Statistical Review of Energy. London: Beacon Press. Briceño-Garmendia, Cecilia. 2008. “Quasi-Fiscal Costs: A Never Ending Concern.” Internal Note, World Bank, Washington, DC. Briceño-Garmendia, Cecilia, and Maria Shkaratan. 2010. “Power Tariffs: Caught between Cost Recovery and Affordability.” Working Paper 20, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Brodman, Janice. 1982. “Rural Electrification and the Commercial Sector in Indonesia.” Discussion Paper D-73L, Resources for the Future, Washington, DC. Calderón, Cesar. 2008. “Infrastructure and Growth in Africa.” Working Paper 3, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Eberhard, Anton, Vivien Foster, Cecilia Briceño-Garmendia, Fatimata Ouedraogo, Daniel Camos, and Maria Shkaratan. 2008. “Underpowered: The State of the Power Sector in Sub-Saharan Africa.” Background Paper 6, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. EIA (Energy Information Administration). 2007. “International Energy Data.” U.S. Department of Energy. http://www.eia.doe.gov/emeu/international. Escribano, Alvaro, J. Luis Guasch, and Jorge Peña. 2008. “Impact of Infrastructure Constraints on Firm Productivity in Africa.” Working Paper 9, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Foley, Gerald. 1990. Electricity for Rural People. London: Panos Institute. Foster, Vivien, and Jevgenijs Steinbuks. 2008. “Paying the Price for Unreliable Power Supplies: In-House Generation of Electricity by Firms in Africa.” Working Paper 2, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Jimenez, Antonio, and Ken Olson. 1998. “Renewable Energy for Rural Health Clinics.” National Renewable Energy Laboratory, Golden, CO. http://www .nrel.gov/docs/legosti/fy98/25233.pdf. Reinikka, Ritva, and Jakob Svensson. 1999. “Confronting Competition: Firms’ Investment Response and Constraints in Uganda.” In Assessing an African Success: Farms, Firms, and Government in Uganda’s Recovery, ed. P. Collier and R. Reinikka, 207–34. Washington, DC: World Bank. Sadelec, Ltd. 2006. “Electricity Prices in Southern and East Africa (Including Selected Performance Indicators).” Sadelec, Ltd., Johannesburg, South Africa. Venkataraman, Krishnaswami. 1990. “Rural Electrification in the Asian and Pacific Region.” In Power Systems in Asia and the Pacific, with Emphasis on Rural Africa Unplugged 21 Electrification, ed. Economic and Social Commission for Asia and the Pacific, 310–32. New York: United Nations. ———. 2008. Enterprise Survey Database. Washington, DC: World Bank. Yepes, Tito, Justin Pierce, and Vivien Foster. 2008. “Making Sense of Africa’s Infrastructure Endowment: A Benchmarking Approach.” Policy Research Working Paper 4912, World Bank, Washington, DC. CHAPTER 2 The Promise of Regional Power Trade Africa consists of many small isolated economies. Integrating physical infrastructure is therefore necessary to promote regional economic integration and enable industries to reach economies of scale. In par- ticular, regional integration would allow countries to form regional power pools, which can already be found at varying stages of maturity in Southern, West, East, and Central Africa. Regional trade would allow countries to substitute hydropower for thermal power, which would lead to a substantial reduction in operating costs—despite the requisite investments in infrastructure and cross-border transmission capacity. Our modeling indicates that the annual costs of power system operation and development in the region could fall by $2.7 billion. The returns to cross-border transmission investment could be 20–30 per- cent in most power pools and can be as high as 120 percent in the Southern African Power Pool (SAPP). The greater share of hydropower associated with regional trade would also reduce annual carbon diox- ide emissions by 70 million tons. Under regional power trade, a few large exporting countries would serve many power importers. The Democratic Republic of Congo, Ethiopia, and Guinea would emerge as the major hydropower exporters. 23 24 Africa’s Power Infrastructure Yet the magnitude of the investments needed to develop their exporting potential is daunting relative to the size of their economies. At the same time, as many as 16 African countries would benefit (from a purely eco- nomic standpoint) from the opportunity to reduce costs by importing more than 50 percent of their power. Savings for those countries range from $0.01 to $0.07 per kilowatt-hour (kWh). The largest beneficiaries of regional trade would be smaller nations that lack domestic hydropower resources. For these countries, the cost savings generated by regional trade would repay the requisite investment in cross-border transmission in less than a year, contingent on neighboring countries developing sufficient surplus power to export. Uneven Distribution and Poor Economies of Scale Only a small fraction of the ample hydropower and thermal energy resources in Sub-Saharan Africa have been developed into power gener- ation capacity. Some of the region’s least expensive sources of power are far from major centers of demand in countries too poor to develop them. For example, 61 percent of regional hydropower potential is found in just two countries: the Democratic Republic of Congo and Ethiopia. Both are poor countries with a gross domestic product (GDP) of less than $30 billion. The uneven distribution of resources in the region has forced many countries to adopt technically inefficient forms of generation powered by expensive imported fuels to serve their small domestic power markets. Expensive diesel or heavy fuel oil generators account for about one-third of installed capacity in Eastern and Western Africa (figure 2.1a). In many cases, countries that lack adequate domestic energy resources could replace this capacity with the much cheaper hydro and gas resources of neighboring countries. Few countries in the region have sufficient demand to justify power plants large enough to exploit economies of scale (figure 2.1b). For exam- ple, 33 out of 48 countries in Sub-Saharan Africa have national power sys- tems that produce and consume less than 500 megawatts (MW), and 11 countries have national power systems of less than 100 MW. The small market size of most countries in Sub-Saharan Africa contributes to severely inflated generation costs. A comparison of operating costs disaggregated into four categories reveals the negative consequences of technically inefficient power The Promise of Regional Power Trade 25 Figure 2.1 Profile of Power Generation Capacity in Sub-Saharan Africa a. Generation technology as percentage of installed capacity 100 % of installed capacity 80 60 40 20 0 CAPP EAPP SAPP WAPP overall power system hydro diesel gas coal other b. Scale of production as percentage of installed capacity 100 % of installed capacity 80 60 40 20 0 CAPP EAPP SAPP WAPP overall power system <10 MW 10–100 MW 100–500 MW >500 MW Source: Eberhard and others 2008. Note: CAPP = Central African Power Pool; EAPP = East African Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool; MW = megawatt. generation (figure 2.2). For example, the average operating cost of predominantly diesel-based power systems can be as high as $0.14 per kWh—almost twice the cost of predominantly hydro-based systems. Similarly, operating costs in countries with small national power sys- tems (less than 200 MW installed capacity) are much higher than in countries with large national power systems (more than 500 MW 26 Africa’s Power Infrastructure Figure 2.2 Disaggregated Operating Costs for Power Systems in Sub-Saharan Africa, 2005 a. By regional power pool b. By technology 0.20 0.20 0.15 0.15 $/kWh $/kWh 0.10 0.10 0.05 0.05 0.00 0.00 dr y es y ll PP PP PP P ll ra hy ntl di ntl ra AP o el CA EA SA e e a a ov W ov in in om om ed ed pr pr c. By scale of power system d. By geographical characteristics 0.20 0.20 0.15 0.15 $/kWh $/kWh 0.10 0.10 0.05 0.05 0.00 0.00 ds ed l l y y y l ta al al cit cit cit er an er as ck pa pa pa ov ov co -lo isl ca ca ca nd gh m w la lo iu hi ed m Source: Eberhard and others 2008. Note: CAPP = Central African Power Pool; EAPP = East African Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool; kWh = kilowatt hour. installed capacity). Island states face a further cost penalty attributa- ble to the high cost of transporting fossil fuels. Despite Power Pools, Low Regional Power Trade Based on the economic geography of the power sector in Sub-Saharan Africa, regional power trade has many potential benefits. In fact, four regional power pools in Sub-Saharan Africa have already been established to promote mutually beneficial cross-border trade in electricity. The the- ory was that enlarging the market for electric power beyond national bor- ders would stimulate capacity investment in countries with a comparative The Promise of Regional Power Trade 27 advantage in generation. The pools would also smooth temporary irregu- larities in supply and demand in national markets. Despite high hopes for the power pools, power trade among countries in the region is still very limited. Most trade occurs within the SAPP, largely between South Africa and Mozambique (figure 2.3). Furthermore, Figure 2.3 Electricity Exports and Imports in Sub-Saharan Africa, 2005 Uganda Côte d’Ivoire Congo, Dem. Rep. Lesotho Kenya Burundi Rwanda Tanzania Egypt, Arab Rep. Niger Algeria Congo, Rep. Zambia Togo Benin Morocco Ghana Swaziland Namibia Botswana Zimbabwe Mozambique South Africa 0 2 4 6 8 10 12 14 16 Terawatt-hour (TWh) exports imports Source: Eberhard and others 2008. Note: TWh = terawatt-hour. 28 Africa’s Power Infrastructure South Africa reexports much of the electricity it imports from Mozambique back to that country’s aluminum smelter.1 A few countries are highly dependent on imports. In SAPP, Botswana, Namibia, and Swaziland all depend on imports from South Africa. In the West African Power Pool (WAPP, the second-largest pool), Benin, Togo, and Burkina Faso import power from Côte d’Ivoire and Ghana, and Niger imports from Nigeria. The countries of Central Africa engage in minimal power trading, although Burundi, the Republic of Congo, and Rwanda depend on imports from the Democratic Republic of Congo. Power trade in East Africa is negligible. The region’s major exporters generate electricity from hydropower (the Democratic Republic of Congo, Mozambique, and Zambia), natural gas (Côte d’Ivoire and Nigeria), or coal (South Africa). No country that relies on oil or diesel generators exports electricity. The region’s power pools have made progress in developing standard agreements that will allow trade to grow. SAPP has also developed a short-term energy market that enables daily Internet trading. Detailed regulatory guidelines to facilitate cross-border transactions have been pre- pared by the Regional Electricity Regulators Association (RERA). WAPP also aims to achieve closer regulatory integration in West Africa. Yet despite numerous successes in promoting regional power trade, overall trading volume in the region remains small (table 2.1). The Potential Benefits of Expanded Regional Power Trading Rosnes and Vennemo (2008) performed detailed simulations to estimate the potential benefits of regional power trade in Sub-Saharan Africa over a 10-year period from 2005 to 2015. They examine two basic scenarios: trade stagnation, in which countries make no further investment in cross-border Table 2.1 Regional Trade in Electricity, 2005 Percentage Consumption (TWh) Imports (TWh) Exports (TWh) electricity traded CAPP 8.80 0.01 1.80 0.1 EAPP 13.41 0.28 0.18 2.1 SAPP 233.97 22.71 25.74 9.7 WAPP 28.63 1.63 2.04 5.7 Source: Eberhard and others 2008. Note: CAPP = Central African Power Pool; EAPP = East African Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool; TWh = terawatt-hour. The Promise of Regional Power Trade 29 transmission, and trade expansion, in which trade occurs whenever the ben- efits outweigh the costs associated with system expansion. The simulation involved various assumptions regarding input prices, including fuel. To explore the sensitivity of the analysis to changes in assumptions, several subscenarios were considered beyond the base case. In the trade expansion scenario, annualized power system costs in the trading regions would be 3–10 percent lower. The savings would be the largest in the Central African Power Pool (CAPP) at 10.3 percent, com- pared with 5–6 percent in SAPP and East African/Nile Basin Power Pool (EAPP/Nile Basin) and only 3.4 percent in WAPP (although savings in some countries in this region are much higher). The annual savings for Sub-Saharan Africa total an estimated $2.7 billion, which is equivalent to 5.3 percent of the annual cost and 7.2 percent of the annual cost when operation of existing equipment is excluded. The savings come largely from substituting hydro for thermal plants, which requires more invest- ment in the short run but substantially reduces operating costs. For exam- ple, power trade generates operating cost savings equivalent to 1 percent of regional GDP in EAPP/Nile Basin and almost 0.5 percent of regional GDP in CAPP. Power trade also reduces the investment requirements of importing countries, which generates further savings. Developing countries, which generally struggle to raise sufficient investment capital to meet their infra- structure needs, clearly benefit from regional power trade. Under the trade expansion scenario, countries must make additional capital investments to facilitate cross-border transmission. The resulting operating cost savings can therefore be viewed as a substantial return on investment. In SAPP, for example, the additional investment is recouped in less than a year and yields a return of 167 percent. In the other three regions, the additional investment is recouped over three to four years, for a lower—but still generous—return of 20–33 percent. The overall return on trade expansion in Sub-Saharan Africa is 27 percent, which is consid- erable compared with investments of similar magnitude. Because trade reduces the use of thermal power plants, the gains from trade increase as fuel prices rise and more hydropower projects become profitable. For example, when the price of oil rises to $75 per barrel (instead of $46 per barrel in the base case), the gains from trade in EAPP/Nile Basin increase from about $1 billion to almost $3 billion. The 10 largest power importing countries in the trade expansion sce- nario would reduce their long-run marginal cost (LRMC) of power by $0.02–0.07 per kWh (figure 2.4). Smaller countries that rely on thermal 30 Africa’s Power Infrastructure Figure 2.4 Savings Generated by Regional Power Trade among Major Importers under Trade Expansion Scenario 8 7 savings in U.S. cents per kWh 6 5 4 3 2 1 0 au ia r la ad Se i l Eq ong ali lG . am a er que Le e Na o ia a n a p nd ga ge ne ric ny on th bo er go ib Re M iss Ch ne ru Ni so Af Ke m ui Lib Le bi Ga An o, -B Bu h ra ea ut ria oz in So Si C to Gu M ua Source: Derived from Rosnes and Vennemo 2008. Note: kWh = kilowatt hour. power, such as Burundi, Chad, Guinea-Bissau, Liberia, Niger, and Senegal, stand to gain the most. Nevertheless, reaping the full benefits of power trade will require a political willingness to depend heavily on power imports. As many as 16 African countries would benefit economically by importing more than 50 percent of their power needs. The future of power trade depends on the health of the power sector in a handful of key exporting countries endowed with exceptionally large and low-cost hydropower resources. In descending order of export poten- tial, these countries are Democratic Republic of Congo, Ethiopia, Guinea, Sudan, Cameroon, and Mozambique (table 2.2). The first three account for 74 percent of the potential exports under trade expansion. Based on a profit margin of $0.01 per kWh, the net export revenue for the top three exporters would account for 2–6 percent of their respective GDP, but the size of the investments to realize these export volumes is daunt- ing. To develop sufficient generation capacity for export, each would need to invest more than $0.7 billion per year, equivalent to more than 8 per- cent of GDP. Such investments are unlikely to be feasible without exten- sive cross-border financing arrangements that allow importing beneficiaries to make up-front capital contributions. Some 22,000 MW of interconnectors would need to be developed to allow power to flow freely across national borders, which would cost The Promise of Regional Power Trade 31 Table 2.2 Top Six Power Exporting Countries in Trade Expansion Scenario Net revenue Required investment Potential net exports $million $million Country (TWh per year) per year % GDP per year % GDP Congo, Dem. Rep. 51.9 519 6.1 749 8.8 Ethiopia 26.3 263 2.0 1,003 7.5 Guinea 17.4 174 5.2 786 23.7 Sudan 13.1 131 0.3 1,032 2.7 Cameroon 6.8 68 0.4 267 1.5 Mozambique 5.9 59 0.8 216 2.8 Source: Derived from Rosnes and Vennemo 2008. Note: GDP = gross domestic product; TWh = terawatt-hour. more than $500 million a year over the next decade. The return on invest- ment in interconnectors is as high as 120 percent in SAPP and 20–30 per- cent for the other power pools. For countries with the most to gain from power imports, investments in cross-border transmission have exception- ally high rates of return and typically pay for themselves in less than a year. What Regional Patterns of Trade Would Emerge? If regional power trade were allowed to expand, rising demand would provide incentives for several countries to develop their significant hydropower potential. In the trade expansion scenario, for example, the hydropower share of the generation capacity portfolio in SAPP rises from 25 to 34 percent. The Democratic Republic of Congo becomes the region’s major exporter of hydropower and exports more than three times its domestic consumption. Mozambique continues to be a signifi- cant exporter. Hydropower from the Democratic Republic of Congo flows southward along three parallel routes through Angola, Zambia, and Mozambique (table 2.3 and figure 2.5). Countries such as Angola, Botswana, Lesotho, Malawi, and Namibia subsequently rely on imports to meet more than 50 percent of their power demand. In addition, South Africa continues to import large volumes of power, although imports still account for only 10 percent of domestic consumption. The EAPP/Nile Basin region experiences a similar shift in generation capacity. The share of hydropower rises from 28 to 48 percent of the gen- eration capacity portfolio, which partially displaces gas-fired power capacity in the Arab Republic of Egypt. Ethiopia and Sudan, the region’s 32 Africa’s Power Infrastructure Table 2.3 Power Exports by Region in Trade Expansion Scenario % Domestic EAPP/Nile % Domestic SAPP TWh demand basin TWh demand Congo, Ethiopia 26.2 –227 Dem. Rep. 51.9 –369 Sudan 13.1 –13 Mozambique 5.9 –33 Uganda 2.8 –61 Lesotho –0.7 68 Tanzania 2.4 –22 Malawi –1.5 56 Rwanda 1.0 –191 Zambia –1.8 1 Djibouti 0.0 0 Zimbabwe –3.5 17 Burundi –0.7 78 Namibia –3.8 2 Kenya –2.8 22 Botswana –4.3 93 Egypt, Arab Rep. –42.2 32 Angola –6.0 65 South Africa –36.4 10 % Domestic % Domestic WAPP TWh demand CAPP TWh demand Guinea 17.4 –564 Cameroon 6.7 –84 Nigeria 2.1 –3 Central African Côte d’Ivoire 0.9 –12 Republic 0.0 0 Gambia, The 0.1 –19 Equatorial Guinea –0.1 100 Guinea-Bissau –0.2 7 Gabon — 42 Mauritania –0.6 55 Chad –1.3 102 Benin –0.9 45 Congo, Rep. –4.4 4 Sierra Leone –0.9 60 Togo –0.9 48 Burkina Faso –1.0 5 Senegal –1.4 30 Niger –1.5 86 Liberia –1.7 89 Mali –1.9 79 Ghana –9.6 52 Source: Derived from Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool; TWh = terawatt-hour. — = Not available. major power exporters, send their power northward into Egypt (see figure 2.5). Exports exceed domestic consumption in both countries. Egypt and Kenya import significant volumes of power (between one-fifth and one-third), but Burundi is the only country to become overwhelm- ingly dependent on imports (about 80 percent). Under trade expansion, the share of hydropower in WAPP does not rise significantly. Nevertheless, cost-effective, larger-scale hydropower in The Promise of Regional Power Trade 33 Guinea replaces more dispersed hydropower projects in other countries throughout the region. Gas-fired power plants in Ghana, Benin, Togo, and Mauritania are also avoided—and are replaced by hydropower in Guinea, which emerges as the region’s major exporter and exports more than 5 times its domestic consumption. In CAPP, the share of hydropower increases from 83 percent to 97 per- cent. Cameroon emerges as the major power supplier in CAPP and exports about half of its production. Hydropower capacity in Cameroon replaces the heavy fuel oil (HFO) –fired thermal capacity in the other countries, in addition to some hydropower in the Republic of Congo. The other coun- tries in the region, except the Central African Republic, import a consider- able share of their consumption: Chad and Equatorial Guinea import all of their domestic consumption from Cameroon, and the Republic of Congo imports about one-third of its consumption and Gabon almost half. Although the benefits of regional power trade are clear, numerous challenges emerge. These are discussed in the remaining sections in this chapter. Water Resources Management and Hydropower Development Water resource management for hydropower is challenging for at least two reasons. First, it often requires multinational efforts and joint decision making by several countries. Many rivers with hydropower potential are international. Africa has 60 river basins that are shared by two or more countries, with the largest—the Nile basin—divided among 10 countries. Other important river basins also belong to several states. For example, nine countries share the Niger, eight share the Zambezi, and the Senegal runs through four neighboring states. The development of hydropower capacity therefore depends on the ability of the riparian countries to come to agree- ments based on joint long-term interests, starting with the location of dams. Second, hydropower must compete for water resources with other sources of demand: household consumption, irrigation, hydrological reg- ulation, and flood and drought management. Therefore, development of hydropower resources will require an established legal and regulatory framework to facilitate international cooperation and multisectoral management. Who Gains Most from Power Trade? Trade is responsible for the substantial differences in the LRMC of power among power pools (table 2.4). For example, in the trade expansion 34 Figure 2.5 Cross-Border Power Trading in Africa in Trade Expansion Scenario (TWh in 2015) (a) (b) EGYPT, ARAB REP. (c) (d) Source: Rosnes and Vennemo 2008. Note: TWh = terawatt-hour. 35 36 Table 2.4 Long-Term Marginal Costs of Power under Trade Expansion and Trade Stagnation $/Kwh a. SAPP b. EAPP/Nile Basin Trade expansion Trade stagnation Difference Trade expansion Trade stagnation Difference SAPP average 0.06 0.07 0.01 EAPP/Nile Basin average 0.12 0.12 0 Angola 0.06 0.11 0.05 Burundi 0.11 0.15 0.04 Botswana 0.06 0.06 0 Djibouti 0.07 0.07 0 Congo, Dem. Rep. 0.04 0.04 0 Egypt, Arab Rep. 0.09 0.09 0 Lesotho 0.06 0.07 0.01 Ethiopia 0.19* 0.16 –0.03 Malawi 0.05 0.05 0 Kenya 0.12 0.13 0.01 Mozambique 0.04 0.06 0.02 Rwanda 0.12 0.12 0 Namibia 0.11 0.12 0.01 Sudan 0.13 0.13 0 South Africa 0.06 0.07 0.01 Tanzania 0.10* 0.08 –0.02 Zambia 0.08 0.08 0 Uganda 0.12* 0.11 –0.01 Zimbabwe 0.08 0.09 0.01 c. WAPP d. CAPP Trade expansion Trade stagnation Difference Trade expansion Trade stagnation Difference WAPP average 0.18 0.19 0.01 CAPP average 0.07 0.09 0.02 Benin 0.19 0.19 0 Cameroon 0.07 0.06 –0.01 Burkina Faso 0.25 0.26 0.01 Central African Republic 0.11 0.11 0 Côte d’Ivoire 0.15 0.15 0 Chad 0.07 0.11 0.04 Gambia, The 0.08 0.07 –0.01 Ghana 0.10 0.10 0 Guinea 0.07 0.06 –0.01 Guinea-Bissau 0.09 0.16 0.07 Liberia 0.08 0.14 0.06 Mali 0.25 0.28 0.03 Mauritania 0.14 0.15 0.01 Niger 0.25 0.30 0.05 Nigeria 0.13 0.13 0 Senegal 0.43 0.47 0.04 Sierra Leone 0.09 0.10 0.01 Togo 0.10 0.11 0.01 Source: Derived from Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool; kWh = kilowatt-hour. 37 38 Africa’s Power Infrastructure scenario, the SAPP and CAPP regions have an estimated average LRMC of $0.07 per kWh, which is considerably lower than $0.12 per kWh and $0.18 per kWh for EAPP/Nile Basin and WAPP, respectively. The LRMC varies widely among countries within each power pool, although trade tends to narrow the range. Trade benefits two types of countries in particular. First, trade allows countries with very high domestic power costs to import significantly cheaper electricity. Perhaps the most striking examples are in WAPP, where Guinea-Bissau, Liberia, and Niger each can save up to $0.06–0.07 per kWh by importing electricity in the trade expansion scenario. Countries in other regions also benefit from substantial savings by importing—up to $0.04–0.05 in Angola in SAPP, Burundi in EAPP/Nile Basin, and Chad in CAPP. Overall savings can be large even for countries with lower unit cost differentials, such as South Africa. Other countries (such as Burundi, Ghana, Malawi, Sierra Leone, and Togo) in the trade expansion scenarios move from being self-reliant to importing heavily, generating savings for each kilowatt-hour that is imported. Second, expanded trade benefits countries with very low domestic power costs by providing them with the opportunity to generate sub- stantial export revenue. Those countries include Democratic Republic of Congo in SAPP, Ethiopia in EAPP/Nile Basin, Guinea in WAPP, and Cameroon in CAPP. Power export revenue under trade expansion is an estimated 6 percent of GDP in Ethiopia and 9 percent of GDP in the Democratic Republic of Congo. In reality, the parties will need to negotiate terms of trade that will determine the value of exports. How Will Less Hydropower Development Influence Trade Flows? In the trade expansion scenario, cheap hydropower from Guinea supplies much of the power in the WAPP region (although not in Nigeria). Realistically, however, it may not be feasible to develop such a huge amount of hydropower in one country and over such a short period. Therefore, in an alternative scenario, only three projects (totaling 375 MW) can be completed in Guinea within the next 10 years (compared with 4,300 MW in the trade expansion scenario). In this scenario, new trade patterns emerge in the WAPP region. Côte d’Ivoire emerges as the region’s major power exporter, and Ghana increases domestic production considerably to reduce net imports. Mauritania and Sierra Leone also become net exporters. Total annualized The Promise of Regional Power Trade 39 costs increase by about 3 percent—or just over $300 million—compared with the trade expansion scenario. At the same time, less hydropower is developed to replace thermal capacity, which leads to a huge tradeoff between capital costs and variable costs: Although capital costs are $500 million lower (mainly due to lower generation investments), variable operating costs are $850 million (30 percent) higher. In addition, the existing thermal plants that are used have lower efficiency and higher variable costs than new hydropower capacity. What Are the Environmental Impacts of Trading Power? Trade expansion offers potential environmental benefits. In the trade expansion scenario, the share of hydropower generation capacity in SAPP rises from 25 to 34 percent, reducing annual carbon dioxide emissions by about 40 million tons. Power production rises by 2.4 TWh in the EAPP/Nile Basin region, yet carbon dioxide emissions still fall by 20 million tons. Reduction in thermal capacity is smaller in WAPP and CAPP, and emissions savings are correspondingly lower: 5.2 and 3.6 million tons, respectively. The International Energy Agency recently estimated that emissions from power and heat production in Africa are 360 million tons. Under the trade expansion, carbon dioxide emissions fall by 70 million tons, or 20 percent of total emissions. These estimates do not, however, include greenhouse gas emissions from hydropower in the form of methane from dams. Technology Choices and the Clean Development Mechanism The Clean Development Mechanism (CDM) allows industrialized coun- tries that have made a commitment under the Kyoto protocol to reduce greenhouse gases to invest in projects that reduce emissions in develop- ing countries. The CDM facilitates financing to cover the difference in cost between a polluting technology and a cleaner but more expensive alternative. The cost of certified emission reduction credits (CERs) asso- ciated with a given project is calculated by dividing the difference in cost by the resulting reduction in emissions. Rosnes and Vennemo (2008) ana- lyze the potential for CDM in the power sector in SAPP under the trade- expansion scenario. Based on a CER price of $15 per ton of carbon dioxide, the CDM stimulates investments in the Democratic Republic of Congo, Malawi, 40 Africa’s Power Infrastructure Namibia, and Zambia and adds 8,000 MW (producing 42 TWh) of hydropower capacity. At the same CER price, the CDM has the potential to reduce carbon dioxide emissions in SAPP by 36 million tons, equivalent to 10 percent of the continent’s current emissions from power and heat production. Although significant, that is still less than the carbon reduction brought about by trade, which reduces emissions by 40 million tons in SAPP. Trade and CDM are not mutually exclusive, of course. Compared with trade stagnation, trade expansion combined with the CDM generates emissions reductions of 76 million tons. How Might Climate Change Affect Power Investment Patterns? Because unpredictable weather patterns reduce hydropower’s reliability, climate change could increase the costs of generating and delivering power in Africa. Rosnes and Vennemo (2008) therefore performed a sim- ulation to estimate the effect of climate change on costs in EAPP/Nile Basin. They assumed that climate change affects both existing and new capacity, reducing hydropower production (in gigawatt-hours per megawatt of installed capacity) by up to 25 percent. Lower firm power would increase the unit cost of hydropower, cause gradual substitution away from hydropower, and increase the total annu- alized cost of the power sector. In this scenario, a 25 percent reduction in firm hydropower availability would increase the annual costs of meeting power demand by a relatively low 9 percent. At the same time, however, reliance on thermal power would increase by 40 percent in EAPP/Nile Basin. In other words, climate change is a sort of positive feedback loop: Sustainable power becomes less reliable and therefore more expensive. It leads to increased reliance on thermal power, which exacerbates the cli- mate problem. Meeting the Challenges of Regional Integration of Infrastructure Increased regional power trade in Africa has clear benefits. Developing sufficiently integrated regional infrastructure, however, poses substantial political, institutional, economic, and financial challenges for policy mak- ers. The first step to meeting those challenges is to build political consen- sus among neighboring states that may have diverging national agendas or The Promise of Regional Power Trade 41 even recent histories of conflict. Thereafter, effective regional institutions will be needed to coordinate a cross-border infrastructure development program and ensure an equitable distribution of benefits. Power needs in the region are vast, but resources are limited. Policy makers will therefore need to set priorities to guide regional integration. Even with clear prior- ities, however, funding and implementing extensive project preparation studies and arranging cross-border finance for complex, multibillion- dollar projects present considerable difficulties. The efficacy of regional infrastructure will ultimately depend on countries to coordinate associ- ated regulatory and administrative procedures (box 2.1). Building Political Consensus Developing appropriate regional infrastructure is only one aspect of regional integration. Compared with economic or political integration, infrastructure integration has more clearly defined benefits and requires countries to cede less sovereignty. Regional infrastructure cooperation is therefore a good first step toward broader integration. Some countries have more to gain from regional integration than oth- ers. In particular, regional power trade benefits small countries with high power costs. As long as regional integration provides substantial economic advantages, however, it should be possible to design compensation mech- anisms that benefit all participating countries. Benefit sharing was pio- neered through international river basin treaties and has applications for integration of regional infrastructure. Any regional initiative requires national and international political consensus. Methods for building consensus vary, but broad principles apply. Improved advocacy. Africa will require improved high-level advocacy and leadership to promote regional integration for infrastructure develop- ment. Regional integration issues remain only a small part of parliamen- tary debate in most countries. The infrequency of regional meetings of heads of state contributes to a lack of follow-through. Governments and international institutions must therefore provide leadership. The African Union (AU) has the mandate to coordinate the regional integration pro- gram defined by the 1991 Abuja Treaty, which created the African Economic Community with regional economic communities as building blocks. The New Partnership for Africa’s Development (NEPAD) is the main vehicle for promoting regional integration but so far has not received sufficient support from political leaders to build consensus around financially and economically viable projects. The NEPAD Heads 42 Africa’s Power Infrastructure Box 2.1 The Difficulties in Forging Political Consensus: The Case of Westcor On October 22, 2004, the Energy Ministers of Angola, Botswana, the Democratic Republic of Congo, Namibia, and South Africa signed an Intergovernmental Memorandum of Understanding pledging cooperation on two projects: the establishment and development of the third phase of the Inga hydroelectric pro- gram in the Democratic Republic of Congo and the power export from there to the other four countries via a new Western Power Corridor transmission system. The chief executives of the five national utilities signed a similar memorandum of understanding among themselves. The Westcor company was established in September 2005 to take the project forward. It is registered in Botswana and has equal shareholdings by the five participating countries. Inga 3 was expected to deliver 3,500 MW. Additional hydroelectric plants in Angola and Namibia were also seen as possibilities. Inga is one of the most favor- able hydro sites in the world. It is situated in the rapids coursing around a U-shaped bend in the massive Congo River. By cutting through the peninsula, a run-of-river hydroelectric operation can be developed without the construction of massive storage dams. Inga 1 (354 MW) and Inga 2 (1424 MW) were built many years ago and are being rehabilitated. A prefeasibility study was completed that suggested potentially attractive power costs. A detailed design was originally scheduled for 2008–09. Despite intensive political lobbying within the African Union, New Partnership for Africa’s Development, Southern African Development Community, Southern African Power Pool, and development finance institutions, funds have yet to be commit- ted to conduct a full feasibility study. There are also considerable obstacles to the conclusion of regulatory, contractual, and financing agreements. In 2009, the government of the Democratic Republic of Congo announced that it was negotiating with BHP Billiton to assist in the development of Inga 3, including a large investment in an aluminum smelter that would be the main off- taker for the project. Westcor has subsequently closed its project office. In the absence of political consensus and meaningful commitment, the future of hydro- electric exports from Inga remains uncertain. Source: Interviews conducted by the authors with staff in the Africa Energy Department of the World Bank, 2009. The Promise of Regional Power Trade 43 of State Implementation Committee, established to remove political obstacles to projects, has not been effective and now meets less regularly than originally. A strong commitment from regional leaders is therefore essential to move projects forward. For example, when political differ- ences threatened to derail the West Africa Gas Pipeline, only the shuttle diplomacy of Nigeria’s President Obasanjo kept the project on track. Stronger trust. Trust is important for regional integration—especially when some countries stand to benefit more than others. Countries may be able to build that trust by collaborating on small, well-defined projects. For example, a bilateral agreement for a cross-border power transaction may be easier to conclude than a large regional investment that requires multicountry off-take agreements. Frequent interaction among policy makers at all levels of government builds relationships that help over- come inevitable disagreements. Finally, supranational organizations can serve as honest brokers for sharing gains and resolving disputes. Credible information. Trust is easier to build when information is shared equally. Decision makers require accurate data to gauge the full costs and benefits of regional infrastructure investments, many of which involve allocating substantial funds and sacrificing some degree of sovereignty. Regional economic communities are then responsible for building con- sensus by ensuring that all stakeholders are aware of the potential bene- fits of investments. Otherwise, countries are unlikely to be willing to bear the full cost of public goods. A realistic and accurate assessment of the likely benefits and costs of regional integration will therefore help to build trust among countries. Strengthening Regional Institutions Africa has many regional institutions, but most are ineffective. The archi- tecture supporting African integration comprises more than 30 institutions, including executive continental bodies, regional economic communities with overlapping membership, sectoral technical bodies, and national planning bodies. As a result, it is unclear who is responsible for strategy planning, project development, and financing. This has slowed the devel- opment of cohesive regional strategies, establishment of realistic priorities (such as regional infrastructure and trade integration), and design of tech- nical plans for specific projects. The AU Commission has struggled to fulfill its mandate because of a lack of human and financial resources. Africa’s regional economic com- munities have limited capabilities and resources and, above all, weak 44 Africa’s Power Infrastructure authority to enforce decisions. Institutions would be more effective if governments were willing to cede a measure of sovereignty in return for greater economic benefits. Greater use of qualified majority rules (which has been an issue of debate for some time in many regional economic communities, although without resolution) in some areas of policy mak- ing would streamline decision making. Furthermore, member states often fail to pay their assessed contributions in full, which constrains financing. Regional economic communities have multiple functions, and infrastruc- ture provision is not always at the forefront (ICA 2008). As a result, they often fail to attract and retain professional staff with the experience to identify and promote complex regional infrastructure projects. Regional special purpose entities or sectoral technical bodies—such as power pools—have been more effective than regional economic commu- nities. A power pool has a clear mandate, sufficient autonomy to execute its responsibilities, a dedicated funding mechanism, and career opportu- nities that attract and retain high-caliber staff. It also receives substantial capacity building. The members of a power pool are national electricity utilities, which similarly have clear functions and roles within their national contexts and are less susceptible to immediate political pressures than are less technical public agencies. Some power pools have been more proactive in promoting the development of their power sector. For example, WAPP appears to be taking initiative in promoting investment and assisting in the establish- ment of a regional electricity regulator (box 2.2). By contrast, SAPP, despite a longer history, seems more concerned with protecting the interests of its member national utilities than with facilitating the entry of private investment. National agencies are also in need of capacity building and streamlined decision making. For complex regional infrastructure projects, several line ministries from each country are often involved, which complicates con- sensus building and obscures responsibilities. High-level government offi- cials often fail to implement regional commitments. Setting Priorities for Regional Infrastructure The financial distress of many utilities in Africa has resulted in a substan- tial backlog of infrastructure investment. Authorities in Africa must there- fore set effective investment priorities, especially considering the limited fiscal space and borrowing ability of many governments. Because infra- structure has a long life, unwise investments can burden governments with an ineffective project that will also require costly maintenance. The Promise of Regional Power Trade 45 Box 2.2 The West African Power Pool (WAPP) and New Investment Unlike other power pools in Africa, WAPP is responsible for developing new infra- structure. The WAPP Articles of Association require WAPP to ensure “the full and effective implementation of the WAPP Priority Projects.” The WAPP Executive Board is responsible for developing a regional transmis- sion and generation master plan. Within the WAPP Secretariat, the Secretary Gen- eral negotiates directly with donors to finance feasibility studies for new projects and subsequently secures grant financing for feasible projects. WAPP has already obtained funding for feasibility studies from several donors, including the World Bank and U.S. Agency for International Development. WAPP often works with multilateral development banks to secure grant or credit financing for development projects. For example, grants and credits from the World Bank and KfW account for all funding of investments for the Coastal Transmission Backbone. In other cases, WAPP has created a special purpose vehi- cle that allows members to take equity stakes in projects, including a number of regional hydro generation projects. Source: Castalia Strategic Advisors 2009. Although our modeling has indicated clear overall benefits for expanded regional trade, many large regional projects are difficult to develop: Financing sums are large, policy and regulatory environments are diverse, and agreements have to be forged between affected stakeholders. Some observers may argue that it is easier to begin by developing smaller national projects that have lower financing requirements and less complex regula- tory and decision-making environments. However, these may be more costly in terms of power generated. Therefore, it still makes sense to priori- tize regional projects and first develop those that have the highest economic returns and still have a reasonable chance of reaching financial closure. For many years, regional power pools have been developing regional power plans with lists of possible projects. Yet they have struggled to agree on priorities: All members want their pet projects on the short list, and national utilities have also been protective of their market dominance (box 2.3). Suitable criteria for priority projects include predicted economic returns and scope for private participation. 46 Africa’s Power Infrastructure Box 2.3 Difficulties in Setting Priorities in SAPP In Southern Africa, energy ministers from the Southern African Development Community (SADC) asked the Southern African Power Pool (SAPP) to prepare a priority list for power projects in the region. SAPP, in turn, asked utilities to provide information on the power projects located in their area. By late 2005, SAPP had prepared a priority list based on seven weighted criteria: project size, leveled energy cost, transmission integration, economic impact, percentage of offtake committed, regional contribution, and number of participating countries. Proj- ects were divided into four categories: rehabilitation, transmission, short-term generation, and long-term generation. SAPP presented the priority list to SADC energy ministers, but they failed to reach an agreement. Individual ministers gen- erally favored projects located in their country, and inevitably some countries had a less significant presence on the list. SAPP then presented an amalgamated list of all possible power projects in the region at an investor conference in 2007. SAPP failed to demonstrate the necessity and viability of the projects, and as a result none of them received financing. Having twice failed to design an accept- able priority list, SAPP hired consultants to prepare a least-cost pool plan and pri- oritize projects. The recommendations were again controversial, and SAPP failed to achieve consensus on the priority list. With the region still in need of infrastructure investment, a group that included SADC, SAPP, Development Bank of Southern Africa, and RERA (the Regional Electric- ity Regulatory Authority of the Economic Community of West African States) asked consultants to prepare a list of short-term regional power projects that required financing. The focus of this list was on getting bankable projects, given that most utilities within SAPP cannot support the required investments on their balance sheet. The consultants sought projects that met four criteria: financial close within 24 months, least-cost rationale, regional impact, and environmental considera- tions. Developers and project sponsors presented the final list at an investor con- ference in mid-2009, but none of the projects has yet reached financial close. Source: Interviews conducted by the authors with staff in the Africa Energy Department of the World Bank, 2009. Economic returns. Projects with the highest returns may not always be new infrastructure. Strategic investments that improve the performance of existing infrastructure systems, such as installing power interconnec- tors between countries with large cost differentials, are often the most cost effective. The Promise of Regional Power Trade 47 Scope for private participation. The prospect of a larger regional market can attract more interest for private financing and public-private partner- ships, which provides a possible solution to the region’s substantial financing gaps. Encouraging private sector involvement requires govern- ment cooperation to facilitate investment. In fact, public control in many countries continues to stifle private investment. For many years, the membership of power pools, such as SAPP, was restricted to state-owned national utilities. The rules have changed, but independent power proj- ects still face many obstacles to gaining full membership in power pools. Priority-setting exercises are under way or planned. For example, a joint AU–African Development Bank study, the Program for Infrastructure Development in Africa, aims to develop a vision of regional infrastructure integration on the continent. The study will need to take account of other ongoing processes such as the Africa–European Union Energy Partnership, which is working to gain consensus on an electricity master plan for Africa. In addition, many regional economic communities and other tech- nical regional institutions have 10-year investment plans that provide many opportunities for external financiers. Priority setting depends on transparency in decision making and agree- ment on selection criteria. Decisions must be based on sufficiently detailed data and reasonable assumptions, and results should be publicly available. Small investments in better information at the country and regional levels will have significant benefits for decision making, espe- cially given the size of public and private funds at stake. Facilitating Project Preparation and Cross-Border Finance Project design is a complex process. The appraisal phase establishes social, economic, financial, technical, administrative, and environmental feasibil- ity (Leigland and Roberts 2007). For regional projects, coordination among national agencies with different procedures, capacity, and admin- istrative constraints adds to the complexity. As a result, the project prepa- ration costs for regional projects tend to be higher, and the process can take longer than for national projects. Preparation costs for regional projects are typically around 5 percent of total financing—approximately double the cost of preparing national projects. These costs are incurred when the success of the project and the likelihood of a sufficient return from the investment are still uncertain. Regional institutions and donors have tried to address these challenges and have established more than 20 project preparation facilities, many of which explicitly support regional activ- ities. Unfortunately, available project preparation resources do not 48 Africa’s Power Infrastructure match the regional needs. African countries need to commit more funds and people with the right technical, legal, and financial skills for infrastructure planning and project implementation. Timely execution of project preparation activities and a steady supply of new projects also encourage participation of the private sector. For operators relying on private financing, a firm planning horizon is therefore even more critical than for the public sector. Multilateral institutions have been developing specific mechanisms for funding regional projects. The World Bank has five criteria for regional projects to qualify for concessional funding from the International Devel- opment Association (IDA): At least three countries must participate, although they can enter at different stages; countries and the relevant regional entity must demonstrate strong commitment; economic and social benefits must spill over country boundaries; projects must include provisions for policy coordination among countries; and projects must be priorities within a well-developed and broadly supported regional strategy. A recent evaluation of World Bank regional integration projects concluded that regional programs have been effective (World Bank 2007). The African Development Bank adopted similar principles in 2008, although requiring only two countries to participate. To encourage greater country ownership, both institutions use a one-third, two-thirds principle, whereby participants are expected to use one IDA or African Development Fund credit from their country allocation, sup- plemented by two credits from regionally dedicated resources. Currently 17.5 percent of the African Development Fund and 15 percent of IDA resources in Africa are dedicated to regional programs. For projects to be eligible for financing from the European Union–Africa Infrastructure Trust Fund, they must be sustainable and have African ownership. They must also be cross-border projects or national projects with a regional impact on two or more countries. Regional projects funded by the Development Bank of Southern Africa must either involve a mini- mum of two countries or be located in a single country with benefits to the region. Small, poor countries with the potential to develop large hydro proj- ects supplying multiple countries face considerable obstacles in financing these projects. For example, the countries must sign secure power pur- chase agreements with large power loads to provide predictable revenue streams. Large, financially viable utilities; industrial customers in neigh- boring countries; or new adjacent energy-intensive investments, such as aluminum smelters, are potential sources for anchor loads, but they are The Promise of Regional Power Trade 49 not always available. The alternative is to combine multiple cross-border power off-take agreements, which will be challenging. Further challenges remain. Although recipients of funds from the African Development Fund and the IDA can leverage their country allocations by participating in regional projects, those receiving a small allocation may be reluctant to use a large percentage on one regional project with unclear benefits. How such concessional resources are allo- cated and whether enough of the overall allocation is dedicated to regional projects remain issues of debate. In addition, development finance institutions offer limited financing instruments for middle- income countries. This is problematic for projects involving Botswana and South Africa as well as North Africa, which could benefit from con- nectivity with countries south of the Sahara. IDA guidelines do not permit grants to regional organizations or supra- national projects. This limits the World Bank’s ability to provide capacity building for weak regional agencies. Some projects with significant regional spillovers—such as the Ethiopia-Sudan interconnector and a thermal power generation project in Uganda—may not involve three or more countries and therefore do not qualify for concessionary regional financing. Developing Regional Regulatory Frameworks Physical infrastructure will not produce economic growth on its own. To ensure its efficient use, the legal, regulatory, and administrative environment must be improved. Worldwide experience in developing power pools has led to consensus on three key building blocks for success: a common legal and regulatory framework, a durable framework for systems planning and operation, and an equitable commercial framework for energy exchanges. Political, regulatory, and physical barriers limit power trade—and therefore market size—throughout Africa. Regional power infrastructure requires coordinated power pricing, third-party access regulations, and effective cross-border trading contracts. The four power pools in Sub-Saharan Africa are at different stages of development. As countries move from bilateral to multilateral power exchanges, however, a commercially acceptable framework will be essen- tial. The WAPP was granted special status by the Economic Community of West African States (ECOWAS) in 2006 to reinforce its autonomy, and the 2007 ratification of an overarching Energy Protocol will help promote security for investors and open access to national transmission grids across the region. In 2008 the ECOWAS Regional Electricity Regulatory 50 Africa’s Power Infrastructure Authority was established to regulate cross-border electricity exchanges between member states. In Southern Africa, RERA has developed guidelines for cross-border power projects. These were formally noted by a Southern African Development Community (SADC) meeting of energy ministers in April 2010. RERA is now disseminating the guidelines among its member reg- ulatory agencies. Conclusion Cross-border trade in power has significant potential to lower costs and stimulate investment. In the short run, greater investments in cross- border transmission links will be needed to accommodate the higher vol- ume of trade, but those investments would be quickly repaid as countries gain access to cheaper power, particularly in Southern Africa. Although the overall savings in the annualized cost of the power sector under trade are relatively small (less than 10 percent), the gains for individual coun- tries may be substantial. Development finance institutions should con- sider accelerating investments in cross-border transmission links and large hydroelectric projects, which the private sector has found too risky because of their high capital costs, long payback periods, and risks related to the enforceability of power-purchase agreements. Note 1. Investment in the large Cahora Bassa hydroelectric plant in Mozambique was justified on the basis of exports of electricity to South Africa. Subsequently, South Africa had excess generation capacity that was made available for a new aluminum smelter built in the port city of Maputo. Bibliography AICD (Africa Infrastructure Country Diagnostic). 2008. AICD Power Sector Database. Washington, DC: World Bank. Castalia Strategic Advisors. 2009. “International Experience with Cross Border Power Trading. A Report to the ECOWAS Regional Electricity Regulatory Authority.” http://www.esmap.org/esmap/sites/esmap.org/files/P111483_ AFR_International%20Experience%20with%20Cross-Border%20Power% 20Trading_Hughes.pdf. Eberhard, Anton, Vivien Foster, Cecilia Briceño-Garmendia, Fatimata Ouedraogo, Daniel Camos, and Maria Shkaratan. 2008. “Underpowered: The State of the The Promise of Regional Power Trade 51 Power Sector in Sub-Saharan Africa.” Background Paper 6, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. ICA (Infrastructure Consortium for Africa). 2008. “Mapping of Donor and Government Capacity-Building Support to African RECs and Other Regional Bodies.” Report of Economic Consulting Associates to the Infrastructure Consortium for Africa, Tunis. Leigland, James, and Andrew Roberts. 2007. “The African Project Preparation Gap: Africans Address a Critical Limiting Factor in Infrastructure Investment.” PPIF Note, World Bank, Washington, DC. Rosnes, Orvika, and Haakon Vennemo. 2008. “Powering Up: Costing Power Infrastructure Spending Needs in Sub-Saharan Africa.” Background Paper 5, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. World Bank. 2007. The Development Potential of Regional Programs: An Evaluation of World Bank Support of Multicountry Operations. Washington, DC: World Bank, Independent Evaluation Group. CHAPTER 3 Investment Requirements Meeting Africa’s infrastructure needs will require substantial investment. Projections of future physical infrastructure requirements provide the basis for estimates of spending requirements in this chapter. In all cases, the spending estimates account for both growth-related and social demands for infrastructure and maintenance and rehabilitation costs. We assume that over a 10-year period the continent should be expected to redress its infrastructure backlog, keep pace with the demands of eco- nomic growth, and attain a number of key social targets for broader infra- structure access. In this chapter, potential generation projects in the Central, East/Nile Basin, Southern, and West African power pools (CAPP, EAPP/Nile Basin, SAPP, and WAPP, respectively) are identified and ranked according to cost effectiveness. Installed capacity will need to grow by more than 10 percent annually— or more than 7,000 megawatts (MW) a year—just to meet Africa’s sup- pressed demand, keep pace with projected economic growth, and provide additional capacity to support efforts to expand electrification. In the decade before 2005, expansion averaged barely 1 percent annually, or less than 1,000 MW per year. Most new capacity would be used to meet non- residential demands from the commercial and industrial sectors. 53 54 Africa’s Power Infrastructure Based on these assumptions, the overall costs for the power sector between 2005 and 2015 in Sub-Saharan Africa are a staggering $41 bil- lion a year—$27 billion for investment and $14 billion for operations and maintenance. Development of new generating capacity constitutes about half of investment costs, and rehabilitation of existing generation and transmission assets about 15 percent. SAPP alone accounts for about 40 percent of total costs. Modeling Investment Needs Nowhere in the world is the gap between available energy resources and access to electricity greater than in Sub-Saharan Africa. The region is rich in oil, gas, and hydropower potential, yet more than two-thirds of its pop- ulation lacks access to electricity. Coverage is especially low in rural areas. National authorities and international organizations have drawn up plans to increase access, but policy makers must make key decisions to under- pin these plans, such as how rapidly the continent can electrify, which mode of power generation is appropriate in each setting, and whether individual countries should move ahead independently or aim for coordi- nated development. They must also realistically assess the effect of major global trends, such as rising oil prices and looming climate change, their impact on decision making, and the sensitivity of power investment deci- sions to broader macroeconomic conditions. To inform decision making, Rosnes and Vennemo (2008), as part of the Africa Infrastructure Country Diagnostic study, developed a model to analyze the costs of expanding the power sector over the course of 10 years under different assumptions. The model simulates optimal (least cost) strategies for generating, transmitting, and distributing electricity in response to demand increases in each of 43 countries participating in the four power pools of Sub-Saharan Africa: the Southern African Power Pool, the East African/Nile Basin Power Pool,1 the West African Power Pool, and the Central African Power Pool.2 Cape Verde, Madagascar, and Mauritius are also included in our study as island states. Each power pool has dominant players. For example, South Africa accounts for 80 percent of overall power demand in SAPP, the Arab Republic of Egypt for 70 per- cent in EAPP/Nile Basin, Nigeria for two-thirds in WAPP, and the Republic of Congo and Cameroon for a combined 90 percent of power demand in CAPP. The cost estimates are based on projections of power demand over the 10 years between 2005 and 2015. Demand has three components: market Investment Requirements 55 demand associated with different levels of economic growth, structural change, and population growth; suppressed demand created by frequent blackouts and the ubiquitous power rationing; and social demand, which is based on political targets for increased access to electricity. In most low-income countries, notional demand exceeds supply.3 The difference between the two is suppressed demand, which arises for two primary reasons. First, people who are on a waiting list to get connected are not captured in baseline demand estimates. Second, frequent black- outs and brownouts reduce consumption but not notional demand. Ultimately, suppressed demand will immediately absorb a certain amount of new production even before taking account of income growth or struc- tural economic changes. In their model, Rosnes and Vennemo (2008) account for suppressed demand differently depending on its source. Waiting lists are a direct result of slow connection and expansion, and so they assume that social demand will include suppressed demand from this source in each sce- nario. Suppressed demand from blackouts, on the other hand, is estimated based on data for blackout duration and frequency from the World Bank’s enterprise surveys (table 3.1). They then adjust electricity demand in the base year (2005) accordingly. Social demand for electricity includes the expected demand of all new connections in the household sector in 2015 (table 3.2). Rosnes and Vennemo (2008) examine three scenarios for electricity access. In the constant access scenario, access rates remain at their 2005 level. Because of population growth, even the constant access scenario implies a number of new connections and therefore greater demand in kilowatt-hours (kWh). In the regional target access scenario, access rates increase by roughly one percentage point per year in each region—an ambitious but still realistic target. Finally, in the national targets scenario, access rates reflect targets set by national governments for urban and rural electricity access. Based on historic trends, demand is projected to grow at 5 percent per year in Sub-Saharan Africa and reach 680 terawatt-hours (TWh) by 2015. In all scenarios, market demand accounts for the great bulk of demand growth over the period. Estimating Supply Needs To estimate supply, the model simulates the least expensive way of meeting projected demand. Calculations are based on cost assumptions for various investments, including refurbishment of existing capacity 56 Africa’s Power Infrastructure Table 3.1 Blackout Data for Selected Countries Average Outages Suppressed Outages duration (hours per Down time demand in (days/year) (hours) year) (% of year) 2005 (GWh) Southern African Power Pool Angola 92 19.31 1,780.8 20.3 435 Congo, Dem. Rep. 182 3.63 659.2 7.5 351 South Africa 6 4.15 24.5 0.3 602 Zambia 40 5.48 219.9 2.5 157 East African/Nile Basin Power Pool Kenya 86 8.20 702.6 8.0 366 Tanzania 67 6.46 435.9 5.0 208 Uganda 71 6.55 463.8 5.3 84 Western African Power Pool Côte d’Ivoire 46 5.94 1,101 13 365 Ghana 61 12.59 1,465 17 979 Nigeria 46 5.94 1,101 64 10,803 Senegal 44 5.67 1,052 17 250 Sierra Leone 46 5.94 1,101 82 189 Central African Power Pool Cameroon 26 4.03 613 7.0 241 Congo, Rep. 39 4.33 924 10.6 616 Gabon 40 5.20 950 10.8 134 Source: Rosnes and Vennemo 2008. Note: GWh = gigawatt-hour. Table 3.2 Projected Market, Social, and Total Net Electricity Demand in Four African Regions TWh Annual Total net Market Social Total net average demand demand demand demand growth rate Region 2005 2015 2015 2015 (%) SAPP 258.8 383.0 14.0 397.0 4.4 EAPP/Nile Basin 100.6 144.8 24.2 169.0 5.3 WAPP 31.3 69.6 24.9 94.5 11.8 CAPP 10.7 17.0 3.0 20.0 6.7 Total 401.4 614.4 66.1 680.5 5.5 Source: Rosnes and Vennemo 2008. Note: Social demand is based on national connection targets. CAPP = Central African Power Pool; EAPP = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool; TWh = terawatt-hour. Investment Requirements 57 for electricity generation and construction of new capacity for cross- border electricity transmission. The model includes four modes of ther- mal generation—natural gas, coal, heavy fuel oil, and diesel—and four renewable generation technologies—large hydropower, mini-hydro, solar photovoltaic, and geothermal. Operation of existing nuclear capacity is also considered, although new investment is not. Initial supply is based on the existing generation capacity in the base year of 2005. Expansion is possible through investments in both new capacity and refurbishment of existing capacity to extend its life. The investment costs for each technology include both capital and variable operating costs (including fuel and maintenance). Expanding access will also require investment to extend and refurbish the transmission and dis- tribution (T&D) grid and enhance off-grid options; these will also require maintenance. The model can be run under a number of scenarios with varying assumptions to highlight the policy implications of each. As mentioned previously, for example, the feasibility of meeting three different electri- fication targets in each region is examined (table 3.3). A lower growth sce- nario assumes lower gross domestic product (GDP) growth. To assess the effect of trade on investment and operating costs, two trade scenarios were simulated. In the trade expansion scenario, trade will expand wher- ever it is worth the cost—that is, wherever the benefits of trade outweigh Table 3.3 Projected Generation Capacity in Sub-Saharan Africa in 2015 in Various Scenarios MW Low- growth Trade scenario stagnation National Trade expansion scenario scenario targets for Regional National National access Generation Constant target targets for targets for rates, trade capacity (MW) access rate access rate access rates access rates expansion Installed capacitya 43,906 43,906 43,906 43,906 43,906 Refurbished capacity 35,917 36,561 37,382 37,535 35,945 New capacity 74,366 77,953 81,722 70,425 65,723 Source: Adapted from Rosnes and Vennemo 2008. Note: MW = megawatt. a. “Installed capacity” refers to installed capacity as of 2005 that is not refurbished before 2015. Existing capacity that is refurbished before 2015 is included in the “refurbished capacity.” 58 Africa’s Power Infrastructure the costs of the additional infrastructure needed to support expanded trade. In another scenario—trade stagnation—no further investment in cross-border grids is made. The model has guidelines for endogenously determining trade flows, which can increase (in the trade expansion sce- narios) or even switch direction compared with the 2005 trade pattern. To meet national electrification targets in 2015 under the trade expan- sion scenario, the region will need about 82,000 MW of new generation capacity—almost equal to total capacity in 2005. Because many power installations in Africa are old, much of the capacity operating in 2005 will need to be refurbished before 2015. The 2005 capacity in SAPP was 48,000 MW. Approximately 28,000 MW of generation capacity will have to be refurbished by 2015. In addition, the region requires more than 33,000 MW of new generation capacity, an increase of about 70 percent over 2005 capacity. EAPP/Nile Basin has minimal refurbishment needs but requires 17,000 MW of new capacity— approximately equal to the region’s installed capacity in 2005. New capacity requirements in WAPP and CAPP are also significant: 18,000 MW in WAPP, or 180 percent of 2005 capacity, and 4,400 MW in CAPP, or 250 percent of 2005 capacity. More than half of 2005 capac- ity must be refurbished in both WAPP and CAPP—7,000 and 900 MW, respectively. Investment requirements are challenging in every region, although they are particularly large in WAPP and CAPP. Fortunately, however, the model’s projections indicate that economic growth will drive most of the growth in demand. Therefore, each region’s financial strength will grow to meet new investment needs as they arise. Table 3.4 provides a summary of new connections that will need to be made to meet national electrification targets by 2015 in the different regions. Overall Cost Requirements The overall costs for the power sector in Africa (including Egypt) between 2005 and 2015 (based on the trade expansion scenario and national targets for access rates) are an estimated $47.6 billion a year— $27.9 billion for investment and $19.7 billion for operations and mainte- nance (table 3.5). About half of the investment cost is for development of new generation capacity and another 15 percent for rehabilitation of existing generation and transmission assets. SAPP alone accounts for about 40 percent of costs. Investment Requirements 59 Table 3.4 New Household Connections to Meet National Electrification Targets, 2005–15 New household Pool connections (millions) CAPP 2.5 EAPP/Nile Basin 20.0 SAPP 12.2 WAPP 21.5 Island statesa 1.2 Total 57.4 Source: Adapted from Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool. a. Island states are Cape Verde, Madagascar, and Mauritius. Annualized capital investment costs (see box 3.1 for definitions of this and other cost categories) range from 2.2 percent of the region’s GDP under trade stagnation to 2.4 percent under trade expansion. Regional annualized capital investment costs under trade expansion exhibit consid- erable variation: 2 percent of GDP in SAPP, 2.8 percent in WAPP, 3.1 per- cent in EAPP/Nile Basin, and 1.8 percent in CAPP (table 3.6). The costs of operating the entire power system are of a similar order of magnitude. Annualized operating costs range from 1.7 percent of GDP under trade expansion to 2.1 percent under trade stagnation. The varia- tion among regions under trade expansion is even more pronounced here: 1.7 percent of GDP in SAPP, 2.6 percent in EAPP/Nile Basin, 1.4 percent in WAPP, and a negligible 0.2 percent in CAPP. Total annualized costs of system expansion and operation are, therefore, 4.2 percent of GDP under trade expansion and 4.4 percent under trade stagnation. The regional figures for SAPP and WAPP are similar: 3.7 percent and 4.2 percent, respectively, under trade expansion, and 3.9 percent and 4.4 percent under trade expansion. Total costs in EAPP/Nile Basin are higher: 5.7 percent and 6 percent of GDP under trade expansion and trade stagnation, respectively. They are lower in CAPP: 2 percent under trade expansion and 2.2 percent under trade stagnation. Around two- thirds of overall system costs are associated with generation infrastructure and the remaining one-third with T&D infrastructure. The overall cost of developing the power system appears high but not unattainable relative to the GDP of each of the trading regions. Among countries within each region, however, both GDP and power investment 60 Table 3.5 Required Spending for the Power Sector in Africa,a 2005–15 $ million Total operations Investment Pool Total expenditure and maintenance Total investment Rehabilitation New generation New T&D CAPP 1,386 159 1,227 76 860 292 EAPP/Nile Basin 15,004 6,807 8,198 485 5,378 3,334 SAPP 18,401 8,359 10,042 2,554 4,544 2,944 WAPP 12,287 4,049 8,238 1,010 3,527 3,701 Island statesb 556 311 245 15 74 156 Total 47,634 19,685 27,950 4,140 14,383 10,427 Source: Adapted from Rosnes and Vennemo 2008. Notes: Assuming national targets for access rates in the trade expansion scenario. CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool; T&D = transmission and distribution. a. Including the Arab Republic of Egypt. b. Island states are Cape Verde, Madagascar, and Mauritius. Investment Requirements 61 Box 3.1 Definitions Overnight investment costs. The total cost of expanding the power system to meet demand in 2015. This includes both new investment and refurbishment costs, but not variable costs. Annualized capital investment costs. The capital investment spending needed each year to meet demand in 2015, taking into account both the discount rate and the varying economic lifetimes of different investments. The formula is as follows: annualized capital cost = investment cost × r/[1–(1+r)–T], where r is the discount rate (assumed to be 12 percent) and T is the economic life- time of the power plant (assumed to be 40 years for hydropower plants, 30 years for coal plants, and 25 years for natural gas plants). The total annualized capital cost refers to both the cost of new generation capacity and the refurbishment of existing capacity, as well as investments in and refurbishment of T&D assets. Annual variable cost. The costs of fuel and variable costs of operation and main- tenance of the system. This includes both existing capacity in 2005 that will still be operational in 2015 and new capacity that will be developed before 2015. Total annualized cost of system expansion. Annualized capital investment costs plus annual variable costs for new capacity. Variable costs associated with opera- tion of existing capacity in 2005 (generation or transmission) are not included. Total annualized costs of system expansion and operation. Annualized capital investment costs plus total annual variable costs (for both existing capacity in 2005 and new capacity). Source: Rosnes and Vennemo 2008. requirements vary widely. As a result, in certain scenarios some countries face power spending requirements that are very burdensome relative to the size of their economies (figure 3.1). In SAPP, for example, investment requirements exceed 6 percent of GDP in the Democratic Republic of Congo, Mozambique, and Zimbabwe under both trade expansion and stagnation. Spending is similarly high in Egypt, Burundi, and Ethiopia in EAPP/Nile Basin. About half of the countries in WAPP have investment requirements of almost 10 percent of GDP—Guinea and Liberia stand 62 Table 3.6 Estimated Cost of Meeting Power Needs of Sub-Saharan Africa under Two Trade Scenarios Southern African East African/Nile Western African Central African Total Sub-Saharan Power Pool Basin Power Pool Power Pool Power Pool Africa Scenario ($billion) (% GDP) ($billion) (% GDP) ($billion) (% GDP) ($billion) (% GDP) ($billion) (% GDP) Trade expansion Total estimated cost 18.4 3.7 15.0 5.7 12.3 4.2 1.4 2.0 47.6 4.2 Capital costs 10.0 2.0 8.2 3.1 8.2 2.8 1.2 1.8 27.9 2.4 Operating costs 8.4 1.7 6.8 2.6 4.0 1.4 0.2 0.2 19.7 1.7 Generation 11.1 2.2 10.5 4.0 6.5 2.2 1.0 1.4 29.5 2.6 T&D 7.3 1.5 4.5 1.7 5.8 2.0 0.4 0.6 18.1 1.6 Trade stagnation Total estimated cost 19.5 3.9 16.0 6.0 12.7 4.4 1.5 2.2 50.3 4.4 Capital costs 10.0 2.0 6.3 2.4 8.0 2.7 1.1 1.6 25.6 2.2 Operating costs 9.4 1.9 9.7 3.7 4.8 1.6 0.4 0.6 24.7 2.2 Generation 12.6 2.5 11.6 4.4 7.1 2.4 1.2 1.7 32.8 2.9 T&D 6.9 1.4 4.4 1.7 5.7 1.9 0.3 0.5 17.5 1.5 Source: Rosnes and Vennemo 2008. Note: Assumes sufficient expansion to meet national electrification targets. Subtotals may not add to totals because of rounding. GDP = gross domestic product; T&D = transmission and distribution. 63 Bu rk percent GDP in 0 5 10 15 20 25 30 0 5 10 15 20 25 aF An as go o la Be ni Le n so M M th Gu aur ali Bo o ts in ita ea ni w -B a So an Source: Rosnes and Vennemo 2008. iss ut a h Ni au Af ge ric r a Cô N ia Na te ige m d’ r ib Iv ia oi Za r m Si Gh e bi er a ra na Co a Le ng M o o, al aw Ga ne m De i bi m Gu a M .R c. West African Power Pool in To oz ep . a. Southern African Power Pool ea g am -B o iss bi qu Se au ne Zi m e g ba Lib al bw er e Figure 3.1 Overall Power Spending by Country in Each Region ia trade expansion 0 1 2 3 4 5 6 7 8 0 5 10 15 20 25 Eq Rw ua an Gu tor da in ial ea Su da n Ga Dj bo ib n ou trade stagnation ti Ca Ug m an er da oo n Ta nz an ia Ch ad Eg Ke yp ny Ce t, a nt Ar ra ab l Re d. Central African Power Pool Re Afr p. pu ica bl n b. East African/Nile Basin Power Pool ic Bu ru Co nd ng i o, Et Re hi p. op ia 64 Africa’s Power Infrastructure out with requirements of almost 30 percent. In CAPP, only the Republic of Congo requires investments of more than 5 percent of GDP. The next sections explore investment requirements and costs in more detail for each region. More detailed output tables for each country can be found in appendix 3 at the end of this book. The SAPP Table 3.7 provides an overview of generation capacity and the capacity mix in SAPP in all scenarios in 2015. The rest of this section provides a description of three trade expansion scenarios. Constant Access Rates under Trade Expansion In this scenario, SAPP will require almost 31,300 MW of new capacity to meet demand under trade expansion in 2015. An additional 28,000 MW of existing capacity will need to be refurbished.4 South Africa accounts for about 80 percent of electricity demand in SAPP. As a result, development there has a strong effect on the rest of the region. Investments in new generation capacity in South Africa amount to Table 3.7 Generation Capacity and Capacity Mix in SAPP, 2015 Low- growth Trade scenario stagnation National Trade expansion scenario scenario targets for Regional National National access Constant target targets for targets for rates, trade access rate access rate access rates access rates expansion Generation capacity (MW) Installed 17,136 17,136 17,136 17,136 17,136 Refurbishment 28,029 28,035 28,046 28,148 28,046 New investments 31,297 32,168 33,319 32,013 20,729 Generation capacity mix (%) Hydro 33 33 34 25 40 Coal 60 60 59 66 52 Gas 0 0 0 2 0 Other 7 7 7 7 8 Source: Rosnes and Vennemo 2008. Note: “Installed capacity” refers to installed capacity as of 2005 that is not refurbished before 2015. Existing capacity that is refurbished before 2015 is included in the definition of “refurbished capacity.” SAPP = Southern African Power Pool; MW = megawatt. Investment Requirements 65 18,700 MW (60 percent of the region’s total). In addition, 21,700 MW of capacity is refurbished. Coal-fired power plants account for the largest share of capacity investments in South Africa. Open-cycle gas turbine generators5 account for another 3,000 MW, and hydropower and pumped storage for 2,000 MW. Elsewhere in SAPP, countries that are rich in hydropower develop substantial new capacity: 7,200 MW in the Democratic Republic of Congo, 3,200 MW in Mozambique, and 2,200 MW in Zimbabwe. In 2005, Zimbabwe imported 14 percent of its electricity, and the new capacity allows the country to meet domestic demand. The Democratic Republic of Congo and Mozambique, on the other hand, export 50 and 6 TWh, respectively, to the rest of the region. The investment cost of expanding the generation system in SAPP is almost $38 billion (table 3.8). Investments in new capacity account for $30.3 billion, and refurbishment costs account for $7.5 billion. In general, refurbishment is much cheaper than developing new capacity. Therefore, Table 3.8 Overnight Investment Costs in SAPP, 2005–15 $ million Low- Trade growth stagnation scenario Trade expansion scenario scenario National National National targets for Regional targets for targets for access Constant target access access rates, trade access rate access rate rates rates expansion Generation Investment cost 30,277 31,103 32,242 34,644 18,589 Refurbishment cost 7,572 7,574 7,577 7,587 7,577 T&D Investment cost 16,384 19,422 23,711 20,653 16,606 Cross-border transmission lines 3,009 2,991 3,058 0 3,082 Distribution grid 12,674 12,674 12,674 12,674 5,544 Connection cost (urban) 643 2,210 3,995 3,995 3,995 Connection cost (rural) 58 1,547 3,985 3,985 3,985 Refurbishment cost 9,775 9,775 9,775 9,775 9,775 Total 64,008 67,874 73,304 72,659 52,546 Source: Rosnes and Vennemo 2008. Note: SAPP = Southern African Power Pool; T&D = transmission and distribution. 66 Africa’s Power Infrastructure despite the large funding gap between the two, refurbishment and new investment make roughly the same contributions (in MW) to new capac- ity. Coal power plants in South Africa are an exception: Refurbishing them is almost as expensive as investing in new plants. The additional costs necessary to bring power from power plants to consumers—the costs of T&D and connection—are also substantial: Investments to expand and refurbish the grid total $16 billion (see table 3.8). The direct cost of connecting new customers to the grid is only $0.7 billion, more than 90 percent of which would be spent in urban areas. Total overnight investment costs are therefore slightly more than $64 billion. Annualized capital costs are $8.8 billion, including $5.6 billion in generation and $3.2 billion in T&D and connection. Annual variable operating costs (including fuel, operation, and maintenance) are $8.3 billion. Operation of new power plants accounts for approxi- mately $2 billion, and operation of existing and refurbished power plants ($3.2 billion) and the grid ($3.1 billion) accounts for the remain- ing costs. The total annualized cost of system expansion is 2.2 percent of the region’s GDP in 2015, and the total annualized cost of system expansion and operation is 3.4 percent. Costs vary widely among countries. The costs of generation-capacity expansion are particularly high in countries with large hydropower development: 5.8 percent of GDP in the Democratic Republic of Congo, 6.2 percent in Mozambique, and 8.5 percent in Zimbabwe. Grid-related costs (investments, refurbishment, and operation) are high in countries such as Zimbabwe, Zambia, Namibia, and the Democratic Republic of Congo. Finally, although the costs of genera- tion-capacity expansion are only 0.7 percent of GDP in 2015 in South Africa, the annual variable costs of the new coal-fired power plants are 0.6 percent of GDP. Regional Target for Access Rate: Electricity Access of 35 Percent on Average Compared with the constant access rate, meeting the average regional target for electricity access (35 percent) requires an additional investment of almost $3.9 billion, or about $0.5 billion in annualized capital costs. The cost of connecting new households accounts for the majority of the additional costs—about $3 billion, or $380 million in annualized costs. Rural areas account for about 40 percent of connection costs, compared with only 10 percent in the constant access rate scenario. Investment Requirements 67 The region also requires additional generation capacity to meet increased demand. Investment costs are $0.8 billion higher ($120 million in annualized costs) compared with the constant access rate scenario. The additional costs of operating the system (variable costs) are much lower— $50 million annually. Overall, the annualized cost of system expansion is 2.3 percent of the region’s GDP in 2015. When variable costs of existing capacity are included, the total annualized cost of system expansion and operation rises to 3.6 percent of GDP. National Targets for Electricity Access Compared with the constant access rate scenario, meeting national targets requires an additional investment of $9.3 billion, or almost $1.3 billion in annualized costs. The largest contributors to this increase are the costs of T&D and connection. For example, connecting new households to the grid accounts for about $7.3 billion ($0.9 billion in annualized costs) of the additional costs. The additional costs of investment in generation capacity are $2 billion higher ($280 million in annualized costs). Variable costs of operating the system are only $75 million higher each year. The annualized cost of system expansion is 2.4 percent of the region’s GDP in 2015. When variable costs of existing capacity are included, the total annu- alized costs of system expansion and operation rise to 3.7 percent of GDP. The EAPP/Nile Basin Table 3.9 provides an overview of generation capacity and the capacity mix in EAPP/Nile Basin in 2015 in all scenarios. The rest of this section provides a description of three trade expansion scenarios. Constant Access Rates under Trade Expansion In this scenario, EAPP/Nile Basin will require 23,000 MW of new capac- ity to accommodate market demand growth in 2015. In addition, more than 1,000 MW of existing capacity must be refurbished. This estimate is based on information about the age of facilities and conditions assembled for this study. Therefore, the need for refurbishment in EAPP/Nile Basin— which is much lower than in SAPP—may have been underestimated. Egypt imports about 40 percent of its electricity (55 TWh) and accounts for approximately 80 percent of total demand in the EAPP/Nile Basin. As a result, development there is of considerable importance for the rest of the region. Natural gas–fired power plants account for almost 7,000 MW of new capacity in Egypt. Elsewhere in EAPP/Nile Basin, 68 Africa’s Power Infrastructure Table 3.9 Generation Capacity and Capacity Mix in EAPP/Nile Basin, 2015 Low-growth Trade scenario stagnation National Trade expansion scenario scenario targets for Regional National National access rates, Constant target targets for targets for trade access rate access rate access rates access rates expansion Generation capacity (MW) Installed 22,132 22,132 22,132 22,132 22,132 Refurbishment 1,369 1,375 1,375 1,381 1,375 New investments 23,045 24,639 25,637 17,972 23,540 Generation capacity mix (%) Hydro 49 47 48 28 48 Coal 2 2 2 3 2 Gas 47 48 49 64 45 Other 2 3 4 5 4 Source: Rosnes and Vennemo 2008. Note: “Installed capacity” in this table refers to capacity in place in 2005 but not refurbished before 2015. Existing capacity that is refurbished before 2015 is included not in the installed capacity figure, but in the refurbishment figure. Data include Egypt. EAPP/Nile Basin = East African/Nile Basin Power Pool; MW = megawatt. countries with hydropower resources develop substantial new capacity: 8,150 MW in Ethiopia, 3,700 MW in Sudan, 1,200 MW each in Tanzania and Uganda, and 300 MW in Rwanda. In addition, Kenya and Tanzania invest in some coal-fired power plants, and Ethiopia and Sudan become large net exporters. To meet projected demand, generation capacity in 2015 must be more than twice the 2005 level. Expanding the generation system over 10 years will cost more than $29 billion (see table 3.10). Investments in new capacity accounts for almost all of this, and refurbishment costs are negligible. The costs of T&D and connection total $11 billion, of which investments in the grid account for $7.5 billion. The cost of connecting new customers is $3 billion, or 40 percent of the total grid investment. Rural areas account for 80 percent of connection costs. Refurbishment of the existing grid requires $3.3 billion. Total overnight investment costs in EAPP/Nile Basin are $40.2 billion. Annualized capital costs are, therefore, approximately $5.3 billion: $4 bil- lion for generation capacity and $1.3 billion for T&D and connection. The annual variable costs of operating the system amount to $5.84 billion. Operation of new power plants accounts for most of this ($4.39 billion), Investment Requirements 69 Table 3.10 Overnight Investment Costs in the EAPP/Nile Basin, 2015 $ million Low-growth Trade scenario stagnation National Trade expansion scenario scenario targets for Regional National National access rates, Constant target targets for targets for trade access rate access rate access rates access rates expansion Generation Investment cost 28,913 30,802 32,667 18,621 31,275 Refurbishment cost 396 398 398 399 398 T&D Investment cost 7,549 16,430 27,385 26,372 26,301 Cross-border transmission lines 1,320 937 1,013 0 964 Distribution grid 3,072 3,072 3,072 3,072 2,037 Connection cost (urban) 2,484 5,263 5,702 5,702 5,702 Connection cost (rural) 674 7,159 17,599 17,599 17,599 Refurbishment cost 3,342 3,342 3,342 3,342 3,342 Total 40,200 50,973 63,793 48,735 61,317 Source: Rosnes and Vennemo 2008. Note: Data include Egypt. EAPP/Nile Basin = East African/Nile Basin Power Pool; T&D = transmission and distribution. and operation of existing and refurbished power plants ($0.69 billion) and the grid ($0.76 billion) account for the rest. The total annualized cost of system expansion is therefore 3.6 percent of the region’s GDP in 2015. Adding the variable costs of system operation, the total annualized cost of system expansion and operation is 4.2 percent of GDP. The cost of system expansion in Egypt—the largest country in the region—is 3.8 percent of its GDP. Capital costs are only 0.9 percent, but because the new capacity is gas fired, fuel costs are 3 percent of GDP. Total annualized costs in Ethiopia are 9.2 percent of its GDP in total—the highest figure in the region. However, investments in gener- ation capacity used for exports account for two-thirds of these costs. Investments in T&D lines and variable costs account for the rest. Costs are particularly low in Burundi and Djibouti—between 1 percent and 2 percent of GDP. In other countries in the region, costs are 2.5–3.5 percent of GDP. 70 Africa’s Power Infrastructure Regional Target for Access Rate: Electricity Access of 35 Percent on Average Compared with the constant access rate scenario, meeting the interna- tional target for electricity access (35 percent on average) requires an additional investment of almost $11 billion, or about $1.3 billion in annu- alized capital costs. Connecting new households to the grid accounts for the majority of additional costs—$9 billion ($1.1 billion in annualized costs). Rural areas account for 60 percent of the connection costs. The region also requires additional generation capacity to meet increased demand. As a result, investment costs are $2 billion higher ($270 million in annualized costs) than in the constant access rate scenario. Variable costs of operating the system are also $700 million higher annually. Overall, the total annualized cost of system expansion and operation increases to 5 percent of GDP in 2015. Because the costs of operating the existing system are only 0.5 percent of GDP, the total annualized cost of expanding the system amounts to 4.4 percent of GDP. National Targets for Electricity Access Meeting national targets requires $24 billion more in investment compared with the constant access rate scenario, or approximately $3 billion in annu- alized capital costs. The largest contributors to the increase are the costs of T&D and connection. Connecting new households to the grid accounts for $20 billion ($2.4 billion annualized costs) of the additional costs. Rural areas account for 75 percent of connection costs. The additional costs of investment in generation capacity are $3.8 billion ($520 million in annual- ized costs), and the variable costs of operating the system are $1 billion higher than in the constant access rate scenario. In the national targets sce- nario, the total annualized cost of system expansion and operation is 5.7 percent of the region’s GDP. Excluding the costs of operating the exist- ing system, the total annualized cost of system expansion is 5.1 percent. WAPP Table 3.11 provides an overview of generation capacity and the capacity mix in WAPP for all scenarios in the region in 2015. The rest of this sec- tion provides a description of three trade expansion scenarios. Constant Access Rates under Trade Expansion In this scenario, WAPP requires almost 16,000 MW of new capacity to meet market demand growth in 2015. Almost all of this is hydropower: 10,290 MW in Nigeria, 4,290 MW in Guinea, 1,000 MW in Ghana, and Investment Requirements 71 Table 3.11 Generation Capacity and Capacity Mix in WAPP, 2015 Low-growth Trade scenario stagnationNational Trade expansion scenario scenariotargets for Regional National National access rates, Constant target targets for targets for trade access rate access rate access rates access rates expansion Generation capacity (MW) Installed 4,096 4,096 4,096 4,096 4,096 Refurbishment 5,530 6,162 6,972 6,842 5,535 New investments 15,979 16,634 18,003 16,239 17,186 Generation capacity mix (%) Hydro 82 79 77 73 80 Coal 1 1 1 1 1 Gas 13 14 16 19 12 Other 4 5 6 7 7 Source: Rosnes and Vennemo 2008. Note: “Installed capacity” refers to installed capacity as of 2005 that is not refurbished before 2015. Existing capacity that is refurbished before 2015 is included in the “refurbished capacity.” WAPP = West African Power Pool; MW = megawatt. 130 MW in Côte d’Ivoire. This means that the available hydropower resources become fully exploited6 in Nigeria, Guinea, and Ghana.7 One coal-fired power plant (250 MW) is also built in Senegal, and some off- grid technologies are built in rural areas.8 In addition to investments in new generation capacity, 5,530 MW of existing capacity is refur- bished: almost 4,000 MW of hydropower (2,850 in Nigeria), 1,200 MW of natural gas–fired power in Nigeria, and 410 MW of heavy fuel oil (HFO) –fueled thermal power plants in various countries. Nigeria accounts for two-thirds of electricity consumption in the region. Hence, developments in Nigeria that influence electricity demand (such as economic development and the politically determined electric- ity access targets) have a large impact on the total cost of electricity sector development in the rest of the region. However, Nigeria does not have a big impact on the trade patterns and resource development in the rest of the region for two reasons. First, Nigeria is not centrally situated and would require large investments in transmission lines to allow for large exports. Second, Nigeria uses its large and relatively cheap hydropower resources to meet domestic demand growth. The ample gas resources that could be used to develop gas-fired power plants are more expensive than hydropower in other countries. 72 Africa’s Power Infrastructure Ghana accounts for 15 percent and Côte d’Ivoire accounts for 6 percent of the region’s demand. In contrast with Nigeria, these countries import about half of their electricity. Guinea accounts for almost 20 percent of the region’s production and exports more than eight times its domestic demand (mostly competitively priced hydro power). The investment cost of expanding the generation system in WAPP is slightly more than $23.3 billion (table 3.11). Investments in new capacity account for the majority of this ($22 billion), but the cost of refurbish- ment is only $1.4 billion. The costs of T&D and connection are almost equal to the costs of new generation capacity: $23.3 billion for investments to expand and refur- bish the grid (table 3.12). Investments in new T&D lines account for more than $17 billion of this. Only 6 percent of this last figure is related to international transmission lines. The direct cost of connecting new cus- tomers to the grid is $4.3 billion, or less than 20 percent of the total grid cost. Rural areas account for 86 percent of this total. Table 3.12 Overnight Investment Costs in WAPP, 2005–15 $ million Low- Trade growth stagnation scenario Trade expansion scenario scenario National National National targets for Regional targets for targets for access Constant target access access rates, trade access rate access rate rates rates expansion Generation Investment cost 21,955 23,632 26,992 25,822 25,128 Refurbishment cost 1,363 1,429 1,511 1,496 1,366 T&D Investment cost 17,241 22,399 29,813 28,872 23,206 Cross-border transmission lines 1,022 968 941 0 912 Distribution grid 11,909 11,909 11,909 11,909 5,332 Connection cost (urban) 3,698 5,254 7,634 7,634 7,634 Connection cost (rural) 612 4,268 9,329 9,329 9,329 Refurbishment cost 6,057 6,057 6,057 6,057 6,057 Total 46,615 53,518 64,373 62,247 55,758 Source: Rosnes and Vennemo 2008. Note: WAPP = West African Power Pool; T&D = transmission and distribution. Investment Requirements 73 Total overnight investment costs are $46.6 billion in this scenario. The annualized capital cost of meeting market demand in 2015 is $6 billion: almost $3 billion in T&D and connection and $3.1 billion in generation. The annual variable operating costs are $3.2 billion. About half of this is related to operating new power plants, and the other half is related to operating existing and refurbished power plants ($0.3 billion) and the grid ($1.3 billion). The total annualized cost of system expansion is there- fore equivalent to 2.1 percent of the region’s GDP in 2015. Adding the variable operation costs of existing capacity, the total annualized cost of system expansion and operation is 3.2 percent of GDP. Investment patterns, and therefore costs, vary widely among countries in the region. For example, Guinea invests in hydropower for export pur- poses, and the total investment costs are 20 percent of GDP. In The Gambia, variable fuel costs of existing HFO-fueled capacity are 4.5 per- cent of GDP, and the grid cost makes up another 1 percent of GDP. In Senegal, both the grid-related cost (investment and variable) and variable generation cost contribute to raising the total cost to 7 percent of GDP. Regional Target Rate: Electricity Access of 54 Percent on Average Compared with the constant access rate scenario, meeting the regional target for electricity access (54 percent on average) requires additional investment of almost $7 billion, or about $1.25 billion in annualized capital costs. Connecting new households to the grid accounts for the majority of additional costs—more than $5 billion ($600 million in annu- alized costs). Almost half of this amount is spent in rural areas. The region also requires additional generation capacity to meet increased demand: Investment costs are $1.7 billion higher ($200 million in annualized costs) than in the constant access rate scenario. Variable operating costs are 12 percent higher (almost $400 million annually) because part of the new generation capacity is supplied by fossil fuels (diesel in rural areas and refurbishment of gas-fired power plants in Nigeria). The total annu- alized cost of system expansion is 2.4 percent of the region’s GDP in 2015. Including variable costs of existing capacity lifts the total annual- ized cost of system expansion and operation to 3.6 percent of GDP. National Targets for Electricity Access Compared with the constant access rate scenario, meeting national targets requires an additional investment of $18 billion, or approximately $3 bil- lion in annualized costs. The largest contributors to this increase are the costs of T&D and connection. For example, connecting new households 74 Africa’s Power Infrastructure to the grid involves an extra investment of $12.5 billion ($1.6 billion in annualized costs). Rural areas account for more than half of connections. The region also requires additional investment in generation capacity to meet increased demand: Investment costs are more than $5 billion higher ($650 million in annualized costs). The variable operating costs are $850 million annually. The total annualized cost of system expansion is 2.9 per- cent of the region’s GDP in 2015. When variable costs of existing capac- ity are included, the total annualized costs of system expansion and operation rise to 4.2 percent of GDP. CAPP Table 3.13 provides an overview of generation capacity and the capacity mix in CAPP for all scenarios. The rest of this section provides a descrip- tion of three trade expansion scenarios. Constant Access Rates under Trade Expansion CAPP requires 3,856 MW of new capacity to meet market demand growth in 2015. All of this is hydropower:9 2,430 MW in Cameroon, 1,318 MW in the Republic of Congo, 84 MW in Gabon, and 24 MW in the Central African Republic. This means that the available hydropower Table 3.13 Generation Capacity and Capacity Mix in CAPP, 2015 Low-growth Trade scenario stagnation National Trade expansion scenario scenario targets for Regional National National access rates, Constant target targets for targets for trade access rate access rate access rates access rates expansion Generation capacity (MW) Installed 260 260 260 260 260 Refurbishment 906 906 906 1,081 906 New investments 3,856 4,143 4,395 3,833 3,915 Generation capacity mix (%) Hydro 97 97 97 83 97 Coal 0 0 0 0 0 Gas 0 0 0 0 0 Other 2 3 3 17 3 Source: Rosnes and Vennemo 2008. Note: “Installed capacity” refers to installed capacity as of 2005 that is not refurbished before 2015. Existing capacity that is refurbished before 2015 is included in the “refurbished capacity.” CAPP = Central African Power Pool; MW = megawatt. Investment Requirements 75 resources are fully exploited in Cameroon.10 In addition, more than 900 MW of existing capacity must be refurbished. Cameroon accounts for 600 MW of refurbished capacity, and Gabon, the Republic of Congo, and the Central African Republic account for the rest. The Republic of Congo accounts for more than one-half (54 percent) of electricity demand in CAPP in 2015, and Cameroon accounts for one- third. Therefore, the development of these two countries has a strong effect on the rest of the region. Gabon has 10 percent of the region’s total demand, but the other countries have minimal electricity demand. Cameroon accounts for 64 percent of total electricity production in the region in 2015, and the Republic of Congo accounts for only 29 per- cent. Cameroon exports more than one-third of its production (5.6 TWh) to the Republic of Congo and exports small amounts to Gabon, Chad, and Equatorial Guinea. It is assumed that imports from the Democratic Republic of Congo to the Republic of Congo remain at their 2005 levels, but this is a small volume (less than 0.5 TWh per year). The investment cost of expanding the generation system in CAPP is almost $6 billion (table 3.14). Investments in new capacity account for Table 3.14 Overnight Investment Costs in CAPP, 2005–15 $ million Low- Trade growth stagnation scenario Trade expansion scenario scenario National National National targets for Regional targets for targets for access Constant target access access rates, trade access rate access rate rates rates expansion Generation Investment cost 5,645 6,157 6,615 5,981 5,766 Refurbishment cost 272 272 272 301 272 T&D Investment cost 1,057 1,648 2,348 2,036 2,311 Cross-border 349 317 312 0 355 Distribution grid 286 286 286 286 205 Connection cost (urban) 412 753 1,010 1,010 1,010 Connection cost (rural) 10 292 740 740 740 Refurbishment cost 222 222 222 222 222 Total 7,196 8,299 9,457 8,540 8,570 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; T&D = transmission and distribution. 76 Africa’s Power Infrastructure the majority of this ($5.6 billion), while the cost of refurbishment is only $0.3 billion. The costs of T&D and connection are much lower than the costs of building new power plants and account for less than 20 percent of total investment costs. The costs of expanding and refurbishing the grid are $1.3 billion, most of which (over $1 billion) is investment in new T&D lines. A third of this last figure is related to international transmis- sion lines. The direct cost of connecting new customers to the grid is 40 percent of the total grid investment cost, or $0.4 billion. Urban areas account for 98 percent of connection costs. Total overnight investment costs in CAPP in the constant access rate scenario are slightly more than $7 billion. The annualized capital cost of meeting market demand through 2015 is therefore almost $1 billion: $780 million in generation and almost $160 million in T&D and connec- tion. Annual variable operating costs amount to $150 million, about $50 million of which is related to operating new power plants. The rest is related to operating existing and refurbished power plants ($30 million) and the grid ($70 million). The total annualized cost of system expansion is about $1 billion, equivalent to 1.4 percent of the region’s GDP in 2015. Adding the variable operation costs of existing capacity, the total annual- ized cost of system expansion and operation is 1.6 percent of GDP. Investment patterns and costs vary widely among countries in the region. In particular, the costs of expanding generation are high in coun- tries with relatively large hydropower development: 3 percent of GDP in the Republic of Congo and 1.6 percent in Cameroon. The Republic of Congo also imports a substantial amount of electricity. Grid-related costs (including investments, refurbishment, and operation) account for another 0.3 percent of GDP in the Republic of Congo, mainly because new cross-border lines need to be built to make the large imports possi- ble. Grid-related costs are 0.3 percent of GDP in Cameroon as well. This is mainly due to connecting new customers to the grid, in addition to investments in the domestic and cross-border grids. Finally, Chad and Equatorial Guinea do not invest in any new generation capacity. Their costs are related to grid expansion, maintenance, and new connection, which are relatively inexpensive. Regional Target for Access Rate: Electricity Access of 44 Percent on Average Compared with the constant access rate scenario, meeting the interna- tional target for electricity access (44 percent on average) requires an additional investment of $1.1 billion, or about $140 million in annualized capital costs. Connecting new households to the grid accounts for about Investment Requirements 77 $0.6 billion ($80 million annually) of total additional costs. Almost 30 percent of the total connection costs are spent in rural areas, compared with only 2 percent in the constant access rate scenario. The region also requires additional generation capacity to meet increased demand: Investment costs are $0.5 billion higher ($66 million in annualized costs) than in the constant access rate scenario. Variable operating costs are slightly higher because some of the new generation capacity in rural areas is based on off-grid diesel generators (there is also some mini-hydro and solar photovoltaic in the rural areas). The total annualized cost of system expansion is therefore 1.6 percent of the region’s GDP in 2015. Including variable costs of existing capacity lifts the total annualized cost of system expansion and operation to 1.8 percent of GDP. National Targets for Electricity Access Meeting national targets requires $2.3 billion more in investment than keeping the access rate constant at current levels. This corresponds to $300 million in annualized costs. The largest contributors to this increase are the costs of T&D and connection. For example, connecting new households to the grid involves an extra cost of about $1.3 billion ($165 million in annualized costs). More than 40 percent of the total costs of new connections are spent in rural areas, compared with only 2 percent in the constant access rate scenario. The region also requires additional generation capacity to meet demand: Investment costs are almost $1 bil- lion higher ($126 million in annualized costs). The total annualized cost of system expansion is therefore 1.8 percent of GDP in 2015. Including the variable operating costs of existing capacity increases the total annu- alized cost of system expansion and operation to 2 percent of GDP. Notes 1. Data for Sub-Saharan Africa exclude Egypt. 2. The membership of the power pool is as follows: SAPP: Angola, Botswana, the Democratic Republic of Congo, Lesotho, Malawi, Mozambique, Namibia, South Africa, Zambia, and Zimbabwe. EAPP: Burundi, Djibouti, Egypt, Ethiopia, Kenya, Rwanda, Sudan, Tanzania, and Uganda. WAPP: Benin, Burkina Faso, Côte d’Ivoire, The Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Senegal, Sierra Leone, and Togo. CAPP: Cameroon, the Central African Republic, Chad, the Republic of Congo, Equatorial Guinea, and Gabon. 3. Notional demand refers to the aggregate quantity of goods and services that would be demanded if all markets were in equilibrium. 78 Africa’s Power Infrastructure 4. This includes both power plants that were operational in 2005 but will need to be refurbished before 2015 and plants that were not operational in 2005. 5. South Africa has already committed to building 3,000 MW of capacity in open-cycle gas turbine generators. This capacity is therefore included exoge- nously in the model. 6. Fully exploited refers to the assumed maximum potential for hydropower in the model. In most cases, this maximum potential has been set equal to identified projects and plans, even though the full hydropower potential of a country may be much larger. The identified projects serve as a proxy for developments that are realistic in the time frame in focus here (the next 10 years, formally before 2015). 7. Because we use only one (average) investment cost per technology per coun- try, not individual costs per project, cheaper resources are often fully utilized in one country before the more expensive resources are developed in a neigh- boring country. The cost of building international transmission lines counter- acts this to some extent. 8. In addition, there are tiny investments in off-grid technologies in rural areas. 9. There are negligible investments in off-grid technologies in rural areas. 10. See note 6 for a definition of “fully exploited.” Reference Rosnes, Orvika, and Haakon Vennemo. 2008. “Powering Up: Costing Power Infrastructure Spending Needs in Sub-Saharan Africa.” Background Paper 5, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. CHAPTER 4 Strengthening Sector Reform and Planning Since the 1990s reform has swept across the power sector in developing regions. Sub-Saharan Africa is no exception. New electricity acts have been adopted that envisage the reform of state-owned electricity utilities and permit private sector participation. Thus far, however, the private sector has had only limited involvement in reforms. Various short-term private management contracts were awarded, but few have resulted in sustainable improvements in the performance of national utilities. Only a few private leases and concessions survive, mostly in Francophone West Africa. The private sector has been involved primarily in the generation sector. Sub-Saharan Africa’s deficit in generation capacity and lack of invest- ment resources has opened the door for independent power projects (IPPs). Power sector reforms originally followed the prescription of indus- try unbundling, privatization, and competition, but electricity markets that meet these criteria are nowhere to be found in Africa. Instead, the region has seen the emergence of hybrid markets in which incumbent state-owned utilities often retain dominant market positions and IPPs are introduced on the margin of the sector. Attracting investment to hybrid power markets presents new chal- lenges. Confusion arises about who holds responsibility for power sector 79 80 Africa’s Power Infrastructure planning, how procurement should be managed, and how to allocate investment among state-owned utilities and IPPs. These challenges need to be addressed if the generation sector in Sub-Saharan Africa is to bene- fit from the promised new private investment. Independent electricity or energy regulatory agencies have also been established in most Sub-Saharan African countries. They were originally intended to protect consumers, facilitate market entry, and provide price certainty for investors, but they are now criticized for inconsistent deci- sion making and for exacerbating regulatory risk. Independent regulation depends on adequate political commitment and competent, experienced institutions. Without these prerequisites, other forms of regulation may be preferable, such as those that curtail regulatory decision-making dis- cretion with more specific legislation, rule, and contracts. Some regulatory functions may also be outsourced to expert panels. Power Sector Reform in Sub-Saharan Africa Power sector reform in Sub-Saharan Africa has been widespread. There have been attempts to improve the performance of state-owned utilities, new regulatory agencies have been created, private management con- tracts and concessions have been awarded, and private investment has been sought in the form of IPPs. As of 2006, all but a few of the 24 countries of Sub-Saharan Africa cov- ered by the Africa Infrastructure Country Diagnostic (AICD) had enacted a power sector reform law, three-quarters had introduced some form of private participation, two-thirds had privatized their state-owned power utilities, two-thirds had established a regulatory oversight body, and more than one-third had independent power producers (figure 4.1). About one- third of the countries have adopted three or four of those reform compo- nents, but few have adopted all of them, and the extent of reform remains limited. In most countries, for example, the national state-owned utility retains its dominant market position. Private sector cooperation is either temporary (for example, a limited-period management contract) or mar- ginal (in the form of independent power producers that contract with the state-owned national utility). In most cases, the national utility is the man- dated buyer of privately produced electricity while still maintaining its own generation plants. There is no wholesale or retail competition in Africa.1 Many countries are reconsidering whether certain reform principles and programs—notably the unbundling of the incumbent utility to foster Strengthening Sector Reform and Planning 81 Figure 4.1 Prevalence of Power Sector Reform in 24 AICD Countries reform law other PSP SOE corporatization regulatory oversight IPPs operating vertical unbundling 0 20 40 60 80 100 percentage of countries Source: Eberhard 2007. Note: “Other PSP” means forms of private sector participation other than independent power projects (IPPs), namely, concessions or management contracts. AICD = Africa Infrastructure Country Diagnostic; SOE = state-owned enterprise. competition—are appropriate for Sub-Saharan Africa.2 Besant-Jones (2006), in his global review of power sector reform, concludes that power sector restructuring to promote competition should be limited to coun- tries large enough to support multiple generators operating at an efficient scale, which excludes most countries of Sub-Saharan Africa. Even South Africa and Nigeria, which are large enough to support unbundling, have not seen much progress. An examination of the database on private participation in infrastruc- ture (PPI) maintained by the Public-Private Infrastructure Advisory Facility (PPIAF), which covers all countries in Sub-Saharan Africa, unearthed nearly 60 medium- to long-term power sector transactions involving the private sector in the region (excluding leases for emergency power generation). Almost half are IPPs, accounting for nearly 3,000 megawatts (MW) of new capacity and involving more than $2 billion of private sector investment (table 4.1). Côte d’Ivoire, Ghana, Kenya, Mauritius, Nigeria, Tanzania, and Uganda each support two or more IPPs. A few IPP investments have been particularly successful, including the 82 Africa’s Power Infrastructure Table 4.1 Overview of Public-Private Transactions in the Power Sector in Sub-Saharan Africa Type of Number of Investment private Number of canceled in facilities participation Countries affected transactions transactions ($ million) Management Chad, Gabon, Gambia, Ghana, or lease Guinea-Bissau, Kenya, Lesotho, contract Madagascar, Malawi, Mali, Namibia, Rwanda, São Tomé and Príncipe, Tanzania, Togo 17 4 5 Concession Cameroon, Comoros, Côte d’Ivoire, contract Gabon, Guinea, Mali, Mozambique, Nigeria, Sao Tomé and Príncipe, Senegal, South Africa, Togo, Uganda 16 5 1,598 Independent Angola, Burkina Faso, Republic of power Congo, Côte d’Ivoire, Ethiopia, project Ghana, Kenya, Mauritius, Nigeria, Senegal, Tanzania, Togo, Uganda 34 2 2,457 Divestiture Cape Verde, Kenya, South Africa, Zambia, Zimbabwe 7 — n.a. Overall 74 11 4,060 Source: World Bank 2007; AICD 2008. Note: — = data not available; n.a. = not applicable. Tsavo IPP in Kenya (box 4.1) and the Azito power plant in Côte d’Ivoire (box 4.2). Gratwick and Eberhard (2008) predict that although IPPs have some- times been costly because of technology choices, procurement problems, and currency devaluation, they will nevertheless continue to expand generation capacity on the continent. Some have been subject to rene- gotiation. Several factors contribute to the success of IPPs: policy reforms, a competent and experienced regulator, timely and competitive bidding and procurement processes, good transaction advice, a finan- cially viable off-taker, a solid power-purchase agreement (PPA), appro- priate credit and security arrangements, availability of low-cost and competitively priced fuel, and development-minded project sponsors. The other half of the PPI transactions in Sub-Saharan Africa have been concessions, leases, or management contracts, typically for the oper- ation of the entire national power system. Many of these projects have Strengthening Sector Reform and Planning 83 Box 4.1 Kenya’s Success with Private Sector Participation in Power Private sector participation in the power sector in Kenya started with the Electric Power Act of 1997. Since then Kenya has implemented important electricity reforms. The act also introduced independent economic regulation in the sector, which is important for creating a more predictable investment climate to encourage public sector participation. It has since become government policy that all bids for generation facilities are open to competition from both public and private firms and that the national generator does not receive preferential treatment. The sector was unbundled in 1998 with the establishment of the Kenya Electricity Generating Company (KenGen, generation) and Kenya Power and Lighting Company (KPLC, transmission and distribution). Now KenGen and KPLC are 30 percent and 50 percent privately owned, respectively. The Electricity Regulatory Board was established in 1998. It was converted into the Energy Regulatory Commission and granted new powers in 2007. To date the government has not overturned a decision of the board or commis- sion, and it maintains a significant degree of autonomy. It has issued rules on complaints and disputes, licenses, and tariff policy. The regulator also oversees generation expansion planning. KPLC manages the procurement and contract- ing process with IPPs, subject to approval by the regulator of power purchase agreements. Five independent power producers supply an increasing proportion of the country’s electricity, and three additional IPPs have recently been bid out. A proposed wind farm has also recently been licensed (but not yet built). An independent evaluation by the University of Cape Town (Gratwick and Eberhard 2008) concluded that IPPs had a positive outcome on the develop- ment of Kenya’s power sector. The public sector developed very little genera- tion capacity in the decade preceding reforms. The performance of KenGen’s existing plant is inferior to adjacent IPPs. The Tsavo IPP in Kenya is a particularly good example of an investment that came through an international competi- tive bidding process and subsequently produced reliable and competitively priced power. Source: Authors’ compilation based on background materials provided by the World Bank’s Africa Energy Department staff, 2009. 84 Africa’s Power Infrastructure Box 4.2 Côte d’Ivoire’s Independent Power Projects Survive Civil War Compagnie Ivoirienne de Production d’Electricité (CIPREL) was among the first IPPs in Africa. CIPREL began producing power in 1994 with a 210 MW open-cycle plant fired by domestically produced natural gas. SAUR Group and Electricité de France (EDF) were major shareholders. At the time, Côte d’Ivoire’s investment climate was among the best in the region, and the economy was growing at an annual rate of 7.7 percent. This favor- able climate, coupled with CIPREL’s success, stimulated interest in the second IPP, Azito, during its international competitive bid in 1996. Ultimately a consortium headed by Cinergy and Asea Brown Boveri was selected to develop the plant, and the deal was safeguarded by a sovereign guarantee and a partial risk guarantee from the World Bank. In 2000 Azito’s 330 MW gas-fired, open-cycle plant came online, becoming the largest IPP in West Africa. Just months after Azito’s deal was finalized and well before the plant was com- pleted, Côte d’Ivoire suffered a political coup. During the years of civil unrest between 1999 and 2007, the revenues of the national utility, Compagnie Ivoiri- enne d’Electricité (CIE), declined by approximately 15 percent, reducing the state’s ability to invest in much-needed electricity infrastructure. Yet the turmoil had no impact on the IPPs, and they continued to produce electricity and make pay- ments to CIE. Both IPPs are keen to expand their interest in the generation sector. Why have IPPs in Côte d’Ivoire fared so well? A stable currency pegged to the euro (and earlier to the French franc) minimizes the exchange-rate risks that have taxed other Sub-Saharan African IPPs. Cohesive power sector planning after the droughts of the 1980s helped the country achieve a good mix of hydro and thermal power sources. The country has a sufficient power supply for itself and for exports to its neighbors in their times of need. The political instability was also con- fined to the north of the country, where there are fewer consumers than in the south. This allowed the utility to collect sufficient revenues, even when they stopped flowing in from rebel-controlled areas. The availability of domestic gas also helped keep power prices down. The sponsors of the IPP (SAUR and EDF) have been involved throughout the power supply chain, which may explain why there have been no disruptions and why interest continues. Development partners (the World Bank via the International Development Association and the International Finance Corporation; the West African Bank for Development; Promotion et Participation pour la Cooperation Economique; and firms with a development mandate, such as IPS and Globeleq have played a critical role in finalizing and sustaining the deals. Source: Gratwick and Eberhard 2008. Strengthening Sector Reform and Planning 85 been unsuccessful; about one-third of the contracts are either in distress or have already been canceled. Long-term private leases or concessions have survived only in Cameroon, Cape Verde, Côte d’Ivoire, Gabon, Mali, and Uganda. Private Management Contracts: Winning the Battle, Losing the War The only remaining private management contracts in the power sector in Sub-Saharan Africa are in Madagascar and The Gambia. After the expiration of management contracts in several other countries (including Namibia, Lesotho, Kenya, Malawi, Tanzania, and Rwanda), utilities reverted to state operation.3 Management contracts were once regarded as the entry point for PPI. Because the state retained full ownership of the assets, the govern- ment could avoid the political objections that inevitably accompany divestiture. Furthermore, because the private management contractor would neither acquire equity nor incur commercial risk, it should be simple for governments to hire competent professionals, pay them a fee for their services (plus bonuses for fulfillment of specified perform- ance targets in most cases), and enjoy the resulting financial and oper- ational improvements. In reality, management contracts have proved complex and contentious. Although widely used (there are 17 contracts in 15 countries in the region) and usually productive in terms of improving utility collection rates and revenues and reducing system losses, management contracts have not been able to overcome the broader policy and institutional deficiencies of the sector. Moreover, they have failed to generate much-needed investment funds, either through generating sufficient revenue or through improving investment ratings and attracting private debt. Nor have they proven sustainable. Of the 17 African management contracts, four were can- celed before their expiration date, and at least five more were allowed to expire after their initial term (in Gabon and Mali management con- tracts were followed by concessions). Why has it proven difficult to implement and retain support for an ostensibly simple management contract? The disconnect among stake- holder expectations bears a large part of the responsibility. Donors and development finance institutions, which have been involved in almost all management contracts, regard it as a first step toward greater liberaliza- tion and privatization of the utility and not an end in itself. Yet only in Gabon and Mali did management contracts mark the beginning of further 86 Africa’s Power Infrastructure liberalization. Even in countries where concessions or divestitures were clearly not an option (mostly because of popular or political opposition to privatization), donors viewed the contracts as part of a larger reform process and expected them to be extended long enough to allow parallel policy and institutional changes to take root. African governments, on the other hand, saw them not as easy first steps but as undesirable obligations that they needed to fulfill to receive crucial donor funding. Assessments of the impact of African electricity management contracts indicate improved performance, including greater labor productivity, better collection rates, and reduced system losses. For example, between mid-2002 and mid-2005 under the management contract in Tanzania, collection rates rose from 67 to 93 percent, system losses fell by 5 percent, 30,000 new con- nections were installed (at a pace far greater than the previous expansion rate), costs fell by 30 percent, and annual revenues rose by 35 percent. Labor relations improved despite the layoff of more than 1,300 workers, whose departure was eased by a generous severance package. The utility introduced a poverty tariff for consumers using 50 kilowatt-hours a month or less (Ghanadan and Eberhard 2007). Working capital overdrafts were cleared, and the utility even secured small loans from private commercial banks (contingent on the continued presence of the management contrac- tors). A management contractor in the rural, northern part of Namibia also produced significant gains. Between 1996 and 2002, the number of cus- tomers doubled, and labor productivity soared without a change in the size of the workforce (Clark and others 2005). Based on the promising results from these and other management con- tracts, donors concluded that they were an effective method for improv- ing utility performance. Some country officials, however, were more skeptical. They acknowledged that performance had improved but argued that they were largely a result of foreign managers being allowed to lay off excess staff, cut service to delinquent customers, and raise tariffs—African managers in state-owned utilities had not had the same freedom. The main counterargument was therefore that if public man- agers were given the same authority as management contractors, they could achieve similar performance at a much lower price. Management contracts may have proved easier to sustain had they been accompanied or followed by large amounts of external investment funding, or had they substantially improved service quality or reduced costs enough to provide investment capital from retained earnings for network rehabilitation and expansion. They were not able to do so, how- ever, partly because of poor initial conditions and partly because they Strengthening Sector Reform and Planning 87 often coincided with cost-raising factors beyond the control of utility managers such as regional drought, soaring oil prices, and the need to pur- chase expensive power from IPPs. African ministries of finance were doubtless pleased with the finan- cial and efficiency gains observed under the management contracts. Yet most customers were unaware of or indifferent to financial improve- ments and were instead concerned with service quantity, quality, and price. In these areas, changes were gradual and modest. Critics of priva- tization and private participation—including some who had been dis- placed from management posts by the management contracts—objected to continued load shedding and the indignity of relying on foreign man- agers. They also protested the substantial contractor fees. For example, the management contractor in Tanzania earned $8.5 million in fixed fees and $8.9 million in performance-based fees during its 56 months in operation. (Those fees were a small fraction of the financial gains pro- duced under the management contract, and the Swedish donor, the Swedish International Development Cooperation Agency, paid a large portion of the performance-based reward). The significant political back- lash convinced policy makers that the benefits of management contracts did not outweigh the costs, and the contracts were allowed to lapse. Although management contracts can improve the efficiency and sus- tainability of utilities, they cannot overcome the obstacles posed by broader policy and institutional weaknesses. Moreover, the performance improvements are gradually distributed to unaware and unorganized consumers, whereas the costs immediately affect a vocal and organized few, whose protests often overcome rational debate. African manage- ment contracts appear to have won the economic battles but lost the political war. They must therefore be restructured to be sustainable and more widely palatable. Sector Reform, Sector Performance Sub-Saharan Africa lags behind other regions in installed capacity, elec- tricity production, access rates, costs, and reliability of supply. Many other performance indicators are also subpar. For example, the utilities have an average of only about 150 customers per employee, compared with an average of more than 500 in the high-income member countries of the Organisation for Economic Co-operation and Development. Transmission and distribution (T&D) losses average 25 percent. Commercial efficiency, collection rates, and cost recovery are also poor. 88 Africa’s Power Infrastructure Figure 4.2 Effect of Management Contracts on Performance in the Power Sector in Sub-Saharan Africaa Connection per employee (number) Implicit collection rates (% of electricity billed) T&D loss (% of generation) Cost recovery (% of billing) 0 20 40 60 80 100 120 140 160 180 200 management contract other Source: Vagliasindi and Nellis 2010. Note: T&D = transmission and distribution. a. Performance differential is statistically significant at the 1 percent level. Power sector reform should improve utility performance (Gboney 2009). Nevertheless, although PPI generally has a positive effect on performance, it does not always improve all performance indicators (figure 4.2). Disaggregated data on PPI, however, reveal that utilities in countries with IPPs almost always fare better and that concessions are far more effective than management contracts in improving perform- ance. Countries with management contracts fail to make any major or sustained improvements (except in labor productivity). The Search for Effective Hybrid Markets The 1990s reform prescription of utility unbundling and privatization followed by wholesale and retail competition was not effective in Africa. Most of the region’s power systems are too small to support meaningful competition. The new reality is therefore one of hybrid power markets. In this model the state-owned utility remains intact and occupies a dom- inant market position, whereas private sector participation (typically in Strengthening Sector Reform and Planning 89 the form of IPPs) compensates for the lack of investment on the part of governments and utilities. Africa’s hybrid electricity markets pose new challenges in policy, regulation, planning, and procurement, which are compounded by widespread power shortages and an increasing reliance on emergency power throughout the region. It is often uncertain where responsibility for ensuring adequate and reliable supply lies in hybrid power markets. Few countries in Africa have an explicit security of supply standard,4 and the incumbent state-owned national utility has typically assumed the responsibility as supplier of last resort. However, few government departments or regulators explicitly monitor adequacy and reliability of supply, and even fewer require utili- ties to regularly disclose public reports regarding their security of supply. If monitoring were institutionalized, then regulators would be in a better position to assess the need for investment in new capacity. Traditionally the state-owned utility bore responsibility for planning and procurement of new power infrastructure. With the advent of power sector reforms and the introduction of IPPs, those functions were often moved to the ministry of energy or electricity. A simultaneous transfer of skills did not always occur, however, resulting in poorly executed plans; in many cases generation expansion planning has collapsed. Where still present, planning tends to take the form of outdated, rigid master plans that do not reflect the changes in price and availability of fuel and equipment and the resulting least-cost options. Planning needs to be dynamic and flexible, and potential investors should benefit from reg- ular disclosure of information regarding demand growth and investment opportunities. At the same time, planning should not preclude the emer- gence of innovative solutions from the market. The allocation of responsibility for capacity expansion should be care- fully considered. The national utility generally has much greater access to resources and professional staff than either the energy ministry or the reg- ulator. It therefore may be the most pragmatic choice to be the authority for national planning, especially if the transmission and system operations are unbundled from generation. If this is the case, however, a governance and oversight mechanism would be needed to ensure that national inter- ests, and not the interests of the utility, motivate planning. Box 4.3 explores South Africa’s difficulties with planning in the power sector. Incumbent state-owned utilities often argue that they are able to sup- ply power more cheaply or quickly than private alternatives (even if they lack the resources to do so). Yet rigorous analysis that assigns appropriate costs to capital seldom supports such claims, which undermine the entry 90 Africa’s Power Infrastructure Box 4.3 Power Sector Planning Dilemmas in South Africa The state-owned national utility Eskom dominates South Africa’s power market. It generates 96 percent of the country’s electricity and through 2006 has provided reliable and secure power supplies. This was largely possible because massive overinvestment in the 1970s and 1980s generated substantial spare capacity. In 1998 the government published a white paper on energy policy, which proposed that Eskom be unbundled, 30 percent be sold, and competition introduced. From 2001 to 2004 consultants worked to design a power exchange and bilateral power market with associated financial contracts for differences, futures, and forward options—not unlike NordPool in Scandinavia or PJM on the East Coast of the United States. During this time the government prohibited Eskom from investing in new capacity because the market would provide new private investment. Eskom was traditionally the supplier of last resort in South Africa and had responsibility for power sector planning and new investments. Now confusion arose as to who was responsible for these functions. Eskom continued to develop plans, but so did the Ministry of Energy and the regulator—and each differed from the other. At the same time, growing demand and a lack of new capacity were eroding reserve margins. The consultants’ plan was never implemented. No new private investment was possible in this context of market uncertainty and in the absence of clear contracting frameworks. In 2004 the government abandoned its plans to establish a power exchange, and Eskom once again assumed responsibility for expanding generation capacity. At the same time, IPPs would be allowed to enter the market. By this point, Eskom was four years behind in its investments. It has since ordered new large-base-load power stations, but these will begin to come online in 2012. In the meantime, South Africa has experienced power rationing and blackouts. The government has reassigned responsibility for power sector planning to Eskom, although the Ministry of Energy decides which of Eskom’s planning sce- narios to adopt. The Ministry then promulgates and publishes the official plan, on which the regulator bases its licensing of generators. Although this arrangement has provided some certainty regarding the alloca- tion of responsibilities for planning, the official plan is prescriptive rather than indicative and potentially excludes many innovative investment solutions from the private sector. So far no new IPPs have been contracted, although some cogeneration contracts have been concluded. The Ministry of Energy is also (continued next page) Strengthening Sector Reform and Planning 91 Box 4.3 (continued) developing a proposal to unbundle the planning, buying, transmission, and sys- tem operation functions from Eskom. The case of South Africa illustrates the complexity and difficulty of involv- ing both state-owned utilities and IPPs in hybrid power markets. In particular, it highlights the importance of clearly allocating responsibility for planning and procurement functions, developing flexible and up-to-date plans, and establishing governance mechanisms to ensure that decisions on capacity expansion and procurement are made transparently, fairly, and in the national interest. Source: Authors. of IPPs. Regardless, most African utilities have not supplied adequate investment in much-needed generation capacity. Poor understanding of the hybrid market prevents policy makers from devising clear and transparent criteria for allocating new building oppor- tunities among the incumbent state-owned utility and IPPs. The failure to order new plants on a timely basis discourages investors and results in power shortages that prompt recourse to expensive emergency power. This has been the case in Tanzania and Rwanda. When authorities finally begin procurement, they may not take the trouble to conduct interna- tional competitive bidding. This is unfortunate, because a rigorous bid- ding process provides credibility and transparency and results in more competitively priced power. Unsolicited bids can lead to expensive power. The best example of that is IPTL in Tanzania, which provides some of the most costly power in the region (when it is operational, because an unresolved arbitration process has recently closed the plant). However, unsolicited bids sometimes allow private investors to offer innovative generation alternatives, and they gen- erally cover the project development costs. Theoretically, unsolicited bids could be subjected to a Swiss challenge whereby the project is bid out competitively, and the original project developer can subsequently improve their offer to beat the most competitive bid. In practice, however, the Swiss challenge would be difficult to implement if the project devel- oper owns associated fuel resources (for example, a coal field) or if the project is unique is some way (for example, the development of methane resources in Lake Kivu in Rwanda). Governments should therefore opt for 92 Africa’s Power Infrastructure international competitive bids when feasible but should also develop poli- cies for handling unsolicited bids. Hybrid markets also require clarity on the IPP off-take arrangements. For various reasons, power from IPPs in Sub-Saharan Africa is likely to be more expensive than from the national utility. For example, the genera- tion plant for the national utility may be largely depreciated and paid for (for instance, old hydroelectric facilities), and prices may not necessarily reflect costs. Customers are thus likely to seek their power from the state- owned utility rather than buying directly from the IPP (unless security of supply concerns make power from IPPs more attractive, despite higher prices). In most cases, however, IPPs will require off-take agreements with incumbent national utilities that aggregate demand and average prices for customers. Surprisingly few African countries have explicitly defined their power market structures or procedures for negotiating and contract- ing PPAs with IPPs. Some countries have used the single-buyer model with the national utility as the buyer. Yet it is not always clear whether this implies that the national utility has exclusive purchasing rights. For example, are IPPs required to sell only to the national utility, or could they also contract separately with large customers or across borders? Countries should therefore make it clear that the central purchasing func- tion of the national utility does not imply exclusivity. IPPs should be per- mitted to seek their own customers. Hybrid power markets will not disappear from the African landscape in the near future. To maximize their benefit, African governments and their development partners must establish a robust institutional founda- tion for the single-buyer model with clear criteria for off-take agree- ments. They must also improve their planning capabilities, establish clear policies for allocating new investment opportunities among the state- owned utilities and IPPs, and commit to competitive and timely bidding processes. Table 4.2 provides a list of common policy questions in the sector and corresponding solutions. Development finance institutions and bilateral donors can provide advice and expertise to governments and utilities on establishing transpar- ent frameworks and procedures for contracting and reaching financial clo- sure with project sponsors and private investors. Yet they must be careful to pay sufficient attention to the peculiarities of the hybrid market. Otherwise lending to public utilities may unintentionally deepen hybrid markets’ inherent contradictions and crowd out private investment. Above all, the sector requires stronger public institutions that can engage effectively with the private sector. Strengthening Sector Reform and Planning 93 Table 4.2 Common Questions in Hybrid Power Markets and Their Policy Solutions Question Policy options Who is responsible for Develop standard for security and adequacy of supply. (The U.S. security and adequacy standard is one cumulative day of outage per 10 years; one day of supply? per year may be reasonable for countries in Sub-Saharan Africa.) Assign responsibility for reporting to utilities and monitoring supply adequacy to regulator. Who is responsible Assign responsibility to ministry, regulator, or utility. Superior for generation access to resources and professional staff may make the expansion planning? national utility the pragmatic choice, but this will require governance mechanisms to provide oversight and guidance on planning assumptions and criteria. Planning should be indicative, dynamic, flexible, and regularly updated, not a rigid master plan. How are investment Establish clear and transparent criteria for allocating new opportunities in new investment opportunities to either national utility or IPPs generation allocated (for example, according to fuel source, technological expertise, between the national or financing or contracting capability). utility and IPPs? Who is responsible for Establish a procurement function (either in a PPP unit or linked initiating procurement to system operator or transmission function) that is informed by of new generation needs identified in planning process. Ensure adequate plant and when? governance and oversight to ensure timely initiation of fair and transparent procurement. Is competitive bidding Employ international competitive bidding processes whenever required, or can possible. Establish under what circumstances and how unsolicited offers be unsolicited bids can be considered. considered and, if so, how? Who is responsible Clarify market structure. Establish nonexclusive central for contracting IPPs? purchasing function (possibly attached to system operator or transmission) that aggregates demand and signs PPAs. Build local capacity to negotiate effectively with private investors. Allow willing buyer-seller contracts between IPP and large customers and cross-border trades and contracting. Can IPP PPA costs be Establish clear cost recovery mechanism for national utilities passed on by national with captive customers who contract with IPPs and decide utility to customers? when PPA costs can be passed on to customers. Test competi- tiveness of procurement. Will IPPs be fairly Ensure that PPAs, grid codes, and market rules have fair take or dispatched by the pay and dispatch provisions. incumbent state-owned utility? Source: Authors. Note: IPP = independent power project; PPA = power-purchase agreement. 94 Africa’s Power Infrastructure Hybrid power markets, with the incumbent state-owned utility desig- nated as the single buyer of electricity from IPPs, have become the most common industry structure in Africa. Although the national utility can play a useful role in aggregating demand and entering into long-term con- tracts with new investors, few advantages are found in assigning it exclu- sive buying rights. Instead, IPPs should be able to enter into willing seller-buyer arrangements and supply directly to both the national utility and large customers. Large customers should also have choice and should be able to contract directly with IPPs or import power. Such an arrange- ment would require nondiscriminatory access to the grid. Perhaps a bet- ter description of such a model is a central nonexclusive buyer rather than a single buyer. Thought also needs to be given to the long-term implications of sign- ing 25- or 30-year contracts with IPPs. It may be advantageous to migrate to a more short-term market in the future. Including sunset clauses in PPAs would encourage IPPs to trade at least part of their production on a power exchange in the future. The Possible Need to Redesign Regulatory Institutions Most countries in Sub-Saharan Africa have established nominally inde- pendent regulatory agencies for their power sector. Regulation was origi- nally intended to ensure financial viability, attract new investment, and encourage efficient, low-cost, and reliable service provision. Governments hoped that independent regulation would insulate tariff setting from polit- ical influence and improve the climate for private investment through more transparent and predictable decision making. An analysis of data collected in the initial sample of 24 AICD countries indicates that the power sector performs better in countries with regula- tors than those without (figure 4.3). Yet the same countries show no obvi- ous improvements in cost recovery, T&D losses, or reserve margins. These apparent contradictions can be explained. Cost recovery calculations can vary based on numerous assumptions that may affect estimates, and reporting on T&D losses is not always reliable. Furthermore, countries that lack regulators (such as Benin, Burkina Faso, Chad, the Democratic Republic of Congo, Mozambique, and Sudan) are among the poorest on the continent and face many additional challenges that affect the per- formance of their power sectors. Despite the better performance of countries with regulators, it is far from clear whether regulation has catalyzed new private investment. Strengthening Sector Reform and Planning 95 Figure 4.3 Power Sector Performance in Countries with and without Regulation access (% of households) Connections per employee (number) T&D loss (% of generation) 0 20 40 60 80 100 120 140 160 180 regulation no regulation Source: Vagliasindi and Nellis 2010. Note: T&D = transmission and distribution. Some critics argue that regulatory agencies have exacerbated the very problems that they were meant to address while creating regula- tory risk for investors. Inexperienced regulators tend to make unpre- dictable or noncredible decisions. Alternatively regulators may have been given excessively wide discretion and overly broad objectives and must make difficult decisions with important social and political conse- quences (Eberhard 2007). The Challenges of Independent Regulation Utility regulation in developing countries has clearly coincided with the emergence of new problems. In many cases, regulators are far from inde- pendent and are subject to pressure from governments to modify or over- turn decisions. Turnover among commissioners has been high, with many resigning under pressure before completing their full term. The discon- nect between law (or rule) and practice is often wide. Tariff setting remains highly politicized, and governments are sensitive to popular resentment against price increases, which are often necessary to cover costs. Establish- ing independent regulatory agencies may be particularly risky for all stake- holders (governments, utilities, investors, and customers) in sectors that are being reformed, especially when prices are not already high enough to ensure sufficient revenue. In some ways, it is not surprising to find political interference and pressure on regulators. 96 Africa’s Power Infrastructure Governments in developing countries often underestimate the diffi- culty of establishing new public institutions. Building enduring systems of governance, management, and organization and creating new professional capacity are lengthy processes. Many regulatory institutions in developing countries are no more than a few years old, and few are older than 10. Many are still quite fragile and lack capacity. Independent regulation requires strong regulatory commitment and competent institutions and people. The reality is that developing coun- tries are often only weakly committed to independent regulation and face capacity constraints (Trémolet and Shah 2005). It may be prudent in such cases to acknowledge that weak regulatory commitment, political expe- diency, fragile institutions, and capacity constraints necessitate limits on regulatory discretion. This does not imply that independent regulation is undesirable. Because of limited institutional capacity in the sector, how- ever, complementary, transitional, or hybrid regulatory options and mod- els (such as regulatory contracts or outsourcing of regulatory functions) may be a better starting point. Regulation by Contract Most of the Sub-Saharan countries that were previously British colonies have independent regulators that operate within a system of common law with wide discretionary powers over decision making. On the other hand, those countries that were previously French colonies have tended to rely on regulatory contracts. For example, Cameroon, Côte d’Ivoire, Gabon, and Mali all have electricity concession contracts that incorporate core regulatory functions. Regulatory contracts comprise detailed predetermined regimes (includ- ing multiyear, tariff-setting systems) in legal instruments such as basic law, secondary legislation, licenses, concession contracts, and PPAs (Bakovic, Tenenbaum, and Woolf 2003). They are generally constructed for private participation but may also be used to improve the performance of state- owned utilities. Long-term contracts must accommodate for the possibility of unex- pected events. In the French legal tradition, a general legal framework and an understanding between the parties to facilitate renegotiation is used to restore financial sustainability in extraordinary circumstances. On the other hand, the English legal tradition usually dictates specifying in advance the events that will trigger renegotiation. Regulatory agencies can successfully coexist with incomplete regula- tory contracts that require additional regulatory mechanisms. The law or Strengthening Sector Reform and Planning 97 contract could explicitly define the role of the regulator—for example, in periodic tariff setting, monitoring of performance, or mediation and arbi- tration. The regulator can also enhance the transparency of regulatory contracts by collecting, analyzing, and publishing performance data. Uganda provides a good example of successful coexistence of the two regulatory forms. The country has an independent regulator, but the gen- eration and distribution components of the power sector have been pri- vatized in concession agreements. Nevertheless, merging these two distinct legal traditions can create problems. For example, even if a contract speci- fies a tariff-setting formula, the regulator might feel obligated by its legisla- tive mandate to intervene in the public interest. In these cases, clarifying regulatory roles and functions is essential. Outsourcing Regulatory Functions Countries may also outsource regulatory functions to external contrac- tors, who perform tariff reviews, benchmarking, compliance monitoring, and dispute resolution. Power sectors that are beset by challenges or problems relating to a regulator’s independence, capacity, or legitimacy are good candidates for regulatory outsourcing. The same is true for reg- ulatory contracts that need additional support for effective administra- tion. For example, the electricity concession in Gabon relies on external parties to monitor and verify performance indicators specified in its con- tract. Outsourcing might also be used when it is cost effective (Trémolet, Shukla, and Venton 2004). Two main models of regulatory outsourcing are found. The first involves hiring outside consultants to provide technical support to reg- ulators or the parties subject to a regulatory contract. Governments can also contract separate advisory regulators or expert panels, funded from an earmarked budget outside the line ministry. The strongest version of the second model requires the advisory regulator or expert panel to clearly explain its recommendations in publicly available documents. The sector minister (or other relevant authority) may request reconsid- eration of the recommendations but must do so within a specified period. If the minister rejects or modifies the recommendations, he or she must provide a written public explanation. Otherwise, the recom- mendations are enacted. Any policy directives or other communications from the minister to the regulator or expert panel must be made pub- licly available. The regulator or expert panel holds public consultations with any stakeholders affected by its recommendations (Brown and others 2006). 98 Africa’s Power Infrastructure Governments may also hire expert panels to arbitrate disputes between regulators and utility operators or those arising from contested interpre- tations in regulatory contracts. Unlike conventional arbitration mecha- nisms, expert panels have the specialist expertise needed to analyze comprehensive tariff reviews and use procedures that are less formal and adversarial. Regional economic bodies or regulatory associations could use expert panels to provide technical assistance to numerous national regulators. They would also provide greater continuity and consistency in specialist support and assist in harmonizing regulatory regimes, which would aid the integration of regional networks. Toward Better Regulatory Systems The different regulatory models embody varying degrees of regula- tory discretion, but they are not mutually exclusive and often coex- ist (figure 4.4). How can countries choose among these options or decide on the appropriate combination? Some observers have argued that the fundamental challenge in regula- tory design is to find governance mechanisms that restrain regulatory dis- cretion over substantive issues such as tariff setting (Levy and Spiller 1994). Others argue that some regulatory discretion is inevitable, or even desirable. The challenge is therefore to establish governance arrangements and procedures that allow a “nontrivial degree of bounded and account- able discretion” (Stern and Cubbin 2005). A Model to Fit the Context The context of a country’s particular power sector should determine the level of regulatory discretion. Regulatory models and governance systems should be securely located within the political, constitutional, and legal arrangements of the country. They should also fit the country’s levels of regulatory commitment, institutional development, and human resource capacity. For a country with weak regulatory commitment and capacity, a good first step might be a set of low-discretion regulatory contracts without a regulatory agency (figure 4.5). In other countries with strong regulatory commitment but weak institutional development and capacity, regulatory functions could be contracted to an expert panel. Countries with unique needs can also adopt a hybrid regulatory model. For example, a government could supplement an independent regulatory agency or regulatory contract by outsourcing some regulatory functions. Strengthening Sector Reform and Planning 99 Figure 4.4 Coexistence of Various Regulatory Options Regulation Regulation by agency by contract Regulator (or ministry) Independent regulator sets administers contract Regulatory regime tariffs and regulates access, (such as a concession (including tariff setting) quality of supply, customer contract) prespecified in detail service, dispute resolution in legal instrument Advisory regulators Expert panels Regulator Regulatory outsources contract provides some support functions for external contractors Independent reviews Government Government policy and policy and legal legal Outsourcing of framework framework regulatory functions to third parties Consultants or expert panels undertake or assist with tariff reviews, standard setting, monitoring, arbitration Source: Eberhard 2007. As noted, regulatory contracts can coexist with independent regulatory oversight. Yet another possibility is a transitional path (as indicated in figure 4.5) in which the regulatory model adapts to accommodate changing circum- stances. While regulatory commitment in a country grows, the government could contract strong advisory panels or establish a separate regulatory agency, perhaps with limited discretion at first. The responsibilities and functions of the regulatory agency could expand as sufficient institutional and resource capacity accumulates. Eventually, the government could out- source some regulatory functions. No regulatory model is ideal, and a country’s regulatory reform process may not always lead to a full-fledged independent regulatory agency. In fact, the context simply may not call for an independent regulator, and an 100 Africa’s Power Infrastructure Figure 4.5 Choice of Regulatory Model Based on the Country Context high low strong advisory regulators independent regulator expert panels contracting-out if cost-effective regional regulators regulatory commitment ? country X regulatory contracts regulatory contracts with contracting-out low institutional and human resource capacity high Source: Adapted from Brown and others 2006. expert panel or a well-designed regulatory contract would suit the coun- try’s needs. Each country therefore must choose from a menu of regula- tory options to create a hybrid model that best fit its particular situation. The model must be flexible enough to evolve according to growth in a country’s regulatory commitment and capacity. In the end, designing and implementing legitimate, competent regulatory institutions in developing countries will always be a challenge. Nevertheless, establishing an effec- tive regulatory system is essential to the region’s strategy of increasing pri- vate participation in the power sector. More effective regulation of incumbent state-owned utilities will remain a critical challenge. Regulators can play a useful role in ensuring that tariffs are cost reflective while improving efficiencies and encouraging utilities to reduce costs. Improved financial performance also helps utilities to raise private debt and fund capacity expansion. These issues are discussed further in chapters 6 and 7. Notes 1. The only exception is a short-term energy market in the Southern African Power Pool. The quantities traded, however, are extremely small. 2. Uganda is one of the exceptions where generation, transmission, and distribu- tion were fully unbundled. In Kenya, generation (KenGen) has been separated Strengthening Sector Reform and Planning 101 from transmission and distribution (KPLC). Ghana has unbundled its trans- mission company and has a separate distribution company. Nigeria has tech- nically unbundled its utility, although the separate entities still coordinate with each other. For historical reasons, local governments in Namibia and South Africa assume some responsibility for distribution. 3. The author of this section is John Nellis (2008). 4. Typically expressed as a loss-of-load probability and an associated generation- reserve margin. Bibliography AICD (Africa Infrastructure Country Diagnostic). 2008. Power Sector Database. Washington, DC: World Bank. Bakovic, Tonci, Bernard Tenenbaum, and Fiona Woolf. 2003. “Regulation by Contract: A New Way to Privatize Electricity Distribution?” Energy and Mining Sector Board Discussion Paper Series, Paper 7, World Bank, Washington, DC. Besant-Jones, J. E. 2006. “Reforming Power Markets in Developing Countries: What Have We Learned?” Energy and Mining Sector Board Discussion Paper Series, Paper 19, World Bank, Washington, DC. Brown, Ashley C., Jon Stern, Bernard W. Tenenbaum, and Defne Gencer. 2006. Handbook for Evaluating Infrastructure Regulatory Systems. Washington, DC: World Bank. Clark, Alix, Mark Davis, Anton Eberhard, and Njeri Wamakonya. 2005. “Power Sector Reform in Africa: Assessing the Impact on Poor People.” ESMAP Report 306/05, World Bank, Washington, DC. Eberhard, A. 2007. “Matching Regulatory Design to Country Circumstances: The Potential for Hybrid and Transitional Models.” Gridlines Note 23, PPIAF, World Bank, Washington, DC. Gboney, William K. 2009. “Econometric Assessment of the Impact of Power Sector Reforms in Africa: A Study of the Generation, Transmission and Distribution Sectors.” Thesis to be submitted in fulfillment of the PhD degree, City University, London. Ghanadan, R., and A. Eberhard. 2007. “Electricity Utility Management Contracts in Africa: Lessons and Experience from the TANESCO-NET Group Solutions Management Contract in Tanzania.” MIR Working Paper, Management Program in Infrastructure Reform and Regulation, Graduate School of Business, University of Cape Town, Cape Town, South Africa. Gratwick, K. N., and Anton Eberhard. 2008. “An Analysis of Independent Power Projects in Africa: Understanding Development and Investment Outcomes.” Development Policy Review 26 (3): 309–38. 102 Africa’s Power Infrastructure Levy, B., and P. Spiller. 1994. “The Institutional Foundations of Regulatory Commitment: A Comparative Analysis of Telecommunications Regulation.” Journal of Law, Economics and Organization 10 (1): 201–46. Nellis, John. 2008. “Private Management Contracts in Power Sector in Sub-Saharan Africa.” Internal note, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Stern, Jon, and John Cubbin. 2005. “Regulatory Effectiveness: The Impact of Regulation and Regulatory Governance Arrangements on Electricity Industry Outcomes.” Policy Research Working Paper Series 3536, World Bank, Washington, DC. Trémolet, Sophie, and Niraj Shah. 2005. “Wanted! Good Regulators for Good Regulation.” Unpublished research paper, PPIAF, World Bank, Washington, DC. Trémolet, Sophie, Padmesh Shukla, and Courtenay Venton. 2004. “Contracting Out Utility Regulatory Functions.” Unpublished research paper, PPIAF, World Bank, Washington, DC. Vagliasindi, Maria, and John Nellis. 2010. “Evaluating Africa’s Experience with Institutional Reform for the Infrastructure Sectors.” AICD Working Paper 22, World Bank, Washington, DC. World Bank. 2007. Private Participation in Infrastructure (PPI) Database. Washington, DC: World Bank. CHAPTER 5 Widening Connectivity and Reducing Inequality Coverage of electricity services in Sub-Saharan Africa, stagnant over the past decade, skews strongly toward higher-income households and urban areas. Many of those who remain without a connection live reasonably close to existing networks, which suggests that in addition to supply con- straints, demand-side barriers may be a factor. In these circumstances, the key questions are whether African households can afford to pay for mod- ern infrastructure services such as electricity—and, if not, whether African governments can afford to subsidize them. The business-as-usual approach to expanding service coverage in Africa does not seem to be working. Reversing this situation will require rethinking the approach to service expansion in four ways. First, coverage expansion is not just about network rollout. A need exists to address demand-side barriers such as high connection charges. Second, it is important to remove unnecessary subsidies to improve cost recovery for household services and ensure that utilities have the financial basis to invest in service expansion. Third, it is desirable to rethink the design of utility subsidies to target them better and to accelerate service expansion. Fourth, progress in rural electrification cannot rely only on decentralized options; it requires a sustained effort by national utilities supported by systematic planning and dedicated rural electrification funds (REFs). 103 104 Africa’s Power Infrastructure Low Electricity Connection Rates Coverage of electricity services in Africa is very low by global standards. Connection rates are less than 30 percent in Africa, compared with approximately 65 percent in South Asia and more than 85 percent in East Asia and the Middle East. Africa’s low coverage of infrastructure services to some extent reflects its relatively low urbanization rates, because urban agglomeration greatly facilitates the extension of infrastructure networks. Household surveys show only modest gains in access to modern infra- structure services over 1990–2005 (figure 5.1). The overall trend masks the fact that the percentage of households with connections in urban Figure 5.1 Patterns of Electricity Service Coverage in Sub-Saharan Africa a. Growth in electricity coverage 35 30 percent of households 25 20 15 10 5 0 1990–95 1996–2000 2001–05 b. Coverage by geographic area, latest year available 100 percent of households 80 60 40 20 0 rural national urban low-income countries all countries middle-income countries Source: Banerjee and others 2008; Eberhard and others 2008. Widening Connectivity and Reducing Inequality 105 areas has actually declined. Although many new connections are being made in urban areas, declining urban coverage largely reflects service providers’ inability to keep pace with average urban population growth of 3.6 percent a year. The pace of service expansion differs across countries. The most dra- matic increase in electricity connections was seen in South Africa after the advent of democracy in 1994. Coverage increased from approximately one-third of the population to more than two-thirds in less than a decade (Marquard and others 2008). A few countries—such as Cameroon, Côte d’Ivoire, Ghana, and Senegal—have made some progress, and close to half of their people now have access. (Box 5.1 examines Ghana’s electrification program.) These are exceptions, however, and most countries of Sub- Saharan Africa lag far behind. For example, Uganda’s electrification rate stands at 8 percent and Chad’s at 4 percent (figure 5.2). Mixed Progress, despite Many Agencies and Funds Despite accelerating urbanization, the region’s rural areas still account for approximately two-thirds of the total population, which presents signifi- cant challenges in raising access rates. It is obviously cheaper to electrify urban areas, followed by higher-density rural areas. Off-grid technologies such as solar photovoltaic panels become an option in remote areas but are still very expensive—typically $0.50–0.75 per kilowatt-hour (kWh). Minigrids, where feasible, are more attractive options in remote areas, especially when combined with small-scale hydropower facilities (ESMAP 2007). Incumbent national utilities—mostly state owned and vertically integrated—are responsible for urban (and often rural) electrification. A significant trend during the past decade, however, has been the establishment of special-purpose agencies and funds for rural electrifi- cation. Half the countries in the Africa Infrastructure Country Diagnostic (AICD) sample have REAs (rural electrification agencies), and more than two-thirds have dedicated REFs. Funding sources for REFs may be levies, fiscal transfers, donor contributions, or combinations of these. The majority of countries have full or partial capital subsidies for rural connections and explicit planning criteria (usually population density, least cost, or financial or economic returns). In some cases, polit- ical pressures trump these criteria. How effective have these institutional and funding mechanisms been in accelerating rural electrification? On average, greater progress has been 106 Africa’s Power Infrastructure Box 5.1 Ghana’s Electrification Program Ghana boasts a national electrification rate of nearly 50 percent. Urban rates of access hover near 80 percent, and rural rates at approximately 20 percent. With access of the population to electricity at less than 25 percent in the region, Ghana’s recent electrification experience may be instructive for neighboring countries. Starting in 1989, when Ghana’s access rates were estimated at 20 percent and the grid supply covered only one-third of the country’s land area, electrification efforts were intensified under the National Electrification Scheme (NES), which was designed to connect all communities with a population of more than 500 to the national grid between 1990 and 2020. The National Electrification Master Plan subsequently laid out 69 projects that would span 30 years to realize the stated policy goal. The first two five-year phases of the plan were undertaken between 1991 and 2000; the country’s two state- owned utilities, Electricity Company of Ghana and the Volta River Authority, were charged with implementation. A rural electrification agency was not used. Project costs of $185 million were covered largely via concessionary financing from sev- eral multilateral and bilateral donors. In addition to the central role of the utilities and the prominence of conces- sionary lending, the Self-Help Electrification Programme (SHEP) was noteworthy in advancing the aims of the NES. SHEP was the means by which communities, within a certain proximity to the network and otherwise not targeted for near-term elec- trification, were able to be connected by purchasing low-voltage distribution poles and demonstrate the readiness of a minimum number of households and businesses to receive power. SHEP was further supported by a 1 percent levy on electricity tariffs. As of 2004, efforts under the NES had led to the electrification of more than 3,000 communities. Contrary to expectations, however, an indigenous industry to supply products for the electrification program has not taken off. Furthermore, SHEP is now considered defunct, having been unable to sustain itself financially. Nevertheless, the NES continues and is cofinanced by development finance insti- tutions and local Ghanaian banks, with an increasing emphasis on minigrids and standalone systems. Source: Clark and others 2005; Mostert 2008. Widening Connectivity and Reducing Inequality 107 Figure 5.2 Electrification Rates in the Countries of Sub-Saharan Africa, Latest Year Available South Africa Nigeria Côte d’Ivoire Senegal Cameroon Ghana Namibia Benin Zambia Madagascar Kenya Ethiopia Mozambique Tanzania Burkina Faso Uganda Niger Malawi Lesotho Rwanda Chad 0 10 20 30 40 50 60 70 percentage of households connected to electricity grid Source: Eberhard and others 2008. made in those countries with electrification agencies and especially those with dedicated funds (figure 5.3). Having a clear set of electrification cri- teria also makes a difference. Countries with higher urban populations also tend to have higher levels of rural electrification, because urban customers tend to cross- subsidize rural electrification (figure 5.4). Surprisingly, no correlation could be found between the proportion of utility income derived from nonresidential electricity sales and the level of growth in residential connections. One would have expected that increased revenue from industrial and commercial customers would also allow for the cross- subsidization of rural electrification. A recent review of electrification agencies in Africa has concluded that centralized approaches, in which a single utility is responsible for national rural electrification, for the most part have been more effective than decentralized approaches involving several utilities or private compa- nies, provided the national utility is reasonably efficient (Mostert 2008). Figure 5.3 Rural Electrification Agencies, Funds, and Rates in Sub-Saharan Africa 108 a. Prevalence of various measures b. Annual growth in rural connections according to to promote rural electrification presence or absence of rural electrification policy no subsidy partial subsidy no policy full subsidy REA + REF REA, no REF policy REF, no REA 0 10 20 30 40 50 0 2 4 6 8 10 percentage of countries growth in percentage of rural connections c. Incidence of rural connections by d. Annual growth in rural connections by presence or absence of agency or fund presence or absence of agency or fund REA + REF REA + REF REA, no REF REA, no REF REF, no REA REF, no REA no REF, no REA no REF, no REA 0 5 10 15 0 5 10 15 percentage of rural connections growth in percentage of rural connections Source: Eberhard and others 2008. Note: REA = rural electrification agency; REF = rural electrification fund. Annual growth in new connections may seem high but comes off a low base; the overall percentage increase in households with access remains low. Widening Connectivity and Reducing Inequality 109 Figure 5.4 Countries’ Rural Electrification Rates by Percentage of Urban Population 100 90 80 percentage of urban population 70 60 R2 = 0.7092 50 40 30 20 10 0 0 5 10 15 20 25 30 35 40 percentage of rural connections Source: Eberhard and others 2008. Côte d’Ivoire and Ghana are examples of countries that have made good progress with a centralized approach to rural electrification. South Africa has also relied mainly on its national utility, Eskom, to undertake rural electrification, with considerable success. In contrast, countries such as Burkina Faso and Uganda have made slow progress, and rural electrifica- tion rates remain very low. These are obviously very poor countries, but it is also noteworthy that they have allowed their REFs to recruit multi- ple private companies on a project-by-project basis rather than make their national utilities responsible for extending access. Exceptions may be identified, however; for example, decentralized rural electrification has been more successful in Mali and Senegal. At first glance, the findings of the Mostert study (2008) would appear to contradict our previous findings that countries with electrification funds (and, to a lesser extent, agencies) tend to perform better in electrification. It should be noted, however, that Mostert’s categorization of countries that rely on central utilities for electrification, on the one hand, versus those with REFs and REAs, on the other, does not match the situation in many 110 Africa’s Power Infrastructure countries where the two approaches complement one another. For exam- ple, South Africa has an electrification fund, but Eskom is responsible for rural electrification. The purpose of the fund is to ring-fence subsidy sources from commercial revenue earned by the utility. Electrification funds create transparency around subsidies and thus help avoid situations where utilities face mixed social and commercial incentives. Decentralized rural electrification often makes most sense when applied to the implementation of off-grid projects and as a way of exploiting the private initiatives of small-scale entrepreneurs and moti- vated communities. Mostert (2008) cites successful examples of this approach in Ethiopia, Guinea, and Mozambique. The lesson is that it may be unrealistic to allocate responsibility for all electrification to separate electrification agencies, but that these agencies should focus mainly on minigrid or off-grid options that complement the efforts of the main util- ity charged with extending grid access. Universal access to electricity services is still many decades away for most countries in Sub-Saharan Africa. By projecting current service expan- sion rates forward and taking into account anticipated demographic growth, it is possible to estimate the year during which countries would reach universal access to each of the modern infrastructure services. The results are sobering. Under business as usual, fewer than 45 percent will reach uni- versal access to electricity in 50 years (Banerjee and others 2008). Inequitable Access to Electricity Electricity coverage in Sub-Saharan Africa is low and skewed to more affluent households. Coverage varies dramatically across households with different budget levels (figure 5.5). Among the poorest 40 percent of the population, coverage of electricity services is well below 10 percent. Conversely, the vast majority of households with coverage belong to the more affluent 40 percent of the population. In most countries, inequality of access has increased over time, which suggests that most new connec- tions have gone to more affluent households. This is not entirely surprising, given that even among households with greater purchasing power, coverage is far from universal. The coverage gap for urban electricity supply is about demand as much as supply. For electricity, the power infrastructure is physically close to 93 percent of the urban population, but only 75 percent of those connect to the service (table 5.1). As a result, approximately half the population without access to the service lives close to power infrastructure, and the Widening Connectivity and Reducing Inequality 111 Figure 5.5 For the Poorest 40 Percent of Households, Coverage of Modern Infrastructure Services Is below 10 Percent 100 percentage coverage 80 60 40 20 0 Q1 Q2 Q3 Q4 Q5 budget quintile Source: Banerjee and others 2008. Table 5.1 Proportion of Infrastructure Electricity Coverage Gap in Urban Africa Attributable to Demand and Supply Factors Percentage, population-weighted average Proportion of Decomposition of coverage gap attributed to: Access Connection Coverage Supply Demand Low-income countries 93 73 69 50 50 Middle-income countries 95 86 81 39 61 Overall 93 75 71 48 52 Source: Banerjee and others 2008. Note: Access is defined as the percentage of the population that lives physically close to infrastructure. Connec- tion is defined as the percentage of the population that connects to infrastructure when it is available. Coverage is defined as the percentage of the population that has the infrastructure service; it is essentially the product of access and connection. In calculating the distribution of the infrastructure coverage gap attributable to demand and supply factors, the connection rate of the top budget quintile in each geographical area is taken to be an upper bound on potential connection absent demand-side constraints. coverage gap is as much about demand (affordability) as supply. This phe- nomenon can often be directly observed in African cities where informal settlements flanking major road corridors lack power service even though distribution lines are running overhead. It may appear paradoxical that households do not universally take up connections to modern infrastructure services once networks become physically available, but often clear budget constraints are present. Poor 112 Africa’s Power Infrastructure households cannot afford high connection charges and rely instead on more accessible substitutes such as wood fuel, charcoal, kerosene, and bottled gas. Of course, slow progress in connections to electricity distri- bution networks cannot be explained only by demand or affordability constraints: Poorly performing utilities also have large backlogs in con- necting users who are willing to pay. The tenure status of households may also impede connection to mod- ern infrastructure services. A study of slum households in Dakar and Nairobi finds that electricity coverage is more than twice as high among owner occupiers as among tenants. Even among owner occupiers, lack of formal legal titles can also affect connection to services (Gulyani, Talukdar, and Jack 2008). Affordability of Electricity—Subsidizing the Well-Off African households get by on very limited household budgets. The aver- age African household of five persons has a monthly budget of less than $180; the range is from nearly $60 in the poorest quintile to $340 in the richest quintile (table 5.2). Thus, even in Africa’s most affluent house- holds, purchasing power is fairly modest in absolute terms. Across the spectrum, household budgets in middle-income countries are roughly twice those in low-income countries. Expenditure on infrastructure services absorbs a significant share of the nonfood budget. Most African households spend more than half of their modest budgets on food, with little left over for other items. Spending on infrastructure services (including utilities, energy, and transport) averages 7 percent of a household’s budget, though in some countries this can be 15–25 percent. As household budgets increase, infrastructure services absorb a growing share and rise from less than 4 percent among the Table 5.2 Monthly Household Budget 2002 dollars Income group Poorest Second Third Fourth Richest National quintile quintile quintile quintile quintile Overall 177 59 97 128 169 340 Low-income countries 139 53 80 103 135 258 Middle-income countries 300 79 155 181 282 609 Source: Banerjee and others 2008. Widening Connectivity and Reducing Inequality 113 poorest to more than 8 percent among the richest (figure 5.6). In terms of absolute expenditure, this difference is even more pronounced: Whereas households in the poorest quintile spend on average no more than $2 per month on all infrastructure services, households in the richest quintile spend almost $40 per month. Given such low household budgets, a key question is whether house- holds can afford to pay for modern infrastructure services. One measure of affordability is nonpayment for infrastructure services. Nonpayment directly limits the ability of utilities and service providers to expand net- works and improve services by undermining their financial strength. From household surveys, it is possible to compare for each quintile the percent- age of households that report paying for the service with the percentage of households that report using the service. Those that do not pay include clandestine collections and formal customers who fail to pay their bills. Overall, an estimated 40 percent of people connected to infrastructure services do not pay for them. Nonpayment rates range from approxi- mately 20 percent in the richest quintile to approximately 60 percent in the poorest quintile (figure 5.7). A significant nonpayment rate, even among the richest quintiles, suggests problems of payment culture along- side any affordability issues. The cost of a monthly subsistence consumption of power can range from $2 (based on a low-cost country tariff of $0.08 per kWh and an Figure 5.6 Infrastructure Services Absorb More of Household Budgets as Incomes Rise 9 40 household expenditure ($/month) 8 35 7 30 budget share (%) 6 25 5 20 4 15 3 2 10 1 5 0 0 Q1 Q2 Q3 Q4 Q5 quintile budget share household expenditure Source: Banerjee and others 2008. 114 Africa’s Power Infrastructure Figure 5.7 About 40 Percent of Households Connected Do Not Pay percentage of households 100 90 80 70 60 50 40 30 20 10 0 ile e e e e til til til til nt in in in in ui qu qu qu qu tq d d h h 1s 4t 5t 2n 3r Source: Banerjee and others 2008. absolute minimum consumption of 25 kWh) to $8 (based on a high-cost country tariff of $0.16 per kWh and a more typical modest household consumption of 50 kWh) (figure 5.8). An affordability threshold of 3 percent of household budgets gauges what utility bills might be affordable to African households. By looking at the distribution of household budgets, it is possible to calculate the percentage of households for whom such bills would absorb more than 3 percent of their budgets and thus prove unaffordable. Monthly bills of $2 are affordable for almost the entire African population. Monthly bills of $8 would remain affordable for most of the population of the middle- income African countries. In low-income countries, monthly bills of $8 would remain perfectly affordable for the richest 20–40 percent of the population, the only ones enjoying access. They would not be affordable, however, for the poorest 60–80 percent that currently lack access if services were extended to them. The affordability problems associated with a universal access policy would be particularly great for a handful of the poorest low-income countries— Burundi, the Democratic Republic of Congo, Ethiopia, Guinea-Bissau, Malawi, Niger, Tanzania, and Uganda—where as much as 80 percent of the population would be unable to afford a monthly bill of $8. Detailed analysis of the effect of significant tariff increases of 40 percent for power in Mali and Senegal confirms that the immediate poverty impact on consumers is small, because very few poor consumers are con- nected to the service. However, broader poverty impacts may be seen as Widening Connectivity and Reducing Inequality 115 Figure 5.8 Subsistence Consumption Priced at Cost Recovery Levels Ranges from $2 to $8 more than 5% of their monthly budget percentage of households spending 100 90 80 70 60 50 40 30 20 10 0 2 4 6 8 10 12 14 16 $ per month upper bound for subsistence consumption lower bound for subsistence consumption low-income countries middle-income countries Source: Banerjee and others 2008. the effects of higher power prices work their way through the economy, and these second-round effects on wages and prices of goods in the econ- omy as a whole can be more substantial (Boccanfuso, Estache, and Savard 2009; Boccanfuso and Savard 2000, 2005). Notwithstanding these findings, tariffs for power are heavily subsidized in most African countries. On average, power tariffs recover only 87 per- cent of full costs. The resulting implicit service subsidies amount to as much as $3.6 billion a year, or 0.56 percent of Africa’s gross domestic product (GDP) (Foster and Briceño-Garmendia 2009). Moreover, these subsidies largely bypass low-income households not even connected to services. Tariff structure design could help subsidize con- sumption by poor households (box 5.2). However, usually most of the resulting subsidy benefits the nonpoor. Because electricity subsidies are typ- ically justified by the need to make services affordable to low-income households, a key question is whether subsidies reach such households. Results across a number of African countries show that the share of subsidies going to the poor is less than half their share in the popula- tion, indicating a very pro-rich distribution (figure 5.9). This result is hardly surprising given that connections to power services are already highly skewed toward more affluent households. This targeting compares 116 Africa’s Power Infrastructure Box 5.2 Residential Electricity Tariff Structures in Sub-Saharan Africa Electricity tariff structures often take the form of increasing block tariffs (IBTs) in which a lower unit price is charged within the first consumption block and higher prices in subsequent consumption blocks. In contrast, decreasing block tariffs (DBTs) have lower unit charges for higher consumption-level blocks. Electricity tariff structures can also be linear, where the first unit of electricity consumed costs the same as the last unit consumed. Block tariff schemes are commonly supplemented by fixed charges; the combination is known as two-part electricity tariffs. The fixed charge is usually determined by the level of development of the network, the location, service costs, and—when subsidization practice applies—the purchasing power of the consumer. Two-thirds of the prevailing electricity tariff structures in Sub-Saharan Africa are IBTs, and one-third are single block or linear rates. The use of linear rates is more common in countries with prepayment systems such as Malawi, Mozambique, and South Africa. About half the countries in Africa have adopted two-part tariffs that combine fixed charges with block energy pricing. The conventional regulatory wisdom is that IBTs are designed as “lifeline” or “baseline” tariffs trying to align the first block of low consumption to a subsidized tariff and higher levels of consumption to higher pricing that would ultimately allow for cost recovery. This assumes that poorer customers will have lower con- sumption levels. This is a reasonable assumption in the power sector, where con- sumption is correlated with ownership of power-consuming devices, more of which are owned by wealthier households. Two-thirds of African countries define the first block at 50 kWh/month or less. Countries in this group include Uganda, at 15 kWh/month; Cape Verde and Côte d’Ivoire, at 40 kWh/month; and Burkina Faso, Cameroon, Ethiopia, Kenya, and Tanzania, at 50 kWh/month. The Democratic Republic of Congo and Mozambique also define a modest threshold level for their first block (100 kWh). Ghana and Zambia have a large first block (300 kWh). Source: Briceño-Garmendia and Shkaratan 2010. Widening Connectivity and Reducing Inequality 117 Figure 5.9 Electricity Subsidies Do Not Reach the Poor Nigeria Gabon Congo Côte d’Ivoire Cape Verde Togo São Tomé and Príncipe Senegal Cameroon Mozambique Ghana Central African Republic Guinea Burundi Burkina Faso Chad Malawi Uganda Rwanda 0 0.2 0.4 0.6 0.8 1.0 measure of distributional incidence of subsidies Source: Banerjee and others 2008; Wodon 2007a, b. Note: A measure of distributional incidence captures the share of subsidies received by the poor divided by the proportion of the population in poverty. A value greater than one implies that the subsidy distribution is progres- sive (pro-poor), because the share of benefits allocated to the poor is larger than their share in the total popula- tion. A value less than one implies that the subsidy distribution is regressive (pro-rich). unfavorably with other areas of social policy. To put these results in per- spective, it is relevant to compare them with the targeting achieved by other forms of social policy. Estimates for Cameroon, Gabon, and Guinea indicate that expenditures on primary education and basic health care reach the poor better than power subsidies (Wodon 2007a). Can African governments afford to further expand today’s subsidy model to achieve universal access? There is little justification for utility subsidies at present given that they do not typically reach unconnected low-income households and that more affluent connected households do not need subsidies to afford the service. However, the preceding analysis indicated that affordability would become a major issue to the extent that 118 Africa’s Power Infrastructure Africa’s low-income countries move aggressively toward universal access. Given the very high macroeconomic cost today of subsidizing even the minority of the population with access to power, it is legitimate to ques- tion whether African governments can afford to scale up this subsidy- based model to the remainder of their populations. Providing universal use of service, subsidies of $2 per household would absorb 1.1 percent of GDP over and above existing spending. This amount is high in relation to existing operations and maintenance expen- diture, so it is difficult to believe that it would be affordable (figure 5.10). The cost of providing a one-time capital subsidy of $200 to cover net- work connection costs for all unconnected households over 20 years would be substantially lower at 0.35 percent of GDP. A key difference is that the cost of this one-time subsidy would disappear at the end of the decade, whereas the use of a service subsidy would continue indefinitely. The welfare case is quite strong for one-time capital subsidies to sup- port universal connection. This is generally the most effective means of subsidizing the poor. Direct grants could also be made to indigent house- holds, but effective targeting is difficult and administration complex. Cross-subsidies can also be achieved through the design of tariff struc- tures that allow for lower rates for a “lifeline” amount of electricity usage for poor households. AICD data across a number of African countries Figure 5.10 Subsidy Needed to Maintain Affordability of Electricity Ongoing use of service subsidy One-time connection subsidy 1.2 1.2 1.0 1.0 percentage of GDP percentage of GDP 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0.0 0.0 electricity electricity operating subsidy needed to capital subsidy needed to maintain affordability maintain affordability O&M spending (2005) capital spending (2005) Source: Banerjee and others 2008. Note: GDP = gross domestic product; O&M = operations and maintenance. Widening Connectivity and Reducing Inequality 119 suggest that many current tariff structures are poorly designed. High fixed charges may inhibit affordability. The level and scope of the lifeline block in IBTs may also be inappropriate, giving too small a benefit to the poor. Alternatively, “pro-poor” tariffs may be poorly targeted and benefit wealthier consumers if the lifeline block is available too widely. It is well known that households without access to utility services end up paying much higher prices, which limits their energy consumption to very low levels. The cost of providing basic illumination through candles is much more costly than electricity per effective unit of lighting. Nonmonetary benefits of connection can also be very significant. Beyond the potential monetary savings, electricity coverage is associated with a wide range of health, education, and productivity benefits. For example, better electricity provision improves literacy and primary school comple- tion rates, because better-quality light allows students to read and study in the absence of sunlight. Policy Challenges for Accelerating Service Expansion The business-as-usual approach to expanding service coverage in Africa does not seem to be working. The low and stagnant coverage of house- hold services comes with a major social and economic toll. Under the business-as-usual approach, most African countries have tackled univer- sal access by providing heavily subsidized services. This approach has tended to bankrupt and debilitate sector institutions without bringing about any significant acceleration of coverage. Furthermore, the associ- ated public subsidies have largely bypassed most needy groups. Few serv- ices and countries are expanding coverage at rates high enough to outstrip demographic growth, particularly urbanization. Reversing this situation will require rethinking the approach to service expansion in four ways. First, coverage expansion is not just about net- work rollout. There is a need to address demand-side barriers such as high connection charges or legal tenure. Second, it is important to remove unnecessary subsidies to improve cost recovery for household services and ensure that utilities have the financial basis to invest in service expan- sion. Third, it is desirable to rethink the design of utility subsidies to tar- get them better and to accelerate service expansion. Fourth, progress in rural electrification cannot rely only on decentralized options; it requires a sustained effort by national utilities supported by systematic planning and dedicated REFs. 120 Africa’s Power Infrastructure Don’t Forget the Demand Side of the Equation Overlooking the demand side of network rollout can lead to much lower returns on infrastructure investments. The challenge of reaching universal access is typically considered a supply problem of rolling out infrastruc- ture networks to increasingly far-flung populations. Household survey evidence shows, however, that in urban areas, a significant segment of the unserved population lives close to a network. The lower the connection rate to existing infrastructure networks, the lower the financial, economic, and social returns to the associated invest- ment, because the physical asset is operating below its full carrying capac- ity. This finding has five implications for network rollout strategy. First, connection, rather than access, needs to be considered the key measure of success. Projects that aim to expand service coverage too often measure their outcomes by the number of people who can connect to the network provided. As a result, little attention is given to whether these connections materialize after the project. Unless the focus of monitoring and evaluation shifts from access to connection, those involved in project implementation will have little incentive to think about the demand side of service coverage. Second, the most cost-effective way of increasing coverage may be to pursue densification programs that aim to increase connection rates in targeted areas. Unserved populations living physically close to infrastruc- ture networks could (in principle) be covered at a much lower capital cost than those living farther away, providing the highest potential return to a limited investment budget. In that sense, they may deserve priority attention in efforts to raise coverage. Third, expanding coverage is not just about network engineering—it requires community engagement. Dealing with the demand-side barriers preventing connection requires a more detailed understanding of the util- ity’s potential client base. What are their alternatives? How much can they afford to pay? What other constraints do they face? This, in turn, suggests a broader skill base than utilities may routinely engage, one that goes beyond standard expertise in network engineering to encompass sociological, economic, and legal analysis of—and engagement with—the target populations. Fourth, careful thought should be given to how connection costs might be recovered. As noted previously, Africa’s widespread high connection charges are one obvious demand-side barrier to connection, even when use-of-service charges would be affordable. In these circumstances, it is legitimate to ask whether substantial, one-time, upfront connection Widening Connectivity and Reducing Inequality 121 charges are the most sensible way to recover the costs of making network connections. Alternatives can be considered, including repaying connec- tion costs over several years through an installment plan, socializing con- nection costs by recovering them through the general tariff and hence sharing them across the entire customer base, or directly subsidizing them from the government budget. Fifth, expansion of utility networks needs to be closely coordinated with urban development. In many periurban neighborhoods, expanding utility networks is hampered by the absence of legal tenure and high rates of tenancy, not to mention inadequate spacing of dwellings. Providing services to these communities will require close cooperation with urban authorities, because many of these issues can be resolved only if they are addressed in a synchronized and coordinated manner. Take a Hard-headed Look at Affordability Underrecovery of costs has serious implications for the financial health of utilities and slows the pace of service expansion. Many of Africa’s power utilities capture only two-thirds of the revenue they need to function sus- tainably. This revenue shortfall is rarely covered through timely and explicit fiscal transfers. Instead, maintenance and investment activities are cut back to make ends meet, which starves the utility of funds to expand service coverage and cuts the quality of service to existing customers. Affordability, the usual pretext for underpricing services, does not bear much scrutiny. The political economy likely provides the real explanation for low tariffs: Populations currently connected to utility services tend to be those with the greatest voice. The implicit subsidies created by under- pricing are extremely pro-rich in their distributional incidence. In all but the poorest African countries, service coverage could be substantially increased before any real affordability problems would be encountered. In the poorest of the low-income countries, affordability is a legitimate concern for the bulk of the population and would constrain universal cov- erage. Even in the poorest countries, however, recovering operating costs should be feasible, with subsidies limited to capital costs. What effect would removing utility subsidies have on reducing poverty? For most countries, electricity spending accounts for only a tiny fraction of total consumption. At the national level, the impact of a 50 percent increase in tariffs or even of a doubling of tariffs is marginal; the share of the population living in poverty increases barely one-tenth of a percentage point. Among households with a connection to the network, the impact is larger but still limited. Indeed, rarely is there more than a one or two 122 Africa’s Power Infrastructure percentage point increase in the share of households in poverty. Because the households that benefit from a connection tend to be richer than other households, the increase in poverty starts from a low base. So the small impact of an increase in tariffs on poverty could be offset by reallocating utility subsidies to other areas of public expenditure with a stronger pro- poor incidence. Tariff increases can be either phased in gradually or effected instantly through a one-time adjustment. Both approaches have advantages and disadvantages. The public acceptability of tariff increases can be enhanced if they form part of a wider package of measures that includes service quality improvements. One way to strengthen social accountability is to have communication strategies link tariffs with service delivery standards and suggest conservation measures to contain the overall bills. Either way, it is perhaps most important to ensure that the realignment of tariffs and costs is not temporary by providing for automatic indexing and periodic revisions of tariffs. In the absence of a strong payment culture, customers who object to tariff hikes may refuse to pay their bills. Therefore, even before addressing tariff adjustments, it is important for utilities to work on raising revenue collection rates toward best practice levels and establishing a payment cul- ture. At least for power, one technological solution is to use prepayment meters, which place customers on a debit card system similar to that used for cellular telephones. For utilities, this eliminates credit risk and avoids nonpayment. For customers, this allows them to control their expenditure and avoid consuming beyond their means. South Africa was at the fore- front in development of the keypad-based prepayment electricity meter with the first product, called Cashpower, launched by Spescom in 1990. Tshwane, also in South Africa, reports universal coverage of its low-income consumers with prepayment meters. In Lesotho, Namibia, and Rwanda, a majority of residential customers are on prepayment meters. In Ghana and Malawi, a clear policy has been pursued of rapidly increasing the share of residential customers on prepayment meters (figure 5.11). Target Subsidies to Promote Service Expansion Subsidies have a valuable and legitimate role in the right circumstances. They may be appropriate when households genuinely cannot purchase a subsistence allowance of a service that brings major social and economic benefits to them and those around them, as long as governments can afford to pay those subsidies. However, utility subsidies’ design and targeting needs to be radically improved to fulfill their intended role. Widening Connectivity and Reducing Inequality 123 Figure 5.11 Prepayment Metering Tshwane LEC NORED ESKOM ELECTROGAZ VRA Escom Sonabel SBEE TANESCO 0 10 20 30 40 50 60 70 80 90 100 percentage of residential customers with prepayment meters Source: Foster and Briceño-Garmendia 2009. As noted previously, the utility subsidies practiced in Africa today largely bypass the poor. African utilities typically subsidize consumption, but subsidizing con- nection is potentially more equitable and effective in expanding coverage. The affordability problems associated with connection charges are often much more serious than those associated with use-of-service charges. Given that connections are disproportionately concentrated among the more affluent, the absence of a connection is disproportionately concen- trated among the poorest. This could make the absence of a connection a good targeting variable. Where coverage is far from universal even among the higher-income groups, who will likely be the first to benefit from coverage expansion, connection subsidies may be just as pro-rich as consumption subsidies. Simulations suggest that the share of connection subsidies going to the poor would be only about 37 percent of the share of the poor in the pop- ulation; this is a highly pro-rich result no better than that of existing con- sumption subsidies (table 5.3). Limiting subsidies to connections in new network rollout as opposed to densification of the existing network would substantially improve tar- geting. The share of connection subsidies going to the poor would rise to 124 Africa’s Power Infrastructure Table 5.3 Potential Targeting Performance of Electricity Connection Subsidies under Various Scenarios Scenarios Targeting performance 1. New connections mirror pattern of existing connections 0.37 2. Only households beyond reach of existing network receive connection subsidies 0.95 3. All unconnected households receive subsidy 1.18 Source: Banerjee and others 2008; Wodon 2007a, b. Note: A measure of distributional incidence captures the share of subsidies received by the poor divided by the proportion of the population in poverty. A value greater than one implies that the subsidy distribution is progressive (pro-poor), because the share of benefits allocated to the poor is larger than their share in the total population. A value less than one implies that the subsidy distribution is regressive (pro-rich). 95 percent of their share in the population, but the outcome would remain pro-rich. Providing a connection subsidy equally likely to reach all unconnected households would ensure that the percentage going to the poor exceeds their share of the population by 118 percent. This strategy ultimately achieves a progressive result. To improve the distributional incidence beyond this modest level would require connection subsidies to be accompanied by other socioeconomic screens. In the low-access envi- ronment in most African countries, the absence of a connection remains a fairly weak targeting variable. Can anything be done to improve the impact of use-of-service subsi- dies? The poor performance of existing utility subsidies is explained partly by pro-rich coverage but also by the widespread use of poorly designed IBTs. Common design failures in power IBTs include large sub- sistence thresholds, so that only consumers with exceptionally high con- sumption contribute fully to cost recovery (Briceño-Garmendia and Shkaratan 2010). Some improvements in targeting could be achieved by eliminating fixed charges, reducing the size of first blocks to cover only genuinely subsistence consumption, and changing from an IBT to a volume-differentiated tariff where those consuming beyond a certain level forfeit the subsidized first block tariff completely. Even with these modifications, however, the targeting of such tariffs would improve only marginally and would not become strongly pro-poor in absolute terms. Global experience suggests that utility subsidy targeting can be improved and become reasonably progressive if some form of geographi- cal or socioeconomic targeting variables can be used beyond the level of consumption (Komives and others 2005). Such targeting schemes hinge, however, on the existence of household registers or property cadastres Widening Connectivity and Reducing Inequality 125 that support the classification of beneficiaries, as well as a significant amount of administrative capacity. Both factors are often absent in Africa, particularly in the low-income countries. Utility service underpricing that benefits just a small minority of the population costs many African countries as much as 1 percent of GDP. As countries move toward universal access, that subsidy burden would increase proportionately and rapidly become unaffordable for the national budget. So countries should consider how the cost of any pro- posed subsidy policy would escalate as coverage improves. This test of a subsidy’s fiscal affordability is an important reality check that can help countries avoid embarking on policies that are simply not scalable. One other potentially effective method of targeting is to limit the allocation of subsidies to lower-cost and lower-quality alternatives that encourage self-selection, such as load-limited supplies. The theory is that more affluent customers will eschew second-best services and automatically select to pay the full cost of the best alternative, thus identifying themselves and leaving the subsidized service to less afflu- ent customers. Systematic Planning Is Needed for Periurban and Rural Electrification As already noted, the majority of the population in Sub-Saharan Africa still resides in rural areas. Some countries have a much higher potential for making rural electrification advances more cost effective, because a higher proportion of their population lives close to existing networks (figure 5.12). Thus Benin, Ghana, Lesotho, Rwanda, Senegal, and Uganda are more favorably positioned than, for example, Burkina Faso, Chad, Madagascar, Mozambique, Niger, Tanzania, or Zambia. The potential for extending access in a given situation depends on pop- ulation density, distance from the grid, economic activity, and developmen- tal needs. Because those circumstances differ widely across regions and countries, the most successful rural electrification will be selective, detailed, and carefully planned. Data show that those countries with clear planning criteria have generally been more successful at rural electrification. Given the scale of investments needed, a systematic approach to plan- ning and financing new investments is critical. The current project- by-project, ad hoc approach in development partner financing has led to fragmented planning, volatile and uncertain financial flows, and duplica- tion of efforts. Engagement across the sector in multiyear programs of access rollout supported by multiple development partners as part of a 126 Africa’s Power Infrastructure Figure 5.12 Potential Rural Access: Distribution of Population by Distance from Substation 100 90 80 percentage of rural population 70 60 50 40 30 20 10 0 in nin m o n m d . Et ire Gh a a Le ya o am ar M e Na wi ia Ni er Rw ria Se da l a Ta an Ug ia Za da a te ep ut ga i an ric bi qu Ca as ad th oo De a op ib an oz sc g n a d ge Ch an an o Cô . R So ne m Be Ni aF M so al Af Ke m Su Iv bi er M aga nz hi d’ h rk Bu o, ng Co < 10 km from substation or < 5 km from MV line 10–20 km from substation 20–50 km from substation > 50 km from substration or < 10 km from lit urban area > 50 km from substation and > 10 km from lit urban area Source: Eberhard and others 2008. Note: Transmission lines are not available for Chad or Niger, so “remote” potential service area is overestimated. coherent national strategy will channel resources in a more sustained and cost-effective way to the distribution subsector. Coordinated action by development partners will also reduce the unit costs of increasing access by achieving economies of scale in implementation. Countries with dedicated REFs have achieved higher rates of electrifi- cation than those without. Of greatest interest, however, are the differ- ences among the countries that have funds. Case studies indicate that the countries that have taken a centralized approach to electrification—with the national utility made responsible for extending the grid—have been more successful than those that followed decentralized approaches. Undoubtedly, those REAs that have attempted to recruit multiple utilities or private companies into the electrification campaign have a contribution to make (see box 5.3), especially in promoting minigrids and off-grid options. These should be seen, however, as complementary to the main utility’s efforts to extend the grid. Widening Connectivity and Reducing Inequality 127 Box 5.3 Rural Electrification in Mali Among new rural electrification agencies created in Africa, Mali’s AMADER (Agence Malienne pour le Developpement de l’Energie Domestique et d’Electri- fication Rurale) has had considerable success. In Mali, only 13 percent of the rural population has access to electricity. Until they are connected, most rural house- holds meet their lighting and small power needs with kerosene, dry cell, and car batteries, with an average household expenditure of $4–$10 per month. About half of Mali’s 12,000 villages have a school or health center clinic or both; however, most are without any form of energy for lighting or for operating equipment. The majority of Malians—more than 80 percent—use wood or charcoal for cooking and heating. The use of these sources of energy make the poor pay about $1.50 per kWh for energy, more than 10 times the price of a kilowatt-hour from the grid. In addition to rural electrification, AMADER promotes community-based wood- land management to ensure sustainable wood fuel supply. It also has interfuel substitution initiatives and programs for the introduction of improved stoves. AMADER, created by law in 2003, employs two major approaches to rural elec- trification: spontaneous “bottom-up” electrification of specific communities and planned “top-down” electrification of large geographic areas. To date, the bottom- up approach, which typically consists of minigrids operated by small local private operators, has been more successful. Eighty electrification subprojects managed by 46 operators are financed so far through the bottom-up approach. By late December 2009, connections had been made to more than 41,472 households, 803 community institutions, 172 schools, and 139 health clinics. Typically, AMADER provides grants for 75 percent of the start-up capital costs of rural elec- trification subprojects, depending on the proposed connection target within the first two years, the average cost per connection, and the average tariff. Most of the bottom-up rural electrification subprojects are based on conven- tional, diesel-fueled minigrids with installed generation capacities mainly below 20 kilowatts. Customers on these isolated minigrids typically receive electricity for six to eight hours daily. In promoting these new projects, AMADER performs three main functions. It is a provider of grants, a supplier of engineering and commercial technical assistance, and a de facto regulator through its grant agreements with operators. The grant agreement can be viewed as a form of “regulation by contract,” because it establishes minimum standards for technical and commercial quality of service and maximum tariffs allowed for both metered and unmetered customers. (continued next page) 128 Africa’s Power Infrastructure Box 5.3 (continued) Renewable energy technologies, particularly solar photovoltaics, have been successfully introduced into Mali’s rural energy mix. Over a period of six years, more than 7,926 solar home systems and more than 500 institutional solar photo- voltaic systems were installed countrywide. A solar power station of 72 kW peak solar photovoltaic plant connected to an 8 kilometer distribution network in the village of Kimparana, the first of its type and scale in West Africa, has been opera- tional since 2006. It is providing power to about 500 households, community institutions, and microenterprises. Biofuels are also being promoted for electricity production in the village of Garalo in partnership with the Mali Folkecenter, a local nongovernmental organization (NGO). Women’s associations are also playing an important role in remote communi- ties as providers of energy services. They manage some of the multifunctional platforms after receiving training in basic accounting in local languages provided by NGOs financed through the project. To date, multifunctional platforms have been installed in 64 communities and have resulted in 7,200 connections. A mul- tifunctional platform is composed of a small 10 kW diesel engine coupled to a generator. The platform can be connected to income-generating equipment, such as cereal grinding mills, battery chargers, dehuskers, and water pumps. AMADER has added public lighting networks of about 2 kilometers to the multi- functional platforms in about 35 communities. To ensure that the projects are financially sustainable, AMADER permits operators to charge residential and commercial cost-reflective tariffs that are often higher than the comparable tariffs charged to grid-connected customers. For example, the energy charge for metered residential customers on isolated minigrids is about 50 percent higher than the comparable energy charge for grid-connected residential customers served by EDM (Electricidade de Moçambique, the national electric util- ity). Many of the minigrid operators also provide service to unmetered customers. Unmetered customers are usually billed on a flat monthly charge per light bulb and power outlet, combined with load-limiting devices, to ensure that a customer does not connect appliances above and beyond what he or she has paid for. To reduce financial barriers for operators, leasing arrangements have been proposed, as well as a loan guarantee program for Malian banks and microfinance institutions that would be willing to provide loans to potential operators and newly connected customers to increase productive energy uses. Work is ongoing to attract private operators to larger concessions and to increase the share of renewable energies in Mali’s rural energy mix. Source: Interviews with World Bank staff from the Africa Energy Department, 2008. Widening Connectivity and Reducing Inequality 129 In an African context, it is legitimate to ask how far it is possible to make progress with rural electrification when the urban electrification process is still far from complete. Across countries, a strong correlation is found between urban and rural electrification rates, as well as a system- atic lag between the two. Countries with seriously underdeveloped gen- eration capacity and tiny urban customer bases are not well placed to tackle the challenges of rural electrification, either technically because of power shortages or financially because of the lack of a basis for cross- subsidization. Dedicated electrification funds should thus also be made available for periurban connections. It is also important to find ways to spread the benefits of electrifica- tion more widely, because universal household electrification is still decades away in many countries. Sectorwide programmatic approaches must ensure that the benefits of electrification touch even the poorest households that are too far from the grid or unable to pay for a grid con- nection. Street lighting may be one way to do this in urban areas. In rural areas, solar-powered electrification of clinics and schools that provide essential public services to low-income communities is one way to allow them to participate in the benefits of electrification. Another way is appropriate technology, such as low-cost portable solar lanterns that are much more accessible and affordable to the rural public. The “Lighting Africa” initiative is supporting the development of the market for such products. Finally, the difficult question needs to be posed as to whether aggres- sive electrification will exacerbate the financial problems of the sector. Diverting scarce capital to network expansion can easily result in a familiar situation where investments barely generate adequate revenue to support operating and maintenance costs, with no contribution to refurbishment or capital-replacement requirements. The resulting cash drains on the utility could be serious. Ultimately, difficult choices need to be made on how to allocate scarce capital. Should it go to network expansion, or are investments in new generation capacity more impor- tant? In either case, careful tradeoffs will be required. References Banerjee, Sudeshna, Quentin Wodon, Amadou Diallo, Taras Pushak, Hellal Uddin, Clarence Tsimpo, and Vivien Foster. 2008. “Access, Affordability and Alternatives: Modern Infrastructure Services in Sub-Saharan Africa.” Background Paper 2, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. 130 Africa’s Power Infrastructure Boccanfuso, Dorothée, Antonio Estache, and Luc Savard. 2009. “Distributional Impact of Developed Countries’ CC Policies on Senegal: A Macro-Micro CGE Application.” Cahiers de Recherche 09-11, Department of Economics, Faculty of Administration, University of Sherbrooke, Quebec, Canada. Boccanfuso, Dorothée, and Luc Savard. 2000. “The Food Crisis and Its Impact on Poverty in Senegal and Mali: Crossed Destinies.” GREDI, Working Paper 08- 20, University of Sherbrook, Quebec, Canada. ———. 2005. “Impact Analysis of the Liberalization of Groundnut Production in Senegal: A Multi-Household Computable General Equilibrium Model.” Cahiers de Recherche 05-12, Department of Economics, Faculty of Administration, University of Sherbrooke, Quebec, Canada. Briceño-Garmendia, Cecilia, and Maria Shkaratan. 2010. “Power Tariffs: Caught between Cost Recovery and Affordability.” Working Paper 20, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Clark, Alix, Mark Davis, Anton Eberhard, and Njeri Wamakonya. 2005. “Power Sector Reform in Africa: Assessing the Impact on Poor People.” ESMAP Report 306/05, World Bank, Washington, DC. Eberhard, Anton, Vivien Foster, Cecilia Briceño-Garmendia, Fatimata Ouedraogo, Daniel Camos, and Maria Shkaratan. 2008. “Underpowered: The State of the Power Sector in Sub-Saharan Africa.” Background Paper 6, Africa Infrastructure Sector Diagnostic, World Bank, Washington, DC. ESMAP (Energy Sector Management Assistance Program). 2007. “Technical and Economic Assessment of Off-Grid, Mini-Grid and Grid Electrification Technologies.” ESMAP Technical Paper 121/07, World Bank, Washington, DC. Foster, Vivien, and Cecilia Briceño-Garmendia, eds. 2009. Africa’s Infrastructure: A Time for Transformation. Paris, France, and Washington, DC: Agence Française de Développement and World Bank. Gulyani, S., D. Talukdar, and D. Jack. 2008. “A Tale of Three Cities: Understanding Differences in Provision of Modern Services.” Working Paper 10, African Infrastructure Country Diagnostic, World Bank, Washington, DC. Komives, Kristin, Vivien Foster, Jonathan Halpern, and Quentin Wodon. 2005. Water, Electricity, and the Poor: Who Benefits from Utility Subsidies? Washington, DC: World Bank. Marquard, A., B. Bekker, A. Eberhard, and T. Gaunt. 2008. “South Africa’s Electrification Programme: An Overview and Assessment.” Energy Policy 36: 3125–37. Mostert, W. 2008. “Review of Experience with Rural Electrification Agencies: Lessons for Africa.” EU Energy Initiative Partnership Dialogue Facility, Eschborn, Germany. Widening Connectivity and Reducing Inequality 131 Wodon, Quentin, ed. 2007a. “Electricity Tariffs and the Poor: Case Studies from Sub-Saharan Africa.” Working Paper 11, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. ———. 2007b. “Water Tariffs, Alternative Service Providers, and the Poor: Case Studies from Sub-Saharan Africa.” Working Paper 12, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. CHAPTER 6 Recommitting to the Reform of State-Owned Enterprises Most electricity utilities in Sub-Saharan Africa are state owned. Yet most of them are inefficient and incur significant technical and commercial losses. Hidden costs abound in the sector: network energy losses, under- pricing, poor billing and collections practices resulting in nonpayment and theft, and overstaffing all absorb revenue that could be used for main- tenance and system expansion. Evidence suggests that reforms in the governance of state-owned enterprises (SOEs) could reduce hidden costs. This has even happened in some African countries. Data gathered by the Africa Infrastructure Country Diagnostic show that those enterprises that have implemented more governance reforms have benefited from improved performance. No single reform will be sufficient to effect lasting improvements in performance. Rather, an integrated approach to governance reform is needed. Roles and responsibilities need to be clarified, which will involve clear identification, separation, and management of government’s differ- ent roles in policy making, ownership of utility assets, and regulation. Roles and responsibilities can further be clarified through public entity legislation, corporatization, codes of corporate governance, performance contracts, effective supervisory and monitoring agencies, and transparent transfers for social programs. 133 134 Africa’s Power Infrastructure Another broad set of reforms involves strengthening the role of interest groups with a stake in more commercial behavior—for example, taxpay- ers, customers, and private investors. This can be promoted through direct competition, improved transparency and information, and commercializa- tion practices such as outsourcing, mixed-capital enterprises, and struc- tural reform. Hidden Costs in Underperforming State-Owned Enterprises The previous chapters have highlighted the deficits of the power sector in Africa. Not only is there insufficient generating capacity, but also national utilities have performed poorly both financially and technically. Average distribution losses in Africa are 23 percent compared with the commonly used norm of 10 percent or less in developed countries. Moreover, average collection rates are only 88.4 percent compared with best practice of 100 percent. Underpricing and inefficiency generate substantial hidden costs for the region’s economy. Combining the costs of distribution losses and uncol- lected revenue and expressing them as a percentage of utility turnover provides a measure of the inefficiency of utilities (figure 6.1). The ineffi- ciency of the median utility is equivalent to 50 percent of turnover, which means that only two-thirds of revenue is captured. The inefficiency of the utilities creates a fiscal drain on the economy, because governments must frequently cover any operating deficit to prevent the utility from becom- ing insolvent. Inefficiencies also seriously undermine the utilities’ future perform- ance. Utility managers with operating deficits are often forced to forgo maintenance. Inefficient operation has a similar adverse effect on investment. For example, countries with below-average efficiency have increased electrification rates by only 0.8 percent each year, compared with 1.4 percent for utilities with above-average efficiency. Less effi- cient utilities also have greater difficulty in meeting demand for power. In countries with utilities of below-average efficiency, suppressed or unmet power demand accounts for 12 percent of total demand, com- pared with only 6 percent in countries with utilities of above-average efficiency (figure 6.2). Chapter 7 explores more quantitative measures of inefficiency and hidden costs and their effect on funding requirements. Recommitting to the Reform of State-Owned Enterprises 135 Figure 6.1 Overall Magnitude of Utility Inefficiencies as a Percentage of Revenue Congo, Dem. Rep. Côte d’Ivoire Nigeria Congo, Rep. Niger Ghana Uganda Mali Malawi Botswana Cape Verde Namibia Cameroon Tanzania Mozambique Chad Ethiopia Benin Burkina Faso Lesotho Rwanda Senegal Kenya Zambia 0 10 20 30 40 50 60 70 80 90 100 percentage of revenue system losses collection inefficiencies overstaffing Source: Briceño-Garmendia and Shkaratan 2010. Driving Down Operational Inefficiencies and Hidden Costs Countries that have made progress in power sector reform, including regulatory reform, have substantially lower hidden costs (figure 6.3). In particular, private sector participation and the adoption of contracts with performance incentives by state-owned utilities appear to substantially reduce hidden costs. The case of Kenya Power and Lighting Company (KPLC) is particularly striking (box 6.1). Over the years, countries have spent substantial sums on institutional reforms in the power sector, including management training, improved internal accounting and external auditing, improved boards of directors, financial and operational information and reporting systems, and estab- lishment and strengthening of supervisory and regulatory agencies. Some 136 Africa’s Power Infrastructure Figure 6.2 Effect of Utility Inefficiency on Electrification and Suppressed Demand a. Impact on pace of electrification 1.6 1.4 annualized increase in access to power (%) 1.2 1.0 0.8 0.6 0.4 0.2 0.0 high efficiency low efficiency b. Impact on magnitude of suppressed demand 16 14 supressed demand as % of 12 generation 10 8 6 4 2 0 high efficiency low efficiency Source: Derived from Eberhard and others 2008. successes have endured (see box 6.2), but in many other cases reforms have not had the intended effect. Effect of Better Governance on Performance of State-Owned Utilities Evidence is increasing that governance reform can improve the perform- ance of state-owned utilities. Governance may be assessed using various criteria, including ownership and shareholder quality, managerial and board autonomy, accounting standards, performance monitoring, out- sourcing to the private sector, exposure to labor markets, and the disci- pline of capital markets (Vagliasindi 2008). Recommitting to the Reform of State-Owned Enterprises 137 Figure 6.3 Impact of Reform on Hidden Costs in the Power Sector in Sub-Saharan Africa high reform high regulation high governance management contract or concession performance contracts with incentives present 0 50 100 150 200 250 300 350 400 average hidden cost of inefficiencies as percentage of utility revenue yes no Source: Eberhard and others 2008. Good governance is not universal among Sub-Saharan Africa utilities (figure 6.4). The most prevalent good governance practices are those relat- ing to managerial autonomy. Most utilities report requirements to be prof- itable and pay market rates for debt, but the vast majority benefit from sizeable subsidies and tax breaks and are not financially sound enough to borrow. Only 60 percent of the sample utilities publish audited accounts, and stock exchange listing is virtually unheard of (Kengen and KPLC in Kenya are the exceptions). Overall, most utilities in the sample meet only about half of the criteria for good governance. A comparison of utilities based on 35 governance indicators provides striking and consistent evidence that good governance improves utility performance (figure 6.5). Making State-Owned Enterprises More Effective Two broad sets of governance reforms are important to ensure that improvements to the performance of state-owned utilities are sustainable. First, roles and responsibilities need to be clarified. This involves clear identification, separation, and management of government’s different roles in policy making, ownership of utility assets, and regulation of prices and quality of utility services. Roles and responsibilities can further be 138 Africa’s Power Infrastructure Box 6.1 Kenya’s Success in Driving Down Hidden Costs In the early 2000s, hidden costs in the form of underpricing, collection losses, and distribution losses on the part of Kenya’s power distribution utility (KPLC) absorbed as much as 1.4 percent of Kenya’s gross domestic product (GDP) per year. Management reforms resulted in revenue collection improvement—from 81 percent in 2004 to 100 percent in 2006. Distribution losses also began to fall, though more gradually, which reflected the greater technical difficulty they posed. Power-pricing reforms also allowed tariffs to rise in line with escalating costs from $0.07 in 2000 to $0.15 in 2006 and $0.20 in 2008. As a result of reforms, hidden costs in Kenya’s power sector fell to 0.4 percent of GDP by 2006 and almost to zero by 2008 (see figure), among the lowest totals of any African country. 100 1.8 1.6 percentage of revenue 75 1.4 percentage of GDP 1.2 1.0 50 0.8 0.6 25 0.4 0.2 0 0.0 2001 2002 2003 2004 2006 2008 underpricing undercollection distribution losses total as % GDP Source: Foster and Briceño-Garmendia 2009. Note: GDP = gross domestic product. clarified through public entity legislation, corporatization, codes of corporate governance, performance contracts, effective supervisory and monitoring agencies, and transparent transfers for social programs. The second broad set of reforms revolves around what Gomez- Ibanez (2007, 33–48) refers to as “changing the political-economy of an SOE,” by which he means strengthening the role of other power-sector stakeholders, such as taxpayers, customers, and private investors. This can be promoted through improved transparency, commercialization Recommitting to the Reform of State-Owned Enterprises 139 Box 6.2 Botswana’s Success with a State-Owned Power Utility The state-owned electricity utility Botswana Power Corporation (BPC) was formed by government decree in 1970 to expand and develop electrical power potential in the country. The utility began as one power station in Gaborone with a network that extended about 45 kilometers outside the city. Since then, its responsibilities and the national network have expanded enormously. The government regulates the utility through the Energy Affairs Division of the Ministry of Minerals, Energy and Water Affairs. During the tenure of BPC, access to electricity increased to 22 percent in 2006 and is set to reach 100 percent by 2016. Government funding has allowed BPC to extend the electricity grid into rural areas. The power system is efficient, with distribution losses of less than 10 percent and a return on assets equal to its cost of capital. When capacity shortages seem likely, BPC must decide between importing power and expanding its own generation facilities. The national system, in 2005, provided 132 megawatts, and neighboring countries supplied another 266 megawatts via the Southern African Power Pool; Botswana has been an active member and major beneficiary of the regional pool since its inception in 1995. Its active trading position has helped to promote multilateral agreements and enhance cooperation among pool members. To be fair, BPC has benefited from the availability of cheap imported power from South Africa (which is now severely threatened by a power crisis there). Regardless, analysts contend that BPC’s strong performance is equally attributa- ble to institutional factors: a strong, stable economy, cost-reflective tariffs, lack of government interference in managerial decisions, good internal governance, and competent and motivated employees. Source: Molefhi and Grobler 2006. practices, structural reform, direct competition, and mixed-capital enterprises (table 6.1). Defined Roles and Responsibilities Utilities management in Sub-Saharan Africa often suffers from mixed— and sometimes contradictory—policy and governance directives and incentives. Governments can interfere with management decisions in an 140 Africa’s Power Infrastructure Figure 6.4 Incidence of Good-Governance Characteristics among State-Owned Utilities labor market discipline managerial and board autonomy overall SOE governance capital market discipline accounting, disclosure, and performance monitoring ownership and shareholder quality outsourcing 0 20 40 60 80 100 percentage of countries Source: Eberhard and others 2008. Note: SOE = state-owned enterprise. ad hoc and nontransparent manner in areas such as overstaffing and excessive salary levels. They may also pressure utilities to electrify certain areas, ignore illegal connections and nonpayment, or maintain excessively low prices. Government may also be unclear about its role as owner of the utility and the need to maintain and expand its assets. Regulation of prices and quality of service may also be arbitrary and unconnected to ensuring the financial sustainability of the utility. The combination of these nontransparent and sometimes contradictory pressures on the man- agement of the utility can be disastrous. Inevitably investment is insuffi- cient, and service quality deteriorates. These challenges can be addressed by clearly identifying, separating, and coordinating government’s different roles and functions in the sector. Clear policy statements can help clarify and make transparent government’s social, economic, and environmental objectives. Sector and public entity Recommitting to the Reform of State-Owned Enterprises 141 Figure 6.5 Effect of Governance on Utility Performance in State-Owned Power Utilities annual net electricity generated, kWh/capita connections/employee MW/million population 0 50 100 150 200 250 300 commercial efficiency cost recovery ratio urban connections T&D losses countries with emergency power generation reserve margin system capacity utilization factor operational percentage of installed generation capacity 0 10 20 30 40 50 60 70 80 90 percent high SOE governance, no concessions low SOE governance, no concessions Source: Eberhard and others 2008. Note: kWh = kilowatt-hour; MW = megawatt; SOE = state-owned enterprise; T&D = transmission and distribution. legislation can also clarify and separate a government’s policy role from its shareholding function and the necessity of balancing demands for more affordable electricity tariffs with the necessity of maintaining finan- cial sustainability (box 6.3). It makes sense to separate the policy-making ministry from the SOE shareholding ministry so that they focus clearly on their respective mandates. However, effective policy coordination will also be needed at the cabinet level to achieve the necessary tradeoffs between social and economic objectives. 142 Africa’s Power Infrastructure Table 6.1 Governance Reforms to Improve State-Owned Utility Performance Changing the political Clarification of roles and responsibilities economy of the utility • Identification, separation, and coordination of • Improved transparency and government’s different roles as policy maker, information asset owner, and regulator • Commercialization and • Public entity legislation outsourcing • Corporatization • Labor market reform • Codes of corporate governance • Structural reform and direct • Performance contracts competition • Effective supervisory or monitoring agencies • Mixed-capital enterprises • Transparent transfers for social programs • Customer-owned enterprises • Independent regulator Source: Eberhard and others 2008. Box 6.3 The Combination of Governance Reforms That Improved Eskom’s Performance The experience of Eskom, South Africa’s national electricity utility, provides a model for the implementation of governance reforms. A clear distinction is now made between the shareholder ministry (Public Enterprises) and the sector policy ministry (Energy). In addition, an independent authority regulates market entry through licenses, sets tariffs, and establishes and monitors technical per- formance and customers’ service standards. Eskom was corporatized through the Eskom Conversion Act and is subject to ordinary corporate law. It must pay divi- dends and taxes and publish annual financial statements according to interna- tional accounting standards. The board (appointed by the Minister of Public Enter- prises) is responsible for day-to-day management subject to a performance contract that includes a range of key performance indicators. Additional legislation (the Public Finance Management Act and the Promo- tion of Administrative Justice Act) defines in more detail how the utility should handle finance, information disclosure, reporting, and authorizations. A general corporate governance code also applies to all state-owned enterprises. The per- formance contract is monitored, albeit not very effectively, by the Ministry of Public Enterprises. The utility benefits from separate subsidies for electrification connections and for consumption (poor households receive their first 50 kilowatt- hours each month free of charge). (continued next page) Recommitting to the Reform of State-Owned Enterprises 143 Box 6.3 (continued) After reforms in the 1980s and the appointment of an experienced private sector manager as Eskom’s chief executive officer, a commercial culture was embedded within the utility, separate business units were created with business plans and new budgeting and accounting systems, and outsourcing was used more widely. Eskom is a mixed-capital enterprise. Although wholly owned by the state, it raises capital on private debt markets, locally and internationally, through issuing bonds. It is rated by all the major global credit agencies. Eskom managers are acutely aware that their financial performance is subject to thorough external scrutiny. Any possible downgrading of their debt can make capital scarce or more expensive when they embark on a major capital expansion program. These reforms have caused Eskom to perform relatively well compared with other African utilities. Recently, however, Eskom has had to institute load shedding because it has had insufficient generation capacity to meet demand. Policy uncer- tainties and an earlier prohibition on Eskom’s investing in new capacity while private sector participation was being considered have led to capacity shortages. What Eskom lacks most of all is direct competition. Eskom is dominant in the region; it generates 96 percent of South Africa’s electricity, transmits 100 percent, and distributes approximately 60 percent. Neither government nor the regulator has a good enough idea of Eskom’s actual efficiency or inefficiency. Indications suggest that planning and cost controls could improve. Only direct competitors could provide an appropriate benchmark. Source: Authors. An independent regulatory authority is better positioned to balance the need for protecting consumers (price and quality of service) with providing incentives for utilities to reach financial sustainability by reducing costs, improving efficiency, and moving toward more cost-reflective pricing. Corporatization of state-owned utilities further helps clarify govern- ment’s role as owner and shareholder. Typically the utility will be made subject to ordinary company law. Government is the shareholder, but the utility has a legal identity that is separate from government. The board also includes independent and nonexecutive directors with legal rights and obligations, which makes political interference more difficult. Corporatized utilities have separate accounts and are typically liable for paying taxes and dividends. 144 Africa’s Power Infrastructure Legislation that brings about corporatization also clarifies the mandate, powers, and duties of the utility and its board, the utility’s obligation to earn a profit or an adequate return on assets, and its financing and bor- rowing permissions. Responsibilities for financial management, budgeting processes, accounting, reporting, and auditing are also clearly defined. Codes of corporate governance may also be adopted to clarify and define the relationship between the shareholder and the utility’s board as well as the way in which the board and management operate. A shareholder compact or performance contract usually sets out the shareholder ministry’s objectives for the utility. It specifies the obligations and responsibilities of the enterprise, on the one hand, and the “owner” (that is, the ministry, the supervisory body, or the regulator), on the other. Performance contracts are negotiated, written agreements that clarify objectives of governments and motivate managers to achieve improved performance. They normally address tariffs, investments, subsidies, and noncommercial (social or political) objectives and their funding; they sometimes include rewards for good managerial (and staff) performance and, more rarely, sanctions for nonfulfillment of objectives. Performance contracts are also used to reveal information and to monitor managers’ performance. Typically they include elements of business plans and specify a number of key performance measures and indicators. Performance contracts can also be used between central SOE boards and decentralized units. Performance indicators could include the following: net income, return on assets, debt and equity ratios, interest cover, dividend policy, productivity improvements, customer satisfaction indexes, connection targets, human resource issues, procurement policy, and environmental adherence. Performance contracts are widespread, but their effectiveness is not guaranteed. They have not always reduced the information advantage that managers enjoy over owners, which often allows managers to negotiate performance targets that are easy for the utility to achieve. Furthermore, managers are not convinced of the credibility of government promises, and they have not been sufficiently motivated by rewards and penalties. This is understandable, considering that contracts often lack mechanisms for enforcing government commitments to pay utility bills or penalize under- performing managers. At the heart of the challenge of making performance contracts work more effectively are the classic principal-agent and moral hazard prob- lems. Politicians may not benefit from better performance and may sub- sequently try to make managers serve objectives that conflict with Recommitting to the Reform of State-Owned Enterprises 145 efficiency, such as rewarding political supporters with jobs or subsidies. Contracts can also be incomplete and fail to anticipate events and contin- gencies. Finally, governments can renege on commitments, including promised budgets for social programs. Performance contracts are there- fore not a panacea and should be used only if governments are prepared to deal with the challenges of information asymmetry, effective incen- tives, and credible commitments. In the end, the extent of hidden costs and inefficiencies that affect African utilities is not accurately known. Basic operational and financial data on firm performance are either not collected, not sent to supervisors, not tabulated and published by the supervising bodies, or not acted upon. In the absence of information—or of action taken on the basis of what information is produced—improved performance cannot be expected. Independent supervisory units that can effectively monitor performance contracts are therefore essential. They would preferably be located in the Ministry of Finance or in a dedicated Public Enterprises Ministry. The pol- icy or sector ministry may be hindered by a focus on short-term social or political outcomes rather than on efficiency and financial sustainability. Alternatively, the supervisory function could be contracted out to an expert panel. Other reforms could include hiring private sector managers to instill a commercial culture in the utility. This would ensure that tariffs are high enough to provide sufficient revenue, the utility earns a rate of return at least equal to its cost of capital, billing and collection approaches 100 percent, and customer service improves. The reforms will eliminate government subsidies of the utility’s cost of capital. Instead, the utility will be required to raise finance from private capital markets. Employment and procurement should be undertaken on a commercial basis, and utilities will be encouraged to outsource functions that another company can per- form more efficiently. Competition among suppliers for outsourcing con- tracts could also drive costs down. Finally, commercial responsibilities should be clearly separated from social goals by establishing transparent mechanisms such as fiscal transfers and subsidies for connections for poor households. This would allow util- ity managers to focus on improving operational efficiency. Altering the Political Economy around the Utility Governance reforms should also strengthen other stakeholders with an interest in reduced operating losses and improved operating perform- ance. These reforms could encompass improved transparency and flow 146 Africa’s Power Infrastructure of information, including comprehensive annual reports and financial statements, performance contracts (made available publicly along with results), investment and coverage plans, prices, costs and tariffs, service standards, benchmarking, and customer surveys. Information needs to be credible, coherent, and timely. However, better dissemination of informa- tion alone is not sufficient to improve performance. Further interventions are necessary. Mixed-capital enterprise arrangements are also conducive to increased stakeholder involvement. These can be established either by selling a minority or noncontrolling equity stake to private investors (either a strate- gic equity partner or shareholders brought in by a partial initial public offer- ing) or through private debt markets. Shareholders (through their voting rights and representatives on the board) and bond holders (through debt covenants) can exercise considerable influence. Credit agencies provide financial discipline over managers, who fear a credit downgrading and an increase in capital costs. Customer-owned enterprises (such as cooperatives and mutuals) are another option. Customers have mandatory representation on boards of directors. Unfortunately, obstacles to collective action can minimize the influence of many small customers, and they can also be suscepti- ble to capture by large customers or special interests. Effective customer governance is more likely in small groups with stable membership and adjacent interests. Cooperatives are more appropriate for smaller, local utilities. Finally, the most effective way to change the political economy of state-owned electricity utilities is structural reform and the introduction of competition. The potentially competitive elements of the industry (generation and retail) can be separated from the natural monopoly ele- ments of the value chain (the transmission and distribution networks). This can be done piecemeal, first by creating separate business units, which are then transformed into separate companies, with competition whenever possible. Increasing the number of industry players and intro- ducing private sector participation allows for comparisons to be made among the performance of these different entities. Customers can choose their suppliers, and investors and employees of competing firms are incentivized to improve performance. The potential for full retail com- petition in the power sector in Africa may be limited, but consideration could be given to at least allowing large customers to choose among the incumbent utility and alternative independent power producers or even cross-border imports. Recommitting to the Reform of State-Owned Enterprises 147 Practical Tools for Improving the Performance of State-Owned Utilities In addition to governance reforms, practical operational tools have been developed for improving the performance of state-owned utili- ties. The Commercial Reorientation of the Electricity Sector Toolkit (CREST) is an experiment underway in several localities served by West African electricity providers. Based on good practices from recent reforms in Indian, European, and U.S. power corporations, CREST is a “bottom-up” approach designed to address system losses, low collec- tion rates, and poor customer service. A combination of technical improvements (such as replacing low-tension with high-tension lines and installing highly reliable armored and aerial bunched cables on the low-tension consumer point to reduce theft) and managerial changes (introducing “spot billing” and combining the four transactions of recording, data transfer, bill generation, and distribution) reduces trans- action times and generates more regular cash flow (Tallapragada 2008). Early applications of CREST have reportedly produced positive changes in several neighborhoods in Guinea and Nigeria, which are two difficult settings. The application of the toolkit should be closely monitored and evaluated and, if successful, should be replicated else- where (Nellis 2008). Conclusion Institutional reform is a lengthy process. Victories on this front will be small and slow in coming. Donors may prefer large and quick solutions, but they must recognize that governance reform of state-owned utili- ties is essential to improving the performance of the African power sector. A key challenge in the sector is funding for new power infra- structure. Improved financial performance of state-owned utilities helps reduce the funding gap by reducing inefficiencies and losses and improving collection rates, revenue, and retained earnings, which can be directed to investments in new capacity or network expansion. Improved performance can also lead to better credit ratings, thereby increasing utilities’ access to private debt markets. Improved credit worthiness also means that state-owned utilities can be more reliable counterparties to independent power producer investors, thus once again increasing investment flows into the sector. Improved state-owned utility performance is thus key to meeting the funding challenges outlined in the next chapter. 148 Africa’s Power Infrastructure References Briceño-Garmendia, Cecilia, and Maria Shkaratan. 2010. “Power Tariffs: Caught between Cost Recovery and Affordability.” Working Paper 8, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Eberhard, Anton, Vivien Foster, Cecilia Briceño-Garmendia, Fatimata Ouedraogo, Daniel Camos, and Maria Shkaratan. 2008. “Underpowered: The State of the Power Sector in Sub-Saharan Africa.” Background Paper 6, Africa Infrastructure Sector Diagnostic, World Bank, Washington, DC. Foster, Vivien, and Cecilia Briceño-Garmendia, eds. 2009. Africa’s Infrastructure: A Time for Transformation. Paris, France, and Washington, DC: Agence Française de Développement and World Bank. Gomez-Ibanez, J. A. 2007. “Alternatives to Infrastructure Privatization Revisited: Public Enterprise Reform from the 1960s to the 1980s.” Policy Research Working Paper 4391, World Bank, Washington, DC. Molefhi, B. O. C., and L. J. Grobler. 2006. “Demand-Side Management: A Challenge and Opportunity for Botswana Electric Energy Sector.” North West University, Potchefstroom, South Africa. Nellis, John. 2008. “Private Management Contracts in Power Sector in Sub- Saharan Africa.” Internal note, Africa Infrastructure Country Diagnostic, World Bank, Washington, DC. Tallapragada, Prasad V. S. N. 2008. “Commercial Reorientation of the Electricity Sector Toolkit: A Methodology to Improve Infrastructure Service Delivery.” Unpublished note, World Bank, Washington, DC. Vagliasindi, Maria. 2008. “Institutional Infrastructure Indicators: An Application to Reforms, Regulation and Governance in Sub-Saharan Africa.” Unpublished paper, AFTSN, World Bank, Washington, DC. CHAPTER 7 Closing Africa’s Power Funding Gap The cost of addressing Africa’s power sector needs is estimated at $40.8 billion a year, equivalent to 6.35 percent of Africa’s gross domestic prod- uct (GDP). The burden varies greatly by country, from 0.3 percent of GDP in Equatorial Guinea to 35.4 percent in Zimbabwe. Approximately two-thirds of the total spending need is capital investment ($26.7 billion a year); the remainder is operations and maintenance (O&M) expenses ($14.1 billion a year). The model used to calculate these estimates was run under the assumption of expanded regional power trade and takes into account all investments needed for the increase in trade and all cost sav- ings achieved as a result. In comparison with other sectors, power sector investment needs are very high: They are 4.5 times larger than in the information and commu- nication technology (ICT) sector and approximately double the invest- ment needs in each of the water, sanitation, and transport sectors. Current spending aimed at addressing power infrastructure needs is higher than previously thought and adds up to an estimated $11.6 bil- lion. Almost equal shares of this amount are spent by three groups of countries: middle-income, resource-rich, and nonfragile low-income countries. Fragile low-income countries spend the remaining small share (5 percent, or approximately $0.83 billion), a reflection of the weakness 149 150 Africa’s Power Infrastructure of their economies. The majority of spending is channeled through public institutions, most notably power sector utilities (state-owned enterprises [SOEs]). Approximately 80 percent of existing spending is domestically sourced from taxes or user charges. The rest is split among official development assistance (ODA) financing, which provides 6 percent of the total; fund- ing from countries outside the Organisation for Economic Co-operation and Development (OECD), which provides 9 percent of the total, and private sector contributions, which provide 4 percent of the total. Almost 75 percent of domestic spending goes to O&M. Capital spending is financed from four sources: One-half comes from the domestic public sector, approximately one-quarter is received from non-OECD financiers, and the rest is contributed by OECD and the private sector. Much can be done to reduce the gap between spending needs and cur- rent levels of spending. Inefficiencies of various kinds total 1.28 percent of GDP. Reducing inefficiencies is a challenging task, but the financial benefit can be substantial. Three types of power sector inefficiencies are found. First, there are utility inefficiencies, which include system losses, undercollection of rev- enue, and overstaffing. These result in a major waste of resources that adds up to $4.40 billion a year. Undercollection, the largest component of utility inefficiencies, amounts to $1.73 billion; system losses account for $1.48 billion, and overstaffing for $1.15 billion. The second type of sector inefficiency is underpricing of power. By setting tariffs below the levels needed to cover actual costs, countries in Sub-Saharan Africa forego revenue of $3.62 billion a year. The third type of inefficiency is poor budget execution, with only 66 percent of the capital budgets allocated to power actually spent. That leaves an estimated $258 million in public investment that is ear- marked for the power sector but diverted elsewhere in the budget. Tackling all these inefficiencies would make an additional $8.24 billion available, but a funding gap of $20.93 billion would still remain. The sit- uation differs by country; one-third of countries in Sub-Saharan Africa would be able to fund their needs, but the remaining two-thirds would face a funding gap of between 6 and 74 percent of total needs even if all inefficiencies were eliminated. The countries in the second group will therefore need to pursue ways to raise additional funds. Historical trends do not suggest strong prospects for increasing allocations from the public budget: Even when fiscal sur- pluses existed, they did not visibly favor infrastructure. External finance Closing Africa’s Power Funding Gap 151 for infrastructure has been buoyant in recent years; in particular, fund- ing from OECD has increased. However, the power sector has not ben- efited from this trend: It has received the least funding compared with transport, water supply and sanitation (WSS), and ICT. Closing Africa’s power infrastructure funding gap inevitably requires reforms to reduce or eliminate inefficiencies. This will help existing resources to go farther and create a more attractive investment climate for external and private finance. Existing Spending in the Power Sector Existing spending on infrastructure in Africa is higher than previously thought when the analysis takes into account budget and off-budget spending (including SOEs and extra budgetary funds) and spending financed by external sources including ODA, official sources in non- OECD countries, and private sources. Africa is spending $11.6 billion a year to address its power infrastruc- ture needs, which is equivalent to 1.8 percent of GDP. This is split between investment (40 percent of the total) and O&M. Although the public sector more or less covers O&M needs, it provides only 51.5 per- cent of investment financing needs. The rest of investment spending is provided by external and private sector investors. Of the total investment funds provided by the public sector for infra- structure, power amounts to one-quarter, transport nearly one-half, and the remaining one-quarter is divided more or less equally between the WSS and ICT sectors (table 7.1). The power sector receives nearly half of the infrastructure funding provided by non-OECD financiers but does Table 7.1 Sectoral Composition of Investment, by Financing Source percent Power Transport WSS ICT Irrigation Domestic public sector 24 47 13 13 3 External and private sector 14 25 23 37 0 Including ODA 19 48 33 0 0 Non-OECD 47 46 7 0 0 Private 5 11 23 61 0 Source: Briceño-Garmendia, Smits, and Foster (2008) for public spending, PPIAF (2008) for private flows, and Foster and others (2008) for non-OECD financiers. Note: All rows total 100 percent. ICT = information and communication technology; ODA = official development assistance; OECD = Organisation for Economic Co-operation and Development; WSS = water supply and sanitation. 152 Africa’s Power Infrastructure less well in ODA and PPI funding. Telecommunications receives the majority of private infrastructure funding. Funding patterns vary considerably across countries, which is explained in part by the economic and political status of each country. We can group countries into four broad categories to make sense of these variations: middle-income countries, resource-rich countries, fragile low-income coun- tries, and nonfragile low-income countries (box 7.1). Middle-income and resource-rich countries spend 1.3 percent and 1.8 percent of GDP on power, respectively. Low-income countries spend sub- stantially more: 2.2 percent of GDP in the nonfragile states and 2.9 per- cent of GDP in fragile states (table 7.2). The composition of spending also varies substantially across country groups. Middle-income countries allo- cate three-quarters of power spending to O&M; this is the case primarily Box 7.1 Introducing a Country Typology Middle-income countries have GDP per capita in excess of $745 but less than $9,206. Examples include Cape Verde, Lesotho, and South Africa (World Bank 2007). Resource-rich countries are low-income countries whose behaviors are strongly affected by their endowment of natural resources (Collier and O’Connell 2006; IMF 2007). Resource-rich countries typically depend on exports of minerals, petro- leum, or both. A country is classified as resource rich if primary commodity rents exceed 10 percent of GDP. (South Africa is not classified as resource-rich, using this criterion). Examples include Cameroon, Nigeria, and Zambia. Fragile states are low-income countries that face particularly severe develop- ment challenges, such as weak governance, limited administrative capacity, vio- lence, or a legacy of conflict. In defining policies and approaches toward fragile states, different organizations have used differing criteria and terms. Countries that score less than 3.2 on the World Bank’s Country Policy and Institutional Per- formance Assessment belong to this group. Fourteen countries of Sub-Saharan Africa are in this category. Examples include Côte d’Ivoire, the Democratic Repub- lic of Congo, and Sudan (World Bank 2005). Other low-income countries constitute a residual category of countries that have GDP per capita below $745 and are neither resource rich nor fragile states. Examples include Benin, Ethiopia, Senegal, and Uganda. (continued next page) Closing Africa’s Power Funding Gap 153 Box 7.1 (continued) MAURITANIA CAPE MALI NIGER VERDE CHAD ERITREA SENEGAL SUDAN GAMBIA GUINEA-BISSAU BURKINA FASO GUINEA BENIN NIGERIA SOMALIA SIERRA LEONE CÔTE GHANA ETHIOPIA D'IVOIRE TOGO CENTRAL AFRICAN LIBERIA CAMEROON REPUBLIC EQUATORIAL GUINEA UGANDA KENYA O GABON NG CONGO, RWANDA CO DEM REP BURUNDI TANZANIA MALAWI ANGOLA ZAMBIA MOZAMBIQUE ZIMBABWE MADAGASCAR MAURITIUS resource-rich countries NAMIBIA BOTSWANA nonfragile low-income countries SWAZILAND fragile low-income countries LESOTHO SOUTH AFRICA middle-income countries Source: Briceño-Garmendia, Smits, and Foster 2008. because the largest, South Africa, has been delaying investment in new capacity. Fragile low-income countries spend 70 percent on O&M, and nonfragile low-income countries allocate 60 percent of the power budget to O&M. By contrast, resource-rich countries spend only 40 percent on O&M and allocate the rest to investment. The variation of power sector spending across countries ranges from less than 0.1 percent of GDP in the Democratic Republic of Congo to almost 6 percent of GDP in Cape Verde (figure 7.1a). Countries with low levels of capital spending include Lesotho (0.10 percent of GDP), South Africa (0.27 percent of GDP), Madagascar (0.36 percent of GDP), and Malawi (0.56 percent of GDP). All these countries require additional investment in new generation capacity or power transmission (Rosnes and Vennemo 2008). At the other end of the scale are countries with high 154 Table 7.2 Power Sector Spending in Sub-Saharan Africa, Annualized Flows Percentage of GDP $ million O&M Capital expenditure O&M Capital expenditure Non- Total Non- Total Public Public OECD capital Public Public OECD capital Country type sector sector ODA financiers PPI expenditures Total sector sector ODA financiers PPI expenditures Total Middle income 0.98 0.28 0.01 0.00 0.00 0.30 1.28 2,656 772 33 1 5 811 3,467 Resource rich 0.72 0.56 0.03 0.33 0.13 1.05 1.77 1,602 1,243 75 736 278 2,333 3,935 Nonfragile low income 1.78 0.39 0.50 0.12 0.15 1.15 2.94 1,970 432 549 129 165 1,274 3,243 Fragile low income 1.49 0.00 0.10 0.55 0.03 0.68 2.16 571 0 37 210 12 260 830 Africa 1.09 0.37 0.11 0.17 0.07 0.72 1.81 7,011 2,363 694 1,076 460 4,594 11,605 Source: Briceño-Garmendia, Smits, and Foster (2008) for public spending; PPIAF (2008) for private flows; Foster and others (2008) for non-OECD financiers. Note: Aggregate public sector expenditure covers general government and state-owned enterprise expenditure on infrastructure. Figures are extrapolations based on the 24-country sample covered in AICD Phase 1. Totals may not add exactly because of rounding errors. GDP = gross domestic product; ODA = official development assistance; OECD = Organisation for Economic Co-operation and Development; O&M = operation and maintenance; PPI = private participation in infrastructure. Closing Africa’s Power Funding Gap 155 levels of capital expenditure. This group includes Uganda (3.1 percent of GDP) and Ghana (1.4 percent of GDP). The funding received from different sources also varies substantially across countries (figure 7.1b). Although public funding is the dominant source in 83 percent of countries, ODA plays a substantial role in many low-income countries. A handful of countries enjoy a significant contri- bution from the private sector. Non-OECD finance contributes a rela- tively small amount to the power sector in most countries, with the exception of Ghana and Niger, where it exceeds 20 percent of the total. Figure 7.1 Power Spending from All Sources as a Percentage of GDP a. By functional category Kenya Mali Zambia Benin Ghana Tanzania Madagascar Malawi Senegal Côte d’lvoire Congo, Rep. Namibia Burkina Faso Nigeria Niger Rwanda Cameroon Lesotho Botswana South Africa Mozambique Chad Congo, Dem. Rep. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 percentage of GDP O&M capital (continued next page) 156 Africa’s Power Infrastructure Figure 7.1 (continued) b. By funding source Uganda Ethiopia Benin Ghana Tanzania Kenya Zambia Madagascar Cape Verde Senegal Namibia Mozambique Burkina Faso Nigeria Niger South Africa Rwanda Cameroon Malawi Côte d’lvoire Lesotho Chad Congo, Dem. Rep. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 percentage of GDP public sector ODA non-OECD financiers PPI Source: Briceño-Garmendia, Smits, and Foster (2008) for public spending, PPIAF (2008) for private flows, Foster and others (2008) for non-OECD financiers. Note: Based on annualized averages for 2001–06. Averages weighted by country GDP. GDP = gross domestic product; ODA = official development assistance; OECD = Organisation for Economic Co-operation and Development; O&M = operations and maintenance; PPI = private participation in infrastructure. Closing Africa’s Power Funding Gap 157 In the middle-income countries, domestic public sector resources (including tax revenue and user charges raised by state entities) account for 99 percent of power sector spending. Across the other country cate- gories, domestic public sector resources invariably contribute at least two-thirds of total spending. In the middle- and low-income countries, domestic public spending is focused on O&M, which accounts for more than three-quarters of the total. In the resource-rich states, domestic pub- lic spending in the power sector is more balanced, with only 57 percent of the total spent on O&M. In the aggregate, external finance contributes roughly one-half of Africa’s total capital spending on the power sector. External sources include ODA, official finance from non-OECD countries (such as China, India, and the Arab funds), and PPI. External finance is primarily for investment—broadly defined to include asset rehabilitation and con- struction—and does not provide for O&M. One-half of external finance for Africa’s power sector comes from non-OECD financiers, approxi- mately one-third from PPI, and the rest, roughly 20 percent, from ODA (table 7.1). External financing favors resource-rich countries: They obtain approx- imately 50 percent of total external funds. The second largest recipient of external financing is the group of nonfragile low-income countries, which receive one-third of the total. ODA is directed primarily (80 percent) to nonfragile low-income states. Two-thirds of financing from each of the other two sources—non-OECD financiers and PPI—benefits resource- rich countries (figure 7.2). How Much More Can Be Done within the Existing Resource Envelope? Africa is losing an estimated $8.24 billion per year to various inefficiencies in its power sector. In this context, four distinct opportunities can be identi- fied for efficiency gains. The lack of cost recovery is the largest source of sector inefficiency: Losses from pricing power below the current costs con- stitute 44 percent of all inefficiencies. Essential interventions include improving utility operations, capitalizing on the benefits of regional trade, and bringing tariffs to the level of the long-run marginal costs of power. Undercollection of bills adds up to 22 percent of total sector inefficiency, and the utilities should tackle this issue. System losses constitute 18 percent of the inefficiencies and need to be addressed. Overstaffing in the power utilities contributes 14 percent of total inefficiencies. 158 Africa’s Power Infrastructure Figure 7.2 Sources of Financing for Power Sector Capital Investment 5,000 4,500 4,000 3,500 3,000 $ million 2,500 2,000 1,500 1,000 500 0 ca e e e h m m m ric ri co co co Af e rc in in in n ou ra w w e dl ha lo lo s re id Sa le ile m gi b- g fra ra Su nf no PPI non-OECD ODA public sector Source: Briceño-Garmendia, Smits, and Foster (2008) for public spending; PPIAF (2008) for private flows; Foster and others (2008) for non-OECD financiers. Note: ODA = official development assistance; OECD = Organisation for Economic Co-operation and Development; PPI = private participation in infrastructure. Increasing Cost Recovery By setting tariffs below the levels needed to recover actual costs, Sub- Saharan countries forego revenue of $3.62 billion a year.1 However, low cost recovery is a function of both low tariffs and high costs. Despite com- paratively high power prices, most Sub-Saharan Africa countries are recovering only their average operating costs and are far from being able to recover total costs with tariffs. Although a few countries—Burkina Faso, Cape Verde, Chad, Côte d’Ivoire, Kenya, Namibia, and Uganda— achieved cost recovery, they are exceptions. Also, in some cases (Burkina Faso, Cape Verde, and Chad), cost recovery has been achieved by elevat- ing tariffs above extremely high costs. Power tariffs in Sub-Saharan Africa are high compared with other regions. The average power tariff of $0.12 per kilowatt-hour (kWh) is twice the level in other developing regions, such as South Asia. The high costs of power can, to a large extent, be explained by lack of economies of scale, underdeveloped regional energy resources, high oil prices, drought, and political instability—factors mostly Closing Africa’s Power Funding Gap 159 beyond the influence of the energy sector or a utility. However, other causes could be resolved at the sector or utility level. One example is sub- sidized residential tariffs, especially in the countries with a high share of residential consumption. Another is inefficient residential tariff structures that decrease with increased consumption and create cross-subsidies from the lower-income households to the more affluent ones, which curtails usage by poorer households and promotes overconsumption of power by more affluent households. When tariffs charged to residential customers are below costs (figure 7.3), motivating and achieving increases is usually socially and politically sensitive and takes time to accomplish. In addition, many countries in Sub- Saharan Africa are pricing power to highly energy-intensive industries at greatly subsidized rates. These arrangements were initially justified as ways of locking in baseload demand to support the development of very large- scale power projects that went beyond the immediate demands of the country, but they have become increasingly questionable as competing demands have grown to absorb this capacity. Salient examples include the aluminum-smelting industry in Cameroon, Ghana, and South Africa and the mining industry in Zambia. As figure 7.3 demonstrates, total costs of power supply are above the average tariffs for all customer groups, including residential and industrial tariffs. On average, total costs exceed residential tariffs by 23 percent and industrial tariffs by 36 percent. Figure 7.3 Power Prices and Costs, Sub-Saharan Africa Average 20 cents per kWh 15 10 5 0 t e ou all co al co cal iff iff iff os nu n ar ar ar gr ff, i ps st st gi lc or ve lt lt lt er tari ar ica st ia tia ria re m hi c or st en om e er e n g st ag ag ist du m -ru sid in cu er lh er m in at ng re av av co er ta lo to op Source: Briceño-Garmendia and Shkaratan 2010. Note: kWh = kilowatt-hour. 160 Africa’s Power Infrastructure Although tariffs in most countries fall below total costs, they recover operational costs, with only a few exceptions. The exceptions include Cameroon, Malawi, Niger, Tanzania, and Zambia. On the aggregate continental level, tariffs are 40 percent above the operational cost level. Differences are seen among customer groups in this respect: Commercial, residential, and industrial tariffs exceed operational costs by 67 percent, 43 percent, and 21 percent, respectively. On Budget Spending: Raising Capital Budget Execution As mentioned previously, most public spending in the power sector SOEs in Sub-Saharan Africa is off-budget, while the on-budget spending constitutes only a small portion of it. The public sector in Sub-Saharan Africa allocates 0.13 percent of GDP, or $827 million, to support the power sector (table 7.3). For a typical African country, this effort trans- lates to about $29 million a year, which is very small in relation to over- all power sector needs. To put this figure in perspective, the power sector needs in Sub-Saharan African countries range from $2 million to $13.5 billion per year, and budgetary support of the sector varies from zero to $444 million. Although 99.6 percent of power sector public spending in the middle-income countries is off budget, for resource-rich countries, off-budget spending is a much smaller part of the total, equal to 71.2 percent of all public resources dedicated to power. Despite the limited allocation of public budgetary spending to the power sector, it is still important to mention one additional source of inefficiency: poor budget execution. Central governments face significant problems in executing their infrastructure budgets. On average, African Table 7.3 Annual Budgetary Flows to Power Sector Percentage of GDP $ billion Country type Power Total Power Total Resource rich 0.37 1.60 0.815 3.55 Middle income 0.01 1.46 0.015 3.96 Nonfragile low income 0.13 1.52 0.145 1.67 Fragile low income 0.0 0.71 0.0 0.27 Africa 0.13 1.48 0.827 9.50 Source: Briceño-Garmendia, Smits, and Foster 2008. Note: Based on annualized averages for 2001–06. Averages weighted by country GDP. Figures are extrapolations based on the 24-country sample covered in AICD Phase 1. Totals may not add exactly because of rounding errors. GDP = gross domestic product. Closing Africa’s Power Funding Gap 161 Table 7.4 Average Budget Variation Ratios for Capital Spending Country type Overall infrastructure Power Middle income 78 — Resource rich 65 60 Nonfragile low income 76 75 Fragile low income — — Sub-Saharan Africa 75 66 Source: Adapted from Briceño-Garmendia, Smits, and Foster 2008. Note: Based on annualized averages for 2001–06. — = data not available. countries are unable to spend as much as one-third of their capital budg- ets for power (table 7.4). The poor timing of project appraisals and late releases of budgeted funds due to procurement problems often prevent the use of resources within the budget cycle. Delays affecting in-year fund releases are also associated with poor project preparation, which leads to changes in the terms agreed upon with contractors in the original contract (such as deadlines, technical specifications, budgets, and costs). In other cases, cash is reallocated to nondiscretionary spending driven by political or social pressures. Unlike in other infrastructure sectors, the power sector’s losses from nonexecution of budgets are small as a percentage of spending. However, the absolute amount is large, and it is important to tackle this ineffi- ciency. If the bottlenecks in power sector capital execution could be resolved, countries would increase their spending on power by $258 mil- lion a year, or 2.2 percent of total current spending, without any increase in current budget allocations. Resolution of these planning, budgeting, and procurement challenges should be included in the region’s reform agenda. Even if budgets are fully spent, concerns are found as to whether funds reach their final destinations. Public expenditure tracking surveys have attempted to trace the share of each budget dollar that results in produc- tive frontline expenditures. Most of the existing case studies concern social sectors as opposed to power, but they illustrate leakages of public capital spending that can be as high as 92 percent (see Pritchett 1996; Rajkumar and Swaroop 2002; Reinikka and Svensson 2002, 2004; Warlters and Auriol 2005). Improving Utility Performance Utility inefficiencies are high and constitute on average 0.68 percent of GDP in Sub-Saharan African countries. In some countries, inefficiencies 162 Africa’s Power Infrastructure amount to almost 5 percent of GDP. Looking at different sources of util- ity inefficiency, one can see that the largest component is undercollec- tion of electricity bills (0.40 percent of GDP), followed by system losses (0.34 percent of GDP) and overstaffing at the SOEs (0.26 percent of GDP). These numbers are monetary equivalents of physical measures of inefficiencies, such as system losses that average 23 percent compared with a global norm of 10 percent. Collection rates average 88.4 percent compared with the best practice standard of 100 percent, and customer- to-employee ratios in Sub-Saharan Africa average 184, substantially below the same indicator in other developing regions. In countries with above-average utility inefficiencies, growth in power access is slow and suppressed demand high compared with the rest of the countries. If revenue cannot cover the necessary expenses because of undercollection or system losses, or the salary bill is excessively high, government resources are used to subsidize the utility. When subsidies cannot cover the net loss, the utilities are forced to skimp on mainte- nance, and performance deteriorates even further. Savings from Efficiency-Oriented Reforms In total, $8.2 billion could be captured through efficiency improvements, cost recovery, and more effective budget execution. The largest potential gains come from improved operational efficiencies that amount to $4.4 billion a year, most of which would come from achieving a 100 percent collection rate ($1.7 billion). A further $1.5 billion a year could be secured by reducing system losses to the internationally recognized norm. Dealing with overstaffing would liberate another $1.2 billion (table 7.5). Reaching cost recovery through cost reduction and tariff adjustment, as described Table 7.5 Potential Gains from Higher Operational Efficiency $ million annually Total Middle Resource Nonfragile Fragile low Sub-Saharan income rich low income income Africa All operational inefficiencies 1,745 1,838 980 1,738 4,355 System losses 22 948 470 498 1,476 Undercollection 96 480 339 1,141 1,728 Overstaffing 1,627 410 172 99 1,152 Source: Briceño-Garmendia, Smits, and Foster 2008. Closing Africa’s Power Funding Gap 163 earlier, would yield $3.6 billion. Finally, achieving full capital execution would add yet another 0.2 billion a year. Ten countries have potential efficiency savings of more than 2 per- centage points of GDP, from as much as 4.5 percent of GDP in the case of Côte d’Ivoire to 2.38 percent of GDP in Ghana. An additional eight countries can potentially save 1–2 percent of their GDP by eliminating inefficiencies (figure 7.4). In 56 percent of the countries, the largest Figure 7.4 Potential Efficiency Gains from Different Sources Senegal Mali Malawi Niger Botswana Cameroon Ghana Tanzania Zambia Nigeria Cape Verde Congo, Rep. Lesotho Benin Kenya Mozambique Madagascar Burkina Faso Ethiopia Rwanda Chad South Africa Namibia 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 percentage of GDP raising capital execution reducing operational inefficiencies improving cost recovery Source: Briceño-Garmendia, Smits, and Foster 2008. Note: Based on annualized averages for 2001–06. Averages weighted by country GDP. GDP = gross domestic product. 164 Africa’s Power Infrastructure source of inefficiencies is the lack of cost recovery. Operational deficien- cies are the main source of inefficiency in 44 percent of the countries. Annual Funding Gap Existing spending and potential efficiency gains can be subtracted from estimated spending needs to gauge the extent of the shortfall in funding. However, even if all of the inefficiencies described previously could be tackled, they would cover only 20 percent of the funding gap for the power sector in Sub-Saharan Africa, 38 percent in resource-rich and low-income fragile states, 18 percent in nonfragile low-income countries, and just 17 percent in middle-income countries. About three-quarters of this funding gap relates to capital investment, and the remainder is O&M needs. Although it may be unrealistic to expect that all these inefficien- cies could be captured, even halving them would make a contribution to financing the African power sector (table 7.6). Seventeen countries face significant funding gaps for the power sector (figure 7.5). By far the most salient cases are Ethiopia and the Democratic Republic of Congo, which have annual gaps of 23 percent of GDP ($2.8 billion annually) and 18 percent ($1.3 billion a year), respec- tively. Mozambique, Senegal, and Madagascar all have funding gaps of Table 7.6 Annual Power Funding Gap Total Cross- Nonfragile Fragile Sub- country Middle Resource low low Saharan gain from income rich income income Africa reallocation Infrastructure spending needs (14,191) (11,770) (9,704) (5,201) (40,797) n.a. Spending directed to needs 3,470 3,959 3,241 830 11,633 n.a. Gain from eliminating inefficiencies 2,431 4,440 1,758 1,924 8,237 n.a. Capital execution 2 294 20 0 258 n.a. Operational inefficiencies: 1,745 1,838 980 1,738 4,355 n.a. Cost recovery 684 2,309 757 186 3,624 n.a. Funding gap (8,289) (3,370) (4,705) (2,447) (20,927) n.a. Potential for reallocation 0 0 0 0 0 773 Source: Briceño-Garmendia, Smits, and Foster 2008. Note: n.a. = Not applicable. Closing Africa’s Power Funding Gap 165 Figure 7.5 Power Infrastructure Funding Gap Ethiopia Congo, Dem. Rep. Mozambique Senegal Madagascar Congo, Rep. South Africa Rwanda Nigeria Namibia Zambia Ghana Tanzania Kenya Uganda Cameroon Benin Chad Burkina Faso Niger Mali Malawi Lesotho Côte d’lvoire Cape Verde Botswana 0 5 10 15 20 25 percentage of GDP capex gap O&M gap Source: Briceño-Garmendia, Smits, and Foster 2008. Note: Based on annualized averages for 2001–06. Averages weighted by country GDP. capex = capital expenditures; GDP = gross domestic product; O&M = operations and management. 5–10 percent of GDP. The Democratic Republic of Congo, South Africa, Rwanda, Nigeria, Namibia, Zambia, Ghana, Tanzania, Kenya, Uganda, and Cameroon have funding gaps of 1–5 percent of GDP. After inefficiencies are eliminated, the power sector’s annual funding gap totals $20.9 billion. Covering it would require raising additional 166 Africa’s Power Infrastructure funds, taking more time to attain investment and coverage targets, or using lower-cost technologies. The remainder of this chapter evaluates the potential for raising additional finance and explores policy adjustments to reduce the price tag and the burden of the funding gap. How Much Additional Finance Can Be Raised? Only limited financing sources are available, and the 2008 global finan- cial crisis has affected all of them adversely. Domestic public finance is the largest source of funding today, but it presents little scope for an increase, except possibly in countries enjoying natural resource wind- falls. The future of ODA and non-OECD financing is unclear in the postcrisis situation. Although private participation in the power sector in Africa has increased over the past two decades, it remains at modest levels, and investors are more cautious after the 2008 financial crisis. The question is whether private participation might increase in the future, assuming capacity expansion, an improved institutional environ- ment, and reduced barriers to entry. Local capital markets have so far contributed little to infrastructure finance outside South Africa, and to a smaller extent in Kenya, but they could eventually become more important in some of the region’s larger economies. Moreover, both of these sources of funding are of limited relevance to the power sector in fragile low-income states, which is where public resources are least available. Little Scope for Raising More Domestic Finance To what extent are countries willing to allocate additional fiscal resources to infrastructure? In the run-up to the current financial crisis, the fiscal situation in Sub-Saharan Africa was favorable. Rapid economic growth, averaging 4 percent a year from 2001 to 2005, translated into increased domestic fiscal revenue of about 3 percent of GDP on average. In resource-rich countries, burgeoning resource royalties added 7.7 percent of GDP to the public budget. In low-income countries, substantial debt relief increased external grants by almost 2 percent of GDP. To what extent were the additional resources available during the recent growth surge allocated to infrastructure? The answer is: surpris- ingly little (table 7.7). The most extreme case is that of the resource-rich countries, particularly Nigeria. Huge debt repayments more than fully absorbed the fiscal windfalls in these countries. As a result, budgetary spending actually contracted by 3.7 percent of GDP. Infrastructure Closing Africa’s Power Funding Gap 167 Table 7.7 Net Change in Central Government Budgets, by Economic Use, 1995–2004 percentage of GDP Sub-Saharan Middle Resource Fragile Nonfragile Use Africa income rich low income low income Net expenditure budget 1.89 4.08 (3.73) 1.69 3.85 Current infrastructure spending as a share of expenditures 0.00 0.02 0.03 0.00 0.09 Capital infrastructure spending as a share of expenditures (0.14) 0.04 (1.46) 0.54 0.22 Source: Adapted from Briceño-Garmendia, Smits, and Foster 2008. Note: Based on annualized averages for 2001–06. Averages weighted by country GDP. Totals are extrapolations based on the 24-country sample as covered in AICD Phase 1. GDP = gross domestic product. investment, which bore much of the decrease in spending, fell by almost 1.5 percent of GDP. In middle-income countries, budgetary spending increased by almost 4.1 percent of GDP, but the effect on infrastructure spending was almost negligible, and the additional resources went prima- rily to current social sector spending. Only in the low-income countries did the overall increases in budgetary expenditure have some effect on infrastructure spending. Even there, however, the effect was fairly modest and confined to capital spending. The nonfragile low-income countries have allocated 30 percent of the budgetary increase to infrastructure investments. The fragile states, despite seeing their overall budgetary expenditures increase by about 3.9 percent of GDP, have allocated only 6 percent of the increase to infrastructure. Compared with other developing regions, Sub-Saharan Africa’s public financing capabilities are characterized by weak tax revenue collection. Domestic revenue generation of approximately 23 percent of GDP trails averages for other developing countries and is lowest for low-income coun- tries (less than 15 percent of GDP a year). Despite the high growth rates in the last decade, domestically raised revenue grew by less than 1.2 percent of GDP. This finding suggests that raising domestic revenue above cur- rent levels would require undertaking challenging institutional reforms to increase the effectiveness of revenue collection and broaden the tax base. Without such reforms, domestic revenue generation will remain weak. The borrowing capacity from domestic and external sources is also limited. Domestic borrowing is often very expensive, with interest rates 168 Africa’s Power Infrastructure that far exceed those on concessional external loans. Particularly for the poorest countries, the scarcity of private domestic savings means that public domestic borrowing tends to precipitate sharp increases in interest rates that build up a vicious circle. For many Sub-Saharan countries, the ratios of debt service to GDP are more than 6 percent. The 2008 global financial crisis can be expected to reduce fiscal receipts because of lower revenue from taxes, royalties, and user charges. Africa is not exempt from its impact. Growth projections for the coming years have been revised downward from 5.1 percent to 3.5 percent, which will reduce tax revenue and likely depress the demand and willingness to pay for infrastructure services. Commodity prices have fallen to levels of the early 2000s. The effect on royalty revenue, however, will depend on the saving regime in each country. Various oil producers have been saving roy- alty revenue in excess of $60 a barrel, so the current downturn will affect savings accounts more than budgets. Overall, this adverse situation created by the global financial crisis will put substantial pressure on public sector budgets. In addition, many African countries are devaluing their currency, reducing the purchasing power of domestic resources. Based on recent global experience, fiscal adjustment episodes tend to fall disproportionately on public investment—and infrastructure in par- ticular. Experience from earlier crises in East Asia and Latin America indi- cates that infrastructure spending is vulnerable to budget cutbacks during crisis periods. Based on averages for eight Latin American countries, cuts in infrastructure investment amounted to about 40 percent of the observed fiscal adjustment from the early 1980s to the late 1990s (Calderón and Servén 2004). This reduction was remarkable because public infrastructure investment already represented less than 25 percent of overall public expenditure in Latin American countries. These infrastructure investment cuts were later identified as the underlying problem holding back eco- nomic growth in the whole region during the 2000s. Similar patterns were observed in East Asia during the financial crisis of the mid-1990s. For example, Indonesia’s total public investment in infrastructure dropped from 6–7 percent of GDP in 1995–97 to 2 percent in 2000. Given recent spending patterns, there is every reason to expect that changes in the over- all budget envelope in Africa will affect infrastructure investment in a sim- ilar pro-cyclical manner. Official Development Assistance—Sustaining the Scale-Up For most of the 1990s and early 2000s, ODA financial flows to power infrastructure in Sub-Saharan Africa remained steady at a meager $492 Closing Africa’s Power Funding Gap 169 million a year. The launch of the Commission for Africa Report in 2004 was followed by the Group of Eight Gleneagles Summit in July 2005, where the Infrastructure Consortium for Africa was created to focus on scaling up donor finance to meet Africa’s infrastructure needs. Donors have so far lived up to their promises, and ODA commitments to African power infrastructure increased by more than 26 percent, from $642 mil- lion in 2004 to $810 million in 2006. Most of this ODA comes from mul- tilateral donors—the African Development Bank, European Community, and International Development Association (IDA)—and France and Japan make significant contributions among the bilaterals. A significant lag occurs between ODA commitments and their disbursement, which suggests that disbursements should continue to increase in the coming years. However, this happens less in the power sector than in other infra- structure sectors. In 2006, the just-reported commitments in power were only 18 percent higher than the estimated ODA disbursements of $694 million (see table 7.1). This gap reflects delays typically associated with project implementation. Because ODA is channeled through the govern- ment budget, the execution of funds faces some of the same problems affecting domestically financed public investment, including procure- ment delays and low country capacity to execute funds. Divergences between donor and country financial systems, as well as unpredictability in the release of funds, may further impede the disbursement of donor resources. Bearing all this in mind, if all commitments up to 2007 are fully honored, ODA disbursements could be expected to rise significantly (IMF 2009; World Economic Outlook 2008). ODA was set to increase further before the crisis, but prospects no longer look so good. The three multilateral agencies—the African Develop- ment Bank, the European Commission, and the World Bank—secured record replenishments for their concessional funding windows for the three to four years beginning in 2008. In principle, funding allocations to African infrastructure totaling $5.2 billion a year could come from the multilateral agencies alone in the near future, and power will likely con- tinue to attract a substantial share of that overall envelope. In practice, however, the crisis may divert multilateral resources away from infrastruc- ture projects and toward emergency fiscal support. Bilateral support, based on annual budget determinations, may be more sensitive to the fiscal squeeze in OECD countries, and some decline can be anticipated. Historical trends suggest that ODA has tended to be pro-cyclical rather than countercyclical (IMF 2009; ODI 2009; UBS Investment Research 2008; World Economic Outlook 2008; and references cited therein). 170 Africa’s Power Infrastructure Non-OECD Financiers—Will Growth Continue? Non-OECD countries financed about $1.1 billion of the African power sector annually during 2001–06 (see table 7.1). This is substantially more than the $0.7 billion provided by ODA over the same period; moreover, the focus of the finance is very different. Non-OECD financiers have been active primarily in oil-exporting countries (Angola, Nigeria, and Sudan). Non-OECD finance for the African power sector has predomi- nantly taken the form of Chinese funding, followed by Indian and then Arab support. About one-third of Chinese infrastructure financing in Africa has been directed to the power sector, amounting to $5.3 billion in cumulative commitments by 2007. Most of this has been focused on the construction of large hydropower schemes. By the end of 2007, China was providing $3.3 billion for the construction of 10 major hydropower projects total- ing 6,000 megawatts (MW). Some of the projects will more than double the generating capacity of the countries where they are located. Outside hydropower, China has invested in building thermal plants, with the most significant projects in Sudan and Nigeria. Main transmission projects are in Tanzania and Luanda (Angola). Non-OECD finance raises concerns about sustainability. The non- OECD financiers from China, India, and the Arab funds follow sec- tors, countries, and circumstances aligned with their national business interests. They offer realistic financing options for power and transport and for postconflict countries with natural resources. However, non- governmental organizations are voicing concerns about the associated social and environmental standards. Non-OECD financiers also provide investment finance without associated support on the operational, insti- tutional, and policy sides, which raises questions about the new assets’ sustainability. How the current economic downturn will affect non-OECD finance is difficult to predict because of the relatively recent nature of these capital inflows. As they originate in fiscal and royalty resources in their countries of origin, they will likely suffer from budgetary cutbacks. The downturn in global commodity prices may also affect the motivation for some of the Chinese infrastructure finance linked to natural resource development. Private Investors—Over the Hill Private investment commitments in the Sub-Saharan power sector surged from $40 million in 1990 to $77 million in 1995, then to $451 million in 2000 and $1.2 billion in 2008. It is important to note that these and all Closing Africa’s Power Funding Gap 171 values reported here exclude royalty payments to governments for power infrastructure, which—although valuable from a fiscal perspective— do not contribute to the creation of new power assets. When project implementation cycles are taken into account, this translates to average annual disbursements in recent years of $460 million, or 0.07 percent of GDP (see table 7.1). These disbursements are very similar in magni- tude to those received from non-OECD financiers, although their com- position differs. Private capital flows to the African power sector have been volatile over time (figure 7.6a), with occasional spikes driven by the closure of a handful of large deals. Excluding this handful of megaprojects, the typical average annual capital flow to African power sector since 2000 has aver- aged no more than $450 million. About 80 percent of private finance for African power has gone to greenfield projects with some $7.7 billion of cumulative commitments, a further 17 percent to concessions that amount to cumulative commit- ments of $1.6 billion, and the remaining 1 percent to divestitures that total $124 million (figure 7.6b). Private capital flows, in particular, are likely to be affected by the 2008 global financial crisis. In the aftermath of the Asian financial crisis, private participation in developing countries fell by about one-half over a period of five years following the peak of this participation in 1997. Existing transactions are also coming under stress as they encounter difficulties refinancing short- and medium-term debt. Local Capital Markets—A Possibility in the Medium Term The outstanding stock of power infrastructure issues in the local capital markets in Africa is $9.6 billion. This is very little compared with annual power sector financing needs ($40.1 billion) and the funding gap ($22.3 billion). Furthermore, this is barely 13 percent of the total outstanding stock of infrastructure issues. In the power sector, the sources of financ- ing are divided almost equally among corporate bond issues (38 percent of total), equity issues (34 percent of total), and bank loans (28 percent of total). Other than in South Africa, corporate bonds are almost nonex- istent. Approximately half of local financing of the power sector comes from loans received from the banks, and the other half is covered by utility-issued securities. In South Africa, the picture is very different: Approximately half of financing is a result of corporate bond issuance, almost one-third comes from issuing securities, and only 18 percent is bank lending. 172 Africa’s Power Infrastructure Figure 7.6 Overview of Private Investment to African Power Infrastructure a. Over time 60,000 50,000 40,000 $ million 30,000 20,000 10,000 0 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 19 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 year b. By type of project $1,598 million $124 million 17% 1% $7,737 million 82% concessions divestitures greenfield projects Source: PPIAF 2008. Closing Africa’s Power Funding Gap 173 Although half of the total value of corporate bonds in infrastructure is accounted for in power utilities, only one-quarter of total bank loans to infrastructure goes to the power sector, and only 6 percent of the total value of equity issues is attributed to the power sector (table 7.8). By comparing countries of different types, one can see that most local capital market financing outside South Africa goes to nonfragile low- income countries (55 percent of total value), and another large part ends up in resource-rich countries (39 percent of total value). Almost the entire value of equities (99 percent of total) is issued in nonfragile low- income countries, and a similar distribution can be observed for corporate bonds, with 88 percent of their value associated with issues in nonfragile low-income countries, although the total value of corporate bonds issued outside South Africa is negligible at $59 million. Most bank loans (68 per- cent of total) benefit resource-rich countries (table 7.9). Bank Lending As of the end of 2006, the amount of commercial bank lending to infra- structure in Africa totaled $11.3 billion. More than $2.7 billion of this total was related to power and water utilities, but distribution between these two sectors was unclear (table 7.8). As well as being limited in size, bank lending to infrastructure tends to be short in tenure for all but the most select bank clients, which reflects the predominantly short-term nature of banks’ deposits and other liabili- ties. Financial sector officials in Ghana, Lesotho, Namibia, South Africa, Uganda, and Zambia reported maximum maturity terms of 20 years, the longest such maturities among the focus countries. Eight other countries reported maximum loan maturities of “10 years plus,” and maximum maturities in four countries were reported as five or more years. Even where 20-year terms are reportedly available, they may not be affordable for infrastructure purposes. In Ghana and Zambia, for example, average lending rates exceed 20 percent because it is difficult to find infrastruc- ture projects that generate sufficient returns to cover a cost of debt that is greater than 20 percent. For most Sub-Saharan countries, the capacity of local banking systems is too small and constrained by structural impediments to adequately finance infrastructural development. There may be somewhat more potential in this regard for syndicated lending to infrastructure projects with the participation of local banks, which has been on an overall trend of increase in recent years. The volume of syndicated loans to infrastruc- ture borrowers rose steeply from $0.6 billion in 2000 to $6.3 billion in 174 Table 7.8 Financial Instruments for Locally Sourced Infrastructure Financing $ million % of total local capital market financing Bank Government Corporate Equity Bank Government Corporate Equity loans bondsa bonds issues Total loans bondsa bonds issues Africa excluding South Africa All infrastructure 5,007.9 46.8 548.1 7,796.2 13,399.0 37 0.30 4 58 Electricity 1,430.9 0.0 58.9 1,302.9 2,792.7 51 0.00 2 47 South Africa All infrastructure 6,274.9 754.3 6,841.3 48,148.7 62,019.2 10 1.00 11 78 Electricity 1,263.8 0.0 3,613.9 1,965.4 6,843.1 18 0.00 53 29 Africa total All infrastructure 11,282.7 801.1 7,389.4 55,944.9 75,418.1 15 1.00 10 74 Electricity 2,694.7 0.0 3,672.8 3,268.4 9,635.9 28 0.00 38 34 Source: Adapted from Irving and Manroth 2009. a. The actual amount of government bonds financing infrastructure may be an underestimate, as a specific financing purpose for these bond issues is generally unavailable. Some of the financing raised via these issues may have been allocated toward infrastructure. Closing Africa’s Power Funding Gap 175 Table 7.9 Outstanding Financing for Power Infrastructure, 2006 Bank Corporate Equity Share of Share of total loans bonds issues Total total infrastructure ($ million) ($ million) ($ million) ($ million) stock (%) stock (%) South Africa 1,264 3,614 1,965 6,843 70 11 Middle income (excluding South Africa) 103 — — 103 1 19 Resource rich 1,119 7 15 1,141 12 43 Nonfragile low income 350 52 1,235 1,637 17 22 Fragile low income 69 — — 69 1 15 Total 2,905 3,673 3,215 9,793 100 14 Share of total stock (%) 30 38 33 100 Share of total infrastructure stock (%) 4 5 4 14 Source: Adapted from Irving and Manroth 2009. Note: — = data not available. 2006, with 80 percent of this amount concentrated in South Africa (Irving and Manroth 2009). As of 2006, the power sector accounted for only 1.4 percent of the value of the syndicated infrastructure loans in Africa. The two major power sector transactions based on syndicated loans for 2006 are reported in table 7.10. Much of this finance is denominated in local currency. Maturities are four to nine years in length with undisclosed spreads. The largest loan is the UNICEM power plant construction loan in Nigeria, which comprised a $210.6 million mixed naira-dollar–denominated loan delivered in four tranches raised from eight local banks, one U.S. bank (Citibank), and a local affiliate of a regional Ecobank. Equity Although the infrastructure companies issue only 7.7 percent of total value of corporate equities in the region, equity financing is a large part of overall local capital market infrastructure financing. A total of $55.9 billion of capital has been raised for infrastructure in this way, including $48.1 billion in South Africa alone and $7.8 billion outside South Africa (table 7.8). The region’s stock exchanges played an important role in rais- ing capital for the power sector, with $3.3 billion raised in this way in 176 Table 7.10 Syndicated Loan Transactions for Power Sector in 2006 Loan amount Currency Number of Country Borrower Project ($ million) denomination tranches Maturity Pricing Bank participation: local vs. nonlocal Nigeria UNICEM Power plant 210.6 Naira and 4 4 years, 7 Undisclosed 8 local; 1 U.S. (Citibank); 1 local affiliate construction dollar years, 9 years of regional Ecobank Kenya Iberafrica Electric utility 16.8 Dollar 1 5 years Undisclosed 1 local; Banque de Afrique (Benin); Power 1 local subsidiary of Stanbic Bank Source: Adapted from Irving and Manroth 2009. Closing Africa’s Power Funding Gap 177 Africa overall, including $2.0 billion in South Africa and $1.3 billion outside South Africa (table 7.11). As of 2006, the largest outstanding value was a KenGen issue on the Nairobi stock exchange that constituted 71 percent of total outstanding equity value in the power sector. The second largest equaled one-quarter of the total value in the sector. The remaining issues were quite small. Overall, power issues account for 2 percent of Sub-Saharan Africa’s stock exchange listings by value (table 7.11). Corporate Bonds In the last decade, governments in the region extended the maturity pro- file of their security issues in an effort to establish a benchmark against which corporate bonds can be priced. Except in South Africa, however, corporate bond markets remain small and illiquid, where they exist at all. At 13 percent of GDP, South Africa’s corporate bond market is by far the largest in the region, with $33.8 billion in issues outstanding at the end of 2006, followed by Namibia’s at $457 million (7.1 percent of GDP). Outside South Africa, the few countries that had corporate bonds listed on their national or regional securities exchange at the end of 2006 had only a handful of such listings, and the amounts issued were small. Overall, $3.7 billion of corporate bonds issued by power companies were outstanding as of the end of 2006 (table 7.8). As much as 98 per- cent of these were issued in South Africa by Eskom, which represents Table 7.11 Details of Corporate Equity Issues by Power Sector Companies by End of 2006 Percentage Outstanding of all stocks Stock value on country Country Issuer exchange ($ million) exchange Côte Compagnie Ivoirienne d’Electricitév BRVM 53.4 4.0 d’Ivoire Kenya Kenya Power & Lighting Ltd. Nairobi SE 307.9 2.7 KenGen Nairobi SE 926.6 8.0 Kenya Power & Lighting Ltd. Pref. 4% Nairobi SE AIM 0.2 0.002 Kenya Power & Lighting Ltd. Pref. 7% Nairobi SE AIM 0.05 0.0004 Nigeria Nigeria Energy Sector Fund Nigeria SE 14.8 0.06 Total electricity generation/power 1,302.9 2.0 Source: Adapted from Irving and Manroth 2009. Note: AIM = alternative investment market; BRVM = Bourse Régionale des Valeurs Mobilières (regional stock exchange). 178 Africa’s Power Infrastructure 11 percent of the total value of outstanding corporate bonds and 53 percent of outstanding infrastructure bonds in that country. Only $0.5 billion in power sector bonds were issued outside South Africa in countries such as Benin, Burkina Faso, Kenya, Mozambique, Namibia, Senegal, Uganda, and Zambia. These small bond issues represent a large portion of total bond value in the respective countries. A single listing of Communauté Electrique de Benin in a small amount of $33.2 million accounted for 60 percent of total corporate bonds outstanding on BRVM. A listing of Zambia’s Lunsemfwa Hydro Power in the amount of $7.0 million represented 43 percent of the Lusaka Stock Exchange’s corporate bond value (table 7.12). Institutional investors, including pension funds and insurance compa- nies, could potentially become an important source of infrastructure financing in the future, with approximately $92 billion in assets accumu- lated in national pension funds and more than $181 billion in insurance assets. However, only a fraction of 1 percent of these assets is invested in infrastructure. It is not expected that this situation will change in the near future or without significant improvement in the macroeconomic environment. Costs of Capital from Different Sources The various sources of infrastructure finance reviewed in the previous sections differ greatly in their associated costs of capital (figure 7.7). For public funds, raising taxes is not a costless exercise. Each dollar raised and Table 7.12 Details of Corporate Bonds Issued by Telecom Operators by End of 2006 Percentage Maturity Outstanding of all Stock Issue terms value corporate Country Issuer exchange date (years) ($ million) bond issues Benin Communauté Electrique BRVM 2003 7 33.2 60 de Benin Communauté Electrique BRVM 2004 7 18.7 34 de Benin Zambia Lunsemfwa Hydro Power LuSE 2003 n.a. 7.0 43 Total electricity generation/power 58.9 6 Source: Adapted from Irving and Manroth 2009. Note: BRVM = Bourse Régionale des Valeurs Mobilières (regional stock exchange); LuSE = Lusaka Stock Exchange; n.a. = not available. Closing Africa’s Power Funding Gap 179 Figure 7.7 Costs of Capital by Funding Source public 1.17 India 0.91 China 0.87 Arab funds 0.65 ODA 0.51 IDA 0.33 grants 0.00 0.00 0.20 0.40 0.60 0.80 1.00 1.20 cost of raising $1 of financing Source: Average marginal cost of public funds as estimated by Warlters and Auriol (2005); cost of equity for private sector as in Estache and Pinglo (2004) and Sirtaine and others (2005); authors’ calculations. Note: IDA = International Development Association; ODA = official development assistance. spent by a Sub-Saharan African government has a social value premium (or marginal cost of public funds) of almost 20 percent. That premium captures the incidence of that tax on the society’s welfare (caused by changes in consumption patterns and administrative costs, among other things). To allow ready comparisons across financing sources, this study standardized the financial terms as the present value of a dollar raised through each of the different sources. In doing so, it recognized that all loans must ultimately be repaid with tax dollars, each of which attracts the 20 percent cost premium. Wide variation exists in lending terms. The most concessional IDA loans charge zero interest (0.75 percent service charge) with a 10-year grace period. India, China, and the Arab funds charge 4 percent, 3.6 per- cent, and 1.5 percent interest, respectively, and grant a four-year grace period. The cost of non-OECD finance is somewhere between that of public funds and ODA. The subsidy factor for Indian and Chinese funds is about 25 percent and for the Arab funds, 50 percent. ODA typically provides a subsidy factor of 60 percent, rising to 75 percent for IDA resources. In addition to the cost of capital, sources of finance differ in the transaction costs associated with their use, which may offset or accentuate some of the differences. 180 Africa’s Power Infrastructure The Most Promising Ways to Increase Funds Given this setting, what are the best ways to increase availability of funds for infrastructure development? The place to start is clearly to get the most from existing budget envelopes by tackling inefficiencies. For some countries, this would be enough to close the funding gap in the power sector. For several others, however, particularly the fragile states, even after capturing all efficiency gains, a significant funding gap would remain. The prospects for improving this situation are not good, espe- cially considering the long-term consequences of the recent financial cri- sis. The possibility exists across the board that all sources of infrastructure finance in Africa may fall rather than increase, which would further widen the funding gap. Only resource-rich countries have the possibility of using natural resource savings accounts to provide a source of financ- ing for infrastructure, but only if macroeconomic conditions allow. What Else Can Be Done? The continent faces a substantial funding gap for power even if all the existing sources of funds—including efficiency gains—are tapped. What other options do these countries have? Realistically, they need either to defer the attainment of the infrastructure targets proposed here or to try to achieve them by using lower-cost technologies. Taking More Time The investment needs presented in this book are based on the objective of redressing Africa’s infrastructure backlog within 10 years. It has been shown that it would be possible for middle-income states to meet this tar- get within existing resource envelopes if the efficiency of resource use could be substantially improved. The same cannot be said for the other country groups. Extending the time horizon for the achievement of these goals should make the targets more affordable. But how long of a delay would be needed to make the infrastructure targets attainable without increasing existing spending envelopes? By spreading the investment needs over 30 rather than 10 years, both resource-rich and nonfragile low-income countries could achieve the pro- posed targets within the existing spending envelopes. The fragile low- income countries would need to spread the investment needs over 60 years to reach the targets using the existing spending levels. These esti- mates are contingent on achieving efficiency gains, without which the time Closing Africa’s Power Funding Gap 181 horizon for meeting the targets would be substantially longer than 30 and 60 years, respectively. Alternatively, the countries would need to consider- ably increase their existing spending to reach the targets (figure 7.8a). Lowering Costs through Regional Integration As we have already shown, regional integration is a crucial step in the power sector reform that would substantially reduce costs, mainly Figure 7.8 Spreading Investment over Time a. Resource envelope plus potential efficiency gains 300 (% deviation from current envelope) variation in resources needed 250 200 150 100 50 0 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 number of years needed to attain investment targets b. Existing resource envelope 600 (% deviation from current envelope) 550 variation in resources needed 500 450 400 350 300 250 200 150 100 50 0 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 number of years needed to attain investment targets Sub-Saharan Africa fragile low income nonfragile low income middle income resource rich Source: Foster and Briceño-Garmendia 2009. Note: The threshold is the index value of 100. 182 Africa’s Power Infrastructure because of economies of scale and increased share of hydropower in total power generation. Pooling energy resources through regional power trade promises to sig- nificantly reduce power costs. In recognition of this benefit, regional power pools have been formed in Southern, West, East, and Central Africa and are at varying stages of maturity. If pursued to its full economic potential, regional trade could reduce the annual costs of power system operation and development by $2.7 billion (assuming efficiency gains have been achieved). The savings come largely from substituting hydropower for thermal power, which would lead to a substantial reduction in operating costs, even though it entails higher investment in capital-intensive hydropower and associated cross-border transmission in the short run. The returns to cross-border transmission can be as high as 120 percent (Southern African Power Pool) or more—typically 20–30 percent for the other power pools. By increasing the share of hydropower, regional trade would also save 70 million tons per year of carbon dioxide emissions. Regional power trade would lead to an increase in the share of hydropower in Africa’s generation portfolio from 36 percent to 48 percent, displacing 20,000 MW of thermal plant and saving 70 million tons per year of carbon dioxide emissions (8 percent of Sub-Saharan Africa’s anticipated emissions through 2015). Optimizing power trade would require 82 gigawatts (GW) of addi- tional generation capacity and 22 GW of new cross-border transmission capacity. New generation, transmission, and distribution will require a substantial investment of $25 billion a year for the next 10 years, but the long-term marginal cost of producing and distributing power, which takes into account construction costs, still averages 13 percent below the cur- rent total costs and only 40 percent above the current effective tariffs. The Way Forward The cost of meeting the power sector spending needs estimated in this volume amounts to $40.1 billion a year, far above existing power sec- tor spending of $11.6 billion a year. The difference between spending needs and current spending cannot be bridged entirely by capturing the estimated $8.2 billion a year of inefficiencies that exist at present, mainly in poorly operated utilities. No exceptions can be found to this general conclusion among country types: No country group covers more than 50 percent of its power sector funding gap by eliminating inefficiencies. Closing Africa’s Power Funding Gap 183 The inefficiencies in question arise from system losses, undercollection and overstaffing ($4.4 billion a year), underrecovery of costs ($3.6 billion a year), and underexecution of capital budgets ($0.2 billion a year). These findings underscore the importance of completing the reform agenda out- lined previously to ensure adequate investment and O&M budgets. Reforming public utilities and improving their operating performance will both increase the level of reinvestment from own resources and reduce their credit risk, enabling them to more easily access private debt markets. Policy and regulatory reforms are important for increased private sector participation. Raising further finance for power infrastructure, particularly invest- ment in new capacity and transmission, will be challenging. Historically, the main sources of finance have been public budgets and ODA, both of which are likely to suffer as a result of the 2008 global financial crisis. More emphasis will need to be placed on increasing finance from the pri- vate sector and non-OECD sources. Note 1. For a detailed analysis of electricity tariffs and cost recovery issues in Sub- Saharan Africa, see Briceño-Garmendia and Shkaratan (2010). 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Closing Africa’s Power Funding Gap 185 Warlters, Michael, and Emmanuelle Auriol. 2005. “The Marginal Cost of Public Funds in Africa.” Policy Research Working Paper 3679, World Bank, Washington, DC. World Bank. 2005. Global Monitoring Report 2005. Washington, DC: World Bank. ———. 2007. DEPweb glossary. Development Education Program, World Bank, Washington, DC. http://www.worldbank.org/depweb/english/modules/ glossary.html#middle-income. World Economic Outlook. 2008. “Estimating the Size of the European Stimulus Packages for 2009.” International Monetary Fund, Washington, DC. APPENDIX 1 Africa Unplugged 187 188 Table A1.1 National Power System Characteristics Installed generation capacity per million Installed people Operational capacity System Generation technology, % generation (MW/million as percentage of capacity of country total capacity (MW) people ) installed capacity (%) factor (%)a Hydro Oil Gas Coal Benin 122 14 36.4 20.9 0.0 100.0 0.0 0.0 Botswana 132 70 100.0 62.8 0.0 17.0 0.0 83.0 Burkina Faso 180 13 100.0 32.7 24.6 75.0 0.0 0.0 Cameroon 902 54 100.0 50.3 92.0 8.0 0.0 0.0 Cape Verde 78 150 100.0 6.5 0.0 95.5 0.0 4.5 Chad 29 3 100.0 45.9 0.0 100.0 0.0 0.0 Congo, Dem. Rep. 2,443 41 40.9 82.1 96.4 3.6 0.0 0.0 Congo, Rep. 120 33 — 38.8 82.3 17.7 0.0 0.0 Côte d’Ivoire 1,084 59 100.0 58.2 42.3 11.4 45.8 0.0 Ethiopia 755 10 95.5 41.0 89.1 9.7 0.0 0.0 Ghana 1,622 72 100.0 44.5 53.3 34.3 6.7 0.0 Kenya 1,211 34 87.6 57.5 58.1 27.2 0.0 0.0 Lesotho 76 42 95.1 65.0 97.9 2.1 0.0 0.0 Madagascar 227 12 61.7 79.3 56.8 43.2 0.0 0.0 Malawi 285 22 91.6 59.8 91.4 3.2 0.0 0.0 Mali 278 23 79.0 38.7 56.3 43.7 0.0 0.0 Mozambique 233 12 63.5 — 93.8 5.6 0.0 0.0 Namibia 393 192 100.0 45.9 62.2 6.6 0.0 31.1 Niger 105 7 87.9 25.0 0.0 69.1 0.0 30.9 Nigeria 5,898 41 63.4 73.6 22.8 14.8 60.3 0.0 Rwanda 31 3 100.0 42.8 95.6 — 0.0 0.0 Senegal 300 25 100.0 65.8 0.0 96.1 0.0 0.0 South Africa 40,481 854 89.9 71.5 5.5 2.0 0.3 86.7 Sudan 801 22 100.0 — 18.6 66.0 9.4 0.0 Tanzania 881 22 96.3 25.3 52.5 24.8 17.7 0.6 Uganda 321 11 70.2 — 85.3 11.8 0.0 0.0 Zambia 1,778 150 66.6 85.3 92.9 5.3 0.0 0.0 Zimbabwe 1,960 146 98.5 43.5 38.3 0.0 0.0 61.7 Benchmarks (Weighted Averages) Sub-Saharan Africa 4,760 91 85.1 68.1 18.1 6.0 5.9 65.4 CAPP 709 27 100.0 50.1 77.7 22.3 0.0 0.0 EAPP 1,169 23 68.9 63.0 79.0 14.0 1.8 0.1 SAPP 9,855 219 86.4 71.2 13.2 2.5 0.1 79.4 WAPP 3,912 41 76.0 64.0 29.4 23.4 44.4 0.2 Predominantly thermal capacity 9,129 158 86.7 71.3 7.8 4.4 5.6 77.5 Predominantly hydro capacity 1,101 34 79.5 60.8 73.7 14.8 7.0 1.1 Installed capacity high 7,625 140 84.7 71.0 15.2 4.6 6.1 69.4 Installed capacity medium 597 19 93.6 49.0 65.2 27.9 2.0 3.0 Installed capacity low 73 10 78.6 30.1 52.9 40.0 0.0 6.4 Source: Eberhard and others 2008. Note: Data as of 2005 or the earliest year available before 2005. For Botswana, Republic of Congo, Mali, and Zimbabwe, data for 2007. kWh = kilowatt hour; MW = megawatt; CAPP = Central African Power Pool; EAPP = East African Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool. — = data not available. 189 a. Calculated as ratio of electricity generated (watt-hours [Wh]) to installed operational capacity in Wh (W x 24 x 365). Table A1.2 Electricity Production and Consumption 190 Consumption of electricity by customer group, as Consumption per customer Generation and net imports percentage of total (%) by customer group (kWh/month) Net electricity Net electricity Net import generated generated per capita (import-export) Medium High Low Medium High (GWh/year) (kWh/capita/year) (GWh/year) Low voltage voltage voltage voltage voltage voltage Benin 81 9 595 40.1 40.1 19.8 35 22,079 — Botswana 726 386 2,394 — — — — — — Burkina Faso 516 38 0 63.1 36.9 0.0 111 22,141 — Cameroon 4,004 240 0 32.8 22.9 44.2 170 49,537 40,108,583 Cape Verde 45 87 0 49.7 38.0 12.3 94 2,266 — Chad 117 12 0 63.5 36.5 0.0 205 33,904 — Congo, Dem. Rep. 7,193 121 –1,794 0.0 14.7 85.3 — — 31,397,692 Congo, Rep. 407 115 449 — — — — — — Côte d’Ivoire 5,524 299 –1,397 51.3 48.7 0.0 147 47,018 — Ethiopia 2,589 36 0 34.9 25.2 39.9 77 387 550,933 Ghana 6,750 300 176 13.4 10.1 76.5 71 1,949 5,214,850 Kenya 5,347 152 28 34.1 20.4 45.4 169 22,997 366,611 Lesotho 410 229 13 38.2 35.1 26.7 293 3,068 54,278 Madagascar 973 51 0 58.6 36.8 4.6 92 25,610 962,978 Malawi 1,368 104 0 35.7 17.1 47.2 252 496 61,300 Mali 942 76 2.27 — — — — — — Mozambique 147 7 –2,413 36.8 40.9 22.3 127 28,998 — Namibia 1,580 770 1,489 3.5 4.0 92.5 161 3,068 — Niger 202 14 220 60.6 0.1 39.4 134 20 5,466,667 Nigeria 24,079 166 0 51.0 27.0 22.0 897 739 22,692 Rwanda 116 13 110 — — — — — — Senegal 2,105 176 0 58.5 31.3 10.1 139 39,774 4,805,556 South Africa 228,071 4,813 –2,343 7.9 5.8 86.3 336 12,170 1,149,338 Sudan — — — — — — — — — Tanzania 1,880 48 136 43.6 14.9 41.5 162 24,898 169,305 Uganda 1,893 63 –170 19.0 7.6 73.4 120 — 150,682 Zambia 8,850 746 222 — — — — — — Zimbabwe 7,471 557 2,659 — — — — — — Benchmarks (Weighted Averages) Sub-Saharan Africa 23,337 470 –214 32 22 33 2,049 81,492 4,285,319 CAPP 2,583 147 0 31 21 39 2,051 584,560 481,303,000 EAPP 3,808 77 –282 21 17 62 1,591 18,972 2,483,018 SAPP 52,890 1,214 –521 7 6 80 2,161 113,767 15,830,794 WAPP 16,079 171 –51 44 27 27 2,234 90,760 370,686 Predominantly thermal 53,340 963 –153 12 8 77 2,360 20,203 4,454,510 Predominantly hydro 3,925 161 –257 21 17 41 1,694 281,735 2,968,714 Installed capacity high 41,975 822 –836 12 9 74 2,355 96,812 4,523,681 Installed capacity medium 2,113 77 162 33 19 42 1,561 17,773 1,978,348 Installed capacity low 149 22 156 28 28 8 1,058 49,345 855,338 Source: Eberhard and others 2008. Note: Data as of 2005 or the earliest year available before 2005. For Botswana, Republic of Congo, Mali, and Zimbabwe, data as of 2007. GW = gigawatt; kWh = kilowatt hour; CAPP = Central African Power Pool; EAPP = East African Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool. — = data not available. 191 Table A1.3 Outages and Own Generation: Statistics from the Enterprise Survey 192 Electricity cited as Power Power outages, Equipment destroyed Generator Power from own business constraint, % firms outages (days) % sales by outages, % sales owners, % firms generator (%) Algeria 11.47 12.32 5.28 — 29.49 6.22 Benin 69.23 56.12 7.79 1.54 26.90 32.80 Botswana 9.65 22.29 1.54 — 14.91 17.57 Burkina Faso 68.97 7.82 3.87 — 29.82 6.52 Burundi 79.56 143.76 11.75 — 39.22 25.28 Cameroon 64.94 15.80 4.92 — 57.79 7.62 Cape Verde 70.69 15.18 6.87 — 43.10 13.53 Egypt, Arab Rep. 26.46 10.40 6.12 — 19.26 5.87 Eritrea 37.66 74.61 5.95 — 43.04 9.31 Ethiopia 42.45 44.16 5.44 — 17.14 1.58 Kenya 48.15 53.40 9.35 0.34 73.40 15.16 Madagascar 41.30 54.31 7.92 0.91 21.50 2.23 Malawi 60.38 63.21 22.64 — 49.06 4.44 Mali 24.18 5.97 2.67 1.36 45.33 5.09 Mauritania 29.66 37.97 2.06 — 26.25 11.75 Mauritius 12.68 5.36 4.01 0.42 39.51 2.87 Morocco 8.94 3.85 0.82 — 13.81 11.16 Namibia 15.09 0.00 1.20 — 13.21 13.33 Niger 26.09 3.93 2.72 — 27.54 14.74 Senegal 30.65 25.64 5.12 0.62 62.45 6.71 South Africa 8.96 5.45 0.92 — 9.45 0.17 Swaziland 21.43 32.38 1.98 — 35.71 10.33 Tanzania 60.24 63.09 — 0.81 59.05 12.28 Uganda 43.85 45.50 6.06 0.74 38.34 6.56 Zambia 39.61 25.87 4.54 0.28 38.16 5.13 Average 38.09 33.14 5.48 0.78 34.94 9.93 Source: Foster and Steinbuks 2008. Note: — = data not available. Africa Unplugged 193 Table A1.4 Emergency, Short-Term, Leased Generation Emergency Cost of Emergency Total generation emergency generation generation capacity, generation, capacity (MW) capacity (MW) % of total % GDP Sierra Leone 20 49 40.8 4.25 Uganda 100 303 33.0 3.29 Madagascar 50 227 22.0 2.79 Ghana 80 1,490 5.4 1.90 Rwanda 15 39 38.5 1.84 Kenya 100 1,211 8.3 1.45 Senegal 40 428 9.3 1.37 Angola 150 830 18.1 1.04 Tanzania 40 881 4.5 0.96 Gabon 14 414 3.4 0.45 Total 609 5,872 183.0 19.00 Source: Foster and Steinbuks 2008. Note: Emergency power plant is generally leased for short periods and thus the amount of emergency power in individual countries varies from year to year. GDP = gross domestic product; MW = megawatt. Table A1.5 Distribution of Installed Electrical Generating Capacity between Network and Private Sector Self-Generation Self-generation, by sector, % of total Utility and government, Commerce/ % of total Mining Fuels Manufacturing services Angola 94 2.69 2.65 0.19 0.14 Benin 97 0.00 0.00 3.13 0.00 Botswana 91 8.84 0.00 0.00 0.00 Burkina Faso 100 0.00 0.00 0.00 0.00 Burundi 98 0.00 0.00 0.41 1.84 Cameroon 99 0.00 0.95 0.00 0.01 Cape Verde 100 0.00 0.00 0.00 0.09 Central African Republic 100 0.00 0.00 0.00 0.23 Chad 100 0.00 0.00 0.00 0.00 Comoros 100 0.00 0.00 0.00 0.00 Congo, Dem. Rep. 93 3.19 1.18 0.13 2.55 Congo, Rep. 53 0.00 42.39 4.43 0.00 Côte d’Ivoire 96 0.00 3.41 0.53 1.48 Equatorial Guinea 49 0.00 51.34 0.00 0.00 Eritrea 100 0.00 0.00 0.00 0.00 Ethiopia 99 0.00 0.00 0.17 0.36 (continued next page) 194 Africa’s Power Infrastructure Table A1.5 (continued) Utility and Self-generation, by sector, % of total government, Commerce/ % of total Mining Fuels Manufacturing services Gabon 81 0.76 18.15 0.00 0.00 Gambia 98 0.00 0.00 0.00 1.55 Ghana 87 0.31 12.53 0.23 0.00 Guinea 82 18.49 0.00 0.00 0.00 Guinea-Bissau 94 0.00 0.00 6.43 0.00 Kenya 95 0.00 0.00 4.28 0.68 Lesotho 100 0.00 0.00 0.00 0.00 Liberia 100 0.00 0.00 0.00 0.00 Madagascar 100 0.00 0.00 0.00 0.02 Malawi 94 0.00 0.00 5.92 0.00 Mali 91 8.14 0.00 0.00 0.69 Mauritania 38 57.10 4.19 0.00 0.23 Mauritius 77 0.00 0.00 20.31 3.03 Mozambique 99 0.00 0.00 0.81 0.33 Namibia 100 0.00 0.00 0.00 0.00 Niger 76 21.79 3.45 1.89 0.00 Nigeria 78 0.50 10.84 3.09 7.75 Rwanda 93 0.00 0.00 4.98 1.83 São Tomé and Príncipe 100 0.00 0.00 0.00 0.00 Senegal 99 0.00 0.00 0.00 0.73 Seychelles 100 0.00 0.00 0.00 0.00 Sierra Leone 100 0.00 0.00 0.00 0.00 Somalia 100 0.00 0.00 0.00 0.00 South Africa 98 0.22 0.63 0.92 0.03 Sudan 93 0.00 1.32 5.31 0.02 Swaziland 49 2.97 0.00 48.53 0.00 Tanzania 89 5.32 0.56 3.58 1.99 Togo 79 20.50 0.00 0.00 1.00 Uganda 93 3.70 0.00 0.32 3.39 Zambia 98 0.00 0.00 0.68 1.38 Zimbabwe 96 0.00 0.00 4.11 0.02 Average 90 3.29 3.27 2.56 0.67 Source: Foster and Steinbuks 2008. Africa Unplugged 195 Table A1.6 Effect of Own Generation on Marginal Cost of Electricity $/kWh Average Average Average Price of Weighted variable cost capital cost total cost kWh average of own of own of own purchased cost of electricity electricity electricity from public electricity (A) (B) (C = A + B) grid (D) (E = ∂C+[1–∂]D)d Algeria 0.04 0.11 0.15 0.03c 0.05 Benin 0.36 0.10 0.46 0.12c 0.27 Burkina Fasoa 0.42 0.32 0.74 0.21c 0.23 Cameroona 0.41 0.04 0.46 0.12c 0.16 Cape Verde a 0.46 0.04 0.50 0.17c 0.26 Egypt, Arab Rep. 0.04 0.26 0.30 0.04c 0.12 Eritrea 0.11 0.03 0.13 0.11 0.12 Kenya 0.24 0.06 0.29 0.10 0.14 Madagascar 0.31 0.08 0.39 — — Malawi 0.46 0.03 0.50 0.05c 0.09 Mali 0.26 0.26 0.52 0.17 0.21 Mauritius 0.26 0.35 0.61 0.14c 0.25 Morocco 0.31 0.32 0.62 0.08c 0.15 Nigera 0.36 0.04 0.41 0.23c 0.26 Senegal 0.25 0.09 0.34 0.16 0.18 Senegalb 0.28 0.40 0.68 0.16 0.30 South Africa 0.18 0.36 0.54 0.04 0.05 Tanzania 0.25 0.04 0.29 0.09 0.13 Uganda 0.35 0.09 0.44 0.09 0.14 Zambia 0.27 0.18 0.45 0.04 0.06 Average 0.28 0.15 0.43 0.11 0.16 Source: Foster and Steinbuks 2008. Note: kWh = kilowatt hour; — = data not available. a. Tourism industry (hotels and restaurants sector) only. b. Survey of informal sector. c. Data not reported in the enterprise surveys (obtained from the public utilities). d. ∂ Share of total electricity consumption coming from own generation. Table A1.7 Losses Due to Outages (“Lost Load”) for Firms with and without Their Own Generator $/hour Without own generator With own generator Algeria 155.8 52.2 Benin 38.4 23.1 Burkina Fasoa 114.1 13.0 Cameroona 403.6 12.3 (continued next page) 196 Africa’s Power Infrastructure Table A1.7 (continued) Without own generator With own generator Cape Verdea 177.7 36.4 Egypt, Arab Rep. 201.5 30.4 Eritrea 31.9 10.2 Kenya 113.1 37.1 Madagascar 434.5 153.0 Malawi 917.3 401.4 Mali 390.3 9.5 Mauritius 468.6 13.9 Morocco 377.5 22.9 Nigera 81.3 22.6 Senegal 166.0 19.2 Senegalb 12.9 1.9 South Africa 1140.1 66.1 Tanzania — 444.3 Uganda 27.6 191.4 Zambia 286.6 39.2 Average 307.0 84.1 Source: Foster and Steinbuks 2008. Note: — = data not available. a. Survey of tourism sector. b. Survey of informal sector. Table A1.8 Operating Costs of Own Generation Fuel price Cost ($/kWh) (cents/liter) <5 kVA 5–100 kVA 100 kVA–1 MW 1 MW–10 MW Grid Algeria 0.10 0.08 0.05 0.03 0.03 0.03 Benin 0.72 0.58 0.32 0.22 0.19 0.12 Botswana 0.61 0.49 0.27 0.18 0.16 0.04 Burkina Faso 0.94 0.75 0.42 0.28 0.25 0.21 Burundi 1.08 0.86 0.49 0.32 0.29 — Cameroon 0.83 0.66 0.37 0.25 0.22 0.12 Cape Verde 0.81 0.65 0.36 0.24 0.22 0.17 Egypt, Arab Rep. 0.10 0.08 0.05 0.03 0.03 0.04 Eritrea 0.25 0.20 0.11 0.08 0.07 0.11 Ethiopia 0.32 0.26 0.14 0.10 0.09 0.06 Kenya 0.56 0.45 0.25 0.17 0.15 0.10 Madagascar 0.79 0.63 0.36 0.24 0.21 — Malawi 0.88 0.70 0.40 0.26 0.24 0.05 Mali 0.55 0.44 0.25 0.17 0.15 0.17 (continued next page) Africa Unplugged 197 Table A1.8 (continued) Fuel price Cost ($/kWh) (cents/liter) <5 kVA 5–100 kVA 100 kVA–1 MW 1 MW–10 MW Grid Mauritania 0.59 0.47 0.27 0.18 0.16 — Mauritius 0.56 0.45 0.25 0.17 0.15 0.14 Morocco 0.70 0.56 0.32 0.21 0.19 0.08 Namibia 0.65 0.52 0.29 0.20 0.18 0.04 Niger 0.91 0.73 0.41 0.27 0.25 0.23 Senegal 0.53 0.42 0.24 0.16 0.14 0.16 South Africa 0.40 0.32 0.18 0.12 0.11 0.04 Swaziland 0.73 0.58 0.33 0.22 0.20 0.05 Tanzania 0.61 0.49 0.27 0.18 0.16 0.09 Uganda 0.70 0.56 0.32 0.21 0.19 0.09 Zambia 0.60 0.48 0.27 0.18 0.16 0.04 Average 0.62 0.50 0.28 0.19 0.17 0.10 Source: Foster and Steinbuks 2008. Note: kVA = kilovolt-ampere; KWh = kilowatt hour; MW = megawatt; — = data not available. APPENDIX 2 The Promise of Regional Power Trade 199 200 Table A2.1 Projected Trading Patterns in 10 Years under Alternative Trading Scenarios, by Region Trade expansion, 2015 Trade stagnation, 2015 Demand 2005 Demand 2015 Imports Exports Net exports Trade, % of Imports Exports Net exports Trade, % of (TWh) (projected) (TWh) (TWh) (TWh) (TWh) demand (TWh) (TWh) (TWh) demand SAPP Angola 2.1 7.9 11.0 5.0 –6.0 65 0.1 0.1 0 0 Botswana 2.4 4.2 10.4 6.2 –4.3 93 1.2 6.5 5.3 –117 Congo, Dem. Rep. 4.7 13.6 0.4 52.2 51.9 –369 0.4 2.7 2.3 –16 Lesotho 0.4 0.9 0.7 0 –0.7 68 0.7 0 –0.7 68 Malawi 1.3 2.3 1.8 0.3 –1.5 56 0 1.6 1.6 –60 Mozambique 11.2 16.4 13.2 19.1 5.9 –33 7.0 9.2 2.1 –12 Namibia 2.6 4.3 4.9 1.1 –3.8 72 1.2 2.0 0.9 –17 South Africa 215.0 319.2 37.7 1.4 –36.4 10 21.8 7.8 –14.0 4.0 Zambia 6.3 9.3 41.1 39.3 –1.8 18 2.4 8.4 6.0 –62 Zimbabwe 12.8 18.7 25.5 22.0 –3.5 17 12.4 8.8 –3.6 18 Total SAPP 258.8 396.8 146.7 146.6 –0.2 –3 47.2 47.1 –0.1 –194 EAPP/Nile Basin Burundi 0.2 0.7 0.9 0.2 –0.7 78 0 0 0 0 Ethiopia 2.1 10.7 3.4 29.6 26.2 –227 3.4 3.3 –0.1 1 Kenya 4.6 12.0 3.3 0.5 –2.8 22 1.0 0.5 –0.5 3 Sudan 3.2 9.2 29.2 42.4 13.1 –134 0.2 0.2 0 0 Tanzania 4.2 7.9 0.5 2.9 2.4 –22 0.5 0.5 0 0 Uganda 1.6 4.2 0.8 3.6 2.8 –61 0.4 0.8 0.4 –9 Total EAPP/ Nile Basin 15.9 44.7 38.1 79.2 41.0 –344 5.5 5.3 –0.2 –5 WAPP Benin 0.6 1.7 1.0 0 –0.9 45 0.4 0 –0.4 18 Burkina Faso 0.5 1.5 1.0 0 –1.0 58 1.0 0 –1.0 58 Cape Verde 0.04 0.1 0 0 0 — — — — — Côte d’Ivoire 2.9 5.4 11.1 12.0 0.9 –12 0.2 3.7 3.5 –47 Gambia, The 0.1 0.4 0 0.1 0.1 –19 0 0 0 0 Ghana 5.9 12.8 11.0 1.4 –9.6 52 2.8 0.3 –2.6 14 Guinea 0.7 2.1 0 17.4 17.4 –564 0 0 0 0 Guinea-Bissau 0.1 0.2 2.1 1.9 –0.2 77 0 0 0 0 Liberia 0.3 1.3 1.7 0 –1.7 89 0 0 0 0 Mali 0.4 1.8 12.7 10.9 –1.9 79 0.1 0.4 0.3 –14 Niger 0.4 1.3 1.5 0 –1.5 86 0.4 0 –0.4 20 Nigeria 16.9 59.2 2.1 4.2 2.1 –3 2.1 2.4 0.3 0 Senegal 1.5 3.5 2.0 0.7 –1.4 30 0.7 0.1 –0.6 13 Sierra Leone 0.2 1.0 2.6 1.7 –0.9 60 0 0 0 0 Togo 0.6 1.5 1.1 0.2 –0.9 48 0 0.5 0.5 –27 Total WAPP 31.14 93.8 49.9 50.5 0.5 26 7.7 7.4 –0.4 35 CAPP Cameroon 3.4 6.4 0.2 6.9 6.7 –84 0.2 0.2 0 0 Central African Republic 0.1 0.5 0 0 0 0 0 0 0 0 Chad 0.1 0.9 1.3 0 –1.3 102 0 0 0 0 Congo, Rep. 5.8 10.3 4.4 0 –4.4 34 0 0 0 0 Equatorial Guinea 0.03 0.1 0.1 0 –0.1 100 0 0 0 0 Gabon 1.2 1.8 1.0 0 –1.0 42 0 0 0 0 Total CAPP 10.63 20.0 7.0 6.9 –0.1 194 0.2 0.2 0.0 0.0 Source: Rosnes and Vennemo 2008. 201 Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool; TWh = terawatt-hour. — = data not available. 202 Table A2.2 Projected Long-Run Marginal Cost in 10 Years under Alternative Trading Scenarios a. SAPP cents/kWh Trade-expansion scenario Trade-stagnation scenario Cost of generation Cost of generation and international Cost of and international Cost of transmission lines domestic T&D Total LRMCs transmission lines domestic T&D Total LRMCs Angola 1.8 4.6 6.4 5.9 4.6 10.5 Botswana 3.5 2.1 5.6 4.0 2.1 6.1 Congo, Dem. Rep. 1.4 2.4 3.9 1.1 2.4 3.6 Lesotho 3.6 2.2 5.8 4.8 2.2 7.0 Malawi 3.3 1.9 5.1 3.5 1.9 5.4 Mozambique 3.3 0.8 4.1 4.7 0.8 5.5 Namibia 3.6 7.3 10.9 4.7 7.3 12.0 South Africa 3.6 2.0 5.5 4.7 2.0 6.7 Zambia 2.9 4.6 7.5 3.3 4.6 7.8 Zimbabwe 3.2 4.6 7.8 3.9 4.6 8.5 Average 3.3 2.7 6.0 4.6 2.7 7.3 b. EAPP/Nile Basin cents/kWh Trade-expansion scenario Trade-stagnation scenario Cost of generation Cost of generation and international Cost of and international Cost of transmission lines domestic T&D Total LRMC transmission lines domestic T&D Total LRMC Burundi 6.8 4.6 11.4 10.3 4.6 14.9 Djibouti 6.6 0.6 7.2 6.6 0.6 7.2 Egypt, Arab Rep. 7.6 0.9 8.5 7.7 0.9 8.6 Ethiopia 6.9 12.2 19.0 4.0 12.2 16.1 Kenya 7.4 5.0 12.4 8.4 5.0 13.3 Rwanda 6.4 6.1 12.4 6.0 6.1 12.1 Sudan 7.5 5.2 12.7 7.4 5.2 12.6 Tanzania 6.5 3.2 9.7 4.5 3.2 7.8 Uganda 6.8 5.4 12.3 5.9 5.4 11.3 Average 7.4 4.7 12.1 7.5 4.7 12.2 (continued next page) 203 204 Table A2.2 (continued) c. WAPP cents/kWh Trade-expansion scenario Trade-stagnation scenario Cost of generation Cost of generation and international Cost of and international Cost of transmission lines domestic T&D Total LRMCs transmission lines domestic T&D Total LRMCs Benin 7.9 11.1 19.0 8.1 11.1 19.2 Burkina Faso 7.2 18.1 25.3 7.9 18.1 26.0 Côte d’Ivoire 6.9 7.8 14.7 7.6 7.8 15.4 Gambia, The 6.3 1.7 8.0 5.8 1.7 7.4 Ghana 7.3 2.3 9.6 8.0 2.3 10.3 Guinea 5.8 1.3 7.0 4.7 1.3 6.0 Guinea-Bissau 6.3 2.2 8.5 13.4 2.2 15.6 Liberia 6.6 1.5 8.1 12.6 1.5 14.1 Mali 6.4 18.2 24.6 9.7 18.2 27.9 Mauritania 6.9 6.7 13.6 7.8 6.7 14.5 Niger 7.9 16.8 24.7 13.6 16.8 30.4 Nigeria 7.6 5.2 12.8 7.6 5.2 12.8 Senegal 6.6 36.8 43.4 10.0 36.8 46.8 Sierra Leone 6.1 2.4 8.6 7.3 2.4 9.7 Togo 7.6 2.7 10.3 8.0 2.7 10.6 Average 7.2 11.1 18.3 8.0 11.1 19.1 d. CAPP cents/kWh Trade-expansion scenario Trade-stagnation scenario Cost of generation Cost of generation and international Cost of and international Cost of transmission lines domestic T&D Total LRMC transmission lines domestic T&D Total LRMC Cameroon 4.4 2.4 6.9 4.0 2.4 6.4 Central African Republic 4.8 6.3 11.1 4.8 6.3 11.1 Chad 4.9 2.0 6.8 9.0 2.0 10.9 Congo, Rep. 5.4 0.2 5.6 7.9 0.2 8.1 Equatorial Guinea 4.8 2.7 7.5 7.0 2.7 9.7 Gabon 4.9 1.6 6.5 5.9 1.6 7.4 Average 4.9 2.2 7.0 7.0 2.2 9.1 Source: Rosnes and Vennemo 2008. Note: Average is weighted by annualized cost. In some cases power exporting countries report higher LRMC under trade expansion. Even if the cost of meeting domestic power consumption may be higher with trade than without; the higher revenues earned from exports would more than compensate for that increment. CAPP = Central African Power Pool; kWh = kilowatt-hour; LRMC = long-run marginal cost; T&D = transmission and distribution. 205 206 Table A2.3 Projected Composition of Generation Portfolio in 10 Years under Alternative Trading Scenarios % of total Trade expansion, 2015 Trade stagnation, 2015 Hydro capacity Coal and gas Other capacity Hydro capacity Coal and gas Other capacity Angola 88 4 8 80 16 3 Benin 16 0 84 12 28 61 Botswana 0 96 4 0 100 0 Burkina Faso 39 0 61 39 0 61 Burundi 43 0 57 60 0 40 Cameroon 95 0 5 91 0 9 Cape Verde 0 4 96 0 0 0 Central African Republic 100 0 0 100 0 0 Chad 0 0 100 0 0 100 Congo, Dem. Rep 100 0 0 99 0 1 Congo, Rep. 100 0 0 85 0 15 Côte d’Ivoire 77 20 2 79 19 2 Equatorial Guinea 0 100 0 73 27 0 Ethiopia 94 0 6 81 0 19 Gabon 99 0 1 65 0 35 Gambia, The 0 0 100 0 0 100 Ghana 75 19 7 67 28 6 Guinea 99 0 1 94 0 6 Guinea-Bissau 0 0 100 44 0 56 Kenya 42 39 19 36 48 17 Lesotho 95 0 5 95 0 5 Liberia 100 0 0 98 0 2 Madagascar 16 0 84 0 0 0 Malawi 91 6 3 98 2 1 Mali 73 6 21 82 3 14 Mauritania 0 0 100 0 58 42 Mauritius 30 60 9 0 0 0 Mozambique 97 3 0 69 30 0 Namibia 66 33 1 31 68 0 Niger 0 99 1 73 14 13 Nigeria 76 21 3 77 20 3 South Africa 8 82 9 8 83 9 Senegal 0 42 58 9 38 53 Sierra Leone 46 0 54 77 0 23 Sudan 87 6 7 73 13 14 Tanzania 61 35 4 67 29 4 Togo 99 0 1 56 44 0 Uganda 91 0 9 87 0 13 Zambia 95 4 1 97 2 1 Zimbabwe 73 26 1 47 52 1 Source: Rosnes and Vennemo 2008. 207 208 Table A2.4 Projected Physical Infrastructure Requirements in 10 Years under Alternative Trading Scenarios MW Trade expansion Trade stagnation Generation Generation Generation New Generation Generation Generation New capacity: capacity: capacity: new cross-border capacity: capacity: capacity: new cross-border installed refurbishment investments transmission installed refurbishment investments transmission Angola 620 203 8 2,120 620 305 1,184 0 Benin 75 112 4 160 75 112 76 0 Botswana 120 12 2,141 2,120 120 12 0 0 Burkina Faso 66 95 0 0 66 95 0 0 Burundi 13 18 30 78 13 18 173 0 Cameroon 249 596 2,471 831 249 596 1,015 0 Cape Verde 0 1 18 0 Central African Republic 0 18 143 0 0 18 143 0 Chad 0 0 0 202 0 22 174 0 Congo, Dem. Rep. 0 2,236 8,401 5,984 0 2,236 761 0 Congo, Rep. 0 129 1,689 498 0 148 2,381 0 Côte d’Ivoire 498 601 1,368 2,226 498 601 1,562 0 Equatorial Guinea 10 0 0 20 10 0 28 0 Ethiopia 831 335 8,699 2,997 831 335 1,933 0 Gabon 0 163 92 111 0 297 92 0 Gambia, The 22 74 4 19 22 66 4 0 Ghana 1,713 160 1,048 979 1,713 160 1,400 0 Guinea 119 28 4,288 2,283 119 28 568 0 Guinea-Bissau 0 22 0 818 0 22 24 0 Kenya 695 389 987 266 695 395 1,237 0 Lesotho 75 0 0 0 75 0 0 0 Liberia 0 64 0 258 0 73 369 0 Madagascar 87 82 349 0 — — — — Malawi 175 100 1 227 175 100 698 0 Mali 288 46 3 2,703 288 66 284 0 Mauritania 37 63 1 79 37 63 136 0 Mauritius 195 0 0 0 — — — — Mozambique 2,174 180 3,248 1,400 2,174 180 2,348 0 Namibia 240 120 2 556 240 120 1,059 0 Niger 0 38 0 206 0 73 202 0 Nigeria 1,011 5,454 10,828 366 1,011 5,208 10,828 0 South Africa 13,463 21,690 19,399 547 13,463 21,690 20,873 0 Senegal 205 139 258 487 205 139 320 0 Sierra Leone 62 46 1 661 62 46 145 0 Sudan 2,554 0 3,704 1,3491 2,554 0 568 0 Tanzania 468 305 2046 266 468 305 1,767 0 Togo 0 31 200 5 0 91 321 0 Uganda 358 191 1,258 537 358 191 707 0 Zambia 268 1670 3 7,526 268 1,670 1,726 0 Zimbabwe 0 1,835 2,251 3,072 0 1,835 2,158 0 SSA: Total 26,654 37,183 74,942 54,020 26,372 37,253 57,128 0 CAPP: Total 259 906 4,395 1,662 259 1,081 3,833 0 EAPP/Nile Basin: Total 4,919 1,238 16,724 17,635 4,919 1,244 6,385 0 SAPP: Total 17,135 28,046 35,454 23,552 17,135 28,148 30,807 0 WAPP: Total 4,059 6,911 18,020 11,171 4,059 6,780 16,103 0 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; SSA = Sub-Saharan Africa; WAPP = West African 209 Power Pool; MW = megawatt. — = data not available. 210 Table A2.5 Estimated Annualized 10-Year Spending Needs to Meet Infrastructure Requirements under Alternative Trading Scenarios $million/year Trade expansion Trade stagnation Cost of Cost of Cost of Cost of Difference in total investment rehabilitation investment rehabilitation cost: trade in new of existing Variable Total in new of existing Variable Total expansion – trade capacity capacity cost cost capacity capacity cost cost stagnation Angola 359 49 78 486 558 50 177 785 –299 Benin 67 19 93 179 74 19 130 223 –44 Botswana 61 14 39 115 246 14 201 461 –346 Burkina Faso 50 21 71 142 50 21 71 142 0 Burundi 80 2 4 87 140 2 6 148 –61 Cameroon 595 52 97 744 328 52 72 452 292 Cape Verde 9 1 15 24 — — — — 24 Central African Republic 48 2 5 56 48 2 5 56 0 Chad 39 0 1 40 72 1 85 157 –117 Congo, Dem. Rep. 1,275 148 49 1,472 526 148 49 723 749 Congo, Rep. 431 7 43 482 559 7 188 754 –272 Côte d’Ivoire 614 81 131 826 644 81 239 964 –138 Equatorial Guinea 3 0 0 3 11 0 1 12 –9 Ethiopia 3,003 102 276 3,381 2,001 102 178 2,281 1,100 Gabon 36 13 13 62 34 17 64 115 –53 Gambia, The 17 3 38 58 17 3 31 51 7 Ghana 560 42 126 728 588 42 624 1,255 –527 Guinea 947 3 98 1,049 161 3 18 183 866 Guinea-Bissau 11 1 9 20 17 1 11 29 –9 Kenya 676 69 274 1,019 697 69 428 1,194 –175 Lesotho 17 2 7 25 17 2 7 25 0 Liberia 39 3 5 48 228 4 18 250 –202 Madagascar 205 6 267 478 — — — — 478 Malawi 34 9 14 56 167 9 14 190 –134 Mali 112 20 47 179 199 21 82 303 –124 Mauritania 29 7 39 74 41 7 97 145 –71 Mauritius 16 9 29 54 — — — — 54 Mozambique 681 30 60 771 465 30 190 685 86 Namibia 108 61 115 284 207 61 315 583 –299 Niger 34 18 24 76 106 20 59 185 –109 Nigeria 4,246 662 2,828 7,736 4,244 659 2,691 7,594 142 South Africa 4,069 1,846 7,596 13,510 4,306 1,846 7,982 14,134 –624 Senegal 369 122 501 993 385 122 555 1,062 –69 Sierra Leone 36 3 28 66 85 3 31 118 –52 Sudan 1,517 43 187 1,748 485 43 135 663 1,085 Tanzania 579 52 280 911 534 52 176 762 149 Togo 97 5 11 113 109 5 105 219 –106 Uganda 498 38 65 601 353 38 56 448 153 Zambia 234 138 99 471 394 138 99 631 –160 Zimbabwe 650 257 302 1,210 577 257 408 1,243 –33 SSA: Total 22,422 3,953 13,925 40,303 19,632 3,944 15,501 39,080 1,223 CAPP: Total 1,152 74 159 1,387 1,052 79 415 1,546 –159 EAPP/Nile Basin: Total 6,353 306 1,086 7,747 4,210 306 979 5,496 2,251 SAPP: Total 7,488 2,554 8,359 18,400 7,463 2,555 9,442 19,460 –1,060 WAPP: Total 7,208 1,004 4,025 12,237 6,907 1,004 4,665 12,578 –341 211 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; SSA = Sub–Saharan Africa; WAPP = West African Power Pool. — = data not available. APPENDIX 3 Investment Requirements 213 214 Africa’s Power Infrastructure Table A3.1 Power Demand, Projected Average Annual Growth Rate Base growth Low growth Annual scenario, % growth scenario, % growth population Electricity Electricity growth (%) GDP/capita demand GDP/capita demand SAPP Angola 2.8 6.3 9.7 3.6 6.4 Botswana –0.4 4.6 5.2 2.5 2.1 Congo, Dem. Rep. 2.5 1.5 4.2 0.8 3.4 Lesotho –0.3 4.3 5.0 2.4 2.1 Malawi 2.2 1.7 3.6 0.9 2.5 Mozambique 1.7 1.9 3.3 1.0 2.1 Namibia 1.0 4.0 5.5 2.2 3.0 South Africa 0.1 3.7 4.3 2.0 1.8 Zambia 1.7 2.2 3.6 1.1 2.2 Zimbabwe 0.6 2.7 3.3 1.4 1.5 Weighted average 1.6 2.7 4.5 1.5 2.8 EAPP/Nile Basin Burundi 3.2 1.3 4.2 0.7 3.4 Djibouti 1.9 1.4 2.9 0.7 2.0 Egypt, Arab Rep. 1.8 2.3 3.9 1.2 2.5 Ethiopia 2.3 2.6 4.8 1.4 3.2 Kenya 2.6 1.5 3.7 0.8 2.8 Rwanda 2.2 2.7 4.9 0.6 2.2 Sudan 2.0 2.8 4.8 1.5 3.1 Tanzania 1.8 2.3 3.9 1.2 2.4 Uganda 3.8 1.2 4.7 0.6 4.0 Weighted average 2.3 2.2 4.3 1.2 2.9 WAPP Benin 2.5 1.8 4.0 0.9 2.9 Burkina Faso 3.0 0.4 2.8 0.2 2.6 Côte d’Ivoire 1.9 1.0 2.3 0.5 1.7 Gambia, The 2.7 1.3 3.5 0.6 2.7 Ghana 1.9 3.2 5.2 1.6 3.2 Guinea 2.6 1.6 3.9 0.8 2.9 Guinea-Bissau 2.0 0.2 1.4 0.1 1.3 Liberia 3.1 1.6 4.3 0.8 3.4 Mali 2.8 1.9 4.5 1.0 3.4 Mauritania 2.9 4.9 8.1 2.5 5.5 Niger 2.9 0.3 2.5 0.1 2.3 Nigeria 2.4 3.2 5.7 1.6 3.8 Senegal 2.5 2.0 4.3 1.0 3.1 Sierra Leone 2.3 0.5 2.1 0.3 1.8 Togo 2.7 0.2 2.2 0.1 2.1 (continued next page) Investment Requirements 215 Table A3.1 (continued) Base growth Low growth Annual scenario, % growth scenario, % growth population Electricity Electricity growth (%) GDP/capita demand GDP/capita demand Weighted average 2.4 2.4 4.7 1.2 3.3 CAPP Cameroon 2.2 2.0 3.9 1.0 2.7 Central African Republic 1.5 1.5 2.6 0.8 1.5 Chad 2.9 0.8 3.2 0.4 2.7 Congo, Rep. 2.8 2.2 4.8 1.1 3.5 Equatorial Guinea 2.0 3.1 5.1 1.6 3.3 Gabon 2.0 1.2 2.7 0.6 1.9 Weighted average 2.4 1.6 3.6 0.8 2.6 Island States Cape Verde 0.5 4.7 6.0 2.3 3.1 Madagascar 2.5 1.2 3.2 0.6 2.5 Mauritius 0.8 2.9 3.8 1.5 1.9 Weighted average 2.3 1.4 3.3 0.7 2.5 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool; GDP = gross domestic product. Table A3.2 Suppressed Demand for Power Outages Average duration of Down time Suppressed demand (hours per year) outages (hours) (% of a year) in 2005 (GWh) SAPP Angola 1,780.8 19.31 20.3 435 Botswana 38.9 1.86 0.4 11 Congo, Dem. Rep. 659.2 3.63 7.5 351 Lesotho 177.9 7.65 2.0 8 Malawi 328.1 4.27 3.7 49 Mozambique 350.4 6.08 4.0 450 Namibia 46.1 2.32 0.5 13 South Africa 24.5 4.15 0.3 602 Zambia 219.9 5.48 2.5 157 Zimbabwe 350.4 6.08 4.0 512 (continued next page) 216 Africa’s Power Infrastructure Table A3.2 (continued) Outages Average duration of Down time Suppressed demand (hours per year) outages (hours) (% of a year) in 2005 (GWh) Average for available sample 350.4 6.1 4.0 EAPP/Nile Basin Burundi 1,461.5 10.34 16.7 25 Djibouti 456.4 5.88 5.2 12 Egypt, Arab Rep. 43.3 2.48 0.5 417 Ethiopia 456.4 5.88 5.2 109 Kenya 702.6 8.20 8.0 366 Rwanda 346.9 4.47 4.0 5 Sudan 456.4 5.88 5.2 168 Tanzania 435.9 6.46 5.0 208 Uganda 463.8 6.55 5.3 84 Average for available sample 456.4 5.88 5.2 WAPP Benin 505 2.72 6 34 Burkina Faso 196 1.61 2 11 Côte d’Ivoire 1,101 5.94 13 365 Gambia, The 1,961 6.86 22 29 Ghana 1,465 12.59 17 979 Guinea 2,759 6.78 31 224 Guinea-Bissau 1,978 17.94 23 14 Liberia 1,101 5.94 41 123 Mali 453 2.44 5 21 Mauritania 129 2.89 1 3 Niger 124 0.50 1 6 Nigeria 1,101 5.94 64 10,803 Senegal 1,052 5.67 17 250 Sierra Leone 1,101 5.94 82 189 Togo 1,101 5.94 13 73 Average for available sample 1,176 5.94 22 CAPP Cameroon 613 4.03 7.0 241 Central African Republic 950 5.20 10.8 11 (continued next page) Investment Requirements 217 Table A3.2 (continued) Outages Average duration of Down time Suppressed demand (hours per year) outages (hours) (% of a year) in 2005 (GWh) Chad 950 5.20 10.8 10 Congo, Rep. 924 4.33 10.6 616 Equatorial Guinea 950 5.20 10.8 3 Gabon 950 5.20 10.8 134 Average for available sample 889 5.20 10.2 Island States Cape Verde 797.0 5.30 9.0 4 Madagascar 221.1 2.67 2.5 21 Mauritius 1,321.0 7.23 15.1 35 Source: Rosnes and Vennemo 2008. Note: Market demand for power is one of three categories of demand for power, the others being social demand or access, and suppressed demand. Because of a lack of data, regional sample averages are applied to the follow- ing countries: Mozambique, Zimbabwe (SAPP); Ethiopia, Sudan, and Djibouti (EAPP/Nile Basin); Benin, Côte d’Ivoire, Liberia, Mali, Nigeria, Senegal, Sierra Leone, and Togo (WAPP). For CAPP, data are available for Cameroon and Republic of Congo only; for the other countries, regional average is applied. CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = South African Power Pool; WAPP = West African Power Pool. GWh = gigawatt-hour. Table A3.3 Target Access to Electricity, by Percentage of Population 218 % of population 2005 access Regional targets National targets Total Urban Rural Total Urban Rural Total Urban Rural SAPP Angola 14 26 4 24 42 9 46 84 15 Botswana 30 45 9 40 59 14 100 100 100 Congo, Dem. Rep. 8 16 2 20 37 8 39 76 12 Lesotho 6 23 1 17 68 4 35 121 13 Malawi 7 29 1 18 76 1 15 56 3 Mozambique 14 26 2 23 41 5 20 37 5 Namibia 37 75 12 45 86 19 53 95 25 South Africa 71 80 50 79 87 66 100 100 100 Zambia 20 45 3 29 57 11 29 50 15 Zimbabwe 41 87 8 49 99 14 67 100 44 Total SAPP 26 45 11 37 60 17 51 79 27 EAPP/Nile Basin Burundi 6 45 0 25 100 13 31 67 25 Djibouti 31 34 5 50 54 11 53 56 29 Egypt, Arab Rep. 93 100 87 100 100 100 100 100 100 Ethiopia 15 76 0 32 100 16 60 100 50 Kenya 27 48 4 42 72 10 67 100 32 Rwanda 16 39 1 29 66 4 18 39 4 Sudan 34 56 12 50 77 23 60 100 21 Tanzania 13 27 1 30 63 2 29 38 22 Uganda 8 44 2 27 100 15 25 100 13 Total EAPP/Nile Basin 35 64 19 50 84 31 60 88 45 WAPP Benin 25 50 6 35 68 9 50 100 11 Burkina Faso 9 40 0 20 84 1 23 100 6 Côte d’Ivoire 54 86 23 63 96 30 73 100 46 Gambia, The 59 82 21 66 88 31 79 100 37 Ghana 55 82 21 62 89 30 76 100 37 Guinea 21 54 2 31 77 3 40 100 3 Guinea-Bissau 14 41 2 25 74 4 33 100 6 Liberia 1 0 2 13 1 4 66 100 6 Mali 15 37 2 25 60 5 39 100 7 Mauritania 23 50 3 34 73 4 46 100 6 Niger 7 37 0 18 93 1 20 100 1 Nigeria 59 84 28 67 89 40 82 100 49 Senegal 34 69 6 44 88 9 51 100 10 Sierra Leone 41 82 2 46 91 4 51 100 6 Togo 21 41 2 30 58 5 50 100 8 Total WAPP 45 75 16 53 85 23 66 100 34 CAPP Cameroon 61 85 21 68 90 31 71 84 49 Central African Republic 3 8 0 15 36 1 34 84 1 Chad 3 9 0 15 46 1 26 84 0 Congo, Rep. 22 35 0 33 52 0 53 84 0 Equatorial Guinea 11 26 0 22 54 0 35 84 0 Gabon 82 85 54 92 93 83 91 84 82 Total CAPP 35 59 8 44 73 12 53 84 19 Island States Cape Verde 55 72 24 62 80 31 84 100 54 Madagascar 18 48 5 36 91 12 36 89 13 Mauritius 100 100 100 100 100 100 100 100 100 Total islands 23 52 9 40 92 16 40 90 17 219 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool. 220 Table A3.4 Target Access to Electricity, by Number of New Connections number of new connections 2005 access Regional targets National targets Total Urban Rural Total Urban Rural Total Urban Rural SAPP Angola 189,517 177,270 12,247 626,062 495,006 131,056 1,544,540 1,270,679 273,861 Botswana 4,082 4,082 0 36,618 31,052 5,566 239,160 110,534 128,626 Congo, Dem. Rep. 405,946 387,713 18,234 2,158,523 1,681,848 476,675 4,986,424 4,118,393 868,031 Lesotho 1,834 1,834 0 41,612 34,804 6,808 104,828 73,248 31,580 Malawi 80,533 76,926 3,608 417,587 412,275 5,312 319,224 270,837 48,387 Mozambique 200,355 200,355 0 621,455 546,922 74,533 514,437 445,893 68,544 Namibia 32,212 32,148 64 69,050 51,026 18,024 103,186 67,936 35,250 South Africa 411,428 411,428 0 1,219,077 854,276 364,801 3,189,412 1,612,810 1,576,602 Zambia 126,822 122,068 4,754 386,443 255,967 130,476 380,456 177,410 203,046 Zimbabwe 182,538 182,538 0 396,442 313,325 83,117 896,805 326,552 570,253 Total SAPP 1,635,267 1,596,360 38,907 5,972,869 4,676,501 1,296,368 12,278,472 8,474,292 3,804,180 EAPP/Nile Basin Burundi 68,320 66,212 2,108 473,983 231,661 242,322 610,986 132,306 478,680 Djibouti 10,887 10,887 0 46,190 45,142 1,049 52,787 48,058 4,729 Egypt, Arab Rep. 2,498,342 1,478,600 1,019,742 3,746,409 1,478,600 2,267,809 3,746,409 1,478,600 2,267,809 Ethiopia 1,033,168 1,022,756 10,411 4,316,696 1,937,724 2,378,972 9,699,988 1,937,724 7,762,265 Kenya 830,330 818,995 11,335 2,179,612 1,934,176 245,436 4,426,566 3,221,815 1,204,751 Rwanda 201,891 201,891 0 483,356 446,265 37,092 239,596 201,891 37,705 Sudan 798,611 777,563 21,048 2,198,508 1,677,706 520,802 3,110,220 2,681,012 429,208 Tanzania 382,227 381,490 737 1,944,457 1,895,796 48,661 1,839,775 823,674 1,016,101 Uganda 260,351 208,876 51,475 1,845,192 877,476 967,716 1,680,515 877,476 803,039 Total EAPP/ Nile Basin 6,084,126 4,967,270 1,116,856 17,234,404 10,524,545 6,709,859 25,406,842 11,402,556 14,004,287 WAPP Benin 139,684 130,235 9,449 338,376 290,292 48,084 635,693 571,764 63,929 Burkina Faso 133,569 132,376 1,193 508,094 496,918 11,176 636,793 631,201 5,592 Côte d’Ivoire 493,151 449,496 43,656 871,445 660,116 211,329 1,285,820 742,790 543,030 Gambia, The 72,255 69,774 2,481 102,539 84,114 18,424 155,214 116,041 39,173 Ghana 685,300 669,002 16,298 1,088,276 852,221 236,055 1,792,067 1,182,491 609,576 Guinea 169,952 166,219 3,733 400,901 379,423 21,478 621,287 597,188 24,099 Guinea-Bissau 10,156 9,575 581 49,891 45,852 4,039 77,215 73,428 3,786 Liberia 621 128 493 96,202 6,238 89,964 512,237 507,613 4,624 Mali 157,054 149,790 7,264 458,506 403,796 54,710 886,285 842,148 44,138 Mauritania 53,747 51,306 2,440 142,323 132,492 9,832 240,357 228,690 11,668 Niger 79,566 78,400 1,166 441,127 429,473 11,654 479,434 474,300 5,134 Nigeria 5,228,457 4,930,767 297,690 7,762,673 5,726,037 2,036,636 12,518,720 7,797,915 4,720,806 Senegal 274,605 256,809 17,796 583,312 519,770 63,542 785,043 679,618 105,426 Sierra Leone 205,924 204,913 1,011 277,461 269,994 7,466 345,993 332,753 13,240 Togo 99,647 97,346 2,301 230,519 212,066 18,453 510,621 490,928 19,693 Total WAPP 7,803,687 7,396,135 407,552 13,351,645 10,508,801 2,842,844 21,482,781 15,268,867 6,213,913 CAPP Cameroon 680,187 674,275 5,912 977,402 810,180 167,222 1,112,508 658,183 454,325 Central African Republic 6,055 5,881 174 122,722 115,646 7,076 308,692 306,516 2,176 Chad 28,363 28,013 350 327,974 317,986 9,988 616,852 614,860 1,991 Congo, Rep. 57,978 57,911 66 163,163 162,836 326 354,860 354,444 416 Equatorial Guinea 3,021 3,017 4 17,875 17,839 36 33,922 33,893 29 Gabon 55,792 55,791 1 90,583 80,555 10,028 86,592 52,504 34,089 Total CAPP 831,395 824,888 6,507 1,699,718 1,505,042 194,675 2,513,427 2,020,401 493,026 221 (continued next page) 222 Table A3.4 (continued) 2005 access Regional targets National targets Total Urban Rural Total Urban Rural Total Urban Rural Island States Cape Verde 6,290 6,280 10 12,899 10,596 2,303 31,655 22,142 9,513 Madagascar 249,261 218,924 30,337 1,107,461 855,885 251,576 1,099,554 821,762 277,792 Mauritius 19,567 12,813 6,754 19,567 12,813 6,754 19,567 12,813 6,754 Total islands 275,118 238,017 37,101 1,139,928 879,295 260,633 1,150,776 856,717 294,059 Total Sub-Saharan Africa 16,629,592 15,022,670 1,606,922 39,398,563 28,094,184 11,304,379 62,832,299 38,022,833 24,809,466 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool. Investment Requirements 223 Table A3.5 Total Electricity Demand TWh Social Total net Market demand Total net Increase in demand demand with national demand net demand in 2005 2015a targets 2015 2015 2005–15 (%) SAPP Angola 2.1 6.0 1.9 7.9 375 Botswana 2.4 4.0 0.2 4.2 174 Congo, Dem. Rep. 4.7 7.4 6.2 13.6 288 Lesotho 0.4 0.8 0.1 0.9 224 Malawi 1.3 1.9 0.4 2.3 176 Mozambique 11.2 15.7 0.7 16.4 145 Namibia 2.6 4.2 0.1 4.3 164 South Africa 215.0 316.0 3.2 319.2 147 Zambia 6.3 9.0 0.4 9.3 147 Zimbabwe 12.8 18.0 0.8 18.7 145 Total 258.8 383.0 14.0 396.9 152 EAPP/Nile Basin Burundi 0.2 0.3 0.5 0.7 349 Djibouti 0.2 0.3 0.1 0.4 199 Egypt, Arab Rep. 84.4 119.9 3.4 123.3 145 Ethiopia 2.1 3.4 7.4 10.7 509 Kenya 4.6 6.8 5.2 12.0 260 Rwanda 0.1 0.2 0.3 0.5 499 Sudan 3.2 5.2 3.9 9.2 287 Tanzania 4.2 6.2 1.7 7.9 187 Uganda 1.6 2.5 1.7 4.2 262 Total 100.6 144.8 24.2 169.0 167 WAPP Benin 0.6 0.9 0.8 1.7 282 Burkina Faso 0.5 0.6 0.9 1.5 299 Côte d’Ivoire 2.9 4.0 1.4 5.4 185 Gambia, The 0.1 0.2 0.2 0.4 399 Ghana 5.9 10.8 2.0 12.8 216 Guinea 0.7 1.3 0.8 2.2 313 Guinea-Bissau 0.1 0.1 0.1 0.2 199 Liberia 0.3 0.6 0.7 1.3 432 Mali 0.4 0.6 1.2 1.8 449 Mauritania 0.2 0.5 0.3 0.8 399 Niger 0.4 0.6 0.7 1.2 299 Nigeria 16.9 45.6 13.6 59.2 349 Senegal 1.5 2.5 1.0 3.5 232 Sierra Leone 0.2 0.5 0.5 1.0 499 Togo 0.6 0.8 0.7 1.5 249 Total 31.3 69.6 24.8 94.3 300 CAPP Cameroon 3.4 5.2 1.2 6.4 187 Central African Republic 0.1 0.1 0.4 0.6 599 Chad 0.1 0.1 0.8 1.0 999 Congo, Rep. 5.8 9.8 0.5 10.3 175 Equatorial Guinea 0.03 0.1 0.05 0.1 332 Gabon 1.2 1.7 0.1 1.8 149 Total 10.7 17.1 3.1 20.2 188 (continued next page) 224 Africa’s Power Infrastructure Table A3.5 (continued) Social Total net Market demand Total net Increase in demand demand with national demand net demand in 2005 2015a targets 2015 2015 2005–15 (%) Island States Cape Verde 0.04 0.1 0.04 0.1 249 Madagascar 0.8 1.1 1.4 2.6 324 Mauritius 0.2 0.4 0.02 0.4 199 Total 1.04 1.6 1.46 3.0 272 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool. a. Assuming all suppressed demand is met. Table A3.6 Generating Capacity in 2015 under Various Trade, Access, and Growth Scenarios Low-growth Trade scenario stagnation National Trade expansion scenario scenario targets for Regional National National access rates, Generation Constant target targets for targets for trade capacity (MW) access rate access rate access rates access rates expansion SAPP Installed capacitya 17,136 17,136 17,136 17,136 17,136 Refurbished capacity 28,029 28,035 28,046 28,148 28,046 New capacity 31,297 32,168 33,319 32,013 20,729 Hydropower share (%) 33 33 34 25 40 EAPP/Nile Basin Installed capacitya 22,132 22,132 22,132 22,132 22,132 Refurbished capacity 1,369 1,375 1,375 1,381 1,375 New capacity 23,045 24,639 25,637 17,972 23,540 Hydropower share (%) 49 47 48 28 48 WAPP Installed capacitya 4,096 4,096 4,096 4,096 4,096 Refurbished capacity 5,530 6,162 6,972 6,842 5,535 New capacity 15,979 16,634 18,003 16,239 17,186 Hydropower share (%) 82 79 77 73 80 (continued next page) Investment Requirements 225 Table A3.6 (continued) Low-growth Trade scenario stagnation National Trade expansion scenario scenario targets for Regional National National access rates, Generation Constant target targets for targets for trade capacity (MW) access rate access rate access rates access rates expansion CAPP Installed capacitya 260 260 260 260 260 Refurbished capacity 906 906 906 1,081 906 New capacity 3,856 4,143 4,395 3,833 3,915 Hydropower share (%) 97 97 97 83 97 Island States Installed capacitya 282 282 282 282 282 Refurbished capacity 83 83 83 83 83 New capacity 189 369 368 368 353 Hydropower share (%) 25 19 19 20 Total Sub-Saharan Africa Installed capacitya 43,906 43,906 43,906 43,906 43,906 Refurbished capacity 35,917 36,561 37,382 37,535 35,945 New capacity 74,366 77,953 81,722 70,425 65,723 Hydropower share (%) 48 47 47 36 52 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; WAPP = West African Power Pool. a. “Installed capacity” refers to installed capacity as of 2005 that will not undergo refurbishment before 2015. Existing capacity that will be refurbished before 2015 is not included in the installed capacity figure, but in the refurbishment figure. Table A3.7a Annualized Costs of Capacity Expansion, Constant Access Rates, Trade Expansion 226 $ million Generation T&D Total Cross- Distribu- Urban Rural Total costs Invest- Rehabil- border tion connec- connec- Rehab- Invest- Rehabili- of capacity ment itation Variable grid grid tion tion ilitation Variable ment tation Variable expansion Angola 0.1 10.5 0 78 139 11 2 38 78 231 49 78 357 Benin 0 4 57 0 18 8 2 15 36 28 19 93 140 Botswana 0 0.6 10.3 12 19 0 0 14 29 30 14 39 84 Burkina Faso 0 4 24 3 10 8 0 17 32 21 21 57 99 Burundi 0 1 0.4 0 3 4 0 1 4 7 2 4 14 Cameroon 410 32 54 22 22 42 1 21 43 497 52 97 646 Cape Verde 3 0 10 0 1 0 0 1 1 4 1 11 16 Central African Republic 5 1 1 0 1 0 0 1 2 6 2 3 12 Chad 0 0 0 0 0 2 0 0 1 2 0 1 4 Congo, Dem. Rep. 652 110 0 53 29 24 3 38 49 761 148 49 958 Congo, Rep. 301 7 24 20 9 4 0 0 13 332 7 37 376 Côte d’Ivoire 40 32 12 32 38 28 8 49 99 146 81 111 338 Equatorial Guinea 0 0 0 0 0 0 0 0 0 1 0 0 1 Ethiopia 1,136 18 133 71 69 64 2 84 116 1342 102 249 1,693 Gabon 19 9 5 2 3 3 0 5 8 27 13 13 54 Gambia, The 0 2 30 0 1 4 0 1 1 6 3 31 40 Ghana 262 9 32 5 79 42 3 34 94 391 42 126 559 Guinea 860 1 91 44 6 10 1 2 7 920 3 98 1,022 Guinea-Bissau 0 1 8 2 0 1 0 0 1 3 1 8 12 Kenya 231 20 144 15 65 51 1 48 130 362 68 274 705 Lesotho 0 0 0 0 6 0 0 2 7 6 2 7 15 Liberia 0 3 1 1 5 0 0 0 4 5 3 5 14 Madagascar 33 4 142 0 2 14 9 2 6 58 6 148 212 Malawi 0 3.8 0 1 7 5 1 5 14 13 9 14 35 Mali 0 2 4 35 24 9 1 18 43 70 20 47 137 Mauritania 0 2 29 0 11 3 0 5 11 15 7 39 61 Mauritius 0 0 8 0 13 1 2 9 21 16 9 29 54 Mozambique 606 9.5 17.4 17 17 12 0 20 43 653 30 60 742 Namibia 0 6.4 13.1 29 67 2 0 55 102 98 61 115 274 Niger 0 2 10 1 4 5 0 16 14 10 18 24 52 Nigeria 1,671 169 1,452 1 1,013 306 55 473 596 3,046 642 2,048 5,736 Senegal 41 4 131 1 261 16 3 118 370 322 122 501 946 Sierra Leone 0 0 6 3 5 13 0 1 5 21 1 10 33 South Africa 2,607 1,046 5,026 2 1,173 18 — 800 2,495 3,800 1,846 7,521 13,167 Sudan 1,166 — 88 50 59 48 4 43 97 1327 43 186 1,556 Tanzania 243 16 132 10 29 24 0 36 60 306 52 192 550 Togo 0 2 0 0 3 6 0 3 7 10 5 8 22 Uganda 289 10 27 16 23 13 6 28 39 347 38 65 451 Zambia 0 57 0 141 43 8 1 81 99 193 138 99 429 Zimbabwe 403 97 117 41 75 0 0 160 185 518 257 302 1,077 SSA: Total 10,978 1,696 7,839 708 3,352 809 105 2,244 4,962 15,951 3,937 12,799 32,693 CAPP: Total 1,901 61 172 172 236 114 7 109 246 2,430 168 419 3,020 EAPP/Nile Basin: Total 2,852 182 460 185 227 184 12 235 411 3,457 417 870 4,747 SAPP: Total 4,544 1,361 5,458 384 1,606 118 16 1,251 3,167 6,667 2,612 8,624 17,900 WAPP: Total 2,877 235 1,868 128 1,468 456 73 748 1,310 5,003 982 3,178 9,166 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; SSA = Sub-Saharan Africa; WAPP = West African Power Pool; T&D = transmission and distribution. — = Not available. 227 228 Table A3.7b Annualized Costs of Capacity Expansion, 35% Access Rates, Trade Expansion $ million Generation T&D Total Cross- Distribu- Urban Rural Total costs Invest- Rehabil- border tion connec- connec- Rehab- Invest- Rehabili- of capacity ment itation Variable grid grid tion tion ilitation Variable ment tation Variable expansion Angola 0.7 10.5 0 81 139 31 24 38 78 277 49 78 403 Benin 1 4 57 0 18 18 9 15 36 46 19 93 158 Botswana 0.1 0.6 10.3 10 19 2 1 14 29 31 14 39 85 Burkina Faso 0 4 39 1 10 31 2 17 32 44 21 71 136 Burundi 5.9 1 0.4 1 3 14 29 1 4 53 2 4 59 Cameroon 415 32 54 21 22 50 31 21 43 539 52 97 688 Cape Verde 3 0 11 0 1 1 1 1 1 5 1 12 18 Central African Republic 13 1 1 0 1 7 1 1 2 23 2 4 29 Chad 0 0 0 0 0 20 2 0 1 22 0 1 23 Congo, Dem. Rep. 697 110 0 53 29 104 89 38 49 972 148 49 1,169 Congo, Rep. 351 7 28 17 9 10 0 0 13 387 7 41 434 Côte d’Ivoire 102 32 15 28 38 41 39 49 99 249 81 114 445 Equatorial Guinea 0 0 0 0 0 1 0 0 0 2 0 0 2 Ethiopia 1,200 18 141 66 69 120 431 84 116 1,887 102 257 2,246 Gabon 20 9 5 2 3 5 2 5 8 32 13 13 59 Gambia, The 1 2 36 0 1 5 3 1 1 10 3 37 50 Ghana 272 9 32 4 79 53 44 34 94 452 42 126 620 Guinea 860 1 91 43 6 24 4 2 7 936 3 98 1,038 Guinea-Bissau 0 1 8 3 0 3 1 0 1 7 1 9 17 Kenya 236 21 144 0 65 120 29 48 130 450 69 274 792 Lesotho 0 0 0 0 6 2 1 2 7 10 2 7 18 Liberia 4 3 1 1 5 0 17 0 4 26 3 5 35 Madagascar 70 4 266 0 2 53 74 2 6 200 6 272 477 Malawi 0 3.8 0 1 7 26 1 5 14 34 9 14 57 Mali 2 2 4 32 24 25 10 18 43 94 20 47 161 Mauritania 0 2 29 1 11 8 2 5 11 22 7 39 68 Mauritius 0 0 8 0 13 1 2 9 21 16 9 29 54 Mozambique 606 9.5 17.4 17 17 34 14 20 43 688 30 60 778 Namibia 0.4 6.4 13.1 29 67 3 3 55 102 103 61 115 279 Niger 0 2 10 1 4 27 2 16 14 33 18 24 75 Nigeria 1,748 177 1,779 1 1,013 355 380 473 596 3,497 651 2,376 6,523 Senegal 42 4 131 2 261 32 12 118 370 349 122 501 972 Sierra Leone 0 1 23 3 5 17 1 1 5 27 3 28 57 South Africa 2,677 1,046 5,072 1 1,173 37 18 800 2,495 3,907 1,846 7,567 13,319 Sudan 1,179 0 90 39 59 104 94 43 97 1,476 43 187 1707 Tanzania 255 16 181 0 29 118 9 36 60 411 52 241 704 Togo 60 2 4 0 3 13 3 3 7 80 5 11 95 Uganda 317 10.1 26.6 10 23 54 116 28 39 520 38 65 624 Zambia 0.6 56.5 0 142 43 16 24 81 99 226 138 99 463 Zimbabwe 404 97 117 36 75 19 15 160 185 549 257 302 1,109 SSA: Total 11,543 1,705 8,445 646 3,352 1,604 1,540 2,244 4,962 18,692 3,949 13,406 36,046 CAPP: Total 1,985 61 178 161 236 242 183 109 246 2,811 168 425 3,404 EAPP/Nile Basin: Total 3,062 183 521 147 227 540 703 235 411 4,680 418 931 6,028 SAPP: Total 4,711 1,360 5,677 370 1,606 445 273 1,251 3,167 7,408 2,612 8,843 18,861 WAPP: Total 3,095 244 2,241 119 1,468 645 528 748 1,310 5,855 993 3,552 10,400 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; SSA = Sub-Saharan Africa; WAPP = West African Power 229 Pool; T&D = transmission and distribution. 230 Table A3.7c Annualized Costs of Capacity Expansion, National Targets for Access Rates, Trade Expansion $ million Generation T&D Total Cross- Distribu- Urban Rural Total costs Invest- Rehabil- border tion connec- connec- Rehab- Invest- Rehabili- of capacity ment itation Variable grid grid tion tion ilitation Variable ment tation Variable expansion Angola 3 11 0 87 139 79 51 38 78 359 49 78 486 Benin 1 4 57 0 18 35 12 15 36 67 19 93 179 Botswana 2 1 10 10 19 7 24 14 29 61 14 39 115 Burkina Faso 0 4 39 0 10 39 1 17 32 50 21 71 142 Burundi 11 1 1 1 3 8 57 1 4 80 2 4 87 Cameroon 426 32 54 21 22 41 85 21 43 595 52 97 744 Cape Verde 4 0 13 0 1 1 3 1 1 9 1 15 24 Central African Republic 28 1 3 0 1 19 0 1 2 48 2 5 56 Chad 0 0 0 0 0 38 0 0 1 39 0 1 40 Congo, Dem. Rep. 775 110 0 54 29 256 162 38 49 1,275 148 49 1,472 Congo, Rep. 385 7 31 15 9 22 0 0 13 431 7 43 482 Côte d’Ivoire 402 32 31 27 38 46 101 49 99 614 81 131 826 Equatorial Guinea 0 0 0 0 0 2 0 0 0 3 0 0 3 Ethiopia 1,345 18 160 61 69 120 1,408 84 116 3,003 102 276 3,381 Gabon 21 9 5 2 3 3 6 5 8 36 13 13 62 Gambia, The 2 2 37 0 1 7 7 1 1 17 3 38 58 Ghana 288 9 32 5 79 73 114 34 94 560 42 126 728 Guinea 860 1 91 40 6 37 4 2 7 947 3 98 1,049 Guinea-Bissau 0 1 8 5 0 5 1 0 1 11 1 9 20 Kenya 264 21 144 3 65 200 144 48 130 676 69 274 1,019 Lesotho 0.1 0 0 0 6 5 6 2 7 17 2 7 25 Liberia 0 3 1 2 5 32 1 0 4 39 3 5 48 Madagascar 70 4 261 0 2 51 82 2 6 205 6 267 478 Malawi 0.3 4 0 1 7 17 9 5 14 34 9 14 56 Mali 1 2 4 26 24 52 8 18 43 112 20 47 179 Mauritania 0 2 29 1 11 14 2 5 11 29 7 39 74 Mauritius 0 0 8 0 13 1 2 9 21 16 9 29 54 Mozambique 606 10 17 17 17 28 13 20 43 681 30 60 771 Namibia 1 6 13 30 67 4 7 55 102 108 61 115 284 Niger 0 2 10 0 4 29 1 16 14 34 18 24 76 Nigeria 1,867 189 2,232 2 1,013 484 880 473 596 4,246 662 2,828 7,736 Senegal 44 4 131 3 261 42 20 118 370 369 122 501 993 Sierra Leone 0 1 23 7 5 21 2 1 5 36 3 28 66 South Africa 2,745 1,046 5,101 1 1,173 70 80 800 2,495 4,069 1,846 7,596 13,510 Sudan 1,177 0 90 37 59 166 78 43 97 1,517 43 187 1,748 Tanzania 303 16 220 12 29 51 184 36 60 579 52 280 911 Togo 60 2 4 0 3 30 4 3 7 97 5 11 113 Uganda 312 10 27 12 23 54 96 28 39 498 38 65 601 Zambia 1 57 0 142 43 11 38 81 99 234 138 99 471 Zimbabwe 412 97 117 37 75 20 106 160 185 650 257 302 1,210 SSA: Total 12,416 1,719 9,004 661 3,352 2,220 3,799 2,244 4,962 22,451 3,960 13,964 40,377 CAPP: Total 2,051 61 184 163 236 378 277 109 246 3,108 168 428 3,708 EAPP/Nile Basin: Total 3,395 183 583 158 227 711 2,051 235 411 6,542 418 991 7,953 SAPP: Total 4,918 1,362 5,739 391 1,606 599 762 1,251 3,167 8,272 2,612 8,906 19,789 WAPP: Total 3,529 256 2,713 117 1,468 933 1,159 748 1,310 7,208 1,004 4,025 12,237 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; SSA = Sub-Saharan Africa; WAPP = West African Power Pool; T&D = transmission and distribution. 231 232 Table A3.7d Annualized Costs of Capacity Expansion, Low Growth Scenario, National Targets for Access Rates, Trade Expansion $ million Generation T&D Total Cross- Distribu- Urban Rural Total costs Invest- Rehabil- border tion connec- connec- Rehab- Invest- Rehabili- of capacity ment itation Variable grid grid tion tion ilitation Variable ment tation Variable expansion Angola 2.6 10.8 0 73 87 79 51 38 78 293 49 78 420 Benin 1 4 57 0 13 35 12 15 36 62 19 93 174 Botswana 2.1 0.6 10.3 17 8 7 24 14 29 57 14 39 111 Burkina Faso 0 4 39 0 9 39 1 17 32 50 21 71 142 Burundi 11.4 1 0.5 0 2 8 57 1 4 80 2 4 86 Cameroon 426 32 54 24 15 41 85 21 43 591 52 97 740 Cape Verde 3 0 11 0 1 1 3 1 1 8 1 12 21 Central African Republic 27 1 3 0 1 19 0 1 2 47 2 5 55 Chad 0 0 0 0 0 38 0 0 1 39 0 1 40 Congo, Dem. Rep. 735 110 0.1 53 23 256 162 38 49 1,228 148 49 1,426 Congo, Rep. 278 7 23 18 6 22 0 0 13 325 7 36 367 Côte d’Ivoire 166 32 18 24 30 46 101 49 99 368 81 117 566 Equatorial Guinea 0 0 0 0 0 2 0 0 0 2 0 0 3 Ethiopia 1,345 18 159.5 62 46 120 1,408 84 116 2,981 102 276 3,359 Gabon 19 9 5 2 2 3 6 5 8 33 13 13 59 Gambia, The 2 2 37 0 1 7 7 1 1 17 3 38 57 Ghana 288 9 32 4 52 73 114 34 94 531 42 126 699 Guinea 860 1 91 41 5 37 4 2 7 947 3 98 1,049 Guinea-Bissau 0 1 8 4 0 5 1 0 1 9 1 9 19 Kenya 264 21 144 2 50 200 144 48 130 661 69 274 1,004 Lesotho 0.1 0 0 0 3 5 6 2 7 14 2 7 22 Liberia 0 3 1 2 2 32 1 0 4 36 3 5 45 Madagascar 68 4 253 0 2 51 82 2 6 202 6 258 466 Malawi 0.3 3.8 0 1 5 17 9 5 14 32 9 14 54 Mali 1 2 4 28 18 52 8 18 43 107 20 47 175 Mauritania 0 2 29 1 7 14 2 5 11 24 7 39 70 Mauritius 0 0 6 0 8 1 2 9 21 11 9 28 47 Mozambique 606 9.5 17.4 16 11 28 13 20 43 673 30 60 763 Namibia 0.7 6.4 13.1 26 34 4 7 55 102 72 61 115 248 Niger 0 2 10 0 4 29 1 16 14 34 18 24 76 Nigeria 1,867 168 1,429 1 343 484 880 473 596 3,576 641 2,026 6,243 Senegal 44 4 131 2 174 42 20 118 370 281 122 501 904 Sierra Leone 0 1 23 6 1 21 2 1 5 31 3 28 61 South Africa 777 1,046 3,820 4 455 70 80 800 2,495 1,385 1,846 6,315 9,546 Sudan 1,177 0 90 37 37 166 78 43 97 1,495 43 187 1,725 Tanzania 285 16 134 9 18 51 184 36 60 548 52 195 794 Togo 60 2 4 0 3 30 4 3 7 97 5 11 113 Uganda 312 10 27 9 19 54 96 28 39 491 38 65 594 Zambia 1 57 0 141 27 11 38 81 99 218 138 99 455 Zimbabwe 412 97 117 52 36 20 106 160 185 626 257 302 1,186 SSA: Total 10,041 1,697 6,801 659 1,558 2,220 3,799 2,244 4,962 18,282 3,939 11,762 33,984 CAPP: Total 1,941 61 176 154 150 378 277 109 246 2,905 168 421 3,495 EAPP/Nile Basin: Total 3,230 183 488 153 164 711 2,051 235 411 6,314 418 899 7,630 SAPP: Total 2,890 1,361 4,365 392 709 599 762 1,251 3,167 5,348 2,612 7,531 15,491 WAPP: Total 3,292 235 1,895 112 656 933 1,159 748 1,310 6,154 983 3,206 10,344 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; SSA = Sub-Saharan Africa; WAPP = West African Power 233 Pool; T&D = transmission and distribution. 234 Table A3.7e Annualized Costs of Capacity Expansion, Trade Stagnation $ million Generation T&D Total Cross- Distribu- Urban Rural Total costs Invest- Rehabil- border tion connec- connec- Rehab- Invest- Rehabili- of capacity ment itation Variable grid grid tion tion ilitation Variable ment tation Variable expansion Angola 289 12 99 0 139 79 51 38 78 558 50 177 785 Benin 8 4 94 0 18 35 12 15 36 74 19 130 223 Botswana 196 1 172 0 19 7 24 14 29 246 14 201 461 Burkina Faso 0 4 39 0 10 39 1 17 32 50 21 71 142 Burundi 72 1 2 0 3 8 57 1 4 140 2 6 148 Cameroon 180 32 29 0 22 41 85 21 43 328 52 72 452 Cape Verde — — — — — — — — — — — — — Central African Republic 28 1 3 0 1 19 0 1 2 48 2 5 56 Chad 33 1 84 0 0 38 0 0 1 72 1 85 157 Congo, Rep. 528 7 175 0 9 22 0 0 13 559 7 188 754 Côte d’Ivoire 458 32 140 0 38 46 101 49 99 644 81 239 964 Congo, Dem. Rep. 80 110 0.1 0 29 256 162 38 49 526 148 49 723 Equatorial Guinea 8 0 0 0 0 2 0 0 0 11 0 1 12 Ethiopia 403 18 62 0 69 120 1,408 84 116 2,001 102 178 2,281 Gabon 21 12 56 0 3 3 6 5 8 34 17 64 115 Gambia, The 2 2 30 0 1 7 7 1 1 17 3 31 51 Ghana 322 9 530 0 79 73 114 34 94 588 42 624 1,255 Guinea 114 1 11 0 6 37 4 2 7 161 3 18 183 Guinea-Bissau 11 1 11 0 0 5 1 0 1 17 1 11 29 Kenya 288 21 298 0 65 200 144 48 130 697 69 428 1,194 Lesotho 0.1 0 0 0 6 5 6 2 7 17 2 7 25 Liberia 191 4 14 0 5 32 1 0 4 228 4 18 250 Madagascar — — — — — — — — — — — — — Malawi 135 4 0 0 7 17 9 5 14 167 9 14 190 Mali 115 3 40 0 24 52 8 18 43 199 21 82 303 Mauritania 13 2 87 0 11 14 2 5 11 41 7 97 145 Mauritius — — — — — — — — — — — — — Mozambique 407 10 147 0 17 28 13 20 43 465 30 190 685 Namibia 130 6 213 0 67 4 7 55 102 207 61 315 583 Niger 72 4 44 0 4 29 1 16 14 106 20 59 185 Nigeria 1,867 186 2,095 0 1,013 484 880 473 596 4,244 659 2,691 7,594 Senegal 62 4 185 0 261 42 20 118 370 385 122 555 1,062 Sierra Leone 56 1 26 0 5 21 2 1 5 85 3 31 118 South Africa 2,984 1,046 5,487 0 1,173 70 80 800 2,495 4,306 1,846 7,982 14,134 Sudan 182 0 38 0 59 166 78 43 97 485 43 135 663 Tanzania 270 16 115 0 29 51 184 36 60 534 52 176 762 Togo 72 3 97 0 3 30 4 3 7 109 5 105 219 Uganda 179 10 18 0 23 54 96 28 39 353 38 56 448 Zambia 302 57 0 0 43 11 38 81 99 394 138 99 631 Zimbabwe 376 97 223 0 75 20 106 160 185 577 257 408 1,243 SSA: Total 10,454 1,722 10,664 0 3,336 2,167 3,712 2,232 4,934 19,673 3,951 15,598 39,225 CAPP: Total 1,271 91 451 0 265 402 378 158 332 2,320 248 784 3,352 EAPP/Nile Basin: Total 2,198 105 810 0 236 501 1,990 246 461 4,928 351 1,271 6,551 SAPP: Total 5,617 1,256 6,631 0 1,584 314 518 1,211 3,125 8,030 2,466 9,757 20,253 WAPP: Total 2,972 336 3,216 0 1,458 1,142 1,217 736 1,259 6,789 1,071 4,475 12,337 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; SSA = Sub-Saharan Africa; WAPP = West African Power 235 Pool; T&D = transmission and distribution. — = data not available. 236 Africa’s Power Infrastructure Table A3.8 Annualized Costs of Capacity Expansion under Different Access Rate Scenarios, Trade Expansion percent of 2005 GDP Trade expansion Trade stagnation Access rate scenarios National targets Sustain Low growth, current Uniform 35% National national levels target targets targets Angola 1.2 1.3 1.6 1.4 2.6 Benin 3.3 3.7 4.2 4.1 5.2 Botswana 0.8 0.8 1.1 1.1 4.4 Burkina Faso 1.8 2.5 2.6 2.6 2.6 Burundi 1.8 7.4 10.9 10.8 18.6 Cameroon 3.9 4.1 4.5 4.5 2.7 Cape Verde 1.6 1.8 2.4 2.1 — Central African Republic 0.9 2.1 4.1 4.1 4.1 Chad 0.1 0.4 0.7 0.7 2.7 Congo, Rep. 6.2 7.1 7.9 6.0 12.4 Côte d’Ivoire 2.1 2.7 5.1 3.5 5.9 Congo, Dem. Rep. 13.5 16.5 20.7 20.1 10.2 Equatorial Guinea 0.01 0.03 0.04 0.04 0.2 Ethiopia 13.8 18.3 27.5 27.3 18.5 Gabon 0.6 0.7 0.7 0.7 1.3 Gambia, The 8.7 10.8 12.6 12.4 11.1 Ghana 5.2 5.8 6.8 6.5 11.7 Guinea 31.3 31.8 32.2 32.2 5.6 Guinea-Bissau 4.0 5.6 6.6 6.3 9.6 Kenya 3.8 4.2 5.4 5.4 6.4 Lesotho 1.1 1.3 1.8 1.5 1.8 Liberia 2.6 6.6 9.1 8.5 47.2 Madagascar 4.2 9.5 9.5 9.2 — Malawi 1.2 2.0 2.0 1.9 6.7 Mali 2.6 3.0 3.4 3.3 5.7 Mauritania 3.3 3.7 4.0 3.8 7.9 Mauritius 0.9 0.9 0.9 0.7 — Mozambique 11.3 11.8 11.7 11.6 10.4 Namibia 4.4 4.5 4.6 4.0 9.4 Niger 1.6 2.3 2.3 2.3 5.6 Nigeria 5.1 5.8 6.9 5.6 6.8 Senegal 10.9 11.2 11.4 10.4 12.2 Sierra Leone 2.7 4.7 5.4 5.0 9.7 South Africa 5.4 5.5 5.6 3.9 5.8 (continued next page) Investment Requirements 237 Table A3.8 (continued) Trade expansion Trade stagnation Access rate scenarios National targets Sustain Low growth, current Uniform 35% National national levels target targets targets Sudan 5.7 6.2 6.4 6.3 2.4 Tanzania 3.9 5.0 6.4 5.6 5.4 Togo 1.0 4.4 5.2 5.2 10.2 Uganda 5.2 7.1 6.9 6.8 5.1 Zambia 5.8 6.3 6.4 6.2 8.6 Zimbabwe 31.5 32.4 35.4 34.7 36.4 SSA: Total 215 262 303 288 333 CAPP: Total 16 25 34 32 41 EAPP/Nile Basin: Total 37 52 70 65 72 SAPP: Total 77 88 94 87 104 WAPP: Total 96 117 132 127 153 Source: Rosnes and Vennemo 2008. Note: CAPP = Central African Power Pool; EAPP/Nile Basin = East African/Nile Basin Power Pool; SAPP = Southern African Power Pool; SSA = Sub-Saharan Africa; WAPP = West African Power Pool. — = data not available. APPENDIX 4 Strengthening Sector Reform and Planning Table A4.1 Institutional Indicators: Summary Scores by Group of Indicators Out of 100, 2007 Reform Regulation sector sector SOE Aggregate Reform specific Regulation specific governance score Benin 13 20 0 28 47 22 Burkina Faso 50 83 50 19 75 55 Cameroon 80 67 48 75 80 70 Cape Verde 69 42 82 31 61 57 Chad 38 42 0 28 60 34 Congo, Dem. Rep. 33 42 0 83 49 41 Cote d’Ivoire 88 83 36 78 70 71 Ethiopia 64 42 56 31 100 59 Ghana 88 58 83 50 70 70 Kenya 86 75 53 78 64 71 Lesotho 79 0 64 0 50 39 Madagascar 67 42 59 67 86 64 Malawi 64 42 61 67 79 63 Mozambique 46 42 0 44 100 46 Namibia 79 42 76 67 73.5 68 Niger 49 50 48 61 74 56 Nigeria 78 58 53 44 56 58 (continued next page) 239 240 Africa’s Power Infrastructure Table A4.1 (continued) Reform Regulation sector sector SOE Aggregate Reform specific Regulation specific governance score Rwanda 62 17 53 56 45 47 Senegal 71 58 58 78 61 65 South Africa 88 42 82 44 65.5 64 Sudan 33 0 — — 50 28 Tanzania 69 58 67 33 64 58 Uganda 84 75 64 33 63 64 Zambia 71 58 64 67 54 63 Source: Vagliasindi and Nellis 2010. Note: SOE = state-owned enterprise; — = data not available. Table A4.2a Institutional Indicators: Description of Reform Indicators Subindex Indicator Indicator values Existence of reform 0 = No reform of the sector Legislation 1 = At least one key reform of the sector Legal reform 0 = No new sector legislation passed within the past 10 years 1 = New sector legislation passed in the past 10 years Unbundling 0 = Vertical integration 1 = Restructuring through vertical separation Restructuring Separation of 0 = No separation of different business services business lines 1 = Separation of different business services SOE corporatization 0 = No state-owned utility corporatized 1 = At least one utility corporatized Existence of 0 = No autonomous regulatory body regulatory body 1 = Autonomous regulatory body Tariff approval 0 = Oversight on tariff approval by line ministry oversight 1 = Oversight on tariff approval by a special entity within the ministry, an interministerial committee, or the regulator Investment plan 0 = Oversight on investment plans by line ministry oversight 1 = Oversight on investment plans by a special entity within the ministry, an interministerial committee, or the regulator Policy oversight Technical standard 0 = Oversight on technical standards by line ministry oversight 1 = Oversight on technical standards by a special entity within the ministry, an interministerial committee, or the regulator Regulation 0 = Oversight on regulation monitoring by line ministry monitoring 1 = Oversight on regulatory monitoring by a special entity oversight within the ministry, an interministerial committee, or the regulator Dispute arbitration 0 = Oversight on dispute resolution by line ministry oversight 1 = Oversight on dispute resolution by a special entity within the ministry, an interministerial committee, or the regulator (continued next page) Strengthening Sector Reform and Planning 241 Table A4.2a (continued) Subindex Indicator Indicator values Private de jure 0 = Private participation forbidden by law 1 = Private participation allowed by law Private de facto 0 = No private participation 1 = At least a form of private participation Private sector 0 = No private sector involvement or service and management works contracts only 1 = Management contract, affermage, lease, or concession Private sector 0 = No private sector involvement, service and works Private sector involvement investment contracts, management contract, affermage, or lease 1 = Concession Absence of 0 = Canceled, distressed private sector participation distressed private 1 = Operational, concluded, and not renewed private sector participation sector participation Absence of 0 = Renegotiation renegotiation in 1 = No renegotiation private sector participation Private ownership 0 = No private ownership 1 = At least a form of greenfield operation/divestiture Full privatization of 0 = No privatization or partial privatization incumbent operator 1 = Full privatization (sales of 51% or more shares) Absence of 0 = Renationalization renationalization 1 = No renationalization Source: Vagliasindi and Nellis 2010. Note: SOE = state-owned enterprise. 242 Chad Rep. Benin Kenya Ghana Malawi Lesotho Ethiopia Country Cameroon Cape Verde Madagascar Burkina Faso Côte d’Ivoire Congo, Dem. Mozambique Table A4.2b 1 1 1 1 1 1 1 0 1 1 1 1 0 — Existence of reform 1 1 1 1 1 1 1 1 0 1 1 1 1 0 Legal reform Legislation 0 0 0 0 1 1 0 0 0 0 0 0 0 0 Unbundling 1 1 0 1 1 1 1 1 1 1 0 1 1 1 Separation of business lines 1 1 1 1 1 1 1 1 1 1 1 1 1 1 SOE corporatization Restructuring 0 1 0 1 1 1 0 1 0 0 1 0 0 ... Existence of regulatory body Regulation monitoring 0 1 1 1 1 0 1 0 1 1 0 0 — — Institutional Indicators: Reform, 2007 oversight 0 1 1 0 1 1 1 1 1 1 0 0 — Dispute arbitration oversight 0 1 1 1 1 1 1 1 1 0 1 1 0 0 Tariff approval oversight 0 0 0 1 1 1 1 1 0 1 1 0 0 — Policy oversight Investment plan oversight 0 1 1 1 1 1 1 1 0 0 0 — — — Technical standard oversight 1 0 1 1 1 1 0 1 0 0 1 1 1 0 Private de jure 1 0 1 0 1 1 0 1 0 0 1 1 1 0 Private de facto 0 0 1 1 1 0 0 1 0 0 1 1 0 0 Private sector management 0 0 0 0 0 0 0 1 0 0 1 1 0 0 Private sector investment Absence of distressed 1 1 1 1 0 1 — — — — — — — — private sector participation Absence of renegotiation in 0 0 0 0 0 — — — — — — — — private sector participation Private sector involvement 0 0 0 0 1 1 0 1 0 0 0 0 1 0 Private ownership 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Full privatization of incumbent operator 1 0 1 — — — — — — — — — — — Absence of renationalization Namibia 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 — — 0 0 — Niger 1 1 0 1 1 1 0 1 0 0 0 0 0 0 0 — — 0 0 — Nigeria 1 1 1 1 1 1 1 0 1 0 1 1 1 0 0 — — 1 0 — Rwanda 1 1 0 0 1 1 1 1 1 0 0 1 1 1 0 0 0 0 0 — Senegal 1 1 0 1 1 1 1 1 1 0 0 1 1 0 0 — — 1 0 — South Africa 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 — — 0 0 — Sudan — — — 1 1 0 — — — — — — — 0 0 — — 0 0 — Tanzania 1 1 0 1 1 1 1 0 1 0 0 1 1 1 0 1 0 1 0 — Uganda 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 0 0 1 Zambia 1 1 0 1 1 1 1 1 1 0 0 1 1 0 0 — — 0 0 — Source: Vagliasindi and Nellis 2010. Note: SOE = state-owned enterprise; — = data not available. 243 244 Africa’s Power Infrastructure Table A4.3a Institutional Indicators: Description of Reform Sector–Specific Indicators Subindex Indicator Indicator values De jure unbundling of 0 = Joint ownership allowed by law generation and transmission 1 = No joint ownership allowed by law De jure unbundling of 0 = Joint ownership allowed by law distribution and transmission 1 = No joint ownership allowed by law Restructuring De jure unbundling of 0 = Joint ownership allowed by law generation and distribution 1 = No joint ownership allowed by law De facto unbundling of 0 = No unbundling generation and transmission 1 = Unbundling De facto unbundling of 0 = No unbundling distribution and transmission 1 = Unbundling De facto unbundling of 0 = No unbundling generation and distribution 1 = Unbundling Responsibility for urban 0 = No decentralization of responsibility of serv- electricity service provision ice provision at the national or state level Decentralization 1 = Decentralization of responsibility of service provision beyond national or state level Responsibility for rural 0 = Accountability of service provision only at the electricity service provision central government level 1 = Accountability of service provision at the regional, state, or local government Single-buyer model 0 = Vertically integrated structure 1 = Single-buyer model Separation of water and 0 = No separation of water and electricity service electricity service provision provision 1 = Separation of water and electricity service Market structure provision De jure IPP 0 = IPPs not allowed by law 1 = IPPs allowed by law De facto IPP 0 = No IPPs 1 = At least one IPP Community-based providers 0 = No presence of community-based service of rural electricity providers 1 = Presence of community-based service providers Source: Vagliasindi and Nellis 2010. Note: IPP = independent power project. Strengthening Sector Reform and Planning 245 Table A4.3b Institutional Indicators: Reform Sector Specific, 2007 Market Restructuring structure De facto unbundling De facto unbundling De facto unbundling De jure unbundling De jure unbundling De jure unbundling Single buyer model of distribution and of distribution and of generation and of generation and of generation and of generation and transmission transmission transmission transmission De facto IPP distribution distribution De jure IPP Country Benin 0 0 0 1 1 — 0 0 0 Burkina Faso 1 1 1 1 1 1 0 1 1 Cameroon 1 1 1 1 1 1 0 1 0 Cape Verde 0 0 0 1 1 1 0 1 0 Chad 0 0 0 1 1 1 0 1 0 Congo, Dem. Rep. 0 0 0 1 1 1 0 1 0 Côte d’Ivoire 1 1 1 1 1 1 0 1 1 Ethiopia 0 0 0 1 1 1 0 1 0 Ghana 0 0 0 1 1 1 0 1 1 Kenya 1 0 1 0 1 0 1 1 1 Lesotho — — — — — — — — — Madagascar 0 0 0 1 1 1 0 1 0 Malawi 0 0 0 1 1 1 0 1 0 Mozambique 0 0 0 1 1 1 0 1 0 Namibia 0 0 0 1 0 0 1 1 0 Niger 1 1 1 1 1 1 0 0 0 Nigeria 0 0 0 1 1 1 0 1 1 Rwanda 0 0 0 0 0 0 0 1 0 Senegal 0 0 0 1 1 1 0 1 1 South Africa 0 0 0 1 1 1 0 1 0 Sudan — — — — — — — — — Tanzania 0 0 0 1 1 1 0 1 1 Uganda 1 1 1 0 0 0 1 1 1 Zambia 0 0 0 1 1 1 0 1 1 Source: Vagliasindi and Nellis 2010. Note: IPP = independent power project; — = data not available. 246 Africa’s Power Infrastructure Table A4.4a Institutional Indicators: Description of Regulation Indicators Subindex Indicator Indicator values Formal autonomy: 0 = Appointment by government/line ministry hire 1 = Otherwise Formal autonomy: 0 = Firing by government/line ministry fire 1 = Otherwise Partial financial 0 = Budget fully funded by government autonomy 1 = At least a proportion of budget funded through fees and/or donors Full financial 0 = At least a proportion of budget funded through Autonomy autonomy government and/or donors 1 = Budget fully funded through fees Partial managerial 0 = Veto decision by government/line ministry autonomy 1 = Veto decision by others Full managerial 0 = Veto decision by government/line ministry/others autonomy 1 = No veto decision Multisectoral 0 = Sector-specific regulator 1 = Multisectoral regulator Commissioner 0 = Individual 1 = Board of Commissioners Publicity of decisions 0 = Regulatory decisions not publicly available reports only 1 = Regulatory decisions publicly available only through reports Publicity of decisions 0 = Regulatory decisions not publicly available or Transparency Internet only available only through reports 1 = Regulatory decisions publicly available through Internet Publicity of decisions 0 = Regulatory decisions not publicly available or public hearing only available through only through reports/Internet 1 = Regulatory decisions publicly available through public hearings Appeal 0 = No right to appeal regulatory decisions 1 = Right to appeal regulatory decision Accountability Partial independence 0 = Appeal to government/line ministries of appeal 1 = Appeal to bodies other than government/line ministries Full independence 0 = No recourse to independent arbitration of appeal 1 = Possibility to appeal to independent arbitration (continued next page) Strengthening Sector Reform and Planning 247 Table A4.4a (continued) Subindex Indicator Indicator values Tariff methodology 0 = No tariff methodology 1 = Some tariff methodology (price cap or ROR) Tariff indexation 0 = No tariff indexation 1 = Some tariff indexation Tools Regulatory review 0 = No tariff review 1 = Periodic tariff review Length of regulatory 0 = No tariff review, annual review or review (period less review than three years) 1 = Multiyear tariff review (at least three years) Existence of a specific 0 = No sectoral fund established sectoral fund 1 = Sectoral fund established USO Finance of sectoral 0 = No funding based on levies fund 1 = At least a percentage of funding coming through sectoral levies Source: Vagliasindi and Nellis 2010. Note: ROR = rate of return; USO = universal service obligation. 248 Africa’s Power Infrastructure Table A4.4b Institutional Indicators: Regulation, 2007 Autonomy Formal Formal Partial Full Partial Full man- auton- auton- financial financial managerial agerial omy hire omy fire autonomy autonomy autonomy autonomy Multisectoral Commissioner Benin — — — — — — — — Burkina Faso — — — — — — — — Cameroon 0 0 1 0 0 0 0 1 Cape Verde 0 1 1 1 0 0 1 1 Chad — — — — — — — — Congo, Dem. Rep. — — — — — — — — Côte d’Ivoire 0 0 1 1 — 1 0 0 Ethiopia 0 0 1 0 0 0 0 1 Ghana 0 0 — — — — 1 1 Kenya 0 0 1 1 0 0 0 1 Lesotho 0 0 1 — 0 0 0 1 Madagascar 0 0 1 1 0 0 0 1 Malawi 0 0 1 0 1 0 0 1 Mozambique — — — — — — — — Namibia 0 0 1 1 0 0 0 1 Niger 0 0 1 0 0 0 1 0 Nigeria 0 0 1 0 1 0 0 1 Rwanda 1 0 1 1 0 0 1 1 Senegal 0 0 — — 1 0 0 1 South Africa 0 0 1 1 1 0 1 1 Sudan — — — — — — — — Tanzania 0 0 1 1 0 0 1 1 Uganda 0 0 1 0 1 0 0 1 Zambia 0 0 1 0 0 0 1 1 Source: Vagliasindi and Nellis 2010. Note: — = data not available. 248 Strengthening Sector Reform and Planning 249 Transparency Accountability Tools Publicity Publicity Partial of deci- of deci- Publicity of inde- Full inde- Length of sions sions decisions pen- pen- Tariff Tariff regula- reports Internet public hear- dence of dence of method- indexa- Regulatory tory only only ing only Appeal appeal appeal ology tion review review — — — — — — 0 0 0 — — — — 0 — — 1 — — — 0 0 0 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 — — — — — — 0 — — — — — — — — — 0 0 0 — 0 0 — 1 1 0 0 0 1 — 1 1 0 1 1 0 1 0 1 — 1 1 1 — — — 1 — — — 1 1 0 1 0 0 1 0 1 1 — — — — — — 1 — — — 1 1 0 1 0 0 1 1 1 1 1 0 1 1 1 0 1 0 1 1 — — — — — — 0 — — — 1 1 1 1 1 0 1 1 — — 1 1 1 1 1 0 0 0 — — 1 1 1 0 — — 1 0 1 1 1 1 1 0 — — 1 0 — — 1 0 0 1 1 0 1 1 1 1 1 1 1 1 1 0 1 1 1 1 — — — — — — — — — — 1 1 1 1 1 0 1 0 1 0 1 1 1 1 1 0 1 1 0 0 1 1 1 1 1 0 1 0 1 0 249 Table A4.5a Institutional Indicators: Description of Regulation Sector-Specific Indicators 250 Subindex Indicator Indicator values Regulation of large customers 0 = Regulation of large customers 1 = No regulation of large customers Transmission tariff regulation methodology 0 = No transmission tariff regulation methodology 1 = Tariff regulation methodology (price cap or rate of return) Third-party access to T&D networks 0 = TPA not allowed by law Tools 1 = TPA allowed by law Minimum quality standards 0 = No well-defined minimum quality standards 1 = Well-defined minimum quality standards Penalties for noncompliance 0 = No penalties for noncompliance to minimum quality standards 1 = Penalties for noncompliance to minimum quality standards Partial cost recovery requirement for rural electricity 0 = Full capital subsidy 1 = Partial capital subsidy Cost recovery Full cost recovery requirement for rural electricity 0 = Partial or full capital subsidy 1 = No subsidy Community contribution to the rural fund 0 = No community contribution to the rural fund 1 = Community contribution to the rural fund Criteria are used to prioritize rural electrification 0 = Criteria other than least cost projects 1 = Least-cost criteria Universal service Opex cost recovery for rural water 0 = No opex recovery 1 = Opex recovery Capex cost recovery for water 0 = Only opex recovery or no recovery 1 = Some capex recovery Incentives for renewable energy 0 = No incentive for renewable energy Environmental 1 = Incentives for renewable energy Source: Vagliasindi and Nellis 2010. Note: capex = capital expenses; opex = operational expenses; T&D = transmission and distribution; TPA = third-party access. Strengthening Sector Reform and Planning 251 Table A4.5b Institutional Indicators: Regulation Sector Specific, 2007 Environ- Tools Access/interconnection Cost recovery mental Incentives for renewable energy Third-party access to transmis- sion and distribution networks Full cost recovery requirement Regulation of large customers Criteria used to prioritize rural Transmission tariff regulation Penalties for noncompliance Partial cost recovery require- Minimum quality standards ment for rural electricity electrification projects for rural electricity Cutoff possibility methodology Country Benin 0 — 1 0 1 — 0 — 0 — Burkina Faso 0 0 1 0 0 1 0 — 0 — Cameroon 1 1 1 0 1 1 0 — — — Cape Verde 1 0 1 0 0 1 0 — 0 — Chad 0 0 1 0 1 — — — 0 — Congo, Dem. Rep. 1 1 1 0 1 — 1 — — — Côte d’Ivoire 1 1 1 0 1 — 0 — 1 — Ethiopia 1 0 1 0 0 1 0 — 0 — Ghana 1 — 1 0 0 1 1 — 0 — Kenya 1 0 1 1 0 1 — — 1 — Lesotho — — — — — — — — 0 — Madagascar 1 0 1 0 0 1 — — 1 — Malawi 1 1 1 0 0 1 — — — — Mozambique — — 1 0 1 0 — — 0 — Namibia 1 1 1 0 0 1 — — — — Niger 0 0 1 0 1 — — — 1 — Nigeria 1 1 1 0 0 1 — — 0 — Rwanda 0 0 1 0 0 1 — — 1 — Senegal 1 1 1 0 0 1 — — 1 — South Africa 1 1 1 0 0 1 — — 0 — Sudan — — — — — — — — — — Tanzania 0 0 1 0 0 1 — — — — Uganda 1 1 0 0 0 1 — — 0 — Zambia 1 1 1 — 0 1 — 1 0 — Source: Vagliasindi and Nellis 2010. Note: — = data not available. 252 Africa’s Power Infrastructure Table A4.6a Institutional Indicators: Description of SOE Governance Indicators Subindex Indicator Indicator values Concentration of 0 = Ownership diversified Ownership and shareholder ownership 1 = 100% owned by one state body Corporatization 0 = Noncorporatized 1 = Corporatized quality Limited liability 0 = Nonlimited liability 1 = Limited liability company Rate of return 0 = No requirement to earn a rate of return policy 1 = Requirement to earn a rate of return Dividend policy 0 = No requirement to pay dividends 1 = Requirement to pay dividends Hiring 0 = Manager does not have the most decisive influence on hiring decisions 1 = Manager has the most decisive influence on hiring decisions Laying off 0 = Manager does not have the most decisive influence on firing decisions 1 = Manager has the most decisive influence on firing decisions Wages 0 = Manager does not have the most decisive influence on setting wages/bonuses Managerial and board autonomy 1 = Manager has the most decisive influence on setting wages/bonuses Production 0 = Manager does not have the most decisive influence on how much to produce 1 = Manager has the most decisive influence on how much to produce Sales 0 = Manager does not have the most decisive influence on to whom to sell 1 = Manager has the most decisive influence on to whom to sell Size of the board 0 = Number of members of board smaller than a given threshold 1 = Number of members of board greater than a given threshold Selection of board 0 = Board members appointed only by government members 1 = Board members appointed by shareholders Presence of 0 = No independent directors in the board independent 1 = At least one independent director in the board directors (continued next page) Strengthening Sector Reform and Planning 253 Table A4.6a (continued) Subindex Indicator Indicator values Publication of 0 = Annual reports not publicly available annual reports 1 = Annual reports publicly available IFRS 0 = IFRS not applied 1 = Compliance to IFRS Accounting and disclosure and performance monitoring External audits 0 = No operational or financial audit 1 = At least some form of external audit Independent 0 = No independent audit of accounts audit of accounts 1 = Independent audit of accounts Audit publication 0 = Audit not publicly available 1 = Audit publicly available Remuneration of 0 = No remuneration of noncommercial activities noncommercial 1 = Remuneration of noncommercial activities activity Performance 0 = No performance contracts contracts 1 = Existence of performance contract Performance 0 = Performance-based incentive systems contracts with 1 = Existence of performance-based incentive systems incentives Penalties for poor 0 = No penalties for poor performance performance 1 = Penalties for poor performance Monitoring 0 = No periodic monitoring of performance 1 = Periodic monitoring of performance Third-party 0 = No monitoring of performance by third party monitoring 1 = Monitoring of performance by third party Billing and collection 0 = Ownership diversified 1 = 100% owned by one state body Outsourcing Meter reading 0 = Noncorporatized 1 = Corporatized Human resources 0 = Nonlimited liability 1 = Limited liability company Information 0 = No requirement to earn a rate of return technology 1 = Requirement to earn a rate of return (continued next page) 254 Africa’s Power Infrastructure Table A4.6a (continued) Subindex Indicator Indicator values Restriction to 0 = Restrictions to dismiss employees according to public dismiss employees service guidelines 1 = Restrictions to dismiss employees only according to Labor market corporate law discipline Wages compared 0 = Wages compared with public sector with private sector 1 = Wages compared with private sector (or between public and private sectors) Benefits compared 0 = Benefits compared with public sector with private sector 1 = Benefits compared with private sector (or between public and private sectors) No exemption from 0 = Exemption from taxation Capital market discipline taxation 1 = No exemption from taxation Access to debt 0 = Access to debt below the market rate compared with 1 = Access to debt equal or above the market rate private sector No state guarantees 0 = At least one state guarantee 1 = No state guarantee Public listing 0 = No public listing 1 = Public listing Source: Vagliasindi and Nellis 2010. Note: IFRS = International Financial Reporting Standards. Table A4.6b Institutional Indicators: SOE Governance, 2007 Ownership and shareholder quality Managerial and board autonomy Concen- Presence tration Rate Selection of of Corpo- of Size of inde- Provider owner- ratiza- Limited return Dividend Laying of the board pendent Country name ship tion liability policy policy Hiring off Wages Production Sales board members directors Benin SBEE 1 — — 0 0 1 1 1 0 1 1 0 — Burkina Faso Sonabel 1 1 0 1 1 1 1 1 1 1 1 — — Cameroon AES SONEL 0 1 1 1 1 1 1 1 1 1 1 0 — Cape Verde Electra 1 1 0 1 0 1 1 1 0 0 1 1 — Chad STEE 1 0 0 1 1 1 1 1 1 1 1 1 1 Congo, SNEL 0 — — 0 1 1 1 1 — — 1 0 — Dem. Rep. Côte d’Ivoire CIE 1 — 0 1 0 1 1 1 1 1 1 1 — Ethiopia EEPCO 1 — — — — — — — — — — — — Ghana ECG 1 1 1 1 1 1 0 1 1 1 1 1 — VRA 0 1 1 1 1 1 1 1 1 — 1 1 — Kenya KENGEN 0 1 1 1 1 1 1 1 — — 1 1 — KPLC 1 1 0 — 0 1 1 1 1 0 1 0 — Lesotho LEC 1 0 0 — — 1 1 1 0 1 1 1 — Madagascar JIRAMA 1 — — 1 1 1 1 1 1 0 1 1 — Malawi Escom 1 — — 1 1 1 1 1 1 1 — — — Mozambique EDM 1 1 — — — — — — — — — — — (continued next page) 255 256 Table A4.6b (continued) Ownership and shareholder quality Managerial and board autonomy Concen- Presence tration Rate Selection of of Corpor- of Size of inde- Provider owner- atiza- Limited return Dividend Laying of the board pendent Country name ship tion liability policy policy Hiring off Wages Production Sales board members directors Namibia Nampower — — — 1 1 1 — 1 1 1 1 1 — NORED 1 — — 0 1 1 1 1 1 0 1 1 1 Niger NIGELEC 1 1 — 1 — 1 1 1 1 1 1 0 — Nigeria PHNC 1 0 0 1 0 1 1 1 1 1 0 1 — Rwanda ELECTROGAZ 1 0 0 0 0 1 1 1 1 1 1 0 — Senegal Senelec — — — 1 1 1 1 0 1 0 — — — South Africa Capetown 1 1 1 1 1 1 1 1 1 0 1 1 — ESKOM — — — — — — — — — — — — — Tshwane 1 — — — — — — — — — — — — Sudan NEC 1 1 — — — — — — — — — — — Tanzania TANESCO 0 1 0 0 0 1 1 1 — 1 0 1 1 Uganda UEDCL 0 1 0 0 0 1 1 1 0 0 0 1 — UEGCL 1 1 0 0 0 1 1 1 1 0 0 0 1 UETCL 1 — — 1 1 1 1 1 1 1 1 1 — Zambia ZESCO 0 — — 0 0 1 1 1 0 — 1 1 — (continued next page) Table A4.6b (continued) Accounting and disclosure and performance monitoring Outsourcing Labor market discipline Capital market discipline Publication of annual reports No exemption from taxation Performance contracts with Benefits vs. private sector noncommercial activity Third-party monitoring Performance contracts Human resources (HR) Restriction to dismiss Billing and collection No state guarantees Independent audit Penalties for poor Wages compared Audit publication Access to debt vs. Remuneration of to private sector External audits Meter reading private sector performance Public listing of accounts Monitoring employees incentives IFRS Country IT Benin 0 1 1 1 0 0 0 1 0 0 1 0 — 0 0 — 1 — 1 0 0 — Burkina Faso 1 1 1 1 0 0 1 0 1 — 1 1 — 1 1 — 1 — 0 0 0 0 Cameroon 1 1 1 1 0 0 1 1 0 0 1 1 — 1 1 — 1 — 1 1 0 0 Cape Verde — 1 1 1 1 0 0 0 — — 1 0 — 0 0 — 1 — 1 1 1 0 Chad 1 0 1 1 0 0 0 0 1 — 1 0 — 0 0 — 1 — 1 1 0 0 Congo, Dem. Rep. 0 1 1 0 — 0 0 0 0 0 1 0 — 0 0 — 1 — 1 — 0 — Côte d’Ivoire 1 1 1 1 1 0 0 1 1 0 1 0 — 0 0 — 1 — 1 1 1 — Ethiopia — — — — — — — — — — — — — — — — — — — — — — Ghana 1 0 1 1 1 0 1 0 0 1 1 0 — 0 0 — 1 — 0 1 0 0 1 1 1 — — — 1 1 — — 1 — — — — — — — 1 — 0 0 Kenya 1 1 1 — — — 1 1 — 1 1 0 — 0 0 — 1 — 1 1 0 0 1 1 1 1 1 0 1 0 0 0 1 0 — 0 0 — 1 — 0 1 1 0 Lesotho 0 0 — — — 0 0 0 0 0 — 0 — 1 0 — 1 — 1 — — 0 Madagascar 0 1 1 1 1 0 1 1 1 1 1 1 — 1 1 — 1 — 1 1 0 0 Malawi 1 1 1 1 0 0 0 0 0 1 1 0 — 1 1 — 1 — 1 — 0 — Mozambique — — — — — — — — — — — — — — — — — — — — — — 257 Namibia 1 1 1 1 1 0 — — — 0 1 0 — 0 0 — 1 — 1 — 1 — 0 1 1 1 0 0 0 0 0 0 1 0 — 1 1 — 1 — 1 — 0 — 258 Table A4.6b (continued) Accounting and disclosure and performance monitoring Outsourcing Labor market discipline Capital market discipline Publication of annual reports No exemption from taxation Performance contracts with Benefits vs. private sector noncommercial activity Third-party monitoring Performance contracts Human resources (HR) Restriction to dismiss Billing and collection No state guarantees Independent audit Penalties for poor Wages compared Audit publication Access to debt vs. Remuneration of to private sector External audits Meter reading private sector performance Public listing of accounts Monitoring employees incentives IFRS Country IT Niger 1 1 1 1 1 0 1 1 1 1 1 1 — 0 0 — 1 — 0 1 0 — Nigeria 0 0 1 1 0 0 0 0 0 0 1 0 — 0 1 — 1 — 1 1 0 0 Rwanda 0 1 1 1 0 0 0 0 0 — 1 0 — 0 0 — 1 — 1 0 0 0 Senegal 1 0 1 1 1 0 1 1 0 1 1 0 — 0 0 — 1 — 0 0 1 — South Africa 1 1 1 1 1 0 1 1 1 1 1 0 — 0 1 — 1 — 1 1 1 0 — — — — — — — — — — — — — — — — — — — — — — — — — — — 0 — — — — — — — — — — — — — — — — Sudan — — — — — 0 — — — — — — — — — — — — — — — — Tanzania 1 1 1 1 1 0 0 1 0 1 1 0 — 0 1 — 1 — 1 1 1 0 Uganda 1 1 1 1 1 0 1 1 1 1 1 0 — 0 1 — 1 — 1 1 0 0 1 1 1 1 1 0 0 0 0 — 1 0 — 0 0 — 1 — 1 1 1 0 1 1 1 1 1 0 0 1 1 0 1 0 — 0 0 — 1 — 1 1 0 — Zambia 1 0 1 1 1 0 0 0 0 1 1 1 — 0 0 — 1 — 1 — 0 — Source: Vagliasindi and Nellis 2010. Note: IFRS = International Financial Reporting Standards; — = data not available. Table A4.7 Private Participation: Greenfield Projects, 1990–2006 Investment Capacity Contract Termination in facilities MW Country Project name Technology/fuel Project type year period year ($ million) developed Angola Chicapa Hydroelectric Plant Hydro Build, own, transfer 2003 40 2044 45 16 Aggreko Cabinda Temporary Power Station Diesel Rental 2006 2 2009 4.7 30 Aggreko Caminhos de Ferro de Angola Diesel Rental 2006 2 2009 4.7 30 Burkina Faso Hydro-Afrique Hydroelectric Plant Hydro Build, own, transfer 1998 14 2012 5.6 12 Congo, Rep. Sounda S.A. Geothermal Build, own, operate 1996 — 1998 325 240 Compagnie Ivoirienne de Production Diesel, Build, own, transfer 1994 19 2013 70 99 d’Electricité (CIPREL) natural gas Azito Power Project Natural gas Build, own, transfer 1999 23 2022 223 420 Ghana SIIF Accra Steam Merchant 1999 2 2001 0 39 Takoradi 2 Natural gas Build, own, operate 1999 25 2024 110 220 Kenya Iberafrica Power Ltd. Diesel Build, own, transfer 1996 7 2011 64 56 Mombasa Barge-Mounted Power Project Diesel Build, own, operate 1996 7 2004 35 46 Kipevu II Diesel Build, own, operate 1999 20 2019 85 75 Ormat Olkaria III Geothermal Geothermal Build, own, operate 1999 20 2019 54 13 Power Plant (phase 1) Aggreko Embakassi and Eldoret — Rental 2006 1 2007 7.89 100 Power Stations Mauritius Deep River Beau Champ Coal, waste Build, own, operate 1998 — — 0 29 Belle Vue Power Plant Coal Build, own, operate 1998 20 2018 109.3 100 FUEL Power Plant Coal, waste Build, own, operate 1998 20 2018 0 40 St. Aubin Power Project Coal, waste Build, own, operate 2004 20 2025 0 34 (continued next page) 259 260 Table A4.7 (continued) Investment Capacity Contract Termination in facilities MW Country Project name Technology/fuel Project type year period year ($ million) developed Nigeria AES Nigeria Barge Limited Natural gas Build, own, operate 2001 — — 240 306 Okpai Independent Power Project Natural gas Build, own, operate 2002 — — 462 450 AEL Ilorin Gas Power Plant Natural gas Build, own, operate 2005 — — 275 105 Dadin Kowa Hydropower Plant Hydro Build, own, transfer 2005 25 2030 26 39 Rwanda Aggreko 10 MW Power Station Rwanda — Rental 2005 2 2007 1.58 10 Senegal GTi Dakar Ltd. Diesel, Build, own, transfer 1997 15 2012 59 56 natural gas Aggreko Dakar Temporary Power Station — Rental 2005 2 2008 6.31 40 Kounoune I IPP Diesel Build, own, operate 2005 15 2020 87 68 South Africa Bethlehem Hydro Hydro Build, own, operate 2005 20 2025 7 4 Darling Wind Farm Wind Build, own, operate 2006 20 2026 9.9 5 Tanzania Tanwat Wood-Fired Power Plant Waste Build, lease, own 1994 6 2000 6 2.5 Independent Power Tanzania Ltd Diesel Build, own, transfer 1997 20 2017 127 100 Songas–Songo Songo Gas-to-Power Project Natural gas Build, own, transfer 2001 20 2021 316 — Songas–Songo Songo Gas-to-Power Project Natural gas Build, own, transfer 2004 20 2021 0 115 Songas–Songo Songo Gas-to-Power Project Natural gas Build, own, transfer 2005 20 2021 0 190 Mtwara Region Gas-to-Power Project Natural gas Build, own, operate 2005 25 2021 32 12 Aggreko Ubungo Temporary Power Station Natural gas Rental 2006 2 2009 6.31 40 Alstom Power Rentals Mwanza Diesel Rental 2006 2 2008 6.31 40 Dowans Lease Power Ubungo Natural gas Rental 2006 2 2009 15.78 100 Uganda Aggreko Kampala Temporary Power Station Diesel Rental 2005 3 2008 11.83 50 Aggreko Jinja Temporary Power Station Diesel Rental 2006 2 2008 11.8 50 Source: World Bank 2007. Note: Termination year can be year when the project is concluded according to the original agreement, rescheduling, or project cancellation. MW = megawatts; — = data not available. Table A4.8 Private Participation: Concessions, Management and Lease Contracts, Divestitures, 1990–2006 Investment in Number of Project Capacity Contract Termination % facilities connections Country Project name Project type status year period year private ($ million) (thousands) MW Concession: Cameroon AES Sonel Build, rehab., Operational 2001 20 2021 56 39.8 452 operate, transfer AES Sonel Build, rehab., Operational 2002 20 2021 56 21.5 — — operate, transfer AES Sonel Build, rehab., Operational 2005 20 2021 56 0 528 n.a. operate, transfer AES Sonel Build, rehab., Operational 2006 20 2021 56 440 528 n.a. operate, transfer Comoros Comorienne de Rehab., operate, Canceled 1998 n.a. 2001 100 0 n.a. 16 d’eau et de transfer l’electricité (CEE) Côte d’Ivoire Compagnie Rehab., operate, Operational 1990 20 2010 100 39.6 411.7 n.a. Ivoirienne transfer d’ Electricité Compagnie Rehab., operate, Operational 2000 20 2010 100 0 760 n.a. Ivoirienne transfer d’ Electricité Compagnie Rehab., operate, Operational 2005 20 2010 85 0 — — Ivoirienne transfer d’ Electricité (continued next page) 261 262 Table A4.8 (continued) Investment in Number of Project Capacity Contract Termination % facilities connections Country Project name Project type status year period year private ($ million) (thousands) MW Gabon Société d’Energie Build, rehab., oper- Operational 1997 20 2017 100 268 84 n.a. et d’Eau du ate, transfer Gabon (SEEG) Société d’Energie Build, rehab., oper- Operational 2002 20 2017 100 0 125 n.a. et d’Eau du ate, transfer Gabon (SEEG) Guinea Société Guineenne Rehab., lease or Concluded 1995 10 2005 66 36.4 n.a. 180 d’Electricité rent, transfer Mali Energie du Mali Build, rehab., Distressed 2000 26 2020 60 337 120 n.a. (EDM) operate, transfer Energie du Mali Build, rehab., Distressed 2004 26 2020 34 0 — — (EDM) operate, transfer Mozambique Energia de Build, rehab., Operational 2004 20 2024 100 5.8 3000 n.a. Mocambique operate, transfer Lda (ENMo) Nigeria Afam Power Rehab., operate, Operational 2005 15 2020 100 238 n.a. 400 Project transfer São Tomé and Sinergie Build, rehab., Operational 2004 45 2049 100 50 n.a. — Príncipe concession operate, transfer contract Senegal Société Nationale Build, rehab., Canceled 1999 25 2000 34 0 n.a. 300 d’Electricité operate, transfer du Senegal (SENELEC) South Africa PN Energy Build, rehab., Operational 1995 n.a. n.a. 67 3 — n.a. Services (Pty) Ltd operate, transfer Togo Togo Electricité Rehab., lease or Canceled 2000 20 2006 100 36 — — rent, transfer Uganda Kasese Electrifica- Rehab., operate, Operational 2003 n.a. n.a. n.a. 0 n.a. 5.5 tion Project transfer Uganda Electricity Rehab., lease or Operational 2003 20 2023 100 6.8 n.a. 300 Generation rent, transfer Company Limited Western Nile Rural Rehab., operate, Operational 2003 20 2023 100 11.3 n.a. 3.5 Electrification transfer Project Umeme Limited Rehab., lease or Operational 2005 20 2025 100 65 250 n.a. rent, transfer Management and lease contracts: Chad Société Tchadienne Canceled 2000 30 2004 100 0 16 n.a. d’Eau et d’Electricité (STEE) Gabon Société Management Concluded 1993 4 1997 100 0 — — Africaine de contract Gestion et d’Investissement (SAGI) 263 (continued next page) 264 Table A4.8 (continued) Investment in Number of Project Capacity Contract Termination % facilities connections Country Project name Project type status year period year private ($ million) (thousands) MW Gambia, The Management Lease contract Canceled 1993 10 1996 100 0 — — Service Gambia (MSG) National Water Management Operational 2006 5 2011 100 0 n.a. 40 and Electricity contract Company Management Contract Ghana Electricity Management Concluded 1994 4 1998 100 0 500 n.a. Corporation of contract Ghana Guinea-Bissau Electricidade Management Concluded 1991 4 1997 100 0 n.a. 10.4 e Aguas de contract Guinea-Bissau Kenya Kenya Power and Management Operational 2006 2 2008 100 0 800 n.a. Lighting contract Company Management Contract Lesotho Lesotho Electricity Management Operational 2002 n.a. n.a. 100 0 n.a. — Corporation (LEC) contract Madagascar Jiro sy Rano Management Operational 2005 2 2007 n.a. 0 340 n.a. Malagasy (Jirama) contract Malawi Electricity Supply Management Concluded 2001 2 2003 100 0 n.a. 300 Corporation contract of Malawi Ltd (ESCOM) Mali Electricité et Management Concluded 1994 5 2000 100 0 — — Eau du Mali contract (Management) Namibia Northern Electricity Management and Concluded 1996 5 2002 n.a. 4 n.a. — lease contract Namibia Reho-Electricity Lease contract Operational 2000 n.a. n.a. n.a. 1 — n.a. Rwanda ELECTROGAZ Management Canceled 2003 5 2006 100 0 25 n.a. contract ELECTROGAZ Management Canceled 2005 5 2006 100 0 67 n.a. contract São Tomé Empresa de Agua Management Concluded 1993 3 1996 100 0 n.a. 4.75 and Príncipe e Electricidade contract Tanzania Tanzania Electricity Management Concluded 2002 4 2006 0 0 — — Supply Company contract (TANESCO) Togo Companie Energie Management Concluded 1997 4 2000 n.a. 0 n.a. n.a. Electrique du Togo contract (continued next page) 265 266 Table A4.8 (continued) Investment in Number of Project Capacity Contract Termination % facilities connections Country Project name Project type status year period year private ($ million) (thousands) MW Divestitures: Cape Verde Electra Partial Operational 1999 30 2030 51 0 35 n.a. Cape Verde Electra Partial Operational 2003 30 2030 51 0 71 n.a. Kenya Kenya Electricity Partial Operational 2006 n.a. n.a. 30 0 n.a. 945 Generating Company South Africa AES Kelvin Power Partial Operational 2001 20 2021 50 28.4 n.a. 600 Zambia Zambia Partial Operational 1997 n.a. n.a. 80 92.5 n.a. n.a. Consolidated Copper Mines Ltd. Power Division distribution Lunsemfwa Hydro Full Operational 2001 n.a. n.a. 100 3 n.a. 38 Power Zimbabwe African Power Partial Operational 1998 n.a. n.a. 51 0 n.a. 920 Source: World Bank 2007. Note: Termination year can be year when the project is concluded according to the original agreement, rescheduling, or project cancellation. MW = megawatts; n.a. = not applicable; — = data not available. APPENDIX 5 Widening Connectivity and Reducing Inequality 267 268 Table A5.1 Access to Electricity percentage of population By time period (national) By location By expenditure quintile Country Early 1990s Late 1990s Early 2000s Rural Urban Q1 Q2 Q3 Q4 Q5 Benin — 14 22 6 51 0 1 3 24 82 Burkina Faso 6 6 10 1 54 0 0 1 2 57 Cameroon 31 42 46 16 77 1 14 37 78 98 Central African Republic 5 — — 1 11 0 0 0 1 25 Chad — 3 4 0 20 0 0 0 0 21 Comoros — 30 — 21 54 0 7 17 48 84 Congo, Dem. Rep. — — — — — — — — — — Congo, Rep. — — 35 16 51 5 14 20 47 88 Côte d’Ivoire 39 50 — 27 90 4 19 41 87 100 Ethiopia — 11 12 2 86 0 0 1 3 56 Gabon — 75 — 31 91 17 69 93 98 99 Ghana 28 39 44 21 77 8 39 28 57 90 Guinea — 17 21 3 63 0 0 4 18 83 Kenya 9 12 13 4 51 0 0 1 7 57 Lesotho — — 6 1 28 0 0 0 1 27 Madagascar 9 11 19 10 52 0 0 1 11 82 Malawi 4 6 7 2 34 0 1 0 3 34 Mali — 8 13 3 41 1 3 2 5 54 Mauritania — — 23 3 51 0 2 5 29 81 Mozambique — 10 11 1 30 0 0 1 4 51 Namibia 20 32 — 10 75 1 1 6 51 100 Niger 6 8 — 0 41 0 0 0 4 36 Nigeria 26 45 51 35 84 10 37 40 78 91 Rwanda 2 7 5 1 27 0 0 1 1 25 Senegal 25 32 46 19 82 4 12 46 76 94 South Africa — 63 — 36 86 10 36 74 98 100 Sudan — — — — — — — — — — Tanzania 6 7 11 2 39 0 0 0 3 50 Togo — 15 — 2 44 0 0 2 10 62 Uganda 7 — 8 3 47 0 0 2 2 38 Zambia 23 20 20 3 50 0 0 0 15 84 Zimbabwe 23 34 — 7 90 0 12 12 50 97 Overall 23 28 31 12 71 4 14 20 38 72 Income group Low income 17 24 27 11 69 3 12 15 32 68 Middle income 59 55 53 27 81 7 28 59 86 97 Urbanization Low 8 8 11 3 56 0 0 1 4 52 Medium 24 30 28 3 48 0 1 2 11 60 High 37 47 51 30 83 8 32 45 79 94 Region East 17 24 27 2 60 0 0 1 3 53 West 25 37 43 20 78 6 23 27 55 80 South 36 37 35 13 66 4 14 28 42 77 Central 25 28 29 8 66 1 11 20 47 76 Source: Banerjee and others 2008. Note: Location and expenditure quintile data are for the latest available year. — = data not available. 269 270 Table A5.2 Adjusted Access, Hook-Up, Coverage of Electricity, Latest Available Year, Urban Areas Share of deficit Share of Share of attributable Mixed deficit deficit to both Pure Pure demand- and attributable to attributable to supply- and Unserved demand-side Supply-side supply-side supply-side demand-side supply-side demand-side Country Access Hookup Coverage population gap gap gap gap factors only factors only factors Benin 83 83 51 49 18 31 26 5 36 53 11 Burkina Faso 92 62 54 46 3 43 27 16 7 57 35 Cameroon 94 98 77 23 15 8 8 0 65 34 1 Central African Republic 57 33 11 89 8 81 27 54 9 30 61 Chad 77 28 20 80 1 79 22 57 2 27 71 Comoros 100 82 54 46 28 18 15 3 61 32 7 Congo, Rep. 98 86 51 49 33 16 13 2 68 27 4 Côte d’Ivoire 100 99 90 10 10 1 1 0 93 7 0 Ethiopia 99 90 86 14 3 11 10 1 20 72 8 Gabon 100 99 91 9 9 1 1 0 94 6 0 Ghana 98 95 77 23 15 8 7 0 67 31 2 Guinea 89 78 63 37 6 31 24 7 16 66 18 Kenya 80 72 51 49 6 42 31 12 13 63 24 Lesotho 87 42 28 72 8 64 27 37 12 37 51 Madagascar 80 86 52 48 16 32 27 5 34 56 10 Malawi 84 48 34 66 7 59 29 31 10 43 47 Mali 81 62 41 59 9 49 31 19 16 52 32 Mauritania 85 84 51 49 20 29 24 5 41 49 10 Mozambique 80 51 30 70 11 59 30 29 16 43 41 Namibia 93 99 75 25 17 8 8 0 69 31 0 Niger 94 49 41 59 6 54 26 27 9 45 46 Nigeria 98 98 84 16 12 4 4 0 73 26 1 Rwanda 72 46 27 73 6 67 31 36 8 42 49 Senegal 99 100 82 18 17 1 1 0 95 5 0 South Africa 95 100 86 14 8 6 6 0 58 42 0 Tanzania 83 55 39 61 7 54 30 25 11 49 40 Togo 96 66 44 56 19 37 24 12 34 44 22 Uganda 93 58 47 53 6 46 27 20 12 51 37 Zambia 84 84 50 50 21 29 24 5 42 49 9 Zimbabwe 100 99 90 10 8 2 1 0 85 15 0 Overall 93 87 71 29 11 18 12 6 52 37 11 Income group Low income 93 84 69 31 11 21 13 7 50 37 13 Middle income 95 98 81 19 11 7 7 1 61 38 1 Urbanization Low 87 67 53 47 6 41 24 17 15 56 29 Medium 86 73 52 48 13 35 22 14 37 42 21 High 97 98 83 17 12 5 5 0 71 28 1 Region East 89 71 59 41 5 36 23 14 15 60 26 West 96 93 78 22 12 10 8 2 67 29 5 South 90 87 69 31 10 20 14 7 48 41 10 Central 69 80 60 40 15 25 12 13 53 30 17 Source: Banerjee and others 2008. 271 272 Table A5.3 Electricity Expenditure and Its Share in Household Budget Expenditure budget (2002 $) Share in household budget (%) Country Year Nationalaa Rural Urban Q1 Q2 Q3 Q4 Q5 National Rural Urban Q1 Q2 Q3 Q4 Q5 Angola 2000 — — — — — — — — — — — — — — — — Benin 2002 — — — — — — — — — — — — — — — — Burkina Faso 2003 4 11 1 12 10 8 6 2 3 10 1 25 15 9 5 1 Burundi 1998 — — — — — — — — — — — — — — — — Cameroon 2004 1 1 1 1 0 0 1 2 1 1 1 3 0 0 1 1 Cape Verde 2001 2 2 3 2 2 2 2 3 2 2 1 3 2 2 2 1 Chad 2001 13 5 15 3 5 8 12 18 4 3 3 3 4 4 4 3 Congo, Dem. Rep. 2005 2 1 2 1 1 1 2 3 2 1 2 2 2 2 2 2 Congo, Rep. 2002 — — — — — — — — — — — — — — — — Côte d’Ivoire 2005 7 5 7 3 5 7 7 9 3 3 3 3 3 4 3 2 Ethiopia 2000 2 0 2 1 1 1 1 3 3 1 2 2 2 2 2 3 Gabon 2005 20 9 21 2 13 17 21 27 4 4 4 2 4 4 4 4 Ghana 1999 5 4 6 1 4 3 5 6 3 3 3 2 4 2 3 2 Guinea-Bissau 2005 — — — — — — — — — — — — — — — — Kenya 1997 8 6 8 0 1 1 2 9 5 6 3 1 2 1 1 4 Madagascar 2001 2 2 2 0 0 1 2 2 1 1 0 0 0 1 1 0 Malawi 2003 10 7 11 1 1 3 4 12 14 12 9 3 1 6 6 10 Mauritania 2000 15 4 16 3 20 10 12 18 7 2 5 4 15 6 5 5 Morocco 2003 14 8 15 6 9 12 15 23 3 2 3 4 3 3 3 2 Mozambique 2003 13 6 14 3 6 6 9 15 20 12 12 15 17 13 16 10 Niger 2005 12 9 12 4 5 7 6 14 10 8 6 7 7 8 5 6 Nigeria 2003 5 4 5 5 4 4 5 5 6 5 5 15 9 6 5 4 Rwanda 1998 10 5 11 — — 1 4 11 10 7 3 — — 1 4 4 São Tomé and Príncipe 2000 26 8 40 1 2 4 7 82 12 5 16 1 2 3 4 19 Senegal 2001 9 6 10 4 5 6 8 11 4 4 3 4 4 4 3 3 Sierra Leone 2003 9 6 9 0 1 2 5 12 8 7 6 0 2 3 4 5 South Africa 2000 12 5 16 2 4 6 9 26 2 2 2 2 3 3 3 2 Tanzania 2000 — — — — — — — — — — — — — — — — Uganda 2002 6 5 6 1 2 2 4 9 7 7 5 5 4 4 4 4 Zambia 2002 5 4 5 1 1 2 4 7 5 5 4 3 2 3 4 4 Overall 9 5 10 3 4 5 6 14 6 5 4 5 5 4 4 4 Income group Low income 9 5 10 2 4 4 5 13 7 5 5 5 5 4 4 5 Middle income 10 5 11 3 6 7 10 16 3 2 2 3 3 3 3 2 Urbanization Low 7 6 8 3 3 4 5 9 6 6 4 6 4 4 4 4 Medium 7 4 8 1 2 3 5 9 9 6 6 5 6 5 7 5 High 11 5 13 3 6 7 8 19 4 3 4 4 4 3 3 4 Region East 6 4 7 1 1 1 3 8 6 5 3 3 2 2 3 4 West 10 6 11 4 6 6 7 17 6 5 5 6 6 5 4 5 South 8 5 10 1 2 4 6 12 9 6 5 5 5 5 6 5 Central 9 4 10 2 5 7 9 12 3 2 3 3 2 2 3 2 Source: Banerjee and others 2008. Note: Q = quintile; — = data not available. a. Sample average. 273 274 Table A5.4 Kerosene Expenditure and Its Share in Household Budget Expenditure budget (2002 $) Share in household budget (%) Country Year Nationalaa Rural Urban Q1 Q2 Q3 Q4 Q5 National Rural Urban Q1 Q2 Q3 Q4 Q5 Angola 2000 Benin 2002 2 2 2 2 2 2 2 2 2 3 2 5 4 3 2 2 Burkina Faso 2003 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 Burundi 1998 1 1 4 1 1 1 2 2 2 2 2 4 3 2 2 2 Cameroon 2004 — — — — — — — — — — — — — — — — Cape Verde 2001 2 1 2 1 1 1 2 2 1 2 1 2 2 1 1 1 Chad 2001 — — — — — — — — — — — — — — — — Congo, Dem. Rep. 2005 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Congo, Rep. 2002 — — — — — — — — — — — — — — — — Côte d’Ivoire 2005 3 3 4 2 3 3 3 4 1 2 1 3 2 2 1 1 Ethiopia 2000 1 0 1 0 0 0 1 1 1 1 1 1 1 1 1 1 Gabon 2005 4 6 3 5 5 4 4 4 1 2 1 5 1 1 1 1 Ghana 1999 4 3 5 2 3 2 7 3 2 2 2 3 3 2 4 1 Guinea-Bissau 2005 — — — — — — — — — — — — — — — — Kenya 1997 2 1 4 1 1 2 2 3 1 1 2 2 2 2 2 1 Madagascar 2001 3 2 4 0 0 0 11 3 1 1 1 0 0 0 4 1 Malawi 2003 2 1 13 1 1 1 1 6 3 2 10 2 2 2 2 5 Mauritania 2000 1 2 1 0 1 2 2 1 1 1 0 0 1 1 1 0 Morocco 2003 3 3 2 3 3 4 4 5 1 1 0 2 1 1 1 0 Mozambique 2003 — — — — — — — — — — — — — — — — Niger 2005 — — — — — — — — — — — — — — — — Nigeria 2003 3 3 4 2 2 3 3 4 4 3 4 6 4 4 4 3 Rwanda 1998 1 1 2 1 1 1 1 2 1 2 1 2 2 2 1 1 São Tomé and Príncipe 2000 — — — — — — — — — — — — — — — — Senegal 2001 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 Sierra Leone 2003 3 2 3 2 2 2 3 4 2 3 2 4 3 3 3 1 South Africa 2000 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 Tanzania 2000 — — — — — — — — — — — — — — — — Uganda 2002 1 1 1 1 1 1 1 2 1 2 1 2 2 2 1 1 Zambia 2002 — — — — — — — — — — — — — — — — Overall 2 2 3 1 2 2 3 3 1 2 2 2 2 2 2 1 Income group Low income 2 2 3 1 1 2 3 0 2 2 2 3 2 2 2 0 Middle income 2 3 2 2 2 2 2 3 1 1 1 2 1 1 1 1 Urbanization Low 2 1 4 1 1 1 3 3 2 2 2 2 2 1 2 1 Medium 2 2 2 1 2 2 2 0 2 2 2 3 3 2 2 0 High 2 3 2 2 2 2 3 3 1 2 1 2 2 1 2 1 Region East 1 1 2 1 1 1 1 2 1 2 1 2 2 2 2 1 West 2 2 3 2 2 2 3 3 2 2 1 3 2 2 2 1 South 2 1 6 0 0 0 4 4 2 1 4 1 1 1 2 2 Central 3 4 2 3 3 2 2 3 1 2 1 3 1 1 1 1 Source: Banerjee and others 2008. Note: Q = quintile; — = data not available. a. Sample average. 275 276 Table A5.5 Liquefied Propane Gasoline (LPG) Expenditure and Its Share in Household Budget Expenditure budget (2002 $) Share in household budget (%) Country Year Nationalaa Rural Urban Q1 Q2 Q3 Q4 Q5 National Rural Urban Q1 Q2 Q3 Q4 Q5 Angola 2000 — — — — — — — — — — — — — — — — Benin 2002 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 Burkina Faso 2003 5 5 5 5 5 5 5 5 4 5 2 10 7 5 4 2 Burundi 1998 — — — — — — — — — — — — — — — — Cameroon 2004 — — — — — — — — — — — — — — — — Cape Verde 2001 3 2 3 1 2 3 3 3 2 3 2 2 3 3 3 2 Chad 2001 13 12 13 7 9 11 13 15 4 6 3 7 6 5 4 2 Congo, Dem. Rep. 2005 1 0 2 1 0 0 0 1 1 0 1 2 0 0 0 1 Congo, Rep. 2002 — — — — — — — — — — — — — — — — Côte d’Ivoire 2005 5 4 5 2 3 4 5 5 2 3 2 2 2 2 2 1 Ethiopia 2000 1 0 1 1 0 0 0 2 1 0 2 3 1 0 0 2 Gabon 2005 11 11 11 9 11 11 11 10 2 4 2 10 3 3 2 2 Ghana 1999 6 5 6 — — 3 6 6 4 4 3 — — 2 3 2 Guinea-Bissau 2005 — — — — — — — — — — — — — — — — Kenya 1997 14 11 14 — — 2 9 14 10 10 6 — — 2 7 6 Madagascar 2001 6 6 6 — 8 — 14 5 2 3 1 — 6 — 5 1 Malawi 2003 — — — — — — — — — — — — — — — — Mauritania 2000 2 1 4 0 1 2 3 4 1 1 1 0 1 1 1 1 Morocco 2003 10 9 11 6 8 10 13 16 2 3 2 4 3 3 2 2 Mozambique 2003 — — — — — — — — — — — — — — — — Niger 2005 8 2 10 1 1 1 2 10 6 2 5 2 1 1 2 4 Nigeria 2003 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Rwanda 1998 3 1 20 0 1 1 1 7 3 1 6 1 1 1 1 3 São Tomé and Príncipe 2000 — — — — — — — — — — — — — — — — Senegal 2001 6 3 7 2 3 4 6 8 3 2 2 2 2 2 3 2 Sierra Leone 2003 5 1 6 0 3 2 7 5 1 4 1 4 2 3 South Africa 2000 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Tanzania 2000 — — — — — — — — — — — — — — — — Uganda 2002 — — — — — — — — — — — — — — — — Zambia 2002 6 3 10 1 1 1 5 12 6 3 8 2 2 2 5 7 Overall 5 4 7 2 3 3 5 7 3 2 3 3 2 2 2 2 Income group Low income 5 3 7 2 3 3 4 6 3 3 3 3 2 2 3 2 Middle income 6 6 6 4 5 6 7 7 2 2 1 4 2 2 2 1 Urbanization Low 7 5 10 3 4 3 6 8 4 4 4 5 4 3 3 3 Medium 3 1 5 1 1 1 2 5 3 1 3 2 1 2 2 3 High 5 4 5 3 4 4 5 6 2 2 2 2 2 2 2 1 Region East 6 4 12 1 0 1 3 7 5 4 5 2 1 1 3 3 West 5 3 5 2 3 3 4 6 3 2 2 2 2 2 2 2 South 4 3 5 0 3 1 6 6 3 2 3 1 3 1 3 3 Central 8 8 8 6 7 7 8 9 2 3 2 6 3 3 2 2 Source: Banerjee and others 2008. Note: Q = quintile; — = data not available. a. Sample average. 277 278 Table A5.6 Wood/Charcoal Expenditure and Its Share in Household Budget Expenditure budget (2002 $) Share in household budget (%) a Country Year National a Rural Urban Q1 Q2 Q3 Q4 Q5 National Rural Urban Q1 Q2 Q3 Q4 Q5 Angola 2000 — — — — — — — — — — — — — — — — Benin 2002 4 4 4 4 4 3 4 4 4 5 3 9 6 5 4 3 Burkina Faso 2003 4 4 4 4 4 4 4 4 3 4 2 8 5 4 3 2 Burundi 1998 8 4 11 2 3 3 4 9 12 6 5 9 8 6 7 8 Cameroon 2004 3 3 3 0 1 1 2 5 3 3 2 1 1 2 2 3 Cape Verde 2001 3 3 3 3 3 3 3 3 3 4 2 5 4 3 3 2 Chad 2001 6 8 5 4 4 5 9 9 2 4 1 4 2 2 3 1 Congo, Dem. Rep. 2005 1 1 2 1 1 1 1 2 1 1 1 1 1 1 1 1 Congo, Rep. 2002 — — — — — — — — — — — — — — — — Côte d’Ivoire 2005 5 6 5 4 5 6 5 5 2 3 2 5 4 3 2 1 Ethiopia 2000 4 4 2 3 4 4 4 5 7 8 3 9 8 8 7 6 Gabon 2005 5 6 5 4 5 4 5 6 1 2 1 4 2 1 1 1 Ghana 1999 6 4 6 2 4 4 8 6 3 3 3 3 3 3 4 2 Guinea-Bissau 2005 — — — — — — — — — — — — — — — — Kenya 1997 4 4 4 2 3 3 4 4 3 3 2 4 4 3 3 2 Madagascar 2001 2 2 2 3 1 1 2 2 1 1 0 3 1 1 1 0 Malawi 2003 6 6 8 5 6 6 7 8 9 10 6 14 13 12 10 7 Mauritania 2000 3 2 4 1 2 3 4 3 1 1 1 1 1 2 2 1 Morocco 2003 2 3 2 2 2 2 3 3 1 1 0 1 1 1 1 0 Mozambique 2003 0 0 0 0 0 0 0 1 1 1 0 1 1 1 1 0 Niger 2005 6 5 7 4 4 5 6 7 5 5 4 8 5 5 5 3 Nigeria 2003 1 1 2 1 2 2 1 1 2 2 2 5 3 2 2 1 Rwanda 1998 8 5 10 1 1 3 4 11 8 7 3 3 3 4 4 4 São Tomé and Príncipe 2000 — — — — — — — — — — — — — — — — Senegal 2001 1 1 1 0 1 0 1 1 0 0 0 0 1 0 0 0 Sierra Leone 2003 3 2 4 1 2 2 3 4 3 3 2 3 3 3 3 2 South Africa 2000 3 4 3 3 4 5 3 2 1 2 0 3 3 2 1 0 Tanzania 2000 — — — — — — — — — — — — — — — — Uganda 2002 4 3 4 2 2 3 4 6 5 5 3 7 5 5 4 3 Zambia 2002 4 2 7 1 1 1 2 9 4 2 5 3 3 2 2 5 Overall 4 3 4 2 3 3 4 5 3 3 2 5 4 3 3 2 Income group Low income 4 3 5 2 3 3 4 5 4 4 2 5 4 4 3 3 Middle income 3 4 3 2 3 3 3 4 2 2 1 3 2 2 1 1 Urbanization Low 5 5 6 3 3 4 5 6 5 5 3 7 5 5 5 4 Medium 3 2 3 1 2 2 2 4 3 2 2 3 3 2 2 2 High 3 3 3 2 3 3 3 4 2 2 1 3 2 2 2 1 Region East 5 4 6 2 3 3 4 7 7 6 3 7 6 5 5 4 West 3 3 4 2 3 3 4 4 2 3 2 4 3 3 3 2 South 3 3 4 2 3 3 3 4 3 3 2 5 4 3 3 2 Central 4 5 4 2 3 3 4 6 2 3 1 3 2 2 2 2 Source: Banerjee and others 2008. Note: Q = quintile; — = data not available. a. Sample average. 279 280 Table A5.7 Rural Access to Power, Off-Grid Power, and Rural Electrification Agency and Fund Estimated rural Estimated rural Rural population population population served by with access Existence of Residential with access, off-grid power, served by Existence of rural rural access, number of number of off-grid electrification electrification rural (%) people people power (%) agency fund Benin 6 269,301 93,000 34.53 Yes Yes Burkina Faso 1 84,560 36,250 42.87 Yes Yes Cameroon 16 1,209,150 Yes No Central African Republic 1 12,838 Chad 0 21,745 No No Comoros 21 79,027 Congo, Rep. 16 250,773 Côte d’Ivoire 27 2,615,106 500,000 19.12 No Yes Ethiopia 2 1,145,293 192,500 16.81 Yes Yes Gabon 31 74,774 Ghana 21 2,378,302 25,000 1.05 No No Guinea 3 195,013 Kenya 4 928,828 397,500 42.80 No Yes Lesotho 1 12,370 No Yes Madagascar 10 1,258,024 Yes Yes Malawi 2 256,185 No Yes Mali 3 238,364 Mauritania 3 47,275 Mozambique 1 189,700 Yes Yes Namibia 10 135,965 No Yes Niger 0 28,564 No No Nigeria 35 23,286,973 1,062,500 4.56 Yes Yes Rwanda 1 107,879 16,000 14.83 No No Senegal 19 1,240,233 285,000 22.98 Yes Yes South Africa 36 6,824,964 No Yes Tanzania 2 498,401 Yes Yes Togo 2 71,490 Uganda 3 610,555 462,500 75.75 Yes Yes Zambia 3 254,274 Yes Yes Zimbabwe 7 617,540 Source: Banerjee and others 2008. Note: Blank cells = data not available. 281 282 Africa’s Power Infrastructure Table A5.8 Share of Urban Households Whose Utility Bill Would Exceed 5 Percent of the Monthly Household Budget at Various Prices percent Monthly bill Group Country $2 $4 $6 $8 $10 $12 $14 $16 Cape Verde 0 0 0 0 0 0 0 0 Morocco 0 0 0 0 0 0 0 0 Senegal 0 0 0 0 0 0 1 1 1 South Africa 0 0 0 0 1 1 1 1 Cameroon 0 0 0 0 1 2 7 17 Côte d’Ivoire 0 0 1 2 3 5 7 10 Congo, Rep. 0 0 3 5 12 21 28 35 Ghana 0 2 7 11 30 46 55 67 Benin 0 2 4 12 33 45 60 71 Kenya 0 0 5 20 36 62 72 78 Sierra Leone 0 4 16 30 44 54 62 67 2 São Tomé and Príncipe 0 2 13 29 46 64 77 81 Burkina Faso 0 4 20 34 47 62 72 78 Zambia 0 4 18 35 50 58 67 76 Nigeria 3 10 23 35 57 78 89 95 Madagascar 0 16 28 47 61 68 78 85 Niger 1 11 28 55 70 79 89 93 Tanzania 1 8 25 55 75 89 96 98 Guinea-Bissau 0 6 38 65 81 89 91 93 Uganda 2 17 45 65 82 90 96 97 3 Burundi 7 29 53 72 82 90 97 100 Malawi 2 32 66 78 87 92 93 94 Congo, Dem. Rep. 9 49 79 91 98 99 100 100 Ethiopia 40 87 95 99 99 99 99 100 Summary Low income 5.0 18.4 32.4 44.5 59.5 72.3 79.7 84.3 Middle income 0.0 0.0 0.1 0.2 1.2 1.8 2.9 4.7 All 3.7 13.7 24.2 33.2 44.7 54.3 60.2 64.1 Source: Banerjee and others 2008. Widening Connectivity and Reducing Inequality 283 Table A5.9 Overall Targeting Performance (Ω) of Utility Subsidies Country Omega (Ω) value Burkina Faso 0.06 Burundi 0.10 Cameroon 0.36 Cape Verde 0.48 Central African Republic 0.27 Chad 0.06 Congo, Rep. 0.62 Côte d’Ivoire 0.51 Gabon 0.78 Ghana 0.31 Guinea 0.22 Mozambique 0.31 Nigeria 0.79 Rwanda 0.01 São Tomé and Príncipe 0.41 Senegal 0.41 Togo 0.47 Uganda 0.02 Source: Banerjee and others 2008. 284 Africa’s Power Infrastructure Table A5.10 Potential Targeting Performance of Connection Subsidies under Different Subsidy Scenarios Scenario 1 Scenario 2 Scenario 3 Distribution of connection Only households subsidies mirrors with access but no All unconnected distribution of existing connection receive households receive Country connections subsidy subsidy Burkina Faso 0.08 0.64 1.10 Burundi 0.23 0.83 1.03 Cameroon 0.46 1.17 1.40 Cape Verde 0.55 1.27 1.35 Central African Republic 0.36 0.73 1.02 Chad 0.12 0.58 1.01 Congo, Rep. 0.41 1.02 1.23 Côte d’Ivoire 0.61 1.33 1.33 Gabon 0.75 1.17 1.30 Ghana 0.38 0.98 1.52 Guinea 0.25 0.52 1.15 Mozambique 0.35 1.08 1.06 Nigeria 0.77 1.09 1.10 Rwanda 0.03 0.47 1.05 São Tomé and Príncipe 0.56 1.15 1.33 Senegal 0.63 1.23 1.22 Togo 0.47 0.92 1.18 Uganda 0.06 0.87 1.08 Source: Banerjee and others 2008. Table A5.11 Value of Cost Recovery Bill at Consumption of 50 kWh/Month Based on total historical cost Based on LRMC % of monthly budget % of monthly budget Country $/month Nationala Q1 Q2 Q3 Q4 Q5 $/month Nationala Q1 Q2 Q3 Q4 Q5 Benin 10 11 24 17 14 12 7 10 11 23 16 13 11 7 Burkina Faso 8 6 16 11 9 7 3 13 10 26 19 15 11 6 Cameroon 9 8 18 12 10 7 5 4 3 7 5 4 3 2 Cape Verde 9 7 14 11 9 8 5 — — — — — — — Chad 7 2 7 4 3 2 1 4 1 4 2 2 1 1 Congo, Dem. Rep. 3 3 8 5 4 3 2 2 2 4 3 2 2 1 Congo, Rep. 10 5 14 9 7 5 3 3 1 4 3 2 2 1 Côte d’Ivoire 5 2 7 4 3 2 1 8 3 9 5 4 3 2 Ethiopia 4 7 13 10 8 7 5 10 17 30 23 19 16 11 Ghana 6 4 10 6 4 3 2 5 3 8 5 4 3 2 Kenya 7 5 13 9 7 5 3 6 4 11 7 6 4 3 Madagascar 7 3 8 5 4 3 1 — — — — — — — Malawi 5 6 14 10 8 7 4 3 4 8 6 5 4 2 Mali 17 26 73 51 39 31 12 13 19 54 38 29 23 9 Niger 16 13 33 23 18 14 7 13 10 26 18 14 11 5 Nigeria 5 6 16 9 7 5 3 7 8 22 13 9 7 5 Rwanda 8 8 28 17 13 9 3 6 6 20 12 9 7 2 Senegal 6 3 6 4 3 3 1 22 9 21 16 13 10 5 South Africa 3 1 4 2 2 1 0 3 1 4 2 2 1 0 Tanzania 7 12 25 18 14 11 8 5 8 18 13 10 8 5 Uganda 5 6 20 11 8 5 2 6 8 23 13 9 6 3 Zambia 3 3 9 6 4 3 2 4 4 11 7 5 4 2 Source: Briceño-Garmendia and Shkaratan 2010. 285 Note: kWh = kilowatt-hour; LRMC = long-run marginal cost; Q = quintile. — = data not available. a. Sample average. 286 Africa’s Power Infrastructure Table A5.12 Residential Tariff Schedules Border Fixed between first charge/ and second Range of month Number block range block prices Country Tariff type Yes/no of blocks (kWh) (cents/kWh) Benin IBT No 3 20 9.6–16.3 Botswana FR Yes 1 n.a. 5.9 Burkina Faso IBT Yes 3 50 18.4–20.8 Cameroon IBT No 3 50 8.6–12.0 Cape Verde IBT No 2 40 22.5–28.0 Chad IBT No 3 30 15.7–38.1 Congo, Dem. Rep. IBT No 11 100 3.98–8.52 Congo, Rep. FR Yes 1 n.a. 11.0 Côte d’Ivoire IBT Yes 2 40 6.9–14.2 Ethiopia IBT Yes 7 50 3.2–8.0 Ghana IBT Yes 3 300 7.6–15.3 Kenya IBT Yes 4 50 4.9–44.0 Lesotho FR No 1 n.a. 7.2 Madagascar FR Yes 1 n.a. 7.6 Malawia IBT/FR Yes/no 3/1 30 2.0–4.1/3.1 Mali IBT No 4 200 26.6–31.0 Mozambiquea IBT/FR Yes/no 4/1 100 4.0–12.1/11.0 Namibia FR No 1 n.a. 11.7 Niger FR Yes 1 n.a. 13.6 Nigeria IBT Yes 5 20 0.9–6.5 Rwanda FR No 1 n.a. 14.6 Senegala IBT No 3 150 23.8–26.2 South Africa IBT No 2 50 0.0–7.2 Sudan — — — — — Tanzaniaa IBT/FR No/yes 2/1 50 4.1–13.0/10.8 Uganda IBT Yes 2 15 3.4–23.3 Zambia IBT Yes 3 300 1.6–3.7 Zimbabwe IBT No 3 50 0.6–13.5 Source: Briceño-Garmendia and Shkaratan 2010. Note: FR = fixed rate; IBT = increasing block tariff; kWh = kilowatt-hour; n.a. = not applicable; — = data not available. a. The country has two tariffs, equally applicable, for typical residential customers. Widening Connectivity and Reducing Inequality 287 Table A5.13 Social Tariff Schedules Price per Fixed charge block Country Type of tariff ($/month) Block border (cents/kWh) Benin Social tranche n.a. 9.6 Botswana n.a. n.a. n.a. Burkina Faso Block 1 0.18 14.3 Cameroona Block 1 residential 12.90 8.6 Cape Verde Block 1, residential — 22.5 Chad Block 1 residential n.a. 15.7 Congo, Dem. Rep. Social tariff 0.01 4.0 Congo, Rep. n.a. n.a. n.a. Côte d’Ivoire Block 1 residential 0.64 6.9 Ethiopia Block 1 residential 0.16 3.2 Ghana Block 1 residential 0.54 7.6 Kenya Block 1 residential 1.74 4.9 Lesotho — — — Madagascar Economic tariff 0.30 25 6.0 >25 27.6 Malawi Block 1 residential 0.92 2.0 Mali Social tariff n.a. 50 13.2 100 20.3 200 23.9 >200 27.7 Mozambique Block 1 residential n.a. 4.0 Namibia n.a. n.a. n.a. Niger — — — Nigeria Pensioners’ tariff 0.23 3.0 Rwanda — — — Senegal Tranche 1 residential n.a. 150 0.24 South Africa Block 1 residential n.a. — Sudan — — — Tanzania n.a. n.a. 3.0 Uganda Block 1 residential 1.09 3.4 Zambia Block 1 residential 1.31 1.6 Zimbabwe Tranche 1 residential n.a. 0.6 Source: Briceño-Garmendia and Shkaratan 2010. Note: kWh = kilowatt-hour; n.a. = not applicable; — = data not available. a. In Cameroon fixed residential charge is 2,500 per kW if subscribed load is up to 200 hours and 4,200 per kW if it is above 200 hours. 288 Africa’s Power Infrastructure Table A5.14 Industrial Tariff Schedules Fixed Demand Range of charge/month charge Number of block prices Country Tariff type Yes/no Yes/no blocks (cents/kWh) Benin FR No No 1 15.1 Botswana FR No No 1 6.7 Burkina Faso TOU Yes Yes 2 31.6–16.8 Cameroon DBT No Yes 2 11.3–9.9 Cape Verde FR No No 1 21.8 Chad IBT No Yes 3 15.9–40.0 Congo, Dem. Rep. DBT No No 5 11.1–10.7 Congo, Rep. FR Yes No 1 9.7 Côte d’Ivoire DBT Yes No 2 18.6–15.9 Ethiopia TOU Yes No 3 6.7–6.3 Ghana IBT Yes No 3 11.1–16.0 Kenya FR Yes No 1 21.4 Lesotho FR No Yes 1 1.2 Madagascar FR Yes Yes 1 16.9 Malawi FR Yes Yes 1 3.0 Mali FR No No 1 23.2 Mozambique FR Yes Yes 1 5.4 Namibia FR Yes Yes 1 8.4 Niger FR Yes Yes 1 12.2 Nigeria IBT Yes No 4 5.0–6.5 Rwanda FR No No 1 17.2 Senegal TOU Yes No 2 14.4–20.8 South Africa IBT/FR Yes No 3/1 4.0–9.5 Tanzania FR Yes Yes 1 5.3 Uganda TOU Yes No 1 21.8 Zambia FR Yes No 1 3.7 Source: Briceño-Garmendia and Shkaratan 2010. Note: DBT = decreasing block tariff; FR = fixed rate; IBT = increasing block tariff; TOU = time of use; kWh = kilowatt-hour. Widening Connectivity and Reducing Inequality 289 Table A5.15 Commercial Tariff Schedules Fixed Demand Range of charge/month charge Number of block prices Country Tariff type Yes/no Yes/no blocks (cents/kWh) Benin FR No No 1 10.7 Botswana FR Yes Yes 1 3.1 Burkina Faso TOU Yes Yes 2 22.6–10.3 Cameroon TOU No Yes 2 8.7–8.5 Cape Verde FR No No 1 17.7 Chad TOU No Yes 3 20.5–37.9 Congo, Dem. Rep. DBT No No 5 15.2–14.6 Congo, Rep. FR Yes Yes 1 11.2 Côte d’Ivoire TOU Yes No 3 10.7–8.8 Ethiopia TOU Yes No 3 4.7–5.9 Ghana FR Yes Yes 1 5.4 Kenya DBT Yes Yes 3 16.4–14.0 Lesotho FR No Yes 1 1.1 Madagascar FR Yes Yes 1 9.9 Malawi FR Yes Yes 1 2.4 Mali — — — — 16.9 Mozambique FR Yes Yes 1 4.5 Namibia FR Yes Yes 1 12.4 Niger FR Yes Yes 1 8.8 Nigeria IBT Yes Yes 5 5.0–6.5 Rwanda FR No No 1 17.2 Senegal TOU Yes No 2 13.0–18.7 South Africa TOU Yes Yes 2 2.6–1.8 Tanzania FR Yes Yes 1 4.9 Uganda TOU Yes Yes 1 16.7 Zambia DBT Yes Yes 4 2.2–1.2 Source: Briceño-Garmendia and Shkaratan 2010. Note: DBT = decreasing block tariff; FR = fixed rate; IBT = increasing block tariff; TOU = time of use; kWh = kilowatt-hour. — = data not available. 290 Africa’s Power Infrastructure Table A5.16 Value and Volume of Sales to Residential Customers as Percentage of Total Sales Country Value of sales (%) Volume of sales (%) Benin — 96 Burkina Faso 63 63 Cameroon 60 33 Cape Verde 56 56 Chad 67 63 Congo, Dem. Rep. 47 70 Côte d’Ivoire 47 — Ethiopia 27 56 Ghana 35 71 Kenya 42 39 Lesotho — 30 Madagascar — 61 Malawi — 36 Mozambique 70 59 Namibia 36 47 Niger 59 — Nigeria 39 51 Rwanda 50 — Senegal 63 59 South Africa 17 51 Tanzania 48 44 Uganda — 36 Source: Briceño-Garmendia and Shkaratan 2010. Note: — = data not available. APPENDIX 6 Recommitting to the Reform of State-Owned Enterprises 291 292 Table A6.1 Electricity Sector Tariffs and Costs cents/kWh Effective tariffs Costs Industrial at Historical Residential at Commercial at demand level operating Historical Average 100 kWh/month 900 kWh/month of 100 kVA costs total costs revenue LRMC Benin 13.6 15.1 10.7 11.6 19.8 14.2 19.0 Botswana 7.5 7.2 4.0 11.9 13.9 18.4 6.0 Burkina Faso 20.0 26.7 15.0 4.4 15.1 19.7 25.0 Cameroon 10.9 11.4 9.2 12.7 17.1 10.9 7.0 Cape Verde 25.8 21.8 17.7 14.3 17.9 18.0 — Chad 30.0 44.7 38.8 9.4 13.7 32.1 7.0 Congo, Dem. Rep. 4.0 11.0 14.6 3.9 6.8 4.3 4.0 Congo, Rep. 16.0 10.7 11.2 13.4 20.1 12.8 6.0 Côte d’Ivoire 11.9 16.9 10.7 6.6 10.9 1.0 15.0 Ethiopia 4.1 8.3 4.7 2.1 8.5 6.0 19.0 Ghana 8.2 13.9 6.4 7.5 12.4 8.0 10.0 Kenya 14.8 21.7 15.1 8.4 14.2 14.0 12.0 Lesotho 7.2 9.3 3.3 6.4 10.8 7.1 6.0 Madagascar 3.0 25.3 10.5 10.5 15.0 45.9 Malawi 4.0 6.9 3.1 5.9 9.1 3.2 5.0 Mali 26.6 23.2 — 16.3 33.6 18.6 25.0 Mozambique 6.8 8.0 5.1 6.3 9.0 7.6 4.0 Namibia 11.7 14.0 13.6 7.3 11.3 12.4 11.0 Niger 14.1 13.2 9.3 23.4 32.1 15.5 25.0 Nigeria 3.4 5.0 5.1 2.2 9.7 2.8 13.0 Rwanda 14.6 17.2 17.2 6.8 16.6 22.2 12.0 Senegal 23.8 22.8 15.8 19.4 25.0 14.9 43.0 South Africa 3.6 7.7 2.7 3.4 6.0 16.0 6.0 Tanzania 6.7 8.0 5.4 8.0 14.1 7.5 10.0 Uganda 21.4 21.9 17.0 5.3 10.4 8.7 12.0 Zambia 2.9 4.4 2.5 3.6 6.5 5.0 8.0 Source: Briceño-Garmendia and Shkaratan 2010. Note: kVA = kilovolt-ampere; kWh = kilowatt-hour; LRMC = long-run marginal cost. Effective tariffs are prices per kWh at typical monthly consumption levels calculated using tariff schedules that are applicable to typical customers within each customer group. — = data not available. 293 Table A6.2 Residential Effective Tariffs at Different Consumption Level cents/kWh 294 50 kWh 75 kWh 100 kWh 150 kWh 200 kWh 300 kWh 400 kWh 450 kWh 500 kWh 900 kWh Benin 12.6 13.3 13.6 14.0 14.1 19.7 22.5 23.5 24.2 27.2 Botswana 9.1 8.0 7.5 6.9 6.7 6.4 6.3 6.2 6.2 6.0 Burkina Faso 20.6 20.2 20.0 19.9 19.8 20.1 20.3 20.4 20.4 20.6 Cameroon 8.6 10.9 10.9 10.9 10.9 12.0 12.0 12.0 12.0 12.0 Cape Verde 23.6 25.1 25.8 26.5 26.9 27.3 27.4 27.5 27.5 27.7 Chad 22.9 27.3 30.0 32.7 34.1 35.4 36.1 36.3 36.5 37.2 Congo, Dem. Rep. 4.0 4.0 4.0 4.0 4.0 3.9 3.9 3.9 3.9 5.5 Congo, Rep. 21.1 17.7 16.0 14.3 13.5 12.6 12.2 12.1 12.0 11.5 Côte d’Ivoire 9.6 11.1 11.9 12.6 13.0 13.4 13.6 13.6 13.7 13.9 Ethiopia 3.9 4.1 4.1 5.3 5.6 6.1 6.2 6.4 6.6 7.2 Ghana 8.7 8.4 8.2 8.0 7.9 7.8 9.1 9.6 9.9 11.8 Kenya 8.4 12.7 14.8 16.9 18.0 19.1 19.9 20.1 20.4 21.2 Lesotho 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 7.2 Madagascar 6.0 4.0 3.0 2.0 1.5 1.0 0.7 0.7 0.6 0.3 Malawi 4.8 4.3 4.0 3.8 3.7 3.6 3.5 3.5 3.5 3.4 Mali 26.6 26.6 26.6 26.6 26.6 28.1 28.8 29.1 29.3 30.0 Mozambique 9.6 7.7 6.8 7.4 7.7 9.0 9.6 9.8 10.0 10.9 Namibia 11.7 11.7 11.7 11.7 11.7 11.7 11.7 11.7 11.7 11.7 Niger 14.5 14.2 14.1 13.9 13.9 13.8 13.7 13.7 13.7 13.7 Nigeria 2.5 3.8 3.4 3.8 4.2 4.9 5.3 5.4 5.6 6.0 Rwanda 14.6 14.6 14.6 14.6 14.6 14.6 14.6 14.6 14.6 14.6 Senegal 23.8 23.8 23.8 23.8 24.2 24.8 25.1 25.2 25.3 25.7 South Africa 0.0 2.4 3.6 4.8 5.4 6.0 6.3 6.4 6.5 6.8 Tanzania 3.2 5.5 6.7 7.9 8.5 9.0 8.8 8.8 8.8 8.6 Uganda 19.5 20.7 21.4 22.0 22.3 22.6 22.8 22.8 22.9 23.1 Zambia 4.2 3.3 2.9 2.4 2.2 2.0 2.1 2.1 2.1 2.5 Zimbabwe 0.6 3.0 4.3 5.5 6.1 6.7 7.0 7.1 7.2 10.0 Source: Briceño-Garmendia and Shkaratan 2010. Note: kWh = kilowatt-hour. See note to table A6.1 regarding effective tariffs. Recommitting to the Reform of State-Owned Enterprises 295 Table A6.3 Electricity Sector Efficiency Cost recovery Collection (%, ratio of ratio residential Residential System Connections (implicit, effective tariff effective losses per sector revenue to to total tariff/LRMC (% production) employee tariff) historical cost) (%) Benin 18 148 100 69 72 Botswana 10 62 54 125 Burkina Faso 25 179 88 133 80 Cameroon 31 180 106 64 156 Cape Verde 17 112 77 144 Chad 33 43 91 220 429 Congo, Dem. Rep. 40 — 107 59 100 Congo, Rep. 47 — 83 80 267 Côte d’Ivoire — 57 7 109 79 Ethiopia 22 84 108 48 22 Ghana 25 146 90 66 82 Kenya 18 227 85 104 123 Lesotho 20 95 108 67 121 Madagascar 24 — 397 20 — Malawi 23 — 79 44 81 Mali 22 — 72 79 106 Mozambique 25 99 102 75 169 Namibia 15 38 107 103 106 Niger 27 118 110 44 56 Nigeria 30 127 67 35 26 Rwanda 23 189 152 88 121 Senegal 21 257 66 95 55 South Africa 10 132 277 60 60 Tanzania 26 124 117 48 67 Uganda 36 444 76 206 178 Zambia 12 — 173 44 36 Source: Eberhard and others 2008. Note: LRMC = long-run marginal cost. — = data not available. 296 Table A6.4 Hidden Costs of Power Utilities as a Percentage of GDP and Utility Revenue Percent Percent of revenues Percent of GDP T&D Undercollection T&D Undercollection losses Underpricing of bills Overstaffing losses Underpricing of bills Overstaffing Benin 12.8 39.1 0.5 13.8 0.2 0.7 0.0 0.2 Botswana 0.7 138.7 61.1 — 0.0 1.8 0.8 — Burkina Faso 12.5 0.0 14.7 9.5 0.2 0.0 0.3 0.2 Cameroon 36.3 57.9 0.0 8.3 0.8 1.2 0.0 0.2 Cape Verde 8.1 0.0 29.6 20.8 0.2 0.0 0.9 0.6 Chad 11.0 0.0 9.1 23.6 0.0 0.0 0.0 0.1 Congo, Dem. Rep. 163.6 201.6 0.0 — 1.3 1.6 0.0 — Congo, Rep. 63.1 30.9 21.0 30.9 0.6 0.3 0.2 0.3 Côte d’Ivoire — 0.0 417.1 24.2 0.0 4.4 0.3 Ethiopia 18.6 33.5 6.3 — 0.2 0.3 0.1 — Ghana 26.5 52.4 2.1 — 0.7 1.5 0.1 — Kenya 9.1 0.0 34.6 5.1 0.3 0.0 1.1 0.2 Lesotho 16.9 32.5 19.5 — 0.3 0.6 0.3 — Madagascar 5.0 2.3 0.0 — 0.3 0.2 0.0 — Malawi 40.5 105.3 75.1 — 0.5 1.3 0.9 — Mali 23.4 36.8 39.1 6.4 0.6 1.0 1.0 0.2 Mozambique 19.9 15.0 4.6 17.7 0.3 0.2 0.1 0.3 Namibia 51.6 0.0 — — 0.1 0.0 — — Niger 39.1 116.5 0.0 12.5 0.6 1.8 0.0 0.2 Nigeria 76.8 195.1 50.3 — 0.4 1.0 0.3 — Rwanda 10.8 9.3 0.0 6.8 0.2 0.1 0.0 0.1 Senegal 9.6 0.0 10.8 5.4 0.3 0.0 0.3 0.2 South Africa 0.0 5.9 0.0 — 0.0 1.0 0.0 — Tanzania 33.5 90.9 0.0 6.1 0.5 1.3 0.0 0.1 Uganda 34.6 0.0 39.4 5.2 0.6 0.0 0.7 0.1 Zambia 2.9 72.9 2.3 — 0.0 1.2 0.0 — Source: Eberhard and others 2008. Note: Unaccounted losses = end-user consumption x average cost recovery price x (total loss rate – normative loss rate) / (1 – normative loss rate). Underpricing = end-user con- sumption x (average cost recovery price – average actual tariff ). Collection inefficiencies = end-user consumption x average actual tariff x (1 – collection rate). GDP = gross domestic product; T&D = transmission and distribution. — = data not available. 297 APPENDIX 7 Closing Africa’s Power Funding Gap 299 300 Table A7.1 Existing Spending on the Power Sectora GDP share (%) Current US$, million p.a. O&M Capital expenditure O&M Capital expenditure Non- Non- Public Public OECD Total Total Public Public OECD Total Total Country sector sector ODA financiers PPI CAPEX spending sector sector ODA financiers PPI CAPEX spending Benin 1.65 0.68 0.31 0.01 0.00 1.01 2.66 71 29 13 1 0 43 114 Botswana 0.97 0.33 0.01 0.00 0.00 0.33 1.30 101 35 1 0 0 35 137 Burkina Faso 0.96 0.19 0.61 0.01 0.00 0.81 1.76 52 10 33 1 0 44 96 Cameroon 1.04 0.05 0.09 0.01 0.36 0.51 1.55 173 8 15 2 60 84 258 Cape Verde 3.24 2.30 0.01 0.06 0.00 2.37 5.62 33 23 0 1 0 24 56 Chad 0.61 0.02 0.23 0.02 0.00 0.28 0.90 36 1 14 1 0 17 53 Congo, Rep. 1.02 0.53 0.04 0.51 0.00 1.08 2.10 62 32 2 31 0 65 128 Côte d’Ivoire 2.13 — 0.00 0.00 0.00 — 2.13 348 — 0 1 0 — 348 Congo, Dem. Rep. 0.00 0.00 0.06 0.00 0.00 0.06 0.06 0 0 4 0 0 4 4 Ethiopia 3.39 0.15 1.31 0.17 0.00 1.63 5.02 417 19 161 20 0 200 618 Ghana 1.20 0.56 0.21 0.55 0.05 1.36 2.56 129 60 22 59 6 146 275 Kenya 2.17 0.58 0.40 0.00 0.07 1.05 3.22 406 110 74 0 13 197 603 Lesotho 1.45 0.09 0.00 0.00 0.00 0.10 1.54 21 1 0 0 0 1 22 Madagascar 2.04 0.15 0.13 0.08 0.00 0.36 2.40 103 8 6 4 0 18 121 Malawi 1.65 0.51 0.04 0.00 0.00 0.56 2.21 47 15 1 0 0 16 63 Mali 1.77 0.36 0.19 0.23 0.38 1.16 2.93 94 19 10 12 20 61 155 Mozambique 0.96 — 0.89 0.07 0.01 — 0.96 63 — 58 5 1 — 63 Namibia 0.96 0.95 0.01 0.00 0.00 0.96 1.92 60 59 1 0 0 60 120 Niger 0.90 0.34 0.01 0.41 0.00 0.77 1.67 30 11 0 14 0 25 56 Nigeria 0.61 0.64 0.03 0.28 0.19 1.13 1.74 685 716 35 309 209 1,269 1,954 Rwanda 0.89 0.00 0.64 0.05 0.01 0.70 1.59 21 0 15 1 0 17 38 Senegal 1.61 0.07 0.21 0.14 0.18 0.60 2.21 140 6 18 12 16 52 192 South Africa 0.97 0.26 0.00 0.00 0.00 0.27 1.23 2,345 631 8 0 5 644 2,989 Tanzania 1.84 0.11 0.28 0.00 0.31 0.70 2.53 260 16 40 0 44 99 358 Uganda 1.19 1.38 1.01 0.00 0.75 3.14 4.33 104 121 88 0 65 275 378 Zambia 1.76 0.93 0.04 0.12 0.00 1.10 2.86 129 69 3 9 0 81 210 Middle-income 0.98 0.29 0.01 0.00 0.00 0.30 1.28 2,654 777 33 1 5 816 3,470 Resource-rich 0.73 0.56 0.03 0.33 0.13 1.05 1.78 1,629 1,240 75 736 278 2,330 3,959 Low-income, nonfragile 1.78 0.39 0.50 0.12 0.15 1.15 2.94 1,969 430 549 129 165 1,272 3,241 Low-income, fragile 1.49 0.00 0.10 0.55 0.03 0.68 2.16 571 0 37 210 12 260 830 Sub-Saharan Africa 1.10 0.37 0.11 0.17 0.07 0.72 1.81 7,033 2,370 694 1,076 460 4,600 11,633 Source: Authors. Note: a. Average for 2001–05, except for Botswana, the Republic of Congo, and Mali, which are average for 2002–07. ODA = official development assistance; OECD = Organisation for Economic Co-operation and Development; PPI = private participation in infrastructure; CAPEX = capital expenditure. — = Not available. 301 302 Africa’s Power Infrastructure Table A7.2 Size and Composition of the Power Sector Funding Gapa current US$, million p.a. Total potential gain from Total Total achieved Funding needs spending efficiency gap Benin (178) 114 17 (47) Botswana (116) 137 55 Cameroon (745) 258 343 (145) Cape Verde (24) 56 19 Chad (39) 53 66 Congo, Rep. (482) 128 45 (310) Côte d’Ivoire (825) 348 668 Congo, Dem. Rep. (1,473) 4 335 (1,134) Ethiopia (3,380) 618 82 (2,681) Ghana (728) 275 317 (137) Kenya (1,019) 603 109 (306) Lesotho (26) 22 20 Madagascar (478) 121 19 (338) Malawi (57) 63 91 Mali (178) 155 9 (13) Mozambique (771) 63 74 (634) Namibia (285) 120 0 (166) Niger (76) 56 126 Nigeria (7,736) 1,954 1,526 (4,256) Rwanda (118) 38 48 (32) Senegal (993) 192 231 (570) South Africa (13,511) 2,989 5 (10,516) Tanzania (910) 358 348 (204) Uganda (601) 378 158 (64) Zambia (472) 210 160 (102) Middle-income (14,191) 3,470 906 (9,814) Resource-rich (11,770) 3,959 3,541 (4,269) Low-income, nonfragie (9,704) 3,241 1,818 (4,645) Low-income, fragile (5,201) 830 2,021 (2,350) Source: Authors. Note: a. Average for 2001–05, except for Botswana, the Republic of Congo, and Mali, which are average for 2002–07. Table A7.3 Sources of Potential Efficiency Gains, by Componenta Current US$, million p.a. GDP share (%) Increase Improve Address Reduce Raise Increase Improve Address Reduce Raise cost system under- over- budget cost system under- over- budget recovery losses collection manning execution Total recovery losses collection manning execution Total Benin 1 6 0 10 0 17 0.01 0.15 0.00 0.23 0.01 0.40 Botswana 20 2 3 30 0 55 0.19 0.02 0.03 0.28 0.00 0.52 Cameroon 205 105 0 30 3 343 1.23 0.64 0.00 0.18 0.02 2.07 Cape Verde 1 3 8 6 1 19 0.09 0.31 0.78 0.60 0.08 1.85 Chad 43 17 0 6 0 66 0.73 0.29 0.00 0.10 0.01 1.13 Congo, Rep. 0 20 7 17 0 45 0.00 0.33 0.12 0.28 0.00 0.73 Côte d’Ivoire — — 626 42 0 668 — — 3.83 0.26 0.00 4.09 Congo, Dem. Rep. 0 92 243 — 0 335 0.00 1.30 3.42 — 0.00 4.72 Ethiopia 42 24 15 — 0 82 0.34 0.20 0.13 — 0.00 0.66 Ghana 70 85 153 7 0 317 0.65 0.80 1.43 0.07 0.00 2.95 Kenya 8 54 0 31 15 109 0.05 0.29 0.00 0.17 0.08 0.58 Lesotho 15 5 0 — 0 20 1.05 0.32 0.03 — 0.01 1.41 Madagascar 0 19 0 — 0 19 0.00 0.37 0.00 — 0.00 0.37 Malawi 72 16 3 — 0 91 2.51 0.55 0.10 — 0.00 3.17 Mali — — — 9 0 9 — — — 0.17 0.00 0.17 303 (continued next page) 304 Table A7.3 (continued) Current US$, million p.a. GDP share (%) Increase Improve Address Reduce Raise Increase Improve Address Reduce Raise cost system under- over- budget cost system under- over- budget recovery losses collection manning execution Total recovery losses collection manning execution Total Mozambique 36 21 0 18 0 74 0.54 0.31 0.00 0.27 0.00 1.12 Namibia 0 0 — — 0 0 0.00 0.00 — — 0.00 0.00 Niger 64 27 28 6 0 126 1.93 0.82 0.84 0.19 0.00 3.78 Nigeria 672 359 344 — 151 1,526 0.60 0.32 0.31 — 0.13 1.36 Rwanda 37 9 0 2 0 48 1.55 0.36 0.00 0.10 0.00 2.01 Senegal 165 51 0 14 2 231 1.90 0.58 0.00 0.16 0.02 2.66 South Africa 0 5 0 — 1 5 0.00 0.00 0.00 — 0.00 0.00 Tanzania 260 75 0 12 1 348 1.84 0.53 0.00 0.08 0.01 2.46 Uganda 0 64 86 8 0 158 0.00 0.73 0.98 0.09 0.00 1.81 Zambia 152 6 0 — 2 160 2.07 0.08 0.00 — 0.02 2.17 MIC 38 14 12 840 2 906 0.01 0.01 0.00 0.31 0.00 0.33 Resource-Rich 1,609 761 528 410 234 3,541 0.72 0.34 0.24 0.18 0.11 1.59 LIC-NoFragile 826 504 308 160 20 1,818 0.75 0.46 0.28 0.15 0.02 1.65 LIC-Fragile 0 498 1,423 99 0 2,021 0.00 1.30 3.71 0.26 0.00 5.26 SSA 2,323 1,340 1,842 1,147 210 6,862 0.36 0.21 0.29 0.18 0.03 1.07 Source: Authors. Note: a. Average for 2001–05, except for Botswana, the Republic of Congo, and Mali, which are average for 2002–07. Index Boxes, figures, notes, and tables are indicated by b, f, n, and t following page numbers. A Angola oil reserves, 2 Abuja Treaty, 41 political consensus, 42b access rates power generation capacity, 1 national, 67, 70, 73–74, 77 power imports, 31 regional, 66–67, 70, 73, 76–77 power trade benefits, 38 Africa–European Union Energy prices of electricity, 12 Partnership, 47 transmission projects, 170 Africa Infrastructure Country Diagnostic annualized capital investment costs (AICD) study in CAPP, 76, 77 investment model, 54 defined, 61b power outages and, 7, 9 in EAPP/Nile Basin, 68–69 power sector reform and, 80, 81f, 94 in SAPP, 66, 67 REAs and, 105 targets for, 70, 226–37t SOEs and, 133 under trade expansion, 59 tariffs for electricity, 118–19 in WAPP, 73–74 African Development Bank, 47, 48, 169 Arab countries, infrastructure African Development Fund, 48, 49 financing from, 170, 179 African Economic Community, 41 Asea Brown Boveri, 84b African Union (AU), 41, 42b, 43–44, 47 AU. See African Union Agence Malienne pour le Developpement Azito power plant de l’Energie Domestique et (Côte d’Ivoire), 82, 84b d’Electrification Rurale (AMADER), 127b B AICD study. See Africa Infrastructure Country Diagnostic backup generators, 7–10, 9f, 12, 13f aluminum smelters, 28, 48, 50n bank lending, 173–75, 176t 305 306 Index Benin Cameroon corporate bonds, 178 aluminum-smelting industry, 159 gas-fired power plants, 33 in CAPP, 54 as nonfragile low-income country, 152b concession contracts, 96 power imports, 28 cost recovery, 160 rural electrification, 125 electricity connections, 105 Besant-Jones, J. E., 81 funding gap, 165 BHP Billiton, 42b grid-related costs, 76 blackouts. See power outages hydropower potential, 1 bonds. See corporate bonds market demand, 74–75 Botswana oil reserves, 2 coal power, 5 as power exporter, 30, 33 financing instruments for, 49 power trade benefits for, 38 political consensus, 42b PPI projects, 85 power imports, 28 as resource-rich country, 152b SOEs in, 139b subsidies and tariffs, 15, 117 Botswana Power Corporation (BPC), 139b Cape Verde bottom-up approaches cost recovery, 158 to electrification, 127b costs study, 54 to SOE performance reform, 147 as middle-income country, 152b budgets power sector spending, 153 electricity expenditures in, 272–79t PPI projects, 85 funding gap and, 160–61, 160–61t tariff structures, 116b management of, 150, 160–61 capital costs, 178–79, 179f monthly household, 112–13, 112t, capital markets, local, 171–73 113f, 114 carbon dioxide emissions, 6, 23, 182 off-budget spending of SOEs, 160 CDM (Clean Development Burkina Faso Mechanism), 39–40 corporate bonds, 178 Central African Power Pool (CAPP) cost recovery, 158 costs in, 54, 59, 76, 77 electricity, affordability of, 114 generation capacity, power, 39, 58, power generation capacity, 3 74, 74t, 76–77 power imports, 28 household utility connections in, 76–77 rural electrification, 109, 125 investment requirements and, 53, tariff structures, 116b 74–77, 74t thermal power, 30 membership of, 77n2 Burundi trade expansion scenario, 29, 33, 38 diesel power, 12 transmission and distribution in, 76, 77 hydropower potential, 2 Central African Republic investment requirements, 61 market demand, 74 power expansion costs, 69 power imports and, 33 power imports, 28, 32 war in, 12 power outages, 7 central nonexclusive buyer models power trade benefits for, 38 for utilities, 94 business-as-usual approaches to service certified emission reduction credits coverage, 103, 119 (CERs), 39–40 Chad cost recovery, 158 C electricity connections, 105 Cahora Bassa hydroelectric plant oil reserves, 2 (Mozambique), 50n1 power generation capacity, 76 Calderón, Cesar, 16 power imports, 33, 75 Index 307 power trade benefits for, 38 power generation capacity, 76 rural electrification, 125 power imports, 28, 33 thermal power, 30 connectivity to electricity. See also charcoal use, 112, 127b, 278–79t household utility connections; China, infrastructure financing from, inequality in electricity access 170, 179 policy challenges, 119–29 CIE (Compagnie Ivoirienne affordability problems, 121–22 d’Electricité), 84b demand-side factors, 103, Cinergy, 84b 119, 120–21 CIPREL (Compagnie Ivoirienne de periurban and rural electrification, Production d’Electricité), 84b 125–29, 126f Clean Development Mechanism subsidies for service (CDM), 39–40 expansion, 122–25 climate change, 6, 40 progress in, 105–10 coal power plants, 3, 5, 65, 66, 71 rates of, 104–5, 104f, 107f, 268–71t Coastal Transmission Backbone, 45b constant access scenarios, 55, 64–69 commercial bank lending, consumption of electricity, 113–14, 173–75, 176t 115f, 190–91t Commercial Reorientation of the inequality in electricity access, 6, 6f Electricity Sector Toolkit contracts and agreements. See specific (CREST), 147 types (e.g., private management Commission for Africa Report, 169 contracts) Communauté Electrique de Benin, 178 corporate bonds, 171, 173, 177–78, 178t Compagnie Ivoirienne cost estimates. See also annualized capital d’Electricité (CIE), 84b investment costs; hidden costs of Compagnie Ivoirienne de Production SOEs; investment requirements; d’Electricité (CIPREL), 84b overnight investment costs concession contracts, 96 market demand in, 54–55, 56t, 67, conflicts, power infrastructure 74–75 damage by, 12, 16 notional demand in, 55, 77n3 Congo, Democratic Republic of in power sector overall, 54, backup generators, 7 58–64, 60t, 63f CDM and, 39 social demand in, 55, 56t economic growth, 16 suppressed demand in, 55, 215–17t electricity, affordability of, 114 cost recovery as fragile low-income country, 152b funding gaps and, 158–60, funding gap, 164–65 159f, 183, 285t as hydropower exporter, 23, 28, inefficiencies of, 164 30, 31, 75 power prices and, 12–15 investment requirements, 61 Côte d’Ivoire oil reserves, 2 concession contracts, 96 political consensus, 42b cost recovery, 158 power generation capacity, 1–2, 3, economic growth, 16 24, 65, 66 efficiency savings, 163 power sector spending, 153 electricity connections, 105 power trade benefits for, 38 as fragile low-income country, 152b tariff structures, 116b independent power projects, 81–82, 84b war in, 12 oil reserves, 2 Congo, Republic of power exports, 28, 38 in CAPP, 54 power generation capacity, 3, 71 investment requirements, 64 power imports, 72 market demand, 74–75 PPI projects, 85 308 Index Côte d’Ivoire (continued) economic development, power rural electrification, 109 infrastructure constraints on, tariff structures, 116b 16–18, 17–18f country typologies, 152, 152–53b. Egypt, Arab Republic of See also specific country types, in EAPP/Nile Basin, 54 (e.g., fragile low-income countries) gas-fired power capacity, 31 coverage gaps for urban electricity supply, investment requirements, 61 110–11, 111t. See also funding gaps power expansion costs, 69 CREST (Commercial Reorientation of the power import, 32, 67 Electricity Sector Toolkit), 147 Electricidade de Moçambique cross-border finance, 41, 47–49 (EDM), 128b cross-border transmission Electricité de France (EDF), 84b investments, 23, 24 electricity customer-owned enterprises, 146 access rates. See access rates capacity. See generation capacity D characteristics of national power systems, 188–89t decreasing block tariffs (DBTs), 116b connectivity. See connectivity demand-side barriers to connectivity, 103, to electricity 119, 120–21 consumption rates. See consumption Democratic Republic of Congo. See Congo, of electricity Democratic Republic of emergency. See emergency power densification programs, 120 household. See household utility development assistance. See official connections development assistance (ODA) outages. See power outages Development Bank of policy challenges, 119–29 Southern Africa, 46b, 48 reform and planning. See power sector diesel power, 12 reform and planning Djibouti, costs of power expansion in, 69 regional trade in. See regional domestic finance sources, 166–68, power trade 167t, 183 rural. See rural areas droughts, 12, 16 subsidies for. See subsidies supply needs estimations. See E estimations of supply needs East African/Nile Basin Power Pool tariffs. See tariffs (EAPP/Nile Basin) unreliability of, 7 climate change and, 40 Electricity Company of Ghana, 106b constant access scenario, 67–69 Electricity Regulatory Board (Kenya), 83b costs in, 54, 59, 68–69 Electric Power Act of 1997 (Kenya), 83b generation capacity, power, 31, emergency power, 1, 10–12, 39, 58, 67–68, 68t 11t, 19n1, 19n6, 193t household utility connections in, 70 Energy Protocol, 49 investment requirements and, 53, 61, Energy Regulatory Commission 67–70, 68t (Kenya), 83b membership of, 77n2 Equatorial Guinea trade expansion scenario, 29, 38 backup generators, 7 transmission and distribution in, oil reserves, 2 68–69, 70 power generation capacity, 76 Eberhard, Anton, 82 power imports, 33, 75 Ecobank, 175 power sector needs, 149 Economic Community of West African equity financing, 175–77, 177t States (ECOWAS), 49–50 Escribano, Alvaro, 16 Index 309 Eskom, 90b, 109, 110, 142–43b, 177–78 power sector spending, 151–57, 151t, Eskom Conversion Act 154–56t, 158f, 300–301t (South Africa), 142b private investors, 166, 170–71, 172f, 183 estimations of supply needs, 55–58, reforms and, 162–64, 162t, 163f, 303–4t 214–15t, 223–24t regional integration, 181–82 Ethiopia size of, 149, 302t electricity, affordability of, 114 time horizon extension, 180–81, 181f electricity connections, 110 utility performance and, 161–62 Ethiopia-Sudan interconnector, 49 funding gap, 164 G investment requirements, 61 as nonfragile low-income country, 152b G-8 Gleneagles Summit, 169 power expansion costs, 69 Gabon as power exporter, 23, 30, 31–32 concession contracts, 96 power generation capacity, 1, 24, 68 market demand, 74–75 power trade benefits for, 38 oil reserves, 2 tariff structures, 116b outsourcing, 97 European Commission, 169 power generation capacity, 1 European Union–Africa Infrastructure power imports, 33 Trust Fund, 48 PPI projects, 85 private management contracts, 85–86 subsidies for electricity, 117 F The Gambia fragile low-income countries fuel costs in, 73 defined, 152b private management contracts, 85 domestic finance in, 167 generation capacity funding gap in, 164, 180 of CAPP, 39, 58, 74, 74t, 76–77 ODA in, 155 cost of, 66, 196–97t SOEs in, 150 of EAPP/Nile Basin, 31, 39, spending needs of, 149–50, 58, 67–68, 68t 152, 153, 180 installation lag in, 3–4f, 193–94t France, ODA from, 169 of SAPP, 31, 39, 58, 64–65, 64t, 67 funding gaps, 149–85, 299–304 scenarios for, 57–58, 57t, 224–25t additional financing of WAPP, 39, 58, 70, 71t, 74 sources, 166–78, 174t Ghana annual gap, 164–66, 164t, 165f aluminum-smelting industry, 159 bank lending, 173–75, 176t bank lending, 173 budget spending and, 160–61, 160–61t diesel power, 12 capital, costs of, 178–79, 179f efficiency savings, 163 capital markets, local, 171–73 electricity connections, 105, 106b corporate bonds, 171, 173, funding gap, 165 177–78, 178t gas-fired power plants, 33 cost recovery, 158–60, 159f, 183, 285t non-OECD financing, 155 domestic finance, 166–68, 167t, 183 oil reserves, 19n2 equity financing, 175–77, 177t power exports, 28 existing resources, 157–58 power generation capacity, 2, 3, 70–71 future considerations, 182–83 power imports, 38, 72 increasing of funding, 180 power sector spending, 155 non-OECD financiers, 166, prepayment electricity meters, 122 170, 179, 183 rural electrification, 109, 125 official development assistance (ODA), tariff structures, 15, 116b 166, 168–69, 179, 183 unbundling of utilities, 101n2 310 Index governance of SOEs, 136–37, 140–41f, independent power projects (IPPs) 142–43b, 142t, 147 CIPREL and, 84b Gratwick, K. N., 82 hybrid markets and, 91–92, 94 greenfield projects, 171, 259–60t KenGen and, 83b Group of Eight Gleneagles Summit, 169 performance indicators for, 88 Guasch, J. Luis, 16 private management contracts and, 87 Guinea sector reform and, 81–82, 90–91b CREST, use of, 147 SOEs and, 79–80 electricity connections, 110 India investment requirements, 61 corporate practices, 147 as power exporter, 23, 30, 33, 38, 73 infrastructure financing from, 170, 179 power generation capacity, 70–71 inefficiencies of SOEs, 135–36, power trade benefits for, 38 135–36f, 147 subsidies for electricity, 117 inequality in electricity access, 110–31. See Guinea-Bissau also connectivity to electricity electricity, affordability of, 114 affordability issues, 111f, 112–19, 290t power trade benefits for, 38 consumption rates, 6, 6f thermal power, 30 electrification rates, 5–6, 5f policy challenges, 119–31 H information and communication technology (ICT) sector, 149, 151 heavy fuel oil (HFO)–fired thermal Infrastructure Consortium for Africa, 169 capacity, 33, 71 Inga hydroelectric program, 42b hidden costs of SOEs, 133, institution strengthening, 43–44 134–36, 137f, 138b, International Development Association 292–94t, 296–97t (IDA), 48, 49, 84b, 169, 179 household utility connections. See also International Energy Agency, 39 connectivity to electricity International Finance Corporation, 84b in CAPP, 76–77 Investment Climate Assessments in EAPP/Nile Basin, 70 (ICAs), 7, 16 in SAPP, 66 investment requirements, 53–78, 213–37. scarcity of, 1 See also cost estimates targets for, 58, 59t CAPP and, 53, 74–77, 74t in WAPP, 72, 73–74 national access targets, 77 hybrid markets regional access targets, 76–77 independent power projects trade expansion, access and, 91–92, 94 rates under, 74–76 in sector reform, 88–95, 93t cost requirements, overall, 54, SOEs and, 91 58–64, 60t, 63f hydropower development, 1, 2, 23, 33, cross-border transmission, 23, 24 38–39, 42b, 50n1 EAPP/Nile Basin and, 53, 61, 67–70, 68t national access targets, 70 I regional access targets, 70 ICAs (Investment Climate trade expansion, access Assessments), 7, 16 rates under, 67–69 ICT sector (information and investment needs modeling, 54–55, communication 218–22t technology), 149, 151 SAPP and, 53, 61, 64–67, 65t IDA. See International Development national access targets, 67 Association regional access targets, 66–67 increasing block tariffs (IBTs), trade expansion, access rates 116b, 119, 124 under, 64–66 Index 311 supply needs estimations, 55–58, Liberia 214–15t, 223–24t investment requirements, 61 WAPP and, 53, 61, 70–74, 71t power trade benefits for, 38 national access targets, 73–74 thermal power, 30 regional access targets, 73 war in, 12 trade expansion, access “Lighting Africa” initiative, 129 rates under, 70–73 load shedding data, 7, 19n5 IPPs. See independent power projects local capital markets, 171–73 IPTL (utility company), 91 long-run marginal costs (LRMCs). See marginal costs in regional J power trade loss-of-load probabilities, 101n4 Japan, ODA from, 169 low-income countries. See fragile low-income countries K Lunsemfwa Hydro Power, 178 Kenya Lusaka Stock Exchange, 178 corporate bonds, 178 cost recovery, 158 M diesel power, 12 funding gap, 165 Madagascar geothermal plants, 2 costs study, 54 hidden costs in power sector, 138b diesel power, 12 independent power funding gap, 164–65 projects, 81–82, 83b power generation capacity, 1 local capital markets, 166 power sector spending, 153 power generation capacity, 3, 68 private management contracts, 85 power imports, 32 rural electrification, 125 private sector participation, 83b Malawi tariff structures, 116b CDM and, 39 unbundling of utilities, 83b, 100–101n2 cost recovery, 160 Kenya Electricity Generating Company electricity, affordability of, 114 (KenGen), 83b, 100n2, 177 power generation capacity, 2 Kenya Power and Lighting Company power imports, 31 (KPLC), 83b, 101n2, 135 power sector spending, 153 kerosene use, 112, 127b, 274–75t prepayment electricity meters, 122 Koeberg nuclear power station prices of electricity, 12 (South Africa), 2 tariff structures, 116b Kyoto protocol, 39 Mali concession contracts, 96 electricity, affordability of, 114 L power generation capacity, 3 Latin America PPI projects, 85 infrastructure spending, 168 private management power generation capacity, 2–3 contracts, 85–86 Lesotho rural electrification, 109, 127–28b bank lending, 173 Mali Folkecenter, 128b as middle-income country, 152b marginal costs in regional power power generation capacity, 2 trade, 29, 34, 36t, 38, power imports, 31 202–5t power sector spending, 153 market demand in cost prepayment electricity meters, 122 estimates, 54–55, 56t, rural electrification, 125 67, 74–75 312 Index Mauritania New Partnership for Africa’s Development backup generators, 7 (NEPAD), 41, 42b, 43 gas-fired power plants, 33 NGOs (nongovernmental power exports, 38 organizations), 128b Mauritius Niger coal power, 19n3 coal power, 19n3 costs study, 54 cost recovery, 160 independent power projects, 81 electricity, affordability of, 114 as regional leader, 16 non-OECD financing, 155 middle-income countries power imports, 28 defined, 152b power outages, 9 funding gap in, 164, 180 power trade benefits for, 38 spending needs of, 149, 152, 157, 160 rural electrification, 125 moral hazard problems, 144–45 thermal power, 30 Mostert, W., 109–10 uranium reserves, 2 Mozambique Nigeria Cahora Bassa hydroelectric plant, 50n1 bank lending, 175 coal power, 19n3 CREST, use of, 147 corporate bonds, 178 domestic finance, 166 electricity connections, 110 funding gap, 165 funding gap, 164–65 independent power projects, 81 investment requirements, 61 oil reserves, 2 as power exporter, 30, 31 power exports, 28 power generation capacity, 1–2, 65, 66 power generation capacity, 1–2, 3, power trade in, 27, 28 12, 70–71 rural electrification, 125 power sector reform, 81 tariff structures, 116b as resource-rich country, 152b thermal plants, 170 unbundling of utilities, 101n2 N in WAPP, 54 Namibia Niger River, 33 bank lending, 173 Nile basin, 33. See also East African/Nile CDM and, 40 Basin Power Pool coal power, 19n3 (EAPP/Nile Basin) corporate bond market, 177, 178 nonfragile low-income countries cost recovery, 158 defined, 152b political consensus, 42b domestic finance in, 167 power generation capacity, 66 funding gap in, 164 power imports, 28, 31 local capital markets in, 173 prepayment electricity meters, 122 ODA in, 155 private management contracts, 86 spending needs of, 49, 149, unbundling of utilities, 101n2 152–53, 180 uranium reserves, 2 nongovernmental organizations national access target scenario, 55, (NGOs), 128b 67, 70, 73–74, 77 non-OECD financiers, 166, 170, National Electrification Master Plan, 106b 179, 183 National Electrification Scheme nonpayment for infrastructure services, (NES), 106b 113, 114f, 122, 140 natural gas reserves, 2 NordPool, 90b natural resource savings accounts, 180 notional demand in cost Nellis, John, 101n3 estimates, 55, 77n3 network rollouts, 103, 119–20, 124 nuclear power plants, 2 Index 313 O power purchase agreements (PPAs), 48, 82, 94, 96 O&M. See operations and maintenance power sector reform and planning, Obasanjo, Olusegun, 43 79–102, 239–66 OECD. See Organisation for Economic hybrid markets and, 88–95, 93t Co-operation and Development performance indicators for, 87–88, off-budget spending of SOEs, 160 88f, 239–58t official development assistance (ODA) private management contracts and, as external funding source, 85–87, 88f, 261–66t 150, 152, 157 regulatory institutions, redesign of, funding gaps and, 166, 168–69, 179, 183 94–100, 95f in low-income countries, 155 contract regulation, 96–97 off-take agreements, 92 improvements in, 98 oil prices, 12, 16 independent regulation, 80, 95–96 oil reserves, 2 model for, 98–100, 99–100f one-third, two-thirds principle, 48 outsourcing and, 80, 97–98 open-cycle gas turbine generators, 65, 78n5 in Sub-Saharan Africa, 80–85, 82t operating costs for power PPI. See private participation in generation, 24–26, 26f infrastructure operations and maintenance (O&M), 149, PPIAF (Public-Private Infrastructure 150, 151, 152–53, 157, 183 Advisory Facility), 81 Organisation for Economic Co-operation PPPs (public-private partnerships), 47 and Development (OECD) prepayment metering, 122, 123f funding increase from, 151 principal-agent problems, 144–45 ODA and, 169 priority setting for regional power trade, performance indicators and, 87 41, 44–47, 46b tariffs and, 12 private investors as funding sources, 166, outages. See power outages 170–71, 172f, 183 outsourcing private management contracts, 85–87, government reforms and, 145 88f, 261–66t SOEs and, 134 private participation in infrastructure (PPI), overnight investment costs, 65t, 66, 68, 81–83, 85, 88, 151, 152, 157 69t, 72–73, 72t, 75–76, 75t Program for Infrastructure Development overstaffing in power utilities, 157, 162, 183 in Africa, 47 Promotion et Participation pour la P Cooperation Economique, 84b Peña, Jorge, 16 propane gas use, 112, 276–77t performance contracts, 144–45 Public-Private Infrastructure Advisory performance indicators for sector reform, Facility (PPIAF), 81 87–88, 88f, 239–58t public-private partnerships (PPPs), 47 periurban electrification, 125–29, 126f. See also urban areas R PJM (utility company), 90b planning. See power sector reform REAs (rural electrification agencies). See and planning rural areas political consensus, 40, 41–43, 42b reforms, efficiency-oriented, 162–64, 162t, power generation. See generation capacity 163f, 303–4t. See also power sector power outages, 7, 8f, 9, 10f, 55, reform and planning 56t, 192t, 195–96t REFs (rural electrification funds). See rural power pools, 23, 26–28, 44. See also areas specific pools (e.g., Southern regional access target scenario, 55, 66–67, African Power Pool) 70, 73, 76–77 314 Index Regional Electricity Regulators RERA (Regional Electricity Regulators Association (RERA), 28, 50 Association), 28, 50 Regional Electricity Regulatory Authority resource-rich countries of the Economic Community of defined, 152b West African States, 46b domestic finance in, 166 regional power trade, 23–51, 199–211 funding gap in, 164 benefits of, 28–31, 33–38, 50 local capital markets in, 173 Clean Development Mechanism spending needs of, 149, 152, (CDM), 39–40 153, 160, 180 climate change and, 40 Rosnes, Orvika, 28, 39, 40, 54, 55 distribution and economies of rural areas scale, 24–26, 25f CAPP, connection costs in, 77 environmental impacts of, 39 EAPP/Nile Basin, connection expansion scenario. See regional trade costs in, 68, 70 expansion scenario electrification of, 103, 105, 107, generation portfolios, 206–7t 108f, 109–10, 119, 125–29, hydropower development and, 126f, 280–81t 23, 33, 38–39 rural electrification agencies (REAs), infrastructure integration, 40–50, 105, 108f, 109, 126 208–11t rural electrification funds (REFs), 103, institutions, strengthening of, 43–44 105, 109, 119, 126 political consensus, 40, 41–43, 42b SAPP, connection costs in, 66 priority setting for, 41, 44–47, 46b WAPP, connection costs in, 72, 73, 74 project preparation and cross-border Rwanda finance, 41, 47–49 diesel power, 12 regulatory frameworks, 41, 49–50 funding gap, 165 marginal costs in, 29, 34, 36t, 38, 202–5t hybrid market, 91 patterns of, 31–33, 200–201t power generation capacity, 2, 3, 68 power pools and, 23, 26–28 power imports, 28 stagnation scenario. See regional trade prepayment electricity meters, 122 stagnation scenario rural electrification, 125 water resources management, 33 regional trade expansion scenario S access rates under, 64–76, 226–33t, 236–37t SADC. See Southern African benefits of, 29–33, 30f, 38 Development Community CDM and, 40 SAPP. See Southern African Power Pool costs of, 36–37t, 39, 57–59 SAUR Group, 84b cross-border power trading, 32, 34–35f Self-Help Electrification Programme environmental impacts of, 39 (SHEP), 106b power exporting countries, Senegal 30–31, 31–32t coal power plant, 71 regional trade stagnation scenario, 28–29, corporate bonds, 178 40, 58, 234–35t economic growth, 16 regulations and regulatory functions electricity, affordability of, 73, 114 by contract, 96–97 electricity connections, 105 institutional redesign, 80, 94–100, funding gap, 164–65 95f, 99–100f as nonfragile low-income country, 152b outsourcing and, 80, 97–98 power outages, 7 in regional power trade, 41, 49–50 rural electrification, 109, 125 for SOEs, 100 thermal power, 30 Republic of Congo. See Congo, Republic of Senegal River, 33 Index 315 SHEP (Self-Help Electrification investment requirements and, 53, 61, Programme), 106b 64–67, 65t Sierra Leone membership of, 47, 77n2 emergency power, 19n6 political consensus and, 42b overhead distribution network, 19n8 power trade in, 27 power exports, 38 priority setting in, 46b war in, 12 promotion efforts, 44 single-buyer models for utilities, 92, 94 short-term energy market in, 101n1 social demand in cost estimates, 55, 56t trade expansion scenario SOEs. See state-owned enterprises and, 29, 31, 38 solar photovoltaic panels, 105, 128b transmission and distribution in, 66, 67 Somalia, war in, 12 Spain, power generation capacity of, 2 South Africa “spot billing,” 147 aluminum-smelting industry, 159 state-owned enterprises (SOEs), bank lending, 173, 175 133–48, 291–97 corporate bond market, 177–78 competition in, 146 electricity connections, 105 dominance of, 89–90 electricity consumption, 6 effectiveness of, 137–47, 295t financing options, 49, 175 performance improvement tools, 147 funding gap, 165 political economy and, 145–46 independent power projects, 90–91b roles and responsibilities, 139–45 local capital markets, 166, 171, 173 fragile low-income countries and, 150 as middle-income country, 152b governance of, 136–37, 140–41f, open-cycle gas turbine generators, 78n5 142–43b, 142t, 147 political consensus, 42b hidden costs of, 133, 134–36, 137f, power generation capacity, 3, 7, 12, 66 138b, 292–94t, 296–97t power imports, 31 hybrid markets and, 91 power plants, 2, 5, 65, 66 independent power projects and, 79–80 power sector planning and reform, 81, inefficiencies in, 135–36, 135–36f, 147 89, 90–91b, 142–43b, 153 off-budget spending of, 160 power trade in, 27–28, 38, 50n regulation of, 100 prepayment electricity meters, 122 stock exchanges, 175, 177, 178 prices of electricity, 12 subsidies. See also tariffs rural electrification, 109, 110 connectivity and, 103 in SAPP, 54, 64 cost recovery and, 162 tariff structures, 15, 116b for electricity, 115, 117–18, 117–18f, unbundling of utilities, 101n2 119, 122–25, 124t, 283–84t uranium reserves, 2 transparency of, 145 Southern African Development subsistence consumption of power, Community (SADC), 42b, 46b, 50 113–14, 115f Southern African Power Pool (SAPP) Sudan BPC and, 139b Ethiopia-Sudan interconnector, 49 CDM and, 40 as fragile low-income country, 152b constant access scenario, 64–66, 67 oil reserves, 2 costs in, 54, 58–59, 66, 67 as power exporter, 30, 31–32 cross-border transmission power generation capacity, 68 investments in, 23 thermal plants, 170 generation capacity, power, 31, 39, 58, supply needs estimations, 55–58, 64–65, 64t, 67 214–15t, 223–24t household utility connections in, 66 suppressed demand in cost interconnectors, return on estimates, 55, 215–17t investment on, 31 Swaziland, power imports to, 28 316 Index T U T&D. See transmission and distribution UCLFs (unplanned capability loss Tanzania factors), 7, 19n4 coal power, 19n3 Uganda cost recovery, 160 bank lending, 173 diesel power, 12 corporate bonds, 178 electricity, affordability of, 114 cost recovery, 158 funding gap, 165 diesel power, 12 hybrid market, 91 electricity, affordability of, 114 independent power projects, 81 electricity connections, 105 natural gas reserves, 2 funding gap, 165 power generation capacity, 68 independent power projects, 81 power outages, 7, 9 as nonfragile low-income country, 152b private management contracts, 86, 87 oil reserves, 19n2 rural electrification, 125 power generation capacity, 2, 68 tariff structures, 116b power sector spending, 155 transmission projects, 170 PPI projects, 85 tariffs. See also subsidies regulation in, 97 costs recovery and, 157, 158–60, rural electrification, 109, 125 162–63 thermal power, 49 decreasing block tariffs (DBTs), 116b unbundling of utilities, 100n2 for electricity, 12, 15, 19n7, 115, unbundling of utilities, 80–81, 83b, 89, 116b, 118–19, 121–22, 90b, 100–101n2 292–94t undercollection of revenues, 150, increasing block tariffs (IBTs), 157, 162, 183 116b, 119, 124 underpricing of power, 150, 157 schedules for, 286–89t UNICEM power plant, 175 underpricing of power and, 150 United States, corporate practices in, 147 taxation University of Cape Town, 83b capital costs and, 178–79 unplanned capability loss factors domestic finance and, 167–68 (UCLFs), 7, 19n4 Togo urban areas gas-fired power plants, 33 CAPP, connection costs in, 76 power generation capacity, 3 connectivity in, 104–5, 107, 120, 121 power imports, 28 coverage gaps in, 110–11, 111t total factor productivity (TFP), 17–18f rural electrification rates and, 129, 282t trade. See regional power trade U.S. Agency for International transmission and distribution (T&D) Development, 45b in CAPP, 76, 77 utilities, state-owned. See state-owned in EAPP/Nile Basin, 68–69, 70 enterprises (SOEs) expansion of, 57 losses in, 94 V performance indicators and, 87 Vennemo, Haakon, 28, 39, 40, 54, 55 in SAPP, 66, 67 Volta River Authority, 106b in WAPP, 72, 73 transparency W electrification funds and, 110 priority setting and, 47 WAPP. See West African Power Pool of regulatory contracts, 97 wars, power infrastructure damage SOEs and, 134, 140, 145–46 by, 12, 16 Tsavo IPP (Kenya), 82, 83b water resources management, 33 Index 317 water supply and sanitation (WSS) ODA and, 169 sector, 151 regional projects, criteria for, 48 West Africa Gas Pipeline, 43 WAPP and, 45b West African Bank for Development, 84b WSS sector (water supply and West African Power Pool (WAPP) sanitation), 151 costs in, 54, 59, 73–74 generation capacity, power, 39, 58, Z 70, 71t, 74 household utility connections in, Zambezi River, 33 72, 73–74 Zambia investment requirements and, 53, 61, bank lending, 173 70–74, 71t CDM and, 40 membership of, 77n2 corporate bonds, 178 power trade in, 28 cost recovery, 160 as regional electricity regulator, 44, 45b funding gap, 165 regulatory framework for, 49 mining industry, 159 trade expansion scenario, 29, 32, 38 power generation capacity, 2, 3, 66 transmission and distribution in, power imports, 31 72, 73 prices of electricity, 12 Westcor, 42b as resource-rich country, 152b Western Power Corridor, 42b rural electrification, 125 wood as fuel, 112, 127b, 278–79t tariff structures, 15, 116b World Bank Zimbabwe capacity building of, 49 coal power, 5 Country Policy and Institutional investment requirements, 61 Performance Assessment, 152b political conflict, 12 on grid-supplied power, 7 power generation capacity, 3, 65, 66 Investment Climate Assessments power sector needs, 149 (ICA), 7, 16 prices of electricity, 12 ECO-AUDIT Environmental Benefits Statement The World Bank is committed to preserving Saved: endangered forests and natural resources. The • 9 trees Office of the Publisher has chosen to print • 3 million British Africa’s Power Infrastructure: Investment, thermal units of Integration, Efficiency on recycled paper with total energy 50 percent post-consumer waste, in accor- • 820 pounds of net dance with the recommended standards for greenhouse gases paper usage set by the Green Press Initiative, a (CO2 equivalent) nonprofit program supporting publishers in • 3,951 gallons of using fiber that is not sourced from endan- waste water gered forests. For more information, visit • 240 pounds of solid www.greenpressinitiative.org. waste Africa’s Power Infrastructure: Investment, Integration, Efficiency is based on the most extensive data collection exercise ever undertaken on infrastructure in Africa: the Africa Country Infrastructure Country Diagnostic (AICD). Data from this study have provided new insights on the extent of a power crisis in the region, characterized by insufficient capacity, low electricity connection rates, high costs, and poor reliability—and on what can be done about it. The continent faces an annual power sector financing gap of about $21 billion, with much of the existing spending channeled to maintain and operate high-cost power systems, leaving little for the huge investments needed to provide a long-term solution. Meanwhile, the power crisis is taking a heavy toll on economic growth and productivity. This book asserts that the current impediments to economic growth and development need to be tackled through policies and investment strategies that renew efforts to reform state-owned utilities, build on the lessons of private participation in infrastructure projects, retarget electrification strategies, expand regional power trade, and mobilize new funding resources. Further development of regional power trade would allow Africa to harness larger-scale and more cost-effective energy sources, reducing energy system costs by US$2 billion and carbon dioxide emissions by 70 million tons annually. But reaping the promise of regional trade depends on a handful of major exporting countries raising the large volumes of finance needed to develop generation capacity for export; it also requires a large number of importing countries to muster the requisite political will. With increased utility efficiency and regional power trade in play, power costs would fall and full cost recovery tariffs could become affordable in much of Africa. This will make util- ities more creditworthy and help sustain the flow of external finance to the sector, which is essential to close the huge financing gap. ISBN 978-0-8213-8455-8 SKU 18455