2 0 1 0 53880 Silent and lethal How quiet corruption undermines Africa's development efforts 2 0 1 0 Copyright © 2010 by the International Bank for Reconstruction and Development/The World Bank 1818 H Street, N.W. Washington, D.C. 20433, U.S.A. All rights reserved Manufactured in the United States of America First printing 2010 This volume is a product of the staff of the International Bank for Reconstruction and Development/The World Bank. The find- ings, 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. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. 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To order Africa Development Indicators 2010, The Little Data Book on Africa 2010, the Africa Development Indicators 2010­Multiple User CD-ROM, please visit www.worldbank.org/publications. To subscribe to Africa Development Indicators Online please visit http://publications.worldbank.org/ADI. For more information about Africa Development Indicators and its companion products, please visit www.worldbank.org/africa. You can email us at ADI@worldbank.org. Cover design: Communications Development Incorporated. Photo credits: front cover, Mark Evans/iStockphoto; back cover, Arne Hoel/World Bank. The map of Africa is provided by the Map Design Unit/World Bank. ISBN: 978-0-8213-8202-8 e-ISBN: 978-0-8213-8203-5 DOI: 10.1596/978-0-8213-8202-8 SKU: 18202 Contents Foreword vii Acknowledgments ix Executive summary xi Silent and lethal: How quiet corruption undermines Africa's development 1 Notes 23 References 25 Indicator tables 31 Users guide 33 Part I. Basic indicators and national and fiscal accounts 1. Basic indicators 1.1 Basic indicators 37 2. National and fiscal accounts 2.1 Gross domestic product, nominal 38 2.2 Gross domestic product, real 39 2.3 Gross domestic product growth 40 2.4 Gross domestic product per capita, real 41 2.5 Gross domestic product per capita growth 42 2.6 Gross national income, nominal 43 2.7 Gross national income, Atlas method 44 2.8 Gross national income per capita, Atlas method 45 2.9 Gross domestic product deflator (local currency series) 46 2.10 Gross domestic product deflator (U.S. dollar series) 47 2.11 Consumer price index 48 2.12 Price indexes 49 2.13 Gross domestic savings 50 2.14 Gross national savings 51 2.15 General government final consumption expenditure 52 2.16 Household final consumption expenditure 53 2.17 Final consumption expenditure plus discrepancy 54 2.18 Final consumption expenditure plus discrepancy per capita 55 2.19 Gross fixed capital formation 56 2.20 Gross general government fixed capital formation 57 2.21 Private sector fixed capital formation 58 2.22 External trade balance (exports minus imports) 59 2.23 Exports of goods and services, nominal 60 2.24 Imports of goods and services, nominal 61 2.25 Exports of goods and services as a share of GDP 62 2.26 Imports of goods and services as a share of GDP 63 Contents iii 2.27 Balance of payments and current account 64 2.28 Exchange rates and purchasing power parity 66 2.29 Agriculture value added 68 2.30 Industry value added 69 2.31 Services plus discrepancy value added 70 2.32 Central government finances, expense, and revenue 71 2.33 Structure of demand 75 Part II. Millennium Development Goals 3. Millennium Development Goals 3.1 Millennium Development Goal 1: eradicate extreme poverty and hunger 76 3.2 Millennium Development Goal 2: achieve universal primary education 79 3.3 Millennium Development Goal 3: promote gender equality and empower women 80 3.4 Millennium Development Goal 4: reduce child mortality 81 3.5 Millennium Development Goal 5: improve maternal health 82 3.6 Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases 83 3.7 Millennium Development Goal 7: ensure environmental sustainability 85 3.8 Millennium Development Goal 8: develop a global partnership for development 87 Part III. Development outcomes 4. Private sector development 4.1 Doing Business indicators 89 4.2 Investment climate 92 4.3 Financial sector infrastructure 94 5. Trade and regional integration 5.1 International trade and tariff barriers 96 5.2 Top three exports and share in total exports, 2007 100 5.3 Regional integration, trade blocs 102 6. Infrastructure 6.1 Water and sanitation 104 6.2 Transportation 105 6.3 Information and communication technology 107 6.4 Energy 109 Participating in growth 7. Human development 7.1 Education 111 7.2 Health 113 8. Agriculture, rural development, and environment 8.1 Rural development 117 8.2 Agriculture 119 8.3 Environment 121 8.4 Fossil fuel emissions 124 9. Labor, migration, and population 9.1 Labor force participation 126 9.2 Labor force composition 128 9.3 Unemployment 130 9. 4 Migration and population 132 iv Africa Development Indicators 2010 10. HIV/AIDS 10.1 HIV/AIDS 134 11. Malaria 11.1 Malaria 138 12. Capable states and partnership 12.1 Aid and debt relief 139 12.2 Status of Paris Declaration indicators 142 12.3 Capable states 144 12.4 Governance and anticorruption indicators 146 12.5 Country Policy and Institutional Assessment ratings 148 12.6 Polity indicators 152 Technical notes 153 Technical notes references 195 Map of Africa 197 Users guide: Africa Development Indicators 2010 CD-ROM 199 Contents v Foreword "Sunlight is the best disinfectant," Associate still, it can have long-term consequences. Justice of the United States Supreme Court Denied an education because of absentee Louis Brandeis said in 1914, referring to the teachers, children suffer in adulthood with benefits of openness and transparency in low cognitive skills and weak health. The ab- tackling corruption in the public sector. To- sence of drugs and doctors means unwanted day, thanks to the efforts of Transparency In- deaths from malaria and other diseases. ternational and other organizations, there is Receiving diluted fertilizer that fails to pro- considerable "sunlight" on well known types duce results, farmers choose not to use any of corruption--public officials demanding fertilizer, leaving them in low-productivity and taking bribes for privileged access to con- agriculture. tracts or exemptions from regulations. On Quiet corruption does not make the average, Africa scores poorly on these indica- headlines the way bribery scandals do. It has tors, with some exceptions--Botswana, Cape yet to be picked up by Transparency Inter- Verde, and Mauritius have consistently done national and other global indexes of corrup- well, and Liberia has made great strides. tion. Tackling quiet corruption is at least as This year's Africa Development Indica- difficult as tackling grand corruption. It will tors essay sheds light on a different type of require a combination of strong and commit- corruption--what the authors call "quiet ted leadership, policies, and institutions at corruption"--when public servants fail to the sectoral level, and--most important-- deliver services or inputs that have been increased accountability and participation by paid for by the government. The most prom- citizens, the demand side of good governance. inent examples are absentee teachers in pub- By highlighting quiet corruption in this lic schools and absentee doctors in primary year's Africa Development Indicators--itself a clinics. Others include drugs being stolen tool for Africans to hold their governments from public clinics and sold in the private accountable--we hope that the essay will do market as well as subsidized fertilizer being for quiet corruption what Justice Brandeis diluted before it reaches farmers. intended with his famous aphorism. Not only is quiet corruption pervasive in Africa, but--as the essay points out--it Obiageli K. Ezekwesili hurts the poor disproportionately. Worse Vice President, Africa Region Foreword vii Acknowledgments Africa Development Indicators is a product of Soong Sup Lee collaborated in the update of the Africa Region of the World Bank. the live database. Mehdi Akhlaghi collabo- Jorge Saba Arbache was the director of rated in the production of The Little Data Book this book and its companions--Africa De- on Africa 2010. velopment Indicators Online 2010, Africa Yohannes Kebede and Michael Mendale Development Indicators 2010--Multiple prepared the ADI Online data visualization User CD-ROM, and The Little Data Book on platform. Africa 2010. Rose Mungai led the work on Jeff rey Lecksell of the World Bank's Map data management, consistency checks, and Design Unit coordinated preparation of the compilation and provided overall data qual- map. ity assurance. The core team included Mpho The box on measuring the impact of re- Chinyolo, Francoise Genouille, Jane K. gional integration in the technical notes was Njuguna, and Christophe Rockmore. Jane prepared by Paul Brenton. Njuguna coordinated all stages of produc- Ann Karasanyi and Ken Omondi pro- tion. Richard Crabbe provided useful pro- vided administrative and logistical support. duction support and suggestions. The over- The team is grateful to the many people who all work was carried out under the guidance provided useful comments on the publica- of Shantayanan Devarajan, Chief Economist tion, especially Inger Andersen, Paul Bren- of the Africa Region. ton, Aziz Bouzaher, Cecilia M. Briceno-Gar- Jorge Saba Arbache, James Habyarima- mendia, Donald Bundy, Moulay Driss Zine na, and Vasco Molini wrote the essay. Balu Eddine El Idrissi, Madhur Gautam, Giuseppe Bumb, Michael Morris, Giuseppe Iarossi, Iarossi, Elizabeth Laura Lule, John F. May, Gäel Raballand, Stephen Minck, Ian Grego- Steven Mink, Emmanuel Mungunasi, Vin- ry, David Rohrbach, Aad van Geldermalsen, cent Palmade, Mona Prasad, Karima Saleh, and Alies van Geldermalsen provided useful Rachel Sebudde, Giovanni Tanzillo, Chris- inputs to the essay. Jose Luis Irigoyen, Vi- topher Thomas, Franke Toornstra, Marilou vien Foster, and Valerie Marie Helene Layrol Jane D. Uy, Stephen Vincent, and Yi-Kyoung kindly prepared box 2. Stephen Mink, Nancy Lee. Their feedback and suggestions helped Claire Benjamin, Michael Morris, Prasad C. improve this year's edition. Mohan, Jose Luis Irigoyen, Vivien Foster Staff from External Affairs oversaw and Valerie Marie Helene Layrol provided printing and dissemination of the book and useful comments on an earlier draft of the its companions. essay. Several institutions provided data to Azita Amjadi, Ramgopal Erabelly, Ab- Africa Development Indicators. Their contribu- dolreza Farivari, Richard Fix, Shelley Lai tion is very much appreciated. Fu, Malarvizhi Veerappan, Shahin Outadi, Communications Development Incor- William Prince, Abarna Gayathri Manickudi porated provided design direction, editing, Panchapakesan, and Jomo Tariku collabo- and layout, led by Bruce Ross-Larson and rated in the data production. Maja Bresslauer, Christopher Trott. Elaine Wilson typeset Mahyar Eshragh-Tabary, Victor Gabor, and the book. Acknowledgments ix Executive summary Silent and lethal: How quiet corruption With this broader defi nition in mind, undermines Africa's development efforts the familiar form of big-time corruption is The corruption that often captures newspa- just the "tip of the iceberg"; the quiet corrup- per headlines and provokes worldwide public tion, that is the less frequently observed de- disapproval is dominated by loud "big-time viations from expected conduct, is below the corruption," notably administrative and po- surface. In addition to capturing the notion litical corruption at the highest government that quiet corruption is not as visible, the levels. In response to this notoriety, the iceberg analogy provides two additional in- bulk of anti-corruption measures have been sights. First, quiet corruption occurs across tailored to address this type of corruption. a much wider set of transactions directly However, recent examinations of the level affecting a large number of beneficiaries. and quality of service delivery in developing Quiet corruption is present in a large share countries, including the World Development of health-provider­patient or teacher-pupil Report 2004, have highlighted the need to interactions, for example. Second, quiet expand the scope of the standard definition corruption very often has deep long-term of corruption--the abuse of public office for consequences on households, farms, and private gain. While acknowledging the im- firms. The widespread prevalence of big-time portance of big-time corruption in reducing and quiet corruption in Africa significantly funding for service delivery, recent research undermines the impact of investments to has devoted increasing attention to identi- meet the Millennium Development Goals fying corrupt practices downstream at the (MDGs). In the parlance of this essay, the frontline of public service provision. iceberg of corruption is sinking considerable Following this literature, this essay in- efforts to improve the well-being of Africa's troduces the term "quiet corruption" to indi- citizens, particularly the poor who rely pre- cate various types of malpractice of frontline dominantly on publicly provided services. providers (teachers, doctors, inspectors, and It is important to raise awareness of the other government representatives) that do profi le of quiet corruption because this mal- not involve monetary exchange. These be- practice has non-negligible long-term con- haviors include both potentially observable sequences. Th is essay elaborates both the deviations, such as absenteeism, but also direct consequences, such as the limitation hard-to-observe deviations from expected of the productivity potential of households, conduct, such as a lower level of effort than fi rms, and farms, and the indirect conse- expected or the deliberate bending of rules quences, such as distrust of public institu- for personal advantage. For example, recent tions and the notion that frontline provider findings indicate that primary school teach- malpractice is inevitable and omnipresent. ers in a number of African countries are not As an example of direct consequences, in school 15 to 25 percent of the time (absen- we might think how poor service delivery teeism), but, in addition, a considerable frac- caused by absenteeism or low effort on the tion of those in school are not found teaching job might hamper a child's development, (low effort). Frontline provider deviations with potential permanent effects on adult from expected behavior that meet these re- educational attainment, cognitive skills, and quirements broaden the scope of corruption. underlying health. As an indirect effect, we Executive summary xi might think of the withdrawal of children and capacity of the national anti-corruption from school because of beliefs about the low units to pursue operationally effective re- quality of education, which shifts the alloca- sponses at the sector level, and adequate tion of time and resources away from human policies and institutions. An equally impor- capital formation toward home production tant second pillar is increasing transparency or labor market participation. in policy formulation and implementation Th is essay further shows how quiet cor- that empowers citizens to raise the account- ruption manifests itself differently according ability of service providers--bolstering the to the nature of service delivery. It focuses "demand side" for good governance. Finally, on four key sectors (education, health care, successful implementation of anti-corrup- agriculture, and the private sector) whose tion reforms also requires that the prefer- progress and success are crucial for poverty ences and interests of all those involved be eradication and more generally achieving aligned with achieving the objectives of the the MDGs. In presenting examples and out- reform. Th is often involves better working lining the long-term consequences of quiet conditions. corruption in these sectors, this essay con- Given the complexity of the task, the tends that one of the main reasons Africa is fight against quiet corruption requires tai- lagging behind is the poor service delivery loring policies to country circumstances, rec- that is a consequence of quiet corruption. ognizing that priorities and responses may The good news is that quiet corruption vary depending on different country condi- can be tackled. Whenever a government's tions. Th is essay outlines a research agenda determination to deal with quiet corruption to identify interventions to address quiet has increased, for example, by increasing corruption. Experimenting with various the availability of information on finances, ways to empower beneficiaries and continu- inputs, and expected outputs, then measur- ing the ongoing efforts to tackle big-time able improvements in service delivery have corruption will go a long way toward achiev- been possible. Although there is no "one size ing this goal. Indeed, although combating fits all" recommendation that applies to ev- loud and visible forms of corruption is nec- ery sector, this essay advocates the need for essary, fighting quiet corruption is critical strong and highly motivated leadership in if governments want to reduce poverty and the fight against corruption, commitment to promote sustainable growth. xii Africa Development Indicators 2010 Silent and lethal: How quiet corruption undermines Africa's development Corruption captures newspaper headlines education providers, agriculture extension and provokes public disapproval. In addition, services, drug inspectors, and the police (see the abuse of public office for private gain-- Razafindrakoto and Roubaud 2006). the most common definition of corruption-- World Development Report 2004 (World has attracted increasing attention by scholars Bank 2003), which examined service deliv- and policy makers interested in economic de- ery, recasts the problem of corruption from velopment. Specifically, corruption and poor a different perspective. While acknowledg- governance help explain why increased fund- ing the importance of big-time corruption in ing allocations, such as those aimed at meet- reducing funding for service delivery, World ing the United Nations Millennium Develop- Development Report 2004 and subsequent ment Goals (MDGs), have not necessarily research have devoted increasing attention translated into improvements in human de- to analyzing corrupt practices downstream, velopment indicators, particularly in Africa.1 at the frontline of public service provision Despite considerable funding increases, the (Reinikka and Svensson 2006). This new region is largely lagging behind in meeting focus has produced two results. First, it has the MDG of reducing child mortality (the enabled the identification of malpractice in- number of children dying before age 5 per volving small monetary transactions, gen- 1,000 live births). Substantial increases in erally referred to as "petty corruption" (de gross enrollment in primary education in Sardan 1999), for example, under-the-table recent years have not been matched by im- payments for services received (Transpar- provements in learning outcomes. Africa's ency International 2005, 2006) or bribes private investment rate is still around 15 to tax collectors and low ranking public of- percent, much lower than in most develop- ficials. Second, the concept of corruption has ing countries. Agricultural productivity is not been gradually extended to practices that do increasing fast enough; the yield per hectare not necessarily involve monetary transac- is still less than half that in other developing tions, such as teacher absenteeism (Patrinos regions. Cutting across all these problems is and Kagia 2007). Furthermore, new survey Africa's fundamental problem, namely weak tools, such as the Public Expenditure Track- governance and associated corruption.2 ing Survey (PETS) and Quantitative Service Until recently, the debate about corrup- Delivery Survey (QSDS), have enabled re- tion and development3 has been dominated searchers to track resources and monitor the by the identification and measurement of attendance of frontline providers. These re- "big-time corruption" (de Sardan 1999), no- search and survey results have improved the tably administrative and political corruption understanding of a broad range of miscon- at the highest levels of government.4 This fo- duct and contributed to reshaping the policy cus has produced measures of governance debate about corruption. weakness and corruption suitable for cross- Following the recent fi ndings on front- country comparisons of political corruption. line provider misconduct, this essay focuses But these measures are not reliable when on behaviors that are difficult to observe it comes to measuring less visible forms of and quantify, but whose impact on service corruption, such as those faced by common delivery and regulation has adverse long- citizens as they interact with health and term effects on households. We introduce Silent and lethal: How quiet corruption undermines Africa's development 1 the term "quiet corruption" to indicate vari- money--either political level thefts or small ous types of malpractice of frontline provid- but frequent bribes--is less salient or "noisy," ers (teachers, doctors, inspectors, and other and consequently less likely to attract public government officials at the front lines of ser- attention. Despite its low visibility, quiet vice provision) that do not involve monetary corruption is ubiquitous. And it is associated exchange. These behaviors include not only with harmful long-term consequences, par- potentially observable deviations, such as ticularly for the poor who are more exposed absenteeism, but also hard to observe devia- to adverse shocks and more reliant on gov- tions from expected conduct, such as a lower ernment services to satisfy their most basic level of effort than expected or the deliberate needs. bending of rules for personal advantage. For Two examples illustrate the magnitude example, education service delivery requires of the consequences of quiet corruption. teachers to be present in school as well as to First, among the reasons for low fertilizer us- deliver classroom instruction required by age among African farmers is the poor qual- the curriculum. Similarly, a building inspec- ity of fertilizers on the market. Despite the tor can turn up to inspect the structural in- capability of manufacturers to produce good tegrity of a new shopping mall but choose to fertilizers, poor controls at the producer and exert little effort in executing the task. wholesaler levels resulted in 43 percent of Quiet corruption, as opposed to cor- the analyzed fertilizers sold in West Africa ruption that involves an exchange of in the 1990s lacking the expected nutrients, meaning that they were basically ineffective Figure 1 Big-time and petty corruption are the "tip of the iceberg" (IFDC 1995). It is likely that poor farmers' experiences with low-quality fertilizers dis- courage fertilizer adoption. Second, a survey of malaria fatalities in rural Tanzania reported that nearly four out of five children who died of malaria sought medical attention from modern health fa- cilities (de Savigny et al. 2008). A range of Big-time and petty manifestations of quiet corruption, includ- ing the absence of diagnostic equipment, corruption drug pilfering, provider absenteeism, and very low levels of diagnostic effort, all con- tributed to this dire statistic (Das and Leon- ard 2009). The concept of quiet corruption is cap- tured in Figure 1. The familiar forms of corruption--both big time and petty--are just the "tip of the iceberg"; the less frequent- Quiet ly observed deviation from expected conduct is quiet corruption. In addition to capturing corruption the notion that quiet corruption is not very visible, the iceberg analogy provides two additional insights. First, quiet corruption occurs across a much wider set of transac- tions affecting a large number of beneficia- ries directly. Quiet corruption is arguably present in a large share of doctor­patient or teacher-pupil interactions, for example. Second, quiet corruption plausibly has deep long-term consequences on households, farms, and firms. Comparing the long-term consequences of different forms of corrup- tion is a hazardous undertaking. In addition 2 Africa Development Indicators 2010 to being affected by the same country level an environment conducive to misconduct by characteristics, all three forms of corruption frontline service providers. are related. The quiet corruption of low-level The scheme of insiders profiting from bi- officials may very well have been "justified" ased rules in the system is mirrored in society. in their minds by the misbehavior of their Police exert their influence to extract benefits superiors involved in big-time corruption. from the disorganized mass of road users; Likewise, by reducing available resources doctors do not show up in public facilities and and compromising the monitoring and en- instead provide services privately; teachers forcement of conduct, big-time corruption do not show up in classes since they have a encourages low-level civil servants to en- second job and their impunity is guaranteed gage in opportunistic behavior. An instance by their superiors in exchange for other fa- of teacher absence could be the result of a vors, and so forth. It follows that corruption poor working environment occasioned by becomes an unavoidable element of daily life big-time corruption or other factors beyond for many citizens, and it diffuses throughout the teacher's and education managers' con- the economy; more big-time corruption be- trol. However, it can also be categorized as gets corruption at the frontlines of service quiet corruption--the abuse of public office delivery, which in turn supports big-time by the teacher. The long-term consequences corruption, creating formidable challenges to of this and other instances of absence com- governance and accountability interventions. pound the effects of both big-time and quiet For a number of key public services, the corruption. cumulative nature of human development Corruption is embedded in the politi- implies that poor service delivery experi- cal economy of Africa. A number of studies enced during the early stages of life can have describe the interaction between various long-term consequences. The direct long- forms of corruption and how it is intrinsi- term effects of quiet corruption begin with cally linked to the way power is exercised. 5 poor service delivery during early childhood, In particular, when a social unit is highly which is then amplified by subsequent poor diverse ethnically 6 --as is the case in many service provision throughout childhood. For post-independence African countries--there example, a mother who is a victim of quiet is likely to be suspicion and division among corruption--poor quality antenatal care-- members, making the process of agreeing to might give birth to an underweight child, rules for governance extremely difficult. In who will likely suffer a series of health set- this context, small groups (elites) that are backs during childhood that potentially highly homogeneous are more likely to pre- magnify the immediate effects of the poor vail and impose rules that bias the system antenatal care. Th is amplification process is in their favor. The enforcement of these bi- also driven by families' increasingly negative ased rules requires either coercion or "addi- expectations of service delivery systems, tional resources" to ensure the cooperation leading to even fewer health service visits of members of other groups who will try to and the use of poorer quality alternatives. In avoid such biased rules. the African context, alternative health ser- In many African states, the coercion op- vices are often nonexistent, of low quality, tion is not feasible because state power is or too costly for the typical household. The limited. In contrast, the option to purchase family's decision to exit the system leads to the cooperation of other groups tends to a worsening of the public sector and can ul- be the most viable. Ruling elites in regimes timately result in the collapse of service de- with limited legitimacy thus regard corrup- livery.8 For example, as McPake et al. (2000) tion purely in terms of its political func- document, the poor quality of health care tionality as a source of patronage resources services in Uganda created a downward spi- to maintain and strengthen the system of ral of underutilization of public health facili- political power.7 The more these elites are ties. Lower demand for services led to even able to privatize state resources, the more lower staff attendance and to shorter open- they can distribute favors and create a base ing hours of health care facilities. of consensus for their privileged position. Considering the pervasiveness of cor- Thus a strategy to control the state creates ruption and that the different types are Silent and lethal: How quiet corruption undermines Africa's development 3 intertwined with the functioning of politi- While these long-term consequences are cal and social systems in many developing very hard to quantify because of the absence countries, it is clear that focusing only on of data that trace out the effects of contem- the monetary forms of corruption misses poraneous misconduct on future outcomes the majority of solutions. Hence, this essay and because of the multiplicity of other fac- attempts to provide a framework to under- tors that may contribute to them, combining stand the implications of the entire "iceberg" evidence from both developed and develop- of misconduct that shapes the level and ing countries provides a sense of the mag- quality of services and regulation in devel- nitude of resulting damage to development. oping countries. The essay outlines evidence The long-term consequences are divided into of quiet corruption and discusses both di- direct consequences, such as the limitation rect and indirect long-term consequences on of the productivity potential of households, households, businesses, and farms. firms, and farms, and indirect consequenc- The framework in Figure 2 describes the es, such as distrust of public institutions mechanisms through which quiet corrup- and the notion that corruption is inevitable tion affects delivery of frontline services, and omnipresent. These two components are such as medical treatment or in-classroom explained in more detail below. instruction, and the provision of business One direct effect of quiet corruption is regulations, such as trading licenses. The the loss of production as a result of the lower three arrows linking quiet corruption and quality of inputs. For example, research on service delivery represent "pathways of in- corruption in the health-care sector rarely fluence." These are denoted as (1) low effort documents how the effect of poor service due to absenteeism, (2) low effort on the job, delivery that might hamper a child's devel- and (3) resource leakage. opment has permanent effects on adult edu- Low effort due to absenteeism refers to cational attainment, cognitive skills, and frontline provider behaviors that restrict the underlying health. The absenteeism of doc- amount of time they are available. Absentee- tors or nurses, for example, might contrib- ism implies that providers work less time at ute to the non-detection of iron deficiency the public facility than contracted for, with (Ramakrishnan et al. 1999) or deficiency of little or no repercussions on their earnings. other micronutrients in a pregnant mother's The second arrow takes into account the ex- diet. The lack of timely intervention affects tent to which frontline providers shirk their the development of the fetus and stunts the duties while on the job. Finally, the third ar- child's full growth. The consequences of this row refers to providers' involvement in the poor health treatment may manifest during leakage of key inputs, such as drugs and adolescence and adulthood and could affect medicines, in the case of health-care work- the individual's productivity (Barker et al. ers, or books and other instructional materi- 1995; Smith 2009). als in the case of teachers. An indirect effect of quiet corruption Despite the difficulties in observing at- operates through changing the beliefs tendance and job effort, the lack of transpar- and expectations of service beneficiaries. ency and accountability, and the weaknesses As a result of this transformation, agents of monitoring and enforcement inherent in may decide to allocate their time in more public service organizations in developing remunerative activities in the short run countries, this essay argues that quiet cor- at the expense of capital accumulation ruption is likely to be equally insidious as and investment in activities that produce big-time corruption. The right-hand portion larger gains only in the long run. A typical of Figure 2 illustrates the linkage between case is the non-investment in the human poor service delivery today and the direct capital of children because of beliefs about and indirect long-term consequences of big- the low quality of education, which shifts time corruption and quiet corruption. Be- the allocation of time and resources away cause of its nature, quiet corruption can af- from education toward home production fect incentives and distort the allocation of or labor market participation. Another ex- resources at the individual, household, firm, ample, as mentioned above, is the lack of and farm levels. adoption of fertilizers and other productive 4 Africa Development Indicators 2010 inputs by farmers who have had bad prior socioeconomic characteristics and political experiences. power of the main clientele. The implication Finally, the notion that corruption is is that reform strategies should differ de- generally ubiquitous and inevitable implies pending on the nature of service. There will that it is an "accumulating process": the more be differences across countries as well, in corrupt the system, the more it produces accord with the levels of accountability and a downward spiral of malpractice (de Sar- transparency and the systems of monitor- dan 1999). Within a corrupt environment, ing, enforceability of rules and procedures, people adjust their strategies accordingly and punishment of corruption. As a conse- and contribute to the general acceptance of quence, there is no recipe on how to prevent the phenomenon, thus making it routine. If and fight quiet corruption that is valid for all professional standards are substituted with sectors and countries. The aim of this essay a pure "fend for yourself" attitude at every is not to arrive at specific recommendations level (Lindelow, Serneels, and Lemma 2005), but rather to stimulate debate around this the system falls into a vicious cycle in which critical development topic, expecting that every misconduct is tolerated and the struc- it will increase interest and efforts that are ture of incentives becomes biased against much needed to combat quiet corruption. those who adhere to the standards. While quiet corruption is indeed pres- Some sectors are more vulnerable to ent in all sectors, the next sections present quiet corruption than others; the main de- evidence and discuss the consequences of terminants are the level of transparency quiet corruption in education, health, the and accountability in the sector, the asym- private sector, and agriculture. Th is selec- metry of information, and the discretion tion is based on the importance of these sec- and monopoly power of service providers, tors for Africa's development as well as the all of which create incentives for miscon- existing evidence on quiet corruption. For duct. The manifestation will also differ from each sector, the presence of quiet corrup- rural to urban areas and will depend on the tion in the typology presented in Figure 2 Figure 2 The functioning of quiet corruption and its long-term consequences Big-time and petty corruption Low effort due to absenteeism Lower productivity Poor service delivery Long-term and regulations direct Lower human capital Quiet consequences corruption Low effort on the job Markets concentration Long-term indirect Poor resources consequences allocation Resource Disbelief in leakage public institutions Silent and lethal: How quiet corruption undermines Africa's development 5 is documented. Furthermore, and to the For purposes of this essay, the frequency of extent possible, the direct and indirect long- documented deviations represents an upper term consequences for economic agents are bound of the prevalence of quiet corruption. presented. Following the framework of Figure 2, the long-term consequences are divided into di- Education rect and indirect effects. The education sector prepares youth for productive engagement in the social, politi- Teacher capture cal, and economic realms as adults. In Africa A considerable body of evidence documents education accounts for a large fraction of the capture of service delivery systems by key government expenditure, with a large share actors in the service delivery chain (Mizala of public resources accruing to teachers. and Romaguera 2004 and others). "Capture" Teacher remuneration accounts for nearly refers to a situation in which key actors are three-quarters of recurrent expenditure in able to alter the rules, such as the conditions education in developing countries (Bruns, of service or the allocation of expenditure in Mingat, and Rakatomalala 2003). Quiet cor- the sector, to their advantage and to the detri- ruption in education, therefore, is not only ment of service beneficiaries and the society costly in terms of the direct loss of consider- at large. In the case of the education system, able scarce public resources, but more impor- teachers are a key group of actors that have tantly in terms of its long-term consequenc- exerted considerable influence over both the es for the human capital base. Given the long allocation of resources within the system, but term consequences of adults with lower skills more importantly, the rules that define their and poor attitude, quiet corruption in educa- conditions of service. Much of this power is tion undermines the serious efforts being in- exercised as a result of the influence wielded vested in the eradication of poverty and im- by teacher unions or through the direct in- provement in the competitiveness of African volvement of current or retired teachers in economies (World Bank 2009). local and national politics. This section presents three different Th is "teacher power" could represent an forms of quiet corruption that have been important constraint on the extent to which identified in the literature. First, the issue of levels of learning can be improved in devel- frontline provider capture of the education oping countries. Two examples demonstrate system: teachers modify the rules and in- the effects of teacher capture on the learn- fluence the allocation of education budgets. ing levels of pupils. In 1998, the Bolivian Second, evidence for low levels of teacher government introduced a policy to ascertain effort in the form of attendance and effort the quality of teachers through a "teach- on the job is discussed. Finally, evidence of ing sufficiency examination." Participation the extent of the leakage of non-salary cash in the test was voluntary and teachers who flows and instructional materials in the edu- passed the exams received a wage increase cation sector is presented. Short-term im- relative to the traditional wage scale. In ad- pacts of each of these forms of quiet corrup- dition, head teachers had to pass this test in tion are linked to long-term effects through order to continue in their role as principals. the cumulative nature of skills acquisition The fi rst round of implementation revealed and evidence from cohort studies in devel- very low levels of teacher quality: 60 percent oped countries. of the teachers who participated failed the Identifying quiet corruption in educa- test and only a very small fraction received tion, as in any other sector, is not straight- a wage increase. The teacher union rejected forward. Much of the evidence presented the results of the test, claiming that the in- below does not unambiguously categorize vitation to participate and the assignment of any observed deviation from expected be- grades were problematic. A series of demon- havior as quiet corruption. For example, it strations and hunger strikes calling for the is difficult to establish the extent to which elimination of the examinations followed. teacher absenteeism or low levels of school The government capitulated and in the inspection reflect either a poor working second year of implementation more than environment or the abuse of public office. 18,500 teachers received wage increases. 6 Africa Development Indicators 2010 The policy was discontinued and replaced by Table 1 Percentage of grade 6 students receiving extra lessons a range of largely non-performance-based incentives (Mizala and Romaguera 2004). Percentage of grade 6 students receiving extra lessons A 2007 proposal by the ministry of edu- SACMEQ I SACMEQ II cation in Uganda to improve management at Country 1995 2000 the school level through performance con- Mauritius 77.5 86.6 tracts with head teachers met a similar fate. Kenya 68.6 87.7 In the proposed contracts, head teachers Zanzibar 46.1 55.9 would sign an agreement with the local gov- Zambia 44.8 55.1 ernment outlining a series of goals to be met Namibia 34.7 44.7 over a two-year period. Failure to meet these Malawi 22.1 79.7 goals could lead to demotions or transfers. Total 49.0 68.3 Even though the policy explicitly stipulated that head teachers would be the main archi- Source: Paviot, Heinsohn, and Korkman (2008). tects of the performance targets, the teacher union successfully opposed the policy on the basis that the penalties included in the con- duration of absence during a given time pe- tracts were excessive and unfair. riod (usually 1­4 weeks). For example, an Other rules that are subverted for teach- important UNICEF multi-country survey of er benefit include the implicit or explicit 14 developing countries conducted in 1995 sanctioning of additional instruction out- and reported in Postlethwaite (1998) reports side regular school hours. The legitimacy high levels of head-teacher reported absen- of this practice in a number of countries is teeism. Among the African countries, Tan- particularly pernicious when public teach- zania, Uganda, and Zambia were the worst ers selectively cover material during regular performers. More than half the teachers in school hours and other material during their Tanzania and Uganda were absent at least private tutoring sessions (Jayachandran one day in the previous week and about a 2008; Dang and Rogers 2008). The extent quarter of teachers were absent for two or to which this extracurricular instruction more days. In Zambia, a quarter of teachers might be occurring is suggested by the high were absent for two or more days. Using a and increasing prevalence of extra tuition, similar methodology, Das et al. (2004) report which is shown in Table 1 using data from an average absence duration of two days per the Southern and Eastern Africa Consor- month in Zambian primary schools in 2002. tium for Monitoring Educational Quality Concerns about the quality of head- (SACMEQ). While these data are generated teacher or teacher reports of absenteeism from pupil reports that are unreliable for es- have motivated the use of direct observation tablishing the existence or level of extra tu- of teacher attendance (Table 2).9 In this ap- ition fees, they suggest a considerable degree proach, which relies on unannounced visits, of discrimination: households that cannot a teacher is reported as being absent if he afford extra lessons receive less and/or lower or she cannot be found by the enumeration quality instruction than is stipulated by the team at a time that he or she is scheduled curriculum. to be in school. Th is methodology has been widely used in western Kenya and a large Low levels of teacher effort multi-country study that included Uganda Teacher effort is an important input into (Chaudhury et al. 2006). Kremer et al. (2004) learning (Park and Hannum 2002; Hanushek, report that 20 percent of teachers in rural Kain, and Rivkin 2005). Perhaps the most western Kenyan primary schools could not important form of quiet corruption in edu- be found during school hours. In Uganda, cation is the low levels of teacher effort that two waves of surveys using this methodolo- arise from teacher absence and low effort gy found teacher absence rates of 27 percent while in school. Evidence on the extent of in 2002 and 20 percent in 2007.10 teacher absence has improved greatly over The above studies document considerably the last decade. Early evidence comes from higher levels of absence among head teach- head-teacher or teacher self-reports of the ers and other senior teachers.12 Whether Silent and lethal: How quiet corruption undermines Africa's development 7 Table 2 Estimates of teacher developed countries. While this measure absenteeism indicates lower levels of instruction, it as- % teachers Days absent sumes that teacher attendance patterns and absent per month (direct (teacher in-class effort and quality are similar across Country observation) self report) developed and developing countries. Higher Uganda (2003)a 27 levels of teacher attendance and the use of Uganda (2007)b 20 substitute teachers in developed countries Kenya (2003)c 20 further deepen the instruction time gap be- Zambia (2007)d 20 tween developed and developing countries. Burkina Faso (1995­8)e 2.2 Additional evidence from direct obser- Cameroon (1995­8) e 1.8 vation studies suggests that in-class behav- Cote d'Ivoire (1995­8) e 1.3 ior of teachers differs from their developed Madagascar (1995­8) e 2.5 country colleagues. While there are prob- Senegal (1995­8) e 4.7 lems of interpretation,13 direct observation Zambia (2002)f 2.0 surveys suggest that even among those teachers who are found present in school, Sources: a. Chaudhury et al. (2006); b. Habyarimana (2007); c. Glewwe, Kremer, and Moulin (2009)11; d. Halsey, Rogers, and Vegas (2009); in-class effort is low. For instance in western e. Postlethwaite (1998); f. Das et al. (2004). Kenya, Glewwe, Kremer, and Moulin (2009) document that 12 percent of teachers were found to be outside the classroom when they this represents low effort is difficult to say should have been teaching. An even higher because a range of duties may draw princi- fraction is estimated in Uganda where nearly pals away from school (to attend meetings or one-third of teachers found were not in the request or collect resources). Taking the ex- classroom during learning periods (Habya- ample of Uganda, head teachers were twice rimana 2007). as likely to be absent as regular teachers Teacher influence and capture could (Habyarimana 2007). In addition, assum- explain much of the low levels of teacher ing that the reported reasons for absence are effort documented. For example, the multi- credible, only half of the absences are offi- country study finds that teacher absence is cially sanctioned. Perhaps even more conse- not concentrated among a few "ghost" teach- quential is evidence from the multi-country ers, but rather is driven by the behavior of a study that documents higher regular teacher large share of teachers. Punishment of poor absence when the head teacher is absent. attendance or tardiness on the job is very Chaudhury et al. (2006) also collected infor- rare. In many cases, warning letters or re- mation about the likelihood that teachers ports of teacher misconduct do not trigger were warned or fired for absence. The results any sanctions. from India are indicative of the low levels of sanctions: only one teacher in 3,000 schools Leakage of resources had been fi red for absence despite high ab- Schools combine instructional materials and senteeism rates. The level and quality of in- teacher and pupil interaction to produce cog- struction provided by teachers is not only nitive skills. This essay documents the leak- a function of their training and attendance age of two key inputs: instructional materials patterns, but also of their behavior while in and school inspection. A teacher with few or school. Measuring the effort level of teachers no instructional materials will find it harder in school and the extent to which it qualifies to impart the necessary skills to her charges. as quiet corruption is challenging. Indeed, In addition, school inspection ensures that a number of studies have tried to quantify the right pedagogical strategies are being this effect with limited success. Some studies implemented and instructional materials are rely on adding up the number of class hours well deployed.14 using the school's timetable. For example, The clearest example of the extent of Postlethwaite (1998) reports that students leakage of instructional resources comes in his developing country sample received from two PETS surveys in Uganda in the only about 80 percent of the total timetable- 1990s. The fi rst study revealed that an av- derived annual instruction time as those in erage of only 13 percent of the resources 8 Africa Development Indicators 2010 intended for schools were reaching them. the consequences of these deviations is Poor information flows about the size of the straightforward. The acquisition of skills and capitation grant and the timing of resource competencies is a cumulative process: cogni- flows provided local education authorities tive achievement today defines how much a with the cover to divert these resources. child will learn tomorrow. Therefore, quiet These fi ndings motivated a government-led corruption today that leads to contempora- intervention to increase the transparency neous lower levels of learning has long-term of grants disbursement. In addition to pros- effects. Some of these long-term effects oper- ecuting offenders, the newspaper and radio ate through decisions that households make. campaign led to large increases in school lev- For example a household might decide that a el funding (Reinnika and Svensson 2005). child who is not learning very much could be In the Zambia PETS of 2002, Das et al. better utilized to look after cows. Evidence of (2004) found that resources meant for reno- this cumulative learning process comes from vation were more likely to go to schools in cohort studies in developed countries that the middle of the wealth distribution, which demonstrate the strong correlation between suggests a degree of collusion between head cognitive skills while young and competen- teachers of middle-tier schools and local ed- cies and earnings in adult life (for example, ucation authorities. Other PETS carried out Case and Paxson 2008). For each of the three in Africa all point to considerable leakages in forms of quiet corruption in education iden- non-salary funding (Gauthier 2006). tified above: teacher capture, low effort, and Finally, the quality of instruction and leakage of resources, there is evidence of a pace of learning is supposed to be monitored negative impact on learning. These short- by a variety of standards officials who typi- term impacts translate into long-term con- cally work in the local education authority. sequences through the cumulative nature of Regular inspection provides crucial infor- skills acquisition and the dynamic decisions mation about challenges and successes that of households. In short, quiet corruption has can be used to generate improvements in arguably grave consequences for the future service delivery.15 While low levels of school competencies of Africa's youth. inspection can be the result of a poor work- Households make dynamic decisions ing environment in which willing officials about whether to enroll/continue a child in lack the means to conduct their duties, the school and how much to invest in time and prima facie evidence is examined as an up- resources based on complementary inputs per bound of the extent of deviations from provided by teachers and schools, and par- norms. It is important to bear in mind that ticularly, based on perceptions of the child's countries have different norms of inspec- learning. Each of the three forms of quiet tion frequency that determine the extent corruption impinges on household decisions to which observed rates of inspection dif- and consequently on the competencies and fer from stipulated rates. Th is essay instead attainment of children. Teacher instruction presents evidence from a number of sources time is a crucial input in the production of that simply report the fraction of schools competencies and skills that are crucial in a that have been visited by an inspector in the wide range of market and non-market activi- year since the survey. Postlethwaite (1998) ties. And the level and quality of teacher in- suggests that in Madagascar, Togo, Ugan- struction time is affected by all three forms da, and Tanzania, more than 70 percent of of quiet corruption. students were in schools that had not been The capture of the education system af- inspected in the previous year. More recent fects attainment and long-run skills acquisi- evidence from a number of surveys (Uganda tion in several ways. First, as the examples Unit Cost Study and PETS in Zambia and above demonstrate, capture supports lower elsewhere) suggest similarly low levels of levels of teacher quality and managerial ef- inspection. fort at the school level. While evidence of the link between teacher quality and learn- Long-term consequences for education ing outcomes is thin, a study in Israel found While it is difficult to attribute all of the de- that teacher training is associated with viations above to misbehavior, establishing learning gains (Angrist and Lavy 2001). Silent and lethal: How quiet corruption undermines Africa's development 9 Second, to varying degrees, capture supports (2004), leading to even lower learning gains. deeper levels of quiet corruption: low levels Second, as mentioned earlier, households of teacher effort, leakage of instructional make human capital investment decisions materials, and lower levels of inspection. on the basis of current and expected learn- The effects of teacher absence, leakage ing achievements. A child who is struggling of instructional materials, or lower moni- in a school system characterized by quiet toring of learning are well documented. For corruption is more likely to drop out or be instance, using data from Zambian primary removed from school, leading to permanent- schools, Das and others (2007) found that ly low levels of skills and competencies. Evi- an increase in absence duration of one day dence from long-term cohort studies (Case, per month reduces test scores by about 4­8 Lubotsky, and Paxson 2002) confi rm the percent of the average annual gains in Eng- long-lasting nature of the adverse effects of lish and mathematics. In addition, Kremer, learning deficiencies at an early age on pro- Miguel, and Thornton (2004) found that test ductivity in later years and complete the link score gains in response to a girls' scholarship between quiet corruption and direct long- program in western Kenya are in part the term consequences. result of increases in teacher attendance of nearly 6 percentage points. Duflo, Hanna, Health and Ryan (2008) showed test score gains of As in the education sector, quiet corruption in 0.2 standard deviations that corresponded the health care sector is widespread in Africa. to a halving of teacher absence in non-for- However, as in the other sectors discussed in mal schools in India. this essay, it is generally very difficult to as- Several studies document the positive certain the intent and therefore culpability of link between more resources and short-term providers. In laying out the evidence for each learning gains in Africa. Using the results of these behaviors in health care and their at- of a newspaper campaign that increased tendant consequences, we advise the reader the amount of funding reaching schools in to keep this caveat in mind. Uganda, Bjorkman (2006) reported gains in national test scores attributable to the Low levels of provider effort increase in capitation grant flows. In addi- As in the education sector, the quality and tion, evidence from Zambia suggests that level of health services depend on the qual- increases in unanticipated funding increase ity of providers, the frequency of attendance, the test scores of grade 6 pupils (Das et al. and effort levels while at work. Evidence on 2004). Evidence from western Kenya sug- quality and effort levels is only just beginning gests that the randomized provision of to emerge and is briefly discussed below. On textbooks increased learning only for the the other hand, evidence on health provider best students (Glewwe, Kremer, and Moulin attendance is considerable and suggests a 2009). In contrast, a recent study in Brazil very discouraging situation. Differences in showed that higher levels of resource leak- measurement methodology notwithstand- age at the municipality level are associated ing, reports of health provider absence are with lower learning gains of pupils (Ferraz, very high. PETS in Mozambique and Chad Finan, and Moreira 2009). (Gauthier 2006) document a rate of absen- While test score outcomes are typically teeism in public facilities of around 20 per- measured for 10- to 14-year-old students, cent. A direct observation survey in Uganda the deleterious effects of quiet corruption recorded a rate of 37 percent in the first extend throughout a child's adolescent and round (2002) that went down 4 percentage adult life. Two particular channels amplify points in the second survey in 2003. Buck- the long-term consequences. First, low lev- ing this trend is Cameroon, where estimated els of learning occasioned by quiet corrup- absence rate is only 5.6 percent. tion produce a poor learning environment in In another survey based on direct ques- the next year that leads to further teacher tions to African, Asian, and Latin American and student absenteeism. Th is dynamic is physicians who had obtained a master's of reinforced by the links between student and public health degree in Europe between 1976 teacher effort documented by Kremer et al. and 1996 (Macq and Van Lerbeghe 2000), 10 Africa Development Indicators 2010 doctors comprised the category most absent on studies carried out in India, Indonesia, among health care personnel, declaring only Mexico, Paraguay, and Tanzania, estimates 73 percent of their time serving the public, of doctor competence and practice paint a that is, in their official job capacity. The rest disturbing picture. Restricting the focus to of the time was divided between a second the evidence from Tanzania, Leonard and job, generally in the private health care sec- Masatu (2007) found that health provider tor, or in teaching or other activities often competence is considerably poorer in rural unrelated to the core activity. This is likely a areas. However, more appropriate to our def- conservative estimate, because respondents inition of quiet corruption, the gap between have incentives to underreport the effective what providers know and what they do, that time spent in other activities. is, provider effort, is particularly worse in A study undertaken in Uganda between government facilities. 1994 and 1997 involving health workers, community members, and the Health Unit Leakage of resources Management Committee documents an Estimating the degree of resource leakage in environment where so-called "coping strat- health care is very challenging. In many coun- egies," activities not directly related to the tries, governments do not state how much job position, are predominant (McPake et al. they have allocated for various health care in- 2000).16 Health workers, besides openly ad- puts, depriving the analysts of a benchmark mitting to extra-legal user fees for services against which to assess receipts. and selling drugs, also declare that their However, for some resources, leakage greatest source of income is agriculture, thus can be measured as the difference between implicitly acknowledging a high rate of ab- stipulated resource flows (typically non-sala- senteeism. A comparison of working hours ry budgetary resources) and actual amounts declared with observed working durations received. Leakage amounts in this category over the course of a month reveal a striking vary from about 38 percent in Kenya to 99 gap: effective hours worked are in most cases percent in Chad (Table 3). While the differ- one-third or less than what is declared. This ences do not singularly represent leakage is consistent with very low utilization of close to the frontline of service delivery, these facilities, which are open for only two the magnitude of the leakage gives a sense to three hours in the morning. of the size and importance of this form of Absenteeism thus gives way to a vicious quiet corruption. cycle of low service utilization by the public, In addition to leakage of non-salary which then further reinforces the poor at- cash flows, the leakage of health goods is tendance of health workers.17 For example, pervasive. A qualitative survey of 50 health Banerjee, Deaton, and Duflo (2004) found workers in Mozambique and Cape Verde that in Rajasthan, India, over the course of concluded that this practice is widespread, 18 months, nurses, who were assigned to particularly among doctors (Ferrinho et al. staff the clinic on a regular basis, were only 2004). The study also documents an "institu- to be found in the facilities 12 percent of the tionalization" of this phenomenon: Mozam- time. The record of absences, and therefore bican health workers report the existence of closure of facilities, followed no pattern, informal contracts between private clinics meaning that patients' likelihood of finding a provider was unpredictable, thereby dis- Table 3 Leakage of resources couraging patients from using the facilities in health care or keeping appointments. % of cash/in-kind Resource Country (year) resources leaked category In addition to high absence rates of Kenya (2004) 38 Non-salary budget health-care workers, a number of studies suggest that quality and effort on the job Tanzania (1999) 41 Non-salary budget is very low. Using direct clinic observation Uganda (2000) 70 Drugs and supplies and vignettes, Das and Hammer (2005) and Ghana (2000) 80 Non-salary budget Leonard and Masatu (2005) provide a sense Chad (2004) 99 Non-salary budget of the magnitude of the problems of low Source: Gauthier (2006). quality and effort in health care.18 Drawing Silent and lethal: How quiet corruption undermines Africa's development 11 and public hospitals to ensure a steady sup- in antifreeze (Cohen et al. 2007). Another ply of certain medicines. Results from a sur- study in South Asia (Newton et al. 2001) re- vey of 90 Mozambican health care workers ported that 38 percent of the anti-malarial, corroborate the findings above (Schwallbach artesunate-based products sold on the mar- et al. 2000). ket contained a lower-than-standard quan- tity of active ingredient, drastically reducing Weak regulation of drugs their efficacy. Akunyili (2005) found that Quiet corruption in the regulation of phar- during the 1990s, Nigeria was flooded with maceuticals is rampant and deadly. The effi- counterfeit drugs that, according to some cacy of medication is dependent on the care- studies, accounted for more than 50 percent ful regulation of standards in the production, of drugs sold in drugstores. While specific distribution, and prescription of pharmaceu- statistics are not available on deaths or seri- ticals. Inadequate or weakly implemented ous illnesses caused by fake medicines, an- quality controls can lead to distribution of ecdotal evidence suggests a connection be- poor quality and often counterfeited drugs, tween drug efficacy and number of fatalities. which result in severe health consequences A further consequence of weak regulation including death of the consumers. Cohen et was the total ban of Nigerian-made pharma- al. (2007) document the existence of sev- ceuticals imposed by neighboring countries. eral areas where quiet corruption along the value chain from production to consumption Long-term consequences for health care of pharmaceuticals compromises long-term Even if drugs are stolen and do not reach fa- health. cilities, they may be reaching the target popu- This high vulnerability to corruption de- lation through different channels. Although rives from the specific features of the health the distribution may be inequitable due to sector. Information between consumer and pricing out particular population segments producer is highly asymmetric. The typi- and could possibly be less effective because cal consumer cannot verify in advance the medicines are dispensed by non-trained per- quality of the medication and has to rely on sonnel, this outcome does not necessarily information provided either by the pharma- imply a dramatic worsening of health con- ceutical producer or the health-care provid- ditions in the population. We sidestep this er. Second, the consumer's inability to verify issue by elucidating the link between quiet quality necessitates government regulation. corruption and contemporaneous and long- The great latitude in regulating pharmaceu- term health outcomes and the long-lasting tical quality is sometimes abused by regula- beliefs of health service users. tors, either directly as a result of low effort While there are few micro-level stud- or indirectly through inducements by drug ies that demonstrate a causal link between producers or distributors. quiet corruption in health care and poor For example, pharmaceutical companies health outcomes, a number of cross-country should follow specific protocols defi ned by regressions suggest a strong relationship. To the World Health Organization in the pro- establish the link between quiet corruption duction and distribution of medication.19 and long-term consequences, a useful start- Failure to comply with mandated procedures ing point is research that has estimated the for handling raw materials and storing, pack- long-run consequences of malaria eradica- aging, and labeling products compromises tion (Cutler et al. 2007), famine, and low the quality of the product. Low effort or cap- birth weight on long-term labor market con- ture of the regulatory authority implies that sequences (Almond et al. 2006), and cohort these regulations are weakly or selectively studies in the United Kingdom and United enforced, which results in the selling of sub- States that examined the effects of low birth standard and sometimes harmful products. weight on cognitive skills and long-term A number of examples highlight the wellbeing--the so-called Barker hypothesis costs of weak regulatory systems. In 1995 (Barker et al. 1995; Barker 1998). in Haiti, 89 people died after using Paraceta- Cross-country research has demonstrat- mol (acetaminophen) cough syrup prepared ed a negative association between country- with diethylene glycol, a toxic chemical used level measures of corruption and health 12 Africa Development Indicators 2010 care indicators. To the extent that country- consequences. Two recent pieces of evidence level corruption is linked to quiet corruption confirm the link between contemporaneous through the "mirror effect" described in the quiet corruption and birth outcomes. Gold- introduction, these results potentially re- stein et al. (2009) found that absence of a flect the effects of quiet corruption. Gupta, nurse responsible for pre- and post-HIV-test Davoodi, and Tiongson (2000) showed that counseling has a great impact on whether corruption indicators are positively associ- prenatal care patients in Kenya are tested ated with child and infant mortality, the for HIV. In addition, they found that women likelihood of an attended birth, immuniza- who are not tested and counseled are more tion coverage, and low birth weight. Closer likely to give birth without a professional to one of the forms of quiet corruption de- attendant, less likely to receive preventive fined above, Rajkumar and Swaroop (2008) mother-to-child transmission medication, found that the effectiveness of public health and less likely to breastfeed their babies.20 spending in reducing child mortality de- They concluded that reducing absenteeism pends crucially on the perception of higher in public health facilities could reduce ver- government integrity. Wagstaff and Claeson tical transmission of HIV by 0.5­1.5 infec- (2004), replicating a Filmer, Hammer, and tions per 1000 live births. Pritchett (2000) study using more recent The second piece of evidence comes from data, found that public spending reduces an intervention inspired by World Develop- under-five child mortality only where gov- ment Report 2004 (World Bank 2003). Bjork- ernance is good, as measured by the World man and Svensson (2007) document the re- Bank's Country Policy and Institutional sults of a report card intervention in Uganda Assessment (CPIA) score. This study specifi- in which beneficiaries were provided with in- cally explored the implications of additional formation on the performance of their public spending for reaching the MDGs, and con- facility in relation to regional and national cludes that more spending in medium and standards. The impact of the report card was low CPIA countries would not reduce child stunning. It raised both the level of health mortality and that per-capita income growth service utilization and provider attendance offers a better investment if mortality de- and, consequently, reduced infant mortality clines are the objective. by one-third, increasing birth weight, and Micro evidence is more specific, enabling improving other health outcomes. a richer description of how quiet corruption The link between these two pieces of evi- in health translates into poor service deliv- dence and long-term consequences is drawn ery and documentation of some of the direct from cohort studies primarily in developed and indirect long-term consequences listed countries that document long-term conse- in Figure 2. Indirect evidence of the link quences of low birth weight and short stat- between service utilization and health out- ure during early childhood with long-term comes comes from a study in Uganda that cognitive and health outcomes. Height at age estimated the effect of banning user fees on three, which is a function of nutrition and utilization and morbidity (Deininger and health during infancy, affects cognitive skills Mpuga 2004). In addition to direct effects in adulthood (Case, Lubotsky, and Paxson on service utilization, quiet corruption alters 2002). Other studies, such as Almond, Chay, the beliefs of households about the efficacy and Lee (2005), demonstrate a link between of treatments obtained in public facilities. mothers' health during gestation and long- Such beliefs reinforce lower service utiliza- term health and labor market outcomes of tion in preference for traditional, sometimes the children (for a review of these and other life-threatening, interventions. studies, see Smith (2009). Assuming that Given the importance of physical and the same mechanisms operating in these de- cognitive development during a child's ges- veloped countries also apply to developing tation and early years, quiet corruption that countries, quiet corruption in health care affects the utilization of key inputs such as that particularly affects early childhood out- prenatal and post-natal care, immunization, comes has large and long-lasting effects on and the treatment of infant and child infec- the competitiveness of an economy and the tions is likely to have far-reaching, long-term well-being of its citizens. Silent and lethal: How quiet corruption undermines Africa's development 13 Private Sector and Agriculture five fi rms expected to make informal pay- This section describes the long-term conse- ments to obtain government services. quences of quiet corruption in the private While many of these payments tend to sector and agriculture, areas with a high be small, their high frequency makes them potential to contribute to economic growth a considerable cost for fi rms. For example, and poverty reduction in Africa. While the Svensson (2003) reported that among prevalence of informal payments for ser- Ugandan firms that paid bribes, the average vices is widely documented for the private amount of informal payments was equiva- sector, evidence for quiet corruption in both lent to US $8,280 (a median US $1,820), cor- the private sector and agriculture is sparse. responding to nearly 8 percent of the firms' Although enterprises are the immediate vic- total costs (1 percent at the median). tims of corruption, our contention is that In the last column in Table 4, a large they do not always bear the ultimate burden fraction of fi rms report that corruption is because they can often pass on any increased a major impediment to firm operations and costs to consumers.21 growth. While it is hard to say how much of A growing body of evidence on the prev- the firms' expectations of having to make in- alence of quiet corruption in the private sec- formal payments are captured by this mea- tor draws from recent surveys of fi rms in sure or the extent to which other business developing countries. Both the fi rms' expe- environment factors are more important rience of actual petty corruption and their constraints, this category likely incorpo- perception of corruption as an impediment to rates forms of quiet corruption. The last row firm operations were elicited on the survey. (Spearman Correlation) reports the results While these two sets of questions shed light of the comparison between the corruption on the extent and severity of petty corrup- measures. The Spearman index 22 reveals a tion, the prevalence of quiet corruption has positive correlation between incidence mea- been difficult to document. However, a care- sures and the perceived one. Yet, none of ful examination of the survey data is indica- the associations is statistically significant, tive of the contours of quiet corruption. which suggests that the rankings reflect dis- Table 4 shows results for five corrup- tinct impediments. tion indicators for the sub-Saharan African The discrepancy between perceived cor- countries surveyed. The first four indicators ruption and incidence of corruption has report the likelihood that fi rms make any attracted a great deal of attention from informal payments to obtain licenses, con- scholars and policy makers.23 Quiet corrup- tracts, or other services. The last indicator tion may help explain the divide. As noted measures the extent to which corruption is by Herrera, Lijane, and Rodriguez (2008), a major or severe constraint to the firms' op- perceived corruption partially captures the erations. There is considerable variation in invisible element, notably the uncertainty the extent to which firms expect to make in- stemming from engaging in corrupt trans- formal payments. For example, the share of actions. For firms paying bribes, corrup- firms in Cape Verde, Mauritius, and Namibia tion has an immediate cost in the form of expected to make informal payments is con- illegal payments--petty corruption--but siderably lower than that of the Organisation also an additional cost represented by the for Economic Co-operation and Develop- capriciousness of interaction with public ment (OECD) country average (Investment institutions. Climate Assessment 2009). Nevertheless, a Although corruption can be seen as a large percentage of fi rms expect that they "tax" and might still allow companies to op- will make informal payments to obtain gov- erate normally (Shleifer and Vishny 1993), ernment services and contracts. In nearly the critical difference between a normal tax half the countries (16 of 35), more than 50 and the "corruption tax" is their predictabil- percent of firms reported an expectation of ity. In the fi rst case, fi rms know the level having to make informal payments to "get and frequency of payments. In the case of things done." In particular, in Burkina Faso, corruption tax, capture by decentralized Cameroon, Democratic Republic of Congo, regulatory officials with considerable discre- Guinea, and Kenya, nearly four out of every tion engenders uncertainty about the level 14 Africa Development Indicators 2010 Table 4 Incidence of corruption and perceived corruption in sub-Saharan Africa countries Perceived Incidence of corruption corruption % of firms % of firms expected to pay % of firms % of firms expected to give % of firms informal payment expected to give expected to give gifts to secure identifying to public officials gifts to get an gifts in meetings a government corruption as a (to get things done) operating license with tax officials contract major constraint Angola (2006) 46.8 10.08 14.84 38.45 36.06 Benin (2004) 57.65 41.25 21.21 75.43 83.85 Botswana (2006) 27.62 3.29 4.47 22.92 22.58 Burkina Faso (2006) 86.96 0 19.51 80.77 53.96 Burundi (2006) 56.46 40.26 22.63 44.36 19.72 Cameroon (2006) 77.6 50.81 65.43 85.23 52.05 Cape Verde (2006) 5.63 0 10.42 14.08 16.33 Congo, Dem. Rep. (2006) 83.79 66.25 64.42 80.54 20.02 Congo, Rep. (2009) 49.21 42.79 37.1 75.18 65.02 Côte d'Ivoire (2009) 30.64 31.8 13.62 32.34 74.99 Ethiopia (2006) 12.42 2.7 4.35 11.8 23.08 Gabon (2009) 26.09 0 22.81 26.61 41.35 Gambia, the (2006) 52.42 23.42 13.56 50.3 9.78 Ghana (2007) 38.77 22.6 18.08 61.23 9.86 Guinea (2006) 84.75 51.87 57.34 74.58 47.66 Guinea-Bissau (2006) 62.72 15.33 22.7 48.41 44.01 Kenya (2007) 79.22 28.75 32.25 71.2 38.35 Lesotho (2009) 13.96 3.34 9.2 26.37 46.71 Liberia (2009) 55.22 49.63 54.42 51.59 31.19 Madagascar (2009) 19.2 18.6 6.79 14.13 42.71 Malawi (2006) 35.65 4.92 15.33 12.26 46.84 Mali (2007) 28.88 24.04 31.08 80.35 15.7 Mauritania (2006) 82.12 33.23 48.23 76.16 17.1 Mauritius (2009) 1.59 0 0.28 8.81 50.72 Mozambique (2007) 14.84 6.87 9.79 31.65 25.36 Namibia (2006) 11.36 0 2.6 8.08 19.14 Niger (2006) 69.7 8.33 17.05 80 58.54 Nigeria (2007) 40.9 40.29 22.85 44.57 24.7 Rwanda (2006) 19.96 4.58 4.9 14.37 4.35 Senegal (2007) 18.12 21.09 18.66 36.32 23.84 Sierra Leone (2009) 18.8 8.71 8.58 33.85 36.87 South Africa (2007) 15.09 0 3.13 33.2 16.87 Tanzania (2006) 49.47 20.05 14.7 42.69 19.73 Uganda (2006) 51.7 12.86 14.53 46.43 23.57 Zambia (2007) 14.33 2.61 4.89 27.39 12.08 Spearman Correlation Index 0.28 0.15 0.23 0.18 with perceived corruption Source of raw data: www.enterpisesurveys.org. The higher the percentage, the higher the incidence of and perceived corruption. No Spearman coefficient is statistically significant. and frequency of informal payments. For operations. By introducing uncertainty into example, an uncertain number of interac- the cost of regulatory and other publicly pro- tions with the revenue authority or electric- vided inputs, the capture of regulatory and ity provider might be required to continue other services increases the gap between Silent and lethal: How quiet corruption undermines Africa's development 15 actual and perceived corruption. The report- market meets the required chemical com- ed gap between perceived and actual cor- position consistent with extension recom- ruption could be even larger, given that the mendations and that packages sold are of existing fi rms are those that are relatively the right weight. However, even in developed successful in operating in a corrupt environ- countries, where strict laws protect consum- ment. As a result of these selective concerns, ers from adulteration, the verification of Hausmann and Velasco (2005) questioned fraud is a serious problem. This is because it the reliability of fi rm-based perceptions of is often not easy to trace back at which step corruption. They note that a more telling of the production or sale the adulteration indicator is the underlying industrial struc- occurs. To address this problem, a common ture, because responses to quiet corruption strategy of the national agencies (such as the in the private sector include a higher degree U.S. Department of Agriculture) is to require of informalization and a high market con- some form of certification of dealers and centration of formal firms. to conduct spot checks through accredited laboratories. Weak regulation of agricultural inputs Unfortunately, for many countries in Another example of the capture of the regu- sub-Saharan Africa, exercising this type latory function of government that has grave of control might be out of reach. Many lack consequences for reducing poverty and in- qualified laboratories, skilled staff, and tech- creasing economic growth is the market for nical tools for conducting even simple sur- fertilizers. As with the market for pharma- veys. Furthermore, the modalities of product ceuticals, asymmetric information between commercialization represent an obstacle for producers and farmers necessitates public the controls; for example, while in developed regulation. National standards agencies are countries, fertilizers are sold in bags, in Af- supposed to ensure that fertilizer sold on the rica, in part due to the high cost, retail sellers Box 1 Quiet corruption in a port authority in Nigeria The Lagos port in Nigeria represents an interesting case of a poorly offences may abandon goods in the port, wait for "their" goods to regulated business environment that gives way to quiet corruption be auctioned, and then bypass the import regulation to get their episodes. In 2006, the reform of the Lagos port was praised as one goods at a relatively low price. In the second scenario, an importer of the best in sub-Saharan Africa in the last decade. Within a few makes a false declaration including an undervaluation of declared months of operation under private ownership, productivity had risen goods and decides when caught to abandon the consignment in at the container terminals. Chronic delays for berthing space had order to obtain the goods through auction, which, in any case, is nearly vanished, leading shipping lines to reduce their congestion cheaper than full payment of import duties with penalty fees for surcharge. However, the benefits of this reform did not last long. In false declaration and incidental port charges. In both cases, the February 2009, the Nigerian Ports Authority (NPA) announced a tem- importer needs to be sure that during the auction process, his porary but immediate suspension of ship entry to enable terminals cargo will be assigned to him and not to another, which is where to clear "alarming" backlogs. In addition, for vessels already heading collusion with the Port Authority plays an important role. The result into Lagos, the NPA considered diverting them elsewhere. of the auction has to be known in advance; otherwise the importer How could the situation deteriorate from the post-reform high would not abandon the cargo. to this point in less than three years? Raballand and Mjekiqi (2009) These cases present all the characteristics of quiet cor- attribute it to a customs circular. On June 12, 2008, Customs man- ruption. In an environment where regulations provide several agement issued a circular (Customs Circular No. 026/2008) to dis- loopholes, reckless businessmen with the connivance of public allow the clearance of goods that featured discrepancies such as authorities manage to avoid clearance costs or to import pro- lack of appropriate import clearance documents and false declara- hibited goods. However, the mechanism used, abandonment of tion. This circular, in fact, modified the behavior of some importers/ cargo that is recovered later via a public auction, has conse- customs brokers; priority clearance in favor of goods that were quences, less visible in the short run, that go beyond the direct easily cleared was given, while the others were abandoned in the revenue loss of clearance evasion. As the Nigerian case shows, port. After the publication of this circular, the amount of uncleared the long-run effect is the port congestion and delays in clear- and abandoned cargo started to grow and congestion increased. ance that completely eliminated the benefits of the 2006 reform There are two possible situations that explain cargo abandon- with obvious consequences on the competitiveness of Nigerian ment. Importers of prohibited goods or those with other related producers. 16 Africa Development Indicators 2010 usually open the bags and sell small amounts IFDC (2007) in sub-Saharan Africa, the (about 1­2 kg). This exposes the products to situation doesn't seem to have improved various forms of adulteration, such as addi- substantially. A survey conducted in 2007 tion of sand or substitution of cheaper and (IFDC 2007) documents the share of sam- unsuitable fertilizer that consumers cannot ples of poor-quality fertilizer sold in 10 Af- easily detect. In addition, a particular type rican countries. Column 3 of Table 5 shows of fertilizer adulteration is the addition of the percentage of fertilizers not satisfying heavy metals; varying amounts of arsenic, quality standards. As the table illustrates, cadmium, chromium, lead, and nickel have a considerable share of widely used fertiliz- been found in fertilizer materials in sub- ers, such as NPK or urea, are of insufficient Saharan Africa. These contaminants are dif- quality: they either show a high moisture or ficult to detect but can cause serious harm if low nutrient content or simply are wrongly they get into the food chain. labeled. For typical African farmers, the cost Although there is little evidence of fertil- of fertilizer and improved seeds accounts for izer adulteration in sub-Saharan Africa, there a large share of their resources. At best, the is empirical support for nutrient deficiencies use of defective inputs does not have any ef- in sold fertilizers. A survey of wholesalers fect on yields, and at worst it degrades the by the International Fertilizer Development soil. Voortmann (2009) documents that Center (IFDC 1995) on fertilizer quality in there are even cases of poor application that West Africa found that, of the 80 fertilizers cause declining yields. analyzed, 43 percent lacked the appropriate Similar lax regulation has been reported nutrients. Of the 685 bags sampled, only 58 for other key inputs such as improved seeds. percent were within a negligible range of the In this regard, survey evidence is non-exis- indicated weight. In addition, 20 percent of tent and anecdotes from experts and other the bags sampled did not have information actors are the only window to misconduct on the type and concentration of nutrients. in this area. For example, the lack of control Furthermore, in only 7 percent of the cases enabled a dishonest company in Zimbabwe did the labels contain the complete address to buy sorghum grain from a late maturing of the responsible party. To compound the variety and sell the same as an early matur- farmers' problem, the IFDC report suggests ing variety. The use the late maturing variety that frequent cases of deliberate adultera- did not provide any grain unless the season tion occur at the retail level where sellers was unusually long and completely jeopar- can easily add deleterious or harmful ingre- dized the harvest of many farmers. dients to increase the weight and sell under- While there is no reliable empirical weight items or even completely misbranded evidence, misconduct that undermines the products. quality/suitability of agricultural inputs Episodes of mislabeled fertilizers sold likely has important implications for agri- at retail level were documented in Mali dur- cultural productivity. Some recent empirical ing the 1990s, when the country started to evidence is suggestive. Initial randomized import low-cost, but poor quality, stocks from Nigeria (Morris et al. 2007) and more Table 5 The prevalence of substandard fertilizers in West Africa recently in Zimbabwe (Djurfeldt et al. 2005). A recent survey on fertilizers in Kenya (GDS Product Total samples Deficient samples Percentage 2005) shows that adulteration and sales of Urea 50 4 8 counterfeit products are isolated events. Ammonium sulphate 7 2 28.6 Nonetheless, among the products sold on Calcium ammonium nitrate (CAN) 9 3 33.3 the market, the survey documents a wide Triple super phosphate (TSP) 4 0 0 fluctuation in the nitrogen and phosphorus Muriate of potash (MOP) 2 0 0 concentration, often not reported on the la- Diammonium phosphates (DAP) 19 1 5.3 bels. Furthermore, about 3 to 5 percent of Nitrogen phosphorus potassium (NPK) 54 19 35.2 fertilizers are deliberately mislabeled in or- Total 145 29 20 der to sell inferior quality fertilizers. On the basis of anecdotal evidence and Note: One sample of ammonium nitrate is excluded. Source: IFDC (2007). a more recent analysis conducted by the Silent and lethal: How quiet corruption undermines Africa's development 17 experiments to measure the impact of fertil- by producers. Auriol, Flauchelm, and Straub izer and improved seeds on yields of maize (2009) showed that, in sectors producing in Western Kenya found no impact as a re- goods for more corrupt public institutions, sult of defective seed or fertilizer. The most the formal sector is dominated by a few large recent results of randomized evaluations in firms. These big formal players recoup the the same area, which show that higher than additional costs resulting from bribery by suggested levels of fertilizer use are the marking up prices and passing these costs on most cost-effective, could possibly reflect to consumers. Furthermore, thanks to their ineffective enforcement of standards (Duflo, network of relationships with politicians, Kremer, and Robinson 2008). these big firms are able to obtain favorable access to inputs such as credit (Khwaja and Long-term consequences for the Mian 2005; Li et al. 2008) or obtain a system private sector and agriculture of regulations biased against new entrants Quiet corruption modifies the structure of that de facto preserves their dominant posi- incentives for entrepreneurs and farmers tion, or both. Hence, the long-run indirect to conduct business, which permanently consequences of quiet corruption are a less alters their current and future investment dynamic economy in which consumers face decisions. Moreover, as discussed below, the higher prices. negative effects go beyond the single perfor- Evidence for the impact of corruption on mance of individual entrepreneurs or farm- increasing the degree of informalization of ers. In the case of firms, quiet corruption acts markets comes from the most recent Invest- as an additional fixed cost that pushes many ment Climate Assessment data (2006­2009) companies out of the market or to the infor- (World Bank 2009).25 In the latest round of mal sector, leaving the most lucrative activi- interviews, entrepreneurs were asked to re- ties to a few large firms that are well connect- port the existence of informal competitors ed with public authorities.24 A recent paper in their markets by responding yes or no on Paraguay illustrates the effects of capture to the question, "Does this establishment of the regulatory function of government compete against unregistered or informal Box 2 Quiet corruption in public utilities In state-owned utilities providing power, telephone, and water Distribution losses take place when utilities fail to adequately services, quiet corruption takes a variety of forms including over- maintain distribution networks and, in addition, tolerate clandes- manning, undercollection of bills, and distribution losses. Recent tine connections, which amount to theft of scarce energy and estimates suggest that these forms of quiet corruption cost Africa water resources. African power utilities typically lose 23 percent some US $5.7 billion a year on aggregate, or just short of 1 percent of their energy in distribution losses. Similarly, African water utili- of GDP (Foster and Briceno-Garmendia 2009). ties typically lose 35 percent of their water in distribution losses, Over-manning takes place when state-owned enterprises retain nearly twice the 20 percent benchmark. These losses amount to more employees than is strictly necessary to discharge their func- US $1.8 billion a year, or 0.3 percent of GDP. tions, often because of political pressure to provide jobs for mem- bers of certain interest groups. Over-manning is found to be par- ticularly material in the case of state-owned telephone incumbents, Table Distribution losses, undercollection, and which amount to US $1.5 billion a year, or 0.2 percent of GDP. over-manning costs as a percentage of GDP in sub-Saharan Africa's energy, information These enterprises have on average only 94 connections per em- and communications technologies (ICT), and ployee, compared to developing-country benchmarks of 420 con- water and sanitation services (WSS) sectors nections per employee, an over-employment ratio of 600 percent. Energy ICT WSS Total Undercollection of bills is a result of lack of effort on the part Distribution losses 0.2 -- 0.1 0.3 of revenue collection officers or their petty corruption in collusion Undercollection 0.3 -- 0.1 0.4 with consumers and is most frequently due to non-payment of bills Over-manning 0.0 0.2 0.0 0.2 by government departments. This problem is prevalent in power Total 0.5 0.2 0.2 0.9 and water utilities, where non-payment can be found across the income spectrum and carries an overall cost of US $2.4 billion a Source: Foster and Briceno-Garmendia (2009). year, or 0.4 percent of GDP. 18 Africa Development Indicators 2010 firms?" Table 6 presents the association be- Table 6 Correlation between perceived market informalization and incidence of perceived corruption tween the degree of informalization of the market with perceived and experienced cor- % of firms expected to give gifts % of firms identifying corruption in meetings with tax officials as a major constraint ruption. To improve comparisons, the sam- Total ­0.1011** ­0.1256** ple is disaggregated by manufacturing and Manufacturing ­0.0955** ­0.0935** nonmanufacturing status and by the num- Non-manufacturing ­0.1100** ­0.1319** ber of regular employees. A negative correla- No. of employees: 1­6 ­0.1368** ­0.0822** tion indicates that as corruption increases, No. of employees: 7­9 ­0.0894** ­0.1937** so does the degree of informalization (infor- No. of employees: 10­15 ­0.1060** ­0.2136** malization is a yes/no question; yes= 0 and No. of employees: 16­35 ­0.1354** ­0.1412** no=1)). No. of employees: over 35 ­0.1079** ­0.0291 Table 6 shows that informalization is correlated with both perceived and expe- **Significant at 5% rienced corruption, suggesting that cor- Source of raw data: ICA (2009). ruption effectively acts as an entry barrier: many firms unable to afford extra costs are forced to remain in the informal market. prices covering 11 routes and 7 countries.27 Th is barrier applies in particular to fi rms Their analysis showed that prices in the with fewer than 35 employees and the retail main corridors in Africa were higher than in and services sectors where rates of informal- other regions. Furthermore, most of these ity are higher. prices were not supported by the underlying While there is evidence of market con- structure of costs, since the transport sec- centration in Africa, only a few cases docu- tor is labor-intensive and wages in Africa ment the effect of corruption on market are relatively low. For example, in 2007, in structure.26 Fafchamps (2004) fi nds that a China, the average transport price was 5 US small group of well-connected traders cap- cents per ton-kilometer, while in Africa in tures the most lucrative markets, leaving the the Durban-Lusaka corridor it was 6 cents, 8 remainder to small, inefficient firms that are cents for the Mombasa-Kampala route, and unable to scale up and challenge these trad- 11 cents for the Douala-Ndjaména corridor. ers' dominant position. In addition, the so- Given that the underlying costs of providing cial network these big firms create plays an these services are not higher than in China, important role by limiting competition from the only plausible explanation for the price outsiders. Ramachandran, Shah, and Tata differences is market power. Teravaninthorn (2007) are more direct in describing this and Raballand specifically considered the capture as a "capacity of lobbying"; although cost of corruption and found two crucial generally less efficient, these large, formal results. The "corruption tax" in the form of firms are better connected, thus protecting levies that policemen and custom officials their high profit margins by resisting exter- charge is significant in West Africa. Such nal competition. It follows that, although costs account for about 20 to 27 percent of African markets were broadly liberalized in variable operating costs in some corridors, the 1980s and 1990s, a few enterprises with although this "tax" is almost insignificant in high market share were able to retain their Eastern and Southern Africa (1 percent). Yet, market power by investing resources in their this is only the visible part of corruption, relationships with the government. Thus the measurable component. Much more im- quiet corruption acts as a constraint on the portant is the untraceable part represented competitiveness of African manufacturing by the extra costs transport companies face and the growth and poverty reduction ben- when dealing with allocation of freight. It efits of private-sector development. goes without saying that often these "extra In addition to reinforcing a non-dynamic costs" are not charged in exchange for any private sector, quiet corruption in the trans- service but are explicitly imposed to create port sector further diminishes the prospects an entry barrier to potential competitors. In- of African manufacturing. Th is is shown by siders, often well connected with the ruling Teravaninthorn and Raballand (2008), who regimes, thus compensate for these costs by constructed a dataset of transport costs and imposing very high markups on prices and Silent and lethal: How quiet corruption undermines Africa's development 19 enjoy all the benefits of a monopoly. Th is may even damage crops. Hence, in the long ultimately enables truckers and freight for- run, farmers that fi nd no increase in yields warders to pass on much of these additional or find decreases may be driven to reduce or costs to final users. even completely avoid using fertilizers, turn- While empirical evidence of the trans- ing to a low-input type of agriculture. Th is port case of quiet corruption described type of agriculture, as widely documented in above is difficult to find, a striking example literature, is bound to produce low yield and of transport market reform in Rwanda after is more exposed to natural shocks. 1994 sheds light on the potential gains that arise from thoroughly addressing the prob- Final remarks lems quiet corruption can generate. After a It is becoming widely accepted that improv- radical reform of the transport sector that ing service delivery to the poor is both a eliminated entry barriers to the transport widespread political demand and central to market, prices declined by more than 30 the realization of the MDGs. Improving gov- percent in nominal terms and almost 75 per- ernance is integral to achieving these goals. cent in real terms. Th is result can be largely Where transparency and accountability attributed to elimination of quiet corrup- mechanisms are weak or lacking, poor peo- tion in the transport sector, since no major ple are often marginalized and development investment in infrastructure was carried out outcomes suffer. This essay attempts to un- during this period in Rwanda. veil the iceberg that threatens to sink Africa's As with the health care and education efforts to improve well being and growth by sectors, more investment in the transport documenting a broadened scope of corrup- sector does not necessarily mean that ser- tion beyond the behaviors recently brought vice conditions improve. In fact, the case of to light by innovative survey tools and in- transport reform in Rwanda clearly reveals spired by World Development Report 2004. As that seriously addressing the effect of quiet discussed, some of these behaviors are not corruption, that is the cartelized market readily observed or are difficult to measure, structure of the trucking industry, might but their long-term consequences are often induce effective gains that eclipse any other severe and cannot be ignored by policy mak- potential benefit arising from a pure increase ers, citizens, international institutions, and in expenditures. Teravaninthorn and Rabal- donor organizations. land (2008) noted that, although the condi- Th is essay outlined a framework to un- tion of African roads is worse than those in derstand the nature and impact of quiet other parts of the world, an investment in corruption, which captures the implicit and their improvement is not necessarily bound less tangible forms of corruption. The quiet to succeed in transport price reduction. corruption approach embraces the recogni- Moving on to the long-term effects of tion that government spending on social quiet corruption on farmers' investment services alone is not sufficient to understand decisions, two main triggers can be iden- the quantity and quality of public services or tified. In the fi rst case, farmers indirectly the determinants of public service delivery pay the cost of the corruption tax that performance. Th is approach looks at issues emanates from other sectors. As explained that are complementary to the more visible earlier, markets in Africa are generally not forms of corruption and have broad implica- competitive and the market of agricultural tions for strategies and policies that focus inputs is not an exception. To the contrary, on results. these products are often imported (Svensson Examples of the existence and conse- 2003), which leads to even higher informal quences of quiet corruption--such as the payments. The high prices of fertilizer force case of low teacher instruction time that the minority of farmers that purchase fertil- leads to poor competencies and ends with izer to use it in rather small doses. the decision of households to disenroll a As pointed out earlier, lax regulation of child--highlighted how quiet corruption fertilizer quality compounds the affordabil- can lead to substantial long-term impacts ity problem and often leads to a negligible on poverty. The good news is that quiet impact on yields; poor quality fertilizers corruption can be tackled. The report card 20 Africa Development Indicators 2010 example from Uganda--in which beneficia- operationally effective responses at the sec- ries were provided with information from tor level, and good policies and institutions. the second generation of corruption indi- Equally important is more transparency and cators on the performance of their public increasing accountability and participation health facility in relation to regional and na- by citizens, the "demand side" for good gov- tional standards and its impacts on the level ernance. Success will also require the estab- of health service utilization and provider lishment of strategies for addressing weak- attendance--confirms this. nesses in existing governance capacity and Progress in service delivery has been pos- accountability in the delivery of services. sible because of the increasing determination Strengthening enforcement and administra- of governments to deal with corruption, as tive control, management of public finance, well as the increasing availability of infor- government decentralization, systematic mation on finances, inputs, outputs, pricing, dissemination of information about projects and oversight of public service provision by and budgets, and investments in human civil society, which are being used to gener- capital are also essential. Successful imple- ate information on performance and to track mentation of anticorruption reforms will absenteeism, leakage of funds, and informal also require that the preferences of all those user fees. The way forward, however, will re- involved be aligned with achieving the ob- quire the development of a third generation jectives or goals of the reform. This often in- of indicators--ones that measure quality of volves better working conditions. services and the performance of service pro- Of course, given the complexity of the viders. A recent intervention to improve edu- task, the fight against quiet corruption re- cation services in Uttar Pradesh highlights quires tailoring policies to country circum- the features that new projects and programs stances, recognizing that priorities and need to incorporate (Banerjee et al. 2008). By responses may vary depending on the differ- teaching households with very little school- ent country conditions. This essay outlines ing to identify children who are struggling in a research agenda to identify interventions school, the intervention empowered house- to address quiet corruption. Experimenting holds to evaluate service quality. with various ways to empower beneficiaries As quiet corruption manifests different- and continuing the ongoing efforts to tackle ly in each economic sector, there is no "one big-time corruption will go a long way to- size fits all" recommendation that applies ward this goal. Indeed, although combating to each and every sector. But vital to fight- loud corruption is necessary, fighting quiet ing quiet corruption at large are strong and corruption is critical if governments want highly motivated leadership, commitment of to reduce poverty and promote sustainable the national anticorruption units to pursue growth. Silent and lethal: How quiet corruption undermines Africa's development 21 Notes 1. See, for example, Rajkumar and Swaroop (2008) fact, the evidence on the relationship between and Amin, Das, and Goldstein (2009). performance pay and teacher absence is quite mixed. Duflo, Hanna, and Ryan (2008) find a posi- 2. Gupta, Davoodi, and Tiongson (2000) show that cor- tive effect on attendance of a pay-for-inputs per- ruption is associated with higher levels of infant mor- formance contract in non-formal schools in India. tality and school dropout and lower birth weight. On the contrary, Glewwe, Kremer, Moulin, and Zitzewitz (2004) and Muralidharan and Sundara- 3. Early evidence of negative association between man (2006) do not find evidence of a teacher at- political corruption and development comes from tendance response to output-based performance Mauro (1995) and Kaufmann and Wei (1999). For pay. the negative relationship between corruption and the capacity to attract foreign direct investments, 13. Since direct observation requires enumerators to see Wei (2000). Tanzi (1998) reviews some of the physically establish attendance, the presence of an evidence and finds support that corruption is as- outsider in a school could be driving some of these sociated with lower government revenue receipts "in-school effort" measures and therefore casting and also alters the composition of public spend- some doubt over the validity of these estimates. ing away from productive sectors. Other evidence In addition, they could be affected by the fact that comes from Baldacci et al. (2004) and Gupta et al. different pedagogical styles entail different levels (2000). A recent strand of literature has extended of direct teacher-pupil interaction. this analysis to examine the extent to which these relationships are affected by institutional quality or 14. PETS have some important limitations in only be- the level of corruption (Meon and Sekkat 2005; ing able to define leakage unambiguously for fund- Mendez and Sepulveda 2006; Aidt 2009). ing flows with clear rules, such as teacher salaries or capitation grants. Given that some important 4. See Scott (1972) for a broad overview of the vari- resource flows in some education systems are not ous forms of political corruption. rule-based, it is difficult to accurately characterize the extent of leakage. 5. Harsch (1993); Wunsch (2000). 15. There is evidence of an association between the 6. See Olson (1965). frequency of inspection and the level of teacher absenteeism (see Chaudhury 2006). 7. See Harsch (1993). 16. The Health Unit Management Committees were 8. See Hirshmann (1970) in this regard. established with the objective of overseeing the management of the public health facility. It con- 9. Recent Annual School Censuses use a similar sists of public health providers together with mem- head-teacher reported measure of absence. bers of the community. 10. The 2002 data come from Chaudhury et al. 17. Evidence of the perception of absenteeism in par- (2006), while the 2007 estimate is from Habya- ticular in Latin America corroborates these find- rimana (2007). ings. Surveys of hospital nurses' perceptions of the frequency of chronic absenteeism among doc- 11. Two districts in western Kenya. tors reported rates of 98 percent in Costa Rica, 30 percent in Nicaragua, 38 percent in Colombia 12. This result suggests that low teacher remuneration (Giedion, Morales, and Acosta 2001) and 24­31 is not a major determinant of teacher absence. In percent across public and social security hospitals Notes 23 in Argentina (Schargrodsky, Mera, and Weinschel- one indicator occur along with higher magnitudes baum 2001). in the other indicator, the two rankings reflect dis- tinct sources of impediments. 18. Vignettes are hypothetical cases presented to doctors in order to estimate doctor quality. Doctor 23. In this regard it is worth mentioning the contribu- questions, diagnostics, and prescriptions are com- tions from Kaufmann and Kraay (2007), Gelb et al. pared to expert panels or existing protocols. (2007), and Gonzalez et al. (2007). 19. The so-defined "good manufacturing practice." 24. The issues of political lobbying and corruption that are focused on obtaining privileged access to rent- 20. WHO guidelines on breastfeeding have been re- seeking activities and the economic and social laxed to accommodate the poor availability or suit- costs of rent-seeking are broadly treated in the ability of formula. literature. See, for example, Baghawati (1982) and Krusell and Rios-Rull (1996). 21. The ability to pass on corruption-related costs to consumers is subject to, among other factors, the 25. For an interesting case of high market informaliza- demand conditions and market structure. tion caused by corruption, see Auriol et al. (2009) on Paraguay. 22. Spearman's rank correlation coefficient is used to analyze the correspondence between the ranking 26. See Biggs and Srivastava (1996) and Van Biese- defined by incidence of corruption measures and broeck (2005). the ranking obtained by the perceived corruption measure. A positive but insignificant rank correla- 27. Burkina Faso, Cameroon, Chad, Ghana, Kenya, tion suggests that, although higher magnitudes in Uganda, and Zambia. 24 Africa Development Indicators 2010 References Aidt, T. 2009. "Corruption, Institutions, and Economic Programs: Evidence from a Randomized Evaluation Development." 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National and fiscal accounts 2.1 Gross domestic product, nominal 38 2.2 Gross domestic product, real 39 2.3 Gross domestic product growth 40 2.4 Gross domestic product per capita, real 41 2.5 Gross domestic product per capita growth 42 2.6 Gross national income, nominal 43 2.7 Gross national income, Atlas method 44 2.8 Gross national income per capita, Atlas method 45 2.9 Gross domestic product deflator (local currency series) 46 2.10 Gross domestic product deflator (U.S. dollar series) 47 2.11 Consumer price index 48 2.12 Price indexes 49 2.13 Gross domestic savings 50 2.14 Gross national savings 51 2.15 General government final consumption expenditure 52 2.16 Household final consumption expenditure 53 2.17 Final consumption expenditure plus discrepancy 54 2.18 Final consumption expenditure plus discrepancy per capita 55 2.19 Gross fixed capital formation 56 2.20 Gross general government fixed capital formation 57 2.21 Private sector fixed capital formation 58 2.22 External trade balance (exports minus imports) 59 2.23 Exports of goods and services, nominal 60 2.24 Imports of goods and services, nominal 61 2.25 Exports of goods and services as a share of GDP 62 2.26 Imports of goods and services as a share of GDP 63 2.27 Balance of payments and current account 64 2.28 Exchange rates and purchasing power parity 66 2.29 Agriculture value added 68 2.30 Industry value added 69 2.31 Services plus discrepancy value added 70 2.32 Central government finances, expense, and revenue 71 2.33 Structure of demand 75 Part II. Millennium Development Goals 3. Millennium Development Goals 3.1 Millennium Development Goal 1: eradicate extreme poverty and hunger 76 3.2 Millennium Development Goal 2: achieve universal primary education 79 3.3 Millennium Development Goal 3: promote gender equality and empower women 80 3.4 Millennium Development Goal 4: reduce child mortality 81 3.5 Millennium Development Goal 5: improve maternal health 82 3.6 Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases 83 Indicator tables 31 3.7 Millennium Development Goal 7: ensure environmental sustainability 85 3.8 Millennium Development Goal 8: develop a global partnership for development 87 Part III. Development outcomes Drivers of growth 4. Private sector development 4.1 Doing Business indicators 89 4.2 Investment climate 92 4.3 Financial sector infrastructure 94 5. Trade and regional integration 5.1 International trade and tariff barriers 96 5.2 Top three exports and share in total exports, 2007 100 5.3 Regional integration, trade blocs 102 6. Infrastructure 6.1 Water and sanitation 104 6.2 Transportation 105 6.3 Information and communication technology 107 6.4 Energy 109 Participating in growth 7. Human development 7.1 Education 111 7.2 Health 113 8. Agriculture, rural development, and environment 8.1 Rural development 117 8.2 Agriculture 119 8.3 Environment 121 8.4 Fossil fuel emissions 124 9. Labor, migration, and population 9.1 Labor force participation 126 9.2 Labor force composition 128 9.3 Unemployment 130 9.3 Migration and population 132 10. HIV/AIDS 10.1 HIV/AIDS 134 11. Malaria 11.1 Malaria 138 12. Capable states and partnership 12.1 Aid and debt relief 139 12.2 Status of Paris Declaration indicators 142 12.3 Capable states 144 12.4 Governance and anticorruption indicators 146 12.5 Country Policy and Institutional Assessment ratings 148 12.6 Polity indicators 152 32 Africa Development Indicators 2010 Users guide Tables and Institutional Assessment ratings are pro- The tables are numbered by section. Coun- vided for later years (usually 2009­10). tries are listed alphabetically by subregion (Sub-Saharan Africa and North Africa). In- Data consistency, reliability, dicators are shown for the most recent year and comparability or period for which data are available and, in Considerable effort has been made to harmo- most tables, for an earlier year or period (usu- nize the data, but full comparability cannot ally 1980, 1990, or 1995). Time series data be assured, and care must be taken in inter- are available on the Africa Development In- preting indicators. Many factors affect data dicators CD-ROM and ADI Online. The term availability, comparability, and reliability. country, used interchangeably with economy, Data coverage may be incomplete because does not imply political independence but of circumstances affecting the collection and refers to any territory for which authorities reporting of data, such as conflicts. Although report separate social or economic statistics. drawn from sources thought to be the most Known deviations from standard definitions authoritative, data should be construed as or breaks in comparability over time or across indicating trends and characterizing differ- countries are footnoted in the tables. When ences across economies. Discrepancies in available data are deemed too weak to pro- data presented in different editions of Africa vide reliable measures of levels and trends Development Indicators reflect updates from or do not adequately adhere to international countries as well as revisions to historical standards, the data are not shown. series and changes in methodology. Readers are therefore advised not to compare data se- Aggregate measure for region ries between editions or across World Bank and subclassifications publications. The aggregates are based on the World Bank's regional classification for Sub-Saharan Af- Classification of economies rica and North Africa, which may differ from For operational and analytical purposes the common geographic usage. Former Spanish World Bank's main criterion for classifying Sahara is not included in any aggregates. economies is gross national income (GNI) per capita (calculated by the World Bank At- Statistics las method; box 1). Every economy is clas- Data are shown for economies as they were sified as low income, middle income (subdi- constituted in 2007, and historical data are vided into lower middle and upper middle), revised to reflect current political arrange- or high income (table 1). Low- and middle- ments. Exceptions are noted in the tables. income economies are sometimes referred Consistent time-series data for 1961­2008 to as developing economies. The term is are available on the Africa Development In- used for convenience; it is not intended dicators CD-ROM and ADI Online. Data for to imply that all economies in the group some indicators, including macroeconomic are experiencing similar development or statistics, Doing Business indicators, invest- that other economies have reached a pre- ment climate indicators, governance and an- ferred or final stage of development. Clas- ticorruption indicators, and Country Policy sification by income does not necessarily Indicator tables 33 Box 1 The World Bank Atlas method for converting gross national income to a common denominator The World Bank uses the Atlas conversion Monetary Fund's unit of account) deflator. The following formulas describe the pro- factor to calculate gross national income The SDR deflator is the average of these cedures for computing the conversion fac- (GNI) and GNI per capita in U.S. dollars for countries' GDP defl ators in SDR terms, tor for year t: certain operational purposes. It reduces the weighted by the amount of each country's impact of exchange rate fluctuations in the currency in one SDR unit. Weights vary cross-country comparison of national in- over time because the SDR's composition comes. The Atlas conversion factor for any and each currency's relative exchange and for calculating per capita GNI in U.S. year is the average of the official exchange rates change. The SDR deflator is calcu- dollars for year t: rate or alternative conversion factor for that lated in SDR terms first and then converted year and the two preceding years, adjusted to U.S. dollars using the SDR to U.S. dollar for differences in relative inflation between Atlas conversion factor. The Atlas conver- the country and Japan, the United King- sion factor is then applied to a country's dom, the United States, and the euro area GNI. The resulting GNI in U.S. dollars is where et* is the Atlas conversion factor (na- averaged together. Inflation is measured by divided by the midyear population for the tional currency to the U.S. dollar), et is the the change in GDP deflator. latest of the three years to derive GNI per average annual exchange rate (national cur- The inflation rate for Japan, the United capita. rency to the U.S. dollar), pt is the GDP de- Kingdom, the United States, and the euro When official exchange rates are flator, ptS$ is the SDR deflator in U.S. dollar area, representing international infl ation, deemed unreliable or unrepresentative of terms, Yt$ is current GNI per capita in U.S. is measured by the change in the spe- the effective exchange rate, an alternative dollars, Yt is current GNI (local currency), cial drawing rights (SDR, the International estimate of the exchange rate is used. and Nt is midyear population. reflect development status. Because GNI applies to only a small number of countries. per capita changes over time, the country Alternative conversion factors are used in composition of income groups may change the Atlas methodology and elsewhere in from one edition of Africa Development Africa Development Indicators as single-year Indicators to the next. Once the classifica- conversion factors. tion is fixed for an edition, based on GNI per capita in the most recent year for which Symbols data are available (2007 in this edition), all .. means that data are not available historical data presented are based on the or that aggregates cannot be cal- same country grouping. culated because of missing data in Low-income economies are those with the years shown. a GNI per capita of $935 or less in 2007. $ means current U.S. dollars unless Middle-income economies are those with a otherwise noted. GNI per capita of more than $935 but less 0 or 0.0 means zero or small enough that than $11,456. Lower middle-income and up- the number would round to zero per middle-income economies are separated at the displayed number of decimal at a GNI per capita of $3,705. High-income places. economies are those with a GNI per capita of $11,456 or more. Data presentation conventions A blank means not applicable or, for an ag- Alternative conversion factors gregate, not analytically meaningful. The World Bank systematically assesses A billion is 1,000 million. the appropriateness of official exchange Growth rates are in real terms, unless oth- rates as conversion factors. An alternative erwise specified. conversion factor is used when the official exchange rate is judged to diverge by an The cutoff date for data is September exceptionally large margin from the rate ef- 30, 2009, except for data on official fectively applied to domestic transactions of development assistance, for which foreign currencies and traded products. This the cutoff date is December 8, 2009. 34 Africa Development Indicators 2010 Table 1 World Bank classification of economies, 2007 Low income Lower middle income Upper middle income High income GNI per capita of GNI per capita higher than GNI per capita of $3,705 GNI per capita of $935 or less $935 and less than $3,705 but less than $11,456 $11,456 and over Benin Algeria Botswana Equatorial Guinea Burkina Faso Angola Gabon Burundi Cameroon Libya Central African Republic Cape Verde Mauritius Chad Congo, Rep. Seychelles Comoros Djibouti South Africa Congo, Dem. Rep. Egypt, Arab Rep. Côte d'Ivoire Lesotho Eritrea Morocco Ethiopia Namibia Gambia, The Sudan Ghana Swaziland Guinea Tunisia Guinea-Bissau Kenya Liberia Madagascar Malawi Mali Mauritania Mozambique Niger Nigeria Rwanda São Tomé and Príncipe Senegal Sierra Leone Somalia Tanzania Togo Uganda Zambia Zimbabwe Source: World Bank. Indicator tables 35 Participating in growth 1.1 Table Basic indicators GDP per capita Net official Constant 2000 prices Life development Land area Average expectancy Under-five Adult literacy rate assistance Population (thousands annual at birth mortality rate (% of ages 15 and older) per capita (millions) of sq km) Dollars growth (%) (years) (per 1,000) Gini index Male Female (current $) 2008 2008 2008 a 2000­08 2007­08 b 2007 2000­07b 2007 2007 2008 SUB­SAHARAN AFRICA 819.3 23,629 624 2.7 51.5 146 .. .. .. 43.6 Excluding South Africa 770.6 22,414 426 3.2 51.6 149 .. .. .. 44.9 Excl. S. Africa & Nigeria 619.3 21,504 410 2.9 52.8 139 .. .. .. 53.7 Angola 18.0 1,247 1,357 10.4 47.3 158 58.6 .. .. 20.5 Benin 8.7 111 359 0.5 61.6 123 38.6 53.1 27.9 74.0 Botswana 1.9 567 4,440 3.2 50.6 40 .. 82.8 82.9 376.1 Burkina Faso 15.2 274 263 2.3 52.2 191 39.6 36.7 21.6 65.6 Burundi 8.1 26 111 0.0 50.6 180 33.3 .. .. 63.0 Cameroon 18.9 465 710 1.3 50.4 148 44.6 .. .. 27.8 Cape Verde 0.5 4 1,632 3.8 71.2 32 50.5 89.4 78.8 438.2 Central African Republic 4.4 623 230 ­1.1 44.7 172 43.6 .. .. 58.0 Chad 11.1 1,259 251 6.7 50.6 209 39.8 43.0 20.8 37.6 Comoros 0.6 2 370 ­0.2 65.1 66 64.3 80.3 69.8 57.9 Congo, Dem. Rep. 64.2 2,267 99 2.4 46.4 161 44.4 .. .. 25.1 Congo, Rep. 3.6 342 1,214 1.8 53.7 125 47.3 .. .. 139.7 Côte d'Ivoire 20.6 318 530 ­1.6 57.8 127 48.4 .. .. 29.9 Djibouti 0.8 23 849 1.6 54.8 127 40.0 .. .. 142.6 Equatorial Guinea 0.7 28 8,692 15.7 50.5 206 .. .. .. 57.1 Eritrea 5.0 101 148 ­2.5 57.9 70 .. .. .. 28.6 Ethiopia 80.7 1,000 190 5.4 55.4 119 29.8 .. .. 41.2 Gabon 1.4 258 4,157 0.1 60.7 91 41.5 90.2 82.2 37.6 Gambia, The 1.7 10 374 2.0 56.1 109 47.3 .. .. 56.5 Ghana 23.4 228 327 3.2 56.8 115 42.8 71.7 58.3 55.4 Guinea 9.8 246 417 1.1 58.1 150 43.3 .. .. 32.4 Guinea-Bissau 1.6 28 128 ­3.3 48.0 198 35.5 .. .. 83.5 Kenya 38.5 569 464 1.9 54.1 121 47.7 .. .. 35.3 Lesotho 2.0 30 525 3.0 42.6 84 52.5 .. .. 71.1 Liberia 3.8 96 148 ­4.5 58.4 133 52.6 60.2 50.9 329.6 Madagascar 19.1 582 271 0.9 60.5 112 47.2 .. .. 44.0 Malawi 14.3 94 165 1.6 48.3 111 39.0 79.2 64.6 63.9 Mali 12.7 1,220 295 2.1 54.3 196 39.0 .. .. 75.8 Mauritania 3.2 1,031 .. 2.2 64.1 119 39.0 63.3 48.3 97.1 Mauritius 1.3 2 4,929 3.3 72.4 15 .. 90.2 84.7 86.4 Mozambique 21.8 786 365 5.6 42.1 169 47.1 57.2 33.0 91.5 Namibia 2.1 823 2,692 3.9 52.8 68 .. 88.6 87.4 97.8 Niger 14.7 1,267 180 0.9 56.9 176 43.9 .. .. 41.3 Nigeria 151.3 911 487 4.0 46.8 189 42.9 80.1 64.1 8.5 Rwanda 9.7 25 313 4.3 50.2 181 46.7 .. .. 95.7 São Tomé and Príncipe 0.2 1 .. .. 65.4 99 .. 93.4 82.7 292.2 Senegal 12.2 193 530 1.7 55.7 114 39.2 .. .. 86.6 Seychelles 0.1 0 8,267 1.3 73.2 13 .. .. .. 139.9 Sierra Leone 5.6 72 262 6.5 47.7 262 42.5 50.0 26.8 66.0 Somalia 9.0 627 .. .. 48.1 142 .. .. .. 84.7 South Africa 48.7 1,214 3,764 3.1 50.5 59 57.8 88.9 87.2 23.1 Sudan 41.3 2,376 532 5.2 58.3 109 .. .. .. 57.6 Swaziland 1.2 17 1,559 1.7 46.4 91 50.7 .. .. 57.7 Tanzania 42.5 886 362 3.9 55.9 116 34.6 79.0 65.9 54.9 Togo 6.5 54 245 ­0.2 62.7 100 34.4 .. .. 51.0 Uganda 31.7 197 348 4.0 53.0 130 42.6 81.8 65.5 52.3 Zambia 12.6 743 387 2.9 45.9 170 50.7 80.8 60.7 86.0 Zimbabwe 12.5 387 .. ­5.7 45.1 90 .. 94.1 88.3 49.0 NORTH AFRICA 163.7 5,738 2,157 3.0 71.1 35 .. .. .. 20.9 Algeria 34.4 2,382 2,191 2.8 72.3 37 .. 84.3 66.4 9.2 Egypt, Arab Rep. 81.5 995 1,784 2.8 70.2 36 32.1 .. .. 16.5 Libya 6.3 1,760 7,740 2.1 74.2 18 .. 94.5 78.4 9.6 Morocco 31.2 446 1,770 3.8 71.1 34 40.9 68.7 43.2 39.0 Tunisia 10.3 155 2,760 4.0 74.3 21 40.8 86.4 69.0 46.4 ALL AFRICA 983.0 29,367 879 2.6 54.8 134 .. .. .. 39.8 a. Provisional. b. Data are for the most recent year available during the period specified. BASIC INDICATORS Part I. Basic indicators and national and fiscal accounts 37 Table 2.1 Gross domestic product, nominal Current prices ($ millions) Annual average growth (%) 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 276,250 300,664 364,492 446,761 551,685 648,327 751,217 864,074 1,003,420 0.7 1.5 16.1 Excluding South Africa 197,062 188,777 253,891 280,236 335,765 405,706 494,058 581,182 728,451 ­1.1 1.1 17.4 Excl. S. Africa & Nigeria 129,282 160,369 194,665 212,440 247,697 293,138 346,595 414,700 515,586 2.3 0.7 15.7 Angola .. 10,260 11,432 13,956 19,775 30,632 45,163 59,263 83,383 .. ­3.8 35.1 Benin 1,405 1,845 2,807 3,558 4,047 4,287 4,623 5,428 6,680 2.3 3.5 14.3 Botswana 1,061 3,792 5,933 8,278 9,827 10,513 11,006 12,324 12,969 12.6 4.4 11.6 Burkina Faso 1,929 3,101 3,290 4,270 5,109 5,427 5,771 6,767 7,948 4.8 0.0 15.1 Burundi 920 1,132 628 595 664 796 919 980 1,163 2.2 ­3.3 7.3 Cameroon 6,741 11,152 10,880 13,622 15,775 16,588 17,957 20,692 23,396 7.3 ­2.5 12.1 Cape Verde .. 339 616 797 925 1,006 1,202 1,447 1,730 .. 6.4 16.6 Central African Republic 797 1,488 1,042 1,139 1,270 1,350 1,477 1,712 1,970 8.1 ­4.3 9.5 Chad 1,033 1,739 1,988 2,737 4,415 5,873 6,300 7,006 8,361 5.7 ­1.3 27.3 Comoros 124 250 251 324 362 387 403 465 530 8.0 ­2.0 12.8 Congo, Dem. Rep. 14,395 9,350 5,548 5,673 6,594 7,239 8,785 9,950 11,588 ­6.2 ­7.1 13.1 Congo, Rep. 1,706 2,799 3,020 3,564 4,343 6,087 7,731 7,646 10,699 2.3 ­2.4 18.6 Côte d'Ivoire 10,175 10,796 11,487 13,737 15,481 16,363 17,367 19,796 23,414 2.0 2.2 10.8 Djibouti .. 452 591 622 666 709 761 818 875 .. 1.7 6.1 Equatorial Guinea .. 132 2,147 2,952 5,241 8,217 9,603 12,576 18,525 .. 22.5 41.3 Eritrea .. .. 675 598 631 1,161 1,282 1,374 1,654 .. 7.2 14.0 Ethiopia .. 12,083 7,790 8,556 10,052 12,305 15,166 19,395 26,487 5.9 ­5.7 16.2 Gabon 4,279 5,952 4,932 6,055 7,178 8,666 9,546 11,568 14,435 ­0.5 ­1.7 15.3 Gambia, The 241 317 370 367 401 461 508 644 782 1.7 3.6 8.0 Ghana 4,445 5,886 6,160 7,624 8,872 10,720 12,715 14,989 16,123 3.2 2.6 17.4 Guinea 6,684 2,667 3,208 3,619 3,938 3,261 3,204 4,564 4,266 ­15.6 3.0 4.0 Guinea-Bissau 111 244 204 236 285 302 317 382 430 3.7 ­0.6 10.2 Kenya 7,265 8,591 13,149 14,904 16,092 18,769 22,479 26,950 34,507 2.6 7.7 13.3 Lesotho 431 577 670 994 1,290 1,376 1,518 1,670 1,622 0.1 3.8 13.2 Liberia 954 384 559 410 460 530 612 735 870 ­0.5 1.8 5.3 Madagascar 4,042 3,081 4,397 5,474 4,364 5,039 5,515 7,347 8,970 ­5.2 3.4 9.0 Malawi 1,238 1,881 2,665 2,425 2,625 2,855 3,164 3,586 4,269 1.8 0.2 11.1 Mali 1,787 2,421 3,343 4,362 4,874 5,305 5,866 6,848 8,740 3.4 0.4 16.8 Mauritania 709 1,020 1,150 1,285 1,548 1,837 2,663 2,644 2,858 3.5 1.4 15.2 Mauritius 1,153 2,383 4,549 5,248 6,064 6,290 6,433 6,786 8,651 7.6 6.7 8.2 Mozambique 3,526 2,463 4,201 4,666 5,698 6,579 7,095 8,011 9,735 ­4.7 8.3 11.9 Namibia 2,169 2,350 3,361 4,934 6,606 7,262 7,979 8,717 8,564 0.1 4.6 14.2 Niger 2,509 2,481 2,170 2,708 2,897 3,330 3,646 4,246 5,354 ­0.2 ­1.8 14.2 Nigeria 64,202 28,472 59,117 67,656 87,845 112,249 146,869 165,921 212,080 ­12.0 3.2 22.5 Rwanda 1,163 2,584 1,641 1,777 1,971 2,379 2,835 3,412 4,457 8.6 ­2.0 12.9 São Tomé and Príncipe .. .. 91 98 107 114 125 145 175 .. .. 11.2 Senegal 3,503 5,717 5,334 6,858 8,030 8,688 9,367 11,299 13,209 6.2 ­1.8 14.3 Seychelles 147 369 698 706 700 884 968 912 833 9.3 6.0 5.6 Sierra Leone 1,101 650 936 991 1,073 1,215 1,423 1,664 1,953 ­4.3 0.6 13.7 Somalia 604 917 .. .. .. .. .. .. .. 6.4 .. .. South Africa 80,710 112,014 110,874 166,654 216,012 242,802 257,730 283,743 276,764 4.1 2.1 13.5 Sudan 7,617 12,409 14,976 17,780 21,684 27,386 36,401 46,228 58,443 10.1 0.8 22.4 Swaziland 543 1,115 1,174 1,796 2,282 2,524 2,670 2,894 2,618 1.9 4.4 11.7 Tanzania .. 4,259 9,758 10,283 11,351 14,142 14,331 16,826 20,490 .. 8.9 10.7 Togo 1,136 1,628 1,476 1,759 2,061 2,108 2,218 2,499 2,823 4.5 ­0.1 10.3 Uganda 1,245 4,304 6,179 6,607 7,924 9,225 9,957 11,892 14,529 20.7 8.8 12.1 Zambia 3,884 3,288 3,716 4,374 5,423 7,157 10,675 11,410 14,314 ­3.1 0.2 22.1 Zimbabwe 6,679 8,784 21,897 7,397 4,712 3,418 .. .. .. ­0.1 ­2.4 ­18.8 NORTH AFRICA 111,546 172,192 225,562 249,580 279,434 322,260 370,254 433,252 563,136 4.8 4.2 11.1 Algeria 42,345 62,045 57,053 68,019 85,014 102,339 116,460 134,304 173,882 4.5 ­1.2 16.4 Egypt, Arab Rep. 22,912 43,130 87,851 82,924 78,845 89,686 107,484 130,476 162,818 6.8 10.8 5.7 Libya .. 28,905 19,195 23,822 30,498 41,743 49,711 58,333 99,926 .. ­0.9 15.6 Morocco 18,821 25,821 40,416 49,823 56,948 59,524 65,637 75,119 86,329 3.7 5.1 11.6 Tunisia 8,743 12,291 21,047 24,992 28,129 28,968 30,962 35,020 40,180 2.3 6.0 9.6 ALL AFRICA 391,472 472,762 589,969 696,175 830,851 970,256 1,121,070 1,296,907 1,566,419 1.9 2.5 14.2 a. Provisional. 38 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.2 Table Gross domestic product, real Constant prices (2000 $ millions) Average annual growth (%) 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 227,428 273,576 367,478 383,138 407,300 430,206 456,824 485,999 510,788 1.8 2.4 5.3 Excluding South Africa 132,111 162,644 226,037 237,297 254,380 269,702 287,820 308,443 327,922 2.1 2.7 5.9 Excl. S. Africa & Nigeria 99,356 127,626 177,831 184,108 195,541 207,687 221,972 238,364 254,170 2.6 2.8 5.6 Angola .. 8,464 10,780 11,137 12,383 14,935 17,707 21,298 24,450 .. 1.0 13.6 Benin 1,084 1,412 2,474 2,571 2,650 2,727 2,831 2,961 3,112 2.7 4.7 3.9 Botswana 1,209 3,395 6,715 7,137 7,604 7,960 8,196 8,544 8,458 10.9 5.6 4.4 Burkina Faso 1,101 1,556 2,915 3,150 3,296 3,505 3,698 3,831 4,002 4.0 5.5 5.6 Burundi 559 865 756 747 783 790 830 860 899 4.5 ­3.2 2.9 Cameroon 6,339 8,793 10,952 11,393 11,815 12,087 12,476 12,913 13,416 4.5 1.3 3.5 Cape Verde .. 303 577 613 608 648 718 768 814 6.3 5.9 5.5 Central African Republic 735 815 956 884 892 914 950 990 1,018 1.6 1.8 0.6 Chad 665 1,106 1,678 1,925 2,572 2,776 2,780 2,786 2,775 6.7 2.3 10.4 Comoros 136 181 217 223 222 232 234 236 238 2.9 1.2 2.0 Congo, Dem. Rep. 7,016 7,659 4,362 4,614 4,921 5,308 5,605 5,956 6,325 2.1 ­5.0 5.5 Congo, Rep. 1,746 2,796 3,503 3,563 3,691 3,975 4,223 4,156 4,388 3.8 0.8 4.0 Côte d'Ivoire 7,727 8,298 10,266 10,106 10,287 10,417 10,488 10,668 10,904 0.7 3.5 0.5 Djibouti .. 660 577 596 619 638 664 693 719 .. ­2.3 3.5 Equatorial Guinea .. 207 2,426 2,764 3,815 4,187 4,239 5,148 5,730 .. 20.7 18.9 Eritrea .. .. 711 692 702 720 713 722 737 .. 7.9 1.3 Ethiopia .. 6,234 8,993 8,798 9,993 11,174 12,387 13,762 15,320 2.1 3.7 8.2 Gabon 3,594 4,298 5,162 5,290 5,361 5,523 5,588 5,899 6,020 0.5 2.9 2.2 Gambia, The 213 305 431 460 493 518 552 587 621 3.5 2.7 5.1 Ghana 2,640 3,267 5,410 5,691 6,010 6,364 6,771 7,184 7,630 2.6 4.3 5.6 Guinea 1,539 2,088 3,372 3,440 3,534 3,651 3,730 3,787 4,105 3.0 4.4 3.1 Guinea-Bissau 115 186 201 186 185 189 196 197 202 3.8 1.4 ­0.9 Kenya 7,078 10,544 13,243 13,631 14,325 15,156 16,126 17,248 17,869 4.1 2.2 4.6 Lesotho 380 542 820 852 891 897 970 1,019 1,059 3.3 4.0 3.9 Liberia 1,391 433 599 411 422 444 479 524 561 ­3.3 0.2 ­1.1 Madagascar 3,099 3,266 3,590 3,941 4,148 4,339 4,557 4,842 5,175 0.8 1.7 3.8 Malawi 1,000 1,243 1,584 1,683 1,779 1,824 1,974 2,143 2,351 2.4 3.8 4.2 Mali 1,536 1,630 2,828 3,039 3,105 3,294 3,469 3,566 3,744 0.5 3.9 5.2 Mauritania 693 816 1,125 1,188 1,249 1,317 1,471 1,499 .. 1.9 2.9 5.1 Mauritius 1,518 2,679 4,846 5,000 5,235 5,475 5,672 5,937 6,254 5.9 5.3 4.1 Mozambique 2,462 2,499 5,173 5,485 5,918 6,414 6,971 7,460 7,942 ­0.9 6.0 8.0 Namibia 2,292 2,591 4,144 4,320 4,850 4,972 5,328 5,544 5,692 1.1 4.0 5.4 Niger 1,523 1,507 1,984 2,071 2,054 2,206 2,334 2,411 2,640 ­0.4 2.4 4.4 Nigeria 31,452 34,978 48,143 53,102 58,731 61,903 65,740 69,981 73,679 0.8 2.4 6.6 Rwanda 1,368 1,673 2,089 2,096 2,207 2,363 2,536 2,737 3,045 2.5 ­1.6 6.7 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 2,683 3,463 4,939 5,268 5,579 5,893 6,034 6,315 6,472 2.7 2.8 4.4 Seychelles 292 395 608 572 556 598 647 694 714 3.1 4.5 2.0 Sierra Leone 929 1,014 958 1,047 1,125 1,207 1,296 1,384 1,454 0.5 ­5.3 10.3 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 95,503 110,945 141,520 145,935 153,034 160,632 169,180 177,804 183,249 1.4 2.0 4.3 Sudan 5,525 7,062 13,832 14,821 15,579 16,564 18,434 20,308 22,002 2.4 5.4 7.4 Swaziland 470 1,033 1,532 1,592 1,632 1,668 1,715 1,776 1,820 7.4 3.1 2.7 Tanzania .. 6,801 10,345 10,931 11,667 12,526 13,370 14,326 15,394 .. 2.7 6.8 Togo 964 1,071 1,382 1,419 1,461 1,479 1,537 1,566 1,583 1.5 3.6 2.4 Uganda .. 3,215 6,916 7,363 7,865 8,363 9,265 10,060 11,019 2.3 7.2 7.5 Zambia 2,730 3,028 3,488 3,686 3,886 4,089 4,342 4,611 4,888 1.0 0.2 5.3 Zimbabwe 4,376 6,734 6,883 6,167 5,933 5,618 .. .. .. 3.3 2.7 ­5.7 NORTH AFRICA 119,695 179,235 263,778 273,960 286,919 300,068 316,723 333,716 353,097 4.2 3.2 4.6 Algeria 35,291 46,367 58,857 62,918 66,190 69,565 70,956 73,085 75,278 2.9 1.7 4.3 Egypt, Arab Rep. 38,506 65,579 105,818 109,211 113,666 118,757 126,890 135,867 145,465 5.5 4.3 4.7 Libya .. .. 37,228 36,204 38,014 40,409 42,511 45,401 48,579 .. .. 4.1 Morocco 20,086 29,312 41,137 43,735 45,835 47,201 50,863 52,244 55,275 4.2 2.4 5.0 Tunisia 8,622 12,237 20,738 21,891 23,213 24,136 25,503 27,118 28,501 3.2 4.6 4.9 ALL AFRICA 349,899 454,267 631,251 657,091 694,201 730,249 773,501 819,632 863,827 2.6 2.7 5.0 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 39 Table 2.3 Gross domestic product growth Annual growth (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 4.2 1.1 3.3 4.3 6.3 5.6 6.2 6.4 5.1 2.2 2.1 4.9 Excluding South Africa 2.0 2.1 3.1 5.0 7.2 6.0 6.7 7.2 6.3 2.1 2.5 5.4 Excl. S. Africa & Nigeria 1.1 0.6 3.5 3.5 6.2 6.2 6.9 7.4 6.6 2.6 2.4 5.3 Angola .. ­0.3 14.5 3.3 11.2 20.6 18.6 20.3 14.8 4.2 1.0 12.2 Benin 6.8 3.2 4.5 3.9 3.1 2.9 3.8 4.6 5.1 3.1 4.5 4.3 Botswana 12.0 6.8 3.3 6.3 6.5 4.7 3.0 4.2 ­1.0 11.5 6.1 4.5 Burkina Faso 0.8 ­0.6 4.7 8.0 4.6 6.4 5.5 3.6 4.5 3.7 5.1 5.1 Burundi 1.0 3.5 4.4 ­1.2 4.8 0.9 5.1 3.6 4.5 4.3 ­1.4 2.6 Cameroon ­2.0 ­6.1 4.0 4.0 3.7 2.3 3.2 3.5 3.9 4.0 0.4 3.7 Cape Verde .. 0.7 4.6 6.2 ­0.7 6.5 10.8 6.9 6.0 6.4 5.2 5.6 Central African Republic ­4.5 ­2.1 ­0.6 ­7.6 1.0 2.4 4.0 4.2 2.8 0.9 1.3 1.0 Chad ­6.0 ­4.2 8.5 14.7 33.6 7.9 0.2 0.2 ­0.4 5.4 2.2 8.4 Comoros .. 5.1 4.1 2.5 ­0.2 4.2 1.2 0.5 1.0 2.7 1.6 1.9 Congo, Dem. Rep. 2.2 ­6.6 3.5 5.8 6.6 7.9 5.6 6.3 6.2 1.8 ­5.5 3.6 Congo, Rep. 17.6 1.0 4.8 1.7 3.6 7.7 6.2 ­1.6 5.6 6.8 0.8 4.4 Côte d'Ivoire ­11.0 ­1.1 ­1.4 ­1.6 1.8 1.3 0.7 1.7 2.2 ­0.2 2.6 0.1 Djibouti .. .. 2.6 3.2 3.8 3.2 4.1 4.3 3.9 .. ­2.0 3.1 Equatorial Guinea .. 3.3 19.5 14.0 38.0 9.7 1.3 21.4 11.3 0.9 20.2 21.2 Eritrea .. .. 3.0 ­2.7 1.5 2.6 ­1.0 1.3 2.0 .. 8.1 0.3 Ethiopia .. 2.7 1.5 ­2.2 13.6 11.8 10.9 11.1 11.3 2.4 2.7 8.0 Gabon 2.6 5.2 ­0.3 2.5 1.3 3.0 1.2 5.6 2.1 1.9 2.5 1.7 Gambia, The 6.3 3.6 ­3.3 6.9 7.1 5.1 6.5 6.3 5.9 3.9 3.1 5.1 Ghana 0.5 3.3 4.5 5.2 5.6 5.9 6.4 6.1 6.2 2.0 4.3 5.3 Guinea 2.6 4.3 4.2 2.0 2.7 3.3 2.2 1.5 8.4 2.9 4.3 3.4 Guinea-Bissau ­16.0 6.1 ­7.1 ­7.1 ­0.6 2.2 3.5 0.6 2.7 2.9 2.0 0.2 Kenya 5.6 4.2 0.5 2.9 5.1 5.8 6.4 7.0 3.6 4.2 2.2 4.0 Lesotho ­2.7 6.0 1.6 3.9 4.6 0.7 8.1 5.1 3.9 2.8 3.9 3.9 Liberia ­4.1 ­51.0 3.7 ­31.3 2.6 5.3 7.8 9.4 7.1 ­4.5 1.2 3.7 Madagascar 0.8 3.1 ­12.7 9.8 5.3 4.6 5.0 6.2 6.9 0.4 1.6 4.0 Malawi 0.4 5.7 ­4.4 6.3 5.7 2.6 8.2 8.6 9.7 1.7 4.1 3.7 Mali ­4.3 ­1.9 4.2 7.4 2.2 6.1 5.3 2.8 5.0 0.6 3.6 5.4 Mauritania 3.4 ­1.8 1.1 5.6 5.2 5.4 11.7 1.9 .. 2.2 2.6 4.5 Mauritius .. 5.8 2.7 3.2 4.7 4.6 3.6 4.7 5.3 5.9 5.4 4.3 Mozambique .. 1.0 8.8 6.0 7.9 8.4 8.7 7.0 6.5 0.4 5.5 7.4 Namibia .. 2.5 4.8 4.2 12.3 2.5 7.1 4.1 2.7 1.1 4.1 4.7 Niger ­2.2 ­1.3 3.0 4.4 ­0.8 7.4 5.8 3.3 9.5 0.0 1.9 4.3 Nigeria 4.2 8.2 1.5 10.3 10.6 5.4 6.2 6.4 5.3 0.9 3.1 6.0 Rwanda 9.0 ­2.4 11.0 0.3 5.3 7.1 7.3 7.9 11.2 3.2 2.1 7.4 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal ­3.3 ­0.7 0.7 6.7 5.9 5.6 2.4 4.7 2.5 2.4 2.7 4.0 Seychelles ­4.2 7.0 1.2 ­5.9 ­2.9 7.5 8.3 7.3 2.8 2.1 4.9 2.3 Sierra Leone 4.8 3.4 27.5 9.3 7.5 7.2 7.3 6.8 5.1 1.1 ­4.3 10.3 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 6.6 ­0.3 3.7 3.1 4.9 5.0 5.3 5.1 3.1 2.2 1.4 4.1 Sudan 1.5 ­5.5 5.4 7.1 5.1 6.3 11.3 10.2 8.3 3.4 4.4 7.6 Swaziland 12.4 9.8 1.8 3.9 2.5 2.2 2.9 3.5 2.5 8.6 3.7 3.4 Tanzania .. 7.0 7.2 5.7 6.7 7.4 6.7 7.1 7.5 3.8 3.1 6.6 Togo 14.6 ­0.2 4.1 2.7 3.0 1.2 3.9 1.9 1.1 2.6 2.6 1.9 Uganda .. 6.5 6.4 6.5 6.8 6.3 10.8 8.6 9.5 3.0 6.9 7.3 Zambia 3.0 ­0.5 2.7 5.7 5.4 5.2 6.2 6.2 6.0 1.4 0.4 5.1 Zimbabwe 14.4 7.0 ­4.4 ­10.4 ­3.8 ­5.3 .. .. .. 5.2 2.6 ­5.8 NORTH AFRICA 5.2 4.0 3.1 3.9 4.7 4.6 5.6 5.4 5.8 4.3 3.3 4.5 Algeria 0.8 0.8 4.7 6.9 5.2 5.1 2.0 3.0 3.0 2.8 1.6 3.9 Egypt, Arab Rep. 10.0 5.7 2.4 3.2 4.1 4.5 6.8 7.1 7.1 5.9 4.3 4.9 Libya .. .. 3.3 ­2.8 5.0 6.3 5.2 6.8 7.0 .. .. 4.1 Morocco 3.6 4.0 3.3 6.3 4.8 3.0 7.8 2.7 5.8 3.9 2.8 4.8 Tunisia 7.4 7.9 1.7 5.6 6.0 4.0 5.7 6.3 5.1 3.6 5.1 4.9 ALL AFRICA 4.5 2.2 3.2 4.1 5.6 5.2 5.9 6.0 5.4 2.9 2.5 4.8 a. Provisional. 40 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.4 Table Gross domestic product per capita, real Constant prices (2000 $) Average annual growth (%) 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 592 533 520 529 548 565 585 608 624 ­1.0 ­0.6 2.5 Excluding South Africa 371 340 342 350 365 377 393 410 426 ­0.9 ­0.2 3.0 Excl. S. Africa & Nigeria 348 333 335 338 350 362 377 395 410 ­0.2 ­0.2 2.9 Angola .. 794 711 712 767 899 1,036 1,213 1,357 .. ­2.4 9.4 Benin 305 294 348 349 348 347 348 353 359 ­0.4 1.3 0.7 Botswana 1,214 2,483 3,783 3,976 4,189 4,336 4,411 4,541 4,440 7.6 3.3 2.7 Burkina Faso 161 175 230 241 244 252 258 259 263 1.3 2.6 2.3 Burundi 135 152 112 107 109 107 109 110 111 1.2 ­3.4 0.2 Cameroon 698 718 659 670 679 679 687 697 710 1.3 ­1.6 1.4 Cape Verde .. 854 1,269 1,325 1,294 1,357 1,482 1,562 1,632 .. 3.4 3.7 Central African Republic 316 271 239 218 216 218 223 228 230 ­1.2 ­1.0 ­0.9 Chad 144 181 184 203 262 274 266 259 251 3.3 ­0.6 5.3 Comoros 405 416 386 387 378 386 382 375 370 0.0 ­1.0 ­0.1 Congo, Dem. Rep. 250 202 82 84 86 90 92 95 99 ­1.2 ­8.6 1.9 Congo, Rep. 962 1,143 1,102 1,093 1,105 1,164 1,212 1,170 1,214 2.1 ­1.4 1.7 Côte d'Ivoire 918 658 568 548 546 541 533 530 530 ­3.2 ­0.3 ­1.6 Djibouti .. 1,177 757 767 783 794 812 832 849 .. ­4.7 1.5 Equatorial Guinea .. 547 4,329 4,796 6,439 6,877 6,779 8,017 8,692 .. 15.2 16.2 Eritrea .. .. 178 166 161 159 152 149 148 .. .. ­1.9 Ethiopia .. 129 130 124 137 150 162 175 190 .. ­0.7 5.2 Gabon 5,274 4,640 4,005 4,020 3,993 4,034 4,004 4,148 4,157 ­1.6 ­0.9 0.1 Gambia, The 346 340 310 321 333 340 351 363 374 ­0.2 ­0.8 1.8 Ghana 239 218 264 272 280 290 302 314 327 ­1.1 1.6 3.1 Guinea 332 340 387 388 391 396 396 394 417 0.2 1.0 1.5 Guinea-Bissau 137 182 147 133 129 128 130 128 128 2.8 ­1.6 ­3.2 Kenya 435 450 402 404 413 426 441 460 464 0.3 ­0.9 1.7 Lesotho 293 338 425 437 453 453 486 508 525 1.1 2.0 2.9 Liberia 728 200 196 131 131 133 138 144 148 ­6.7 ­1.9 ­3.7 Madagascar 360 290 222 237 242 246 252 260 271 ­2.4 ­1.7 0.8 Malawi 161 132 129 134 138 138 145 154 165 ­2.4 1.6 1.2 Mali 253 213 267 278 276 284 290 289 295 ­1.5 1.4 2.4 Mauritania 461 419 413 424 433 445 483 480 .. ­0.6 0.2 .. Mauritius 1,572 2,535 4,004 4,089 4,245 4,404 4,527 4,709 4,929 4.8 4.1 3.4 Mozambique 203 185 270 280 295 312 332 349 365 ­1.0 2.8 5.6 Namibia 2,309 1,828 2,134 2,194 2,432 2,462 2,603 2,665 2,692 ­2.4 1.3 3.2 Niger 263 193 166 168 160 166 170 170 180 ­3.0 ­1.4 1.3 Nigeria 443 370 367 394 426 438 454 473 487 ­2.5 ­0.3 3.5 Rwanda 263 234 245 241 250 263 275 290 313 ­1.1 ­0.9 4.5 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 476 460 473 492 508 522 521 531 530 0.0 0.3 1.4 Seychelles 4,532 5,645 7,267 6,913 6,740 7,209 7,651 8,165 8,267 1.8 2.9 1.1 Sierra Leone 285 248 211 221 229 236 246 255 262 ­1.7 ­5.7 6.9 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 3,463 3,152 3,128 3,186 3,302 3,426 3,570 3,716 3,764 ­0.8 ­0.7 2.8 Sudan 269 261 380 399 411 428 466 502 532 0.5 2.8 5.1 Swaziland 780 1,196 1,391 1,437 1,463 1,483 1,509 1,542 1,559 4.1 0.7 1.5 Tanzania .. 267 288 296 308 321 333 347 362 .. ­0.3 3.9 Togo 346 273 249 249 250 247 250 249 245 ­2.3 ­0.4 ­0.4 Uganda .. 181 266 274 283 291 312 328 348 .. 3.5 4.0 Zambia 473 383 318 329 339 348 361 375 387 ­2.0 ­2.5 2.8 Zimbabwe 601 644 550 493 475 450 .. .. .. 0.3 0.1 .. NORTH AFRICA 1,300 1,497 1,772 1,812 1,867 1,922 1,997 2,071 2,157 1.4 1.3 2.9 Algeria 1,876 1,834 1,874 1,973 2,045 2,117 2,128 2,159 2,191 ­0.1 ­0.3 2.5 Egypt, Arab Rep. 867 1,135 1,452 1,470 1,501 1,539 1,614 1,697 1,784 2.6 2.1 2.8 Libya .. .. 6,686 6,371 6,555 6,828 7,040 7,375 7,740 .. .. 2.3 Morocco 1,037 1,213 1,410 1,482 1,536 1,566 1,668 1,693 1,770 1.5 0.7 3.9 Tunisia 1,351 1,501 2,120 2,225 2,337 2,407 2,518 2,652 2,760 0.6 3.0 3.8 ALL AFRICA 735 718 738 750 774 796 824 853 879 ­0.2 ­0.1 2.5 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 41 Table 2.5 Gross domestic product per capita growth Annual growth (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 1.1 ­1.7 0.8 1.7 3.7 3.0 3.6 3.9 2.6 ­0.8 ­0.7 2.4 Excluding South Africa ­1.0 ­0.8 0.5 2.3 4.5 3.3 4.0 4.5 3.7 ­0.9 ­0.3 2.8 Excl. S. Africa & Nigeria ­1.9 ­2.3 0.9 0.9 3.5 3.5 4.1 4.7 3.9 ­0.4 ­0.4 2.6 Angola .. ­3.1 11.0 0.1 7.8 17.1 15.3 17.1 11.8 1.5 ­1.9 9.0 Benin 3.8 ­0.1 1.1 0.4 ­0.3 ­0.5 0.5 1.3 1.8 0.2 1.1 0.9 Botswana 8.0 3.7 2.1 5.1 5.4 3.5 1.7 3.0 ­2.2 7.9 3.5 3.2 Burkina Faso ­1.5 ­3.4 1.4 4.6 1.3 3.1 2.4 0.7 1.5 1.1 2.1 1.9 Burundi ­1.9 0.9 1.9 ­3.9 1.8 ­2.1 2.0 0.5 1.4 1.0 ­2.8 ­0.1 Cameroon ­4.8 ­8.9 1.6 1.6 1.4 0.1 1.1 1.5 1.9 0.9 ­2.2 1.4 Cape Verde .. ­1.5 2.8 4.4 ­2.3 4.9 9.2 5.4 4.5 4.2 3.0 3.9 Central African Republic ­7.0 ­4.5 ­2.2 ­9.0 ­0.6 0.7 2.2 2.3 0.9 ­1.6 ­1.3 ­0.7 Chad ­8.1 ­7.2 4.5 10.5 28.9 4.4 ­2.9 ­2.6 ­3.1 2.5 ­1.0 4.8 Comoros .. 2.4 2.0 0.3 ­2.3 2.1 ­0.9 ­1.9 ­1.4 0.1 ­0.6 ­0.2 Congo, Dem. Rep. ­0.9 ­9.7 0.6 2.7 3.4 4.5 2.3 3.3 3.2 ­1.2 ­8.2 0.7 Congo, Rep. 14.0 ­1.8 2.3 ­0.8 1.1 5.3 4.1 ­3.4 3.7 3.6 ­1.4 2.2 Côte d'Ivoire ­15.0 ­4.6 ­3.5 ­3.6 ­0.3 ­0.9 ­1.5 ­0.6 ­0.1 ­4.3 ­0.7 ­2.1 Djibouti .. .. 0.5 1.3 2.0 1.4 2.3 2.5 2.1 .. ­4.5 1.0 Equatorial Guinea .. ­0.1 16.1 10.8 34.2 6.8 ­1.4 18.3 8.4 ­2.9 16.3 17.8 Eritrea .. .. ­1.3 ­6.8 ­2.7 ­1.4 ­4.5 ­1.8 ­1.2 .. 6.5 ­3.5 Ethiopia .. ­0.6 ­1.1 ­4.7 10.7 9.0 8.0 8.3 8.5 ­0.8 ­0.5 5.3 Gabon ­0.3 1.9 ­2.4 0.4 ­0.7 1.0 ­0.7 3.6 0.2 ­1.2 ­0.5 ­0.3 Gambia, The 2.7 ­0.5 ­6.4 3.5 3.8 2.0 3.5 3.4 3.0 0.2 ­0.7 1.9 Ghana ­1.9 0.5 2.1 2.8 3.2 3.6 4.1 3.9 4.0 ­1.0 1.5 2.9 Guinea ­0.3 0.6 2.3 0.2 0.8 1.3 0.1 ­0.6 6.0 0.1 1.0 1.3 Guinea-Bissau ­18.5 3.6 ­9.4 ­9.4 ­3.0 ­0.2 1.1 ­1.6 0.5 0.8 ­0.5 ­2.1 Kenya 1.7 0.8 ­2.0 0.3 2.4 3.1 3.6 4.2 0.9 0.5 ­0.7 1.3 Lesotho ­5.2 4.4 0.5 3.0 3.7 ­0.1 7.3 4.5 3.4 0.6 2.2 3.0 Liberia ­7.3 ­50.0 0.3 ­33.1 ­0.2 1.8 3.6 4.7 2.4 ­6.2 ­2.3 ­0.5 Madagascar ­1.8 0.1 ­15.2 6.7 2.3 1.7 2.2 3.4 4.0 ­2.3 ­1.4 1.1 Malawi ­2.6 1.8 ­6.9 3.6 3.1 0.0 5.5 5.9 6.9 ­2.4 1.9 1.0 Mali ­6.4 ­4.3 1.1 4.3 ­0.9 2.9 2.2 ­0.2 1.9 ­1.7 0.9 2.3 Mauritania 0.6 ­4.3 ­1.8 2.6 2.2 2.6 8.7 ­0.6 .. ­0.4 ­0.2 1.6 Mauritius .. 5.0 1.8 2.1 3.8 3.7 2.8 4.0 4.7 4.9 4.2 3.4 Mozambique .. ­0.3 6.1 3.5 5.4 6.0 6.4 5.0 4.5 ­0.6 2.6 4.9 Namibia .. ­1.7 3.2 2.8 10.8 1.2 5.7 2.4 1.0 ­2.4 1.0 3.1 Niger ­5.2 ­4.4 ­0.6 0.8 ­4.2 3.7 2.2 0.0 6.0 ­2.9 ­1.6 0.7 Nigeria 1.2 5.1 ­1.0 7.6 7.9 2.9 3.7 4.1 3.0 ­1.9 0.2 3.5 Rwanda 5.4 ­2.0 8.0 ­1.4 3.7 5.0 4.7 5.2 8.2 ­0.4 1.3 4.3 São Tomé and Príncipe .. .. 9.7 3.6 4.8 3.9 5.0 4.1 3.9 .. .. 5.0 Senegal ­6.0 ­3.5 ­1.9 3.9 3.2 2.9 ­0.3 1.9 ­0.2 ­0.5 ­0.1 1.3 Seychelles ­5.4 6.1 ­1.8 ­4.9 ­2.5 7.0 6.1 6.7 1.3 1.2 3.3 1.4 Sierra Leone 2.6 2.1 22.6 4.8 3.3 3.4 4.0 3.9 2.4 ­1.2 ­4.5 6.7 Somalia ­9.1 ­1.5 .. .. .. .. .. .. .. 0.8 ­1.5 .. South Africa 4.2 ­2.3 2.7 1.9 3.6 3.7 4.2 4.1 1.3 ­0.3 ­0.8 2.7 Sudan ­1.7 ­7.7 3.2 5.0 3.0 4.1 8.9 7.7 5.9 0.5 1.8 5.3 Swaziland 9.1 6.0 1.0 3.3 1.9 1.4 1.8 2.2 1.1 4.8 1.2 2.3 Tanzania .. 3.7 4.5 2.9 3.9 4.4 3.8 4.1 4.4 0.6 0.1 3.8 Togo 11.1 ­3.0 1.3 0.1 0.4 ­1.3 1.3 ­0.6 ­1.4 ­0.9 ­0.3 ­0.8 Uganda .. 2.7 3.1 3.1 3.4 2.9 7.2 5.1 6.0 ­0.5 3.5 3.9 Zambia ­0.3 ­3.4 0.4 3.3 3.1 2.8 3.7 3.7 3.4 ­1.7 ­2.4 2.6 Zimbabwe 10.4 3.9 ­4.5 ­10.3 ­3.7 ­5.2 .. .. .. 1.4 0.6 ­5.9 NORTH AFRICA 2.4 1.6 1.4 2.2 3.1 2.9 3.9 3.7 4.1 1.5 1.3 2.8 Algeria ­2.5 ­1.7 3.2 5.3 3.6 3.5 0.5 1.5 1.5 ­0.3 ­0.4 2.3 Egypt, Arab Rep. 7.4 3.2 0.4 1.3 2.1 2.5 4.9 5.1 5.1 3.2 2.3 2.9 Libya .. .. 1.2 ­4.7 2.9 4.2 3.1 4.8 5.0 .. .. 2.0 Morocco 1.1 2.0 2.1 5.1 3.7 1.9 6.5 1.5 4.6 1.6 1.1 3.5 Tunisia 4.6 5.4 0.5 4.9 5.1 3.0 4.6 5.3 4.1 1.0 3.3 3.9 ALL AFRICA 1.5 ­0.6 0.8 1.7 3.2 2.8 3.5 3.6 3.0 0.0 ­0.1 2.3 a. Provisional. 42 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.6 Table Gross national income, nominal Current prices ($ millions) Annual average growth (%) 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 262,202 283,208 345,820 423,700 523,033 612,326 719,137 816,943 943,131 0.8 1.8 16.0 Excluding South Africa 187,659 175,700 238,947 262,139 311,536 375,040 468,354 544,541 679,313 ­1.1 1.5 17.3 Excl. S. Africa & Nigeria 121,180 150,392 185,833 201,617 232,519 274,867 324,509 386,366 478,417 2.7 1.1 15.3 Angola .. 8,214 9,791 12,230 17,295 26,601 39,679 50,485 70,958 .. ­2.4 35.8 Benin 1,402 1,806 2,781 3,515 4,006 4,259 4,623 5,428 6,652 2.1 3.7 14.4 Botswana 1,028 3,686 5,233 7,559 8,869 9,664 10,230 11,731 12,691 10.8 3.9 11.9 Burkina Faso 1,924 3,094 3,288 4,269 5,102 5,411 5,756 6,752 7,932 4.8 0.0 15.1 Burundi 922 1,117 614 577 646 776 910 974 1,159 1.9 ­3.3 7.2 Cameroon 5,618 10,674 10,207 13,097 15,374 16,126 17,706 20,612 23,072 9.0 ­2.4 12.9 Cape Verde .. 340 605 781 907 973 1,157 1,420 1,703 .. 6.2 16.5 Central African Republic 800 1,465 1,033 1,137 1,268 1,348 1,473 1,702 1,948 7.8 ­4.3 9.6 Chad 1,038 1,721 1,928 2,279 3,720 4,847 5,146 5,808 6,693 5.5 ­1.2 23.7 Comoros 124 249 250 323 360 385 404 467 531 7.9 ­2.0 12.8 Congo, Dem. Rep. 14,102 8,579 5,250 5,485 6,309 6,826 8,316 9,315 10,323 ­6.8 ­7.0 13.0 Congo, Rep. 1,544 2,324 2,201 2,679 3,247 4,509 5,961 5,548 8,367 1.9 ­5.2 19.8 Côte d'Ivoire 9,680 9,209 10,807 13,018 14,763 15,643 16,590 18,913 22,442 1.3 3.3 11.1 Djibouti .. .. 606 673 731 776 834 893 951 .. 1.3 7.1 Equatorial Guinea .. 124 1,161 1,392 2,312 4,173 5,163 6,674 11,868 .. 16.9 41.0 Eritrea .. .. 669 588 616 1,152 1,273 1,365 1,641 .. 7.3 13.9 Ethiopia .. 12,016 7,750 8,490 9,989 12,269 15,127 19,409 26,521 5.8 ­5.8 16.3 Gabon 3,856 5,336 4,453 5,342 5,987 7,708 7,902 10,042 12,191 ­0.1 ­1.9 15.0 Gambia, The 237 291 347 336 366 418 460 597 736 1.6 3.7 7.7 Ghana 4,426 5,774 6,030 7,459 8,674 10,533 12,588 14,851 15,875 2.9 2.6 17.6 Guinea .. 2,518 3,170 3,580 3,879 3,212 3,257 4,497 4,222 .. 3.3 4.3 Guinea-Bissau 105 233 195 223 274 290 308 374 422 3.4 ­0.7 11.0 Kenya 7,039 8,224 13,028 14,738 15,950 18,763 22,516 27,055 34,288 2.6 8.3 13.5 Lesotho 695 937 834 1,250 1,600 1,680 1,898 2,087 2,043 0.4 1.4 13.0 Liberia 930 .. 453 350 373 417 444 560 676 ­3.2 .. 5.7 Madagascar 4,024 2,958 4,326 5,394 4,285 4,960 5,435 7,288 8,894 ­6.0 3.8 9.1 Malawi 1,138 1,837 2,621 2,385 2,582 2,813 3,125 3,563 4,246 2.2 0.2 11.3 Mali 1,768 2,405 3,103 4,203 4,679 5,099 5,524 7,445 8,484 2.8 0.1 17.6 Mauritania 672 1,076 1,276 1,343 1,613 1,901 2,769 2,750 .. 4.8 1.8 16.1 Mauritius 1,130 2,363 4,541 5,246 6,028 6,285 6,478 6,853 8,941 7.7 6.6 8.6 Mozambique 3,550 2,320 4,028 4,469 5,358 6,095 6,414 7,274 8,721 ­5.6 8.6 11.1 Namibia 1,818 2,388 3,395 5,163 6,689 7,149 7,948 8,610 8,460 0.2 4.5 13.8 Niger 2,476 2,423 2,146 2,718 3,039 3,397 3,647 4,245 5,338 0.1 ­1.7 14.3 Nigeria 61,079 25,585 52,716 59,996 78,110 98,881 141,277 155,392 197,319 ­12.5 3.7 23.4 Rwanda 1,165 2,572 1,622 1,746 1,936 2,351 2,806 3,395 4,420 8.5 ­2.0 13.0 São Tomé and Príncipe .. .. .. .. .. 111 127 151 179 .. .. .. Senegal .. .. .. .. .. .. 9,278 11,203 13,104 .. .. .. Seychelles 142 355 630 663 666 844 924 841 765 8.9 5.9 5.3 Sierra Leone 1,071 580 903 946 1,014 1,166 1,365 1,629 1,914 ­4.8 1.5 13.8 Somalia 603 835 .. .. .. .. .. .. .. 5.5 .. .. South Africa 77,425 107,918 108,079 162,044 211,700 237,860 252,594 274,723 267,815 4.3 2.2 13.5 Sudan 7,570 11,409 13,697 16,428 19,990 25,397 33,503 41,682 52,386 9.7 1.9 22.2 Swaziland .. 1,174 1,177 1,754 2,284 2,702 2,684 2,957 2,662 .. 4.5 11.6 Tanzania .. 4,072 9,579 10,135 11,153 14,002 14,097 16,129 19,876 .. 9.3 10.4 Togo 1,096 1,598 1,454 1,736 2,033 2,073 2,180 2,455 2,806 4.6 ­0.1 10.5 Uganda 1,237 4,227 6,062 6,484 7,801 8,991 9,712 11,663 14,218 20.7 9.1 12.0 Zambia 3,594 3,008 3,565 4,231 5,026 6,761 9,507 10,026 12,986 ­4.1 0.7 20.9 Zimbabwe 6,610 8,494 21,651 7,207 4,503 3,220 .. .. .. ­0.2 ­2.6 ­19.2 NORTH AFRICA 103,183 159,989 234,312 254,999 283,945 326,528 379,219 448,199 580,032 4.9 5.4 11.7 Algeria 41,147 59,955 54,823 65,319 81,414 97,259 111,940 132,594 171,880 4.5 ­1.3 16.8 Egypt, Arab Rep. 21,453 42,025 88,763 83,006 78,757 89,474 108,015 131,653 164,215 7.5 11.2 5.6 Libya .. .. .. 24,357 30,253 41,462 50,765 59,730 101,397 .. .. 30.7 Morocco 18,402 24,835 39,448 48,783 55,961 58,760 64,703 74,139 85,236 3.3 5.3 11.9 Tunisia 8,450 11,882 20,096 23,957 26,895 27,309 29,553 33,249 35,518 2.0 6.0 9.0 ALL AFRICA 369,535 446,415 581,241 682,334 811,670 944,386 1,104,866 1,272,332 1,530,861 2.1 3.0 14.4 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 43 Table 2.7 Gross national income, Atlas method Current prices ($ millions) Average annual growth (%) 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 219,358 283,925 333,120 375,065 463,951 577,651 684,310 779,264 893,449 0.9 2.1 14.8 Excluding South Africa 166,400 170,871 214,354 244,444 296,562 352,549 428,428 506,600 613,196 ­1.2 1.6 15.7 Excl. S. Africa & Nigeria 114,173 147,023 168,676 188,346 222,319 263,864 306,722 360,905 434,567 2.0 1.2 13.3 Angola .. 7,261 9,134 10,678 14,637 21,941 32,657 45,509 62,113 .. ­1.6 35.0 Benin 1,223 1,629 2,523 2,985 3,708 4,316 4,670 5,120 5,951 1.1 3.9 13.1 Botswana 860 3,311 5,475 6,493 7,927 9,811 10,505 11,484 12,328 9.4 5.1 12.0 Burkina Faso 1,726 2,762 3,003 3,684 4,634 5,528 5,989 6,399 7,278 3.5 ­0.5 14.3 Burundi 761 1,125 666 623 666 723 843 956 1,092 3.8 ­3.5 2.9 Cameroon 4,613 10,553 9,817 11,393 14,183 16,295 17,781 19,489 21,781 8.7 ­1.5 11.9 Cape Verde .. 316 571 678 807 972 1,143 1,320 1,561 .. 7.0 14.1 Central African Republic 668 1,308 965 1,003 1,187 1,358 1,471 1,608 1,804 7.1 ­3.5 7.8 Chad 929 1,504 1,755 1,999 3,254 4,204 4,783 5,463 5,916 4.5 ­0.6 23.2 Comoros .. 221 228 271 326 389 411 435 483 8.6 ­1.1 12.4 Congo, Dem. Rep. 14,859 7,912 4,555 5,455 6,383 7,000 7,876 8,786 9,843 ­8.4 ­5.7 12.6 Congo, Rep. 1,248 2,062 2,257 2,440 2,929 3,799 5,021 5,370 7,134 2.4 ­5.1 18.2 Côte d'Ivoire 7,929 8,763 9,936 11,191 13,655 15,691 16,519 17,771 20,257 0.9 3.6 9.3 Djibouti .. .. 593 675 754 803 847 895 957 .. 1.1 7.9 Equatorial Guinea .. 117 1,180 1,231 1,928 3,170 4,296 6,235 9,875 .. 16.3 38.0 Eritrea .. .. 684 647 655 801 983 1,308 1,492 .. 4.2 9.4 Ethiopia .. 11,542 8,195 8,167 9,954 12,195 14,298 17,568 22,742 6.4 ­4.9 11.5 Gabon 2,811 4,314 4,395 4,727 5,357 7,010 7,397 9,175 10,490 0.5 ­0.7 13.4 Gambia, The 207 277 372 369 391 417 457 541 653 0.7 4.2 3.1 Ghana 3,976 5,536 5,502 6,549 8,144 9,966 11,704 13,763 15,744 4.1 2.5 13.7 Guinea .. 2,588 3,171 3,392 3,824 3,862 3,722 3,722 .. .. 4.1 2.7 Guinea-Bissau 99 206 185 189 234 283 315 340 386 3.5 ­0.4 8.6 Kenya 6,381 8,394 12,878 14,032 16,074 18,604 21,050 24,834 29,541 2.5 6.4 10.1 Lesotho 502 866 902 1,019 1,279 1,603 1,922 2,077 2,179 1.6 3.0 12.6 Liberia 849 .. 459 342 364 407 431 531 634 ­3.2 .. 2.6 Madagascar 3,424 2,632 3,842 4,858 5,184 5,377 5,352 6,357 7,766 ­4.1 4.8 7.1 Malawi 1,001 1,625 1,801 2,243 2,822 2,865 3,156 3,547 4,107 2.1 1.4 12.4 Mali 1,492 2,146 2,702 3,476 4,365 5,195 5,546 6,941 7,360 1.5 1.3 16.6 Mauritania 617 1,044 1,246 1,310 1,532 1,792 2,324 2,636 .. 4.9 3.8 13.1 Mauritius .. 2,304 4,621 4,997 5,759 6,527 6,846 7,067 8,122 8.7 7.7 7.9 Mozambique .. 2,211 4,332 4,491 5,147 5,986 6,604 7,266 8,119 ­3.3 7.2 8.9 Namibia .. 2,300 3,710 4,292 5,537 6,864 7,989 8,536 8,880 0.2 5.4 15.2 Niger 2,083 2,241 2,003 2,381 2,879 3,381 3,646 3,998 4,823 ­0.2 ­1.8 12.6 Nigeria 47,183 24,151 45,399 55,621 73,419 87,689 119,713 143,293 175,622 ­10.6 3.3 23.8 Rwanda 1,119 2,408 1,804 1,759 1,932 2,278 2,627 3,142 3,955 8.3 ­2.9 7.0 São Tomé and Príncipe .. .. .. .. .. 117 130 145 164 .. .. .. Senegal .. .. .. .. .. .. 9,304 10,328 11,825 .. .. .. Seychelles 113 332 573 620 680 803 909 940 889 9.7 6.6 7.8 Sierra Leone 1,074 768 928 1,012 1,079 1,198 1,323 1,537 1,785 ­6.6 0.6 12.4 Somalia 656 959 .. .. .. .. .. .. .. 5.9 .. .. South Africa 58,621 113,320 119,414 131,451 168,226 225,603 256,958 274,323 283,310 4.7 2.9 13.6 Sudan 7,909 12,988 12,905 15,277 18,511 22,946 29,250 36,703 46,520 10.0 0.4 19.3 Swaziland .. 940 1,314 1,417 1,804 2,542 2,684 2,934 2,945 .. 7.3 11.0 Tanzania .. 4,607 9,773 10,463 11,564 13,382 14,518 15,934 18,350 .. 7.2 9.0 Togo 973 1,433 1,375 1,561 1,877 2,105 2,253 2,361 2,607 3.2 0.4 9.2 Uganda .. 5,396 6,227 6,596 7,642 8,692 10,029 11,397 13,254 21.2 6.1 9.4 Zambia 3,074 3,315 3,454 4,014 4,602 5,849 7,221 9,116 11,986 ­6.2 0.5 16.9 Zimbabwe 5,789 8,524 9,973 9,874 7,334 4,467 .. .. .. 0.2 ­2.1 ­2.9 NORTH AFRICA 86,426 152,924 242,799 255,953 280,596 318,146 361,047 417,123 499,568 6.0 4.8 8.5 Algeria 32,949 57,942 54,987 62,068 73,987 89,353 103,878 122,196 146,365 6.6 ­1.9 14.6 Egypt, Arab Rep. 18,546 40,173 97,225 93,204 90,725 92,817 101,669 120,049 146,851 8.8 10.2 1.6 Libya .. .. .. 24,288 25,650 34,726 44,645 55,477 72,735 .. .. 24.7 Morocco 16,000 23,440 38,743 44,362 53,196 60,348 66,312 70,652 80,544 1.9 5.4 10.6 Tunisia 7,430 11,018 19,533 22,257 26,324 28,754 30,756 32,822 33,998 2.2 6.9 8.7 ALL AFRICA 308,411 440,553 575,774 632,091 746,236 898,214 1,048,300 1,199,655 1,396,577 2.5 3.0 12.4 a. Provisional. 44 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.8 Table Gross national income per capita, Atlas method Current prices ($) Annual average growth (%) 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 571 553 471 518 625 759 877 975 1,091 ­2.0 ­0.6 12.4 Excluding South Africa 467 358 324 360 426 493 584 674 796 ­4.1 ­1.2 13.5 Excl. S. Africa & Nigeria 400 384 318 346 398 460 521 598 702 ­1.0 ­1.5 11.3 Angola .. 680 600 680 910 1,320 1,910 2,590 3,450 .. ­4.5 32.2 Benin 340 340 350 410 490 550 570 610 690 ­1.6 0.4 9.7 Botswana 860 2,420 3,080 3,620 4,370 5,340 5,650 6,100 6,470 6.0 2.6 10.4 Burkina Faso 250 310 240 280 340 400 420 430 480 0.9 ­3.3 10.5 Burundi 180 200 100 90 90 100 110 120 140 0.7 ­4.7 2.0 Cameroon 510 860 590 670 810 920 980 1,050 1,150 5.4 ­4.1 9.5 Cape Verde .. 890 1,260 1,470 1,720 2,040 2,360 2,680 3,130 .. 4.7 12.9 Central African Republic 290 430 240 250 290 320 340 370 410 4.4 ­5.9 6.5 Chad 200 250 190 210 330 410 460 510 530 1.7 ­3.6 17.9 Comoros .. 510 400 470 550 650 670 690 750 5.9 ­3.2 9.6 Congo, Dem. Rep. 530 210 90 100 110 120 130 140 150 ­11.2 ­8.5 8.9 Congo, Rep. 690 840 710 750 880 1,110 1,440 1,510 1,970 ­0.6 ­7.2 16.6 Côte d'Ivoire 940 690 550 610 720 820 840 880 980 ­3.2 0.4 7.3 Djibouti .. .. 780 870 950 1,000 1,030 1,070 1,130 .. ­1.6 5.7 Equatorial Guinea .. 310 2,110 2,140 3,250 5,210 6,870 9,710 14,980 .. 12.3 36.3 Eritrea .. .. 170 150 150 180 210 270 300 .. 1.7 7.4 Ethiopia .. 240 120 120 140 160 190 220 280 3.3 ­7.6 10.2 Gabon 4,120 4,660 3,410 3,590 3,990 5,120 5,300 6,450 7,240 ­2.5 ­3.6 11.7 Gambia, The 340 310 270 260 260 270 290 330 390 ­3.1 0.4 1.7 Ghana 360 370 270 310 380 450 520 600 670 0.9 ­0.3 11.8 Guinea .. 420 360 380 420 420 400 390 .. .. 0.8 0.9 Guinea-Bissau 120 200 140 130 160 190 210 220 250 1.5 ­2.7 6.7 Kenya 390 360 390 420 460 520 580 660 770 ­1.0 3.3 8.4 Lesotho 390 540 470 520 650 810 960 1,040 1,080 ­0.5 1.4 11.5 Liberia 440 .. 150 110 110 120 120 150 170 ­4.8 .. 1.0 Madagascar 400 230 240 290 300 310 300 340 410 ­6.6 1.8 5.4 Malawi 160 170 150 180 220 220 230 250 290 ­2.1 ­0.2 9.5 Mali 250 280 250 320 390 450 460 560 580 ­0.8 ­1.4 12.7 Mauritania 410 540 460 470 530 600 760 840 .. 2.3 1.0 9.9 Mauritius .. 2,180 3,820 4,090 4,670 5,250 5,460 5,610 6,400 7.9 6.5 7.3 Mozambique .. 160 230 230 260 290 310 340 370 ­3.7 3.9 6.7 Namibia .. 1,620 1,910 2,180 2,780 3,400 3,900 4,100 4,200 ­3.7 2.4 12.7 Niger 360 290 170 190 220 250 270 280 330 ­3.0 ­5.3 9.3 Nigeria 660 260 350 410 530 620 830 970 1,160 ­13.0 0.4 20.9 Rwanda 220 340 210 200 220 250 290 330 410 4.3 ­3.0 6.8 São Tomé and Príncipe .. .. .. .. .. 760 840 920 1,020 .. .. .. Senegal .. .. .. .. .. .. 800 870 970 .. .. .. Seychelles 1,760 4,750 6,850 7,490 8,240 9,680 10,740 11,060 10,290 8.8 5.0 6.3 Sierra Leone 330 190 200 210 220 230 250 280 320 ­8.8 0.8 8.8 Somalia 100 140 .. .. .. .. .. .. .. 6.1 .. .. South Africa 2,130 3,220 2,640 2,870 3,630 4,810 5,420 5,730 5,820 2.1 0.7 11.7 Sudan 390 480 350 410 490 590 740 910 1,130 6.8 ­2.2 18.0 Swaziland .. 1,090 1,190 1,280 1,620 2,260 2,360 2,550 2,520 .. 4.9 9.7 Tanzania .. 180 270 280 300 340 360 390 430 .. 4.2 6.7 Togo 350 370 250 270 320 350 370 370 400 ­0.5 ­2.4 6.3 Uganda .. 300 240 250 280 300 340 370 420 17.0 2.9 6.8 Zambia 530 420 310 360 400 500 600 740 950 ­9.2 ­2.3 15.9 Zimbabwe 790 810 800 790 590 360 .. .. .. ­3.4 ­3.9 ­2.9 NORTH AFRICA 939 1,277 1,631 1,693 1,826 2,038 2,276 2,588 3,051 3.2 2.9 8.1 Algeria 1,750 2,290 1,750 1,950 2,290 2,720 3,110 3,610 4,260 3.4 ­3.8 13.6 Egypt, Arab Rep. 420 700 1,330 1,250 1,200 1,200 1,290 1,500 1,800 5.9 8.0 1.9 Libya .. .. .. 4,270 4,420 5,870 7,390 9,010 11,590 .. .. 23.4 Morocco 830 970 1,330 1,500 1,780 2,000 2,170 2,290 2,580 ­0.4 3.6 9.5 Tunisia 1,160 1,350 2,000 2,260 2,650 2,870 3,040 3,210 3,290 ­0.3 5.2 7.3 ALL AFRICA 648 696 673 722 832 979 1,116 1,249 1,421 ­0.4 0.4 10.6 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 45 Table 2.9 Gross domestic product deflator (local currency series) Index (2000 = 100) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 15 40 111 117 127 139 150 163 183 23 67 133 Excluding South Africa 17 40 111 117 126 139 152 164 186 25 67 133 Excl. S. Africa & Nigeria 20 40 110 117 124 139 149 162 183 26 68 132 Angola .. .. 460 931 1,329 1,780 2,041 2,126 2,548 .. 3 1,280 Benin 38 50 111 113 113 116 120 123 135 47 73 115 Botswana 13 41 110 113 119 132 154 174 203 22 62 134 Burkina Faso 52 76 110 111 115 115 115 119 125 67 84 113 Burundi 21 31 107 120 130 151 158 171 213 24 51 139 Cameroon 34 58 105 106 107 110 115 117 119 50 79 109 Cape Verde .. 66 105 106 113 115 123 127 134 60 81 114 Central African Republic 32 70 107 105 106 109 114 116 122 54 83 109 Chad 46 60 116 116 127 157 166 169 190 55 78 139 Comoros 36 70 113 119 121 124 126 133 140 54 82 121 Congo, Dem. Rep. .. .. 639 722 769 937 1,064 1,252 1,495 0 2 829 Congo, Rep. 29 38 84 82 87 113 134 124 153 39 50 107 Côte d'Ivoire 39 50 110 111 112 116 122 125 135 50 75 115 Djibouti .. 69 102 104 108 111 115 118 122 .. 85 109 Equatorial Guinea .. 24 87 87 102 145 166 164 203 26 41 127 Eritrea .. .. 138 161 192 260 287 304 359 .. 66 213 Ethiopia .. 49 91 102 106 117 130 152 197 42 79 121 Gabon 35 53 94 93 99 116 125 132 151 44 63 112 Gambia, The 15 64 134 170 191 199 202 213 226 31 82 172 Ghana 0 11 166 213 244 280 316 360 424 3 37 249 Guinea 5 48 108 120 145 186 256 300 417 17 77 193 Guinea-Bissau 0 6 99 103 114 118 119 130 143 1 47 114 Kenya 10 24 103 109 117 123 132 138 175 16 57 122 Lesotho 13 40 124 127 135 141 153 167 183 22 67 137 Liberia 2 2 141 145 146 166 181 210 237 2 22 160 Madagascar 4 21 124 127 145 172 192 210 230 10 54 156 Malawi 2 7 217 236 270 311 366 393 428 3 29 272 Mali 35 57 116 117 116 119 124 129 147 50 79 119 Mauritania 20 42 116 119 133 157 203 198 .. 29 75 142 Mauritius 21 54 111 117 124 130 135 145 156 33 74 125 Mozambique 0 6 124 131 141 153 167 180 191 1 45 145 Namibia 11 34 123 124 127 134 146 160 179 19 55 134 Niger 49 63 107 107 105 112 115 119 128 63 78 111 Nigeria 2 7 146 162 195 234 280 293 336 3 41 206 Rwanda 20 33 96 117 132 144 158 175 205 25 70 137 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 39 63 106 107 107 110 114 121 129 55 81 111 Seychelles 56 87 110 117 121 142 144 154 193 70 92 132 Sierra Leone 0 5 98 106 123 139 155 171 191 1 41 132 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 9 38 119 124 131 139 149 162 180 18 65 135 Sudan .. .. .. .. .. .. .. .. .. .. .. .. Swaziland 13 40 116 123 130 139 152 165 171 19 69 134 Tanzania .. 15 114 122 132 159 168 183 199 11 49 143 Togo 35 58 105 101 105 106 106 107 112 49 78 105 Uganda .. 28 104 112 129 127 130 139 148 4 69 121 Zambia 0 1 151 181 214 251 285 318 353 0 32 220 Zimbabwe 2 7 394 1,883 9,064 30,632 .. .. .. 4 24 7,042 NORTH AFRICA 21 54 105 111 123 133 143 161 181 33 77 129 Algeria 6 16 103 111 123 143 158 169 198 9 50 134 Egypt, Arab Rep. 13 43 105 112 125 133 143 161 181 20 73 129 Libya .. .. 128 166 204 264 300 316 492 .. 81 230 Morocco 35 68 102 103 104 105 107 111 114 50 84 105 Tunisia 30 64 105 107 110 114 118 121 127 46 82 112 ALL AFRICA 15 40 110 117 125 139 149 162 182 23 68 132 a. Provisional. 46 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.10 Table Gross domestic product deflator (U.S. dollar series) Index (2000 = 100) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 121 110 99 117 135 151 164 178 196 108 109 137 Excluding South Africa 149 116 112 118 132 150 172 188 222 123 104 144 Excl. S. Africa & Nigeria 130 126 109 115 127 141 156 174 203 120 113 136 Angola .. 121 106 125 160 205 255 278 341 95 91 185 Benin 130 131 113 138 153 157 163 183 215 103 116 147 Botswana 88 112 88 116 129 132 134 144 153 77 108 121 Burkina Faso 175 199 113 136 155 155 156 177 199 147 135 143 Burundi 164 131 83 80 85 101 111 114 129 153 123 99 Cameroon 106 127 99 120 134 137 144 160 174 102 125 129 Cape Verde .. 112 107 130 152 155 167 188 213 95 117 146 Central African Republic 108 183 109 129 142 148 155 173 194 117 143 139 Chad 155 157 118 142 172 212 227 251 301 121 129 182 Comoros 91 138 116 146 163 167 172 197 223 89 125 154 Congo, Dem. Rep. 205 122 127 123 134 136 157 167 183 133 126 138 Congo, Rep. 98 100 86 100 118 153 183 184 244 84 81 139 Côte d'Ivoire 132 130 112 136 150 157 166 186 215 108 123 147 Djibouti .. 69 102 104 108 111 115 118 122 .. 85 109 Equatorial Guinea .. 64 89 107 137 196 227 244 323 54 65 168 Eritrea .. .. 95 86 90 161 180 190 224 .. 99 136 Ethiopia .. 194 87 97 101 110 122 141 173 167 151 114 Gabon 119 138 96 114 134 157 171 196 240 96 104 144 Gambia, The 113 104 86 80 81 89 92 110 126 91 109 95 Ghana 168 180 114 134 148 168 188 209 211 177 166 153 Guinea 434 128 95 105 111 89 86 121 104 420 136 101 Guinea-Bissau 97 131 102 127 154 160 162 194 212 105 116 145 Kenya 103 81 99 109 112 124 139 156 193 86 86 126 Lesotho 114 106 82 117 145 153 156 164 153 94 119 129 Liberia 69 89 93 100 109 119 128 140 155 76 101 115 Madagascar 130 94 122 139 105 116 121 152 173 108 101 127 Malawi 124 151 168 144 148 157 160 167 182 118 132 148 Mali 116 149 118 144 157 161 169 192 233 108 132 152 Mauritania 102 125 102 108 124 139 181 176 .. 108 140 129 Mauritius 76 89 94 105 116 115 113 114 138 71 104 110 Mozambique 143 99 81 85 96 103 102 107 123 157 93 98 Namibia 95 91 81 114 136 146 150 157 150 79 97 125 Niger 165 165 109 131 141 151 156 176 203 137 127 141 Nigeria 204 81 123 127 150 181 223 237 288 127 76 170 Rwanda 85 154 79 85 89 101 112 125 146 112 123 103 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 131 165 108 130 144 147 155 179 204 120 136 141 Seychelles 50 93 115 123 126 148 150 131 117 65 103 124 Sierra Leone 119 64 98 95 95 101 110 120 134 98 99 107 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 85 101 78 114 141 151 152 160 151 88 115 126 Sudan 138 176 108 120 139 165 197 228 266 196 122 158 Swaziland 115 108 77 113 140 151 156 163 144 87 123 125 Tanzania .. 63 94 94 97 113 107 117 133 76 77 106 Togo 118 152 107 124 141 143 144 160 178 106 131 133 Uganda .. 134 89 90 101 110 107 118 132 157 109 104 Zambia 142 109 107 119 140 175 246 247 293 111 111 170 Zimbabwe 153 130 318 120 79 61 .. .. .. 136 101 137 NORTH AFRICA 93 96 86 91 97 107 117 130 159 91 92 109 Algeria 120 134 97 108 128 147 164 184 231 128 101 140 Egypt, Arab Rep. 60 66 83 76 69 76 85 96 112 62 76 88 Libya .. .. 52 66 80 103 117 128 206 .. 89 104 Morocco 94 88 98 114 124 126 129 144 156 72 99 121 Tunisia 101 100 101 114 121 120 121 129 141 89 111 116 ALL AFRICA 112 104 93 106 120 133 145 158 181 101 102 126 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 47 Table 2.11 Consumer price index Annual growth (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA Angola .. .. 108.9 98.2 43.5 23.0 13.3 12.2 12.5 .. 1,122.5 87.7 Benin .. .. 2.5 1.5 0.9 5.4 3.8 1.3 7.9 .. 9.7 3.5 Botswana 13.6 11.4 8.0 9.2 6.9 8.6 11.6 7.1 12.7 10.8 10.8 8.8 Burkina Faso 12.2 ­0.5 2.2 2.0 ­0.4 6.4 2.3 ­0.2 10.7 5.0 4.5 3.1 Burundi 2.5 7.0 ­1.4 7.9 10.7 13.5 2.8 8.3 24.1 7.2 13.5 11.1 Cameroon 9.6 1.1 2.8 0.6 0.2 2.0 5.1 0.9 5.3 9.1 5.6 2.5 Cape Verde .. 10.7 1.9 1.2 ­1.9 0.4 5.4 4.4 6.8 6.7 6.4 2.1 Central African Republic .. 0.0 2.3 4.1 ­2.1 2.9 .. .. 9.3 3.6 3.9 3.4 Chad .. ­0.7 5.2 ­1.8 ­5.4 7.9 8.0 ­9.0 10.3 3.0 5.5 3.5 Comoros .. .. .. .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. 46.6 81.3 31.5 12.9 4.0 21.3 13.1 16.9 .. 57.0 3,367.2 121.7 Congo, Rep. .. 2.9 4.4 ­0.6 2.4 3.1 6.5 2.7 7.3 1.0 8.5 2.8 Côte d'Ivoire 14.7 ­0.8 3.1 3.3 1.4 3.9 2.5 1.9 6.3 6.7 6.0 3.2 Djibouti 12.1 .. .. .. .. .. .. .. .. 5.3 .. .. Equatorial Guinea .. 0.9 7.6 7.3 4.2 5.6 4.4 2.8 6.6 ­5.5 6.6 5.8 Eritrea .. .. .. .. .. .. .. .. .. .. .. .. Ethiopia 4.5 5.2 1.7 17.8 3.3 11.6 12.3 17.2 44.4 4.6 8.0 11.2 Gabon 12.3 7.7 0.0 2.2 0.4 1.2 ­1.4 5.0 5.3 6.5 3.7 1.7 Gambia, The 6.8 12.2 8.6 17.0 14.2 4.8 2.1 5.4 4.5 17.5 5.4 6.9 Ghana 50.1 37.3 14.8 26.7 12.6 15.1 10.9 10.7 16.5 48.3 27.6 18.4 Guinea .. .. .. .. .. .. .. .. 18.4 .. .. 18.4 Guinea-Bissau .. 33.0 3.3 ­3.5 0.9 3.3 2.0 4.6 10.5 70.5 37.5 3.7 Kenya 13.9 17.8 2.0 9.8 11.6 10.3 14.5 9.8 26.2 11.8 17.4 11.1 Lesotho 16.3 11.6 33.8 6.7 5.0 3.4 6.0 8.0 10.7 13.9 12.4 7.8 Liberia 14.7 .. .. .. .. .. .. .. .. 5.6 .. .. Madagascar 18.2 11.8 15.9 ­1.2 13.8 18.5 10.8 10.3 9.2 18.6 17.3 10.7 Malawi .. 11.8 14.7 9.6 11.4 15.4 14.0 8.0 8.7 16.8 31.0 14.9 Mali .. 0.6 5.0 ­1.3 ­3.1 6.4 1.5 1.4 9.2 ­0.1 4.2 2.6 Mauritania .. 6.6 3.9 5.2 10.4 12.1 6.2 7.3 7.3 7.5 6.4 6.7 Mauritius 42.0 13.5 6.5 3.9 4.7 4.9 8.9 8.8 9.7 11.2 7.6 6.3 Mozambique .. 47.0 16.8 13.4 12.7 7.2 13.2 8.2 10.3 45.1 34.5 11.5 Namibia .. .. .. 7.2 4.1 2.3 5.1 6.7 10.4 .. .. 5.9 Niger 10.3 ­0.8 2.6 ­1.6 0.3 7.8 0.0 0.1 11.3 3.6 4.3 3.0 Nigeria 10.0 7.4 12.9 14.0 15.0 17.9 8.2 5.4 11.6 20.9 30.6 12.3 Rwanda 7.2 4.2 2.0 7.4 12.3 9.0 8.9 9.1 15.4 4.7 8.6 7.9 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 8.7 0.3 2.2 0.0 0.5 1.7 2.1 5.9 5.8 6.9 4.4 2.4 Seychelles 13.6 3.9 0.2 3.3 3.9 0.9 ­0.4 5.3 37.0 4.0 2.0 6.9 Sierra Leone .. .. .. .. .. .. .. 11.5 17.5 .. .. 14.5 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 13.7 14.3 9.2 5.6 ­0.9 2.1 3.2 6.1 9.8 14.6 9.9 5.1 Sudan 25.4 65.2 8.3 7.7 8.4 8.5 7.2 8.0 16.0 36.2 80.4 8.6 Swaziland 18.7 13.1 12.0 7.3 3.4 4.8 5.3 9.5 13.4 15.0 9.5 8.2 Tanzania 30.2 35.8 1.0 5.3 4.7 5.0 7.3 7.0 10.3 30.1 23.1 5.7 Togo 12.3 1.0 3.1 ­1.0 0.4 6.8 2.2 1.0 8.7 5.0 7.1 3.0 Uganda .. 33.1 ­0.3 8.7 3.7 8.4 7.3 6.1 12.1 111.2 13.0 5.7 Zambia .. 107.0 22.2 21.4 18.0 18.3 9.0 10.7 12.4 69.3 76.2 17.7 Zimbabwe 5.4 17.4 140.1 431.7 282.4 302.1 1,096.7 24,411.0 .. 12.8 28.6 3,349.6 NORTH AFRICA Algeria 9.5 16.7 1.4 2.6 3.6 1.6 2.5 3.5 4.4 9.0 18.6 2.7 Egypt, Arab Rep. 20.8 16.8 2.7 4.5 11.3 4.9 7.6 9.3 18.3 17.4 10.5 7.1 Libya 9.7 8.5 ­9.8 ­2.2 ­2.2 2.0 3.4 .. .. 7.9 6.7 ­2.9 Morocco 9.4 6.8 2.8 1.2 1.5 1.0 3.3 2.0 3.8 7.6 4.4 2.0 Tunisia .. 6.5 2.7 2.7 3.6 2.0 4.5 3.1 4.9 7.6 4.9 3.2 a. Provisional. 48 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.12 Table Price indexes Exports of goods and Imports of goods and Inflation, GDP deflator Consumer price index services price index services price index (annual %) (2000 = 100) (2000 = 100) (2000 = 100) 2007 2008a 2007 2008a 2007 2008a 2007 2008a SUB­SAHARAN AFRICA 6.8 10.8 111.8 125.2 .. .. 158.0 175.8 Excluding South Africa 6.7 11.2 112.1 126.6 .. .. .. .. Excl. S. Africa & Nigeria 6.8 10.8 111.8 125.2 .. .. 158.9 183.1 Angola 4.1 19.9 127.2 143.0 .. .. .. .. Benin 2.9 9.4 105.1 113.5 .. .. .. .. Botswana 13.0 17.2 119.5 134.6 132.9 132.5 181.0 191.3 Burkina Faso 3.7 5.1 102.1 113.0 .. .. .. .. Burundi 8.3 24.5 111.4 138.2 .. .. .. .. Cameroon 2.1 1.7 106.1 111.7 201.7 242.6 163.6 172.5 Cape Verde 3.2 5.4 110.0 117.5 69.3 74.2 118.2 126.5 Central African Republic 2.0 4.6 107.7 117.7 139.1 145.4 184.8 200.6 Chad 1.7 11.9 98.3 108.5 251.5 301.3 251.5 301.3 Comoros 5.2 5.5 .. .. 193.3 213.1 193.3 213.1 Congo, Dem. Rep. 17.7 19.5 132.2 .. 172.8 162.7 125.1 121.0 Congo, Rep. ­7.9 23.8 109.4 117.4 .. .. .. .. Côte d'Ivoire 2.7 8.1 104.4 111.0 155.3 187.4 183.0 244.0 Djibouti 3.1 3.1 .. .. .. .. .. .. Equatorial Guinea ­1.2 23.7 107.3 114.4 .. .. .. .. Eritrea 5.9 18.0 .. .. 111.3 .. 113.2 .. Ethiopia 16.8 29.1 131.7 190.1 118.4 141.9 151.5 171.1 Gabon 5.2 14.2 103.6 109.0 246.2 367.4 168.6 197.9 Gambia, The 5.7 6.0 107.5 112.3 116.1 117.2 136.4 164.6 Ghana 13.8 18.0 122.8 143.1 164.3 184.3 164.8 170.9 Guinea 17.4 38.9 100.0 118.4 202.1 131.2 220.0 145.4 Guinea-Bissau 9.6 9.5 106.7 117.8 115.9 .. 146.1 .. Kenya 4.7 27.0 125.6 158.6 159.4 203.1 137.1 169.4 Lesotho 9.2 9.6 114.6 126.8 120.6 134.7 89.4 87.2 Liberia 16.0 12.8 .. .. .. .. .. .. Madagascar 9.7 9.6 122.2 133.5 141.7 145.8 140.5 163.7 Malawi 7.4 8.9 123.0 133.8 344.3 429.9 209.7 300.8 Mali 4.1 13.6 103.0 112.4 165.1 .. 186.7 .. Mauritania ­2.6 .. 113.9 122.3 142.0 .. .. .. Mauritius 7.0 7.6 118.5 130.1 115.4 139.2 132.9 161.8 Mozambique 7.4 6.5 122.5 135.1 141.9 137.5 190.6 197.2 Namibia 9.3 12.0 112.1 123.7 174.4 265.4 142.0 266.3 Niger 3.3 7.6 100.1 111.4 .. .. .. .. Nigeria 4.8 14.4 114.1 127.3 .. .. .. .. Rwanda 10.5 17.4 118.8 137.1 .. .. .. .. São Tomé and Príncipe 19.4 23.7 .. .. .. .. .. .. Senegal 5.6 7.3 108.1 114.3 169.9 183.3 183.5 198.8 Seychelles 6.7 25.3 104.9 143.8 115.6 96.9 115.6 96.9 Sierra Leone 10.3 11.7 111.5 131.0 .. .. .. .. Somalia .. .. .. .. .. .. .. .. South Africa 9.0 10.8 109.5 120.2 183.9 200.5 157.0 168.1 Sudan 7.0 15.8 115.7 134.3 224.6 261.3 224.7 261.3 Swaziland 8.9 3.4 115.3 130.7 157.4 134.4 117.2 101.1 Tanzania 9.0 8.9 114.8 126.6 .. .. .. .. Togo 1.3 4.4 103.2 112.2 .. .. .. .. Uganda 7.3 6.3 113.9 127.6 131.1 139.5 132.1 137.4 Zambia 11.8 10.8 120.6 135.7 132.3 120.2 106.2 111.2 Zimbabwe .. .. 293,318.0 .. .. .. .. .. NORTH AFRICA 5.4 12.3 107.0 112.0 .. .. 136.3 168.1 Algeria 6.8 17.2 106.1 110.9 237.9 367.9 162.5 194.8 Egypt, Arab Rep. 12.6 12.3 117.7 139.2 87.2 106.0 82.9 105.9 Libya 5.4 55.5 .. .. .. .. .. .. Morocco 3.8 3.1 105.4 109.4 152.7 189.6 157.9 191.3 Tunisia 2.4 5.0 107.8 113.1 158.5 202.8 166.6 210.2 ALL AFRICA 6.7 11.3 111.4 123.0 .. .. 149.1 172.6 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 49 Table 2.13 Gross domestic savings Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 35.4 16.1 22.0 21.5 22.6 24.9 28.6 29.0 33.6 22.2 14.5 24.7 Excluding South Africa 31.4 9.7 20.2 22.1 26.2 29.5 34.1 33.0 36.6 16.1 10.4 26.8 Excl. S. Africa & Nigeria 14.3 12.9 14.7 15.8 18.0 20.1 23.0 23.0 26.6 13.1 12.4 19.1 Angola .. 29.7 23.9 19.2 25.1 37.9 49.5 47.9 62.6 24.0 22.0 35.9 Benin ­6.3 2.2 3.7 6.0 5.5 6.9 .. .. .. ­2.4 3.8 5.8 Botswana 26.7 42.6 52.2 50.4 50.7 52.4 52.4 51.2 49.6 35.3 39.7 52.1 Burkina Faso ­7.2 5.4 3.7 4.5 1.8 4.8 2.8 .. .. ­1.6 9.0 2.6 Burundi ­0.6 ­5.4 ­9.7 ­8.7 ­11.0 ­23.1 ­19.9 .. .. 3.1 ­5.2 ­12.3 Cameroon 21.7 20.7 19.0 17.8 18.5 18.1 18.9 18.1 19.7 24.2 18.5 18.8 Cape Verde .. ­8.1 ­15.7 ­15.8 ­1.5 4.4 4.6 5.3 8.2 ­2.2 ­5.6 ­4.4 Central African Republic ­8.9 ­0.6 4.3 1.6 0.0 0.1 1.4 1.5 1.6 ­1.1 3.7 2.2 Chad .. ­7.7 ­40.8 18.0 24.5 35.7 43.6 34.6 25.2 ­8.1 ­0.5 16.9 Comoros ­10.1 ­3.2 ­4.0 ­5.8 ­10.6 ­12.9 ­14.0 ­11.4 ­8.1 ­4.5 ­4.5 ­8.6 Congo, Dem. Rep. 10.1 9.3 4.0 5.0 4.0 6.4 4.5 8.8 6.9 10.9 8.8 5.3 Congo, Rep. 35.7 23.8 51.0 51.3 51.3 57.6 65.7 57.2 .. 31.9 28.8 55.5 Côte d'Ivoire 20.4 11.3 26.7 21.0 20.0 17.2 19.6 14.3 14.8 19.6 17.8 19.0 Djibouti .. ­10.4 4.9 5.3 4.3 8.6 12.2 18.1 .. .. ­6.4 5.8 Equatorial Guinea .. ­20.1 79.0 80.1 78.9 83.7 86.1 86.9 72.8 .. 13.7 80.3 Eritrea .. .. ­27.4 ­40.9 ­41.5 ­27.2 ­17.2 ­17.7 .. .. ­29.7 ­29.2 Ethiopia .. 9.6 9.9 7.7 8.8 2.6 1.5 5.5 3.8 10.5 9.7 6.4 Gabon 60.6 36.9 43.7 48.2 54.6 58.3 57.4 55.0 66.3 44.3 43.6 54.8 Gambia, The 5.8 10.7 12.9 11.1 8.9 4.0 11.2 6.7 6.2 6.5 7.4 9.0 Ghana 4.9 5.5 7.4 7.0 7.3 4.9 5.7 7.6 5.6 4.8 7.5 6.5 Guinea .. 22.2 9.5 7.8 7.4 11.3 10.5 10.4 10.5 15.1 18.3 10.8 Guinea-Bissau ­1.0 2.8 ­11.8 ­1.6 14.1 11.5 ­3.9 7.7 4.9 ­0.9 1.5 ­0.8 Kenya 18.1 18.5 9.8 10.5 10.8 9.4 8.1 9.0 10.6 18.3 14.6 9.4 Lesotho ­52.0 ­42.4 ­17.7 ­23.0 ­17.5 ­22.3 ­21.4 ­23.4 ­34.7 ­66.3 ­34.6 ­20.7 Liberia 14.8 .. ­3.3 ­3.2 ­0.7 2.4 ­34.6 ­30.5 .. 2.2 .. ­10.5 Madagascar ­1.4 5.5 7.7 8.9 8.5 8.0 14.1 11.1 10.4 2.9 4.2 10.2 Malawi 10.8 13.4 .. ­3.4 2.0 ­1.1 ­1.3 4.9 4.1 12.7 3.4 1.6 Mali 1.1 6.4 11.3 13.3 8.6 11.0 14.8 13.5 .. ­0.4 7.6 12.3 Mauritania ­3.5 4.9 ­1.9 ­5.0 ­3.1 ­15.0 18.8 18.7 .. 3.1 2.4 0.9 Mauritius 14.5 23.5 25.2 24.8 23.4 18.9 17.5 17.5 16.9 20.0 24.1 21.6 Mozambique ­8.9 ­5.8 14.9 6.1 10.0 9.3 12.8 11.9 13.0 ­6.2 ­2.9 10.4 Namibia 38.4 18.2 16.4 10.3 16.8 19.8 26.7 19.1 13.5 10.8 12.7 16.9 Niger 14.6 1.2 5.3 5.1 4.1 13.7 .. .. .. 7.3 2.7 6.0 Nigeriab .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 4.2 6.2 ­0.5 0.4 4.4 5.1 2.7 2.8 1.3 5.0 ­5.5 2.3 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 2.1 2.4 6.8 8.8 7.9 14.1 10.7 8.5 7.7 4.3 5.4 9.4 Seychelles 27.1 20.3 24.4 21.5 14.7 3.1 8.1 ­1.9 6.7 24.1 21.7 13.1 Sierra Leone 0.9 8.7 ­8.2 ­3.7 ­0.4 4.2 7.8 6.1 7.5 9.1 2.8 ­1.4 Somalia ­12.9 ­12.5 .. .. .. .. .. .. .. ­6.3 ­12.5 .. South Africa 37.9 23.2 19.9 19.2 17.3 17.2 17.1 18.3 18.4 28.5 19.4 18.4 Sudan 2.1 8.2 13.3 15.7 18.7 13.8 13.9 20.5 24.3 4.2 9.6 16.2 Swaziland 1.2 5.3 14.6 18.1 13.5 11.2 11.5 11.6 15.1 3.7 2.0 11.9 Tanzania .. 1.3 11.8 12.0 11.2 9.7 10.7 .. .. .. 2.0 10.6 Togo 23.2 14.7 0.6 5.3 4.5 1.5 .. .. .. 12.3 6.7 1.8 Uganda ­0.4 0.6 5.9 6.7 9.7 11.3 7.6 8.2 5.8 2.3 4.3 7.7 Zambia 19.3 16.6 7.9 13.0 19.9 21.8 31.5 30.4 24.7 14.0 9.0 17.2 Zimbabwe 13.8 17.5 7.1 6.2 4.1 0.6 .. .. .. 16.5 16.9 7.2 NORTH AFRICA 29.5 22.8 24.3 27.6 31.2 35.6 37.2 36.5 45.5 24.9 20.2 31.8 Algeria 43.1 27.1 40.9 44.9 47.7 54.9 56.9 56.5 71.5 31.5 30.1 51.1 Egypt, Arab Rep. 15.2 16.1 13.9 14.3 15.6 15.7 17.1 16.3 17.2 15.5 14.2 15.2 Libya .. 27.2 26.4 .. .. .. .. .. .. .. 17.6 27.6 Morocco 14.9 19.9 23.8 24.5 24.2 23.2 24.0 23.4 23.8 16.7 17.8 23.4 Tunisia 24.0 20.0 21.4 21.2 21.2 21.4 21.5 22.4 21.9 22.7 22.3 22.0 ALL AFRICA 34.8 19.2 23.2 24.2 26.0 29.0 31.9 32.0 38.2 24.1 17.2 27.6 a. Provisional. b. For 1994­2000 Nigeria's values were distorted because the official exchange rate used by the government for oil exports and oil value added was significantly overvalued. 50 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.14 Table Gross national savings Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 13.2 12.9 10.7 11.8 11.6 10.9 10.0 9.8 4.3 13.0 12.3 10.4 Excluding South Africa 4.6 9.1 8.0 9.4 9.8 9.0 7.9 7.8 0.7 7.0 9.2 8.1 Excl. S. Africa & Nigeria 7.0 10.7 10.5 12.4 13.3 12.5 11.2 10.9 0.9 8.7 11.0 10.9 Angola .. .. 9.8 7.6 12.6 24.8 37.1 32.8 47.4 .. 4.8 21.6 Benin .. .. 7.3 9.4 8.9 10.6 .. .. .. .. 10.8 9.9 Botswana 28.7 43.3 44.1 45.2 46.3 50.9 53.3 55.6 54.8 33.7 41.6 51.0 Burkina Faso ­1.6 13.7 7.5 9.1 5.1 7.9 6.3 .. .. 4.7 16.5 6.4 Burundi .. .. 2.9 6.0 5.2 1.1 4.5 .. .. .. 1.4 3.2 Cameroon 5.1 16.1 15.1 15.5 16.9 16.6 18.9 19.6 20.2 19.2 13.5 17.2 Cape Verde .. .. 9.4 9.2 21.8 28.8 26.4 26.0 26.8 .. 8.1 18.4 Central African Republic .. .. 7.4 3.9 4.4 2.3 6.6 4.5 4.0 .. 12.5 5.3 Chad .. ­2.7 ­40.2 4.9 13.7 21.3 27.5 20.3 7.8 ­3.3 3.5 7.8 Comoros .. 10.1 9.6 7.2 6.5 5.9 5.0 9.1 11.2 .. 6.8 8.5 Congo, Dem. Rep. 9.3 0.8 5.3 9.9 6.2 5.6 7.8 8.3 0.2 7.4 0.4 4.7 Congo, Rep. .. .. 24.0 26.7 26.3 31.8 42.9 .. .. .. 3.2 28.9 Côte d'Ivoire .. .. 16.8 12.3 12.4 10.0 12.1 7.9 9.6 .. 11.9 11.1 Djibouti .. .. 15.6 17.6 16.2 20.1 19.4 .. .. .. 11.4 15.1 Equatorial Guinea .. ­22.0 32.5 26.4 22.1 33.6 38.9 38.7 35.7 .. 6.0 33.8 Eritrea .. .. 28.6 26.6 20.3 3.9 9.7 .. .. .. 15.6 19.6 Ethiopia .. 11.9 19.5 20.6 21.5 16.7 15.1 20.5 16.5 11.8 15.3 18.3 Gabon .. 24.0 32.4 33.8 35.2 45.3 37.3 39.6 48.7 23.5 29.3 39.0 Gambia, The .. .. 18.2 15.2 23.8 11.7 17.0 10.6 10.8 .. 16.2 15.1 Ghana .. .. 20.0 20.5 25.7 22.9 21.4 23.6 19.6 .. 10.0 21.2 Guinea .. 14.6 9.2 6.8 5.7 9.3 11.8 8.7 9.2 8.8 14.2 9.6 Guinea-Bissau ­6.3 15.3 ­1.0 9.8 31.6 24.8 12.8 34.4 22.9 ­0.3 5.5 13.0 Kenya 15.4 18.6 13.2 13.5 16.2 16.1 16.2 17.2 17.6 16.2 15.1 15.1 Lesotho 34.5 40.8 24.7 19.5 25.5 21.4 29.1 39.1 24.8 33.0 29.3 27.5 Liberia .. .. ­11.1 ­6.4 33.1 39.8 ­17.3 ­14.7 .. .. .. 0.3 Madagascar .. 9.2 8.3 13.0 12.7 11.1 16.2 14.0 12.4 5.0 4.9 12.7 Malawi .. 13.6 .. 0.7 4.8 4.2 2.9 9.4 9.1 .. 2.3 4.5 Mali 1.9 15.1 9.0 14.4 8.6 11.4 13.0 25.7 .. 2.6 14.4 13.8 Mauritania 3.9 17.6 16.8 9.9 8.2 ­5.4 28.7 29.2 .. 17.1 9.0 12.4 Mauritius 14.0 26.3 26.6 26.3 23.8 19.7 19.1 19.8 22.7 19.7 26.5 23.4 Mozambique ­6.9 2.1 15.0 7.3 10.0 7.7 9.5 9.3 10.4 ­3.8 0.1 9.6 Namibia 26.9 34.8 25.6 24.2 28.1 27.9 38.2 29.3 24.8 18.5 27.3 27.7 Niger 13.0 ­1.2 4.7 6.4 10.0 17.0 .. .. .. 5.5 1.0 7.6 Nigeriab .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 13.3 11.3 10.3 11.3 18.6 20.6 13.1 15.8 13.0 10.9 8.1 14.3 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal .. .. .. .. .. .. 18.7 19.1 17.9 .. .. 18.6 Seychelles .. .. 16.4 16.7 12.4 2.1 7.5 ­3.3 2.7 .. 22.0 9.9 Sierra Leone 0.5 2.6 10.6 14.0 9.4 14.7 12.0 9.6 14.1 7.2 0.2 8.0 Somalia ­5.8 .. .. .. .. .. .. .. .. 3.2 .. .. South Africa 34.0 19.3 16.9 15.8 14.5 14.0 14.0 14.0 14.0 24.6 16.6 14.9 Sudan 7.9 0.9 9.2 12.2 16.0 12.9 9.7 11.9 15.4 7.4 5.1 11.4 Swaziland .. 19.7 9.8 7.9 6.6 12.3 7.4 18.2 30.5 .. 16.4 13.9 Tanzania .. .. 11.1 11.8 10.7 9.7 10.4 .. .. .. 2.0 10.4 Togo .. .. 4.1 7.3 6.5 3.2 .. .. .. .. 4.5 4.1 Uganda ­0.9 0.6 7.1 7.5 10.8 10.8 12.1 13.8 12.0 2.6 6.5 10.0 Zambia 7.3 6.7 5.9 10.7 13.0 17.7 23.9 22.9 19.8 2.2 0.6 12.4 Zimbabwe .. 15.7 7.0 5.9 4.0 ­0.4 .. .. .. 17.3 16.0 5.9 NORTH AFRICA 20.7 14.2 14.9 14.5 14.5 13.6 14.2 14.5 .. 16.8 11.7 14.2 Algeria .. .. 38.8 43.5 46.3 51.9 54.4 56.8 71.6 .. 27.8 49.4 Egypt, Arab Rep. .. .. .. .. .. .. .. 26.3 23.6 .. .. 25.0 Libya .. .. .. .. .. .. .. .. .. .. .. .. Morocco 18.3 24.4 29.4 30.5 30.7 30.6 31.8 32.4 34.4 20.0 21.2 30.5 Tunisia .. .. 22.3 22.1 22.4 20.7 22.7 22.6 16.7 .. 21.9 21.8 ALL AFRICA 15.2 13.4 12.3 12.8 12.6 11.8 11.4 11.4 2.8 14.1 12.1 11.2 a. Provisional. b. For 1994­2000 Nigeria's values were distorted because the official exchange rate used by the government for oil exports and oil value added was significantly overvalued. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 51 Table 2.15 General government final consumption expenditure Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 12.4 17.2 14.1 15.0 15.0 14.5 13.7 13.4 12.3 15.2 16.7 14.1 Excluding South Africa 11.7 15.3 12.3 12.0 11.6 10.9 10.3 10.0 9.4 13.7 14.0 11.2 Excl. S. Africa & Nigeria 14.6 14.8 13.1 13.0 12.9 12.4 12.0 11.5 10.8 14.2 13.7 12.3 Angola .. 34.5 .. .. .. .. .. .. .. 31.5 40.7 .. Benin 8.6 11.0 12.5 13.3 13.6 15.0 .. .. .. 12.7 10.5 12.9 Botswana 21.3 24.1 20.9 21.5 21.3 20.6 19.2 19.5 19.2 24.3 26.7 20.6 Burkina Faso 9.2 21.1 25.2 22.2 21.6 22.3 22.0 .. .. 15.6 22.5 22.3 Burundi 9.2 10.8 19.1 22.7 26.1 26.5 28.8 .. .. 9.3 17.0 22.9 Cameroon 9.7 12.8 10.2 10.0 10.2 10.0 9.6 9.2 12.7 10.0 10.6 10.2 Cape Verde .. 14.7 11.7 14.7 20.6 20.3 20.4 20.6 18.4 13.1 17.0 17.7 Central African Republic 15.1 14.9 12.9 11.0 10.5 13.3 11.1 2.7 3.5 15.6 13.9 10.1 Chad .. 10.0 7.7 7.6 4.9 4.5 5.9 6.1 5.8 11.3 8.1 6.4 Comoros 30.9 24.5 17.4 14.7 14.3 13.5 12.6 12.3 12.1 28.6 20.3 13.9 Congo, Dem. Rep. 8.4 11.5 5.5 6.3 8.2 8.1 7.1 10.4 11.0 9.0 9.9 7.8 Congo, Rep. 17.6 13.8 18.4 17.0 16.0 13.0 13.2 14.1 .. 17.7 18.1 14.7 Côte d'Ivoire 16.9 16.8 7.8 8.2 8.3 8.3 8.3 8.4 8.1 16.5 11.9 8.0 Djibouti .. 31.5 28.3 29.5 29.7 27.1 28.3 26.0 .. .. 31.8 28.2 Equatorial Guinea .. 39.7 5.1 3.8 2.9 2.7 2.6 2.3 2.6 27.4 25.1 3.3 Eritrea .. .. 41.1 50.3 52.9 37.2 35.9 31.4 .. .. 39.7 45.4 Ethiopia .. 13.2 14.8 13.4 13.1 12.3 12.1 10.6 11.3 11.2 9.8 13.3 Gabon 13.2 13.4 11.0 10.1 9.3 8.3 8.4 8.9 7.8 18.3 13.2 9.4 Gambia, The 31.2 13.7 12.9 11.0 16.9 18.4 18.1 16.2 15.8 29.1 13.8 15.3 Ghana 11.2 9.3 9.9 11.5 12.2 11.7 13.4 14.1 13.6 9.0 11.7 11.8 Guinea .. 11.0 7.5 7.8 6.3 5.7 5.6 6.0 4.9 11.8 8.2 6.4 Guinea-Bissau 27.6 10.3 12.8 12.8 13.7 18.1 17.1 15.4 13.9 18.9 8.4 14.5 Kenya 19.8 18.6 17.1 18.1 17.9 17.4 16.6 17.2 10.8 18.3 15.8 16.2 Lesotho 21.8 21.4 28.7 27.6 25.7 26.8 26.8 25.4 26.8 21.8 26.3 27.8 Liberia 19.1 .. 13.7 8.5 10.4 11.1 11.5 14.6 .. 22.0 .. 12.0 Madagascar 12.1 8.0 8.1 9.2 6.9 6.1 4.6 4.7 4.6 9.8 7.9 6.9 Malawi 19.3 15.1 10.7 11.9 12.2 12.1 11.8 11.5 10.9 17.5 16.6 12.4 Mali 11.6 13.8 8.7 8.4 10.0 9.9 9.9 10.7 .. 12.3 12.7 9.4 Mauritania 45.3 25.9 22.3 30.1 21.9 22.7 19.9 20.1 .. 30.6 14.5 23.3 Mauritius 14.4 12.8 12.8 14.1 14.2 14.4 14.5 13.7 12.9 13.5 13.0 13.6 Mozambique 12.2 13.5 9.4 10.2 10.8 10.4 10.7 11.8 12.3 13.8 9.7 10.4 Namibia 17.4 30.6 21.5 22.2 20.4 19.3 18.4 19.2 18.0 27.9 31.0 20.6 Niger 10.4 15.0 12.2 11.4 13.2 11.7 .. .. .. 11.9 14.6 12.3 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 12.5 10.1 12.5 14.4 12.0 12.0 11.9 10.7 9.1 13.0 11.5 11.7 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 24.8 18.4 13.3 13.3 13.7 9.6 9.7 10.0 10.0 19.3 15.0 11.7 Seychelles 28.7 27.7 22.7 25.5 28.3 21.3 19.8 18.0 14.8 33.1 29.0 22.1 Sierra Leone 8.4 7.8 16.4 15.6 13.5 13.4 13.0 10.5 12.7 7.7 10.6 14.1 Somalia 15.6 .. .. .. .. .. .. .. .. 17.6 .. .. South Africa 14.3 19.7 18.4 19.3 19.4 19.4 19.4 19.7 20.2 17.4 19.4 19.1 Sudan 16.0 5.8 10.1 10.8 11.8 17.1 16.7 14.8 16.4 11.1 6.1 12.6 Swaziland 27.0 14.3 16.7 15.3 16.0 15.6 15.3 14.9 23.6 21.5 17.2 17.1 Tanzania .. 17.8 12.4 14.8 15.9 15.2 16.2 .. .. .. 14.0 13.8 Togo 22.4 14.2 8.4 9.8 9.7 17.6 18.5 18.6 16.3 16.9 12.8 13.2 Uganda .. 7.5 16.8 15.7 13.9 14.5 14.1 12.9 11.8 9.9 11.1 14.4 Zambia 25.5 19.0 11.8 14.4 18.1 9.7 10.2 10.4 9.0 23.0 17.7 11.5 Zimbabwe 18.5 19.4 17.9 16.6 23.3 27.2 .. .. .. 20.1 17.2 19.4 NORTH AFRICA 17.7 16.2 14.9 14.8 14.6 13.4 12.9 12.7 9.5 18.7 16.1 13.6 Algeria 15.2 16.1 15.4 14.8 13.8 11.5 11.3 12.0 6.8 17.2 16.6 12.6 Egypt, Arab Rep. 15.7 11.3 12.5 12.7 12.8 12.7 12.3 11.3 10.8 16.2 10.9 11.9 Libya .. 24.4 16.7 .. .. .. .. .. .. .. 24.3 19.6 Morocco 18.3 15.5 18.3 18.1 18.7 19.4 18.5 18.2 15.6 16.6 17.0 18.2 Tunisia 14.5 16.4 15.9 15.7 15.4 15.4 14.7 14.4 13.6 16.5 16.0 15.1 ALL AFRICA 13.6 16.7 14.4 14.9 14.8 14.1 13.3 13.1 11.2 16.0 16.3 13.9 a. Provisional. 52 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.16 Table Household final consumption expenditure Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 58.9 65.3 67.8 67.6 67.9 68.2 67.6 66.6 66.5 63.3 68.1 67.7 Excluding South Africa .. 72.5 73.5 73.1 72.0 72.5 71.6 .. .. 72.5 74.2 72.9 Excl. S. Africa & Nigeria 71.4 72.5 73.5 73.1 72.0 72.5 71.6 71.6 72.4 72.4 74.2 72.7 Angola .. 35.8 .. .. .. .. .. .. .. 44.5 42.6 .. Benin 97.7 86.8 83.8 80.7 80.9 78.1 .. .. .. 89.7 85.7 81.3 Botswana 52.0 33.2 26.9 28.1 28.0 27.0 28.4 29.3 31.2 40.4 33.6 27.3 Burkina Faso 98.0 73.5 71.2 73.3 76.6 72.8 75.2 .. .. 86.0 68.5 75.2 Burundi 91.4 94.5 90.6 85.9 84.9 96.6 91.1 .. .. 87.5 88.3 89.4 Cameroon 68.6 66.6 70.8 72.2 71.4 72.0 71.5 72.6 67.6 65.8 70.9 71.0 Cape Verde .. 93.4 104.0 101.1 80.9 75.4 75.0 74.1 73.5 89.1 88.6 86.7 Central African Republic 93.7 85.7 82.8 87.4 89.5 86.6 87.5 95.9 94.9 85.5 82.4 87.7 Chad .. 97.6 133.1 74.4 70.6 59.8 50.5 59.3 68.9 96.8 92.5 76.7 Comoros 79.2 78.7 86.6 91.1 96.2 99.5 101.4 99.1 96.0 75.9 84.2 94.8 Congo, Dem. Rep. 81.5 79.1 90.4 88.7 87.9 85.5 88.4 80.8 82.1 80.0 81.3 87.0 Congo, Rep. 46.8 62.4 30.7 31.7 32.7 29.4 21.1 28.7 .. 50.3 53.1 29.8 Côte d'Ivoire 62.8 71.9 65.5 70.8 71.7 74.5 72.0 77.3 77.1 63.9 70.3 73.0 Djibouti .. 78.9 66.8 65.2 66.0 64.2 59.5 55.9 .. .. 73.8 66.0 Equatorial Guinea .. 80.3 15.9 16.1 18.2 13.6 11.3 10.8 24.5 .. 61.2 16.3 Eritrea .. .. 86.3 90.6 88.6 90.0 81.3 86.2 .. .. 90.0 83.8 Ethiopia .. 77.2 75.2 78.8 78.2 85.1 86.4 83.9 84.9 78.4 80.5 80.2 Gabon 26.1 49.7 45.3 41.7 36.2 33.3 34.2 36.1 25.8 37.4 43.2 35.7 Gambia, The 63.0 75.6 74.3 78.0 74.2 77.6 70.7 77.1 78.0 64.4 78.8 75.7 Ghana 83.9 85.2 82.7 81.5 80.5 83.5 80.9 78.3 80.8 86.2 80.8 81.7 Guinea .. 66.9 83.0 84.4 86.3 82.9 83.8 83.6 84.6 73.1 73.5 82.8 Guinea-Bissau 73.3 86.9 98.9 88.7 72.2 70.4 86.7 77.0 81.3 82.0 90.1 86.3 Kenya 62.1 62.8 73.2 71.3 71.3 73.2 75.3 73.9 78.6 63.3 69.6 74.4 Lesotho 130.2 121.0 89.0 95.4 91.8 95.5 94.6 98.0 107.9 144.5 108.4 92.9 Liberia 66.1 .. 89.7 94.7 90.3 86.4 123.1 115.9 .. 75.8 .. 98.4 Madagascar 89.3 86.4 84.2 81.9 84.5 85.9 81.3 84.2 85.0 87.2 87.9 82.9 Malawi 69.9 71.5 .. 91.6 85.8 88.9 89.6 83.7 85.0 69.8 80.0 85.8 Mali 87.4 79.8 80.0 78.3 81.4 79.1 75.3 75.7 .. 88.1 79.7 78.3 Mauritania 58.2 69.2 79.7 74.9 81.2 92.3 61.3 61.2 .. 66.3 83.0 75.8 Mauritius 71.0 63.7 62.0 61.1 62.4 66.7 68.0 68.8 70.2 66.5 62.9 64.8 Mozambique 96.7 92.3 75.7 83.7 79.2 80.4 76.5 76.3 74.7 92.3 93.2 79.2 Namibia 44.2 51.2 62.1 67.5 62.8 60.9 54.9 61.8 68.5 61.3 56.3 62.5 Niger 75.1 83.8 82.5 83.6 82.7 74.6 .. .. .. 80.8 82.7 81.7 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 83.3 83.7 88.0 85.3 83.6 82.8 85.4 86.6 89.6 82.0 94.0 86.0 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 73.1 79.2 80.0 77.9 78.4 76.3 79.6 81.5 82.3 76.4 79.6 78.9 Seychelles 44.2 52.0 52.9 52.9 57.0 75.6 72.1 83.9 78.5 42.7 49.3 64.8 Sierra Leone 90.7 83.5 91.8 88.1 86.9 82.3 79.1 83.4 79.8 83.2 86.6 87.3 Somalia 97.3 .. .. .. .. .. .. .. .. 100.6 .. .. South Africa 47.8 57.1 61.7 61.5 63.4 63.4 63.5 62.1 61.5 54.2 61.2 62.5 Sudan 81.9 86.1 76.6 73.5 69.5 69.1 69.4 64.8 59.2 84.8 84.3 71.1 Swaziland 71.8 80.4 68.7 66.6 70.5 73.2 73.2 73.5 61.3 74.7 80.8 70.9 Tanzania .. 80.9 75.8 73.1 72.9 75.1 73.1 .. .. .. 84.0 75.6 Togo 54.5 71.1 91.0 84.8 85.8 80.9 .. .. .. 70.8 80.5 87.3 Uganda .. 91.9 77.3 77.5 76.4 74.2 78.3 78.9 82.4 87.2 84.6 77.8 Zambia 55.2 64.4 80.3 72.6 62.0 68.5 58.3 59.1 66.3 62.9 73.3 71.3 Zimbabwe 67.7 63.1 75.0 77.2 72.6 72.2 .. .. .. 63.4 65.9 73.4 NORTH AFRICA 61.3 64.1 61.8 61.4 60.3 59.1 58.2 59.1 57.1 63.1 65.6 60.0 Algeria 41.7 56.8 43.7 40.4 38.5 33.6 31.8 31.5 21.7 51.3 53.3 36.2 Egypt, Arab Rep. 69.2 72.6 73.6 73.0 71.7 71.6 70.6 72.4 72.0 68.3 75.0 72.9 Libya .. 48.4 56.9 .. .. .. .. .. .. .. 58.1 52.8 Morocco 66.8 64.6 57.9 57.3 57.1 57.5 57.5 58.4 60.6 66.7 65.3 58.4 Tunisia 61.5 63.6 62.7 63.1 63.4 63.3 63.7 63.2 64.5 60.8 61.7 62.9 ALL AFRICA 60.0 64.7 65.1 65.0 64.7 64.4 63.6 63.3 62.3 63.2 66.9 64.3 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 53 Table 2.17 Final consumption expenditure plus discrepancy Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 64.6 83.9 78.0 78.5 77.4 75.1 71.4 71.0 66.4 77.8 85.5 75.3 Excluding South Africa 68.6 90.3 79.8 77.9 73.8 70.5 65.9 67.0 63.4 83.9 89.6 73.2 Excl. S. Africa & Nigeria 85.7 87.1 85.3 84.2 82.0 79.9 77.0 77.0 73.4 86.9 87.6 80.9 Angola .. 70.3 76.1 80.8 74.9 62.1 50.5 52.1 37.4 76.0 78.0 64.1 Benin 106.3 97.8 96.3 94.0 94.5 93.1 .. .. .. 102.4 96.2 94.2 Botswana 73.3 57.4 47.8 49.6 49.3 47.6 47.6 48.8 50.4 64.7 60.3 47.9 Burkina Faso 107.2 94.6 96.3 95.5 98.2 95.2 97.2 .. .. 101.6 91.0 97.4 Burundi 100.6 105.4 109.7 108.7 111.0 123.1 119.9 .. .. 96.9 105.2 112.3 Cameroon 78.3 79.3 81.0 82.2 81.5 81.9 81.1 81.9 80.3 75.8 81.5 81.2 Cape Verde .. 108.1 115.7 115.8 101.5 95.6 95.4 94.7 91.8 102.2 105.6 104.4 Central African Republic 108.9 100.6 95.7 98.4 100.0 99.9 98.6 98.5 98.4 101.1 96.3 97.8 Chad .. 107.7 140.8 82.0 75.5 64.3 56.4 65.4 74.8 108.1 100.5 83.1 Comoros 110.1 103.2 104.0 105.8 110.6 112.9 114.0 111.4 108.1 104.5 104.5 108.6 Congo, Dem. Rep. 89.9 90.7 96.0 95.0 96.0 93.6 95.5 91.2 93.1 89.1 91.2 94.7 Congo, Rep. 64.3 76.2 49.0 48.7 48.7 42.4 34.3 42.8 .. 68.1 71.2 44.5 Côte d'Ivoire 79.6 88.7 73.3 79.0 80.0 82.8 80.4 85.7 85.2 80.4 82.2 81.0 Djibouti .. 110.4 95.1 94.7 95.7 91.4 87.8 81.9 .. .. 106.4 94.2 Equatorial Guinea .. 120.1 21.0 19.9 21.1 16.3 13.9 13.1 27.2 .. 86.3 19.7 Eritrea .. .. 127.4 140.9 141.5 127.2 117.2 117.7 .. .. 129.7 129.2 Ethiopia .. 90.4 90.1 92.3 91.2 97.4 98.5 94.5 96.2 89.5 90.3 93.6 Gabon 39.4 63.1 56.3 51.8 45.4 41.7 42.6 45.0 33.7 55.7 56.4 45.2 Gambia, The 94.2 89.3 87.1 88.9 91.1 96.0 88.8 93.3 93.8 93.5 92.6 91.0 Ghana 95.1 94.5 92.6 93.0 92.7 95.1 94.3 92.4 94.4 95.2 92.5 93.5 Guinea .. 77.8 90.5 92.2 92.6 88.7 89.5 89.6 89.5 84.9 81.7 89.2 Guinea-Bissau 101.0 97.2 111.8 101.6 85.9 88.5 103.9 92.3 95.1 100.9 98.5 100.8 Kenya 81.9 81.5 90.2 89.5 89.2 90.6 91.9 91.0 89.4 81.7 85.4 90.6 Lesotho 152.0 142.4 117.7 123.0 117.5 122.3 121.4 123.4 134.7 166.3 134.6 120.7 Liberia 85.2 .. 103.3 103.2 100.7 97.6 134.6 130.5 .. 97.8 .. 110.5 Madagascar 101.4 94.5 92.3 91.1 91.5 92.0 85.9 88.9 89.6 97.1 95.8 89.8 Malawi 89.2 86.6 .. 103.4 98.0 101.1 101.3 95.1 95.9 87.3 96.6 98.4 Mali 98.9 93.6 88.7 86.7 91.4 89.0 85.2 86.5 .. 100.4 92.4 87.7 Mauritania 103.5 95.1 101.9 105.0 103.1 115.0 81.2 81.3 .. 96.9 97.6 99.1 Mauritius 85.5 76.5 74.8 75.2 76.6 81.1 82.5 82.5 83.1 80.0 75.9 78.4 Mozambique 108.9 105.8 85.1 93.9 90.0 90.7 87.2 88.1 87.0 106.2 102.9 89.6 Namibia 61.6 81.8 83.6 89.7 83.2 80.2 73.3 80.9 86.5 89.2 87.3 83.1 Niger 85.4 98.8 94.7 94.9 95.9 86.3 .. .. .. 92.7 97.3 94.0 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 95.8 93.8 100.5 99.6 95.6 94.9 97.3 97.2 98.7 95.0 105.5 97.7 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 97.9 97.6 93.2 91.2 92.1 85.9 89.3 91.5 92.3 95.7 94.6 90.6 Seychelles 72.9 79.7 75.6 78.5 85.3 96.9 91.9 101.9 93.3 75.9 78.3 86.9 Sierra Leone 99.1 91.3 108.2 103.7 100.4 95.8 92.2 93.9 92.5 90.9 97.2 101.4 Somalia 112.9 112.5 .. .. .. .. .. .. .. 106.3 112.5 .. South Africa 62.1 76.8 80.1 80.8 82.7 82.8 82.9 81.7 81.6 71.5 80.6 81.6 Sudan 97.9 91.8 86.7 84.3 81.3 86.2 86.1 79.5 75.7 95.8 90.4 83.8 Swaziland 98.8 94.7 85.4 81.9 86.5 88.8 88.5 88.4 84.9 96.3 98.0 88.1 Tanzania .. 98.7 88.2 88.0 88.8 90.3 89.3 .. .. .. 98.0 89.4 Togo 76.8 85.3 99.4 94.7 95.5 98.5 .. .. .. 87.7 93.3 98.2 Uganda 100.4 99.4 94.1 93.3 90.3 88.7 92.4 91.8 94.2 97.7 95.7 92.3 Zambia 80.7 83.4 92.1 87.0 80.1 78.2 68.5 69.6 75.3 86.0 91.0 82.8 Zimbabwe 86.2 82.5 92.9 93.8 95.9 99.4 .. .. .. 83.5 83.1 92.8 NORTH AFRICA 70.5 77.2 75.7 72.4 68.8 64.4 62.8 63.5 54.5 75.1 79.8 68.2 Algeria 56.9 72.9 59.1 55.1 52.3 45.1 43.1 43.5 28.5 68.5 69.9 48.9 Egypt, Arab Rep. 84.8 83.9 86.1 85.7 84.4 84.3 82.9 83.7 82.8 84.5 85.8 84.8 Libya .. 72.8 73.6 .. .. .. .. .. .. .. 82.4 72.4 Morocco 85.1 80.1 76.2 75.5 75.8 76.8 76.0 76.6 76.2 83.3 82.2 76.6 Tunisia 76.0 80.0 78.6 78.8 78.8 78.6 78.5 77.6 78.1 77.3 77.7 78.0 ALL AFRICA 65.2 80.8 76.8 75.8 74.0 71.0 68.1 68.0 61.8 75.9 82.8 72.4 a. Provisional. 54 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.18 Table Final consumption expenditure plus discrepancy per capita Current prices ($) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 465 492 402 484 575 639 688 767 814 464 470 574 Excluding South Africa 379 357 306 322 356 400 444 518 599 351 307 387 Excl. S. Africa & Nigeria 388 365 313 329 364 409 453 529 611 359 314 396 Angola .. 677 574 721 918 1,144 1,334 1,759 1,733 581 469 1,008 Benin 420 376 380 455 503 507 .. .. .. 332 343 414 Botswana 781 1,591 1,597 2,287 2,668 2,724 2,817 3,198 3,433 821 1,789 2,432 Burkina Faso 303 331 250 312 371 371 391 .. .. 260 235 306 Burundi 224 210 102 93 103 133 145 .. .. 215 170 114 Cameroon 581 723 530 658 739 764 802 914 994 663 631 709 Cape Verde .. 1,034 1,568 1,997 1,996 2,016 2,365 2,785 3,185 809 1,201 2,079 Central African Republic 373 497 249 276 308 322 342 389 438 352 341 311 Chad .. 306 307 237 340 372 339 426 565 221 232 325 Comoros 406 593 464 596 682 728 749 824 891 394 507 639 Congo, Dem. Rep. 461 223 99 98 111 115 138 145 168 287 153 116 Congo, Rep. 605 872 466 532 634 755 761 921 .. 681 620 618 Côte d'Ivoire 962 760 466 588 657 704 710 843 969 681 630 657 Djibouti .. 891 737 759 806 805 816 804 .. .. 833 788 Equatorial Guinea .. 418 806 1,019 1,869 2,204 2,129 2,569 7,637 .. 410 2,160 Eritrea .. .. 215 202 205 326 320 334 .. .. 239 258 Ethiopia .. 226 102 111 126 161 195 233 316 200 160 163 Gabon 2,472 4,057 2,153 2,383 2,429 2,636 2,917 3,662 3,355 2,570 2,723 2,561 Gambia, The 368 316 232 227 247 290 287 372 442 290 324 296 Ghana 383 372 278 338 384 465 536 606 652 350 358 416 Guinea .. 338 334 376 404 314 305 425 388 1,156 382 352 Guinea-Bissau 134 232 166 171 170 182 219 229 259 171 208 195 Kenya 365 299 361 395 414 478 565 654 801 299 315 490 Lesotho 506 513 408 627 771 850 924 1,027 1,083 460 611 731 Liberia 425 .. 189 135 144 155 237 264 .. 437 .. 188 Madagascar 477 258 251 299 233 263 262 351 420 320 245 284 Malawi 178 172 .. 200 200 218 236 245 287 150 180 209 Mali 291 296 280 346 396 407 418 480 .. 238 267 345 Mauritania 489 499 431 482 554 713 711 688 .. 459 571 556 Mauritius 1,020 1,725 2,813 3,226 3,766 4,103 4,234 4,441 5,666 1,078 2,412 3,768 Mozambique 316 193 187 224 255 291 295 330 389 275 187 265 Namibia 1,346 1,357 1,446 2,249 2,756 2,883 2,859 3,392 3,506 1,459 1,659 2,495 Niger 371 314 172 208 217 217 .. .. .. 279 217 189 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 214 339 193 204 214 251 299 351 453 270 283 264 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 608 741 477 584 673 662 722 869 998 550 580 649 Seychelles 1,667 4,196 6,301 6,688 7,234 10,330 10,510 10,936 9,007 2,170 5,142 8,124 Sierra Leone 335 145 223 217 219 228 249 288 325 248 188 236 Somalia 105 154 .. .. .. .. .. .. .. 136 154 .. South Africa 1,818 2,444 1,963 2,941 3,856 4,288 4,511 4,847 4,641 2,094 2,782 3,514 Sudan 364 421 357 404 465 610 793 910 1,070 496 325 583 Swaziland 889 1,222 911 1,328 1,770 1,994 2,078 2,221 1,904 753 1,469 1,624 Tanzania .. 165 239 245 266 327 319 .. .. .. 193 269 Togo 314 354 264 292 337 347 .. .. .. 271 308 290 Uganda 99 241 223 229 258 285 310 356 432 231 220 283 Zambia 543 347 312 339 379 477 609 645 854 418 340 472 Zimbabwe 791 693 1,625 555 362 272 .. .. .. 704 536 676 NORTH AFRICA 854 1,110 1,148 1,196 1,251 1,329 1,467 1,707 1,875 961 1,137 1,390 Algeria 1,281 1,789 1,074 1,176 1,374 1,405 1,504 1,724 1,442 1,697 1,217 1,303 Egypt, Arab Rep. 438 626 1,038 957 879 980 1,133 1,365 1,654 529 809 1,158 Libya .. 4,824 2,537 .. .. .. .. .. .. .. 5,113 3,691 Morocco 827 856 1,055 1,274 1,447 1,517 1,637 1,865 2,106 654 1,006 1,438 Tunisia 1,041 1,206 1,691 2,001 2,231 2,271 2,398 2,658 3,038 961 1,467 2,158 ALL AFRICA 536 603 529 603 686 751 813 919 984 554 588 709 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 55 Table 2.19 Gross fixed capital formation Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 17.7 18.1 15.5 16.3 16.5 16.6 17.3 18.6 18.5 18.5 17.3 16.8 Excluding South Africa 14.0 17.6 16.3 16.9 16.9 16.8 16.9 18.0 17.8 15.9 18.3 17.1 Excl. S. Africa & Nigeria 17.4 17.0 17.4 18.3 18.8 19.0 19.7 20.7 20.6 16.5 17.9 18.9 Angola .. 11.1 12.6 12.7 9.1 8.1 13.7 14.4 12.3 14.2 23.2 12.4 Benin .. 13.4 18.1 18.1 17.5 18.9 .. .. .. 14.8 15.7 18.5 Botswana 34.5 32.4 21.9 21.5 20.2 19.0 17.9 24.4 27.0 29.0 27.2 21.6 Burkina Faso 14.1 17.7 17.1 17.5 19.3 19.4 20.8 .. .. 17.4 21.2 18.2 Burundi 13.9 15.2 6.1 10.6 13.0 10.5 16.4 .. .. 16.1 9.0 9.9 Cameroon 20.0 17.3 19.8 18.1 18.3 17.7 16.7 16.7 18.7 21.1 14.5 18.0 Cape Verde .. 22.9 20.9 18.7 37.4 37.1 37.5 40.3 42.9 26.9 29.6 30.3 Central African Republic 6.9 11.4 9.0 6.1 6.2 8.9 9.2 8.9 10.3 10.2 11.2 8.5 Chad .. 4.8 59.7 48.6 22.7 19.1 21.2 18.2 14.1 4.4 11.0 29.0 Comoros 28.5 11.9 11.0 10.3 9.4 9.3 9.8 13.8 16.1 24.3 14.6 11.1 Congo, Dem. Rep. 8.8 12.8 9.0 12.2 12.7 .. .. 19.6 17.0 11.4 8.0 11.3 Congo, Rep. 35.8 17.2 22.5 25.1 23.6 21.5 22.4 26.7 .. 32.5 24.9 23.6 Côte d'Ivoire 24.4 8.5 10.9 9.7 9.8 9.7 9.3 8.6 10.1 15.8 11.4 9.9 Djibouti .. 14.1 10.0 14.4 21.5 19.0 29.9 38.9 .. .. 11.1 18.8 Equatorial Guinea .. 17.4 32.4 41.6 40.5 37.6 31.4 33.3 28.2 .. 59.5 42.0 Eritrea .. .. 29.8 28.1 22.3 18.5 12.6 10.6 .. .. 26.1 22.8 Ethiopia .. 12.9 23.9 21.8 25.5 23.0 24.2 25.0 20.8 15.7 16.5 22.9 Gabon 26.7 21.4 24.5 24.0 24.4 21.3 24.5 26.2 27.3 33.8 25.4 24.4 Gambia, The .. 22.3 21.2 19.2 24.8 .. .. .. .. 18.9 20.1 20.0 Ghana 6.1 14.4 18.8 22.9 28.4 29.9 30.4 34.1 32.0 7.9 19.7 27.4 Guinea .. 22.9 13.2 10.1 11.3 14.0 13.3 12.6 12.7 16.4 20.0 13.4 Guinea-Bissau 28.2 29.9 9.6 14.5 23.5 26.5 22.8 25.7 23.8 32.0 25.9 19.2 Kenya 18.3 20.6 17.2 15.8 16.3 18.7 19.1 19.5 24.7 18.8 17.6 18.5 Lesotho 35.6 56.3 46.1 34.0 32.0 28.9 23.8 26.6 28.8 40.7 60.9 35.0 Liberia .. .. 4.7 9.4 13.2 16.4 .. .. .. .. .. 9.7 Madagascar 14.4 14.8 14.3 17.9 23.4 22.2 25.3 27.5 35.7 10.8 12.4 22.2 Malawi 22.2 20.1 .. 16.2 18.2 21.5 20.7 23.9 30.2 15.8 15.2 19.6 Mali 15.5 23.0 18.6 24.2 21.0 22.6 22.9 23.3 .. 17.2 22.5 23.5 Mauritania .. 20.0 21.1 25.9 46.4 44.8 23.3 25.9 .. 26.6 13.6 28.6 Mauritius 24.2 28.3 22.3 22.2 22.1 21.3 22.9 24.9 24.2 21.1 27.1 23.2 Mozambique 7.6 22.1 30.0 22.3 18.7 18.7 18.6 18.7 23.0 12.2 20.7 22.3 Namibia 27.2 21.2 19.9 19.1 18.6 18.6 22.1 20.7 22.6 18.6 21.0 19.9 Niger 25.5 11.4 14.0 14.1 16.6 18.9 .. .. .. 14.2 9.0 14.5 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 12.2 14.6 17.7 18.6 20.4 21.6 20.5 20.7 20.8 14.4 14.5 19.7 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 14.6 18.0 24.8 21.2 22.7 29.7 28.2 30.9 30.2 17.4 19.9 25.9 Seychelles 36.5 23.0 25.6 10.4 12.7 24.7 26.1 33.2 28.3 25.6 29.2 25.2 Sierra Leone 14.9 9.6 10.1 13.9 10.7 17.4 15.5 13.4 19.7 11.4 7.2 12.7 Somalia 43.1 14.9 .. .. .. .. .. .. .. 26.9 14.9 .. South Africa 25.9 19.1 15.0 15.9 16.2 16.8 18.6 20.5 22.2 23.1 16.3 17.3 Sudan 10.8 10.4 13.2 14.1 17.2 18.9 20.4 20.3 20.2 12.4 10.6 16.4 Swaziland 35.0 14.5 20.1 19.1 16.2 15.4 14.1 13.0 14.9 25.4 16.7 16.9 Tanzania .. 25.8 19.0 18.5 18.2 16.1 16.4 .. .. .. 21.0 17.5 Togo 28.2 25.3 18.8 20.9 21.2 22.3 .. .. .. 19.0 15.6 20.4 Uganda .. 12.7 20.0 20.7 20.0 22.2 21.0 21.9 23.3 9.3 15.9 20.8 Zambia 18.2 13.5 20.6 24.1 23.1 22.9 23.1 24.2 21.4 12.4 12.4 21.4 Zimbabwe 14.1 18.2 10.2 13.8 17.1 21.0 .. .. .. 16.0 20.1 14.3 NORTH AFRICA 26.4 24.1 21.2 20.5 20.8 20.3 20.8 22.9 23.4 26.8 21.4 21.1 Algeria 33.8 27.0 24.4 24.0 24.1 22.3 23.1 25.7 27.9 31.9 26.2 23.9 Egypt, Arab Rep. 24.6 26.9 17.8 16.3 16.4 17.9 18.7 20.9 23.7 27.8 20.4 18.7 Libya .. 13.9 14.4 .. .. .. .. .. .. .. 12.7 13.1 Morocco 22.2 24.0 25.2 25.1 26.3 27.5 28.1 31.3 32.0 23.1 22.2 27.4 Tunisia 28.3 24.4 25.4 23.4 22.6 22.2 23.5 23.6 24.1 27.5 25.3 24.1 ALL AFRICA 19.8 20.4 17.8 17.9 18.0 17.9 18.4 20.0 20.4 21.2 18.8 18.4 a. Provisional. 56 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.20 Table Gross general government fixed capital formation Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA .. 5.0 4.3 4.4 4.4 4.3 5.1 5.5 5.6 5.4 4.5 4.7 Excluding South Africa .. 5.8 5.4 5.7 5.9 5.7 6.7 7.4 7.2 6.3 6.0 6.2 Excl. S. Africa & Nigeria .. 5.6 5.8 6.2 6.6 6.5 7.9 8.5 8.4 6.0 5.9 6.8 Angola .. .. 6.8 7.6 4.9 5.0 11.3 12.1 10.5 .. 7.8 7.8 Benin .. 7.4 6.6 6.1 5.4 6.7 .. .. .. 9.1 7.5 6.7 Botswana 0.0 8.6 10.6 10.2 8.7 7.7 8.3 7.7 8.4 9.7 11.7 9.1 Burkina Faso .. 9.7 6.4 6.3 7.2 7.4 8.0 .. .. 10.4 10.5 7.0 Burundi 12.8 12.5 4.6 8.3 10.7 8.8 .. .. .. 13.8 9.3 6.9 Cameroon 4.4 5.5 2.3 2.3 2.6 2.5 2.4 2.4 4.3 6.9 2.9 2.6 Cape Verde .. 10.3 13.0 9.8 7.7 8.9 8.6 10.1 9.2 19.3 20.3 10.1 Central African Republic 3.7 4.7 4.8 2.2 2.0 4.0 3.7 2.7 3.7 5.5 6.2 3.5 Chad .. .. 10.1 12.5 7.8 7.0 8.0 8.3 7.7 3.8 7.4 9.0 Comoros 23.2 5.2 5.8 5.4 4.4 4.5 5.0 6.8 7.9 18.7 7.0 5.3 Congo, Dem. Rep. 5.1 4.0 1.0 2.7 2.8 .. .. 8.8 6.9 4.4 1.7 3.2 Congo, Rep. .. 5.6 8.7 6.5 7.0 5.3 8.6 10.9 .. 11.1 6.4 8.0 Côte d'Ivoire 11.4 3.6 3.2 2.7 2.8 2.7 3.1 2.6 3.0 7.1 5.6 2.7 Djibouti .. 9.1 4.5 6.7 7.7 9.3 7.6 12.7 .. .. 6.1 6.7 Equatorial Guinea .. 10.5 8.5 9.9 13.1 10.3 15.1 16.9 16.8 .. 6.9 11.5 Eritrea .. .. 19.8 20.4 17.0 16.8 11.5 9.4 .. .. 17.6 17.5 Ethiopia .. 4.0 14.0 12.8 15.7 14.7 16.7 18.2 14.9 4.9 6.6 14.7 Gabon 5.3 3.9 4.0 3.7 4.2 4.2 4.8 4.5 4.3 6.7 6.5 4.1 Gambia, The .. 7.4 7.9 5.7 10.9 9.0 8.0 3.8 .. 10.4 7.8 7.6 Ghana .. 7.5 9.6 8.9 12.4 12.0 12.4 14.3 13.8 6.3 11.1 11.6 Guinea .. 9.7 4.0 4.4 4.0 3.4 3.2 3.3 2.9 7.5 6.1 3.9 Guinea-Bissau .. 27.4 8.9 13.1 18.8 14.5 11.9 13.3 13.2 33.3 20.2 13.0 Kenya 0.0 9.7 4.3 4.2 4.3 3.8 4.9 4.9 4.3 0.8 7.0 4.4 Lesotho 9.9 24.6 11.5 9.1 7.5 7.8 7.1 9.8 10.8 16.1 17.4 9.3 Liberia .. .. 0.0 0.0 0.0 0.0 .. .. .. .. .. 0.0 Madagascar .. 7.9 4.8 7.8 10.0 8.7 10.5 7.6 9.8 6.9 6.9 8.2 Malawi 17.5 7.7 .. 2.4 2.0 7.0 7.7 13.9 9.5 9.5 9.2 7.9 Mali .. 10.5 7.0 6.9 7.5 7.7 8.6 8.8 .. 10.2 10.1 7.8 Mauritania .. 6.2 9.1 12.0 9.1 8.1 5.6 4.7 .. 7.6 5.0 8.0 Mauritius 9.1 4.6 7.0 7.9 7.7 6.6 7.1 6.6 4.6 6.0 3.7 6.9 Mozambique 7.6 12.0 12.2 10.5 9.7 8.6 11.8 11.7 16.0 9.5 12.1 11.5 Namibia 15.7 8.2 5.8 6.4 6.3 6.4 6.8 7.0 6.8 10.7 8.2 6.5 Niger 20.4 7.4 8.8 8.4 5.4 6.4 .. .. .. 11.2 5.6 7.1 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 12.2 5.9 5.2 5.4 7.9 9.1 7.6 8.6 10.1 12.1 7.2 7.4 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 4.7 4.1 5.7 6.2 6.7 10.0 9.7 11.2 10.0 3.7 4.5 7.7 Seychelles .. 8.2 7.4 1.7 3.1 4.6 8.1 5.1 3.6 12.0 9.9 7.8 Sierra Leone 5.3 3.9 4.4 4.8 4.6 5.8 5.1 3.5 8.7 4.0 3.8 5.2 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 6.4 3.9 2.5 2.6 2.5 2.4 2.7 2.7 2.8 5.7 2.8 2.6 Sudan 6.9 .. 3.0 2.9 5.0 5.5 6.4 7.2 7.4 4.3 0.7 4.7 Swaziland 11.9 4.5 12.5 13.0 10.7 9.8 8.7 0.1 0.0 8.0 5.4 7.9 Tanzania .. 10.5 7.6 7.4 7.3 6.4 6.6 .. .. .. 5.8 6.7 Togo 20.2 7.3 1.4 3.7 5.3 2.8 3.6 2.0 5.0 11.2 3.7 3.2 Uganda .. 6.2 5.6 5.1 4.9 5.0 4.6 4.9 5.5 4.4 5.6 5.3 Zambia .. 6.2 11.8 11.4 8.7 7.1 4.0 6.2 5.8 .. 6.8 8.5 Zimbabwe 1.8 3.4 2.1 2.1 5.1 1.5 .. .. .. 2.9 2.9 2.3 NORTH AFRICA .. 9.2 9.2 8.6 8.6 8.9 9.0 9.2 .. 11.8 9.5 8.8 Algeria 11.0 8.2 10.0 10.8 10.5 10.8 12.0 12.6 0.0 13.8 7.2 9.2 Egypt, Arab Rep. .. 14.7 9.4 8.3 8.7 9.3 8.0 7.8 6.5 16.9 14.5 8.5 Libya .. .. .. .. .. .. .. .. .. .. .. .. Morocco .. 4.8 4.0 3.8 3.8 3.7 3.6 4.0 4.5 7.1 4.2 4.1 Tunisia 15.0 8.7 .. .. .. 9.8 .. .. .. 14.1 11.5 11.1 ALL AFRICA .. 6.5 6.2 5.9 5.9 5.9 6.5 6.8 6.6 7.8 6.3 6.2 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 57 Table 2.21 Private sector fixed capital formation Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 11.3 12.5 10.9 11.9 12.0 12.2 12.6 13.5 12.9 12.2 12.6 12.1 Excluding South Africa .. 10.5 10.5 11.1 10.8 10.7 10.9 11.3 10.5 9.5 11.7 10.8 Excl. S. Africa & Nigeria .. 10.1 11.2 12.0 12.0 12.1 12.7 12.9 12.2 9.0 11.4 12.0 Angola .. 1.7 5.8 5.1 4.2 3.0 2.4 2.3 1.8 9.2 16.5 4.5 Benin .. 6.0 11.6 12.0 12.1 12.2 .. .. .. 4.5 8.3 11.8 Botswana 34.5 23.8 11.3 11.3 11.5 11.3 9.6 16.7 18.6 19.4 15.5 12.5 Burkina Faso .. 8.0 10.8 11.1 .. .. .. .. .. 8.8 10.8 10.4 Burundi 1.1 2.7 1.5 2.3 2.3 1.7 .. .. .. 2.3 ­0.3 1.9 Cameroon 15.6 11.9 17.5 15.8 15.7 15.2 14.3 14.3 14.3 14.2 11.7 15.5 Cape Verde .. 12.6 7.9 8.9 29.7 28.2 28.9 30.2 33.7 7.6 9.3 20.2 Central African Republic 3.2 6.7 4.2 3.9 4.1 4.9 5.6 6.2 6.6 4.7 5.0 5.0 Chad .. .. 49.6 36.1 14.9 12.0 13.2 9.9 6.4 0.6 4.3 20.0 Comoros 5.3 6.7 5.2 4.9 5.0 4.8 4.9 6.9 8.1 5.5 7.7 5.7 Congo, Dem. Rep. 3.7 8.9 8.0 9.5 10.0 .. .. 10.8 10.1 7.1 6.3 8.1 Congo, Rep. .. 11.6 13.8 18.6 16.6 16.2 13.8 15.8 .. 11.4 18.5 15.6 Côte d'Ivoire 13.0 4.9 7.7 7.0 7.1 7.0 6.3 6.1 7.1 8.7 6.2 7.2 Djibouti .. 5.1 5.6 7.7 13.8 9.7 22.3 26.2 .. .. 5.8 12.1 Equatorial Guinea .. 6.9 23.9 31.7 27.4 27.4 16.2 16.4 11.4 .. 52.6 30.6 Eritrea .. .. 10.0 7.7 5.3 1.8 1.1 1.2 .. .. 8.6 5.3 Ethiopia .. 8.9 9.9 9.0 9.7 8.3 7.6 6.7 5.9 12.8 9.9 8.2 Gabon 21.4 17.6 20.5 20.2 20.2 17.1 19.7 21.7 23.0 27.2 18.9 20.3 Gambia, The .. 14.9 13.3 13.5 13.9 .. .. .. .. 8.6 12.3 11.9 Ghana .. 6.9 9.2 14.0 16.0 17.9 18.0 19.7 18.1 3.8 8.6 15.8 Guinea .. 8.8 9.2 5.7 7.4 10.7 10.2 9.3 9.9 8.9 11.7 9.5 Guinea-Bissau .. 8.4 0.7 1.5 4.7 12.1 11.0 12.4 10.6 10.0 7.7 6.2 Kenya 8.2 10.9 7.7 7.8 7.5 6.7 25.4 24.9 20.4 10.7 9.8 12.8 Lesotho 25.7 31.7 21.2 23.2 17.9 16.8 16.1 14.6 17.5 24.6 43.8 20.5 Liberia .. .. 2.2 4.8 4.2 4.3 .. .. .. .. .. 3.5 Madagascar .. 6.9 9.5 10.1 13.4 13.5 14.7 19.8 25.9 3.6 5.5 14.0 Malawi 4.7 12.4 .. 13.8 16.2 14.5 13.0 10.0 20.7 6.3 6.0 11.7 Mali .. 12.4 11.6 17.3 13.5 15.0 14.3 14.6 .. 9.9 12.4 15.8 Mauritania .. 13.7 11.9 13.9 37.3 36.7 17.7 21.3 .. 19.0 13.9 21.9 Mauritius 15.1 23.7 15.3 14.3 14.5 14.8 15.9 18.3 19.5 15.1 23.4 16.3 Mozambique 0.0 10.1 17.7 11.8 8.9 10.1 6.8 6.9 7.1 2.7 8.6 10.8 Namibia 11.4 13.0 13.9 20.1 15.7 16.2 16.4 16.3 15.8 7.8 12.8 15.3 Niger 5.1 4.0 5.2 5.7 11.3 12.5 .. .. .. 3.0 3.4 7.4 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda .. 8.7 12.5 13.3 12.5 12.5 13.0 12.1 10.7 7.8 7.2 12.3 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 9.9 13.9 19.2 15.0 16.0 19.7 18.5 19.7 20.2 13.7 15.4 18.2 Seychelles .. 14.8 18.2 8.7 9.7 20.1 18.1 28.1 24.6 10.1 19.3 17.4 Sierra Leone 9.5 5.7 5.7 9.0 6.1 11.6 10.4 9.9 11.0 7.3 3.3 7.5 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 19.5 15.3 12.5 13.3 13.6 14.4 15.9 17.9 19.4 17.4 13.5 14.7 Sudan 3.8 .. 10.1 11.2 12.2 13.4 14.0 13.0 12.8 8.9 9.9 11.7 Swaziland 23.1 10.1 7.6 6.0 5.5 5.6 5.4 12.9 15.0 17.3 11.3 9.1 Tanzania .. 15.3 11.4 11.1 10.9 9.6 9.8 .. .. .. 15.2 10.8 Togo 8.0 18.0 17.4 17.2 15.9 19.5 .. .. .. 7.8 11.8 17.3 Uganda .. 6.5 14.4 15.6 15.1 17.3 16.4 16.9 17.9 5.4 10.3 15.5 Zambia .. 7.2 8.8 12.7 14.3 15.8 19.1 18.0 15.5 4.9 5.7 12.9 Zimbabwe 12.3 14.8 8.1 11.7 12.0 19.5 .. .. .. 13.1 17.2 12.1 NORTH AFRICA .. 16.0 13.8 13.5 13.9 13.4 14.0 16.3 23.9 13.9 12.8 14.9 Algeria 22.8 18.8 14.5 13.2 13.6 11.5 11.0 13.1 27.9 18.1 19.0 14.7 Egypt, Arab Rep. .. 12.3 8.4 8.1 7.7 8.6 10.7 13.1 20.2 9.3 5.9 10.5 Libya .. .. .. .. .. .. .. .. .. .. .. .. Morocco 16.7 19.2 21.3 21.3 22.4 23.8 24.5 27.3 27.5 16.1 18.0 23.3 Tunisia 13.3 15.6 .. .. .. 12.3 .. .. .. 13.5 13.8 13.0 ALL AFRICA 12.7 13.8 12.0 12.5 12.7 12.7 13.2 14.6 16.9 12.9 12.7 13.2 a. Provisional. 58 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.22 Table External trade balance (exports minus imports) Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 2.4 1.8 ­1.0 ­0.9 0.7 2.1 2.8 1.6 4.1 ­0.5 ­0.9 1.4 Excluding South Africa ­0.1 ­0.7 ­3.1 ­2.9 1.4 3.9 6.1 3.8 7.3 ­3.7 ­3.6 2.0 Excl. S. Africa & Nigeria ­5.3 ­3.1 ­3.9 ­4.5 ­2.6 ­0.5 2.3 1.3 5.1 ­4.6 ­4.9 ­1.1 Angola .. 18.0 11.3 6.6 16.0 29.8 35.8 33.5 50.2 9.1 2.2 23.5 Benin ­21.5 ­12.0 ­13.9 ­12.8 ­12.7 ­12.6 .. .. .. ­17.5 ­12.5 ­13.0 Botswana ­13.4 5.3 11.5 8.7 9.9 17.2 22.5 10.4 4.6 5.3 9.7 13.3 Burkina Faso ­22.3 ­13.5 ­12.4 ­12.9 ­13.5 ­15.6 ­15.3 .. .. ­19.6 ­13.5 ­14.2 Burundi ­14.5 ­19.9 ­16.2 ­19.3 ­24.3 ­33.9 ­36.2 .. .. ­13.5 ­14.4 ­22.3 Cameroon 0.8 2.9 ­0.8 0.3 ­0.4 ­1.0 2.1 0.8 1.1 0.4 3.7 0.5 Cape Verde .. ­31.0 ­36.6 ­34.5 ­38.9 ­32.7 ­32.8 ­35.0 ­34.7 ­29.0 ­35.2 ­34.7 Central African Republic ­15.9 ­12.9 ­4.6 ­4.5 ­6.2 ­8.8 ­7.9 ­7.4 ­8.7 ­12.1 ­7.7 ­6.3 Chad ­11.9 ­14.4 ­101.0 ­34.1 0.2 15.5 21.3 15.4 10.2 ­13.5 ­13.6 ­13.9 Comoros ­43.2 ­22.9 ­15.0 ­16.1 ­19.9 ­22.2 ­23.8 ­25.2 ­24.2 ­33.3 ­22.6 ­19.7 Congo, Dem. Rep. 0.1 0.3 ­4.9 ­7.2 ­8.8 ­7.6 ­11.2 ­10.8 ­10.1 ­0.8 1.2 ­6.8 Congo, Rep. ­0.1 7.9 27.6 25.6 27.0 35.6 42.9 30.1 .. ­0.5 2.9 31.2 Côte d'Ivoire ­6.2 4.6 16.6 10.9 9.2 7.5 10.3 5.6 4.8 3.2 6.5 8.9 Djibouti .. ­24.6 ­5.2 ­9.2 ­17.2 ­10.3 ­17.6 ­20.8 .. .. ­17.5 ­13.0 Equatorial Guinea .. ­37.4 47.3 20.4 35.1 43.8 53.7 51.6 46.1 ­28.6 ­45.8 35.6 Eritrea .. .. ­57.3 ­69.0 ­63.8 ­45.7 ­29.7 ­28.2 .. .. ­55.8 ­52.0 Ethiopia .. ­3.3 ­14.0 ­14.1 ­16.7 ­20.4 ­22.7 ­19.4 ­17.0 ­5.3 ­6.8 ­16.4 Gabon 33.1 15.2 19.2 24.3 30.2 37.0 32.8 28.8 39.0 9.7 17.7 30.4 Gambia, The ­20.9 ­11.7 ­8.3 ­9.2 ­21.1 ­22.8 ­17.2 ­16.5 ­18.9 ­13.2 ­12.6 ­14.3 Ghana ­0.7 ­9.0 ­12.3 ­15.9 ­21.1 ­25.0 ­24.7 ­26.4 ­26.3 ­3.1 ­12.4 ­21.1 Guinea 3.1 ­2.4 ­4.0 ­2.4 ­4.0 ­2.7 ­2.8 ­2.2 ­2.2 0.8 ­3.0 ­2.9 Guinea-Bissau ­29.2 ­27.1 ­21.4 ­14.1 ­11.3 ­13.9 ­28.0 ­16.6 ­20.0 ­32.9 ­24.5 ­20.0 Kenya ­6.4 ­5.6 ­5.4 ­6.0 ­6.3 ­7.4 ­9.9 ­11.2 ­14.1 ­4.9 ­3.7 ­8.9 Lesotho ­89.1 ­98.6 ­62.5 ­55.6 ­48.8 ­51.4 ­46.3 ­49.9 ­63.4 ­107.4 ­95.1 ­55.7 Liberia ­0.1 .. ­8.1 ­12.6 ­13.9 ­14.0 ­54.6 ­50.5 .. 2.9 ­39.6 ­20.8 Madagascar ­16.4 ­11.4 ­6.6 ­9.0 ­14.8 ­14.2 ­11.2 ­16.4 ­25.3 ­7.7 ­8.2 ­12.0 Malawi ­14.0 ­9.6 ­24.9 ­21.8 ­18.2 ­24.5 ­23.9 ­21.0 ­27.8 ­6.7 ­14.3 ­20.3 Mali ­14.4 ­16.6 ­7.3 ­10.9 ­12.4 ­11.7 ­8.1 ­9.8 .. ­17.6 ­14.9 ­11.2 Mauritania ­29.8 ­15.1 ­23.0 ­30.9 ­49.4 ­59.8 ­4.5 ­7.2 .. ­24.4 ­11.2 ­27.7 Mauritius ­10.9 ­7.2 3.8 2.1 ­0.6 ­4.4 ­7.1 ­9.3 ­8.2 ­3.5 ­4.3 ­2.5 Mozambique ­16.5 ­27.9 ­15.1 ­16.2 ­8.6 ­9.4 ­5.8 ­6.7 ­10.0 ­18.4 ­23.6 ­12.0 Namibia 7.8 ­15.5 ­2.1 ­9.1 ­2.3 0.1 3.9 ­1.9 ­9.1 ­7.6 ­10.0 ­3.4 Niger ­13.5 ­6.9 ­8.9 ­9.2 ­10.5 ­9.4 .. .. .. ­8.0 ­6.2 ­8.9 Nigeriab 10.2 14.6 ­0.7 2.3 12.9 15.5 15.1 10.5 13.1 1.1 4.1 11.3 Rwanda ­11.9 ­8.5 ­18.2 ­18.3 ­15.9 ­16.5 ­17.8 ­17.9 ­19.5 ­10.3 ­19.9 ­17.5 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal ­14.5 ­6.8 ­10.4 ­12.1 ­12.9 ­15.6 ­17.5 ­22.4 ­22.5 ­12.1 ­7.1 ­14.6 Seychelles ­11.2 ­4.3 ­1.2 11.2 2.0 ­21.6 ­18.0 ­35.1 ­21.6 ­2.3 ­8.6 ­12.1 Sierra Leone ­15.4 ­1.3 ­18.3 ­17.6 ­11.2 ­13.2 ­7.6 ­7.4 ­12.2 ­3.1 ­4.5 ­14.1 Somalia ­55.3 ­28.0 .. .. .. .. .. .. .. ­35.1 ­28.0 .. South Africa 8.0 5.5 3.8 2.3 ­0.4 ­0.8 ­3.3 ­3.1 ­4.0 5.1 2.8 0.2 Sudan ­12.6 ­3.0 ­6.2 ­4.2 ­3.8 ­9.9 ­10.9 ­3.8 0.7 ­8.3 ­6.7 ­5.4 Swaziland ­39.4 ­9.9 ­5.5 ­1.0 ­2.7 ­4.2 ­2.6 ­1.4 0.1 ­23.5 ­15.2 ­5.0 Tanzania .. ­24.8 ­7.4 ­6.6 ­7.1 ­6.5 ­5.8 .. .. .. ­19.3 ­7.0 Togo ­5.3 ­11.9 ­18.0 ­13.6 ­13.5 ­16.9 ­19.5 ­20.5 ­27.0 ­7.2 ­9.6 ­18.7 Uganda ­6.6 ­12.1 ­14.3 ­14.2 ­10.5 ­11.1 ­13.6 ­13.9 ­17.7 ­6.2 ­11.7 ­13.3 Zambia ­4.0 ­0.7 ­14.0 ­12.4 ­4.4 ­2.1 8.4 6.4 2.5 ­2.1 ­5.6 ­5.1 Zimbabwe ­3.2 0.1 ­0.9 ­5.2 ­10.1 ­16.2 .. .. .. ­0.8 ­2.6 ­5.2 NORTH AFRICA ­0.6 ­3.6 0.9 3.4 4.2 7.7 9.1 6.0 9.5 ­4.1 ­2.4 5.1 Algeria 4.0 ­1.5 9.7 14.4 14.4 23.4 27.3 23.6 34.6 ­2.5 1.6 20.2 Egypt, Arab Rep. ­12.4 ­12.7 ­4.4 ­2.6 ­1.4 ­2.3 ­1.6 ­4.6 ­6.6 ­13.2 ­6.7 ­3.9 Libya .. 8.6 11.4 .. .. .. .. .. .. .. 3.6 14.1 Morocco ­9.4 ­5.4 ­2.1 ­2.8 ­5.0 ­5.6 ­5.5 ­9.1 ­9.4 ­7.4 ­4.9 ­5.3 Tunisia ­5.4 ­7.0 ­4.3 ­3.9 ­2.9 ­0.4 ­2.3 ­2.4 ­3.1 ­6.1 ­4.3 ­3.1 ALL AFRICA 1.6 ­0.2 ­0.3 0.6 1.9 3.9 4.9 3.0 6.0 ­1.9 ­1.4 2.7 a. Provisional. b. For 1994­2000 Nigeria's values were distorted because the official exchange rate used by the government for oil exports and oil value added was significantly overvalued. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 59 Table 2.23 Exports of goods and services, nominal Current prices ($ millions) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 83,549 79,598 113,518 145,066 184,997 231,923 277,748 318,957 413,690 66,396 87,532 212,485 Excluding South Africa 54,740 52,169 76,939 98,305 127,300 165,412 201,670 229,410 314,556 39,889 55,783 151,925 Excl. S. Africa & Nigeria 34,967 40,236 58,121 69,425 88,700 113,180 138,282 163,152 222,731 32,451 43,553 106,876 Angola .. 3,992 8,406 9,716 13,780 24,286 33,317 43,809 74,618 2,613 4,265 24,774 Benin 222 264 380 487 539 577 .. .. .. 214 327 448 Botswana 563 2,087 2,811 3,697 4,357 5,120 5,581 5,797 5,928 999 2,350 4,386 Burkina Faso 173 340 290 376 549 542 665 .. .. 189 286 417 Burundi 81 89 39 50 64 91 99 .. .. 111 89 63 Cameroon 1,880 2,251 2,169 2,757 3,061 3,393 4,131 4,563 6,837 2,240 2,198 3,484 Cape Verde .. 43 194 253 138 171 229 285 345 41 79 214 Central African Republic 201 220 162 154 168 170 207 254 284 181 185 194 Chad 175 234 252 674 2,252 3,234 3,852 3,476 3,677 153 254 1,989 Comoros 11 36 40 51 46 48 47 57 68 22 40 47 Congo, Dem. Rep. 2,372 2,759 1,174 1,483 1,994 2,242 2,517 2,705 2,693 2,016 1,595 1,850 Congo, Rep. 1,024 1,502 2,462 2,825 3,662 5,160 6,717 5,582 .. 1,092 1,393 3,895 Côte d'Ivoire 3,561 3,421 5,747 6,297 7,517 8,354 9,144 9,222 11,953 3,142 4,129 7,429 Djibouti .. 244 228 248 246 288 307 484 .. .. 210 276 Equatorial Guinea .. 42 2,139 2,859 4,724 7,183 8,332 10,299 14,498 32 160 5,892 Eritrea .. .. 86 43 43 67 84 86 .. .. 132 73 Ethiopia .. 672 982 1,139 1,498 1,858 2,105 2,488 3,074 608 715 1,679 Gabon 2,770 2,740 2,642 3,350 4,465 5,610 6,203 7,487 11,151 1,964 2,728 5,243 Gambia, The 103 190 157 158 184 185 203 214 235 108 195 188 Ghana 376 993 2,625 3,101 3,487 3,475 4,581 5,057 5,940 554 1,684 3,677 Guinea 2,084 829 785 806 829 925 1,073 1,700 1,187 2,021 798 983 Guinea-Bissau 14 24 61 71 92 94 59 107 128 15 32 82 Kenya 2,144 2,207 3,274 3,590 4,283 5,342 5,977 7,042 8,599 1,805 2,594 4,869 Lesotho 91 98 390 520 721 703 759 880 767 67 187 591 Liberia 613 .. 111 133 171 201 175 245 .. 519 43 160 Madagascar 539 512 704 1,264 1,424 1,356 1,649 2,233 2,363 414 673 1,500 Malawi 307 447 907 723 655 559 595 845 998 295 465 690 Mali 263 415 1,066 1,153 1,237 1,359 1,884 1,871 .. 255 514 1,262 Mauritania 261 465 382 356 473 659 1,453 1,524 .. 387 465 716 Mauritius 539 1,529 2,757 3,099 3,350 3,556 3,868 4,194 5,331 764 2,191 3,548 Mozambique 383 201 1,188 1,353 1,828 2,164 2,831 3,010 3,114 215 373 1,915 Namibia 1,712 1,220 1,546 2,141 2,630 2,937 3,628 4,173 3,335 1,139 1,543 2,605 Niger 617 372 330 438 491 512 .. .. .. 420 325 403 Nigeria 18,859 12,366 18,839 28,891 38,609 52,238 63,404 66,617 92,201 7,725 12,563 45,140 Rwanda 168 145 133 139 200 245 275 332 360 173 107 221 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 837 1,453 1,523 1,826 2,123 2,340 2,401 2,875 3,294 989 1,347 2,121 Seychelles 100 230 586 671 684 717 860 993 1,091 123 298 732 Sierra Leone 252 146 164 230 247 292 355 349 487 187 155 263 Somalia 200 90 .. .. .. .. .. .. .. 119 90 .. South Africa 28,555 27,149 36,578 46,760 57,700 66,527 76,171 89,567 100,562 26,088 31,523 60,733 Sudan 806 499 1,996 2,613 3,822 4,992 6,015 9,287 13,292 841 579 5,069 Swaziland 405 658 1,172 1,872 2,056 2,250 2,259 2,311 2,101 394 886 1,812 Tanzania .. 538 1,631 2,022 2,538 2,964 3,106 .. .. .. 962 2,185 Togo 580 545 498 595 691 850 938 1,048 1,142 464 441 732 Uganda 242 312 693 752 1,008 1,310 1,524 1,990 2,272 371 500 1,209 Zambia 1,608 1,180 1,030 1,256 2,079 2,482 4,120 4,802 5,267 1,060 1,099 2,548 Zimbabwe 1,561 2,009 2,019 1,854 2,002 1,941 .. .. .. 1,530 2,469 2,141 NORTH AFRICA 37,505 46,844 66,974 80,326 99,923 126,988 147,357 172,176 261,135 34,399 48,912 121,273 Algeria 14,541 14,546 20,012 26,028 34,067 48,761 56,953 63,297 102,773 12,221 12,420 43,828 Egypt, Arab Rep. 6,992 8,647 16,091 18,074 22,258 27,214 32,191 39,469 61,354 6,654 12,435 27,766 Libya .. 11,468 9,164 .. .. .. .. .. .. .. 8,527 10,099 Morocco 3,273 6,830 12,186 14,282 16,726 19,234 22,449 26,892 35,089 3,790 8,363 18,701 Tunisia 3,518 5,353 9,520 10,950 13,199 14,402 15,600 18,958 26,186 3,312 7,168 14,112 ALL AFRICA 122,545 126,555 180,495 225,868 285,752 359,801 426,557 492,585 674,727 101,527 136,479 334,315 a. Provisional. 60 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.24 Table Imports of goods and services, nominal Current prices ($ millions) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 76,874 74,318 117,172 149,237 181,048 218,168 256,486 305,310 372,119 67,736 90,366 201,602 Excluding South Africa 54,910 53,452 84,902 106,320 122,534 149,665 171,702 207,051 261,529 46,219 62,474 139,405 Excl. S. Africa & Nigeria 41,883 45,176 65,628 78,904 95,211 114,757 130,295 157,764 196,532 38,640 51,177 106,642 Angola .. 2,147 7,110 8,801 10,621 15,144 17,129 23,941 32,731 1,895 4,032 14,212 Benin 524 486 772 944 1,055 1,119 .. .. .. 447 579 864 Botswana 705 1,888 2,130 2,979 3,380 3,308 3,109 4,512 5,333 842 1,896 3,199 Burkina Faso 603 758 697 928 1,240 1,390 1,547 .. .. 567 640 1,016 Burundi 214 314 140 165 225 360 432 .. .. 254 234 229 Cameroon 1,829 1,931 2,254 2,712 3,128 3,562 3,763 4,395 6,587 2,219 1,816 3,401 Cape Verde .. 148 419 529 497 500 624 791 945 118 237 554 Central African Republic 327 411 210 205 246 289 324 381 455 292 282 283 Chad 298 485 2,259 1,608 2,241 2,324 2,509 2,400 2,823 305 469 1,944 Comoros 64 93 77 103 118 134 143 174 196 67 93 120 Congo, Dem. Rep. 2,354 2,731 1,447 1,892 2,573 2,792 3,499 3,778 3,863 2,107 1,537 2,415 Congo, Rep. 1,026 1,282 1,629 1,913 2,488 2,994 3,398 3,281 .. 1,093 1,309 2,325 Côte d'Ivoire 4,190 2,927 3,837 4,796 6,093 7,132 7,356 8,106 10,838 2,906 3,406 6,129 Djibouti .. 355 259 305 361 361 441 654 .. .. 295 365 Equatorial Guinea .. 92 1,124 2,256 2,882 3,583 3,179 3,809 5,953 61 270 2,828 Eritrea .. .. 473 456 446 598 465 474 .. .. 482 486 Ethiopia .. 1,069 2,072 2,346 3,174 4,366 5,547 6,255 7,577 1,093 1,330 3,915 Gabon 1,354 1,837 1,694 1,882 2,299 2,400 3,068 4,154 5,517 1,586 1,823 2,692 Gambia, The 153 227 188 192 269 290 290 320 383 137 242 260 Ghana 407 1,522 3,380 4,316 5,356 6,160 7,723 9,020 10,188 709 2,509 5,881 Guinea 1,878 892 912 892 986 1,013 1,163 1,802 1,281 1,953 905 1,085 Guinea-Bissau 46 90 104 104 124 137 148 170 214 67 91 138 Kenya 2,608 2,691 3,981 4,478 5,290 6,740 8,200 10,064 13,456 2,154 3,071 6,725 Lesotho 475 666 808 1,072 1,350 1,411 1,462 1,713 1,796 496 926 1,234 Liberia 614 .. 156 184 235 275 509 616 .. 491 180 287 Madagascar 1,202 864 993 1,756 2,072 2,070 2,269 3,438 4,630 668 942 2,240 Malawi 480 629 1,570 1,251 1,134 1,259 1,353 1,597 2,186 384 716 1,293 Mali 520 817 1,311 1,630 1,841 1,979 2,360 2,542 .. 536 882 1,742 Mauritania 473 619 647 753 1,239 1,758 1,573 1,715 .. 576 607 1,135 Mauritius 665 1,701 2,584 2,988 3,389 3,830 4,325 4,823 6,044 809 2,334 3,747 Mozambique 965 888 1,821 2,108 2,320 2,783 3,245 3,550 4,091 773 1,001 2,573 Namibia 1,542 1,584 1,616 2,589 2,780 2,927 3,317 4,337 4,117 1,284 1,844 2,790 Niger 957 545 523 688 795 825 .. .. .. 583 448 629 Nigeria 12,324 8,203 19,245 27,360 27,282 34,849 41,280 49,192 64,469 7,362 11,214 32,656 Rwanda 307 364 430 464 513 638 781 944 1,228 354 405 652 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 1,344 1,840 2,078 2,657 3,162 3,694 4,037 5,407 6,262 1,408 1,719 3,432 Seychelles 117 246 594 593 671 908 1,034 1,313 1,271 123 344 836 Sierra Leone 421 154 336 404 367 452 464 471 724 225 191 416 Somalia 534 346 .. .. .. .. .. .. .. 403 346 .. South Africa 22,073 21,016 32,316 42,967 58,544 68,549 84,692 98,333 111,723 21,441 27,961 62,348 Sudan 1,763 877 2,924 3,367 4,650 7,701 9,995 11,041 12,883 1,744 1,289 6,390 Swaziland 619 768 1,237 1,889 2,117 2,357 2,329 2,350 2,098 515 1,109 1,894 Tanzania .. 1,595 2,353 2,703 3,344 3,881 3,941 .. .. .. 2,000 2,958 Togo 640 738 763 833 969 1,206 1,371 1,561 1,905 542 586 1,107 Uganda 324 834 1,575 1,693 1,838 2,332 2,878 3,638 4,846 619 1,039 2,401 Zambia 1,764 1,203 1,552 1,796 2,319 2,631 3,221 4,068 4,909 1,148 1,283 2,606 Zimbabwe 1,771 2,002 2,218 2,238 2,477 2,495 .. .. .. 1,598 2,661 2,390 NORTH AFRICA 38,163 53,024 64,846 71,794 88,203 102,168 113,750 146,378 207,611 40,285 53,422 102,010 Algeria 12,847 15,472 14,491 16,239 21,808 24,838 25,211 31,633 42,597 13,875 11,636 22,271 Egypt, Arab Rep. 9,822 14,109 19,917 20,219 23,330 29,246 33,931 45,443 72,031 10,787 16,572 32,078 Libya .. 8,996 6,979 .. .. .. .. .. .. .. 7,464 5,968 Morocco 5,033 8,227 13,038 15,691 19,547 22,569 26,044 33,750 43,188 4,955 9,907 22,025 Tunisia 3,987 6,220 10,421 11,918 14,026 14,521 16,322 19,799 27,451 3,834 7,842 14,919 ALL AFRICA 116,318 127,628 182,015 221,784 270,088 321,633 372,122 453,488 581,372 108,793 143,884 304,525 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 61 Table 2.25 Exports of goods and services as a share of GDP Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 30.2 26.4 31.3 32.6 33.8 36.2 37.4 37.4 41.9 25.2 27.3 35.3 Excluding South Africa 27.8 27.6 30.3 35.1 37.9 40.8 40.8 39.5 43.2 23.2 30.1 37.7 Excl. S. Africa & Nigeria 27.0 25.1 29.9 32.7 35.8 38.6 39.9 39.3 43.2 24.1 28.1 36.0 Angola .. 38.9 73.5 69.6 69.7 79.3 73.8 73.9 89.5 34.8 63.4 77.3 Benin 15.8 14.3 13.5 13.7 13.3 13.5 .. .. .. 16.6 16.4 14.1 Botswana 53.1 55.1 47.4 44.7 44.3 48.7 50.7 47.0 45.7 62.0 51.2 47.7 Burkina Faso 9.0 11.0 8.8 8.8 10.7 10.0 11.5 .. .. 9.5 11.1 9.7 Burundi 8.8 7.9 6.2 8.4 9.6 11.4 10.7 .. .. 10.4 9.0 8.7 Cameroon 27.9 20.2 19.9 20.2 19.4 20.5 23.0 22.1 29.2 25.7 20.9 22.2 Cape Verde .. 12.7 31.5 31.7 14.9 17.0 19.1 19.7 19.9 15.5 16.9 23.5 Central African Republic 25.2 14.8 15.5 13.5 13.2 12.6 14.0 14.8 14.4 20.5 16.2 14.9 Chad 16.9 13.5 12.7 24.6 51.0 55.1 61.1 49.6 44.0 14.3 16.1 36.6 Comoros 8.7 14.3 15.7 15.8 12.7 12.5 11.7 12.2 12.8 14.7 17.4 13.9 Congo, Dem. Rep. 16.5 29.5 21.2 26.1 30.2 31.0 28.6 27.2 23.2 21.4 23.1 25.4 Congo, Rep. 60.0 53.7 81.5 79.3 84.3 84.8 86.9 73.0 .. 52.0 60.2 80.9 Côte d'Ivoire 35.0 31.7 50.0 45.8 48.6 51.1 52.7 46.6 51.1 37.1 36.8 47.6 Djibouti .. 53.8 38.6 39.9 37.0 40.6 40.3 59.2 .. .. 43.2 41.0 Equatorial Guinea .. 32.2 99.6 96.8 90.1 87.4 86.8 81.9 78.3 35.9 52.9 91.2 Eritrea .. .. 12.7 7.3 6.8 5.8 6.5 6.3 .. .. 22.0 9.0 Ethiopia .. 5.6 12.6 13.3 14.9 15.1 13.9 12.8 11.6 6.6 8.1 13.1 Gabon 64.7 46.0 53.6 55.3 62.2 64.7 65.0 64.7 77.2 53.3 54.0 63.4 Gambia, The 42.7 59.9 42.5 43.1 46.0 40.0 39.9 33.3 30.1 47.8 52.6 39.9 Ghana 8.5 16.9 42.6 40.7 39.3 32.4 36.0 33.7 36.8 11.2 25.2 39.5 Guinea 31.2 31.1 24.5 22.3 21.0 28.4 33.5 37.2 27.8 29.6 23.8 27.2 Guinea-Bissau 12.7 9.9 29.8 30.0 32.1 31.3 18.7 28.0 29.8 9.9 13.3 28.9 Kenya 29.5 25.7 24.9 24.1 26.6 28.5 26.6 26.1 24.9 25.7 27.6 25.1 Lesotho 21.0 17.0 58.2 52.3 55.9 51.1 50.0 52.7 47.3 16.5 23.4 49.4 Liberia 64.3 .. 19.9 32.4 37.3 37.9 28.6 33.3 .. 55.3 11.4 29.2 Madagascar 13.3 16.6 16.0 23.1 32.6 26.9 29.9 30.4 26.3 13.6 20.1 27.2 Malawi 24.8 23.8 34.0 29.8 25.0 19.6 18.8 23.6 23.4 23.7 25.1 25.3 Mali 14.7 17.1 31.9 26.4 25.4 25.6 32.1 27.3 .. 15.8 20.8 28.6 Mauritania 36.8 45.6 33.3 27.7 30.6 35.9 54.6 57.7 .. 47.9 36.7 40.0 Mauritius 46.8 64.2 60.6 59.1 55.2 56.5 60.1 61.8 61.6 53.1 61.5 60.4 Mozambique 10.9 8.2 28.3 29.0 32.1 32.9 39.9 37.6 32.0 6.8 12.8 30.4 Namibia 78.9 51.9 46.0 43.4 39.8 40.5 45.5 47.9 38.9 61.2 49.7 42.7 Niger 24.6 15.0 15.2 16.2 16.9 15.4 .. .. .. 21.0 16.2 16.4 Nigeria 29.4 43.4 31.9 42.7 44.0 46.5 43.2 40.1 43.5 21.4 42.0 43.2 Rwanda 14.4 5.6 8.1 7.9 10.1 10.3 9.7 9.7 8.1 10.4 6.0 9.1 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 23.9 25.4 28.5 26.6 26.4 26.9 25.6 25.4 24.9 27.4 26.4 26.8 Seychelles 68.0 62.5 84.0 95.1 97.8 81.1 88.8 108.8 130.9 62.1 59.9 94.0 Sierra Leone 22.9 22.4 17.6 23.2 23.0 24.1 24.9 20.9 24.9 19.5 19.8 21.4 Somalia 33.2 9.8 .. .. .. .. .. .. .. 15.5 9.8 .. South Africa 35.4 24.2 33.0 28.1 26.7 27.4 29.6 31.6 36.3 28.8 23.5 30.1 Sudan 10.6 4.0 13.3 14.7 17.6 18.2 16.5 20.1 22.7 7.4 5.4 16.8 Swaziland 74.6 59.0 99.8 104.2 90.1 89.1 84.6 79.9 80.2 70.2 61.1 88.1 Tanzania .. 12.6 16.7 19.7 22.4 21.0 21.7 .. .. .. 16.4 19.2 Togo 51.1 33.5 33.8 33.8 33.5 40.3 42.3 41.9 40.4 46.1 30.2 36.5 Uganda 19.4 7.2 11.2 11.4 12.7 14.2 15.3 16.7 15.6 11.6 9.8 13.3 Zambia 41.4 35.9 27.7 28.7 38.3 34.7 38.6 42.1 36.8 34.4 32.8 33.6 Zimbabwe 23.4 22.9 9.2 25.1 42.5 56.8 .. .. .. 21.4 34.1 32.1 NORTH AFRICA 33.6 27.2 29.7 32.2 35.8 39.4 39.8 39.7 46.4 26.5 26.4 35.5 Algeria 34.3 23.4 35.1 38.3 40.1 47.6 48.9 47.1 59.1 23.8 25.8 43.7 Egypt, Arab Rep. 30.5 20.0 18.3 21.8 28.2 30.3 29.9 30.3 37.7 22.2 21.8 25.6 Libya .. 39.7 47.7 .. .. .. .. .. .. .. 28.7 37.6 Morocco 17.4 26.5 30.2 28.7 29.4 32.3 34.2 35.8 40.6 22.2 25.9 32.1 Tunisia 40.2 43.6 45.2 43.8 46.9 49.7 50.4 54.1 65.2 36.9 42.5 49.7 ALL AFRICA 31.3 26.8 30.6 32.4 34.4 37.1 38.0 38.0 43.1 25.6 26.9 35.1 a. Provisional. 62 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.26 Table Imports of goods and services as a share of GDP Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 27.8 24.7 32.3 33.6 33.1 34.0 34.5 35.8 37.7 25.8 28.2 33.8 Excluding South Africa 27.9 28.3 33.4 37.9 36.5 36.9 34.8 35.6 35.9 26.8 33.8 35.7 Excl. S. Africa & Nigeria 32.4 28.2 33.7 37.1 38.4 39.1 37.6 38.0 38.1 28.7 33.0 37.2 Angola .. 20.9 62.2 63.1 53.7 49.4 37.9 40.4 39.3 25.6 61.3 53.8 Benin 37.3 26.3 27.5 26.5 26.1 26.1 .. .. .. 34.1 28.9 27.0 Botswana 66.4 49.8 35.9 36.0 34.4 31.5 28.2 36.6 41.1 56.7 41.5 34.4 Burkina Faso 31.3 24.5 21.2 21.7 24.3 25.6 26.8 .. .. 29.2 24.6 24.0 Burundi 23.3 27.8 22.3 27.7 33.9 45.3 47.0 .. .. 23.8 23.4 31.0 Cameroon 27.1 17.3 20.7 19.9 19.8 21.5 21.0 21.2 28.2 25.3 17.2 21.7 Cape Verde .. 43.7 68.1 66.3 53.8 49.7 51.9 54.7 54.7 44.6 52.1 58.2 Central African Republic 41.1 27.6 20.1 18.0 19.4 21.4 21.9 22.3 23.1 32.5 24.0 21.3 Chad 28.9 27.9 113.7 58.7 50.8 39.6 39.8 34.3 33.8 27.7 29.7 50.5 Comoros 51.9 37.1 30.8 31.8 32.6 34.7 35.5 37.3 36.9 47.9 40.0 33.7 Congo, Dem. Rep. 16.4 29.2 26.1 33.3 39.0 38.6 39.8 38.0 33.3 22.2 21.9 32.2 Congo, Rep. 60.1 45.8 53.9 53.7 57.3 49.2 43.9 42.9 .. 52.6 57.3 49.7 Côte d'Ivoire 41.2 27.1 33.4 34.9 39.4 43.6 42.4 40.9 46.3 33.9 30.3 38.6 Djibouti .. 78.4 43.7 49.1 54.2 50.9 57.9 80.0 .. .. 60.7 54.0 Equatorial Guinea .. 69.6 52.3 76.4 55.0 43.6 33.1 30.3 32.1 64.5 98.6 55.6 Eritrea .. .. 70.0 76.3 70.7 51.5 36.3 34.5 .. .. 77.8 61.0 Ethiopia .. 8.8 26.6 27.4 31.6 35.5 36.6 32.2 28.6 11.9 14.9 29.6 Gabon 31.6 30.9 34.3 31.1 32.0 27.7 32.1 35.9 38.2 43.6 36.3 33.0 Gambia, The 63.6 71.6 50.8 52.3 67.1 62.8 57.1 49.8 49.0 61.0 65.3 54.1 Ghana 9.2 25.9 54.9 56.6 60.4 57.5 60.7 60.2 63.2 14.3 37.6 60.6 Guinea 28.1 33.4 28.4 24.6 25.0 31.1 36.3 39.5 30.0 28.8 26.9 30.1 Guinea-Bissau 41.8 37.0 51.2 44.1 43.4 45.2 46.7 44.6 49.8 42.8 37.7 48.8 Kenya 35.9 31.3 30.3 30.0 32.9 35.9 36.5 37.3 39.0 30.6 31.3 34.1 Lesotho 110.1 115.6 120.7 107.9 104.7 102.5 96.3 102.6 110.8 123.9 118.5 105.1 Liberia 64.4 .. 27.9 44.9 51.2 51.9 83.2 83.8 .. 52.4 51.0 50.1 Madagascar 29.7 28.0 22.6 32.1 47.5 41.1 41.1 46.8 51.6 21.3 28.3 39.2 Malawi 38.8 33.4 58.9 51.6 43.2 44.1 42.8 44.5 51.2 30.4 39.4 45.6 Mali 29.1 33.7 39.2 37.4 37.8 37.3 40.2 37.1 .. 33.4 35.7 39.8 Mauritania 66.7 60.7 56.2 58.6 80.0 95.7 59.1 64.9 .. 72.2 47.9 67.7 Mauritius 57.6 71.4 56.8 56.9 55.9 60.9 67.2 71.1 69.9 56.6 65.8 62.9 Mozambique 27.4 36.1 43.4 45.2 40.7 42.3 45.7 44.3 42.0 25.1 36.4 42.4 Namibia 71.1 67.4 48.1 52.5 42.1 40.3 41.6 49.7 48.1 68.7 59.7 46.1 Niger 38.1 22.0 24.1 25.4 27.4 24.8 .. .. .. 29.0 22.4 25.3 Nigeria 19.2 28.8 32.6 40.4 31.1 31.0 28.1 29.6 30.4 20.3 37.8 32.0 Rwanda 26.4 14.1 26.2 26.1 26.0 26.8 27.5 27.7 27.5 20.7 26.0 26.6 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 38.4 32.2 39.0 38.7 39.4 42.5 43.1 47.9 47.4 39.6 33.5 41.4 Seychelles 79.1 66.7 85.2 84.0 95.8 102.7 106.9 143.9 152.5 64.4 68.4 106.2 Sierra Leone 38.2 23.8 35.9 40.8 34.2 37.2 32.6 28.3 37.1 22.5 24.2 35.5 Somalia 88.5 37.7 .. .. .. .. .. .. .. 50.6 37.7 .. South Africa 27.3 18.8 29.1 25.8 27.1 28.2 32.9 34.7 40.4 23.8 20.7 29.9 Sudan 23.1 7.1 19.5 18.9 21.4 28.1 27.5 23.9 22.0 15.7 12.1 22.2 Swaziland 114.0 68.9 105.3 105.2 92.8 93.4 87.2 81.2 80.1 93.7 76.3 93.1 Tanzania .. 37.5 24.1 26.3 29.5 27.4 27.5 .. .. .. 35.6 26.2 Togo 56.4 45.3 51.7 47.4 47.0 57.2 61.8 62.5 67.5 53.3 39.8 55.2 Uganda 26.0 19.4 25.5 25.6 23.2 25.3 28.9 30.6 33.4 17.8 21.5 26.6 Zambia 45.4 36.6 41.8 41.1 42.8 36.8 30.2 35.6 34.3 36.5 38.4 38.7 Zimbabwe 26.5 22.8 10.1 30.3 52.6 73.0 .. .. .. 22.2 36.7 37.3 NORTH AFRICA 34.2 30.8 28.7 28.8 31.6 31.7 30.7 33.8 36.9 30.6 28.8 30.3 Algeria 30.3 24.9 25.4 23.9 25.7 24.3 21.6 23.6 24.5 26.3 24.2 23.5 Egypt, Arab Rep. 42.9 32.7 22.7 24.4 29.6 32.6 31.6 34.8 44.2 35.4 28.5 29.4 Libya .. 31.1 36.4 .. .. .. .. .. .. .. 25.1 23.5 Morocco 26.7 31.9 32.3 31.5 34.3 37.9 39.7 44.9 50.0 29.6 30.9 37.3 Tunisia 45.6 50.6 49.5 47.7 49.9 50.1 52.7 56.5 68.3 43.0 46.8 52.8 ALL AFRICA 29.7 27.0 30.9 31.9 32.5 33.1 33.2 35.0 37.1 27.5 28.4 32.4 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 63 Table 2.27 Balance of payments and current account Exports of goods and services Imports of goods and services Total trade (exports and imports) Current prices Share of GDP Current prices Share of GDP Current prices Share of GDP ($ millions) (%) ($ millions) (%) ($ millions) (%) 2008 a 2008a 2008 a 2008a 2008 a 2008a SUB­SAHARAN AFRICA 413,690 41.9 372,119 37.7 785,809 76.9 Excluding South Africa 314,556 43.2 261,529 35.9 576,086 .. Excl. S. Africa & Nigeria 222,731 43.2 196,532 38.1 419,264 .. Angola 74,618 89.5 32,731 39.3 107,349 128.7 Benin .. .. .. .. .. .. Botswana 5,928 45.7 5,333 41.1 11,261 86.8 Burkina Faso .. .. .. .. .. .. Burundi .. .. .. .. .. .. Cameroon 6,837 29.2 6,587 28.2 13,424 57.4 Cape Verde 345 19.9 945 54.7 1,290 74.6 Central African Republic 284 14.4 455 23.1 739 37.5 Chad 3,677 44.0 2,823 33.8 6,500 77.7 Comoros 68 12.8 196 36.9 264 49.7 Congo, Dem. Rep. 2,693 23.2 3,863 33.3 6,556 56.6 Congo, Rep. .. .. .. .. .. .. Côte d'Ivoire 11,953 51.1 10,838 46.3 22,791 97.3 Djibouti .. .. .. .. .. .. Equatorial Guinea 14,498 78.3 5,953 32.1 20,451 110.4 Eritrea .. .. .. .. .. .. Ethiopia 3,074 11.6 7,577 28.6 10,650 40.2 Gabon 11,151 77.2 5,517 38.2 16,668 115.5 Gambia, The 235 30.1 383 49.0 619 79.1 Ghana 5,940 36.8 10,188 63.2 16,128 100.0 Guinea 1,187 27.8 1,281 30.0 2,468 57.9 Guinea-Bissau 128 29.8 214 49.8 342 79.6 Kenya 8,599 24.9 13,456 39.0 22,055 63.9 Lesotho 767 47.3 1,796 110.8 2,564 158.1 Liberia .. .. .. .. .. .. Madagascar 2,363 26.3 4,630 51.6 6,993 78.0 Malawi 998 23.4 2,186 51.2 3,184 74.6 Mali .. .. .. .. .. .. Mauritania .. .. .. .. .. .. Mauritius 5,331 61.6 6,044 69.9 11,376 131.5 Mozambique 3,114 32.0 4,091 42.0 7,205 74.0 Namibia 3,335 38.9 4,117 48.1 7,452 87.0 Niger .. .. .. .. .. .. Nigeria 92,201 43.5 64,469 30.4 156,670 73.9 Rwanda 360 8.1 1,228 27.5 1,587 35.6 São Tomé and Príncipe .. .. .. .. .. .. Senegal 3,294 24.9 6,262 47.4 9,557 72.4 Seychelles 1,091 130.9 1,271 152.5 2,361 283.4 Sierra Leone 487 24.9 724 37.1 1,211 62.0 Somalia .. .. .. .. .. .. South Africa 100,562 36.3 111,723 40.4 212,285 76.7 Sudan 13,292 22.7 12,883 22.0 26,174 44.8 Swaziland 2,101 80.2 2,098 80.1 4,198 160.4 Tanzania .. .. .. .. .. .. Togo 1,142 40.4 1,905 67.5 3,047 107.9 Uganda 2,272 15.6 4,846 33.4 7,118 49.0 Zambia 5,267 36.8 4,909 34.3 10,176 71.1 Zimbabwe .. .. .. .. .. .. NORTH AFRICA 261,135 46.4 207,611 36.9 468,746 .. Algeria 102,773 59.1 42,597 24.5 145,370 83.6 Egypt, Arab Rep. 61,354 37.7 72,031 44.2 133,385 81.9 Libya .. .. .. .. .. .. Morocco 35,089 40.6 43,188 50.0 78,277 90.7 Tunisia 26,186 65.2 27,451 68.3 53,637 133.5 ALL AFRICA 674,727 43.1 581,372 37.1 1,256,099 .. a. Provisional. 64 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS Net income Net current transfers Current account balance Total reserves including gold Current prices Share of GDP Current prices Share of GDP Current prices Share of GDP Current prices Share of GDP ($ millions) (%) ($ millions) (%) ($ millions) (%) ($ millions) (%) 2007 2007 2007 2007 2007 2007 2008 a 2008a .. .. .. .. ­4,164 .. 156,071 15.6 .. .. .. .. 16,615 .. 122,001 16.7 .. .. .. .. ­5,356 .. 68,402 13.3 ­8,778 ­14.8 ­222 ­0.4 9,402 15.9 18,359 22.0 .. .. .. .. .. .. 1,260 18.9 ­346 ­2.8 1,105 9.0 2,434 19.8 9,119 70.3 .. .. .. .. .. .. 926 11.7 ­6 ­0.6 241 24.6 ­116 ­11.8 267 22.9 ­385 ­1.9 416 2.0 ­547 ­2.6 3,112 13.3 ­31 ­2.1 301 20.8 ­197 ­13.6 258 14.9 .. .. .. .. .. .. 131 6.7 .. .. .. .. .. .. 1,355 16.2 .. .. .. .. .. .. 113 21.3 .. .. .. .. .. .. .. .. ­1,885 ­24.7 ­38 ­0.5 ­2,181 ­28.5 3,881 36.3 ­810 ­4.1 ­379 ­1.9 ­146 ­0.7 2,252 9.6 24 2.9 79 9.7 ­171 ­21.0 .. .. .. .. .. .. .. .. 4,431 23.9 .. .. .. .. .. .. .. .. 40 0.2 3,387 17.5 ­828 ­4.3 871 3.3 .. .. .. .. .. .. 1,935 13.4 ­40 ­6.2 76 11.9 ­53 ­8.2 .. .. ­139 ­0.9 2,043 13.6 ­2,151 ­14.4 .. .. ­63 ­1.4 ­131 ­2.9 ­456 ­10.0 .. .. .. .. .. .. .. .. 124 29.0 ­192 ­0.7 2,108 7.8 ­1,102 ­4.1 2,879 8.3 420 25.2 625 37.4 212 12.7 .. .. ­150 ­20.4 1,139 155.0 ­211 ­28.7 .. .. .. .. .. .. .. .. 982 11.0 .. .. .. .. .. .. .. .. ­291 ­4.3 400 5.8 ­581 ­8.5 1,071 12.3 .. .. .. .. .. .. .. .. 223 3.3 125 1.8 ­434 ­6.4 1,796 20.8 ­592 ­7.4 602 7.5 ­785 ­9.8 .. .. ­158 ­1.8 1,000 11.5 747 8.6 1,293 15.1 .. .. .. .. .. .. 702 13.1 ­16,746 ­10.1 18,016 10.9 21,972 13.2 53,599 25.3 ­15 ­0.4 413 12.1 ­147 ­4.3 596 13.4 4 3.1 1 0.8 ­67 ­46.1 .. .. ­74 ­0.7 1,290 11.4 ­1,311 ­11.6 1,601 12.1 ­71 ­7.8 50 5.5 ­264 ­28.9 64 7.7 ­104 ­6.3 78 4.7 ­181 ­10.9 .. .. .. .. .. .. .. .. .. .. ­9,085 ­3.2 ­2,953 ­1.0 ­20,780 ­7.3 34,070 12.3 ­2,253 ­4.9 382 0.8 ­3,268 ­7.1 1,399 2.4 64 2.2 194 6.7 ­66 ­2.3 752 28.7 ­79 ­0.5 617 3.7 ­1,856 ­11.0 2,893 14.1 .. .. .. .. .. .. 580 20.5 ­246 ­2.1 1,108 9.3 ­528 ­4.4 2,301 15.8 ­1,383 ­12.1 530 4.6 ­505 ­4.4 1,096 7.7 .. .. .. .. .. .. .. .. .. .. .. .. 27,839 .. 310,523 55.1 .. .. .. .. .. .. 148,099 85.2 1,388 1.1 8,322 6.4 412 0.3 34,331 21.1 1,971 3.4 ­219 ­0.4 28,454 48.8 96,335 96.4 ­405 ­0.5 7,703 10.3 ­122 ­0.2 22,720 26.3 ­1,754 ­5.0 1,619 4.6 ­904 ­2.6 9,039 22.5 .. .. .. .. 23,675 .. 466,594 29.8 NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 65 Table 2.28 Exchange rates and purchasing power parity Purchasing power parity (PPP) Official exchange rate conversion factor Ratio of PPP conversion factor (local currency units to $) (local currency units to international $) to market exchange rate 2006 2007 2008 2006 2007 2008 2006 2007 2008 SUB­SAHARAN AFRICA Excluding South Africa Excl. S. Africa & Nigeria Angola 49.5 50.2 58.9 80.4 76.7 75.0 0.6 0.7 0.8 Benin 219.2 219.7 235.3 522.9 479.3 447.8 0.4 0.5 0.5 Botswana 2.7 3.0 3.4 5.8 6.1 6.8 0.5 0.5 0.5 Burkina Faso 193.9 196.0 201.5 522.9 479.3 447.8 0.4 0.4 0.5 Burundi 347.2 366.2 446.2 1,028.7 1,081.9 1,185.7 0.3 0.3 0.4 Cameroon 252.9 251.5 250.3 522.9 479.3 447.8 0.5 0.5 0.6 Cape Verde 71.8 72.2 74.5 87.9 80.6 75.3 0.8 0.9 1.0 Central African Republic 266.6 264.8 271.1 522.9 479.3 447.8 0.5 0.6 0.6 Chad 214.1 212.2 232.5 522.9 479.3 447.8 0.4 0.4 0.5 Comoros 223.7 229.2 236.6 392.2 359.5 335.9 0.6 0.6 0.7 Congo, Dem. Rep. 235.9 270.4 316.2 468.3 516.7 559.3 0.5 0.5 0.6 Congo, Rep. 308.8 277.1 335.9 522.9 479.3 447.8 0.6 0.6 0.8 Côte d'Ivoire 291.2 291.4 308.4 522.9 479.3 447.8 0.6 0.6 0.7 Djibouti 84.6 85.0 85.8 177.7 177.7 177.9 0.5 0.5 0.5 Equatorial Guinea 318.8 306.9 371.5 522.9 479.3 447.8 0.6 0.6 0.8 Eritrea 6.8 7.0 8.1 15.4 15.4 15.4 0.4 0.5 0.5 Ethiopia 2.4 2.8 3.5 8.7 9.0 9.6 0.3 0.3 0.4 Gabon 268.1 274.8 307.3 522.9 479.3 447.8 0.5 0.6 0.7 Gambia, The 7.4 7.7 7.9 28.1 24.9 .. 0.3 0.3 0.3 Ghana 0.4 0.5 0.5 0.9 0.9 .. 0.4 0.5 0.5 Guinea 1,624.1 1,857.1 2,524.2 .. .. .. 0.3 0.4 0.4 Guinea-Bissau 212.1 226.4 242.7 522.9 479.3 447.8 0.4 0.5 0.5 Kenya 30.7 31.3 39.0 72.1 67.3 69.2 0.4 0.5 0.6 Lesotho 3.7 3.9 4.2 6.8 7.0 8.3 0.5 0.6 0.5 Liberia 29.7 33.5 37.0 58.0 61.3 63.2 0.5 0.5 0.6 Madagascar 702.0 750.0 804.7 2,142.3 1,873.9 1,708.4 0.3 0.4 0.4 Malawi 45.0 47.1 50.2 136.0 140.0 .. 0.3 0.3 0.4 Mali 242.3 245.7 273.1 522.9 479.3 447.8 0.5 0.5 0.6 Mauritania 124.4 118.0 .. 268.6 258.6 .. 0.5 0.4 .. Mauritius 14.8 15.4 16.2 31.7 31.3 28.5 0.5 0.5 0.6 Mozambique 11.6 12.1 12.6 25.4 25.8 .. 0.5 0.5 0.5 Namibia 4.5 4.8 5.3 6.8 7.0 8.3 0.7 0.7 0.6 Niger 225.4 226.9 239.0 522.9 479.3 447.8 0.4 0.5 0.5 Nigeria 69.8 71.3 79.8 128.7 125.8 118.5 0.5 0.6 0.7 Rwanda 198.2 213.5 245.3 551.7 547.0 546.8 0.4 0.4 0.4 São Tomé and Príncipe 6,516.4 7,578.5 9,176.0 12,448.6 13,536.8 14,695.2 0.5 0.6 0.6 Senegal 254.4 261.8 275.0 522.9 479.3 447.8 0.5 0.5 0.6 Seychelles 3.3 3.5 4.2 5.5 6.7 9.5 0.6 0.5 0.4 Sierra Leone 1,164.5 1,251.2 1,367.5 2,961.9 2,985.2 2,980.7 0.4 0.4 0.5 Somalia .. .. .. .. .. .. .. .. .. South Africa 4.0 4.3 4.6 6.8 7.0 8.3 0.6 0.6 0.6 Sudan 1.1 1.2 1.3 2.2 2.0 2.1 0.5 0.6 0.7 Swaziland 3.5 3.7 3.8 6.8 7.0 8.3 0.5 0.5 0.5 Tanzania 403.8 428.6 456.9 1,251.9 1,245.0 1,196.3 0.3 0.3 0.4 Togo 233.9 230.9 236.0 522.9 479.3 447.8 0.4 0.5 0.5 Uganda 614.8 642.5 668.5 1,831.5 1,723.5 1,720.7 0.3 0.4 0.4 Zambia 2,654.2 2,890.7 3,133.5 3,603.1 4,002.5 3,745.7 0.7 0.7 0.8 Zimbabwe .. .. .. 164.4 9,675.8 .. .. .. .. NORTH AFRICA Algeria 34.1 35.5 40.7 72.6 69.3 64.6 0.5 0.5 0.6 Egypt, Arab Rep. 1.7 1.8 2.0 5.7 .. .. 0.3 0.3 0.4 Libya 0.8 0.8 1.3 1.3 1.3 1.2 0.6 0.7 1.0 Morocco 4.8 4.9 4.9 8.8 8.2 7.8 0.5 0.6 0.6 Tunisia 0.6 0.6 0.6 1.3 1.3 1.2 0.4 0.5 0.5 ALL AFRICA 66 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS Gross domestic product Real effective exchange rate Per capita (index, 2000 = 100) PPP $ billions PPP $ 2006 2007 2008 2006 2007 2008 2006 2007 2008 1,466.2 1,606.6 1,731.8 1,878.5 2,009.7 2,113.9 1,039.9 1,147.0 1,248.6 1,418.3 1,526.1 1,620.3 768.0 850.1 929.3 1,305.2 1,408.3 1,500.7 .. .. .. 73.4 90.6 106.3 4,295.0 5,162.6 5,898.5 .. .. .. 11.0 11.8 12.7 1,356.7 1,410.8 1,467.9 .. .. .. 23.6 25.2 25.5 12,683.8 13,405.6 13,391.8 .. .. .. 15.6 16.5 17.7 1,083.7 1,119.8 1,161.3 76.9 71.4 73.7 2.7 2.9 3.1 358.0 369.3 382.8 113.4 114.7 119.1 37.1 39.4 41.9 2,042.1 2,127.8 2,215.1 .. .. .. 1.5 1.6 1.7 3,034.0 3,283.0 3,504.3 114.4 115.1 123.8 2.9 3.1 3.3 679.2 713.3 735.7 126.7 .. .. 15.4 15.8 16.1 1,469.9 1,470.4 1,455.3 .. .. .. 0.7 0.7 0.8 1,152.1 1,160.5 1,169.0 32.8 31.9 31.6 17.4 19.0 20.6 287.5 304.8 321.4 .. .. .. 13.1 13.2 14.3 3,755.3 3,724.3 3,945.9 116.0 118.0 123.3 31.2 32.6 34.0 1,584.9 1,618.0 1,651.2 .. .. .. 1.6 1.7 1.8 1,951.7 2,052.6 2,140.2 150.8 158.7 170.9 15.8 19.6 22.3 25,186.2 30,577.1 33,872.9 .. .. .. 2.9 3.0 3.2 620.9 625.9 632.1 99.6 .. .. 54.0 61.6 70.1 704.9 783.3 868.1 100.5 105.6 109.8 18.6 20.2 21.0 13,340.8 14,188.7 14,526.5 54.2 59.4 68.3 1.9 2.1 2.3 1,219.9 1,294.5 1,362.8 116.4 115.7 109.2 28.7 31.2 33.9 1,281.2 1,366.3 1,452.1 .. .. .. 10.3 10.7 11.8 1,089.9 1,111.7 1,204.0 .. .. .. 0.8 0.8 0.8 518.9 524.0 537.8 .. .. .. 52.7 57.9 61.3 1,442.1 1,542.3 1,589.9 129.4 128.8 117.0 2.8 3.0 3.2 1,401.4 1,503.3 1,587.8 .. .. .. 1.2 1.3 1.5 344.8 370.6 387.8 .. .. .. 16.8 18.4 20.0 929.6 986.7 1,048.9 74.8 66.0 51.0 9.6 10.7 11.9 704.6 765.8 836.8 .. .. .. 12.7 13.4 14.3 1,057.8 1,083.2 1,127.6 .. .. .. 5.8 6.0 .. 1,889.4 1,927.5 .. .. .. .. 13.3 14.2 15.3 10,577.2 11,296.4 12,079.3 .. .. .. 15.6 17.1 18.6 743.4 801.4 855.4 .. .. .. 12.0 12.8 13.4 5,847.2 6,145.5 6,342.7 .. .. .. 8.5 9.0 10.0 615.7 631.8 684.0 133.3 130.7 144.7 268.0 292.9 315.0 1,851.8 1,979.0 2,081.9 .. .. .. 7.9 8.7 9.9 856.5 924.6 1,021.9 .. .. .. 0.2 0.3 0.3 1,533.5 1,638.2 1,738.5 .. .. .. 19.2 20.7 21.6 1,660.3 1,737.3 1,772.0 .. .. .. 1.6 1.8 1.9 18,995.3 20,810.2 21,529.6 73.6 73.9 79.8 3.6 4.0 4.3 686.5 732.2 766.3 .. .. .. .. .. .. .. .. .. 99.5 90.9 76.9 433.2 467.4 492.2 9,141.2 9,767.7 10,108.6 .. .. .. 71.1 80.4 89.0 1,798.5 1,989.3 2,153.3 .. .. .. 5.2 5.5 5.8 4,549.9 4,773.1 4,928.2 .. .. .. 44.4 48.9 53.7 1,107.5 1,184.0 1,262.9 112.4 113.5 121.8 5.0 5.2 5.4 806.8 823.2 829.5 88.1 90.3 92.7 29.6 32.9 36.9 996.8 1,075.4 1,164.7 180.0 153.9 145.7 14.5 15.8 17.1 1,205.7 1,283.0 1,355.8 .. .. .. .. .. .. .. .. .. 886.7 958.1 1,033.9 5,590.0 5,945.1 6,315.0 83.2 82.3 85.0 248.1 262.3 276.0 7,437.7 7,747.9 8,032.7 .. .. .. 367.3 403.7 441.6 4,672.4 5,042.3 5,416.4 .. .. .. 80.7 88.4 96.7 13,357.2 14,364.2 15,402.4 92.9 92.6 93.7 120.2 126.8 137.0 3,942.7 4,108.3 4,388.5 84.6 82.3 81.6 70.4 76.9 82.6 6,955.5 7,520.2 7,996.1 2,350.7 2,562.1 2,763.0 2,503.0 2,667.2 2,810.8 NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 67 Table 2.29 Agriculture value added Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 18.5 21.8 18.0 15.8 13.9 13.7 14.1 14.4 14.6 20.9 19.9 15.5 Excluding South Africa 23.4 32.1 24.2 23.4 21.0 20.4 20.2 20.0 19.3 29.2 31.5 22.3 Excl. S. Africa & Nigeria 27.9 29.5 24.6 24.9 23.4 22.5 22.1 21.6 20.3 28.7 29.3 23.5 Angola .. 17.9 7.9 8.3 8.6 7.7 8.9 9.7 10.1 15.2 11.3 8.3 Benin 35.4 36.1 33.8 32.1 32.1 32.2 .. .. .. 33.8 36.1 33.7 Botswana 12.7 4.5 2.2 2.2 2.0 1.8 1.7 1.7 1.6 7.8 3.9 2.0 Burkina Faso 28.4 28.0 32.6 33.4 30.6 33.0 32.8 .. .. 28.9 32.0 32.1 Burundi 57.6 51.1 36.5 36.1 36.1 31.6 .. .. .. 53.1 46.0 35.3 Cameroon 28.7 24.0 20.4 20.1 19.0 19.0 19.3 19.0 19.1 24.4 22.9 19.7 Cape Verde .. 14.4 7.1 6.8 9.7 9.2 8.7 8.5 8.1 16.6 12.9 8.6 Central African Republic 37.6 43.8 51.0 56.9 52.6 51.7 52.0 50.9 50.3 41.4 45.6 51.9 Chad 45.7 27.9 37.9 32.3 22.9 20.9 20.9 20.8 19.0 36.3 35.4 28.4 Comoros 34.0 41.4 50.2 50.5 50.9 51.0 45.2 45.3 45.8 36.3 40.2 48.6 Congo, Dem. Rep. 25.3 30.1 50.1 50.1 46.1 43.8 42.1 38.9 .. 29.0 46.5 47.4 Congo, Rep. 11.7 12.9 6.3 6.4 5.9 4.6 4.0 5.0 .. 10.0 10.5 5.4 Côte d'Ivoire 25.9 32.5 25.7 25.6 23.2 22.8 22.9 23.9 23.7 27.1 27.2 24.1 Djibouti .. 2.7 3.1 3.1 3.1 3.1 3.2 3.5 .. 2.8 3.0 3.2 Equatorial Guinea .. 58.9 6.3 5.4 4.0 2.6 2.7 2.7 2.0 62.4 40.3 4.7 Eritrea .. .. 14.7 13.4 12.6 21.2 23.3 23.3 .. .. 20.6 17.4 Ethiopia .. 51.7 40.4 38.9 40.4 43.0 44.4 43.0 39.8 53.3 55.4 42.3 Gabon 6.8 7.3 6.1 6.1 5.6 4.9 4.9 4.8 4.6 7.7 7.7 5.5 Gambia, The 27.0 24.3 24.9 28.2 29.1 28.3 26.3 24.8 24.7 29.2 24.6 27.8 Ghana 57.9 44.8 35.1 36.5 38.0 37.5 35.6 34.0 32.2 51.9 39.5 35.5 Guinea .. 24.7 18.7 21.5 15.0 19.0 12.7 15.8 7.5 24.2 19.5 16.5 Guinea-Bissau 42.2 56.9 56.4 56.8 51.9 50.0 50.1 48.8 51.5 47.0 53.7 52.0 Kenya 27.8 25.3 25.9 25.8 24.9 24.2 23.8 23.0 18.9 28.0 26.7 24.8 Lesotho 22.4 20.9 9.2 8.7 8.6 7.2 7.8 6.7 6.5 21.2 16.6 8.6 Liberia 32.2 54.4 75.5 71.6 68.2 65.8 55.5 54.0 .. 33.5 67.2 67.0 Madagascar 26.7 26.1 29.8 26.8 26.2 25.7 25.1 24.3 23.4 30.5 26.4 25.9 Malawi 39.2 38.5 34.6 33.8 32.8 29.3 30.5 30.1 28.5 39.2 33.5 32.3 Mali 43.6 44.1 32.3 35.8 33.4 33.7 34.1 33.4 .. 41.1 42.9 34.5 Mauritania 28.5 26.6 23.6 25.1 23.1 21.4 12.1 11.3 .. 27.5 31.0 20.8 Mauritius 14.0 11.0 6.3 5.4 5.4 5.3 4.9 4.7 4.0 12.9 9.1 5.2 Mozambique 33.9 34.1 25.4 25.4 24.8 24.5 24.7 24.4 25.4 37.8 32.3 23.9 Namibia 10.5 10.6 10.0 10.2 8.9 10.4 9.7 9.5 7.5 10.4 10.1 9.6 Niger 43.1 35.3 39.6 40.0 .. .. .. .. .. 38.6 39.4 39.4 Nigeria .. .. 47.1 41.5 33.4 32.4 31.7 32.2 31.9 .. .. 35.8 Rwanda 45.8 32.5 35.5 38.5 38.8 38.9 41.9 38.9 34.6 40.2 40.6 38.0 São Tomé and Príncipe .. .. 19.9 21.1 22.6 16.8 .. .. .. .. .. 20.0 Senegal 17.9 17.9 13.6 15.4 13.9 14.5 13.2 12.2 13.6 19.6 17.7 14.4 Seychelles 6.8 4.8 3.0 3.0 3.0 2.5 2.4 2.4 2.3 6.1 3.9 2.7 Sierra Leone 30.4 44.0 44.9 44.2 43.5 43.5 45.0 42.5 41.0 37.4 45.6 44.8 Somalia 64.4 62.7 .. .. .. .. .. .. .. 62.7 62.7 .. South Africa 5.8 4.2 3.8 3.2 2.8 2.4 2.5 2.8 2.3 5.0 3.8 2.9 Sudan 29.9 39.0 40.2 36.9 33.1 30.2 28.5 26.9 24.4 33.2 40.5 33.5 Swaziland 19.5 8.9 8.9 7.9 7.4 7.1 6.4 6.3 6.7 16.4 10.2 7.8 Tanzania .. 42.0 41.2 41.4 42.3 37.7 37.5 .. .. .. 43.0 40.4 Togo 27.5 33.8 38.1 40.8 41.2 43.7 .. .. .. 31.8 37.4 39.3 Uganda 71.8 53.3 23.4 24.5 21.7 25.1 24.0 22.3 20.8 54.8 44.3 24.1 Zambia 14.0 18.2 19.9 20.5 21.5 21.0 20.3 19.7 18.1 14.3 18.8 20.1 Zimbabwe 15.1 14.8 12.7 15.0 14.1 13.4 .. .. .. 14.8 15.0 14.5 NORTH AFRICA 11.4 12.8 12.6 12.7 11.8 10.3 10.4 9.9 10.4 11.7 12.6 11.4 Algeria 7.9 10.4 9.2 9.7 9.4 7.7 7.6 7.8 9.2 9.1 10.3 8.7 Egypt, Arab Rep. 17.4 18.4 15.4 15.3 14.3 14.0 13.2 13.4 14.3 18.9 16.2 14.5 Libya .. .. .. .. .. .. .. .. .. .. .. .. Morocco 18.4 17.7 14.7 15.5 14.7 13.2 15.2 12.2 14.2 16.2 16.9 14.2 Tunisia 14.1 15.7 10.3 12.1 12.7 11.2 10.8 10.3 10.0 13.8 14.0 11.3 ALL AFRICA 15.9 18.2 15.8 14.6 13.1 12.6 12.9 12.9 13.1 17.3 17.1 13.9 a. Provisional. 68 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.30 Table Industry value added Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 30.4 32.6 28.5 29.7 31.4 33.4 34.3 34.1 36.9 31.4 30.7 31.9 Excluding South Africa 22.7 29.5 28.9 31.4 35.1 38.4 39.4 38.8 43.2 25.4 28.5 35.0 Excl. S. Africa & Nigeria 24.1 24.2 26.3 27.4 29.8 33.2 34.8 35.4 39.5 22.4 23.7 31.1 Angola .. 40.8 68.2 67.4 66.1 72.6 69.7 72.4 86.3 39.4 56.9 71.1 Benin 12.3 13.2 13.7 13.7 13.3 13.4 .. .. .. 14.0 13.7 13.7 Botswana 43.9 56.9 50.7 47.6 48.2 49.3 50.9 45.5 43.3 52.4 50.5 49.5 Burkina Faso 19.8 20.4 19.8 20.3 21.6 21.9 22.0 .. .. 20.4 20.0 21.0 Burundi 11.7 17.3 16.7 17.0 17.0 18.2 .. .. .. 13.7 16.9 17.1 Cameroon 23.5 28.8 29.6 28.4 28.4 29.6 30.6 29.9 31.9 30.2 28.6 30.2 Cape Verde .. 21.4 16.1 19.7 15.2 16.7 16.1 16.4 16.7 19.0 19.7 16.6 Central African Republic 18.9 18.1 14.3 14.9 13.3 13.4 13.4 13.4 13.5 15.2 19.1 14.0 Chad 9.0 16.9 14.3 23.4 46.0 52.8 55.7 39.1 34.9 13.2 13.3 32.2 Comoros 13.2 8.3 11.6 12.7 12.2 11.0 11.8 11.9 12.0 12.5 11.4 11.8 Congo, Dem. Rep. 33.1 28.2 21.1 21.1 23.9 25.9 25.6 26.0 .. 28.7 20.4 22.9 Congo, Rep. 46.6 40.6 63.3 61.5 63.6 68.6 70.2 59.8 .. 45.1 45.4 65.6 Côte d'Ivoire 19.7 23.2 22.9 21.6 23.1 25.9 25.9 25.3 25.3 20.8 22.2 24.3 Djibouti .. 19.2 14.0 14.0 14.5 14.8 14.8 15.4 .. 17.6 14.6 14.3 Equatorial Guinea .. 10.2 87.3 87.6 91.1 93.8 93.6 93.8 95.0 8.5 37.9 90.4 Eritrea .. .. 20.7 22.2 23.2 19.2 17.2 18.4 .. .. 16.5 20.3 Ethiopia .. 10.6 12.9 13.1 12.8 11.9 11.7 12.4 11.7 11.0 9.6 12.2 Gabon 60.4 43.0 51.7 52.0 55.3 61.4 61.2 60.2 73.7 53.7 48.2 58.1 Gambia, The 13.0 11.0 13.1 12.7 11.4 11.7 12.4 12.8 13.0 11.8 11.7 12.2 Ghana 11.9 16.8 25.3 25.2 24.7 25.1 26.0 26.1 26.1 12.8 22.5 25.5 Guinea .. 34.6 30.4 28.9 29.5 33.1 36.7 42.6 33.0 33.8 29.2 32.8 Guinea-Bissau 18.7 17.4 12.9 12.8 12.4 13.0 12.8 12.0 12.0 15.2 12.0 12.5 Kenya 17.8 16.3 15.5 15.6 16.2 17.0 16.5 15.8 12.0 16.8 15.4 15.4 Lesotho 24.2 28.8 28.6 27.4 28.3 28.8 30.8 32.7 31.4 23.8 36.5 29.1 Liberia 25.2 16.8 8.0 10.6 13.4 15.7 16.7 18.6 .. 25.8 11.0 13.0 Madagascar 14.3 11.7 13.6 14.1 14.5 14.3 14.8 16.2 16.1 12.3 11.2 14.4 Malawi 20.2 24.7 15.6 16.8 16.7 18.2 17.6 17.9 17.1 20.2 20.4 16.8 Mali 11.9 15.4 25.4 21.8 21.9 22.3 22.2 22.1 .. 13.7 15.6 22.4 Mauritania 24.4 25.8 25.0 21.5 25.4 26.4 44.0 42.1 .. 24.4 24.3 29.5 Mauritius 22.3 27.7 27.5 26.6 25.7 24.5 23.5 24.7 24.5 24.1 28.0 25.7 Mozambique 31.5 16.9 21.2 23.6 24.8 23.0 23.8 22.8 23.0 23.4 15.8 22.9 Namibia 52.7 34.3 29.5 26.4 27.0 26.7 32.2 33.2 20.3 41.4 27.4 27.7 Niger 22.9 16.2 17.0 17.3 .. .. .. .. .. 19.8 17.4 17.3 Nigeria .. .. 29.6 35.7 41.1 43.0 41.6 38.9 43.1 .. .. 39.0 Rwanda 21.5 24.6 13.9 12.8 13.7 14.0 13.5 13.9 12.3 21.0 19.5 13.5 São Tomé and Príncipe .. .. 17.1 17.8 21.0 20.5 .. .. .. .. .. 18.7 Senegal 17.9 19.9 22.3 21.3 21.8 20.7 20.6 21.7 20.9 18.4 21.1 21.3 Seychelles 15.6 16.3 30.3 27.4 28.2 21.9 20.5 22.7 22.4 16.5 21.5 25.6 Sierra Leone 20.2 18.0 23.2 23.3 23.5 23.5 24.3 23.2 22.8 14.8 30.8 23.8 Somalia 7.5 .. .. .. .. .. .. .. .. 7.5 .. .. South Africa 45.5 36.4 30.1 28.6 27.7 27.4 27.6 27.6 26.1 40.4 31.9 28.2 Sudan 12.9 14.7 19.7 20.9 24.2 26.7 27.6 29.2 32.3 14.2 13.0 24.4 Swaziland 25.9 36.8 38.5 39.6 38.4 38.0 41.0 42.1 43.3 27.2 36.9 39.7 Tanzania .. 16.1 14.9 15.2 15.2 13.8 14.4 .. .. .. 14.3 14.7 Togo 24.8 22.5 18.5 22.2 22.8 24.0 .. .. .. 22.0 21.0 20.4 Uganda 4.5 10.4 22.8 22.5 20.7 23.4 22.7 24.0 23.7 8.9 13.8 22.5 Zambia 39.1 45.3 23.4 24.1 26.0 28.5 31.9 34.8 39.5 40.9 34.8 28.2 Zimbabwe 27.9 29.8 18.8 19.2 18.0 16.8 .. .. .. 27.6 27.1 19.1 NORTH AFRICA 42.1 35.4 38.3 39.1 40.3 41.9 42.7 41.8 45.2 38.7 34.8 40.3 Algeria 53.8 44.0 48.7 50.6 52.3 57.6 58.9 57.9 72.2 47.9 45.5 55.9 Egypt, Arab Rep. 35.1 27.3 32.6 33.4 34.7 34.1 36.2 34.7 37.0 29.2 29.9 33.8 Libya .. .. .. .. .. .. .. .. .. .. .. .. Morocco 30.9 32.4 24.3 25.0 25.7 25.3 24.4 24.2 18.4 32.9 30.5 24.2 Tunisia 31.1 29.8 29.6 28.3 28.2 28.9 29.2 29.6 28.4 31.5 28.8 28.8 ALL AFRICA 33.1 33.5 32.2 33.1 34.7 36.6 37.5 37.1 40.2 33.5 32.1 35.1 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 69 Table 2.31 Services plus discrepancy value added Share of GDP (%) Annual average 1980 1990 2002 2003 2004 2005 2006 2007 2008a 1980­89 1990­99 2000­08 SUB­SAHARAN AFRICA 32.9 44.0 43.6 44.8 45.1 43.6 42.8 42.5 38.8 39.4 47.1 43.5 Excluding South Africa 29.8 41.3 38.8 37.6 37.1 35.3 35.6 36.1 34.4 36.6 40.9 36.7 Excl. S. Africa & Nigeria 38.6 41.4 43.1 41.9 40.7 38.6 38.3 37.9 35.0 39.3 41.6 39.8 Angola .. 41.2 24.0 24.3 25.3 19.8 21.4 17.9 3.7 45.4 31.8 20.6 Benin 52.3 50.7 52.6 54.2 54.6 54.4 .. .. .. 52.2 50.2 52.6 Botswana 29.9 31.8 39.9 41.8 41.2 40.5 39.6 45.1 47.3 30.6 37.5 40.9 Burkina Faso 48.5 48.8 41.1 40.2 41.0 41.8 43.7 .. .. 47.8 42.8 41.9 Burundi 23.2 23.0 36.8 36.9 36.9 41.0 .. .. .. 24.5 27.7 37.6 Cameroon 39.6 44.9 42.4 44.1 45.3 48.8 47.5 48.6 46.4 40.4 42.9 44.8 Cape Verde .. 64.3 76.9 73.4 75.1 74.1 75.3 75.2 .. 64.4 67.4 74.7 Central African Republic 37.6 30.2 28.6 23.5 29.2 29.8 29.0 30.2 30.3 37.0 29.6 28.7 Chad 46.7 50.5 43.9 40.4 28.7 24.4 25.1 28.8 28.6 48.6 47.9 34.2 Comoros 52.8 50.3 38.3 36.7 36.9 38.0 .. .. .. 51.2 48.4 38.0 Congo, Dem. Rep. 36.1 39.0 27.0 27.0 28.0 28.4 27.3 29.8 .. 37.8 32.0 27.1 Congo, Rep. 41.7 46.5 30.4 32.0 30.5 26.8 25.8 35.1 .. 44.9 44.1 29.0 Côte d'Ivoire 54.4 44.3 51.4 52.8 53.7 51.3 51.2 50.9 51.0 52.0 50.6 51.6 Djibouti .. 65.4 70.4 69.5 69.4 71.0 72.2 72.4 .. 65.1 70.1 70.9 Equatorial Guinea .. 26.6 4.8 5.2 3.8 2.9 2.8 2.7 2.3 23.9 19.4 3.7 Eritrea .. .. 54.2 55.3 54.7 53.4 54.1 54.1 .. .. 52.7 54.9 Ethiopia .. 32.8 39.5 40.9 38.2 37.1 36.5 37.5 41.7 30.1 29.7 38.1 Gabon 32.8 49.7 42.2 41.9 39.1 33.8 33.9 34.9 21.7 38.6 44.0 36.4 Gambia, The 47.6 48.6 52.2 49.8 45.9 48.0 48.2 48.9 48.8 45.1 49.1 48.0 Ghana 30.2 38.4 39.6 38.2 37.3 37.4 38.4 40.0 41.7 35.3 38.0 39.1 Guinea .. 44.5 43.9 43.0 49.4 41.8 45.0 36.0 54.9 42.7 48.4 44.7 Guinea-Bissau 34.4 19.3 29.1 28.6 29.7 28.1 28.7 31.0 29.3 34.8 29.7 29.7 Kenya 39.7 44.1 47.4 47.5 47.7 47.8 48.6 49.5 58.1 41.7 44.7 48.6 Lesotho 44.5 40.4 55.8 55.9 53.4 54.5 52.4 51.3 52.3 43.1 39.7 54.1 Liberia 32.3 28.8 16.4 17.7 18.4 18.4 27.9 27.5 .. 34.0 21.8 20.0 Madagascar 47.8 53.5 50.8 50.8 50.2 50.8 51.5 52.4 53.4 46.2 54.9 51.6 Malawi 30.3 22.3 41.4 39.2 39.7 41.4 41.2 39.7 37.5 29.5 36.1 39.9 Mali 34.7 37.4 34.5 34.7 36.5 36.2 36.0 .. .. 37.6 33.5 35.2 Mauritania 41.0 37.3 42.9 44.5 41.8 42.5 35.9 36.7 .. 38.5 36.0 40.8 Mauritius 48.5 45.0 55.2 55.6 56.0 57.2 59.1 59.3 60.1 47.2 49.7 56.9 Mozambique 26.0 40.9 44.8 41.5 40.8 43.3 41.0 41.4 41.3 34.0 44.9 42.8 Namibia 31.2 45.3 51.9 56.6 55.9 54.5 50.5 49.7 65.4 41.7 51.9 54.8 Niger 34.0 48.6 43.4 42.7 .. .. .. .. .. 41.6 43.2 43.4 Nigeria .. .. 20.3 19.9 23.2 23.5 25.9 27.8 29.0 .. .. 24.2 Rwanda 32.6 42.8 50.6 48.8 47.5 47.2 44.7 47.1 53.1 38.8 39.9 48.5 São Tomé and Príncipe .. .. 63.0 61.2 56.4 62.7 .. .. .. .. .. 61.3 Senegal 53.3 52.0 51.8 51.1 51.9 51.7 54.9 55.7 56.9 51.0 50.9 52.8 Seychelles 77.5 78.9 66.7 69.6 68.8 75.6 77.1 74.9 75.3 77.4 74.6 71.7 Sierra Leone 41.4 31.8 25.8 27.0 27.8 28.0 25.9 29.4 31.9 41.3 18.7 26.0 Somalia 22.2 .. .. .. .. .. .. .. .. 23.5 .. .. South Africa 42.7 50.2 57.1 58.8 59.2 59.2 58.6 58.2 54.8 46.8 55.6 58.2 Sudan 48.3 42.5 35.7 37.4 36.5 37.4 38.6 38.9 38.0 46.3 42.8 37.2 Swaziland 40.5 39.6 34.8 35.1 36.5 38.2 37.1 36.9 33.6 40.4 37.7 35.7 Tanzania .. 33.3 36.1 35.3 34.1 30.3 30.9 .. .. .. 34.8 34.2 Togo 47.7 43.7 43.3 37.1 36.0 32.4 .. .. .. 46.2 41.7 40.3 Uganda 23.4 30.5 47.2 46.0 42.7 44.8 46.6 46.3 47.3 31.2 34.3 45.5 Zambia 39.7 24.8 46.8 46.2 45.8 45.8 44.7 36.6 27.8 34.8 35.2 43.0 Zimbabwe 53.1 45.4 58.1 55.0 52.2 40.0 .. .. .. 49.0 46.3 51.4 NORTH AFRICA 38.4 41.9 46.8 45.1 43.7 41.8 40.9 42.6 40.3 40.4 43.3 43.3 Algeria 31.6 37.0 33.8 32.0 31.0 28.1 28.1 29.1 23.7 34.9 35.8 30.0 Egypt, Arab Rep. 42.9 49.5 45.6 44.9 45.1 45.9 44.7 47.3 50.4 47.5 47.8 46.3 Libya .. .. .. .. .. .. .. .. .. .. .. .. Morocco 50.3 46.8 49.9 49.1 49.6 51.3 50.2 52.3 58.5 49.9 47.8 51.1 Tunisia 54.8 54.5 60.2 59.7 59.1 59.9 60.1 60.0 61.6 54.8 57.3 59.9 ALL AFRICA 34.2 43.4 44.8 45.2 45.1 43.5 42.6 42.9 39.7 39.6 45.9 43.7 a. Provisional. 70 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.32 Table Central government finances, expense, and revenue Finances Share of GDP (%) Revenue, excluding grants Expense Cash surplus or deficit 1990 2000 2007 1990 2000 2007 1990 2000 2007 SUB­SAHARAN AFRICA .. .. .. .. .. .. .. .. .. Excluding South Africa .. .. .. .. .. .. .. .. .. Excl. S. Africa & Nigeria .. .. .. .. .. .. .. .. .. Angola .. .. .. .. .. .. .. .. .. Benina .. .. .. .. .. .. .. .. .. Botswanaa 50.8 .. .. 26.7 .. .. 19.1 .. .. Burkina Faso .. .. .. .. .. .. .. .. .. Burundia .. .. .. .. .. .. .. .. .. Cameroona 14.3 .. .. 14.6 .. .. ­5.6 .. .. Cape Verde .. .. .. .. .. .. .. .. .. Central African Republic .. .. .. .. .. .. .. .. .. Chad .. .. .. .. .. .. .. .. .. Comoros .. .. .. .. .. .. .. .. .. Congo, Dem. Rep.a 1.0 0.0 .. 1.7 0.0 .. ­0.7 0.0 .. Congo, Rep. .. .. .. .. .. .. .. .. .. Côte d'Ivoirea .. 16.7 19.2 .. .. 20.5 .. .. ­0.8 Djibouti .. .. .. .. .. .. .. .. .. Equatorial Guinea .. .. .. .. .. .. .. .. .. Eritrea .. .. .. .. .. .. .. .. .. Ethiopiaa .. .. .. .. .. .. .. .. .. Gabon .. .. .. .. .. .. .. .. .. Gambia, Thea 19.4 .. .. 15.5 .. .. 0.1 .. .. Ghanaa 12.5 .. 25.7 .. .. 29.4 .. .. ­7.7 Guineaa .. .. .. .. .. .. .. .. .. Guinea-Bissau .. .. .. .. .. .. .. .. .. Kenya .. 19.7 18.9 .. 16.8 19.7 .. 2.0 ­3.0 Lesotho 42.1 48.3 60.3 31.5 .. 45.4 ­0.5 .. 8.8 Liberia .. .. .. .. .. .. .. .. .. Madagascar .. 11.7 11.9 .. 10.6 11.2 .. ­2.0 ­2.7 Malawi .. .. .. .. .. .. .. .. .. Mali .. 13.4 16.2 .. 11.6 15.2 .. ­3.4 ­5.6 Mauritania .. .. .. .. .. .. .. .. .. Mauritius 24.3 22.0 20.9 20.4 21.6 21.3 0.3 ­1.1 ­2.3 Mozambique .. .. .. .. .. .. .. .. .. Namibia 31.3 28.6 .. .. 27.6 .. .. ­2.6 .. Niger .. .. 13.6 .. .. 11.8 .. .. ­0.9 Nigeria .. .. .. .. .. .. .. .. .. Rwandaa 10.8 .. .. 12.7 .. .. ­5.4 .. .. São Tomé and Príncipe .. .. .. .. .. .. .. .. .. Senegal .. 16.9 .. .. 12.8 .. .. ­0.9 .. Seychelles .. 38.7 40.4 .. 43.1 41.2 .. ­13.9 ­6.0 Sierra Leonea 5.6 11.4 .. .. 28.7 .. .. ­9.3 .. Somalia .. .. .. .. .. .. .. .. .. South Africa .. 26.3 31.9 .. 27.9 30.0 .. ­2.0 1.6 Sudana .. .. .. .. .. .. .. .. .. Swazilanda .. .. .. .. .. .. .. .. .. Tanzania .. .. .. .. .. .. .. .. .. Togoa .. .. 17.0 .. .. 17.5 .. .. ­0.8 Ugandaa .. 10.8 .. .. 15.5 .. .. ­1.9 .. Zambiaa 20.4 .. 17.6 .. .. 22.9 .. .. ­0.8 Zimbabwea 24.1 .. .. 24.5 .. .. ­2.6 .. .. NORTH AFRICA .. .. .. .. .. .. .. .. .. Algeriaa .. 38.3 40.4 .. 20.8 18.7 .. 9.7 6.2 Egypt, Arab Rep.a 23.0 .. 27.1 24.0 .. 29.3 ­2.0 .. ­4.6 Libya .. .. .. .. .. .. .. .. .. Morocco .. .. 34.8 .. .. 29.2 .. .. 2.5 Tunisiaa 30.7 29.2 30.0 30.4 27.6 29.0 ­3.2 ­2.7 ­2.2 ALL AFRICA .. .. .. .. .. .. .. .. .. (continued) NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 71 Table 2.32 Central government finances, expense, and revenue (continued) Finances Share of GDP (%) Net incurrance of liabilities Domestic Foreign Total debt 1990 2000 2007 1990 2000 2007 1990 2000 2007 SUB­SAHARAN AFRICA .. .. .. .. .. .. .. .. .. Excluding South Africa .. .. .. .. .. .. .. .. .. Excl. S. Africa & Nigeria .. .. .. .. .. .. .. .. .. Angola .. .. .. .. .. .. 3.1 18.7 7.6 Benina .. .. .. .. .. .. .. .. .. Botswanaa ­0.8 .. .. 0.0 .. .. .. .. .. Burkina Faso .. .. .. .. .. .. .. .. .. Burundia .. .. .. .. .. .. .. 2.4 5.1 Cameroona .. .. .. 5.2 .. .. .. .. .. Cape Verde .. .. .. .. .. .. 1.7 3.0 .. Central African Republic .. .. .. .. .. .. .. .. .. Chad .. .. .. .. .. .. .. 2.9 .. Comoros .. .. .. .. .. .. 0.4 1.6 4.1 Congo, Dem. Rep.a 0.6 .. .. .. .. .. .. .. .. Congo, Rep. .. .. .. .. .. .. 8.2 9.0 3.0 Côte d'Ivoirea .. ­0.9 .. .. 1.7 .. 11.7 8.3 3.1 Djibouti .. .. .. .. .. .. .. 2.4 .. Equatorial Guinea .. .. .. .. .. .. .. .. .. Eritrea .. .. .. .. .. .. .. 0.5 1.5 Ethiopiaa .. .. .. .. .. .. 2.0 1.7 0.9 Gabon .. .. .. .. .. .. .. .. .. Gambia, Thea .. .. .. .. .. .. .. .. .. Ghanaa .. .. 5.1 .. .. 2.3 .. 7.1 2.7 Guineaa .. .. .. .. .. .. 6.3 3.9 1.6 Guinea-Bissau .. .. .. .. .. .. .. 6.1 8.9 Kenya .. .. 2.1 .. .. .. 9.2 4.7 1.5 Lesotho ­7.4 .. .. 8.5 .. .. .. .. 6.4 Liberia .. .. .. .. .. .. .. .. .. Madagascar .. 1.3 0.7 .. 1.7 2.2 .. .. .. Malawi .. .. .. .. .. .. .. .. .. Mali .. ­1.0 .. .. 3.0 3.5 .. .. .. Mauritania .. .. .. .. .. .. 12.7 7.1 3.5 Mauritius 4.4 3.1 ­0.6 ­0.5 ­0.4 2.1 6.5 10.8 3.8 Mozambique .. .. .. .. .. .. 2.3 2.4 13.1 Namibia .. .. .. .. .. .. .. .. .. Niger .. .. ­1.9 .. .. 2.4 .. .. .. Nigeria .. .. .. .. .. .. .. .. .. Rwandaa 3.3 .. .. .. .. .. .. .. .. São Tomé and Príncipe .. .. .. .. .. .. .. .. 121.6 Senegal .. 0.3 .. .. 0.5 .. 5.6 .. .. Seychelles .. 0.7 ­5.4 .. 13.1 11.9 .. 2.1 .. Sierra Leonea .. .. .. .. .. .. 3.3 7.3 3.5 Somalia .. .. .. .. .. .. .. .. .. South Africa .. 1.6 0.3 .. 0.3 ­0.2 .. 2.9 1.6 Sudana .. .. .. .. .. .. .. .. .. Swazilanda .. .. .. .. .. .. .. .. .. Tanzania .. .. .. .. .. .. 4.2 0.7 0.3 Togoa .. .. ­0.5 .. .. 0.7 .. .. .. Ugandaa .. 0.6 .. .. 2.0 .. 3.6 2.6 0.5 Zambiaa 6.8 .. .. 1.0 .. .. .. .. .. Zimbabwea .. .. .. .. .. .. 5.1 .. .. NORTH AFRICA .. .. .. .. .. .. .. .. .. Algeriaa .. 0.4 ­3.6 .. ­2.4 ­1.2 .. .. 2.2 Egypt, Arab Rep.a .. .. 7.3 .. .. 0.5 .. .. .. Libya .. .. .. .. .. .. .. .. .. Morocco .. .. ­2.9 .. .. 0.1 .. 7.3 5.3 Tunisiaa 3.6 0.6 0.3 1.8 ­0.2 ­1.0 10.7 9.6 7.7 ALL AFRICA .. .. .. .. .. .. .. .. .. 72 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS Expense Share of expense (%) Goods and services Compensation of employees Interest payments Subsidies and other transfers Other expenses 1990 2000 2007 1990 2000 2007 1990 2000 2007 1990 2000 2007 1990 2000 2007 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 35.2 .. .. 29.1 .. .. 2.8 .. .. 31.8 .. .. 1.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 16.7 .. .. 55.6 .. .. 7.8 .. .. 13.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 56.3 59.4 .. 25.4 27.4 .. 7.4 .. .. .. 13.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 34.2 .. .. 32.9 .. .. 8.5 .. .. 17.7 .. .. 6.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 31.3 .. .. 31.7 .. .. 23.6 .. .. 13.4 .. .. .. .. .. .. .. 14.9 .. .. 37.5 .. .. 10.6 .. .. 37.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 21.3 15.5 .. 55.2 43.5 .. 17.8 10.9 .. 3.4 .. .. 2.2 .. 30.8 .. 36.7 38.6 .. 32.9 18.7 .. 5.5 8.9 .. 10.7 2.9 .. 6.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 17.7 13.9 .. 40.7 46.0 .. 13.4 10.1 .. 9.7 14.0 .. 18.6 16.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 37.6 37.8 .. 36.5 32.6 .. 8.0 2.4 .. 0.4 15.8 .. 17.5 11.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 10.5 11.6 11.9 44.8 38.2 35.4 17.9 12.3 14.6 25.7 32.8 33.4 1.2 5.2 4.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 21.6 .. .. 51.2 .. .. 7.3 .. .. .. .. .. .. .. .. .. 29.6 .. .. 30.2 .. .. 3.0 .. .. 9.3 .. .. 28.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 35.3 .. .. 43.5 .. .. 7.9 .. .. 15.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 26.0 .. .. 41.4 .. .. 10.7 .. .. 18.7 .. .. .. .. .. 24.6 24.3 .. 36.3 32.0 .. 17.3 16.5 .. 21.6 26.9 .. .. 0.3 .. 14.9 .. .. 23.4 .. .. 21.9 .. .. 5.5 .. .. 34.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 11.3 10.5 .. 15.6 14.2 .. 18.1 8.8 .. 52.9 59.1 .. 2.2 8.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 25.1 .. .. 30.7 .. .. 5.9 .. .. 26.6 .. .. 11.7 .. 55.1 .. .. 12.3 .. .. 5.2 .. .. 27.4 .. .. .. .. .. .. 31.9 .. .. 30.3 .. .. 6.9 .. .. 24.1 .. .. 6.8 21.7 .. .. 40.9 .. .. 17.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 6.4 5.4 .. 33.8 28.2 .. 19.0 4.6 .. 40.8 32.4 .. .. 29.4 22.4 .. 7.8 26.6 .. 24.1 16.3 .. 17.6 .. .. 39.4 .. .. 11.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 8.7 .. .. 45.7 .. .. 6.7 .. .. 29.4 .. .. 9.5 7.0 8.6 6.3 31.4 39.8 37.9 10.9 12.1 9.1 44.9 .. 37.0 5.8 .. 9.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. (continued) NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 73 Table 2.32 Central government finances, expense, and revenue (continued) Revenue Share of revenue (%) Taxes on income, Interest profits, and Taxes on goods Taxes on Other Social Grants and payments capital gains and services international trade taxes contributions other revenue 1990 2000 2007 1990 2000 2007 1990 2000 2007 1990 2000 2007 1990 2000 2007 1990 2000 2007 1990 2000 2007 SUB­SAHARAN AFRICA .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Excluding South Africa .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Excl. S. Africa & Nigeria .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Angola .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Benin .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Botswana 1.4 .. .. 37.6 .. .. 1.8 .. .. 12.9 .. .. 0.1 .. .. .. .. .. 47.6 .. .. Burkina Faso .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Burundi .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Cameroon 8.0 .. .. 18.9 .. .. 22.2 .. .. 15.5 .. .. 4.6 .. .. 1.8 .. .. 27.5 .. .. Cape Verde .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Central African Republic .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Chad .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Comoros .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. 10.1 .. .. 2.2 0.0 .. 1.5 0.0 .. 3.8 0.0 .. 0.1 0.0 .. 1.0 .. .. 2.3 0.0 .. Congo, Rep. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Côte d'Ivoire .. 23.2 8.9 .. 23.0 .. .. 19.9 .. .. 38.8 .. .. 3.7 .. .. 8.1 6.9 .. 6.4 .. Djibouti .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Equatorial Guinea .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Eritrea .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Ethiopia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Gabon .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Gambia, The 16.6 .. .. 11.3 .. .. 32.9 .. .. 37.7 .. .. 0.5 .. .. 0.3 .. .. 17.3 .. .. Ghana 10.2 .. 9.6 0.0 .. .. 0.0 .. .. 0.0 .. .. .. .. .. .. .. .. 0.0 .. .. Guinea .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Guinea-Bissau .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Kenya .. 15.2 10.9 .. 28.5 .. .. 41.4 .. .. 15.0 .. .. 0.5 .. .. 0.0 .. .. 14.7 .. Lesotho 10.8 10.0 4.0 8.7 17.2 .. 16.0 12.5 .. 43.6 41.4 .. 0.1 .. .. .. .. .. 31.6 28.9 .. Liberia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Madagascar .. 9.3 7.0 .. 11.6 .. .. 21.5 .. .. 39.6 .. .. 1.2 .. .. .. .. .. 26.0 .. Malawi .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Mali .. 5.0 1.7 .. 12.5 .. .. 41.6 .. .. 11.3 .. .. 5.0 .. .. .. .. .. 29.5 .. Mauritania .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Mauritius 14.9 11.9 14.8 13.7 11.4 .. 20.6 37.9 .. 45.7 27.5 .. 6.1 5.4 .. 4.5 5.3 5.0 9.4 12.5 .. Mozambique .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Namibia 1.3 6.9 .. 32.6 31.8 .. 23.9 20.8 .. 25.3 36.4 .. 0.9 1.1 .. .. .. .. 17.2 9.9 .. Niger .. .. 1.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Nigeria .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 7.3 .. .. 14.0 .. .. 27.1 .. .. 20.5 .. .. 3.1 .. .. 5.4 .. .. 30.0 .. .. São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Senegal .. 7.4 .. .. 21.3 .. .. 33.7 .. .. 29.5 .. .. 3.3 .. .. .. .. .. 12.2 .. Seychelles .. 18.6 16.7 .. 17.3 .. .. 5.1 .. .. 41.0 .. .. 1.6 .. .. 13.8 18.1 .. 21.3 .. Sierra Leone 25.7 32.5 .. 29.7 15.4 .. 22.1 7.6 .. 38.1 29.4 .. 0.2 .. .. .. .. .. 9.9 47.7 .. Somalia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa .. 19.1 8.3 .. 51.7 .. .. 33.1 .. .. 3.0 .. .. 2.8 .. .. 2.1 1.9 .. 7.4 .. Sudan .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Swaziland .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Tanzania .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Togo .. .. 5.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Uganda .. 4.7 .. .. 9.9 .. .. 29.4 .. .. 21.8 .. .. 0.1 .. .. .. .. .. 38.7 .. Zambia 7.1 .. 7.2 39.5 .. 33.1 37.4 .. 35.8 17.2 .. 8.1 0.2 .. 0.2 0.0 .. .. 5.8 .. 22.7 Zimbabwe 17.7 .. .. 43.7 .. .. 25.6 .. .. 17.1 .. .. 1.1 .. .. 3.3 .. .. 9.2 .. .. NORTH AFRICA Algeria .. 10.3 2.1 .. 79.5 .. .. 7.0 .. .. 8.9 .. .. 1.0 .. .. .. .. .. 3.5 .. Egypt, Arab Rep. 16.0 .. 18.7 23.1 .. 33.2 16.3 .. 22.4 16.5 .. 5.9 13.0 .. 3.4 14.5 .. .. 40.3 .. 51.8 Libya .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Morocco .. .. 5.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 13.2 .. .. .. Tunisia 10.6 11.3 8.8 12.3 20.4 29.1 19.1 37.1 34.4 27.5 10.7 6.5 4.8 4.4 4.8 13.0 17.0 18.1 23.4 10.5 12.0 ALL AFRICA .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. a. Data were reported on a cash basis and have been adjusted to the accrual framework. 74 Part I. Basic indicators and national and fiscal accounts NATIONAL AND FISCAL ACCOUNTS 2.33 Table Structure of demand Share of GDP (%) Household final General government consumption final consumption Gross fixed capital Exports of goods Imports of goods Gross national expenditure expenditure formation and services and services savings 1990 2000 2008a 1990 2000 2008a 1990 2000 2008a 1990 2000 2008a 1990 2000 2008a 1990 2000 2008a SUB­SAHARAN AFRICA 65.3 68.7 66.5 17.2 14.6 12.3 18.1 15.9 18.5 26.4 34.1 41.9 24.7 31.1 37.7 12.9 12.9 4.3 Excluding South Africa 72.5 73.8 .. 15.3 11.9 9.4 17.6 16.7 17.8 27.6 38.0 43.2 28.3 35.0 35.9 9.1 11.0 0.7 Excl. S. Africa & Nigeria 72.5 73.8 72.4 14.8 12.5 10.8 17.0 17.5 20.6 25.1 33.5 43.2 28.2 35.8 38.1 10.7 14.1 0.9 Angola 35.8 .. .. 34.5 .. .. 11.1 15.1 12.3 38.9 89.6 89.5 20.9 62.8 39.3 .. 23.8 47.4 Benin 86.8 82.4 .. 11.0 11.6 .. 13.4 18.9 .. 14.3 15.2 .. 26.3 28.1 .. .. 10.9 .. Botswana 33.2 23.2 31.2 24.1 22.9 19.2 32.4 21.7 27.0 55.1 52.6 45.7 49.8 33.7 41.1 43.3 51.7 54.8 Burkina Faso 73.5 78.5 .. 21.1 20.8 .. 17.7 18.7 .. 11.0 9.1 .. 24.5 25.2 .. 13.7 5.1 .. Burundi 94.5 88.5 .. 10.8 17.5 .. 15.2 6.1 .. 7.9 7.8 .. 27.8 19.9 .. .. 1.2 .. Cameroon 66.6 70.2 67.6 12.8 9.5 12.7 17.3 16.0 18.7 20.2 23.3 29.2 17.3 19.7 28.2 16.1 16.0 20.2 Cape Verde 93.4 92.9 73.5 14.7 21.3 18.4 22.9 19.7 42.9 12.7 27.5 19.9 43.7 61.4 54.7 .. 9.1 26.8 Central African Republic 85.7 80.8 94.9 14.9 14.0 3.5 11.4 9.5 10.3 14.8 19.8 14.4 27.6 24.1 23.1 .. 8.2 4.0 Chad 97.6 86.8 68.9 10.0 7.7 5.8 4.8 20.9 14.1 13.5 16.9 44.0 27.9 34.7 33.8 ­2.7 7.9 7.8 Comoros 78.7 94.0 96.0 24.5 11.7 12.1 11.9 10.1 16.1 14.3 16.7 12.8 37.1 32.5 36.9 10.1 9.9 11.2 Congo, Dem. Rep. 79.1 88.0 82.1 11.5 7.5 11.0 12.8 3.5 17.0 29.5 22.4 23.2 29.2 21.4 33.3 0.8 ­1.3 0.2 Congo, Rep. 62.4 29.1 .. 13.8 11.6 .. 17.2 20.9 .. 53.7 80.3 .. 45.8 43.6 .. .. 30.1 .. Côte d'Ivoire 71.9 74.9 77.1 16.8 7.2 8.1 8.5 11.2 10.1 31.7 40.4 51.1 27.1 33.3 46.3 .. 8.0 9.6 Djibouti 78.9 76.8 .. 31.5 29.7 .. 14.1 8.8 .. 53.8 35.1 .. 78.4 50.4 .. .. 5.4 .. Equatorial Guinea 80.3 20.9 24.5 39.7 4.6 2.6 17.4 61.3 28.2 32.2 98.6 78.3 69.6 85.4 32.1 ­22.0 45.7 35.7 Eritrea .. 79.1 .. .. 63.8 .. .. 23.8 .. .. 15.1 .. .. 81.8 .. .. 12.2 .. Ethiopia 77.2 73.8 84.9 13.2 17.9 11.3 12.9 20.3 20.8 5.6 12.0 11.6 8.8 24.0 28.6 11.9 16.2 16.5 Gabon 49.7 32.2 25.8 13.4 9.6 7.8 21.4 21.9 27.3 46.0 69.0 77.2 30.9 32.7 38.2 24.0 42.2 48.7 Gambia, The 75.6 77.8 78.0 13.7 13.7 15.8 22.3 17.4 .. 59.9 48.0 30.1 71.6 56.8 49.0 .. 13.6 10.8 Ghana 85.2 84.3 80.8 9.3 10.2 13.6 14.4 23.1 32.0 16.9 48.8 36.8 25.9 67.2 63.2 .. 15.7 19.6 Guinea 66.9 77.7 84.6 11.0 6.8 4.9 22.9 18.9 12.7 31.1 23.6 27.8 33.4 27.9 30.0 14.6 13.3 9.2 Guinea-Bissau 86.9 94.6 81.3 10.3 14.0 13.9 29.9 11.3 23.8 9.9 31.8 29.8 37.0 51.6 49.8 15.3 ­2.7 22.9 Kenya 62.8 77.7 78.6 18.6 15.1 10.8 20.6 16.7 24.7 25.7 21.6 24.9 31.3 31.7 39.0 18.6 13.0 17.6 Lesotho 121.0 81.5 107.9 21.4 33.8 26.8 56.3 48.9 28.8 17.0 32.6 47.3 115.6 98.5 110.8 40.8 30.8 24.8 Liberia .. .. .. .. .. .. .. .. .. .. 21.5 .. .. 26.0 .. .. .. .. Madagascar 86.4 83.2 85.0 8.0 9.0 4.6 14.8 15.0 35.7 16.6 30.7 26.3 28.0 38.0 51.6 9.2 9.4 12.4 Malawi 71.5 81.6 85.0 15.1 14.6 10.9 20.1 12.3 30.2 23.8 25.6 23.4 33.4 35.3 51.2 13.6 2.2 9.1 Mali 79.8 79.4 .. 13.8 8.6 .. 23.0 24.6 .. 17.1 26.8 .. 33.7 39.4 .. 15.1 16.0 .. Mauritania 69.2 82.8 .. 25.9 25.8 .. 20.0 19.4 .. 45.6 46.2 .. 60.7 74.2 .. 17.6 0.8 .. Mauritius 63.7 63.0 70.2 12.8 13.1 12.9 28.3 25.3 24.2 64.2 62.7 61.6 71.4 64.6 69.9 26.3 25.3 22.7 Mozambique 92.3 79.5 74.7 13.5 9.0 12.3 22.1 31.0 23.0 8.2 17.5 32.0 36.1 37.0 42.0 2.1 14.8 10.4 Namibia 51.2 63.1 68.5 30.6 23.5 18.0 21.2 16.6 22.6 51.9 40.9 38.9 67.4 44.5 48.1 34.8 25.4 24.8 Niger 83.8 83.4 .. 15.0 13.0 .. 11.4 11.2 .. 15.0 17.8 .. 22.0 25.7 .. ­1.2 2.8 .. Nigeria .. .. .. .. .. .. .. .. .. 43.4 54.0 43.5 28.8 32.0 30.4 .. .. .. Rwanda 83.7 87.7 89.6 10.1 11.0 9.1 14.6 18.3 20.8 5.6 8.7 8.1 14.1 25.7 27.5 11.3 12.9 13.0 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Senegal 79.2 76.0 82.3 18.4 12.8 10.0 18.0 22.4 30.2 25.4 27.9 24.9 32.2 37.2 47.4 .. .. 17.9 Seychelles 52.0 53.9 78.5 27.7 24.2 14.8 23.0 25.2 28.3 62.5 78.2 130.9 66.7 81.4 152.5 .. 17.2 2.7 Sierra Leone 83.5 100.0 79.8 7.8 14.3 12.7 9.6 6.9 19.7 22.4 18.1 24.9 23.8 39.3 37.1 2.6 ­9.0 14.1 Somalia .. .. .. .. .. .. 14.9 .. .. 9.8 .. .. 37.7 .. .. .. .. .. South Africa 57.1 63.0 61.5 19.7 18.1 20.2 19.1 15.1 22.2 24.2 27.9 36.3 18.8 24.9 40.4 19.3 15.8 14.0 Sudan 86.1 76.5 59.2 5.8 7.6 16.4 10.4 12.1 20.2 4.0 15.3 22.7 7.1 17.7 22.0 0.9 10.1 15.4 Swaziland 80.4 78.0 61.3 14.3 18.7 23.6 14.5 17.4 14.9 59.0 76.1 80.2 68.9 90.1 80.1 19.7 12.8 30.5 Tanzania 80.9 79.2 .. 17.8 10.6 .. 25.8 17.4 .. 12.6 16.8 .. 37.5 24.2 .. .. 10.1 .. Togo 71.1 92.0 .. 14.2 10.2 16.3 25.3 17.8 .. 33.5 30.7 40.4 45.3 50.7 67.5 .. 0.4 .. Uganda 91.9 77.8 82.4 7.5 14.5 11.8 12.7 19.2 23.3 7.2 10.6 15.6 19.4 22.5 33.4 0.6 8.6 12.0 Zambia 64.4 87.4 66.3 19.0 9.5 9.0 13.5 16.0 21.4 35.9 27.1 36.8 36.6 41.5 34.3 6.7 ­1.3 19.8 Zimbabwe 63.1 72.8 .. 19.4 13.9 .. 18.2 11.8 .. 22.9 35.9 .. 22.8 36.2 .. 15.7 9.6 .. NORTH AFRICA 64.1 61.3 57.1 16.2 14.5 9.5 24.1 20.1 23.4 27.2 28.4 46.4 30.8 25.0 36.9 14.2 12.9 .. Algeria 56.8 41.6 21.7 16.1 13.6 6.8 27.0 20.7 27.9 23.4 41.2 59.1 24.9 21.4 24.5 .. 41.3 71.6 Egypt, Arab Rep. 72.6 75.9 72.0 11.3 11.2 10.8 26.9 18.9 23.7 20.0 16.2 37.7 32.7 22.8 44.2 .. .. 23.6 Libya 48.4 46.6 .. 24.4 20.5 .. 13.9 12.9 .. 39.7 35.0 .. 31.1 15.2 .. .. .. .. Morocco 64.6 61.4 60.6 15.5 18.4 15.6 24.0 26.0 32.0 26.5 28.0 40.6 31.9 33.4 50.0 24.4 24.0 34.4 Tunisia 63.6 60.7 64.5 16.4 15.6 13.6 24.4 26.0 24.1 43.6 44.5 65.2 50.6 48.2 68.3 .. 23.2 16.7 ALL AFRICA 64.7 65.3 62.3 16.7 14.5 11.2 20.4 17.8 20.4 26.8 31.7 43.1 27.0 28.5 37.1 13.4 12.9 2.8 a. Provisional. NATIONAL AND FISCAL ACCOUNTS Part I. Basic indicators and national and fiscal accounts 75 Table 3.1 Millennium Development Goal 1: eradicate extreme poverty and hunger International poverty line Share of population Poverty gap ratio at PPP $1.25 a day Share of population Poverty gap ratio at PPP $2 a day below PPP $1.25 a day (incidence × depth of poverty) below PPP $2 a day (incidence × depth of poverty) Surveys Surveys Surveys Surveys Surveys Surveys Surveys Surveys 1990­99 b 2000­07 b 1990­99 b 2000­07 b 1990­99 b 2000­07 b 1990­99b 2000­07b Year Percent Year Percent Year Percent Year Percent Year Percent Year Percent Year Percent Year Percent SUB­SAHARAN AFRICA Angola .. 2000 54.3 .. 2000 29.9 .. 2000 70.2 .. 2000 42.3 Benin .. 2003 47.3 .. 2003 15.7 .. 2003 75.3 .. 2003 33.5 Botswana 1994 31.2 .. 1994 11.0 .. 1994 49.4 .. 1994 22.3 .. Burkina Faso 1998 70.0 2003 56.5 1998 30.2 2003 20.3 1998 87.6 2003 81.2 1998 49.1 2003 39.2 Burundi 1998 86.4 2006 81.3 1998 47.3 2006 36.4 1998 95.4 2006 93.4 1998 64.1 2006 56.0 Cameroon 1996 51.5 2001 32.8 1996 18.9 2001 10.2 1996 74.4 2001 57.7 1996 36.0 2001 23.6 Cape Verde .. 2001 20.6 .. 2001 5.9 .. 2001 40.2 .. 2001 14.9 Central African Republic 1993 82.8 2003 62.4 1993 57.0 2003 28.3 1993 90.7 2003 81.9 1993 68.4 2003 45.3 Chad .. 2003 61.9 .. 2003 25.6 .. 2003 83.3 .. 2003 43.9 Comoros .. 2004 46.1 .. 2004 20.8 .. 2004 65.0 .. 2004 34.2 Congo, Dem. Rep. .. 2006 59.2 .. 2006 25.3 .. 2006 79.5 .. 2006 42.4 Congo, Rep. .. 2005 54.1 .. 2005 22.8 .. 2005 74.4 .. 2005 38.8 Côte d'Ivoire 1998 24.1 2002 23.3 1998 6.7 2002 6.8 1998 49.1 2002 46.8 1998 18.1 2002 17.6 Djibouti 1996 4.8 2002 18.8 1996 1.6 2002 5.3 1996 15.1 2002 41.2 1996 4.5 2002 14.6 Equatorial Guinea .. .. .. .. .. .. .. .. Eritrea .. .. .. .. .. .. .. .. Ethiopia 1995 60.5 2005 39.0 1995 21.2 2005 9.6 1995 84.6 2005 77.5 1995 41.2 2005 28.8 Gabon .. 2005 4.8 .. 2005 0.9 .. 2005 19.6 .. 2005 5.0 Gambia, The 1998 66.7 2003 34.3 1998 34.7 2003 12.1 1998 82.0 2003 56.7 1998 50.0 2003 24.9 Ghana 1998 39.1 2006 30.0 1998 14.4 2006 10.5 1998 63.3 2006 53.6 1998 28.5 2006 22.3 Guinea 1994 36.8 2003 70.1 1994 11.5 2003 32.2 1994 63.8 2003 87.2 1994 26.4 2003 50.2 Guinea-Bissau 1993 52.1 2002 48.8 1993 20.6 2002 16.5 1993 75.7 2002 77.9 1993 37.4 2002 34.8 Kenya 1997 19.6 2005 19.7 1997 4.6 2005 6.1 1997 42.7 2005 39.9 1997 14.7 2005 15.1 Lesotho 1995 47.6 2003 43.4 1995 26.7 2003 20.8 1995 61.1 2003 62.2 1995 37.3 2003 33.0 Liberia .. 2007 83.7 .. 2007 40.8 .. 2007 94.8 .. 2007 59.5 Madagascar 1999 82.3 2005 67.8 1999 44.3 2005 26.5 1999 93.1 2005 89.6 1999 61.0 2005 46.9 Malawi 1998 83.1 2004 73.9 1998 46.0 2004 32.3 1998 93.5 2004 90.4 1998 62.3 2004 51.8 Mali 1994 86.1 2006 51.4 1994 53.1 2006 18.8 1994 93.9 2006 77.1 1994 67.2 2006 36.5 Mauritania 1996 23.4 2000 21.2 1996 7.1 2000 5.7 1996 48.3 2000 44.1 1996 17.8 2000 15.9 Mauritius .. .. .. .. .. .. .. .. Mozambique 1997 81.3 2003 74.7 1997 42.0 2003 35.4 1997 92.9 2003 90.0 1997 59.4 2003 53.5 Namibia 1993 49.1 .. 1993 24.6 .. 1993 62.2 .. 1993 36.5 .. Niger 1994 78.2 2005 65.9 1994 38.6 2005 28.1 1994 91.5 2005 85.6 1994 56.5 2005 46.6 Nigeria 1996 68.5 2004 64.4 1996 32.1 2004 29.6 1996 86.4 2004 83.9 1996 49.7 2004 46.9 Rwanda .. 2000 76.6 .. 2000 38.2 .. 2000 90.3 .. 2000 55.7 São Tomé and Príncipe .. .. .. .. .. .. .. .. Senegal 1995 54.1 2005 33.5 1995 19.5 2005 10.8 1995 79.4 2005 60.3 1995 37.9 2005 24.6 Seychelles .. .. .. .. .. .. .. .. Sierra Leone 1990 62.8 2003 53.4 1990 44.8 2003 20.3 1990 75.0 2003 76.1 1990 54.0 2003 37.5 Somalia .. .. .. .. .. .. .. .. South Africa 1995 21.4 2000 26.2 1995 5.2 2000 8.2 1995 39.9 2000 42.9 1995 15.0 2000 18.3 Sudan .. .. .. .. .. .. .. .. Swaziland 1995 78.6 2001 62.9 1995 47.7 2001 29.4 1995 89.3 2001 81.0 1995 61.6 2001 45.8 Tanzania 1992 72.6 2000 88.5 1992 29.7 2000 46.8 1992 91.3 2000 96.6 1992 50.1 2000 64.4 Togo .. 2006 38.7 .. 2006 11.4 .. 2006 69.3 .. 2006 27.9 Uganda 1999 60.5 2005 51.5 1999 24.5 2005 19.1 1999 82.7 2005 75.6 1999 42.9 2005 36.4 Zambia 1998 55.4 2004 64.3 1998 26.9 2004 32.8 1998 74.8 2004 81.5 1998 41.7 2004 48.3 Zimbabwe .. .. .. .. .. .. .. .. NORTH AFRICA Algeria 1995 6.8 .. 1995 1.4 .. 1995 23.6 .. 1995 6.4 .. Egypt, Arab Rep. 1996 2.5 2005 2.0 1996 0.5 2005 0.5 1996 26.3 2005 18.4 1996 5.0 2005 3.5 Libya .. .. .. .. .. .. .. .. Morocco 1999 6.8 2007 2.5 1999 1.2 2007 0.5 1999 24.4 2007 14.0 1999 6.5 2007 3.1 Tunisia 1995 6.5 2000 2.6 1995 1.3 2000 0.5 1995 20.4 2000 12.8 1995 5.8 2000 3.0 76 Part II. Millennium Development Goals MILLENNIUM DEVELOPMENT GOALS Share of population below Share of urban population below Share of rural population below national poverty linea national poverty linea national poverty linea (poverty headcount ratio) (poverty headcount ratio) (poverty headcount ratio) Surveys 1990­99b Surveys 2000­07b Surveys 1990­99b Surveys 2000­07b Surveys 1990­99b Surveys 2000­07b Year Percent Year Percent Year Percent Year Percent Year Percent Year Percent .. .. .. .. .. .. 1999 29.0 2003 39.0 1999 23.3 2003 29.0 1999 33.0 2003 46.0 .. .. .. .. .. .. 1998 54.6 2003 46.4 1998 22.4 2003 19.2 1998 61.1 2003 52.4 1998 68.0 .. 1998 66.5 .. 1998 64.6 .. 1996 53.3 2007 39.9 1996 41.4 2007 12.2 1996 59.6 2007 55.0 .. .. .. .. .. .. .. .. .. .. .. .. 1996 64.0 .. 1996 63.0 .. 1996 67.0 .. .. .. .. .. .. .. .. 2004 71.3 .. 2004 61.5 .. 2004 75.7 .. 2005 42.3 .. .. .. 2005 49.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1994 53.0 .. .. .. .. .. 1996 45.5 2000 44.2 1996 33.3 2000 37.0 1996 47.0 2000 45.0 .. .. .. .. .. .. 1998 57.6 2003 61.3 1998 48.0 2003 57.0 1998 61.0 2003 63.0 1997 39.5 2005 28.5 1997 19.4 2005 10.8 1997 49.6 2005 39.2 1994 40.0 .. .. .. .. .. .. 2002 65.7 .. 2002 52.6 .. .. 1997 52.3 2005 45.9 1997 49.2 2005 33.7 1997 52.9 2005 49.1 1994 66.6 2002 56.3 1994 36.7 2002 41.5 1994 68.9 2002 60.5 .. 2007 63.8 .. 2007 55.1 .. 2007 67.7 1999 71.3 2005 68.7 1999 52.1 2005 52.0 1999 76.7 2005 68.7 1998 65.3 2004 52.4 1998 54.9 2004 25.4 1998 66.5 2004 55.9 1998 63.8 .. 1998 30.1 .. 1998 75.9 .. 1996 50.0 2000 46.3 1996 30.1 2000 25.4 1996 65.5 2000 61.2 1992 10.6 .. .. .. .. .. 1996 69.4 2002 54.1 1996 62.0 2002 51.5 1996 71.3 2002 55.3 .. .. .. .. .. .. 1993 63.0 .. 1993 52.0 .. 1993 66.0 .. 1992 34.1 2003 54.7 1992 30.4 2003 43.1 1992 36.4 2003 63.8 1993 51.2 2005 56.9 .. 2005 13.0e .. 2005 62.5 .. .. .. .. .. .. 1992 33.4 .. 1992 23.7 .. 1992 40.4 .. .. .. .. .. .. .. .. 2003 65.9 .. 2003 56.4 .. 2003 78.5 .. .. .. .. .. .. 1995 31.0 2008 22.0 .. .. .. .. .. .. .. .. .. .. .. 2001 69.2 .. 2001 49.0 .. 2001 75.0 1991 38.6 2007 33.6 1991 28.1f 2007 16.4f 1991 40.8 2007 37.6 .. .. .. .. .. .. 1999 33.8 2005 31.1 1999 9.6 2005 13.4 1999 37.4 2005 34.2 1998 72.9 2006 59.3 1998 56.0 2006 26.7 1998 83.1 2006 76.8 1996 34.9 .. 1996 7.9 .. 1996 48.0 .. 1995 22.6 .. 1995 14.7 .. 1995 30.3 .. 1996 22.9 2000 16.7 1996 22.5 .. 1996 23.3 .. .. .. .. .. .. .. 1999 19.0 .. 1999 12.0 .. 1999 27.2 .. 1995 7.6 .. 1995 3.6 .. 1995 13.9 .. (continued) MILLENNIUM DEVELOPMENT GOALS Part II. Millennium Development Goals 77 Table 3.1 Millennium Development Goal 1: eradicate extreme poverty and hunger (continued) Population below Share of poorest quintile in national Prevalence of child malnutrition, underweight minimum dietary consumption or incomea (% of children under age 5) energy consumption Surveys 1990­99b Surveys 2000­07b Surveys 1990­99b Surveys 2000­08b Share (%) Total (millions) Year Percent Year Percent Year Percent Year Percent 2004­06c 2004­06c SUB­SAHARAN AFRICA Angola .. 2000 2.0 1996 37.0 2001 27.5 44 7.1 Benin .. 2003 6.9 .. 2001 21.5 19 1.6 Botswana 1995 3.1 .. .. 2000 10.7 26 0.5 Burkina Faso 1998 6.1 2003 7.0 1999 33.7 2003 35.2 9 1.3 Burundi 1998 5.1 2006 9.0 .. 2000 38.9 63 4.9 Cameroon 1996 5.7 2001 5.6 1998 17.8 2004 15.1 23 4.0 Cape Verde .. 2001 4.5 .. .. 14 0.1 Central African Republic 1993 2.0 2003 5.2 1995 23.3 2000 21.8 41 1.7 Chad .. 2003 6.3 1997 34.3 2004 33.9 38 3.9 Comoros .. 2004 2.6 1996 22.3 2000 25.0 51 0.4 Congo, Dem. Rep. .. 2006 5.5 .. 2001 33.6 75 43.9 Congo, Rep. .. 2005 5.0 .. 2005 11.8 21 0.8 Côte d'Ivoire 1998 5.8 2002 5.0 1999 18.2 2006 16.7 14 2.5 Djibouti 1996 6.4 2002 6.0 .. .. 31 0.2 Equatorial Guinea .. .. .. 2004 10.6 .. .. Eritrea .. .. 1996 38.3 2002 34.5 66 3.0 Ethiopia 1995 7.2 2005 9.3 .. 2005 34.6 44 34.6 Gabon .. 2005 6.1 .. 2001 8.8 d .. Gambia, The 1998 4.0 2003 4.8 .. 2006 15.8 29 0.5 Ghana 1998 5.6 2006 5.2 1999 20.3 2008 13.9 8 1.7 Guinea 1994 6.4 2003 5.8 1999 21.2 2005 22.5 16 1.5 Guinea-Bissau 1993 5.2 2002 7.2 .. 2000 21.9 31 0.5 Kenya 1997 6.0 2005 4.7 1998 17.6 2003 16.5 30 10.8 Lesotho 1995 1.5 2003 3.0 .. 2005 16.6 15 0.3 Liberia .. 2007 6.4 .. 2007 20.4 38 1.3 Madagascar 1999 5.9 2005 6.2 1997 35.5 2004 36.8 35 6.6 Malawi 1998 4.8 2004 7.0 1992 24.4 2005 18.4 29 3.8 Mali 1994 4.6 2006 6.5 1996 38.2 2006 27.9 10 1.2 Mauritania 1996 6.4 2000 6.2 .. 2001 30.4 8 0.2 Mauritius .. .. .. .. 6 0.1 Mozambique 1997 5.6 2003 5.4 1997 28.1 2003 21.2 37 7.5 Namibia 1993 1.5 .. 1992 21.5 2007 17.5 19 0.4 Niger 1994 6.0 2005 5.9 1998 45.0 2006 39.9 28 3.8 Nigeria 1996 5.1 2004 5.1 1990 35.1 2003 27.2 8 11.3 Rwanda .. 2000 5.3 1992 24.3 2005 18.0 40 3.7 São Tomé and Príncipe .. .. .. 2000 10.1 5 0.0 Senegal 1995 6.5 2005 6.2 1993 21.9 2005 14.5 25 2.9 Seychelles .. .. .. .. 8 0.0 Sierra Leone 1990 1.1 2003 6.1 .. 2005 28.3 46 2.5 Somalia .. .. .. 2006 32.8 .. .. South Africa 1995 3.6 2000 3.1 .. .. d .. Sudan .. .. .. 2000 38.4 20 7.5 Swaziland 1995 2.7 2001 4.5 .. 2000 9.1 18 0.2 Tanzania 1992 7.4 2000 7.3 1999 25.3 2005 16.7 35 13.6 Togo .. 2006 7.6 1998 23.2 .. 37 2.3 Uganda 1999 6.0 2005 6.1 1995 21.5 2001 19.0 15 4.4 Zambia 1998 3.4 2004 3.6 1997 19.6 2002 23.3 45 5.2 Zimbabwe 1995 4.6 .. 1999 11.5 2006 14.0 39 5.1 NORTH AFRICA Algeria 1995 6.9 .. 1995 11.3 2002 10.2 d .. Egypt, Arab Rep. 1996 9.5 2005 9.0 1996 10.8 2005 5.4 d .. Libya .. .. 1995 4.3 .. d .. Morocco 1999 6.4 2007 6.5 1992 8.1 2004 9.9 d .. Tunisia 1995 5.6 2000 5.9 .. .. d .. a. Data are based on expenditure shares, except for Namibia, for which data are based on income shares. b. Data are for the most recent year available during the period specified. c. Average over the period. d. Less than 5 percent. e. Refers to Kigali only. f. Refers to Dar es Salaam only. 78 Part II. Millennium Development Goals MILLENNIUM DEVELOPMENT GOALS 3.2 Table Millennium Development Goal 2: achieve universal primary education Net primary enrollment ratio Primary completion rate Share of cohort reaching grade 5 Youth literacy rate (% of relevant age group) (% of relevant age group) (% of grade 1 students) (% of ages 15­24) 1991 2000 2007­08a 1991 2000 2007­08a 1991 2000 2001­07a 1991 2000 2007 SUB­SAHARAN AFRICA Angola 50.3 .. .. 34.7 .. .. .. .. .. .. .. .. Benin 41.1 51.8 .. 20.7 34.9 .. 54.8 84.0 71.5 .. .. 52.4 Botswana 88.3 81.6 .. 89.5 89.9 .. 84.0 89.5 82.5 89.3 .. 94.1 Burkina Faso 27.0 35.4 58.1 19.5 25.0 37.1 69.7 69.1 79.6 20.2 .. 39.3 Burundi 53.0 42.6 81.2 45.9 24.9 39.2 61.7 56.1 66.2 .. 73.3 .. Cameroon 69.4 .. .. 53.0 49.9 55.5 .. .. 84.3 .. .. .. Cape Verde 91.1 97.7 84.5 .. 101.8 86.2 .. .. 92.2 .. .. 97.3 Central African Republic 51.8 .. 56.2 26.7 .. 30.5 23.0 .. 59.5 .. 58.5 .. Chad 33.9 53.1 .. 17.9 22.3 30.4 50.5 53.9 37.7 .. 37.6 44.4 Comoros 56.7 55.1 .. .. .. .. .. .. 80.3 .. .. 89.5 Congo, Dem. Rep. 53.9 .. .. 45.9 .. 50.7 54.7 .. .. .. .. .. Congo, Rep. 81.9 .. 53.8 54.3 .. 72.3 60.1 .. 66.3 .. .. .. Côte d'Ivoire 44.6 52.2 .. 43.4 39.1 44.7 72.5 87.6 78.3 .. 60.7 .. Djibouti 28.5 26.9 45.3 26.9 28.0 .. 87.3 .. 89.9 .. .. .. Equatorial Guinea 96.2 90.7 67.1 .. .. 66.7 .. .. 32.6 .. 94.9 .. Eritrea 14.7 37.8 41.2 .. 36.4 46.4 .. 60.5 59.9 .. .. .. Ethiopia 21.9 38.4 71.4 .. 21.6 46.3 18.3 64.6 64.4 .. .. .. Gabon 93.9 .. .. .. .. .. .. .. 69.3 .. .. 97.0 Gambia, The 46.4 68.5 66.5 .. 73.9 69.0 .. 98.7 73.0 .. .. .. Ghana 53.6 60.2 72.9 61.2 .. 77.7 80.5 66.2 88.6 .. 70.7 77.8 Guinea 27.4 47.9 73.6 17.4 32.8 64.2 58.6 .. 82.8 .. .. .. Guinea-Bissau 37.9 45.2 .. .. 26.9 .. .. .. .. .. .. .. Kenya .. 66.2 86.3 .. .. .. .. .. 82.9 .. 80.3 .. Lesotho 72.0 77.7 .. 58.9 60.1 .. 65.9 66.7 73.7 .. .. .. Liberia .. 66.2 30.9 .. .. 54.7 .. .. .. .. .. 71.8 Madagascar 64.3 64.6 98.5 33.3 35.5 61.5 21.1 .. 42.3 .. 70.2 .. Malawi 48.5 .. 87.0 28.7 65.7 55.4 64.4 51.9 43.4 .. .. 83.0 Mali 24.6 .. 63.0 12.6 32.8 52.2 69.7 91.7 81.2 .. .. .. Mauritania 36.4 64.5 80.4 34.1 52.6 59.4 75.3 59.6 63.7 .. 61.3 66.4 Mauritius 91.3 92.9 95.4 106.6 104.6 93.5 97.4 99.3 99.0 .. 94.5 96.2 Mozambique 42.1 56.1 .. 26.4 16.1 46.3 34.2 51.9 64.0 .. .. 52.9 Namibia 85.9 81.2 86.5 .. 84.9 77.1 62.3 94.2 97.8 88.1 .. 92.7 Niger 24.1 27.2 44.9 17.6 18.4 39.6 62.4 74.0 72.0 .. .. .. Nigeria 55.2 60.8 .. .. .. .. 89.1 .. 82.9 71.2 .. 86.7 Rwanda 66.9 .. 93.6 35.4 20.7 .. 59.9 39.1 45.8 74.9 77.6 .. São Tomé and Príncipe 95.6 .. 97.1 .. .. 75.6 .. .. 78.7 93.8 .. 95.2 Senegal 45.3 56.5 71.9 .. 37.7 50.1 84.5 72.3 65.0 .. .. .. Seychelles .. .. .. .. 112.9 113.9 .. 91.0 98.7 .. .. .. Sierra Leone 43.1 .. .. .. .. 80.8 .. .. .. .. .. 54.1 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 90.2 91.7 85.8 75.8 90.1 84.5 .. .. 82.4 .. .. 95.4 Sudan .. 41.2 .. 42.0 37.5 50.0 93.8 .. 70.5 .. 77.2 .. Swaziland 74.8 75.4 87.0 59.9 64.3 74.6 77.0 73.9 82.1 .. 88.4 .. Tanzania 50.5 53.4 .. 62.4 .. 111.7 81.3 81.4 87.2 .. .. 77.5 Togo 64.0 76.5 77.2 34.9 61.0 57.4 48.0 73.8 54.3 .. 74.4 .. Uganda 51.1 .. 94.6 .. .. .. 36.0 56.7 48.7 69.8 .. 86.3 Zambia 78.0 67.2 94.0 .. 60.1 88.1 .. .. 89.0 .. .. 75.1 Zimbabwe 84.1 83.5 .. 97.2 .. .. 76.1 .. 69.7 .. .. 91.2 NORTH AFRICA Algeria 88.9 91.6 95.4 79.5 82.6 95.1 94.5 97.2 96.0 .. .. 92.5 Egypt, Arab Rep. 86.2 93.4 95.7 .. 98.1 98.5 .. 99.0 96.8 .. .. .. Libya .. .. .. .. .. .. .. .. .. .. .. 98.9 Morocco 56.1 75.8 88.8 48.1 56.7 83.4 75.1 80.1 83.9 .. .. 75.1 Tunisia 93.5 93.8 95.0 74.2 86.7 99.9 86.4 93.1 96.4 .. .. 95.7 a. Data are for the most recent year available during the period specified. MILLENNIUM DEVELOPMENT GOALS Part II. Millennium Development Goals 79 Table 3.3 Millennium Development Goal 3: promote gender equity and empower women Ratio of girls to boys in primary Ratio of literate young Women in Share of women employed in and secondary school women to men national parliament the nonagricultural sector (%) (% of ages 15­24) (% of total seats) (%) 1991 2000 2007­08a 1990 2000 2007 1990 2000 2008 1990 2000 2000­08a SUB­SAHARAN AFRICA Angola .. .. .. .. .. .. 15.0 16.0 37.3 .. .. .. Benin 49.5 64.2 .. .. .. 64.9 3.0 6.0 10.8 .. .. 24.3 Botswana 108.7 101.6 .. 107.4 .. 102.6 5.0 .. 11.1 33.5 39.4 42.4 Burkina Faso 62.3 70.0 84.0 52.9 .. 70.9 .. 8.0 15.3 12.5 .. .. Burundi 81.8 .. 90.0 .. 91.6 .. .. 6.0 30.5 14.3 .. .. Cameroon 83.0 .. 84.5 .. .. .. 14.0 6.0 13.9 .. .. .. Cape Verde .. .. 103.8 .. .. 101.4 12.0 11.0 18.1 .. 38.9 38.9 Central African Republic 59.8 .. .. .. 66.6 .. 4.0 7.0 10.5 .. .. 46.8 Chad 41.6 55.9 64.3 .. 41.7 66.4 .. 2.0 5.2 3.8 .. .. Comoros 71.1 84.1 .. .. .. 94.2 0.0 .. 3.0 .. .. .. Congo, Dem. Rep. .. .. 73.4 .. .. .. 5.0 .. 8.4 25.9 .. .. Congo, Rep. 85.1 84.5 .. .. .. .. 14.0 12.0 7.3 26.1 .. .. Côte d'Ivoire 65.3 69.1 .. .. 73.6 .. 6.0 .. 8.9 .. .. .. Djibouti 70.5 71.0 80.0 .. .. .. 0.0 0.0 13.8 .. .. 26.7 Equatorial Guinea .. 86.3 .. .. 100.2 .. 13.0 5.0 6.0 10.5 .. .. Eritrea .. 77.4 77.8 .. .. .. .. 15.0 22.0 .. .. .. Ethiopia 68.4 65.1 82.6 .. .. .. .. 2.0 21.9 .. .. 47.3 Gabon .. 95.8 .. .. .. 97.9 13.0 8.0 16.7 .. .. .. Gambia, The 65.6 83.0 103.4 .. .. .. 8.0 2.0 9.4 20.9 .. .. Ghana 78.5 89.4 95.4 .. 86.2 95.1 .. 9.0 10.9 .. 31.7 31.7 Guinea 44.9 61.3 76.1 .. .. .. .. 9.0 19.3 .. .. .. Guinea-Bissau .. 65.0 .. .. .. .. 20.0 .. 14.0 10.8 .. .. Kenya 93.6 97.6 95.2 .. 101.1 .. 1.0 4.0 8.9 21.4 .. .. Lesotho 123.5 107.2 .. .. .. .. .. 4.0 25.0 .. .. .. Liberia .. 72.7 .. .. .. 111.6 .. .. 12.5 .. .. 11.4 Madagascar 97.5 .. 96.5 .. 93.9 .. 7.0 8.0 7.9 .. 35.6 37.7 Malawi 81.3 92.6 99.8 .. .. 98.3 10.0 8.0 13.0 10.5 .. .. Mali 57.1 68.5 76.0 .. .. .. .. 12.0 10.2 .. .. 34.6 Mauritania 71.3 95.0 102.6 .. 81.9 89.3 .. 4.0 22.1 .. 35.8 35.8 Mauritius 101.6 98.2 .. .. 101.7 102.0 7.0 8.0 17.1 36.7 38.6 37.5 Mozambique 71.5 74.9 85.4 .. .. 81.2 16.0 .. 34.8 11.4 .. .. Namibia 106.4 103.2 103.8 105.5 .. 103.8 7.0 22.0 26.9 .. 48.8 46.8 Niger 53.3 65.8 71.5 .. .. .. 5.0 1.0 12.4 11.0 .. .. Nigeria 77.2 80.1 .. 76.8 .. 95.7 .. .. 7.0 .. 18.6 21.1 Rwanda 92.1 96.1 100.2 .. 97.9 .. 17.0 17.0 56.3 .. 33.0 33.0 São Tomé and Príncipe .. .. 100.0 95.9 .. 100.5 12.0 9.0 1.8 .. 34.8 37.7 Senegal 68.8 82.0 93.6 .. .. .. 13.0 12.0 22.0 .. .. 10.6 Seychelles .. 101.4 105.6 .. .. .. 16.0 24.0 23.5 .. .. .. Sierra Leone 66.8 .. 86.4 .. .. 68.1 .. 9.0 13.2 .. .. 23.2 Somalia .. .. .. .. .. .. 4.0 .. 8.2 21.7 .. .. South Africa 103.9 100.4 99.8 .. .. 101.8 3.0 30.0 33.0 .. .. 43.1 Sudan 77.5 .. 87.6 .. 84.4 .. .. .. 18.1 22.2 .. .. Swaziland 97.7 95.4 91.7 .. 103.2 .. 4.0 3.0 .. .. .. .. Tanzania 96.7 .. .. .. .. 96.5 .. 16.0 30.4 .. .. 29.3 Togo 58.9 69.1 75.2 .. 76.0 .. 5.0 .. 11.1 41.0 .. .. Uganda 81.7 92.8 98.5 81.7 .. 95.4 12.0 18.0 30.7 .. .. 39.0 Zambia .. 91.3 95.6 .. .. 82.3 7.0 10.0 15.2 .. 33.7 33.7 Zimbabwe 92.1 94.5 .. .. .. 93.9 11.0 14.0 15.2 15.4 20.4 21.9 NORTH AFRICA Algeria 82.9 .. .. .. .. 96.2 2.0 3.0 7.7 .. 13.0 17.0 Egypt, Arab Rep. 81.4 92.4 .. .. .. .. 4.0 2.0 1.8 20.5 18.6 20.7 Libya .. .. .. .. .. 98.3 .. .. 7.7 .. .. 15.8 Morocco 69.6 82.4 88.1 .. .. 79.3 0.0 1.0 10.5 28.7 26.2 28.2 Tunisia 86.1 100.0 .. .. .. 97.2 4.0 12.0 22.8 .. 24.6 25.3 a. Data are for the most recent year available during the period specified. 80 Part II. Millennium Development Goals MILLENNIUM DEVELOPMENT GOALS 3.4 Table Millennium Development Goal 4: reduce child mortality Under-five mortality rate Infant mortality rate Child immunization rate, measles (per 1,000) (per 1,000 live births) (% of children ages 12­23 months) 1990 2000 2007 1990 2000 2007 1990 2000 2007 SUB­SAHARAN AFRICA Angola 258 158 158 150 116 116 38 88 88 Benin 184 123 123 111 78 78 79 61 61 Botswana 57 40 40 45 33 33 87 90 90 Burkina Faso 206 191 191 112 104 104 79 94 94 Burundi 189 180 180 113 108 108 74 75 75 Cameroon 139 148 148 85 87 87 56 74 74 Cape Verde 60 32 32 45 24 24 79 74 74 Central African Republic 171 172 172 113 113 113 82 62 62 Chad 201 209 209 120 124 124 32 23 23 Comoros 120 66 66 88 49 49 87 65 65 Congo, Dem. Rep. 200 161 161 127 108 108 38 79 79 Congo, Rep. 104 125 125 67 79 79 75 67 67 Côte d'Ivoire 151 127 127 104 89 89 56 67 67 Djibouti 175 127 127 116 84 84 85 74 74 Equatorial Guinea 170 206 206 103 124 124 88 51 51 Eritrea 147 70 70 88 46 46 .. 95 95 Ethiopia 204 119 119 122 75 75 38 65 65 Gabon 92 91 91 60 60 60 76 55 55 Gambia, The 153 109 109 104 82 82 86 85 85 Ghana 120 115 115 76 73 73 61 95 95 Guinea 231 150 150 137 93 93 35 71 71 Guinea-Bissau 240 198 198 142 118 118 53 76 76 Kenya 97 121 121 64 80 80 78 80 80 Lesotho 102 84 84 81 68 68 80 85 85 Liberia 205 133 133 138 93 93 .. 95 95 Madagascar 168 112 112 103 70 70 47 81 81 Malawi 209 111 111 124 71 71 81 83 83 Mali 250 196 196 148 117 117 43 68 68 Mauritania 130 119 119 81 75 75 38 67 67 Mauritius 24 15 15 20 13 13 76 98 98 Mozambique 201 168 168 135 115 115 59 77 77 Namibia 87 68 68 57 47 47 .. 69 69 Niger 304 176 176 143 83 83 25 47 47 Nigeria 230 189 189 120 97 97 54 62 62 Rwanda 195 181 181 117 109 109 83 99 99 São Tomé and Príncipe 101 99 99 65 64 64 71 86 86 Senegal 149 114 114 72 59 59 51 84 84 Seychelles 19 13 13 17 12 12 86 99 99 Sierra Leone 290 262 262 169 155 155 .. 67 67 Somalia 203 142 142 121 88 88 30 34 34 South Africa 64 59 59 49 46 46 79 83 83 Sudan 125 109 109 79 69 69 57 79 79 Swaziland 96 91 91 70 66 66 85 91 91 Tanzania 157 116 116 96 73 73 80 90 90 Togo 150 100 100 89 65 65 73 80 80 Uganda 175 130 130 106 82 82 52 68 68 Zambia 163 170 170 99 103 103 90 85 85 Zimbabwe 95 90 90 62 59 59 87 66 66 NORTH AFRICA Algeria 69 37 37 54 33 33 83 92 92 Egypt, Arab Rep. 93 36 36 68 30 30 86 97 97 Libya 41 18 18 35 17 17 89 98 98 Morocco 89 34 34 69 32 32 79 95 95 Tunisia 52 21 21 41 18 18 93 98 98 MILLENNIUM DEVELOPMENT GOALS Part II. Millennium Development Goals 81 Table 3.5 Millennium Development Goal 5: improve maternal health Maternal mortality ratio Births attended by skilled health staff (per 100,000 live births) (% of total) Modeled estimate National estimate Surveys 1990­99a Surveys 2000­08a 2005 2000­07a Year Percent Year Percent SUB­SAHARAN AFRICA Angola 1,400 .. 1996 22.5 2007 47.3 Benin 840 397 1996 59.8 2006 77.7 Botswana 380 .. 1996 87.0 2000 94.2 Burkina Faso 700 .. 1999 30.9 2006 53.5 Burundi 1,100 615 .. 2005 33.6 Cameroon 1,000 669 1998 58.2 2006 63.0 Cape Verde 210 15 1998 88.5 2005 77.5 Central African Republic 980 543 1995 45.9 2006 53.4 Chad 1,500 1,099 1997 15.0 2004 14.4 Comoros 400 380 1996 51.6 2000 61.8 Congo, Dem. Rep. 1,100 1,289 .. 2007 74.0 Congo, Rep. 740 781 .. 2005 83.4 Côte d'Ivoire 810 543 1999 47.1 2006 56.8 Djibouti 650 .. .. 2003 60.6 Equatorial Guinea 680 .. 1994 5.0 2000 64.6 Eritrea 450 .. 1995 20.6 2002 28.3 Ethiopia 720 673 .. 2005 5.7 Gabon 520 519 .. 2000 85.5 Gambia, The 690 730 1990 44.1 2006 56.8 Ghana 560 .. 1998 44.3 2006 49.7 Guinea 910 980 1999 34.8 2005 38.0 Guinea-Bissau 1,100 405 1993 25.0 2006 38.8 Kenya 560 414 1998 44.3 2003 41.6 Lesotho 960 762 1993 60.9 2004 55.4 Liberia 1,200 .. .. 2007 46.4 Madagascar 510 469 1997 47.3 2004 51.3 Malawi 1,100 807 1992 54.8 2006 53.6 Mali 970 464 1996 40.0 2006 49.0 Mauritania 820 747 1991 40.0 2007 60.9 Mauritius 15 22 1999 98.5 2003 98.4 Mozambique 520 408 1997 44.2 2003 47.7 Namibia 210 271 1992 68.2 2006 81.4 Niger 1,800 648 1998 17.6 2006 32.9 Nigeria 1,100 .. 1999 41.6 2003 35.2 Rwanda 1,300 750 1992 25.8 2008 52.1 São Tomé and Príncipe .. 148 .. 2006 80.7 Senegal 980 401 1999 48.3 2005 51.9 Seychelles .. 57 .. .. Sierra Leone 2,100 1,800 .. 2005 43.2 Somalia 1,400 1,044 1999 34.2 2006 33.0 South Africa 400 166 1998 84.4 2003 92.0 Sudan 450 .. 1991 86.3 2006 49.2 Swaziland 390 589 1994 56.0 2007 69.0 Tanzania 950 578 1999 35.8 2005 43.4 Togo 510 .. 1998 50.5 2006 62.0 Uganda 550 435 1995 37.8 2006 42.1 Zambia 830 729 1999 47.1 2007 46.5 Zimbabwe 880 555 1999 72.5 2006 68.5 NORTH AFRICA Algeria 180 .. 1992 77.0 2006 95.2 Egypt, Arab Rep. 130 84 1998 55.2 2008 78.9 Libya 97 .. 1995 94.4 .. Morocco 240 227 1995 39.6 2004 62.6 Tunisia 100 .. 1995 80.5 2000 89.9 a. Data are for the most recent year available during the period specified. 82 Part II. Millennium Development Goals MILLENNIUM DEVELOPMENT GOALS 3.6 Table Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases Children sleeping under Contraceptive use, any method insecticide-treated nets Prevalence of HIV (% of married women ages 15­49) (% of children under age 5) (% of ages 15­49) Surveys 1990­99a Surveys 2000­08a Surveys 2000­08a 1990 2007 Year Percent Year Percent Year Percent SUB­SAHARAN AFRICA Angola 0.3 2.1 1996 8.1 2001 6.2 2006 17.7 Benin 0.1 1.2 1996 16.4 2006 17.0 2006 20.2 Botswana 4.7 23.9 1996 47.6 2000 44.4 .. Burkina Faso 1.9 1.6 1999 11.9 2006 17.4 2006 9.6 Burundi 1.7 2.0 .. 2002 19.7 2005 8.3 Cameroon 0.8 5.1 1998 19.3 2006 29.2 2006 13.1 Cape Verde .. .. 1998 52.9 2005 61.3 .. Central African Republic 1.8 6.3 1995 14.8 2006 19.0 2006 15.1 Chad 0.7 3.5 1997 4.1 2004 2.8 .. Comoros <0.1 <0.1 1996 21.0 2000 25.7 2000 9.3 Congo, Dem. Rep. .. .. 1991 7.7 2007 20.6 2007 5.8 Congo, Rep. 5.1 3.5 .. 2005 44.3 2005 6.1 Côte d'Ivoire 2.2 3.9 1999 15.0 2006 12.9 2006 5.9 Djibouti 0.2 3.1 .. 2006 17.8 2006 1.3 Equatorial Guinea 1.0 3.4 .. 2000 10.1 2000 0.7 Eritrea 0.1 1.3 1995 8.0 2002 8.0 2002 4.2 Ethiopia 0.7 2.1 1997 3.3 2005 14.7 2007 33.1 Gabon 0.9 5.9 .. 2000 32.7 .. Gambia, The .. 0.9 1990 11.8 2001 17.5 2006 49.0 Ghana 0.1 1.9 1999 22.0 2008 23.5 2008 28.2 Guinea 0.2 1.6 1999 6.2 2005 9.1 2005 0.3 Guinea-Bissau 0.2 1.8 .. 2006 10.3 2006 39.0 Kenya .. .. 1998 39.0 2003 39.3 2003 6.0 Lesotho 0.8 23.2 1992 23.2 2004 37.3 .. Liberia 0.4 1.7 .. 2007 11.4 2005 3.0 Madagascar .. 0.1 1999 25.0 2004 27.1 2000 0.2 Malawi 2.1 11.9 1996 21.9 2006 41.0 2006 23.0 Mali 0.2 1.5 1996 6.7 2006 8.2 2006 27.1 Mauritania <0.1 0.8 1992 4.1 2007 9.3 2003 2.1 Mauritius <0.1 1.7 1991 74.6 2002 75.8 .. Mozambique 1.4 12.5 1997 5.6 2004 16.5 2008 22.8 Namibia 1.2 15.3 1992 28.9 2007 55.1 .. Niger 0.1 0.8 1998 8.2 2006 11.2 2006 7.4 Nigeria 0.7 3.1 1999 15.3 2007 14.7 2003 1.2 Rwanda 9.2 2.8 1996 13.7 2008 36.4 2008 24.0 São Tomé and Príncipe .. .. .. 2000 29.3 2007 54.0 Senegal 0.1 1.0 1999 10.5 2005 11.8 2008 31.0 Seychelles .. .. .. .. .. Sierra Leone 0.2 1.7 1992 2.6 2008 8.2 2008 25.9 Somalia <0.1 0.5 1999 7.9 2006 14.6 2006 9.2 South Africa 0.8 18.1 1998 56.3 2003 60.3 .. Sudan 0.8 1.4 1999 7.0 2006 7.6 2006 27.6 Swaziland 0.9 26.1 .. 2007 50.6 2006 0.6 Tanzania 4.8 6.2 1999 25.4 2005 26.4 2007 25.7 Togo 0.7 3.3 1998 23.5 2006 16.8 2006 38.4 Uganda 13.7 5.4 1995 14.8 2006 23.7 2006 9.7 Zambia 8.9 15.2 1999 22.0 2007 40.8 2008 41.1 Zimbabwe 14.2 15.3 1999 53.5 2006 60.2 2005 2.9 NORTH AFRICA Algeria .. 0.1 1995 56.9 2006 61.4 .. Egypt, Arab Rep. .. .. 1998 51.7 2008 60.3 .. Libya .. .. 1995 45.2 .. .. Morocco .. 0.1 1997 58.4 2004 63.0 .. Tunisia .. 0.1 1995 60.0 2006 60.2 .. (continued) MILLENNIUM DEVELOPMENT GOALS Part II. Millennium Development Goals 83 Table 3.6 Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases (continued) Tuberculosis cases detected under DOTS Incidence of tuberculosis (% of estimated cases) (per 100,000 people) Surveys 1990­99a Surveys 2000­07a 1999 2007 Year Percent Year Percent SUB-SAHARAN AFRICA Angola 245.0 286.5 1999 50.7 2007 101.8 Benin 83.8 90.9 1999 85.8 2006 86.0 Botswana 587.7 731.4 1999 71.9 2007 57.2 Burkina Faso 181.7 226.2 1999 16.0 2007 18.4 Burundi 294.9 367.0 1999 36.3 2007 26.8 Cameroon 154.0 191.7 1999 20.8 2007 91.4 Cape Verde 161.8 150.5 .. 2007 44.0 Central African Republic 277.3 345.1 1996 61.5 2006 70.8 Chad 240.0 298.7 1999 34.9 2007 18.5 Comoros 58.7 42.0 1998 54.4 2006 41.6 Congo, Dem. Rep. 314.7 391.7 1999 50.4 2007 60.7 Congo, Rep. 323.9 403.1 1998 54.6 2007 55.7 Côte d'Ivoire 337.9 420.5 1999 44.4 2007 42.2 Djibouti 694.7 812.5 1999 74.5 2007 42.3 Equatorial Guinea 205.6 255.9 1998 86.2 2004 74.9 Eritrea 83.6 95.4 1999 40.7 2007 34.5 Ethiopia 303.9 378.2 1999 24.6 2007 28.1 Gabon 210.1 406.4 .. 2007 66.2 Gambia, The 220.9 258.4 1998 72.8 2007 63.9 Ghana 212.0 202.9 1999 31.0 2007 35.9 Guinea 190.0 287.4 1999 53.2 2007 53.5 Guinea-Bissau 188.0 219.9 .. 2006 67.6 Kenya 381.9 352.6 1999 60.0 2007 72.1 Lesotho 519.1 636.6 1998 78.2 2007 16.5 Liberia 236.9 277.1 1998 43.8 2006 69.3 Madagascar 213.0 250.8 1998 67.4 2007 69.5 Malawi 417.3 345.7 1999 45.4 2007 41.4 Mali 297.4 318.9 1999 18.8 2007 22.9 Mauritania 271.6 317.7 .. 2007 39.3 Mauritius 24.7 22.4 1999 93.4 2007 68.7 Mozambique 346.6 431.3 1999 50.5 2007 49.0 Namibia 616.2 766.8 1999 85.0 2007 83.6 Niger 149.1 174.3 1999 37.2 2007 52.8 Nigeria 249.7 310.7 1999 12.3 2007 22.6 Rwanda 319.0 397.0 1999 44.0 2007 25.4 São Tomé and Príncipe 115.9 101.1 .. .. Senegal 232.2 271.5 1999 48.1 2007 48.3 Seychelles 37.1 32.4 1998 67.1 2005 62.1 Sierra Leone 355.0 573.9 1998 36.2 2007 36.9 Somalia 248.7 248.7 1999 45.6 2007 63.9 South Africa 478.8 948.2 1999 66.1 2007 78.1 Sudan 208.0 243.3 1999 27.3 2007 30.6 Swaziland 690.5 1,198.0 .. 2007 54.7 Tanzania 326.5 297.4 1999 56.0 2007 50.5 Togo 366.9 429.2 1999 11.2 2007 15.1 Uganda 324.1 329.6 1999 59.6 2007 50.9 Zambia 603.3 506.1 .. 2007 58.3 Zimbabwe 628.4 782.1 1999 49.4 2007 26.6 NORTH AFRICA Algeria 46.6 56.6 1997 132.5 2007 98.4 Egypt, Arab Rep. 28.1 21.0 1999 37.7 2007 72.2 Libya 23.0 17.2 1999 148.0 2007 161.8 Morocco 115.2 91.6 1999 91.0 2007 92.8 Tunisia 26.8 26.0 1999 93.6 2007 78.2 a. Data are for the most recent year available during the period specified. 84 Part II. Millennium Development Goals MILLENNIUM DEVELOPMENT GOALS 3.7 Table Millennium Development Goal 7: ensure environmental sustainability Nationally protected areas Forest area (% of total GDP per unit of energy use (% of total land area) land area) (2000 PPP $ per kg of oil equivalent) 1990 2000 2007 2006 1990 2000 2006 SUB­SAHARAN AFRICA Angola 48.9 47.9 47.2 10.1 5.4 4.6 6.9 Benin 30.0 24.2 20.1 23.6 3.2 4.2 3.8 Botswana 24.2 22.1 20.7 30.8 7.4 9.3 11.7 Burkina Faso 26.1 25.3 24.7 14.0 .. .. .. Burundi 11.3 7.7 5.2 6.0 .. .. .. Cameroon 52.7 48.0 44.7 8.6 5.0 4.6 5.1 Cape Verde 14.3 20.4 21.0 .. .. .. .. Central African Republic 37.2 36.8 36.4 15.2 .. .. .. Chad 10.4 9.8 9.3 9.1 .. .. .. Comoros 6.4 4.3 2.4 .. .. .. .. Congo, Dem. Rep. 62.0 59.6 58.7 8.6 1.9 0.9 1.0 Congo, Rep. 66.5 66.1 65.7 14.3 10.5 11.4 10.5 Côte d'Ivoire 32.1 32.5 32.8 12.2 5.4 4.4 4.1 Djibouti 0.2 0.2 0.2 .. .. .. .. Equatorial Guinea 66.3 60.9 57.1 16.2 .. .. .. Eritrea .. 15.6 15.3 5.0 .. 3.5 4.0 Ethiopia 16.7 13.7 12.7 18.6 1.8 1.8 2.3 Gabon 85.1 84.7 84.4 13.5 11.2 10.6 9.9 Gambia, The 44.2 46.1 47.5 .. .. .. .. Ghana 32.7 26.8 23.2 15.9 2.5 2.6 2.9 Guinea 30.1 28.1 27.1 6.1 .. .. .. Guinea-Bissau 78.8 75.4 73.0 10.2 .. .. .. Kenya 6.5 6.3 6.1 12.1 3.0 2.7 2.8 Lesotho 0.2 0.2 0.3 0.2 .. .. .. Liberia 42.1 35.9 31.5 15.8 .. .. .. Madagascar 23.5 22.4 21.9 2.6 .. .. .. Malawi 41.4 37.9 35.5 19.5 .. .. .. Mali 11.5 10.7 10.1 2.1 .. .. .. Mauritania 0.4 0.3 0.2 .. .. .. .. Mauritius 19.2 18.7 18.0 3.3 .. .. .. Mozambique 25.4 24.8 24.4 5.8 0.9 1.3 1.7 Namibia 10.6 9.8 9.1 5.2 .. 8.3 7.9 Niger 1.5 1.0 1.0 6.6 .. .. .. Nigeria 18.9 14.4 11.3 6.2 1.9 2.0 2.5 Rwanda 12.9 13.9 21.7 8.1 .. .. .. São Tomé and Príncipe 28.5 28.5 28.5 .. .. .. .. Senegal 48.6 46.2 44.6 11.2 5.8 5.5 6.2 Seychelles 87.0 87.0 87.0 8.3 .. .. .. Sierra Leone 42.5 39.8 37.9 4.1 .. .. .. Somalia 13.2 12.0 11.1 0.3 .. .. .. South Africa 7.6 7.6 7.6 6.1 3.0 3.0 3.2 Sudan 32.1 29.7 27.9 4.8 2.5 3.4 3.9 Swaziland 27.4 30.1 32.0 3.1 .. .. .. Tanzania 46.8 42.1 38.9 38.7 2.2 2.2 2.1 Togo 12.6 8.9 6.4 11.1 2.6 2.0 2.0 Uganda 25.0 20.6 17.5 31.9 .. .. .. Zambia 66.1 60.1 55.9 40.4 1.8 1.7 1.9 Zimbabwe 57.5 49.4 43.7 14.8 .. .. .. NORTH AFRICA Algeria 0.8 0.9 1.0 5.0 6.6 6.3 6.6 Egypt, Arab Rep. 0.0 0.1 0.1 5.3 5.8 6.1 5.7 Libya 0.1 0.1 0.1 0.1 .. 3.7 4.4 Morocco 9.6 9.7 9.8 1.1 9.3 8.0 8.3 Tunisia 4.1 6.2 7.0 1.5 6.4 6.9 7.8 (continued) MILLENNIUM DEVELOPMENT GOALS Part II. Millennium Development Goals 85 Table 3.7 Millennium Development Goal 7: ensure environmental sustainability (continued) Carbon dioxide emissions Population with sustainable access Population with sustainable access per capita to an improved water source to improved sanitation (metric tons) (%) (%) 1990 2000 2006 1990 2000 2006 1990 2000 2006 SUB­SAHARAN AFRICA Angola 0.4 0.7 0.6 39 44 51 26 40 50 Benin 0.1 0.2 0.4 63 64 65 12 24 30 Botswana 1.6 2.5 2.6 93 95 96 38 45 47 Burkina Faso 0.1 0.1 0.1 34 56 72 5 9 13 Burundi 0.1 0.0 0.0 70 71 71 44 42 41 Cameroon 0.1 0.2 0.2 49 63 70 39 47 51 Cape Verde 0.2 0.4 0.6 .. 80 .. .. 41 .. Central African Republic 0.1 0.1 0.1 58 63 66 11 22 31 Chad 0.0 0.0 0.0 .. 34 48 5 7 9 Comoros 0.2 0.2 0.1 93 88 85 18 29 35 Congo, Dem. Rep. 0.1 0.0 0.0 43 45 46 15 25 31 Congo, Rep. 0.5 0.3 0.4 .. 70 71 .. 20 20 Côte d'Ivoire 0.5 0.4 0.3 67 75 81 20 22 24 Djibouti 0.7 0.6 0.6 76 83 92 .. 65 67 Equatorial Guinea 0.3 0.5 7.0 43 43 43 51 51 51 Eritrea 0.0 0.2 0.1 43 54 60 3 4 5 Ethiopia 0.1 0.1 0.1 13 29 42 4 7 11 Gabon 6.6 1.0 1.5 .. 85 87 .. 36 36 Gambia, The 0.2 0.2 0.2 .. 86 86 .. 49 52 Ghana 0.3 0.3 0.4 56 72 80 6 9 10 Guinea 0.2 0.2 0.1 45 61 70 13 16 19 Guinea-Bissau 0.2 0.2 0.2 .. 58 57 .. 30 33 Kenya 0.2 0.3 0.3 41 51 57 39 41 42 Lesotho .. .. .. .. 77 78 .. 34 36 Liberia 0.2 0.2 0.2 57 63 64 40 32 32 Madagascar 0.1 0.1 0.2 39 45 47 8 11 12 Malawi 0.1 0.1 0.1 41 63 76 46 55 60 Mali 0.1 0.1 0.0 33 51 60 35 42 45 Mauritania 1.4 0.5 0.5 37 50 60 20 22 24 Mauritius 1.4 2.3 3.1 100 100 100 94 94 94 Mozambique 0.1 0.1 0.1 36 41 42 20 27 31 Namibia 0.0 0.9 1.4 57 81 93 26 32 35 Niger 0.1 0.1 0.1 41 41 42 3 5 7 Nigeria 0.5 0.6 0.7 50 49 47 26 28 30 Rwanda 0.1 0.1 0.1 65 65 65 29 25 23 São Tomé and Príncipe 0.6 0.6 0.7 .. 82 86 .. 22 24 Senegal 0.4 0.4 0.4 67 72 77 26 27 28 Seychelles 1.6 7.0 8.8 .. 87 .. .. .. .. Sierra Leone 0.1 0.1 0.2 .. 57 53 .. 12 11 Somalia 0.0 0.1 0.0 .. 23 29 .. 21 23 South Africa 9.5 8.4 8.7 81 89 93 55 57 59 Sudan 0.2 0.2 0.3 64 69 70 33 34 35 Swaziland 0.5 1.1 0.9 .. 59 60 .. 50 50 Tanzania 0.1 0.1 0.1 49 53 55 35 34 33 Togo 0.2 0.3 0.2 49 55 59 13 12 12 Uganda 0.0 0.1 0.1 43 56 64 29 32 33 Zambia 0.3 0.2 0.2 50 54 58 42 49 52 Zimbabwe 1.6 1.2 0.9 78 80 81 44 45 46 NORTH AFRICA Algeria 3.1 3.8 4.0 94 89 85 88 92 94 Egypt, Arab Rep. 1.3 2.0 2.1 94 97 98 50 61 66 Libya 9.2 9.3 9.2 71 71 .. 97 97 97 Morocco 1.0 1.2 1.5 75 80 83 52 65 72 Tunisia 1.6 2.1 2.3 82 90 94 74 81 85 86 Part II. Millennium Development Goals MILLENNIUM DEVELOPMENT GOALS 3.8 Table Millennium Development Goal 8: develop a global partnership for development Debt sustainability Heavily Indebted Poor Countries Debt service relief Public and publicly guaranteed debt service (HIPC) Debt Initiative committed (% of exports) Decision point a Completion pointa ($ millions)a 1990 2000 2005­07b SUB­SAHARAN AFRICA Angola 7.1 20.4 10.0 Benin Jul. 2000 Mar. 2003 460 8.6 10.9 8.1 Botswana 4.3 2.0 0.9 Burkina Faso Jul. 2000 Apr. 2002 930 7.7 15.1 10.1 Burundi Aug. 2005 Jan. 2009 1,472 40.7 25.1 42.1 Cameroon Oct. 2000 Apr. 2006 4,917 12.4 13.9 5.6 Cape Verde 8.9 10.5 4.8 Central African Republic Sep. 2007 Jun. 2009 7.5 .. .. Chad May 2001 260 2.3 .. .. Comoros 2.5 .. .. Congo, Dem. Rep. Jul. 2003 Floating 10,389 .. .. .. Congo, Rep. Mar. 2006 Floating 2,881 30.8 0.5 1.2 Côte d'Ivoire Mar. 1998/Mar. 2009 14.7 14.9 1.6 Djibouti .. 4.8 12.0 Equatorial Guinea .. .. .. Eritrea .. 2.8 2.8 Ethiopia Nov. 2001 Apr. 2004 3,275 33.1 12.2 4.6 Gabon 3.8 8.8 1.4 Gambia, The Dec. 2000 Dec. 2007 90 17.9 .. 12.8 Ghana Feb. 2002 Jul. 2004 3,500 19.9 12.0 2.6 Guinea Dec. 2000 Floating 800 17.7 17.3 11.6 Guinea-Bissau Dec. 2000 Floating 790 22.0 .. 46.4 Kenya 22.7 15.7 6.0 Lesotho 4.1 10.3 6.9 Liberia Mar. 2008 .. .. 111.5 Madagascar Dec. 2000 Oct. 2004 1,900 31.9 8.4 4.9 Malawi Dec. 2000 Aug. 2006 1,000 22.4 10.8 5.8 Mali Sep. 2000 Mar. 2003 895 9.7 10.2 3.2 Mauritania Feb. 2000 Jun. 2002 1,100 24.8 .. .. Mauritius 4.5 16.3 2.5 Mozambique Apr. 2000 Sep. 2001 4,300 17.2 7.0 1.2 Namibia .. .. .. Niger Dec. 2000 Apr. 2004 1,190 3.2 6.0 9.4 Nigeria 22.3 8.2 1.4 Rwanda Dec. 2000 Apr. 2005 1,316 9.4 14.8 3.3 São Tomé and Príncipe Dec. 2000 Mar. 2007 200 28.6 21.0 37.7 Senegal Jun. 2000 Apr. 2004 850 13.7 13.2 3.3 Seychelles 7.6 3.3 8.2 Sierra Leone Mar. 2002 Dec. 2006 950 7.7 29.6 3.5 Somalia .. .. .. South Africa .. 5.5 3.3 Sudan 4.5 10.1 3.2 Swaziland 5.3 2.1 1.9 Tanzania Apr. 2000 Nov. 2001 3,000 25.1 10.8 2.1 Togo Nov. 2008 8.6 3.2 2.1 Uganda Feb. 2000 May 2000 1,950 47.1 6.5 2.4 Zambia Dec. 2000 Apr. 2005 3,900 12.6 17.4 0.9 Zimbabwe 18.2 .. .. NORTH AFRICA Algeria 63.3 .. .. Egypt, Arab Rep. 23.2 8.5 4.7 Libya .. .. .. Morocco 23.1 23.0 8.5 Tunisia 23.9 20.5 11.3 (continued) MILLENNIUM DEVELOPMENT GOALS Part II. Millennium Development Goals 87 Table 3.8 Millennium Development Goal 8: develop a global partnership for development (continued) Youth unemployment rate (ages 15­24) Information and communications Total Male Female Fixed-line and mobile (share of total (share of male (share of female telephone subscribers Personal computers Internet users labor force) labor force) labor force) (per 100 people) (per 100 people) (per 100 people) Year Percent Year Percent Year Percent 1990 2000 2008 1990 2000 2005­07a 1995 2000 2008 SUB­SAHARAN AFRICA Angola .. .. .. .. .. .. 0.7 0.6 38.2 .. 0.1 0.6 .. 0.1 3.1 Benin 2002 0.8 2002 1.1 2002 0.6 0.3 1.6 .. 0.1 0.2 0.7 .. 0.2 1.8 Botswana 2001 39.7 2001 33.9 2001 46.1 1.9 20.7 85.5 1.0 3.5 4.8 0.1 2.9 4.2 Burkina Faso .. .. .. .. .. .. 0.2 0.7 .. 0.0 0.1 0.6 .. 0.1 0.9 Burundi .. .. .. .. .. .. 0.1 0.6 6.3 .. 0.1 0.9 0.0 0.1 0.8 Cameroon .. .. .. .. .. .. 0.3 1.3 33.7 0.1 0.3 1.1 .. 0.3 .. Cape Verde .. .. .. .. .. .. 2.3 16.9 70.1 .. 5.7 14.0 .. 1.8 20.6 Central African Republic .. .. .. .. .. .. 0.2 0.4 .. .. 0.2 0.3 .. 0.1 0.4 Chad .. .. .. .. .. .. 0.1 0.2 .. .. 0.1 0.2 .. 0.0 1.2 Comoros .. .. .. .. .. .. 0.8 1.3 .. 0.0 0.6 0.9 .. 0.3 .. Congo, Dem. Rep. .. .. .. .. .. .. 0.1 0.0 14.5 .. .. 0.0 .. 0.0 0.5 Congo, Rep. .. .. .. .. .. .. 0.6 3.0 .. .. 0.4 0.6 .. 0.0 4.3 Côte d'Ivoire .. .. .. .. .. .. 0.6 4.3 52.5 .. 0.5 1.7 0.0 0.2 3.2 Djibouti .. .. .. .. .. .. 1.0 1.4 .. 0.6 0.9 2.4 0.0 0.2 .. Equatorial Guinea .. .. .. .. .. .. 0.3 2.1 .. .. 0.4 1.5 .. 0.1 1.8 Eritrea .. .. .. .. .. .. .. 0.8 3.0 .. 0.2 0.8 0.0 0.1 3.0 Ethiopia 2006 24.9 2006 19.5 2006 29.4 0.3 0.4 5.1 .. 0.1 0.7 0.0 0.0 0.4 Gabon .. .. .. .. .. .. 2.2 12.9 .. 0.6 1.0 3.4 .. 1.2 6.2 Gambia, The .. .. .. .. .. .. 0.7 3.0 73.2 0.1 1.2 3.5 0.0 0.9 6.9 Ghana 2000 16.6 2000 16.4 2000 16.7 0.3 1.8 50.2 0.1 0.3 0.6 0.0 0.2 4.3 Guinea .. .. .. .. .. .. 0.2 0.8 .. 0.1 0.3 0.5 0.0 0.1 0.9 Guinea-Bissau .. .. .. .. .. .. 0.6 0.9 32.0 .. .. 0.2 .. 0.2 2.4 Kenya .. .. .. .. .. .. 0.7 1.3 42.8 0.1 0.5 1.4 0.0 0.3 8.7 Lesotho .. .. .. .. .. .. 0.8 2.3 .. .. .. 0.3 .. 0.2 3.6 Liberia 2007 4.7 2007 5.7 2007 3.7 0.4 0.3 .. .. .. .. .. 0.0 .. Madagascar 2005 2.3 2005 1.7 2005 2.8 0.3 0.8 26.2 .. 0.2 0.6 .. 0.2 1.7 Malawi .. .. .. .. .. .. 0.3 0.8 .. .. 0.1 0.2 .. 0.1 2.2 Mali .. .. .. .. .. .. 0.1 0.5 26.4 0.0 0.1 0.8 .. 0.1 1.0 Mauritania .. .. .. .. .. .. 0.3 1.3 67.8 .. 1.0 4.6 .. 0.2 .. Mauritius 2007 24.6 2007 20.0 2007 31.3 5.5 38.8 110.2 3.2 10.1 17.6 .. 7.3 29.9 Mozambique .. .. .. .. .. .. 0.4 0.8 20.6 .. 0.3 1.4 .. 0.1 1.6 Namibia 2001 44.8 2001 40.4 2001 49.3 3.7 10.2 .. .. 4.0 24.0 0.0 1.6 5.4 Niger 2001 3.2 2001 4.0 2001 1.7 0.1 0.2 .. .. 0.0 0.1 .. 0.0 0.5 Nigeria .. .. .. .. .. .. 0.3 0.5 42.5 0.5 0.6 0.8 .. 0.1 7.3 Rwanda .. .. .. .. .. .. 0.1 0.7 13.8 .. .. 0.3 .. 0.1 3.1 São Tomé and Príncipe .. .. .. .. .. .. 1.9 3.3 .. .. .. 3.9 .. 4.6 15.4 Senegal .. .. .. .. .. .. 0.6 4.6 46.1 0.7 1.6 2.2 0.0 0.4 8.4 Seychelles 2002 20.3 .. .. .. .. 12.4 57.4 125.7 .. 13.6 21.2 .. 7.4 37.1 Sierra Leone 2004 5.2 2004 7.3 2004 3.5 0.3 0.7 .. .. .. .. 0.0 0.1 0.3 Somalia .. .. .. .. .. .. 0.2 1.5 .. .. .. 0.9 0.0 0.2 .. South Africa 2007 46.9 2007 43.0 2007 52.0 9.4 30.2 .. 2.8 6.6 8.5 0.7 5.5 8.6 Sudan .. .. .. .. .. .. 0.2 1.2 27.9 0.0 0.3 10.7 0.0 0.0 9.2 Swaziland .. .. .. .. .. .. 1.6 6.0 .. .. 1.1 3.7 0.0 0.9 4.1 Tanzania 2001 8.9 .. .. .. .. 0.3 0.8 30.9 .. 0.3 0.9 .. 0.1 1.2 Togo .. .. .. .. .. .. 0.3 1.8 26.1 0.3 1.9 3.1 0.0 1.9 5.4 Uganda .. .. .. .. .. .. 0.2 0.8 27.6 0.0 0.2 1.7 0.0 0.2 7.9 Zambia 2000 21.4 2000 23.1 2000 19.5 0.8 1.7 28.8 .. 0.7 1.1 0.0 0.2 5.5 Zimbabwe 2002 24.9 2002 28.2 2002 21.4 1.2 4.1 .. 0.3 1.6 6.9 0.0 0.4 11.4 NORTH AFRICA Algeria 2006 24.3 2004 42.8 2004 46.3 3.2 6.1 .. 0.3 0.7 1.1 0.0 0.5 .. Egypt, Arab Rep. 2005 34.1 2005 23.3 2005 62.2 2.8 9.8 65.4 0.4 1.1 4.6 0.0 0.6 15.4 Libya .. .. .. .. .. .. 5.0 12.1 .. .. .. 2.2 .. 0.2 .. Morocco 2007 17.6 2007 18.2 2007 16.1 1.7 13.2 82.6 0.3 1.2 3.6 0.0 0.7 33.0 Tunisia 2005 30.7 2005 31.4 2005 29.3 3.7 11.2 95.0 .. 2.2 7.5 0.0 2.7 27.1 Note: 0.0 indicates less than 1. a. As of 2009. b. Data are for the most recent year available during the period specified. 88 Part II. Millennium Development Goals MILLENNIUM DEVELOPMENT GOALS Drivers of growth 4.1 Table Doing Business indicators Starting a business Registering property Time required for each Cost Minimum capital Cost Number of procedure (% of GNI (% of GNI Number of Time required (% of property Overall ranking procedures (days) per capita) per capita) procedures (days) value) 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 SUB­SAHARAN AFRICA .. .. 10 9 48 45 118.6 197.5 180.5 152.2 7 7 91 80 10.3 10.0 Angola 170 169 8 8 68 68 196.8 151.1 39.1 29.0 7 7 334 184 11.6 11.4 Benin 172 172 7 7 31 31 196.0 155.5 347.0 290.8 4 4 120 120 11.9 11.8 Botswana 39 45 10 10 78 61 2.3 2.1 0.0 0.0 4 5 11 16 4.9 5.0 Burkina Faso 155 147 5 4 16 14 62.3 50.3 458.8 428.2 6 4 136 59 13.4 13.2 Burundi 177 176 11 11 32 32 215.0 151.6 0.0 0.0 5 5 94 94 7.7 6.3 Cameroon 167 171 13 12 37 34 137.1 121.1 188.0 182.9 5 5 93 93 17.8 17.8 Cape Verde 147 146 12 9 52 24 35.7 17.0 47.5 38.9 6 6 73 73 7.7 7.6 Central African Republic 183 183 11 8 22 22 237.6 244.9 513.9 507.1 5 5 75 75 18.6 18.6 Chad 176 178 19 19 75 75 175.0 176.7 365.1 369.3 6 6 44 44 22.7 22.7 Comoros 153 162 11 11 23 24 188.6 182.1 280.8 261.8 5 5 24 24 20.8 20.8 Congo, Dem. Rep. 182 182 13 13 155 149 435.4 391.0 0.0 0.0 8 8 57 57 9.2 9.8 Congo, Rep. 179 179 10 10 37 37 106.4 86.5 131.2 96.5 7 7 116 116 10.8 10.3 Côte d'Ivoire 163 168 10 10 40 40 135.1 133.3 215.9 204.9 6 6 62 62 13.9 13.9 Djibouti 157 163 11 11 37 37 200.2 195.1 514.0 500.5 7 7 40 40 13.2 13.2 Equatorial Guinea 169 170 20 20 136 136 101.7 100.4 15.4 12.4 6 6 23 23 6.2 6.2 Eritrea 175 175 13 13 84 84 102.2 76.5 396.7 297.0 12 12 101 101 5.2 5.2 Ethiopia 111 107 7 5 16 9 29.8 18.9 693.6 492.4 12 10 43 41 3.1 2.2 Gabon 151 158 9 9 58 58 20.3 17.8 30.2 26.5 7 7 39 39 10.5 10.5 Gambia, The 135 140 8 8 27 27 254.9 215.1 0.0 0.0 5 5 371 371 4.6 4.6 Ghana 87 92 9 8 34 33 32.7 26.4 16.6 13.4 5 5 34 34 1.2 1.1 Guinea 171 173 13 13 41 41 135.7 139.2 476.9 489.7 6 6 104 104 13.9 13.9 Guinea-Bissau 181 181 16 16 233 213 460.7 323.0 1,015.0 779.9 9 9 211 211 5.4 7.6 Kenya 84 95 12 12 30 34 39.7 36.5 0.0 0.0 8 8 64 64 4.1 4.2 Lesotho 128 130 7 7 40 40 37.8 27.0 14.5 11.9 6 6 101 101 8.2 8.0 Liberia 159 149 6 5 31 20 61.6 52.9 0.0 0.0 10 10 50 50 13.3 13.2 Madagascar 144 134 5 2 7 7 11.0 7.1 289.8 0.0 7 7 74 74 7.5 9.7 Malawi 131 132 10 10 39 39 125.9 108.0 0.0 0.0 6 6 88 88 3.3 3.2 Mali 162 156 10 7 25 15 121.5 89.2 390.4 334.6 5 5 29 29 20.3 20.0 Mauritania 161 166 9 9 19 19 33.9 34.7 422.6 450.4 4 4 49 49 5.2 5.2 Mauritius 24 17 5 5 6 6 5.0 4.1 0.0 0.0 4 4 210 26 10.7 10.7 Mozambique 140 135 10 10 26 26 22.9 19.3 122.5 0.0 8 8 42 42 12.9 11.3 Namibia 54 66 10 10 66 66 22.1 20.4 0.0 0.0 9 9 23 23 9.9 9.6 Niger 174 174 11 9 19 17 170.1 118.7 702.1 613.7 4 4 35 35 11.1 11.0 Nigeria 121 125 8 8 31 31 90.1 76.7 0.0 0.0 13 13 82 82 20.9 20.9 Rwanda 143 67 8 2 14 3 108.9 10.1 0.0 0.0 4 4 315 60 0.6 0.5 São Tomé and Príncipe 180 180 10 10 144 144 88.9 81.7 0.0 0.0 7 7 62 62 10.9 10.9 Senegal 152 157 4 4 8 8 72.7 63.7 236.2 206.9 6 6 124 124 20.6 20.6 Seychelles 105 111 9 9 38 38 8.3 7.3 0.0 0.0 4 4 33 33 7.0 7.0 Sierra Leone 156 148 6 6 17 12 145.8 118.8 0.0 0.0 7 7 86 236 12.9 12.4 Somalia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa 32 34 6 6 22 22 6.0 5.9 0.0 0.0 6 6 24 24 8.8 8.7 Sudan 149 154 10 10 39 36 50.8 36.0 0.0 0.0 6 6 9 9 3.1 3.0 Swaziland 114 115 13 13 61 61 35.1 33.9 0.6 0.5 11 11 46 46 7.1 7.1 Tanzania 126 131 12 12 29 29 41.5 36.8 0.0 0.0 9 9 73 73 4.4 4.4 Togo 166 165 13 7 53 75 251.3 205.0 559.9 514.0 5 5 295 295 13.4 13.1 Uganda 106 112 18 18 25 25 100.7 84.4 0.0 0.0 13 13 77 77 4.1 3.5 Zambia 999 90 6 6 18 18 28.6 28.4 1.5 1.3 6 6 39 39 6.6 6.6 Zimbabwe 160 159 10 10 96 96 432.7 4,999.5 0.0 0.0 4 5 30 31 25.1 10.1 NORTH AFRICA .. .. 9 9 14 14 14.3 12.5 12.9 10.7 8 8 52 51 4.9 4.8 Algeria 134 136 14 14 24 24 10.8 12.1 36.6 31.0 14 11 51 47 7.5 7.1 Egypt, Arab Rep. 116 106 6 6 7 7 18.3 16.1 2.0 0.0 7 7 72 72 0.9 0.9 Libya .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Morocco 130 128 6 6 12 12 20.0 16.1 13.1 11.8 8 8 47 47 4.9 4.9 Tunisia 73 69 10 10 11 11 7.9 5.7 0.0 0.0 4 4 39 39 6.1 6.1 (continued) PRIVATE SECTOR DEVELOPMENT Part III. Development outcomes 89 Drivers of growth Table 4.1 Doing Business indicators (continued) Protecting investors (0 least protection to Enforcing contracts Dealing with construction permits 10 most protection) Cost Number of Time required Cost Number of Time required (% of GNI Disclosure Director liability procedures (days) (% of debt) procedures (days) per capita) index index 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 SUB­SAHARAN AFRICA 39 39 669 656 48.7 48.9 17 17 266 259 2,603.9 2,148.9 5 5 3 3 Angola 46 46 1,011 1,011 44.4 44.4 12 12 328 328 831.1 597.7 5 5 6 6 Benin 42 42 825 825 64.7 64.7 15 15 410 410 303.6 254.4 6 6 1 1 Botswana 29 29 987 687 28.0 28.0 24 24 167 167 311.9 246.2 7 7 8 8 Burkina Faso 37 37 446 446 85.6 83.0 15 15 214 132 931.1 721.2 6 6 1 1 Burundi 44 44 832 832 38.6 38.6 22 22 212 212 11,303.8 7,968.2 4 4 1 1 Cameroon 43 43 800 800 46.6 46.6 15 15 426 426 1,277.2 1,242.5 6 6 1 1 Cape Verde 37 37 425 425 21.8 21.8 18 18 120 120 639.1 523.3 1 1 5 5 Central African Republic 43 43 660 660 82.0 82.0 21 21 239 239 278.9 275.2 6 6 1 1 Chad 41 41 743 743 77.4 77.4 9 9 181 181 974.7 985.9 6 6 1 1 Comoros 43 43 506 506 89.4 89.4 18 18 164 164 77.9 72.6 6 6 1 1 Congo, Dem. Rep. 43 43 645 625 151.8 151.8 14 14 322 322 1,725.8 1,485.1 3 3 3 3 Congo, Rep. 44 44 560 560 53.2 53.2 14 14 169 169 345.6 265.6 6 6 1 1 Côte d'Ivoire 33 33 770 770 41.7 41.7 21 22 628 629 243.3 230.9 6 6 1 1 Djibouti 40 40 1,225 1,225 34.0 34.0 14 14 195 195 982.8 948.3 5 5 2 2 Equatorial Guinea 40 40 553 553 18.5 18.5 18 18 201 201 159.4 128.4 6 6 1 1 Eritrea 39 39 405 405 22.6 22.6 .. .. .. .. .. .. 4 4 5 5 Ethiopia 38 37 690 620 15.2 15.2 12 12 128 128 790.7 561.3 4 4 4 4 Gabon 38 38 1,070 1,070 34.3 34.3 16 16 210 210 39.4 34.5 6 6 1 1 Gambia, The 32 32 434 434 37.9 37.9 17 17 146 146 394.0 336.4 2 2 1 1 Ghana 36 36 487 487 23.0 23.0 18 18 220 220 1,281.6 10,999.0 7 7 5 5 Guinea 50 50 276 276 45.0 45.0 32 32 255 255 243.0 249.6 6 6 1 1 Guinea-Bissau 41 41 1,140 1,140 25.0 25.0 15 15 167 167 2,628.8 2,020.0 6 6 1 1 Kenya 40 40 465 465 34.2 47.2 10 11 125 120 46.3 161.7 3 3 2 2 Lesotho 41 41 695 695 19.5 19.5 15 15 601 601 817.1 670.4 2 2 1 1 Liberia 41 41 1,280 1,280 35.0 35.0 25 24 321 77 60,988.7 28,295.9 4 4 1 1 Madagascar 38 38 871 871 42.4 42.4 16 16 178 178 764.8 630.7 5 5 6 6 Malawi 42 42 432 432 142.4 142.4 21 21 213 213 1,289.2 1,094.8 4 4 7 7 Mali 39 36 710 626 52.0 52.0 14 14 215 185 955.1 818.5 6 6 1 1 Mauritania 46 46 370 370 23.2 23.2 25 25 201 201 475.0 506.3 5 5 3 3 Mauritius 37 36 750 720 17.4 17.4 18 18 107 107 41.0 35.5 6 6 8 8 Mozambique 30 30 730 730 142.5 142.5 17 17 381 381 747.9 632.0 5 5 4 4 Namibia 33 33 270 270 35.8 35.8 12 12 139 139 181.8 124.7 5 5 5 5 Niger 39 39 545 545 59.6 59.6 17 17 265 265 2,694.0 2,355.0 6 6 1 1 Nigeria 39 39 457 457 32.0 32.0 18 18 350 350 693.4 573.4 5 5 7 7 Rwanda 24 24 310 260 78.7 78.7 14 14 210 210 607.1 456.1 2 7 5 9 São Tomé and Príncipe 43 43 1,185 1,185 50.5 50.5 13 13 255 255 740.5 631.4 3 3 1 1 Senegal 44 44 780 780 26.5 26.5 16 16 220 220 528.7 463.1 6 6 1 1 Seychelles 38 38 720 720 14.3 14.3 19 19 144 144 47.0 30.3 4 4 8 8 Sierra Leone 40 40 515 515 149.5 149.5 25 25 283 283 452.2 368.5 3 6 6 7 Somalia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa 30 30 600 600 33.2 33.2 17 17 174 174 27.5 24.5 8 8 8 8 Sudan 53 53 810 810 19.8 19.8 19 19 271 271 240.3 206.4 0 0 6 6 Swaziland 40 40 972 972 23.1 23.1 13 13 93 93 94.9 91.8 0 0 1 1 Tanzania 38 38 462 462 14.3 14.3 21 22 308 328 2,087.0 3,281.3 3 3 4 4 Togo 41 41 588 588 47.5 47.5 15 15 277 277 1,400.1 1,285.3 6 6 1 1 Uganda 38 38 535 510 44.9 44.9 16 16 143 143 703.5 584.0 2 2 5 5 Zambia 35 35 471 471 38.7 38.7 17 17 254 254 1,023.1 912.7 3 3 6 6 Zimbabwe 38 38 410 410 32.0 32.0 19 19 1,426 1,426 16,368.8 24,468.3 8 8 1 1 NORTH AFRICA 42 42 705 705 23.8 23.8 22 22 184 176 433.5 2,658.3 5 6 4 4 Algeria 47 46 630 630 21.9 21.9 22 22 240 240 46.8 39.6 6 6 6 6 Egypt, Arab Rep. 42 41 1,010 1,010 26.2 26.2 28 25 249 218 376.7 331.6 8 8 3 3 Libya .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Morocco 40 40 615 615 25.2 25.2 19 19 163 163 292.5 263.7 6 6 2 2 Tunisia 39 39 565 565 21.8 21.8 20 20 84 84 1,017.8 998.3 0 5 5 5 a. Average of the disclosure, director liability, and shareholder suits indexes. b. Average of the rigidity of hours, difficulty of hiring, and difficulty of firing indexes. 90 Part III. Development outcomes PRIVATE SECTOR DEVELOPMENT Protecting investors (0 least protection to Employing workers 10 most protection) (0 least rigid or difficult to 100 most rigid or difficult) Shareholder suits Investor protection Rigidity of Difficulty of Difficulty of Firing cost Rigidity of index indexa hours index hiring index firing index (weeks of wages) employment indexb 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 5 5 4.3 4.4 30 30 38 38 40 40 68 67 36 36 6 6 5.7 5.7 60 60 67 67 70 70 58 58 66 66 3 3 3.3 3.3 40 40 39 39 40 40 36 36 40 40 3 3 6.0 6.0 0 0 0 0 40 40 90 90 13 13 4 4 3.7 3.7 20 20 33 33 10 10 34 34 21 21 5 5 3.3 3.3 53 53 0 0 30 30 26 26 28 28 6 6 4.3 4.3 20 20 28 28 70 70 33 33 39 39 6 6 4.0 4.0 33 33 33 33 70 70 93 93 46 46 5 5 4.0 4.0 40 40 61 61 50 50 22 22 50 50 5 5 4.0 4.0 20 20 39 39 40 40 36 36 33 33 5 5 4.0 4.0 40 40 39 39 40 40 100 100 40 40 4 4 3.3 3.3 47 47 50 72 70 70 31 31 56 63 3 3 3.3 3.3 40 40 78 78 70 70 33 33 63 63 3 3 3.3 3.3 47 47 33 33 20 20 49 49 33 33 0 0 2.3 2.3 40 40 67 67 30 30 56 56 46 46 4 4 3.7 3.7 60 60 67 67 70 70 133 133 66 66 5 5 4.7 4.7 40 40 0 0 20 20 69 69 20 20 5 5 4.3 4.3 20 20 33 33 30 30 40 40 28 28 3 3 3.3 3.3 60 60 17 17 80 80 43 43 52 52 5 5 2.7 2.7 40 40 0 0 40 40 26 26 27 27 6 6 6.0 6.0 20 20 11 11 50 50 178 178 27 27 1 1 2.7 2.7 20 20 33 33 20 20 26 26 24 24 5 5 4.0 4.0 27 27 67 67 70 70 87 87 54 54 10 10 5.0 5.0 0 0 22 22 30 30 47 47 17 17 8 8 3.7 3.7 20 20 22 22 0 0 44 44 14 14 6 6 3.7 3.7 20 20 22 22 40 40 84 84 27 27 6 6 5.7 5.7 40 40 89 89 40 40 30 30 56 56 5 5 5.3 5.3 0 0 44 44 20 20 84 84 21 21 3 4 3.3 3.7 20 20 33 33 40 40 31 31 31 31 3 3 3.7 3.7 20 20 56 56 40 40 31 31 39 39 9 9 7.7 7.7 13 33 0 0 40 20 35 4 18 18 9 9 6.0 6.0 33 33 67 67 20 20 134 134 40 40 6 6 5.3 5.3 20 20 0 0 20 20 24 24 13 13 3 3 3.3 3.3 53 53 100 100 50 50 35 35 68 68 5 5 5.7 5.7 0 0 0 0 20 20 50 50 7 7 1 3 2.7 6.3 40 0 44 11 30 10 26 26 38 7 6 6 3.3 3.3 67 67 50 50 60 60 91 91 59 59 2 2 3.0 3.0 53 53 72 72 50 50 38 38 59 59 5 5 5.7 5.7 13 13 44 44 50 50 39 39 36 36 8 6 5.7 6.3 40 40 33 33 50 50 189 189 41 41 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 8 8 8.0 8.0 20 20 56 56 30 30 24 24 35 35 4 4 3.3 3.3 20 20 39 39 50 50 118 118 36 36 5 5 2.0 2.0 0 0 11 11 20 20 53 53 10 10 8 8 5.0 5.0 13 13 100 100 50 50 18 18 54 54 4 4 3.7 3.7 40 40 61 83 40 40 36 36 47 54 5 5 4.0 4.0 0 0 0 0 0 0 13 13 0 0 7 7 5.3 5.3 33 33 22 11 20 20 178 178 25 21 4 4 4.3 4.3 40 40 0 0 60 60 446 446 33 33 4 4 4.3 4.7 28 28 43 40 58 58 63 63 43 42 4 4 5.3 5.3 40 40 44 44 40 40 17 17 41 41 5 5 5.3 5.3 20 20 0 0 60 60 132 132 27 27 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1 1 3.0 3.0 40 40 100 89 50 50 85 85 63 60 6 6 3.7 5.3 13 13 28 28 80 80 17 17 40 40 PRIVATE SECTOR DEVELOPMENT Part III. Development outcomes 91 Drivers of growth Table 4.2 Investment climate Enterprise Surveys Private Domestic Firms that Viewed by firms as a major constraint (% of firms) sector fixed Net foreign credit to believe the court capital direct private system is fair, Crime, Customs formation investment sector impartial, and theft, and Tax Labor Labor Transpor- and trade (% of GDP) ($ millions) (% of GDP) uncorrupt (%) Corruption discord rates Finance Electricity regulations skills tation regulations 2008a 2007­08b 2008a 2007­09 b 2007­09b 2007­09b 2007­09b 2007­09b 2007­09b 2007­09b 2007­09b 2007­09b 2007­09b SUB­SAHARAN AFRICA 12.9 39.4 Angola 1.8 ­1,805.1 12.7 .. .. .. .. .. .. .. .. .. .. Benin .. .. 20.9 .. .. .. .. .. .. .. .. .. .. Botswana 18.6 ­32.3 22.0 .. .. .. .. .. .. .. .. .. .. Burkina Faso .. .. 18.6 .. .. .. .. .. .. .. .. .. .. Burundi .. 0.5 21.5 .. .. .. .. .. .. .. .. .. .. Cameroon 14.3 589.2 10.4 .. .. .. .. .. .. .. .. .. .. Cape Verde 33.7 191.5 54.1 .. .. .. .. .. .. .. .. .. .. Central African Republic 6.6 .. 7.0 .. .. .. .. .. .. .. .. .. .. Chad 6.4 .. 3.7 .. .. .. .. .. .. .. .. .. .. Comoros 8.1 .. 11.5 .. .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. 10.1 .. .. .. .. .. .. .. .. .. .. .. .. Congo, Rep. .. 2,638.4 3.5 32.3 65.0 44.1 40.9 44.8 71.1 24.5 51.5 48.4 45.9 Côte d'Ivoire 7.1 426.9 16.3 35.3 75.0 53.8 30.5 66.6 39.8 6.1 26.7 38.2 19.4 Djibouti .. 195.4 27.8 .. .. .. .. .. .. .. .. .. .. Equatorial Guinea 11.4 .. 4.4 .. .. .. .. .. .. .. .. .. .. Eritrea .. .. .. .. .. .. .. .. .. .. .. .. .. Ethiopia 5.9 222.0 .. .. .. .. .. .. .. .. .. .. .. Gabon 23.0 .. 8.6 41.3 41.4 34.1 30.9 30.4 58.0 16.4 42.7 48.8 35.1 Gambia, The .. 68.5 .. .. .. .. .. .. .. .. .. .. .. Ghana 18.1 970.4 .. 59.8 38.8 0.9 30.6 66.2 86.2 1.7 4.6 17.6 9.8 Guinea 9.9 385.9 .. .. .. .. .. .. .. .. .. .. .. Guinea-Bissau 10.6 .. 9.1 .. .. .. .. .. .. .. .. .. .. Kenya 20.4 691.7 26.4 22.3 79.2 3.9 58.2 41.8 27.6 4.3 3.3 30.6 23.6 Lesotho 17.5 130.3 10.9 33.2 46.7 33.5 47.1 28.6 44.3 11.3 16.5 19.8 21.7 Liberia .. 131.6 .. 44.3 31.2 26.8 19.0 35.0 59.1 2.6 5.1 39.3 15.6 Madagascar 25.9 .. 11.1 28.8 42.7 48.1 40.8 39.4 54.6 2.2 17.0 26.6 18.7 Malawi 20.7 .. .. .. .. .. .. .. .. .. .. .. .. Mali .. 65.5 17.1 49.6 28.9 0.6 54.0 60.4 55.7 1.9 8.0 20.1 8.2 Mauritania .. .. .. .. .. .. .. .. .. .. .. .. .. Mauritius 19.5 325.3 93.6 63.6 50.7 41.5 25.1 46.3 42.9 8.8 45.7 45.8 17.7 Mozambique 7.1 587.0 18.7 16.6 14.8 1.8 30.8 50.1 24.8 6.0 18.8 23.0 12.2 Namibia 15.8 718.5 47.1 .. .. .. .. .. .. .. .. .. .. Niger .. .. 11.0 .. .. .. .. .. .. .. .. .. .. Nigeria .. 5,618.7 33.1 53.5 40.9 4.1 20.9 53.1 75.9 4.0 6.3 28.1 5.0 Rwanda 10.7 80.1 .. .. .. .. .. .. .. .. .. .. .. São Tomé and Príncipe .. 32.2 28.3 .. .. .. .. .. .. .. .. .. .. Senegal 20.2 272.7 24.2 55.4 18.1 0.5 40.5 49.2 57.7 4.8 9.5 27.4 15.1 Seychelles 24.6 240.8 38.3 .. .. .. .. .. .. .. .. .. .. Sierra Leone 11.0 94.5 7.1 29.7 36.9 14.2 42.5 34.6 53.4 11.4 16.0 29.9 26.9 Somalia .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa 19.4 11,936.5 79.6 59.6 15.1 1.0 4.6 15.5 20.8 5.9 8.7 3.9 1.9 Sudan 12.8 2,425.6 10.9 .. .. .. .. .. .. .. .. .. .. Swaziland 15.0 14.3 25.6 .. .. .. .. .. .. .. .. .. .. Tanzania .. 647.0 16.3 .. .. .. .. .. .. .. .. .. .. Togo .. .. 19.2 .. .. .. .. .. .. .. .. .. .. Uganda 17.9 787.4 14.1 .. .. .. .. .. .. .. .. .. .. Zambia 15.5 983.9 15.3 55.0 14.8 1.0 25.5 20.1 11.9 5.9 8.0 10.6 9.8 Zimbabwe .. .. .. .. .. .. .. .. .. .. .. .. .. NORTH AFRICA 23.9 18,544.3 34.4 Algeria 27.9 .. 12.9 .. 64.7 0.9 46.7 50.1 48.1 13.8 36.8 24.7 36.1 Egypt, Arab Rep. 20.2 10,913.3 42.8 .. 7.3 0.0 49.5 25.0 19.8 27.1 30.6 5.2 23.5 Libya .. 3,921.8 6.3 .. .. .. .. .. .. .. .. .. .. Morocco 27.5 2,193.8 79.5 43.5 13.4 0.0 55.7 31.6 37.0 15.8 31.0 8.2 14.3 Tunisia .. 1,515.3 66.6 .. .. .. .. .. .. .. .. .. .. a. Provisional. b. Data are for the most recent year available during the period specified. 92 Part III. Development outcomes PRIVATE SECTOR DEVELOPMENT Enterprise Surveys Regulation and tax administration Interest rate Time dealing Average time to clear customs spread Market Time to prepare, Highest marginal with officials (days) (lending rate Listed capitalization of Turnover ratio for Number of tax file, and pay taxes Total tax rate tax rate, corporate (% of minus deposit domestic listed companies traded stocks payments (hours) (% of profi t) (%) management time) Direct exports Imports rate) companies (% of GDP) (%) 2010 2010 2010 2007­09 b 2007­09 b 2007­09 b 2007­09 b 2008a 2008 2008a 2008a 38 302 66.8 10.1 15.9 31 272 53.2 .. .. .. .. 6.1 .. .. .. 55 270 73.3 .. .. .. .. .. .. .. .. 19 140 17.1 15.0 .. .. .. 7.9 19 27.4 3.1 46 270 44.9 .. .. .. .. .. .. .. .. 32 140 278.6 .. .. .. .. .. .. .. .. 41 1,400 50.5 .. .. .. .. .. .. .. .. 56 100 49.7 .. .. .. .. 6.2 .. .. .. 54 504 203.8 .. .. .. .. .. .. .. .. 54 122 60.9 .. .. .. .. .. .. .. .. 20 100 41.1 .. .. .. .. 4.5 .. .. .. 32 308 322.0 .. .. .. .. .. .. .. .. 61 606 65.5 .. 6.0 .. 31.4 .. .. .. .. 66 270 44.7 35.0 1.8 16.6 31.2 .. 38 30.2 4.1 35 114 38.7 .. .. .. .. .. .. .. .. 46 296 59.5 .. .. .. .. .. .. .. .. 18 216 84.5 .. .. .. .. .. .. .. .. 19 198 31.1 30.0 .. .. .. .. .. .. .. 26 272 44.7 .. 2.8 3.8 10.3 .. .. .. .. 50 376 292.4 .. .. .. .. .. .. .. .. 33 224 32.7 22.0 4.0 6.8 6.8 .. 35 21.1 5.2 56 416 49.9 .. .. .. .. .. .. .. .. 46 208 45.9 .. .. .. .. .. .. .. .. 41 417 49.7 .. 5.1 12.0 12.0 8.7 53 31.6 11.8 21 324 18.5 .. 5.6 5.4 4.4 8.5 .. .. .. 32 158 43.7 .. 7.5 .. 6.7 .. .. .. .. 23 201 39.2 .. 17.1 14.2 19.3 33.5 .. .. .. 19 157 25.8 .. .. .. .. .. 14 41.5 3.9 58 270 52.1 .. 2.4 9.1 9.1 .. .. .. .. 38 696 86.1 .. .. .. .. .. .. .. .. 7 161 22.9 15.0 9.4 10.3 11.7 11.4 41 39.8 8.9 37 230 34.3 32.0 3.3 10.4 10.4 7.3 .. .. .. 37 375 9.6 .. .. .. .. 5.4 7 7.2 2.8 41 270 46.5 .. .. .. .. .. .. .. .. 35 938 32.2 .. 6.1 12.8 12.8 3.5 213 23.5 29.3 34 160 31.3 .. .. .. .. .. .. .. .. 42 424 47.2 .. .. .. .. 19.7 .. .. .. 59 666 46.0 .. 2.9 8.9 8.9 .. .. .. .. 16 76 44.1 .. .. .. .. 7.8 .. .. .. 29 357 235.6 .. 7.4 .. 12.2 14.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 9 200 30.2 28.0 6.0 5.9 5.9 3.5 425 177.5 60.6 42 180 36.1 .. .. .. .. .. .. .. .. 33 104 36.6 .. .. .. .. 6.7 7 .. .. 48 172 45.2 30.0 .. .. .. 6.9 7 6.3 .. 53 270 52.7 .. .. .. .. .. .. .. .. 32 161 35.7 30.0 .. .. .. .. 6 .. .. 37 132 16.1 .. 4.6 6.6 6.6 12.5 .. .. .. 51 270 39.4 .. .. .. .. .. 81 .. .. 28 379 54.9 9.8 9.8 5.7 34 451 72.0 .. .. 16.8 16.8 6.3 .. .. .. 29 480 43.0 20.0 0.0 8.7 8.7 5.7 373 52.7 61.9 .. .. .. .. .. .. .. 3.5 .. .. .. 28 358 41.7 .. 11.4 3.8 3.8 .. 77 76.2 31.1 22 228 62.8 .. .. .. .. .. 49 15.9 25.5 PRIVATE SECTOR DEVELOPMENT Part III. Development outcomes 93 Drivers of growth Table 4.3 Financial sector infrastructure Macroeconomy Foreign currency sovereign ratings Gross national savings Money and quasi money (M2) Real interest rate Long-term Short-term (% of GDP) (% of GDP) (%) 2009 2009 2007 2008b 2007 2008b 2007 2008b SUB­SAHARAN AFRICA 9.8 4.3 37.4 37.8 Angola .. .. 32.8 47.4 16.2 18.1 13.0 ­6.3 Benin B B .. .. 30.7 32.9 .. .. Botswana .. .. 55.6 54.8 37.5 40.6 2.9 ­0.5 Burkina Faso .. .. .. .. 21.3 22.8 .. .. Burundi .. .. .. .. 34.7 34.4 7.9 ­6.4 Cameroon B B 19.6 20.2 18.1 19.6 12.7 .. Cape Verde B+ B 26.0 26.8 77.2 75.4 7.1 4.3 Central African Republic .. .. 4.5 4.0 14.7 14.5 12.8 .. Chad .. .. 20.3 7.8 11.8 11.8 13.0 .. Comoros .. .. 9.1 11.2 25.6 26.7 5.1 1.4 Congo, Dem. Rep. .. .. 8.3 0.2 10.4 .. .. .. Congo, Rep. .. .. .. .. 18.9 17.7 24.9 .. Côte d'Ivoire .. .. 7.9 9.6 27.0 27.8 .. .. Djibouti .. .. .. .. 78.0 83.7 7.9 .. Equatorial Guinea .. .. 38.7 35.7 6.4 6.2 16.4 .. Eritrea .. .. .. .. 115.8 .. .. .. Ethiopia .. .. 20.5 16.5 25.3 .. .. .. Gabon BB- B 39.6 48.7 18.2 16.9 9.3 .. Gambia, The .. .. 10.6 10.8 50.1 .. 21.0 .. Ghana B+ B 23.6 19.6 .. .. .. .. Guinea .. .. 8.7 9.2 .. .. .. .. Guinea-Bissau .. .. 34.4 22.9 33.9 38.4 .. .. Kenya B+ B 17.2 17.6 39.1 35.0 8.3 ­10.2 Lesotho .. .. 39.1 24.8 32.2 33.4 4.6 6.0 Liberia .. .. ­14.7 .. 23.1 .. ­0.8 .. Madagascar .. .. 14.0 12.4 20.6 20.5 32.2 32.3 Malawi .. .. 9.4 9.1 14.8 .. 18.9 .. Mali .. .. 25.7 .. 29.1 25.7 .. .. Mauritania .. .. 29.2 .. .. .. 26.7 .. Mauritius .. .. 19.8 22.7 101.3 102.8 13.9 12.9 Mozambique .. .. 9.3 10.4 28.1 31.0 11.3 11.0 Namibia .. .. 29.3 24.8 38.5 38.2 3.2 1.6 Niger .. .. .. .. 15.7 15.7 .. .. Nigeria BB- B .. .. 22.5 29.4 11.6 0.9 Rwanda B- B 15.8 13.0 .. .. 4.8 .. São Tomé and Príncipe .. .. .. .. 38.6 34.2 10.9 7.0 Senegal .. .. 19.1 17.9 34.3 33.4 .. .. Seychelles .. .. ­3.3 2.7 79.2 66.6 3.9 ­10.8 Sierra Leone .. .. 9.6 14.1 19.7 20.6 13.3 11.5 Somalia .. .. .. .. .. .. .. .. South Africa BBB+ F2 14.0 14.0 62.5 64.3 3.8 3.9 Sudan .. .. 11.9 15.4 20.2 18.2 .. .. Swaziland .. .. 18.2 30.5 23.6 26.3 3.9 11.1 Tanzania .. .. .. .. 27.2 27.9 6.5 5.6 Togo .. .. .. .. 34.8 38.8 .. .. Uganda B B 13.8 12.0 19.0 20.7 11.0 .. Zambia .. .. 22.9 19.8 20.5 21.6 6.3 7.5 Zimbabwe .. .. .. .. .. .. .. .. NORTH AFRICA 14.5 .. 69.4 65.6 Algeria .. .. 56.8 71.6 54.7 53.9 1.1 ­7.8 Egypt, Arab Rep. .. .. 26.3 23.6 88.5 84.2 ­0.1 0.0 Libya BBB+ F2 .. .. 30.4 26.4 0.6 ­31.8 Morocco BBB- F3 32.4 34.4 97.5 101.3 .. .. Tunisia .. .. 22.6 16.7 59.2 61.0 .. .. a. Data are consolidated for regional security markets where they exist. b. Provisional. 94 Part III. Development outcomes PRIVATE SECTOR DEVELOPMENT Intermediation Capital marketsa Domestic credit to Interest rate spread Ratio of bank non- Market capitalization Turnover ratio for private sector (lending rate minus performing loans to Listed domestic of listed companies traded stocks (% of GDP) deposit rate) total gross loans (%) companies (% of GDP) (%) 2007 2008b 2007 2008b 2007 2008b 2007 2008 2007 2008b 2007 2008b 69.6 39.4 10.5 12.7 10.9 6.1 .. .. .. .. .. .. .. .. 20.0 20.9 .. .. .. .. .. .. .. .. .. .. 20.1 22.0 7.6 7.9 .. .. 18 19 47.8 27.4 2.2 3.1 16.8 18.6 .. .. .. .. .. .. .. .. .. .. 23.4 21.5 .. .. .. .. .. .. .. .. .. .. 9.2 10.4 10.8 .. .. .. .. .. .. .. .. .. 47.7 54.1 7.3 6.2 .. .. .. .. .. .. .. .. 6.7 7.0 10.8 .. .. .. .. .. .. .. .. .. 2.9 3.7 10.8 .. .. .. .. .. .. .. .. .. 9.7 11.5 8.0 4.5 .. .. .. .. .. .. .. .. 3.7 .. .. .. .. .. .. .. .. .. .. .. 2.5 3.5 10.8 .. .. .. .. .. .. .. .. .. 16.1 16.3 .. .. .. .. 38 38 42.2 30.2 2.5 4.1 23.4 27.8 8.1 .. .. .. .. .. .. .. .. .. 2.9 4.4 10.8 .. .. .. .. .. .. .. .. .. 25.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 12.0 8.6 10.8 .. 7.6 .. .. .. .. .. .. .. 16.2 .. 15.0 .. .. .. .. .. .. .. .. .. .. .. .. .. 6.4 .. 32 35 15.9 21.1 3.9 5.2 .. .. .. .. .. .. .. .. .. .. .. .. 5.7 9.1 .. .. .. .. .. .. .. .. .. .. 27.2 26.4 8.2 8.7 22.7 .. 51 53 49.7 31.6 10.6 11.8 10.1 10.9 7.7 8.5 3.0 .. .. .. .. .. .. .. 10.0 .. 11.3 .. .. .. .. .. .. .. .. .. 10.2 11.1 28.5 33.5 .. .. .. .. .. .. .. .. 10.5 .. 21.7 .. .. .. 9 14 .. 41.5 .. 3.9 18.9 17.1 .. .. .. .. .. .. .. .. .. .. .. .. 15.5 .. .. .. .. .. .. .. .. .. 83.5 93.6 10.1 11.4 .. .. 90 41 83.5 39.8 8.0 8.9 13.5 18.7 7.7 7.3 2.6 .. .. .. .. .. .. .. 50.4 47.1 5.3 5.4 2.8 .. 9 7 8.1 7.2 3.7 2.8 9.4 11.0 .. .. .. .. .. .. .. .. .. .. 25.3 33.1 6.7 3.5 8.4 .. 212 213 52.0 23.5 28.2 29.3 .. .. 9.1 .. .. .. .. .. .. .. .. .. 31.6 28.3 19.7 19.7 .. .. .. .. .. .. .. .. 22.7 24.2 .. .. 18.6 .. .. .. .. .. .. .. 32.5 38.3 7.8 7.8 .. .. .. .. .. .. .. .. 5.3 7.1 15.0 14.8 31.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 163.9 79.6 4.0 3.5 1.4 .. 422 425 293.8 177.5 55.0 60.6 12.6 10.9 .. .. .. .. .. .. .. .. .. .. 25.4 25.6 6.1 6.7 4.0 .. 6 7 7.0 .. .. .. 14.9 16.3 7.4 6.9 .. .. 7 7 .. 6.3 .. .. 21.3 19.2 .. .. .. .. .. .. .. .. .. .. 10.5 14.1 9.8 .. 4.1 .. .. 6 .. .. .. .. 11.9 15.3 9.7 12.5 .. .. 15 .. 20.6 .. 4.1 .. .. .. 457.5 .. .. .. 82 81 .. .. 5.1 .. 37.7 34.4 13.4 12.9 6.3 6.3 .. .. .. .. .. .. .. .. 50.6 42.8 6.4 5.7 .. .. 435 373 106.8 52.7 45.6 61.9 7.2 6.3 3.5 3.5 .. .. .. .. .. .. .. .. 69.9 79.5 .. .. 7.9 .. 74 77 100.5 76.2 42.1 31.1 64.3 66.6 .. .. 17.3 .. 50 49 15.3 15.9 13.3 25.5 PRIVATE SECTOR DEVELOPMENT Part III. Development outcomes 95 Drivers of growth Table 5.1 International trade and tariff barriers Trade Average Annual growth Exports of Imports of Exports of Imports of (% of GDP) (%) Merchan- goods and goods and goods and goods and Exports of Imports of Exports of Imports of Terms of Total dise Services services services services services goods and goods and goods and goods and trade index (% of GDP) (% of GDP) (% of GDP) ($ millions) ($ millions) (% of GDP) (% of GDP) services services services services (2000=100) 2008 a 2008 a 2007­08 a 2008 a 2008 a 2008 a 2008a 2007­08a 2007­08a 2008a 2008a 2008a SUB­SAHARAN AFRICA 76.9 65.4 13.6 413,690 372,119 41.9 37.7 35.3 33.8 .. 6.5 Angola 128.7 104.8 21.9 74,618 32,731 89.5 39.3 77.3 53.8 .. .. .. Benin .. 45.5 .. .. .. .. .. 14.1 27 .. .. .. Botswana 86.8 78.8 15.5 5,928 5,333 45.7 41.1 47.7 34.4 2.5 1.1 69.3 Burkina Faso .. 30.4 .. .. .. .. .. 9.7 24 .. .. .. Burundi .. 39.5 21.2 .. .. .. .. 8.7 31 .. .. .. Cameroon 57.4 37.2 10.1 6,837 6,587 29.2 28.2 22.2 21.7 24.6 1.4 140.6 Cape Verde 74.6 49.6 54.3 345 945 19.9 54.7 23.5 58.2 13.0 1.1 58.7 Central African Republic 37.5 25.1 .. 284 455 14.4 23.1 14.9 21.3 6.9 1.1 72.5 Chad 77.7 77.7 .. 3,677 2,823 44 33.8 36.6 50.5 ­11.7 1.0 100.0 Comoros 49.7 38.7 .. 68 196 12.8 36.9 13.9 33.7 8.5 1.0 100.0 Congo, Dem. Rep. 56.6 69.5 .. 2,693 3,863 23.2 33.3 25.4 32.2 5.7 1.1 134.5 Congo, Rep. .. 111.2 50.3 .. .. .. .. 80.9 49.7 .. .. .. Côte d'Ivoire 97.3 73.7 17.1 11,953 10,838 51.1 46.3 47.6 38.6 7.4 1.0 76.8 Djibouti .. 74.2 43.6 .. .. .. .. 41 54 .. .. .. Equatorial Guinea 110.4 118.7 .. 14,498 5,953 78.3 32.1 91.2 55.6 .. .. .. Eritrea .. 33.3 .. .. .. .. .. 9 61 .. .. .. Ethiopia 40.2 34.4 16.1 3,074 7,577 11.6 28.6 13.1 29.6 3.1 1.1 82.9 Gabon 115.5 75.5 .. 11,151 5,517 77.2 38.2 63.4 33 ­0.2 1.1 185.7 Gambia, The 79.1 43.9 29.7 235 383 30.1 49 39.9 54.1 8.8 1.0 71.2 Ghana 100 99.5 25.5 5,940 10,188 36.8 63.2 39.5 60.6 4.7 1.1 107.9 Guinea 57.9 68.0 7.5 1,187 1,281 27.8 30 27.2 30.1 7.7 1.1 90.2 Guinea-Bissau 79.6 60.1 .. 128 214 29.8 49.8 28.9 48.8 .. .. .. Kenya 63.9 46.5 15.4 8,599 13,456 24.9 39 25.1 34.1 ­4.2 1.1 119.9 Lesotho 158.1 180.6 11.2 767 1,796 47.3 110.8 49.4 105.1 ­22.0 1.1 154.5 Liberia .. 129.5 216.4 .. .. .. .. 29.2 50.1 .. .. .. Madagascar 78 60.0 .. 2,363 4,630 26.3 51.6 27.2 39.2 2.9 1.2 89.1 Malawi 74.6 58.3 .. 998 2,186 23.4 51.2 25.3 45.6 ­5.4 1.0 142.9 Mali .. 48.1 16.8 .. .. .. .. 28.6 39.8 .. .. .. Mauritania .. 122.5 .. .. .. .. .. 40 67.7 .. .. .. Mauritius 131.5 80.9 51.6 5,331 6,044 61.6 69.9 60.4 62.9 5.4 1.0 86.0 Mozambique 74 68.8 15.4 3,114 4,091 32 42 30.4 42.4 6.8 1.1 69.7 Namibia 87 87.3 12.8 3,335 4,117 38.9 48.1 42.7 46.1 ­47.5 0.5 99.7 Niger .. 42.4 .. .. .. .. .. 16.4 25.3 .. .. .. Nigeria 73.9 58.3 9.5 92,201 64,469 43.5 30.4 43.2 32 .. .. .. Rwanda 35.6 30.5 13.2 360 1,228 8.1 27.5 9.1 26.6 .. .. .. São Tomé and Príncipe .. 60.4 15.8 .. .. .. .. .. .. .. .. .. Senegal 72.4 61.3 21.6 3,294 6,262 24.9 47.4 26.8 41.4 6.2 1.1 92.2 Seychelles 283.4 163.3 84.9 1,091 1,271 130.9 152.5 94 106.2 31.0 1.2 100.0 Sierra Leone 62 39.9 8.2 487 724 24.9 37.1 21.4 35.5 .. .. .. Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 76.7 65.1 10.7 100,562 111,723 36.3 40.4 30.1 29.9 3.0 1.1 119.3 Sudan 44.8 37.0 7.2 13,292 12,883 22.7 22 16.8 22.2 23.0 1.0 100.0 Swaziland 160.4 152.4 33.2 2,101 2,098 80.2 80.1 88.1 93.1 6.4 1.0 133.0 Tanzania .. 47.9 18.9 .. .. .. .. 19.2 26.2 .. .. .. Togo 107.9 82.5 .. 1,142 1,905 40.4 67.5 36.5 55.2 .. .. .. Uganda 49 48.0 12.3 2,272 4,846 15.6 33.4 13.3 26.6 7.3 1.3 101.5 Zambia 71.1 71.0 10.5 5,267 4,909 36.8 34.3 33.6 38.7 20.7 1.2 108.1 Zimbabwe .. .. .. .. .. .. .. 32.1 37.3 .. .. .. NORTH AFRICA .. 66.0 20.9 261,135 207,611 46.4 36.9 35.5 30.3 .. 16.7 Algeria 83.6 67.5 .. 102,773 42,597 59.1 24.5 43.7 23.5 5.0 1.1 188.8 Egypt, Arab Rep. 81.9 45.4 26.3 61,354 72,031 37.7 44.2 25.6 29.4 27.8 1.2 100.1 Libya .. 74.6 4.7 .. .. .. .. 37.6 23.5 .. .. .. Morocco 90.7 71.5 23.4 35,089 43,188 40.6 50 32.1 37.3 5.1 1.1 99.1 Tunisia 133.5 109.3 22 26,186 27,451 65.2 68.3 49.7 52.8 8.0 1.1 96.5 96 Part III. Development outcomes TRADE AND REGIONAL INTEGRATION Structure of merchandise exports Structure of merchandise imports (% of total) (% of total) Agricultural Agricultural Food raw materials Fuel Ores and metals Manufactures Food raw materials Fuel Ores and metals Manufactures 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 .. .. .. .. .. 9.9 1.1 17.8 2.5 64.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.8 0.2 0.2 23.2 73.1 13.1 0.9 15.6 2.3 67.4 .. .. .. .. .. .. .. .. .. .. 35.0 4.2 3.8 2.1 20.7 12.4 0.9 28.0 0.9 57.6 .. .. .. .. .. .. .. .. .. .. 40.8 0.0 0.0 .. 58.8 25.7 1.4 11.1 0.9 59.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 13.8 .. .. .. 6.3 19.5 0.2 0.8 0.2 53.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 39.5 8.8 32.6 0.4 18.1 17.4 0.6 30.2 1.4 48.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 61.1 19.9 0.0 2.9 13.4 7.0 0.9 13.3 1.4 77.3 .. .. .. .. .. .. .. .. .. .. 81.6 6.2 .. 0.5 11.7 31.1 1.9 16.9 1.0 49.1 46.6 4.9 0.6 2.4 10.5 14.5 1.1 1.6 1.6 81.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 42.8 11.9 4.3 2.8 36.8 11.0 1.9 21.3 2.2 62.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 31.5 3.4 4.7 3.3 56.8 14.6 1.0 16.6 0.3 67.0 85.6 3.8 0.0 0.0 10.6 10.6 1.0 13.8 0.7 73.9 7.0 13.8 0.5 0.2 3.2 14.8 0.5 22.2 0.5 61.8 .. .. .. .. .. .. .. .. .. .. 31.1 0.6 0.1 0.8 67.1 18.8 2.5 18.3 1.1 57.6 11.1 2.8 15.5 64.0 5.8 17.8 0.9 16.2 0.3 46.8 23.6 0.5 0.4 34.5 39.1 15.4 0.6 10.3 0.8 72.5 14.3 2.6 1.5 63.3 5.6 23.6 4.7 17.0 1.4 52.9 .. .. .. .. .. .. .. .. .. .. 44.5 4.6 0.0 46.3 4.6 13.7 1.8 8.6 2.8 73.1 .. .. .. .. .. .. .. .. .. .. 36.8 2.9 19.3 4.1 36.1 25.1 1.5 26.6 1.3 45.5 97.8 0.0 0.0 0.0 2.2 22.1 1.2 25.3 0.4 48.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 6.6 2.1 10.6 29.3 50.7 5.2 1.0 18.6 3.3 64.7 .. .. .. .. .. 5.3 0.3 0.3 0.3 93.2 21.1 7.2 1.2 0.5 69.8 21.2 1.0 15.6 1.0 60.9 35.0 6.8 0.6 12.6 16.6 11.7 0.8 29.9 1.3 55.4 15.7 9.3 0.0 12.8 62.2 14.6 1.1 27.0 2.3 54.9 62.2 7.6 1.3 2.2 20.8 12.5 1.0 18.7 1.2 62.9 7.5 1.2 0.5 77.7 12.5 5.2 0.4 12.3 4.8 76.1 16.3 11.4 0.6 19.2 48.3 10.6 3.8 18.0 6.2 54.4 6.0 0.5 63.4 2.7 25.0 15.7 2.8 12.9 3.1 59.9 0.2 0.0 98.4 0.5 0.9 19.8 2.3 1.1 1.9 74.9 7.9 1.6 52.2 2.8 18.6 19.5 3.7 14.7 3.5 42.4 .. .. .. .. .. .. .. .. .. .. 19.1 1.5 3.8 10.3 65.1 12.3 2.6 20.0 3.5 61.4 9.5 0.5 16.2 1.4 69.8 9.8 2.2 12.8 3.4 70.7 (continued) TRADE AND REGIONAL INTEGRATION Part III. Development outcomes 97 Drivers of growth Table 5.1 International trade and tariff barriers (continued) Tariff barriers, all products (%) Export indexes Competitiveness Share of (0 low to 100 high) indicator (%) Simple Disper- lines with Share of Share Share of mean Simple sion Weighted inter- lines with of lines lines with Diversi- Concen- Destina- Sectoral Global Binding bound mean around mean national domestic that are specific fication tration tion effect effect coverage rate tariff the mean tariff peaks peaks bound rates 2007 2006 2006 2003­07 2003­07 2007 2007 2007­08 a 2007­08a 2007­08a 2007­08a 2007­08a 2007 2007­08a SUB­SAHARAN AFRICA .. 52.7 43.2 54.3 38.9 11.3 0.9 7.4 37.2 3.1 50.6 0.0 Angola 1.1 95.5 .. 17.0 44.5 .. .. 7.4 0.9 7.4 23.6 2.9 100.0 0.0 Benin 6.4 62.3 41.6 2.2 ­22.0 .. .. 13.7 0.6 16.6 52.7 0.0 39.3 0.0 Botswana 2.8 72.5 74.0 ­9.9 ­6.4 .. .. 8.2 1.5 8.7 31.4 7.6 96.6 0.0 Burkina Faso 1.9 58.0 63.3 ­9.7 11.1 .. .. 12.4 0.6 9.2 44.6 0.0 39.2 0.0 Burundi 2.6 60.7 45.9 3.7 12.7 .. .. 12.8 0.8 10.7 34.1 0.0 21.8 0.0 Cameroon 3.3 51.2 38.1 3.9 ­4.1 .. .. 18.6 0.6 12.5 52.6 0.0 13.3 0.0 Cape Verde 9.0 47.5 54.4 ­8.2 21.4 .. .. 13.8 1.2 12.2 45.6 14.7 .. 0.0 Central African Republic 5.5 46.9 40.1 ­7.4 ­11.7 .. .. 17.5 0.6 13.6 47.4 0.0 62.5 0.0 Chad 1.1 .. .. ­4.8 589.7 .. .. 17.0 0.6 13.6 44.8 0.0 13.5 0.0 Comoros 4.9 47.5 50.4 ­31.4 14.8 .. .. 8.1 0.6 6.6 45.2 0.0 .. 0.0 Congo, Dem. Rep. 7.6 38.4 .. 15.1 14.0 .. .. 12.9 0.5 11.6 42.6 0.0 100.0 0.0 Congo, Rep. 1.4 86.9 .. ­2.7 5.7 .. .. 18.6 0.6 14.7 52.6 0.0 16.1 0.0 Côte d'Ivoire 7.7 .. .. ­8.0 ­4.9 .. .. 12.7 .. 10.3 45.2 0.0 .. 0.0 Djibouti 5.9 19.1 .. ­0.8 31.6 .. .. .. .. .. .. .. 100.0 .. Equatorial Guinea 1.3 90.4 .. 14.1 23.8 .. .. 18.3 0.6 15.6 52.3 0.0 .. 0.0 Eritrea 2.1 18.0 31.2 ­5.7 190.3 .. .. .. .. .. .. .. .. .. Ethiopia 4.7 43.2 25.3 1.4 12.7 .. .. 16.7 0.7 11.9 50.2 0.0 .. 0.0 Gabon 1.9 83.7 60.3 13.2 ­14.8 100.0 21.5 18.5 0.6 14.0 52.5 0.0 100.0 0.0 Gambia, The 6.6 50.6 58.3 ­7.3 ­5.8 .. .. 18.7 0.2 14.7 90.9 0.0 13.7 0.0 Ghana 4.5 44.2 28.8 ­5.1 0.0 .. .. 13.0 0.5 9.8 40.8 0.0 14.3 0.0 Guinea 3.2 65.7 30.7 16.0 ­19.9 .. .. 13.9 0.6 12.5 57.7 0.0 38.9 0.0 Guinea-Bissau 1.2 74.9 .. ­13.0 ­6.1 .. .. 14.0 0.6 14.0 55.0 0.0 97.8 0.0 Kenya 21.9 18.8 24.5 ­3.7 ­4.1 .. .. 12.0 1.0 8.8 36.7 0.5 14.6 0.0 Lesotho 6.6 46.6 61.9 ­14.6 5.5 .. .. 8.8 1.5 13.7 35.2 5.4 100.0 0.0 Liberia 3.5 .. .. 0.6 ­18.9 .. .. .. .. .. .. .. .. .. Madagascar 21.2 19.6 45.3 ­14.4 ­2.3 30.5 27.3 12.1 0.6 8.3 41.1 0.0 29.7 0.0 Malawi 3.8 59.9 30.9 ­9.2 4.8 .. .. 10.5 0.8 8.1 39.9 0.0 31.2 0.0 Mali 2.0 73.9 24.1 ­9.9 ­8.9 .. .. 12.6 0.6 10.1 44.5 0.0 40.6 0.0 Mauritania 3.9 74.0 36.0 17.8 10.3 .. .. 12.6 0.6 10.1 49.0 0.0 39.3 0.0 Mauritius 13.4 28.3 39.4 ­6.9 ­8.5 17.7 98.3 3.4 2.6 2.3 14.0 14.7 17.8 0.0 Mozambique 3.5 57.4 61.9 ­1.1 32.1 .. .. 11.0 0.7 7.7 36.7 0.0 13.6 0.0 Namibia 9.1 30.0 37.6 6.8 24.8 .. .. 6.5 1.5 1.1 25.8 7.2 96.6 0.0 Niger 1.4 47.2 46.1 21.5 2.1 96.6 44.8 12.8 0.6 7.1 47.0 0.0 96.8 0.0 Nigeria 1.3 85.2 41.9 16.4 8.5 .. .. 10.7 0.7 8.9 33.5 3.4 19.2 0.0 Rwanda 4.1 54.4 50.2 14.9 ­36.2 .. .. 19.3 0.6 11.6 55.2 0.0 100.0 0.0 São Tomé and Príncipe 3.9 86.9 47.1 ­9.8 ­15.9 .. .. .. .. .. .. .. .. .. Senegal 22.3 24.7 29.9 ­4.2 ­2.9 .. .. 13.0 0.6 10.1 47.7 0.0 100.0 0.0 Seychelles 3.9 62.8 53.2 ­1.7 ­18.4 .. .. 6.5 4.3 28.3 12.8 12.8 .. 0.0 Sierra Leone 7.3 53.9 97.4 ­6.6 10.8 .. .. .. .. .. .. .. 100.0 .. Somalia 6.6 .. .. ­5.4 ­2.1 .. .. .. .. .. .. .. .. .. South Africa 45.6 15.6 23.1 6.0 ­1.9 96.1 19.4 7.9 1.6 4.7 25.8 7.3 96.6 0.0 Sudan 1.2 87.2 82.4 12.4 23.7 .. .. 14.2 .. 11.4 34.7 0.0 .. 0.0 Swaziland 20.0 41.5 75.9 ­5.8 1.1 .. .. 9.7 1.5 7.9 36.4 8.8 96.6 0.0 Tanzania 30.1 35.3 24.9 ­1.1 2.6 .. .. 12.5 0.9 10.3 38.1 0.6 13.4 0.0 Togo 9.3 28.9 32.2 3.1 ­32.3 .. .. 13.6 0.6 13.6 50.9 0.0 14.0 0.0 Uganda 10.4 25.1 23.6 ­3.8 5.5 .. .. 12.6 1.0 10.6 38.8 0.5 15.8 0.0 Zambia 2.5 68.4 43.5 27.9 51.1 17.1 106.9 10.6 0.7 4.9 48.7 0.0 16.7 0.0 Zimbabwe 10.8 22.3 35.8 9.8 ­22.5 22.2 93.4 .. 1.8 .. .. .. 21.0 .. NORTH AFRICA .. .. .. .. .. .. .. .. .. .. .. .. Algeria 2.4 60.6 36.8 ­0.4 15.8 .. .. 16.3 0.6 9.5 60.7 0.0 .. 0.0 Egypt, Arab Rep. 17.2 35.6 24.8 4.8 26.2 .. .. 12.5 4.4 8.3 18.0 0.3 99.3 0.0 Libya 1.3 79.9 .. 17.5 14.6 .. .. .. .. .. .. .. .. .. Morocco 67.3 15.9 37.1 ­4.2 2.1 .. .. 11.7 1.2 9.4 41.1 0.3 100.0 0.0 Tunisia 35.8 18.7 42.7 ­4.2 5.3 .. .. .. .. .. .. .. 57.6 .. a. Provisional. b. Data are for the most recent year available during the period specified. 98 Part III. Development outcomes TRADE AND REGIONAL INTEGRATION GATS commitments Tariff barriers, primary products (%) Tariff barriers, manufactured products (%) index Average cost to ship 20 Average time to Dispersion Dispersion (0 least liberal ft container from port to clear customs Simple around the Weighted Simple around the Weighted to 100 most final destination ($) (days) mean tariff mean mean tariff mean tariff mean mean tariff liberal) Direct export Import Direct exports Imports 2007­08 a 2007­08 a 2007­08a 2007­08 a 2007­08 a 2007­08a 2008 2010 2010 2007­09 b 2007­09 b 12.4 0.9 5.9 11.1 0.9 7.9 11.1 1,918 2,909 10.1 15.9 11.9 0.9 14.4 6.7 1.0 5.8 4.4 2,250 3,240 .. .. 16.5 0.6 13.2 13.3 0.6 17.6 6.2 1,251 1,400 .. .. 3.2 1.7 0.7 8.5 1.6 9.2 4.4 2,810 3,264 .. .. 14.8 0.6 12.8 12.2 0.6 8.3 3.2 2,262 3,830 .. .. 11.7 0.8 7.9 12.9 0.8 11.3 35.4 2,747 4,285 .. .. 21.9 0.6 10.8 18.2 0.6 14.4 3.1 1,250 2,002 .. .. 16.2 1.2 13.0 13.2 1.3 11.7 .. 1,325 1,129 .. .. 18.9 0.6 13.9 17.3 0.6 13.2 2.5 5,491 5,554 .. .. 20.6 0.6 18.3 16.5 0.6 12.7 2.7 5,497 6,150 .. .. 4.0 0.5 3.0 9.1 0.5 9.5 .. 1,073 1,057 .. .. 14.1 0.5 12.1 12.7 0.5 11.4 11.2 2,607 2,483 .. .. 21.9 0.6 18.6 18.2 0.6 14.1 2.2 2,490 2,959 .. 31.4 15.2 .. 10.7 12.3 .. 10.1 .. 1,969 2,577 16.6 31.2 .. .. .. .. .. .. 4.8 836 911 .. .. 21.5 0.6 21.4 17.8 0.6 14.3 .. 1,411 1,411 .. .. .. .. .. .. .. .. .. 1,431 1,581 .. .. 19.7 0.6 11.8 16.4 0.7 11.9 .. 1,940 29,993 .. .. 21.1 0.6 15.2 18.1 0.6 13.7 6.3 1,945 1,955 3.8 10.3 17.0 0.2 12.2 19.2 0.2 17.4 51.7 831 922 .. .. 16.8 0.4 14.4 12.5 0.6 8.8 13.9 1,013 1,203 6.8 6.8 15.4 0.6 14.0 13.7 0.6 11.2 4.8 855 1,391 .. .. 16.5 0.6 16.9 13.5 0.6 12.5 2.4 1,545 2,349 .. .. 16.9 1.1 8.4 11.5 1.0 9.0 3.2 2,055 2,190 12.0 12.0 6.0 1.7 4.9 9.0 1.5 14.1 47.3 1,549 1,715 5.4 4.4 .. .. .. .. .. .. .. 1,232 1,212 .. 6.7 13.9 0.7 4.2 11.9 0.6 10.4 0.4 1,279 1,660 14.2 19.3 13.8 0.8 10.3 10.0 0.8 7.5 14.7 1,713 2,570 .. .. 15.2 0.6 11.2 12.2 0.6 9.9 3.0 2,075 2,955 9.1 9.1 11.2 0.7 9.2 12.8 0.6 11.0 3.3 1,520 1,523 .. .. 5.4 3.4 3.4 3.0 2.9 1.9 9.2 737 689 10.3 11.7 13.9 0.8 8.0 10.5 0.7 7.5 5.0 1,100 1,475 10.4 10.4 3.6 1.7 0.6 6.9 1.6 1.3 3.9 1,686 1,813 .. .. 15.2 0.6 5.8 12.4 0.6 9.7 2.3 3,545 3,545 .. .. 12.3 0.7 9.6 10.5 0.8 8.1 10.8 1,263 1,440 12.8 12.8 17.1 0.6 8.8 19.5 0.6 12.6 5.6 3,275 5,070 .. .. .. .. .. .. .. .. .. 690 577 .. .. 14.9 0.6 9.3 12.8 0.6 11.0 19.8 1,098 1,940 8.9 8.9 14.0 8.6 50.5 4.8 4.0 6.4 .. 1,839 1,839 .. .. .. .. .. .. .. .. 27.5 1,573 1,639 .. 12.2 .. .. .. .. .. .. .. .. .. .. .. 5.2 1.8 1.7 8.2 1.7 6.1 53.4 1,531 1,807 5.9 5.9 18.0 .. 11.6 13.7 .. 11.3 .. 2,050 2,900 .. .. 9.8 1.7 3.1 9.7 1.5 8.7 8.2 2,184 2,249 .. .. 18.5 1.1 12.0 11.9 1.0 9.8 1.0 1,262 1,475 .. .. 16.0 0.6 9.3 13.3 0.6 17.3 4.0 940 963 .. .. 19.3 1.1 20.4 11.9 1.0 9.4 3.2 3,190 3,390 .. .. 8.0 0.6 5.7 10.8 0.8 4.4 14.2 2,664 3,335 6.6 6.6 .. 1.0 .. .. 1.9 .. 6.9 3,280 5,101 .. .. .. .. .. .. .. .. .. 867 1,027 9.8 9.8 17.0 0.6 8.8 16.2 0.6 9.8 .. 1,248 1,428 16.8 16.8 36.2 11.6 6.3 9.5 1.3 9.8 10.9 737 823 8.7 8.7 .. .. .. .. .. .. .. .. .. .. .. 19.3 2.3 11.4 10.9 1.1 8.2 15.4 700 1,000 3.8 3.8 .. .. .. .. .. .. 5.5 783 858 .. .. TRADE AND REGIONAL INTEGRATION Part III. Development outcomes 99 Drivers of growth 5.2 Table Top three exports and share in total exports, 2007 First Second Share Share of total of total exports exports Product (%) Product (%) SUB­SAHARAN AFRICA Angola Petroleum oils and oils from bituminous minerals, crude 96.7 Benin Cotton, not carded, combed 29.8 Petroleum oils and oils from bituminous minerals, noncrude 20.8 Botswana Diamonds, not mounted or set 56.0 Nickel mattes 21.2 Burkina Faso Cotton, not carded, combed 71.6 Sesamum seeds 4.3 Burundi Coffee, not roasted, not decaffeinated 62.1 Black tea (fermented) and partly fermented tea in packages exceeding 3 kg 4.3 Cameroon Petroleum oils and oils from bituminous minerals, crude 52.7 Wood sawn or chipped lengthwise, sliced or peeled, more than 6mm thick 9.1 Cape Verde Fish, frozen, excluding fish fillets and other fish meat 25.4 Cotton, not carded, combed 12.9 Central African Republic Wood in the rough or roughly squared 30.3 Diamonds, not mounted or set, unsorted 21.4 Chad Petroleum oils and oils from bituminous minerals, crude 95.3 Cotton, not carded, combed 2.3 Comoros Vessels and other floating structures for breaking up 31.0 Cloves (whole fruit, cloves and stems) 19.8 Congo, Dem. Rep. Petroleum oils and oils from bituminous minerals, crude 83.2 Congo, Rep. Diamonds, not mounted or set 24.6 Petroleum oils and oils from bituminous minerals, crude 14.9 Côte d'Ivoire Cocoa beans, whole or broken, raw or roasted 29.4 Petroleum oils and oils from bituminous minerals, crude 17.0 Djibouti Sheep 26.9 Goats 24.0 Equatorial Guinea Petroleum oils and oils from bituminous minerals, crude 87.9 Methanol (methyl alcohol) 3.9 Eritrea Natural uranium and its compounds 69.1 Nuclear reactors, boilers, machinery & mechanical appliance 6.4 Ethiopia Coffee, not roasted, not decaffeinated 42.1 Sesamum seeds 16.3 Gabon Petroleum oils and oils from bituminous minerals, crude 71.8 Manganese ores and concentrates 9.6 Gambia, The Cashew nuts, in shells 36.0 Titanium ores and concentrates 8.5 Ghana Cocoa beans, whole or broken, raw or roasted 45.6 Manganese ores and concentrates 8.4 Guinea Aluminium ores and concentrates 52.4 Aluminium oxide other than artificial 15.3 Guinea-Bissau Cashew nuts, in shells 91.3 Kenya Cut flowers and flower buds, fresh 13.7 Other black tea (fermented) and other partly fermented tea 11.8 Lesotho Diamonds, not mounted or set 28.9 Articles, knitted or crocheted of cotton 18.5 Liberia Tankers 46.1 Other vessels for transport of goods and/or persons 21.9 Madagascar Articles, knitted or crocheted of wool or fine animal hair 12.4 Shrimps and prawns 10.1 Malawi Tobacco, partly or wholly stemmed 49.5 Raw sugar not containing added flavor 8.8 Mali Cotton, not carded, combed 70.8 Guavas, mangoes, and mangosteens 4.4 Mauritania Iron ores and concentrates, including roasted iron pyrites 45.3 Petroleum oils and oils from bituminous minerals, noncrude 19.0 Mauritius T-shirts, singlets, and other vests, knitted or crocheted of cotton 17.5 Cane sugar and chemically pure sucrose, solid 15.9 Mozambique Aluminium, not alloyed 51.3 Petroleum oils and oils from bituminous minerals, noncrude 9.9 Namibia Diamonds, not mounted or set 20.2 Unwrought zinc, containing by weight 99.99 percent or more of zinc 18.7 Niger Natural uranium and its compounds 83.7 Paintings, drawings, and pastels 2.2 Nigeria Petroleum oils and oils from bituminous minerals, crude 87.5 Liquefied natural gas 6.6 Rwanda Coffee, not roasted, not decaffeinated 43.2 Tin ores and concentrates 15.6 São Tomé and Príncipe Cocoa beans, whole or broken, raw or roasted 49.5 Prefabricated buildings 4.6 Senegal Petroleum oils and oils from bituminous minerals, noncrude 14.3 Phosphoric acid and polyphosphoric acids 9.5 Seychelles Tunas, skipjack, and bonito (Sarda spp.) 47.8 Yellowfin tunas (Thunnus albacares) 11.0 Sierra Leone Diamonds, not mounted or set 31.1 Aluminium ores and concentrates 11.7 Somalia Goats 33.7 Live bovine animals other than purebred breeding animals 10.5 South Africa Platinum, unwrought or in powder form 7.6 Diamonds, not mounted or set 6.1 Sudan Petroleum oils and oils from bituminous minerals, crude 92.3 Swaziland Raw sugar not containing added flavor 12.7 Food preparations not elsewhere specified or included 10.2 Tanzania Tobacco, partly or wholly stemmed 8.5 Coffee, not roasted, not decaffeinated 7.5 Togo Cocoa beans, whole or broken, raw or roasted 25.3 Petroleum oils and oils from bituminous minerals, noncrude 13.0 Uganda Coffee, not roasted, not decaffeinated 25.6 Fish fillets and other fish meat, fresh or chilled 12.8 Zambia Refined copper, cathodes and sections of cathodes 62.1 Copper ores and concentrates 6.3 Zimbabwe Nickel, not alloyed 22.7 Tobacco, partly or wholly stemmed 11.1 NORTH AFRICA Algeria Petroleum oils and oils from bituminous minerals, crude 63.1 Petroleum oils and oils from bituminous minerals, noncrude 10.5 Egypt, Arab Rep. Liquefied natural gas 18.2 Petroleum oils and oils from bituminous minerals, crude 11.6 Libya Petroleum oils and oils from bituminous minerals, crude 86.2 Petroleum oils and oils from bituminous minerals, noncrude 8.9 Morocco Phosphoric acid and polyphosphoric acids 5.2 Elec. int. circuits & microassemblies, other monolithic integrated circuits 3.8 Tunisia Petroleum oils and oils from bituminous minerals, crude 3.8 Trousers, bib and brace overalls, breeches, and shorts, cotton 5.6 AFRICAa Petroleum oils and oils from bituminous 48.6 Petroleum oils and oils from bituminous minerals, 4.3 minerals, crude (19.5) noncrude (4.0) Note: Products are reported when accounting for more than 2 percent of total exports. a. Values in parentheses are Africa's share of total world exports. b. As reported. 100 Part III. Development outcomes TRADE AND REGIONAL INTEGRATION Third Number of exports Share of total accounting for exports 75 percent of Product (%) total exports Copper waste and scrap 10.9 5 Copper mattes 3.7 2 Guavas, mangoes, and mangosteens 2.6 2 Other black tea (fermented) and other partly fermented tea 3.4 6 Cocoa beans, whole or broken, raw or roasted 6.1 5 Cocoa paste, not deflated 10.2 9 Cotton, not carded or combed 16.8 4 1 Essential oils, including concretes and absolutes resinoids extracted oleoresins 19.0 4 1 Cobalt ores and concentrates 14.7 6 Cocoa paste, not deflated 6.3 9 Petroleum oils and oils from bituminous minerals, crude 14.0 4 Liquefied natural gas 3.2 1 Sesamum seeds 3.3 2 Cut flowers and flower buds, fresh 6.5 7 Wood in the rough or roughly squared 0.0b 2b Ground nut oil and its fractions, crude 8.5 11 Petroleum oils and oils from bituminous minerals, noncrude 4.1 10 Copper ores and concentrates 7.9 3 1 Petroleum oils and oils from bituminous minerals, noncrude 5.9 51 Men's or boys' suits, ensembles, jackets, blazers, trousers, bib and brace overalls, breeches and shorts (other than swimwear), cotton 14.5 6 Natural rubber latex 11.6 3 Women's or girls' suits, ensembles, jackets, blazers, dresses, skirts, divided skirts, trousers, bib and brace overalls, breeches and shorts (other than swimwear) 8.0 26 Other black tea (fermented) and other partly fermented tea 5.7 6 Sesamum seeds 2.0 2 Molluscs or aquatic invertebrates other than crustaceans, other than live, fresh or chilled 9.7 4 Prepared of preserved fish, tunas, skipjack, and bonito (Sarda spp.) 9.5 24 Electrical energy (optional heading) 5.1 5 Natural uranium and its compounds alloys, dispersions (including cermets), ceramic products, and mixtures containing natural uranium 12.1 7 1 Petroleum oils and oils from bituminous minerals, noncrude 2.0 1 Other black tea (fermented) and other partly fermented tea 13.7 4 Parts and accessories (other than covers, carrying cases and the like) suitable for use solely or principally with machines of headings 84.69­84.72 4.6 12 Ground nut oil and its fractions, crude 7.1 34 Other fish, frozen, excluding fillets and other meat, skipjack or stripe bellied bonito 7.9 5 Titanium ores and concentrates 11.2 8 Pure-bred breeding animals 10.4 7 Gold (including gold plated with platinum) unwrought form 5.1 102 3 Mixtures of odoriferous substances of a kind used in the food or drink 9.9 25 Fish fillets and other fish meat, fresh or chilled 7.4 36 Portland cement, aluminous cement, slag cement, supersulphate cement, and similar hydraulic cements, in the form of clinkers 8.3 9 Tobacco, partly or wholly stemmed 7.3 16 Cobalt mattes and other intermediate products of cobalt 5.3 4 Nickel ores and concentrates 9.4 13 Liquefied natural gas 9.7 3 Petroleum oils and oils from bituminous minerals, noncrude 8.7 68 1 Natural calcium phosphates, natural aluminium calcium phosphates, and phosphatic chalk unground 3.2 72 Ignition wiring sets and other wiring sets of a kind used in vehicles, aircraft, or ships 4.6 82 Liquefied natural gas 3.4 37 (22.4) TRADE AND REGIONAL INTEGRATION Part III. Development outcomes 101 Drivers of growth 5.3 Table Regional integration, trade blocs Year of entry into force Type of of most most Merchandise exports within bloc Year recent recent ($ millions) established agreement agreementa 1990 1995 2000 2004 2005 2006 2007 Economic and Monetary Community of Central African States (CEMAC ) 1994 1999 CU 114 120 96 174 198 245 304 Common Market for Eastern and Southern Africa (COMESA) 1994 1994 FTA 830 1,367 1,443 2,420 2,866 3,468 4,582 East African Community (EAC) 1996 2000 CU 132 628 689 930 1043 1,279 1,587 Economic Community of Central African States (ECCAS) 1983 2004b NNA 133 157 181 221 251 310 385 Economic Community of West African States (ECOWAS) 1975 1993 PS 1,384 1,875 2,715 4,366 2,497 5,957 7,341 Indian Ocean Commission (IOC) 1984 2005b NNA 75 113 106 155 159 172 204 Southern African Development Community (SADC) 1992 2000 FTA 1,720 3,615 4,427 6,655 7,798 8,694 11,952 West African Economic and Monetary Union (WAEMU/UEMOA) 1994 2000 CU 499 560 741 1,233 1,390 1,545 1,917 Year of entry into force Type of of most most Merchandise exports within bloc Year recent recent (% of total bloc exports) established agreement agreementa 1990 1995 2000 2004 2005 2006 2007 Economic and Monetary Community of Central African States (CEMAC ) 1994 1999 CU 2.0 2.1 1.0 1.2 0.9 0.9 1.1 Common Market for Eastern and Southern Africa (COMESA) 1994 1994 FTA 3.6 6.1 4.6 5.0 4.5 4.2 4.7 East African Community (EAC) 1996 2000 CU 7.4 19.5 22.6 18.9 17.6 19.3 20.4 Economic Community of Central African States (ECCAS) 1983 2004b NNA 1.3 1.5 1.0 0.8 0.6 0.5 0.6 Economic Community of West African States (ECOWAS) 1975 1993 PS 9.7 9.0 7.6 9.3 9.3 8.4 9.4 Indian Ocean Commission (IOC) 1984 2005b NNA 4.8 5.9 4.4 4.3 4.6 4.8 5.7 Southern African Development Community (SADC) 1992 2000 FTA 17.9 32.8 9.5 9.7 9.3 9.1 10.1 West African Economic and Monetary Union (WAEMU/UEMOA) 1994 2000 CU 11.3 10.3 13.1 12.9 13.4 13.1 15.2 102 Part III. Development outcomes TRADE AND REGIONAL INTEGRATION Year of entry into force Type of of most most Merchandise exports by bloc Year recent recent (% of world exports) established agreement agreementa 1990 1995 2000 2004 2005 2006 2007 Economic and Monetary Community of Central African States (CEMAC ) 1994 1999 CU 0.2 0.1 0.1 0.1 0.2 0.2 0.2 Common Market for Eastern and Southern Africa (COMESA) 1994 1994 FTA 0.7 0.4 0.5 0.5 0.6 0.7 0.7 East African Community (EAC) 1996 2000 CU 0.1 0.1 0.0 0.1 0.1 0.1 0.1 Economic Community of Central African States (ECCAS) 1983 2004b NNA 0.3 0.2 0.3 0.3 0.4 0.5 0.5 Economic Community of West African States (ECOWAS) 1975 1993 PS 0.4 0.4 0.6 0.5 0.6 0.6 0.6 Indian Ocean Commission (IOC) 1984 2005b NNA 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Southern African Development Community (SADC) 1992 2000 FTA 0.3 0.2 0.7 0.7 0.8 0.8 0.9 West African Economic and Monetary Union (WAEMU/UEMOA) 1994 2000 CU 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Note: Economic and Monetary Community of Central Africa (CEMAC; formerly Central African Customs and Economic Union [UDEAC]), Cameroon, the Central African Republic, Chad, the Republic of Congo, Equatorial Guinea, and Gabon; Common Market for Eastern and Southern Africa (COMESA), Burundi, Comoros, the Democratic Republic of Congo, Djibouti, the Arab Republic of Egypt, Eritrea, Ethiopia, Kenya, Libyan Arab Republic, Madagascar, Malawi, Mauritius, Rwanda, Seychelles, Sudan, Swaziland, Uganda, Zambia, and Zimbabwe; East African Community (EAC), Burundi, Kenya, Rwanda, Tanzania, and Uganda; Economic Community of Central African States (ECCAS), Angola, Burundi, Cameroon, the Central African Republic, Chad, the Democratic Republic of Congo, the Republic of Congo, Equatorial Guinea, Gabon, and São Tomé and Príncipe; Economic Community of West African States (ECOWAS), Benin, Burkina Faso, Cape Verde, Côte d'Ivoire, the Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone, and Togo; Indian Ocean Commission (IOC), Comoros, Madagascar, Mauritius, Réunion, and Seychelles; Southern African Development Community (SADC; formerly Southern African Development Coordination Conference), Angola, Botswana, the Democratic Republic of Congo, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania, Zambia, and Zimbabwe; West African Economic and Monetary Union (UEMOA), Benin, Burkina Faso, Côte d'Ivoire, Guinea-Bissau, Mali, Niger, Senegal, and Togo. a. CU is customs union; FTA is free trade agreement; NNA is not notified agreement, which refers to preferential trade agreements established among member countries that are not notified to the World Trade Organization (these agreements may be functionally equivalent to any of the other agreements); and PS is partial scope agreement. b. Years of the most recent agreement are collected from the official website of the trade bloc. TRADE AND REGIONAL INTEGRATION Part III. Development outcomes 103 Drivers of growth 6.1 Table Water and sanitation Financing Access, Quality Committed supply side Access, demand side of supply nominal Internal Population with sustainable access Population with sustainable Water supply investment in ODA gross fresh water to an improved water source access to improved sanitation failure for firms water projects disbursements for resources per (% of (% of (% of (% of (% of (% of receiving water with private water supply and capita (cubic total urban rural total urban rural (average days participation sanitation sector meters) population) population) population) population) population) population) per year) ($ millions) ($ millions) 2007 2006 2006 2006 2006 2006 2006 2006 2000­08 a 2007 2008 SUB­SAHARAN AFRICA 4,859 58 81 46 31 43 24 1,381.9 1,668.1 Angola 8,431 51 62 39 50 79 16 83.5 .. 41.8 22.3 Benin 1,227 65 78 57 30 59 11 .. .. 51.1 63.5 Botswana 1,276 96 100 90 47 60 30 0.0 .. 1.3 2.2 Burkina Faso 846 72 97 66 13 41 6 11.8 .. 79.5 60.5 Burundi 1,284 71 84 70 41 44 41 94.1 .. 12.4 15.7 Cameroon 14,731 70 88 47 51 58 42 6.8 0.0 4.2 18.5 Cape Verde 610 .. .. .. .. .. .. 12.8 .. 3.7 6.4 Central African Republic 32,463 66 90 51 31 40 25 .. .. 1.6 1.9 Chad 1,394 48 71 40 9 23 4 .. .. 18.9 25.5 Comoros 1,910 85 91 81 35 49 26 .. .. 1.6 1.3 Congo, Dem. Rep. 14,423 46 82 29 31 42 25 81.8 .. 39.4 61.9 Congo, Rep. 62,516 71 95 35 20 19 21 .. 0.0 1.3 1.8 Côte d'Ivoire 3,819 81 98 66 24 38 12 .. .. 4.5 7.9 Djibouti 360 92 98 54 67 76 11 .. .. 1.7 3.2 Equatorial Guinea 40,485 43 45 42 51 60 46 .. .. 0.7 0.0 Eritrea 578 60 74 57 5 14 3 .. .. 3.4 8.2 Ethiopia 1,551 42 96 31 11 27 8 .. .. 75.6 106.5 Gabon 115,340 87 95 47 36 37 30 .. .. 0.0 18.6 Gambia, The 1,857 86 91 81 52 50 55 .. .. 15.8 9.1 Ghana 1,325 80 90 71 10 15 6 .. 0.0 118.8 124.4 Guinea 23,505 70 91 59 19 33 12 .. .. 14.5 14.7 Guinea-Bissau 10,383 57 82 47 33 48 26 43.2 .. 3.3 3.0 Kenya 552 57 85 49 42 19 48 .. .. 50.8 100.3 Lesotho 2,607 78 93 74 36 43 34 .. .. 7.9 18.8 Liberia 55,138 64 72 52 32 49 7 .. .. 3.1 7.1 Madagascar 18,114 47 76 36 12 18 10 .. .. 12.7 17.4 Malawi 1,160 76 96 72 60 51 62 .. .. 15.4 13.9 Mali 4,865 60 86 48 45 59 39 .. .. 38.0 47.1 Mauritania 128 60 70 54 24 44 10 92.5 .. 12.1 21.9 Mauritius 2,182 100 100 100 94 95 94 .. .. 13.1 11.9 Mozambique 4,693 42 71 26 31 53 19 .. .. 72.6 81.6 Namibia 2,961 93 99 90 35 66 18 10.2 0.0 5.9 11.8 Niger 247 42 91 32 7 27 3 .. 3.4 21.8 38.1 Nigeria 1,493 47 65 30 30 35 25 .. .. 87.4 108.7 Rwanda 1,005 65 82 61 23 34 20 .. .. 38.3 37.7 São Tomé and Príncipe 13,796 86 88 83 24 29 18 .. .. 0.8 0.9 Senegal 2,169 77 93 65 28 54 9 .. 0.0 75.5 76.1 Seychelles .. .. 100 .. .. .. 100 .. .. 0.0 0.2 Sierra Leone 29,518 53 83 32 11 20 5 .. .. 15.1 13.3 Somalia 690 29 63 10 23 51 7 .. .. 2.5 1.9 South Africa 936 93 100 82 59 66 49 .. 0.0 12.1 52.7 Sudan 742 70 78 64 35 50 24 .. 120.7 20.9 21.8 Swaziland 2,293 60 87 51 50 64 46 18.1 .. 0.0 1.0 Tanzania 2,035 55 81 46 33 31 34 .. 8.5 127.5 148.8 Togo 1,825 59 86 40 12 24 3 .. .. 1.4 3.0 Uganda 1,273 64 90 60 33 29 34 .. 0.0 92.3 64.2 Zambia 6,513 58 90 41 52 55 51 .. 0.0 52.0 39.5 Zimbabwe 985 81 98 72 46 63 37 .. .. 0.2 12.1 NORTH AFRICA 291 92 96 87 75 90 59 .. 376.3 462.8 Algeria 332 85 87 81 94 98 87 .. 874.0 5.7 4.6 Egypt, Arab Rep. 23 98 99 98 66 85 52 .. .. 76.5 55.7 Libya 98 .. .. .. 97 97 96 .. .. 0.0 0.0 Morocco 940 83 100 58 72 85 54 .. .. 188.5 301.0 Tunisia 410 94 99 84 85 96 64 .. .. 95.3 98.5 a. Data are for the most recent year available during the period specified. 104 Part III. Development outcomes INFRASTRUCTURE Drivers of growth 6.2 Table Transportation Access, supply side Access, demand side Road density Rural access (% Vehicle fleet (per 1,000 people) Ratio to arable land Ratio to total land of rural population Road network Rail lines (road km/1,000 sq (road km/100 sq within 2 km of an Commercial Passenger (km) (km) km arable land) km of land area) all-season road) vehicles vehicles 2000­07a 2000­07a 2000­07a 2000­07a 2000­07a 2000­06a 2000­06a SUB­SAHARAN AFRICA .. .. .. 6.9 .. .. .. Angola 51,429 .. 17.1 4.1 .. .. 8 Benin 19,000 .. 6.9 17.2 32 .. 13 Botswana 25,798 .. 107.5 4.6 .. 113 47 Burkina Faso 92,495 .. 19.1 33.8 25 7 5 Burundi 12,322 .. 12.5 48.0 .. .. 1 Cameroon 51,346 974 8.6 11.0 22 11 11 Cape Verde 1,350 .. 27.0 33.5 .. .. .. Central African Republic 24,307 .. 12.6 3.9 .. .. 1 Chad 40,000 .. 9.3 3.2 .. 6 .. Comoros 880 .. 11.0 47.3 .. 1 1 Congo, Dem. Rep. 153,497 3,641 22.9 6.8 26 .. .. Congo, Rep. 17,289 795 34.9 5.1 .. .. 8 Côte d'Ivoire 80,000 639 28.6 25.2 .. .. 7 Djibouti 3,065 .. 3,065.0 13.2 .. .. .. Equatorial Guinea 2,880 .. 22.2 10.3 .. .. .. Eritrea 4,010 .. 7.1 4.0 .. .. .. Ethiopia 42,429 .. 3.0 4.2 33 2 1 Gabon 9,170 810 28.2 3.6 .. .. .. Gambia, The 3,742 .. 11.2 37.4 .. 7 5 Ghana 57,614 977 14.4 25.3 .. 18 12 Guinea 44,348 .. 27.7 18.1 37 14 8 Guinea-Bissau 3,455 .. 11.5 12.3 .. 1 .. Kenya 63,265 1,917 12.0 11.1 .. 18 9 Lesotho 5,940 .. 18.0 19.6 .. .. .. Liberia 10,600 .. 27.9 11.0 .. .. 6 Madagascar 49,827 .. 16.9 8.6 22 .. .. Malawi 15,451 710 5.4 16.4 .. .. .. Mali 18,709 733 4.4 1.5 .. .. .. Mauritania 11,066 .. 23.1 1.1 .. .. .. Mauritius 2,021 .. 22.0 99.6 .. 138 104 Mozambique 30,400 .. 7.6 3.9 12 .. .. Namibia 42,237 .. 51.8 5.1 .. 85 42 Niger 18,550 .. 1.3 1.5 33 5 4 Nigeria 193,200 3,528 5.9 21.2 .. .. 17 Rwanda 14,008 .. 12.2 56.8 .. 3 1 São Tomé and Príncipe 320 .. 53.3 33.3 .. .. .. Senegal 13,576 906 4.6 7.1 .. 14 10 Seychelles 458 .. 458.0 99.6 .. 121 74 Sierra Leone 11,300 .. 21.1 15.8 22 4 2 Somalia 22,100 .. 21.2 3.5 .. .. .. South Africa 364,131 24,487 24.7 30.0 .. 151 103 Sudan 11,900 5,478 0.7 0.5 .. .. .. Swaziland 3,594 .. 20.2 20.9 .. 84 40 Tanzania 78,891 4,460 8.3 8.9 16 .. 1 Togo 7,520 .. 3.0 13.8 .. .. 10 Uganda 70,746 259 13.6 35.9 .. 5 2 Zambia 91,440 1,273 17.4 12.3 51 .. .. Zimbabwe 97,267 .. 30.1 25.1 .. .. 45 NORTH AFRICA 57,626 12,892 .. 7.0 .. .. 47 Algeria 108,302 3,572 14.5 4.6 .. 91 58 Egypt, Arab Rep. 92,370 5,195 31.2 9.3 .. .. 29 Libya 83,200 .. 45.8 4.7 .. 257 232 Morocco 57,625 1,907 7.2 12.9 .. 59 46 Tunisia 19,232 2,218 6.9 12.4 .. 95 83 (continued) INFRASTRUCTURE Part III. Development outcomes 105 Drivers of growth 6.2 Table Transportation (continued) Quality Pricing Financing Roads Committed nominal ODA gross disbursements Road network Price of Price of investment in transport for transportation in good or fair Ratio of paved to diesel fuel gasoline projects with private and storage condition (%) total roads (%) ($ per liter) ($ per liter) participation ($ millions) ($ millions) 2000­08 a 2000­07a 2008 2008 2000­07a 2007 2008 SUB­SAHARAN AFRICA .. 12.1 1.06 1.14 187.0 2,047.3 2,460.1 Angola .. 10.4 0.39 0.53 53.0 0.8 1.8 Benin 67.7 9.5 1.03 1.03 .. 52.9 99.4 Botswana .. 32.6 1.02 0.88 .. 0.1 0.1 Burkina Faso 91.3 4.2 1.33 1.38 .. 115.8 38.2 Burundi 24.0 10.4 1.23 1.39 .. 23.8 34.3 Cameroon 62.7 8.4 1.04 1.14 0.0 66.6 92.1 Cape Verde .. 69.0 1.43 1.84 .. 42.7 76.1 Central African Republic .. .. 1.44 1.44 .. 2.6 5.1 Chad 63.3 0.8 1.32 1.30 .. 15.8 58.2 Comoros .. 76.5 .. .. 0.5 3.4 0.6 Congo, Dem. Rep. 23.2 1.8 1.21 1.23 .. 101.4 159.4 Congo, Rep. .. 5.0 0.57 0.81 .. 30.6 28.2 Côte d'Ivoire 74.1 8.1 1.20 1.33 0.0 0.0 6.7 Djibouti .. 45.0 .. .. 300.0 5.6 3.6 Equatorial Guinea .. .. .. .. 72.0 .. .. Eritrea .. 21.8 1.07 2.53 .. 2.3 1.8 Ethiopia 73.0 12.8 0.89 0.92 .. 218.9 313.8 Gabon 25.0 10.2 0.90 1.14 91.8 7.3 7.0 Gambia, The 94.6 19.3 0.75 0.79 .. 6.5 6.4 Ghana 83.4 14.9 0.90 0.90 0.0 112.3 119.3 Guinea 44.2 9.8 1.02 1.02 .. 10.8 35.5 Guinea-Bissau .. 27.9 .. .. .. 32.5 16.8 Kenya 66.0 14.1 1.14 1.20 0.0 110.9 97.5 Lesotho 56.5 18.3 0.93 0.79 .. 8.3 16.1 Liberia .. 6.2 1.03 0.74 .. 13.8 31.2 Madagascar 33.7 11.6 1.43 1.55 0.0 159.5 117.8 Malawi 88.5 45.0 1.67 1.78 .. 14.2 33.0 Mali 62.0 18.0 1.10 1.30 55.4 121.5 81.0 Mauritania .. 26.8 1.06 1.49 .. 50.1 41.6 Mauritius .. 100.0 .. .. .. 2.6 1.5 Mozambique 61.3 18.7 1.37 1.71 186.9 140.8 100.5 Namibia 68.3 12.8 0.88 0.78 .. 26.9 25.8 Niger 66.8 20.5 0.97 0.99 .. 44.1 60.7 Nigeria 64.2 15.0 1.13 0.59 262.1 42.8 44.3 Rwanda 31.0 19.0 1.37 1.37 .. 20.6 50.7 São Tomé and Príncipe .. 68.1 .. .. .. 4.9 3.7 Senegal 41.8 29.3 1.26 1.35 55.4 62.6 82.9 Seychelles .. 96.0 .. .. .. .. .. Sierra Leone .. 8.0 0.91 0.91 .. 10.2 22.6 Somalia .. 11.8 1.15 1.12 .. 1.5 0.1 South Africa 65.0 17.3 0.95 0.87 3,483.0 0.6 0.4 Sudan .. 36.3 0.45 0.65 30.0 0.5 29.3 Swaziland .. 30.0 0.93 0.86 .. 11.3 0.0 Tanzania 71.4 8.6 1.30 1.11 134.0 156.3 162.8 Togo .. 31.6 0.88 0.89 .. 0.0 0.0 Uganda 29.3 23.0 1.22 1.30 0.0 112.7 178.5 Zambia 51.6 22.0 1.61 1.70 15.6 27.0 77.0 Zimbabwe 60.0 19.0 1.05 1.30 .. 0.0 0.0 NORTH AFRICA .. 68.0 0.20 0.49 1,731.0 637.9 617.9 Algeria .. 70.2 0.20 0.34 161.0 72.0 90.4 Egypt, Arab Rep. .. 81.0 0.20 0.49 730.0 142.2 110.2 Libya .. 57.2 0.12 0.14 .. .. .. Morocco .. 61.9 0.83 1.29 140.0 290.4 265.7 Tunisia .. 65.8 0.84 0.96 840.0 123.2 144.7 a. Data are for the most recent year available during the period specified. 106 Part III. Development outcomes INFRASTRUCTURE Drivers of growth 6.3 Table Information and communication technology Access, supply side Access, demand side Quality Telephone subscribers (per 100 people) Average delay for Telephone faults Unmet firm in obtaining Internet demand Households with a mainline phone users Total Cleared by next Mainline Mobile (% of mainline own telephone connection (per 100 (per 100 working day Total telephone telephone telephones) (% of households) (days) people) mainlines) (%) 2008 2008 2008 2006 2007­09 a 2007­09a 2008 2006 2006 SUB­SAHARAN AFRICA 30.3 0.9 32.0 4.5 Angola 38.2 0.6 37.6 .. .. .. 3.1 .. .. Benin .. .. 39.7 70.2 2.8 .. 1.8 7.0 14.8 Botswana 85.5 7.5 78.0 .. .. .. 4.2 .. .. Burkina Faso .. .. 16.8 .. .. .. 0.9 .. .. Burundi 6.3 0.4 6.0 .. .. .. 0.8 .. .. Cameroon 33.7 1.1 32.6 .. .. .. .. .. .. Cape Verde 70.1 14.4 55.7 0.6 .. .. 20.6 3.0 91.5 Central African Republic .. .. 3.5 .. .. .. 0.4 .. .. Chad .. .. 16.4 .. .. .. 1.2 .. .. Comoros .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. 14.5 0.1 14.4 .. .. .. 0.5 .. .. Congo, Rep. .. .. 50.0 .. .. 25.5 4.3 .. .. Côte d'Ivoire 52.5 1.7 50.7 .. 17.4 5.8 3.2 .. .. Djibouti .. .. .. .. .. .. .. .. .. Equatorial Guinea .. .. 52.5 .. .. .. 1.8 .. .. Eritrea 3.0 0.8 2.2 22.7 .. .. 3.0 63.8 41.6 Ethiopia 5.1 1.1 3.9 7.7 .. .. 0.4 .. 47.0 Gabon .. .. 89.8 4.7 12.8 8.6 6.2 .. .. Gambia, The 73.2 2.9 70.2 .. .. .. 6.9 .. .. Ghana 50.2 0.6 49.6 0.7 6.9 184.3 4.3 3.2 76.5 Guinea .. .. 26.4 .. .. .. 0.9 .. .. Guinea-Bissau 32.0 0.3 31.8 .. .. .. 2.4 .. .. Kenya 42.8 0.7 42.1 21.1 .. 27.1 8.7 70.1 63.7 Lesotho .. .. 28.8 .. 5.6 53.7 3.6 .. .. Liberia .. .. 19.3 .. .. .. .. .. .. Madagascar 26.2 0.9 25.3 .. 2.0 29.9 1.7 36.0 54.8 Malawi .. .. 12.5 .. .. .. 2.2 .. .. Mali 26.4 0.7 25.7 .. 2.4 43.4 1.0 .. .. Mauritania 67.8 2.4 65.4 .. 2.9 .. .. .. .. Mauritius 110.2 28.7 81.4 .. 76.3 38.6 29.9 .. .. Mozambique 20.6 0.4 20.2 4.2 .. 10.7 1.6 46.0 87.0 Namibia .. .. 49.8 .. 17.0 .. 5.4 .. .. Niger .. .. 11.4 .. 0.6 .. 0.5 .. .. Nigeria 42.5 0.9 41.6 .. .. 7.6 7.3 .. .. Rwanda 13.8 0.2 13.6 .. .. .. 3.1 .. 76.0 São Tomé and Príncipe .. .. 30.4 3.6 .. .. 15.4 14.0 98.0 Senegal 46.1 2.0 44.1 0.0 17.0 8.9 8.4 2.0 85.0 Seychelles 125.7 26.9 98.8 10.6 64.0 .. 37.1 6.0 90.0 Sierra Leone .. .. 18.1 .. .. 21.4 0.3 .. .. Somalia .. .. .. .. .. .. .. .. .. South Africa .. .. 92.4 .. 54.6 23.5 8.6 .. .. Sudan 27.9 0.9 27.1 0.0 10.0 .. 9.2 5.0 90.0 Swaziland .. .. 39.1 .. .. .. 4.1 0.7 70.0 Tanzania 30.9 0.3 30.6 0.7 9.3 .. 1.2 .. 93.0 Togo 26.1 2.2 24.0 11.3 7.0 .. 5.4 .. .. Uganda 27.6 0.5 27.0 .. 2.7 .. 7.9 .. .. Zambia 28.8 0.7 28.0 .. 5.1 17.3 5.5 .. .. Zimbabwe .. .. 13.3 47.0 .. .. 11.4 57.0 44.0 NORTH AFRICA 72.2 13.2 59.0 20.9 Algeria .. .. .. 0.0 38.0 40.8 .. .. .. Egypt, Arab Rep. 65.4 14.7 50.6 0.4 67.7 85.5 15.4 0.1 88.0 Libya .. .. .. .. .. .. .. .. .. Morocco 82.6 9.6 73.1 .. 18.1 6.4 33.0 .. .. Tunisia 95.0 12.0 83.0 1.1 .. .. 27.1 20.0 68.5 (continued) INFRASTRUCTURE Part III. Development outcomes 107 Drivers of growth 6.3 Table Information and communication technology (continued) Pricing Financing Price Cost of 3-minute call Connection charge Annual investment Committed nominal ODA gross basket for during peak hours ($) ($) ($ millions) investment in telecom- disbursements Internet Fixed Fixed Mobile Tele- munication projects for com- ($ per telephone Cellular To Residential Business Mobile telephone commu- commu- with private participa- munication month) local local U.S. telephone telephone cellular service nication nications tion ($ millions) ($ millions) 2007 2007 2006 2007 2007 2006 2006 2006 2006 2006 2007 2008 SUB­SAHARAN AFRICA 42.3 0.19 0.72 0.19 46.3 52.2 9.6 9,509.9 191.7 Angola 63.1 0.30 0.90 0.30 58.7 58.7 .. .. .. .. 198.0 11.4 Benin 43.1 0.03 0.96 0.03 201.6 366.6 9.6 .. .. 3.9 205.0 0.8 Botswana 29.7 0.17 0.20 0.17 37.5 55.0 3.4 268.5 135.5 404.0 28.0 0.3 Burkina Faso 67.8 0.21 1.03 0.21 52.2 52.2 114.8 134.2 66.6 202.6 88.8 5.0 Burundi 86.0 .. 0.58 .. .. .. 2.9 .. .. .. 0.0 1.6 Cameroon 48.3 0.31 1.32 0.31 83.5 208.7 9.6 .. 125.2 211.4 149.4 8.7 Cape Verde 48.3 .. 1.22 .. .. .. 46.0 8.7 5.0 15.9 0.0 0.2 Central African Republic 130.4 0.21 0.57 0.21 73.9 73.9 38.3 .. .. .. 12.0 0.1 Chad 105.0 .. 1.05 .. .. .. 7.7 .. .. .. 53.5 0.1 Comoros 20.8 0.14 0.70 0.14 112.7 112.7 63.8 .. .. .. .. .. Congo, Dem. Rep. .. .. .. .. .. .. .. .. .. .. 320.0 3.9 Congo, Rep. .. .. .. .. .. .. .. .. .. .. 90.0 0.2 Côte d'Ivoire 20.3 0.38 2.26 0.38 20.9 20.9 19.1 20.3 266.2 382.5 253.7 1.2 Djibouti 41.5 .. 0.51 .. .. .. 56.3 .. .. .. .. 0.3 Equatorial Guinea .. .. .. .. .. .. .. .. .. .. 9.3 0.0 Eritrea .. .. 0.33 .. .. .. 91.1 4.4 9.2 16.5 0.0 0.1 Ethiopia 14.6 .. 0.29 .. .. .. 42.3 37.5 .. 60.3 .. 4.0 Gabon .. .. 1.03 .. .. .. 3.8 .. .. .. 131.4 0.0 Gambia, The .. .. .. .. .. .. .. .. .. .. 0.0 0.3 Ghana 9.4 0.16 0.45 0.16 85.5 0.7 7.0 .. .. .. 420.0 0.9 Guinea .. .. .. .. .. .. .. .. .. .. 18.0 0.1 Guinea-Bissau .. .. .. .. .. .. .. .. .. .. 39.5 0.2 Kenya 63.9 0.08 1.17 0.08 34.2 50.4 34.7 174.3 618.6 792.9 877.0 6.0 Lesotho 77.5 0.24 .. 0.24 43.0 44.7 7.4 .. .. .. 4.8 0.0 Liberia .. .. .. .. .. .. .. .. .. .. 17.0 0.0 Madagascar 28.9 0.19 0.45 0.19 31.5 31.5 4.7 14.9 34.3 50.8 119.6 0.4 Malawi 52.7 0.09 0.60 0.09 .. .. 3.1 .. .. .. 37.0 0.6 Mali 43.2 0.15 0.85 0.15 80.6 41.8 57.4 .. .. 93.9 87.0 0.5 Mauritania 37.3 0.22 0.50 0.22 18.5 18.5 11.1 4.6 25.6 30.2 30.1 0.2 Mauritius 16.4 0.07 0.11 0.07 31.9 63.9 .. .. .. .. 26.1 1.4 Mozambique 34.4 0.35 0.40 0.35 18.8 18.8 0.2 .. .. 21.4 65.6 7.9 Namibia 55.8 0.19 1.23 0.19 37.8 37.8 7.2 .. .. .. 8.5 8.0 Niger 84.5 0.16 0.92 0.16 49.7 74.5 .. .. .. .. 110.0 0.5 Nigeria 40.8 0.14 0.61 0.14 71.5 71.5 3.9 .. .. .. 2,761.0 4.7 Rwanda 79.7 .. 0.80 .. .. .. 22.7 .. 9.8 .. 114.4 6.5 São Tomé and Príncipe 39.4 0.11 0.61 0.11 29.6 .. .. .. .. 1.1 .. 1.6 Senegal 40.4 0.21 0.57 0.21 20.9 20.9 40.2 57.4 126.3 183.8 567.0 2.0 Seychelles 59.5 0.13 1.63 0.13 78.2 78.2 9.1 .. .. 12.8 0.0 .. Sierra Leone .. .. 1.03 .. .. .. .. .. .. .. 26.3 0.0 Somalia .. .. .. .. .. .. .. .. .. .. 0.0 .. South Africa 28.2 0.19 1.42 0.19 54.4 54.4 22.0 .. .. .. 1,217.0 4.5 Sudan 28.9 .. 0.31 .. .. .. .. .. .. .. 478.0 0.3 Swaziland 39.1 0.08 1.33 0.08 30.2 50.5 5.8 .. .. .. 3.8 0.0 Tanzania 19.7 0.24 0.74 0.24 16.1 16.1 5.8 .. .. .. 301.5 3.3 Togo 37.0 0.19 0.72 0.19 104.3 104.3 17.2 26.4 41.1 67.4 0.0 0.0 Uganda 51.7 0.26 0.62 0.26 68.7 68.7 5.5 .. .. .. 500.6 10.8 Zambia 78.6 0.15 .. 0.15 12.5 37.5 .. .. .. .. 141.0 1.2 Zimbabwe .. .. .. .. .. .. .. 1.3 2.2 3.5 0.0 0.3 NORTH AFRICA 13.6 0.02 0.33 0.02 44.4 25.7 3.8 4,111.0 10.9 Algeria 23.1 0.00 0.22 0.00 0.0 0.0 16.5 .. .. .. 561.0 2.3 Egypt, Arab Rep. 4.2 0.02 0.16 0.02 108.5 35.9 17.4 1,018.2 1,451.2 2,669.8 2,758.0 1.2 Libya .. .. 0.34 .. .. .. 3.8 374.2 212.5 .. .. 0.0 Morocco 15.6 0.24 1.14 0.24 73.2 146.5 3.4 .. .. .. 716.0 0.9 Tunisia 11.6 0.02 0.33 0.02 15.6 15.6 3.8 86.4 216.4 311.8 76.0 2.4 a. Data are for the most recent year available during the period specified. 108 Part III. Development outcomes INFRASTRUCTURE Drivers of growth 6.4 Table Energy Access, demand side Energy production GDP per unit of Sourcea Electric power energy use (2000 Solid fuels use Total (% of total) consumption PPP $ per kg of (% of (billion kWh) Hydroelectric Coal Natural gas Nuclear Oil (kWh per capita) oil equivalent) population) 2006 2006 2006 2006 2006 2006 2006 2006 2007 SUB­SAHARAN AFRICA Angola 3.0 90.1 0.0 0.0 0.0 9.9 148.0 6.9 47.7 Benin 0.1 0.0 0.0 0.0 0.0 100.0 74.1 3.8 94.3 Botswana 1.0 0.0 99.4 0.0 0.0 0.6 1,419.1 11.7 42.5 Burkina Faso .. .. .. .. .. .. .. .. 95.0 Burundi .. .. .. .. .. .. .. .. 95.0 Cameroon 4.0 94.1 0.0 0.0 0.0 5.9 185.6 5.1 80.6 Cape Verde .. .. .. .. .. .. .. .. 36.2 Central African Republic .. .. .. .. .. .. .. .. 95.0 Chad .. .. .. .. .. .. .. .. 93.6 Comoros .. .. .. .. .. .. .. .. 76.0 Congo, Dem. Rep. 7.9 99.7 0.0 0.0 0.0 0.3 95.7 1.0 95.0 Congo, Rep. 0.5 82.1 0.0 17.9 0.0 0.0 164.4 10.5 83.9 Côte d'Ivoire 5.5 27.3 0.0 72.7 0.0 0.0 174.5 4.1 77.2 Djibouti .. .. .. .. .. .. .. .. 13.3 Equatorial Guinea .. .. .. .. .. .. .. .. .. Eritrea 0.3 0.0 0.0 0.0 0.0 99.3 .. 4.0 62.7 Ethiopia 3.3 99.7 0.0 0.0 0.0 0.3 38.4 2.3 95.0 Gabon 1.7 54.8 0.0 15.3 0.0 29.5 1,017.5 9.9 27.5 Gambia, The .. .. .. .. .. .. .. .. 94.7 Ghana 8.4 66.7 0.0 0.0 0.0 33.3 311.9 2.9 85.9 Guinea .. .. .. .. .. .. .. .. 95.0 Guinea-Bissau .. .. .. .. .. .. .. .. 95.0 Kenya 6.5 50.6 0.0 0.0 0.0 30.5 145.3 2.8 68.7 Lesotho .. .. .. .. .. .. .. .. 72.1 Liberia .. .. .. .. .. .. .. .. .. Madagascar .. .. .. .. .. .. .. .. 95.0 Malawi .. .. .. .. .. .. .. .. 95.0 Mali .. .. .. .. .. .. .. .. 95.0 Mauritania .. .. .. .. .. .. .. .. 60.6 Mauritius .. .. .. .. .. .. .. .. 5.0 Mozambique 14.7 99.9 0.0 0.1 0.0 0.1 461.4 1.7 95.0 Namibia 1.6 94.1 5.2 0.0 0.0 0.6 1,545.5 7.9 58.5 Niger .. .. .. .. .. .. .. .. 95.0 Nigeria 23.1 33.4 0.0 57.8 0.0 8.8 116.4 2.5 78.8 Rwanda .. .. .. .. .. .. .. .. 95.0 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. Senegal 2.4 9.6 0.0 1.9 0.0 85.1 156.8 6.2 55.7 Seychelles .. .. .. .. .. .. .. .. 5.0 Sierra Leone .. .. .. .. .. .. .. .. 95.0 Somalia .. .. .. .. .. .. .. .. 95.0 South Africa 251.9 1.5 93.5 0.0 4.7 0.0 4,809.9 3.2 17.3 Sudan 4.2 32.5 0.0 0.0 0.0 67.5 90.3 3.9 89.9 Swaziland .. .. .. .. .. .. .. .. 60.8 Tanzania 2.8 51.7 3.8 43.8 0.0 0.6 57.8 2.1 95.0 Togo 0.2 41.2 0.0 0.0 0.0 57.5 101.7 2.0 95.0 Uganda .. .. .. .. .. .. .. .. 95.0 Zambia 9.4 99.4 0.2 0.0 0.0 0.4 710.0 1.9 85.7 Zimbabwe 9.8 56.8 43.0 0.0 0.0 0.2 955.3 .. 71.2 NORTH AFRICA Algeria 35.2 0.6 0.0 97.2 0.0 2.2 869.9 6.6 5.0 Egypt, Arab Rep. 115.4 11.2 0.0 72.1 0.0 16.1 1,303.7 5.7 5.0 Libya 24.0 0.0 0.0 40.9 0.0 59.1 3,688.4 4.4 5.0 Morocco 23.2 6.9 58.1 12.8 0.0 21.4 685.1 8.3 6.8 Tunisia 14.1 0.7 0.0 84.9 0.0 14.2 1,220.7 7.8 5.0 (continued) INFRASTRUCTURE Part III. Development outcomes 109 Drivers of growth 6.4 Table Energy (continued) Quality Financing Firms identifying Average delay for Electric power Firms using Committed nominal electricity as major or firm in obtaining transmission Electrical Firms that share electricity investment in energy ODA gross very severe obstacle electrical and distribution outages of firms or own their from projects with private disbursements to business operation connection losses (average number own generator generator participation for energy and growth (%) (days) (% of output) of days per year) (%) (%) ($ millions) ($ millions) 2007­09 b 2007­09 b 2006 2006­09 b 2007­09 b 2007­09 b 2007 2008 SUB­SAHARAN AFRICA 1,044.2 Angola .. .. 14.5 .. .. .. .. 3.0 Benin .. .. .. .. .. .. .. 29.6 Botswana .. .. 14.9 .. .. .. 28.0 0.4 Burkina Faso .. .. .. .. .. .. .. 39.5 Burundi .. .. .. .. .. .. 0.0 1.1 Cameroon .. .. 14.7 .. .. .. 0.0 5.6 Cape Verde .. .. .. .. .. .. .. 1.8 Central African Republic .. .. .. .. .. .. 12.0 .. Chad .. .. .. .. .. .. .. 2.5 Comoros .. .. .. .. .. .. .. .. Congo, Dem. Rep. .. .. 3.7 .. .. .. 320.0 36.0 Congo, Rep. 71.1 8.5 64.2 25.3 81.8 56.3 .. 0.0 Côte d'Ivoire 39.8 20.9 18.6 4.5 6.5 15.1 .. 81.9 Djibouti .. .. .. .. .. .. .. 7.3 Equatorial Guinea .. .. .. .. .. .. 9.3 0.0 Eritrea .. .. .. .. .. .. 0.0 12.3 Ethiopia .. .. 10.0 .. .. .. .. 54.5 Gabon 58.0 34.5 17.7 7.8 22.9 9.7 0.0 .. Gambia, The .. .. .. .. .. .. .. 0.0 Ghana 86.2 24.4 15.6 9.7 26.6 29.5 100.0 34.3 Guinea .. .. .. .. .. .. .. 6.7 Guinea-Bissau .. .. .. .. .. .. .. 3.9 Kenya 27.6 40.5 17.0 7.3 65.7 14.7 0.0 57.0 Lesotho 44.3 13.9 .. 7.2 30.9 .. .. ­0.1 Liberia 59.1 .. .. 5.6 66.5 97.1 17.0 16.5 Madagascar 54.6 92.1 .. 13.7 29.3 18.6 .. 21.4 Malawi .. .. .. .. .. .. .. 2.1 Mali 55.7 48.4 .. 4.4 23.8 16.0 .. 11.8 Mauritania .. .. .. .. .. .. 30.1 26.4 Mauritius 42.9 19.2 .. 3.6 24.5 3.4 .. .. Mozambique 24.8 12.7 14.1 3.1 12.6 10.8 .. 54.6 Namibia .. .. 22.1 .. .. .. .. 0.8 Niger .. .. .. .. .. .. 110.0 1.7 Nigeria 75.9 7.7 27.1 26.8 85.7 60.9 280.0 66.9 Rwanda .. .. .. .. .. .. .. 26.4 São Tomé and Príncipe .. .. .. .. .. .. .. 0.0 Senegal 57.7 9.4 25.5 11.8 55.4 24.7 .. 90.2 Seychelles .. .. .. .. .. .. 0.0 .. Sierra Leone 53.4 14.8 .. 15.9 81.8 44.8 1.2 18.2 Somalia .. .. .. .. .. .. 0.0 .. South Africa 20.8 15.8 8.7 2.2 18.4 10.9 .. 5.2 Sudan .. .. 15.2 .. .. .. 478.0 2.0 Swaziland .. .. .. .. .. .. 3.8 .. Tanzania .. .. 20.9 .. .. .. .. 61.4 Togo .. .. 45.7 .. .. .. .. 21.6 Uganda .. .. .. .. .. .. 810.8 158.0 Zambia 11.9 97.0 6.4 4.2 13.7 19.5 .. 1.5 Zimbabwe .. .. 7.2 .. .. .. .. 0.2 NORTH AFRICA 667.2 Algeria 48.1 49.1 17.9 5.1 39.5 7.4 .. 0.4 Egypt, Arab Rep. 19.8 142.7 10.9 8.7 29.9 14.3 469.0 330.9 Libya .. .. 7.3 .. .. .. .. 3.0 Morocco 37.0 18.8 18.5 2.5 18.0 6.5 .. 244.1 Tunisia .. .. 12.5 .. .. .. .. 67.4 a. Shares may not sum to 100 percent because other sources of generated electricity (such as geothermal, solar, and wind) are not shown. b. Data are for the most recent year available during the period specified. 110 Part III. Development outcomes INFRASTRUCTURE Participating in growth 7.1 Table Education Primary education Literacy rate (%) Gross enrollment ratio Net enrollment ratio Student- Youth (ages 15­24) Adult (ages 15 and older) (% of relevant age group) (% of relevant age group) teacher Total Male Female Total Male Female Total Male Female Total Male Female ratio 2007 2007 2007 2007 2007 2007 2007-08 a 2007-08a 2007-08a 2007-08a 2007-08a 2007-08a 2007-08a SUB­SAHARAN AFRICA Angola .. .. .. .. .. .. .. .. .. .. .. .. .. Benin 52.4 63.4 41.1 40.5 53.1 27.9 .. .. .. .. .. .. .. Botswana 94.1 92.9 95.3 82.9 82.8 82.9 .. .. .. .. .. .. .. Burkina Faso 39.3 46.7 33.1 28.7 36.7 21.6 71.0 76.0 65.9 58.1 62.3 53.9 48.9 Burundi .. .. .. .. .. .. 114.5 118.7 110.3 81.2 82.2 80.3 52.0 Cameroon .. .. .. .. .. .. 109.6 117.9 101.3 .. .. .. 44.4 Cape Verde 97.3 96.6 97.9 83.8 89.4 78.8 101.5 104.6 98.3 84.5 85.3 83.7 24.9 Central African Republic .. .. .. .. .. .. 73.6 86.2 61.2 56.2 64.7 47.9 89.6 Chad 44.4 53.4 35.4 31.8 43.0 20.8 74.0 87.1 60.8 .. .. .. 60.4 Comoros 89.5 92.1 86.8 75.1 80.3 69.8 .. .. .. .. .. .. .. Congo, Dem. Rep. .. .. .. .. .. .. 85.1 94.1 76.2 .. .. .. 38.3 Congo, Rep. .. .. .. .. .. .. 105.9 110.0 101.8 53.8 56.0 51.6 58.5 Côte d'Ivoire .. .. .. .. .. .. 72.1 80.6 63.7 .. .. .. 41.0 Djibouti .. .. .. .. .. .. 55.5 58.9 52.1 45.3 47.9 42.7 34.0 Equatorial Guinea .. .. .. .. .. .. 124.2 127.5 121.0 67.1 68.0 66.2 27.6 Eritrea .. .. .. .. .. .. 54.9 59.9 49.9 41.2 43.9 38.5 47.9 Ethiopia .. .. .. .. .. .. 90.8 96.7 84.8 71.4 74.3 68.5 .. Gabon 97.0 98.0 95.9 86.2 90.2 82.2 .. .. .. .. .. .. .. Gambia, The .. .. .. .. .. .. 83.4 80.4 86.4 66.5 63.8 69.3 40.9 Ghana 77.8 79.7 75.8 65.0 71.7 58.3 103.7 104.4 103.1 72.9 72.5 73.3 32.2 Guinea .. .. .. .. .. .. 90.8 97.8 83.6 73.6 78.6 68.5 45.4 Guinea-Bissau .. .. .. .. .. .. .. .. .. .. .. .. .. Kenya .. .. .. .. .. .. 112.6 113.5 111.8 86.3 86.3 86.3 45.6 Lesotho .. .. .. .. .. .. .. .. .. .. .. .. .. Liberia 71.8 67.9 75.7 55.5 60.2 50.9 83.4 88.2 78.5 30.9 31.9 29.8 23.8 Madagascar .. .. .. .. .. .. 141.4 143.7 139.1 98.5 98.0 98.9 48.7 Malawi 83.0 83.7 82.3 71.8 79.2 64.6 116.5 114.4 118.6 87.0 84.0 90.1 66.8 Mali .. .. .. .. .. .. 83.1 92.3 74.0 63.0 69.8 56.2 51.7 Mauritania 66.4 70.0 62.5 55.8 63.3 48.3 103.2 100.4 106.3 80.4 78.1 82.9 42.5 Mauritius 96.2 95.3 97.2 87.4 90.2 84.7 101.4 101.4 101.4 95.4 94.7 96.1 21.5 Mozambique 52.9 58.4 47.5 44.4 57.2 33.0 111.0 118.8 103.3 .. .. .. 64.8 Namibia 92.7 90.9 94.4 88.0 88.6 87.4 109.2 109.7 108.8 86.5 84.1 89.0 29.9 Niger .. .. .. .. .. .. 53.3 60.8 45.5 44.9 51.1 38.3 39.7 Nigeria 86.7 88.6 84.7 72.0 80.1 64.1 .. .. .. .. .. .. .. Rwanda .. .. .. .. .. .. 147.4 146.1 148.6 93.6 92.3 94.9 69.3 São Tomé and Príncipe 95.2 95.0 95.5 87.9 93.4 82.7 130.2 131.4 129.0 97.1 97.8 96.5 .. Senegal .. .. .. .. .. .. 83.5 83.6 83.5 71.9 72.0 71.9 34.2 Seychelles .. .. .. .. .. .. 125.3 126.1 124.6 .. .. .. 12.5 Sierra Leone 54.1 64.4 43.9 38.1 50.0 26.8 147.1 154.9 139.3 .. .. .. 43.7 Somalia .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa 95.4 94.6 96.3 88.0 88.9 87.2 102.5 104.3 100.7 85.8 85.6 86.0 31.0 Sudan .. .. .. .. .. .. 66.4 71.3 61.2 .. .. .. 36.7 Swaziland .. .. .. .. .. .. 113.4 117.8 109.0 87.0 86.2 87.8 32.4 Tanzania 77.5 78.9 76.2 72.3 79.0 65.9 112.4 112.2 112.6 .. .. .. 52.6 Togo .. .. .. .. .. .. 97.1 104.2 90.0 77.2 82.3 72.2 39.1 Uganda 86.3 88.3 84.2 73.6 81.8 65.5 116.2 115.7 116.7 94.6 93.2 96.1 57.0 Zambia 75.1 82.4 67.8 70.6 80.8 60.7 119.0 120.7 117.2 94.0 93.7 94.4 49.3 Zimbabwe 91.2 94.1 88.3 91.2 94.1 88.3 .. .. .. .. .. .. .. NORTH AFRICA Algeria 92.5 94.2 90.6 75.4 84.3 66.4 109.7 113.2 106.0 95.4 96.1 94.5 24.0 Egypt, Arab Rep. .. .. .. .. .. .. 104.7 107.5 101.7 95.7 97.9 93.5 27.1 Libya 98.9 99.7 98.0 86.8 94.5 78.4 .. .. .. .. .. .. .. Morocco 75.1 83.8 66.5 55.6 68.7 43.2 107.2 113.0 101.3 88.8 91.2 86.4 27.4 Tunisia 95.7 97.0 94.3 77.7 86.4 69.0 104.7 106.0 103.2 95.0 94.6 95.5 18.2 (continued) HUMAN DEVELOPMENT Part III. Development outcomes 111 Participating in growth 7.1 Table Education (continued) Public spending on Secondary education Tertiary education education (%) Gross enrollment ratio Net enrollment ratio Student- Gross enrollment ratio Share of (% of relevant age group) (% of relevant age group) teacher (% of relevant age group) government Share of Total Male Female Total Male Female ratio Total Male Female expenditure GDP 2007-08a 2007-08a 2007-08a 2007-08a 2007-08a 2007-08a 2007-08a 2007-08a 2007-08a 2007-08a 2007 2007 SUB­SAHARAN AFRICA Angola .. .. .. .. .. .. .. .. .. .. .. .. Benin .. .. .. .. .. .. .. .. .. .. .. .. Botswana .. .. .. .. .. .. .. .. .. .. 21.0 8.1 Burkina Faso 18.1 20.7 15.3 14.1 16.2 11.9 30.3 3.0 4.0 2.0 .. .. Burundi 15.2 17.7 12.8 .. .. .. 28.0 1.9 2.6 1.2 .. .. Cameroon 25.2 28.0 22.2 .. .. .. .. 7.2 8.0 6.3 17.0 3.9 Cape Verde 79.3 72.7 86.0 60.7 56.8 64.6 19.0 8.9 8.1 9.8 16.4 5.7 Central African Republic .. .. .. .. .. .. .. .. .. .. .. .. Chad 18.8 26.0 11.6 .. .. .. 32.9 .. .. .. .. .. Comoros .. .. .. .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. 33.4 43.6 23.1 .. .. .. 15.7 4.1 6.0 2.1 .. .. Congo, Rep. .. .. .. .. .. .. .. .. .. .. .. .. Côte d'Ivoire .. .. .. .. .. .. .. 7.9 10.5 5.3 .. .. Djibouti 29.5 34.7 24.2 24.4 28.4 20.4 34.3 2.6 3.1 2.1 22.8 8.6 Equatorial Guinea .. .. .. .. .. .. .. .. .. .. .. .. Eritrea 29.2 34.3 24.2 25.1 29.3 21.0 49.3 .. .. .. .. .. Ethiopia 30.5 36.5 24.4 .. .. .. .. 2.7 4.1 1.4 23.3 5.5 Gabon .. .. .. .. .. .. .. .. .. .. .. .. Gambia, The 48.6 49.7 47.5 40.1 40.1 40.0 22.7 .. .. .. .. .. Ghana 53.3 56.5 50.1 44.9 47.1 42.7 17.5 5.8 7.5 4.1 .. .. Guinea 37.6 47.8 27.0 30.1 37.4 22.4 38.2 .. .. .. .. .. Guinea-Bissau .. .. .. .. .. .. .. .. .. .. .. .. Kenya 52.8 56.3 49.3 44.8 47.0 42.6 26.6 3.5 4.4 2.5 .. .. Lesotho .. .. .. .. .. .. .. .. .. .. .. .. Liberia .. .. .. .. .. .. .. .. .. .. .. .. Madagascar 26.4 27.0 25.7 21.2 21.1 21.3 24.3 3.2 3.4 3.0 16.4 3.4 Malawi 28.3 30.8 25.7 23.9 25.0 22.8 .. 0.5 0.7 0.3 .. .. Mali 31.6 38.6 24.7 .. .. .. 35.6 4.4 .. .. .. .. Mauritania 25.2 26.7 23.6 16.8 17.8 15.7 26.6 4.0 .. .. .. .. Mauritius .. .. .. .. .. .. .. 14.0 12.9 15.0 .. .. Mozambique 18.3 21.2 15.5 2.6 2.8 2.3 36.9 .. .. .. .. .. Namibia 59.0 54.4 63.6 49.6 44.4 54.8 24.6 .. .. .. .. .. Niger 10.6 13.2 8.1 9.0 11.1 6.9 27.3 1.0 1.7 0.5 .. .. Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 18.1 19.1 17.1 .. .. .. 22.0 .. .. .. 19.0 4.9 São Tomé and Príncipe 46.3 44.7 47.9 38.1 36.1 40.2 .. .. .. .. .. .. Senegal 26.3 29.8 22.7 22.2 25.0 19.4 25.2 7.7 10.0 5.5 .. .. Seychelles 111.8 105.3 119.1 94.3 .. .. 13.3 .. .. .. .. .. Sierra Leone 31.6 37.5 25.8 22.8 26.7 19.0 23.9 .. .. .. .. .. Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 97.1 94.8 99.4 73.4 71.1 75.7 29.0 .. .. .. 17.4 5.4 Sudan 33.4 34.6 32.1 19.0 .. .. 18.5 .. .. .. .. .. Swaziland 54.4 57.5 51.3 29.2 31.6 26.8 19.1 .. .. .. .. .. Tanzania .. .. .. 25.8 27.6 24.0 .. 1.5 2.0 1.0 .. .. Togo 39.3 51.6 27.2 .. .. .. 35.5 5.2 .. .. 17.2 3.7 Uganda 22.5 24.6 20.4 18.9 19.9 17.9 18.4 .. .. .. .. .. Zambia 43.1 45.7 40.6 40.9 43.7 38.1 42.6 .. .. .. .. 1.5 Zimbabwe .. .. .. .. .. .. .. .. .. .. .. .. NORTH AFRICA Algeria .. .. .. .. .. .. .. 24.0 20.1 28.1 .. .. Egypt, Arab Rep. .. .. .. .. .. .. .. .. .. .. 12.6 3.8 Libya .. .. .. .. .. .. .. .. .. .. .. .. Morocco 55.8 60.1 51.4 .. .. .. .. 11.3 12.0 10.7 .. .. Tunisia 88.0 .. .. .. .. .. 15.9 30.8 24.7 37.2 .. .. a. Data are for the most recent year available during the period specified. 112 Part III. Development outcomes HUMAN DEVELOPMENT Participating in growth 7.2 Table Health Mortality Diseases Life expectancy at birth Infant mortality Maternal mortality Prevalence Malaria (years) Under-five rate ratio, modeled of HIV Incidence of Clinical mortality rate (per 1,000 estimate (per (% of ages tuberculosis (per cases Reported Total Male Female (per 1,000) live births) 100,000 live births) 15­49) 100,000 people) reported deaths 2007­08 a 2007­08 a 2007­08 a 2007 2007 2005 2007 2007 2008 2008 SUB­SAHARAN AFRICA 51.5 50.5 52.6 146 88 899 5.0 369 25,729,664 91,244 Angola 47.3 45.3 49.3 158 116 1,400 2.1 287 1,377,992 9,465 Benin 61.6 60.5 62.8 123 78 840 1.2 91 .. .. Botswana 50.6 50.5 50.7 40 33 380 23.9 731 1,201 12 Burkina Faso 52.2 50.7 53.8 191 104 700 1.6 226 36,514 7,834 Burundi 50.6 49.2 52.2 180 108 1,100 2.0 367 876,741 226 Cameroon 50.4 50.0 50.8 148 87 1,000 5.1 192 1,650,749 7,673 Cape Verde 71.2 68.6 73.9 32 24 210 .. 151 35 2 Central African Republic 44.7 43.3 46.1 172 113 980 6.3 345 152,260 456 Chad 50.6 49.3 52.0 209 124 1,500 3.5 299 57,644 1,018 Comoros 65.1 63.0 67.4 66 49 400 <0.1 42 .. 47 Congo, Dem. Rep. 46.4 45.2 47.7 161 108 1,100 .. 392 1,462,300 18,928 Congo, Rep. 53.7 52.8 54.7 125 79 740 3.5 403 .. .. Côte d'Ivoire 57.8 56.5 59.1 127 89 810 3.9 421 1,343,654 1,249 Djibouti 54.8 53.6 56.0 127 84 650 3.1 813 119 .. Equatorial Guinea 50.5 49.3 51.7 206 124 680 3.4 256 50,758 .. Eritrea 57.9 55.6 60.3 70 46 450 1.3 95 4,702 19 Ethiopia 55.4 54.0 56.9 119 75 720 2.1 378 458,561 1,169 Gabon 60.7 59.5 62.1 91 60 520 5.9 406 40,701 156 Gambia, The 56.1 54.5 57.8 109 82 690 0.9 258 10,910 403 Ghana 56.8 55.9 57.7 115 73 560 1.9 203 827,438 3,889 Guinea 58.1 56.1 60.1 150 93 910 1.6 287 33,405 441 Guinea-Bissau 48.0 46.5 49.6 198 118 1,100 1.8 220 11,299 487 Kenya 54.1 53.0 55.2 121 80 560 .. 353 839,904 .. Lesotho 42.6 42.9 42.3 84 68 960 23.2 637 .. .. Liberia 58.4 57.1 59.8 133 93 1,200 1.7 277 606,952 345 Madagascar 60.5 58.9 62.2 112 70 510 0.1 251 89,138 276 Malawi 48.3 48.1 48.4 111 71 1,100 11.9 346 4,986,779 7,748 Mali 54.3 52.1 56.6 196 117 970 1.5 319 .. 1,227 Mauritania 64.1 62.4 66.0 119 75 820 0.8 318 302 .. Mauritius 72.4 69.1 75.9 15 13 15 1.7 22 .. .. Mozambique 42.1 41.7 42.4 169 115 520 12.5 431 4,831,491 4,424 Namibia 52.8 52.5 53.1 68 47 210 15.3 767 4,907 171 Niger 56.9 57.8 56.0 176 83 1,800 0.8 174 413,252 2,691 Nigeria 46.8 46.4 47.3 189 97 1,100 3.1 311 143,079 8,677 Rwanda 50.2 48.5 52.1 181 109 1,300 2.8 397 228,015 563 São Tomé and Príncipe 65.4 63.6 67.4 99 64 .. .. 101 1,572 16 Senegal 55.7 54.2 57.3 114 59 980 1.0 272 202,466 722 Seychelles 73.2 68.9 77.7 13 12 .. .. 32 .. .. Sierra Leone 47.7 46.4 49.0 262 155 2,100 1.7 574 154,459 871 Somalia 48.1 46.9 49.4 142 88 1,400 0.5 249 23,905 21 South Africa 50.5 49.0 52.0 59 46 400 18.1 948 7,796 43 Sudan 58.3 56.8 59.9 109 70 450 1.4 243 457,362c 1,125c Swaziland 46.4 47.0 45.7 91 66 390 26.1 1,198 58 5 Tanzania 55.9 55.1 56.8 116 73 950 6.2 297 67 29 Togo 62.7 61.0 64.5 100 65 510 3.3 429 273,471 2,663 Uganda 53.0 52.4 53.6 130 82 550 5.4 330 894,505 2,372 Zambia 45.9 45.4 46.5 170 103 830 15.2 506 3,080,301 3,781 Zimbabwe 45.1 44.8 45.4 90 59 880 15.3 782 92,900 .. NORTH AFRICA 71.1 69.4 73.0 35 30 156 42 418 .. Algeria 72.3 70.9 73.7 37 33 180 0.1 57 196 .. Egypt, Arab Rep. 70.2 68.5 72.0 36 30 130 .. 21 80 .. Libya 74.2 71.7 76.9 18 17 97 .. 17 .. .. Morocco 71.1 69.0 73.4 34 32 240 0.1 92 142 .. Tunisia 74.3 72.4 76.3 21 18 100 0.1 26 .. .. (continued) HUMAN DEVELOPMENT Part III. Development outcomes 113 Participating in growth 7.2 Table Health (continued) Prevention and treatment Child Tuberculosis Children with immunization Contraceptive use Births Tuberculosis treatment fever receiving rate (% of (% of married attended Children sleeping cases detected success rate any antimalarial children ages Malnutrition (% of women ages 15­49) by skilled under insecticide- under DOTS (% of treatment same 12­23 months) children under age 5) health staff Any Modern treated nets (% of estimated registered or next day Measles DPT b Stunting Underweight (% of total) method method (% of under age 5) cases) cases) (% of under age 5) 2007 2007 2000­08a 2000­08a 2000­08a 2000­08 a 2000­08a 2000­08 a 2007 2006 2000­08a SUB­SAHARAN AFRICA 73 73 .. .. .. .. 47.1 75.5 .. Angola 88 83 50.8 27.5 47.3 6.2 4.5 17.7 101.8 17.7 28.0 Benin 61 67 39.1 21.5 77.7 17.0 5.9 20.2 .. .. 54.0 Botswana 90 97 29.1 10.7 94.2 44.4 42.1 .. 57.2 72.5 .. Burkina Faso 94 99 43.1 35.2 53.5 17.4 13.3 9.6 18.4 72.8 48.0 Burundi 75 74 63.1 38.9 33.6 19.7 8.5 8.3 26.8 82.6 30.0 Cameroon 74 82 35.4 15.1 63.0 29.2 12.0 13.1 91.4 74.2 58.0 Cape Verde 74 81 .. .. 77.5 61.3 .. .. 44.0 78.6 .. Central African Republic 62 54 44.6 21.8 53.4 19.0 8.6 15.1 .. .. 57.0 Chad 23 20 44.8 33.9 14.4 2.8 1.7 .. 18.5 54.2 53.0 Comoros 65 75 46.9 25.0 61.8 25.7 19.3 9.3 .. .. 62.7 Congo, Dem. Rep. 79 87 44.4 33.6 74.0 20.6 5.8 5.8 60.7 86.2 29.8 Congo, Rep. 67 80 31.2 11.8 83.4 44.3 12.7 6.1 55.7 52.5 48.0 Côte d'Ivoire 67 76 40.1 16.7 56.8 12.9 8.0 5.9 42.2 73.2 36.0 Djibouti 74 88 .. .. 60.6 17.8 17.1 1.3 42.3 77.5 9.5 Equatorial Guinea 51 33 35.0 10.6 64.6 10.1 6.1 0.7 .. .. 48.6 Eritrea 95 97 43.7 34.5 28.3 8.0 5.1 4.2 34.5 89.7 3.6 Ethiopia 65 73 50.7 34.6 5.7 14.7 13.7 33.1 28.1 84.1 9.5 Gabon 55 38 26.3 8.8 85.5 32.7 11.8 .. 66.2 46.5 .. Gambia, The 85 90 27.6 15.8 56.8 17.5 12.7 49.0 63.9 57.7 62.6 Ghana 95 94 28.0 13.9 49.7 23.5 16.6 28.2 35.9 76.4 24.0 Guinea 71 75 39.3 22.5 38.0 9.1 4.0 0.3 53.5 75.4 43.5 Guinea-Bissau 76 63 36.1 21.9 38.8 10.3 6.1 39.0 .. .. 45.7 Kenya 80 81 35.8 16.5 41.6 39.3 31.5 6.0 72.1 85.1 24.0 Lesotho 85 83 45.2 16.6 55.4 37.3 35.2 .. 16.5 66.5 .. Liberia 95 88 39.4 20.4 46.4 11.4 10.3 3.0 .. .. 58.8 Madagascar 81 82 52.8 36.8 51.3 27.1 16.7 0.2 69.5 78.0 34.2 Malawi 83 87 52.5 18.4 53.6 41.0 38.4 23.0 41.4 78.0 23.9 Mali 68 68 38.5 27.9 49.0 8.2 6.3 27.1 22.9 76.0 31.7 Mauritania 67 75 39.5 30.4 60.9 9.3 8.0 2.1 39.3 40.6 20.7 Mauritius 98 97 .. .. 98.4 75.8 39.3 .. 68.7 91.7 .. Mozambique 77 72 47.0 21.2 47.7 16.5 11.7 22.8 49.0 82.7 23.0 Namibia 69 86 29.6 17.5 81.4 55.1 53.5 .. 83.6 76.4 9.8 Niger 47 39 54.8 39.9 32.9 11.2 5.0 7.4 52.8 76.5 33.0 Nigeria 62 54 43.0 27.2 35.2 14.7 9.1 1.2 22.6 76.4 33.3 Rwanda 99 97 51.7 18.0 52.1 36.4 26.1 24.0 25.4 86.4 5.6 São Tomé and Príncipe 86 97 35.2 10.1 80.7 29.3 27.4 54.0 .. .. 24.7 Senegal 84 94 20.1 14.5 51.9 11.8 10.0 31.0 48.3 76.0 22.0 Seychelles 99 99 .. .. .. .. .. .. .. .. .. Sierra Leone 67 64 46.9 28.3 43.2 8.2 6.0 25.9 36.9 87.1 30.1 Somalia 34 39 42.1 32.8 33.0 14.6 1.2 9.2 63.9 89.0 7.9 South Africa 83 97 .. .. 92.0 60.3 60.3 .. 78.1 73.8 .. Sudan 79 84 47.6 38.4 49.2 7.6 5.7 27.6 30.6 81.7 .. Swaziland 91 95 36.6 9.1 69.0 50.6 46.8 0.6 54.7 42.5 0.6 Tanzania 90 83 44.4 16.7 43.4 26.4 19.5 25.7 50.5 84.7 56.7 Togo 80 88 .. .. 62.0 16.8 11.1 38.4 15.1 67.3 47.7 Uganda 68 64 44.8 19.0 42.1 23.7 17.9 9.7 50.9 69.6 61.8 Zambia 85 80 52.5 23.3 46.5 40.8 26.5 41.1 58.3 84.9 43.3 Zimbabwe 66 62 35.8 14.0 68.5 60.2 57.9 2.9 26.6 60.0 4.7 NORTH AFRICA 96 97 24.3 4.6 70.4 59.3 53.1 .. .. .. .. Algeria 92 95 21.6 10.2 95.2 61.4 52.0 .. 98.4 90.8 .. Egypt, Arab Rep. 97 98 23.8 5.4 78.9 60.3 57.6 .. 72.2 86.9 .. Libya 98 98 .. .. .. .. .. .. 161.8 76.5 .. Morocco 95 95 23.1 9.9 62.6 63.0 52.0 .. 92.8 86.6 .. Tunisia 98 98 .. .. 89.9 60.2 51.5 .. 78.2 90.6 .. 114 Part III. Development outcomes HUMAN DEVELOPMENT Water and sanitation Human resources Population with sustainable access Population with sustainable access Health workers to an improved water source to improved sanitation (per 1,000 people) (% of total (% of urban (% of rural (% of total (% of urban (% of rural Nurses and Community population) population) population) population) population) population) Physicians midwives workers 2006 2006 2006 2006 2006 2006 2005 2005 2005 58 81 46 31 43 24 .. .. .. 51 62 39 50 79 16 0.1 1.4 .. 65 78 57 30 59 11 0.0 0.8 0.0 96 100 90 47 60 30 0.4 2.7 .. 72 97 66 13 41 6 0.1 0.5 0.1 71 84 70 41 44 41 0.0 0.2 0.1 70 88 47 51 58 42 0.2 1.6 .. .. .. .. .. .. .. 0.5 0.9 0.1 66 90 51 31 40 25 0.1 0.4 0.0 48 71 40 9 23 4 0.0 0.3 0.0 85 91 81 35 49 26 0.2 0.7 0.1 46 82 29 31 42 25 0.1 0.5 .. 71 95 35 20 19 21 0.2 1.0 0.0 81 98 66 24 38 12 0.1 0.6 .. 92 98 54 67 76 11 0.2 0.4 0.0 43 45 42 51 60 46 0.3 0.5 0.6 60 74 57 5 14 3 0.1 0.6 .. 42 96 31 11 27 8 0.0 0.2 0.2 87 95 47 36 37 30 0.3 5.0 .. 86 91 81 52 50 55 0.1 1.3 0.3 80 90 71 10 15 6 0.2 0.9 .. 70 91 59 19 33 12 0.1 0.5 0.0 57 82 47 33 48 26 0.1 0.7 1.5 57 85 49 42 19 48 0.1 1.2 .. 78 93 74 36 43 34 0.1 0.6 .. 64 72 52 32 49 7 0.0 0.3 0.0 47 76 36 12 18 10 0.3 0.3 0.0 76 96 72 60 51 62 0.0 0.6 .. 60 86 48 45 59 39 0.1 0.6 0.0 60 70 54 24 44 10 0.1 0.6 0.1 100 100 100 94 95 94 1.1 3.7 0.2 42 71 26 31 53 19 0.0 0.3 .. 93 99 90 35 66 18 0.3 3.1 .. 42 91 32 7 27 3 0.0 0.2 .. 47 65 30 30 35 25 0.3 1.7 0.9 65 82 61 23 34 20 0.1 0.4 1.4 86 88 83 24 29 18 0.5 1.9 0.9 77 93 65 28 54 9 0.1 0.3 .. .. 100 .. .. .. 100 1.5 7.9 .. 53 83 32 11 20 5 0.0 0.5 0.1 29 63 10 23 51 7 .. .. .. 93 100 82 59 66 49 0.8 4.1 0.2 70 78 64 35 50 24 0.3 0.9 0.1 60 87 51 50 64 46 0.2 6.3 3.7 55 81 46 33 31 34 0.0 0.4 .. 59 86 40 12 24 3 0.0 0.4 0.1 64 90 60 33 29 34 0.1 0.7 .. 58 90 41 52 55 51 0.1 2.0 .. 81 98 72 46 63 37 0.2 0.7 0.0 92 96 87 75 90 59 .. .. .. 85 87 81 94 98 87 1.1 2.2 0.0 98 99 98 66 85 52 2.4 3.4 .. .. .. .. 97 97 96 1.3 4.8 .. 83 100 58 72 85 54 0.5 0.8 .. 94 99 84 85 96 64 1.3 2.9 .. (continued) HUMAN DEVELOPMENT Part III. Development outcomes 115 Participating in growth 7.2 Table Health (continued) Health expenditure Private prepaid Share of GDP (%) Share of total health expenditure (%) Out-of-pocket plans External (% of private (% of private Health resources expenditure expenditure expenditure Total Public Private Public Private for health on health) on health) per capita ($) 2006 2006 2006 2006 2006 2006 2006 2006 2006 SUB­SAHARAN AFRICA 5.7 2.4 3.3 41.5 58.5 .. 46.9 .. 54 Angola 2.6 2.3 0.3 86.8 13.2 7.0 100.0 0.0 71 Benin 4.7 2.4 2.3 50.2 49.8 21.0 94.9 5.1 26 Botswana 7.1 5.4 1.7 76.5 23.5 5.8 27.5 5.2 379 Burkina Faso 6.3 3.6 2.7 56.9 43.1 32.9 91.5 2.1 27 Burundi 8.7 0.7 8.0 8.6 91.4 47.5 57.4 .. 10 Cameroon 4.6 1.0 3.6 21.2 78.8 8.0 94.8 .. 45 Cape Verde 4.9 3.8 1.1 78.3 21.7 17.5 99.7 0.3 112 Central African Republic 4.0 1.5 2.5 38.3 61.7 21.2 95.0 .. 14 Chad 4.9 2.6 2.3 53.9 46.1 17.7 96.2 0.4 29 Comoros 3.2 1.8 1.4 55.1 44.9 31.9 100.0 0.0 16 Congo, Dem. Rep. 6.8 1.3 5.5 18.7 81.3 51.9 48.9 .. 10 Congo, Rep. 2.1 1.5 0.6 71.7 28.3 3.4 100.0 .. 44 Côte d'Ivoire 3.8 0.9 2.9 23.6 76.4 8.3 87.8 12.2 35 Djibouti 6.8 5.0 1.8 74.1 25.9 30.1 98.6 1.4 63 Equatorial Guinea 2.1 1.7 0.4 80.4 19.6 3.5 75.6 0.0 440 Eritrea 3.6 1.7 1.9 45.9 54.1 37.6 100.0 0.0 8 Ethiopia 3.9 2.3 1.6 59.3 40.7 42.7 80.6 3.0 7 Gabon 4.5 3.3 1.2 73.0 27.0 1.8 100.0 .. 351 Gambia, The 5.0 2.8 2.2 56.8 43.2 34.7 71.2 4.6 15 Ghana 5.1 1.7 3.4 34.2 65.8 22.6 77.8 6.0 33 Guinea 5.8 0.8 5.0 14.1 85.9 11.8 99.5 0.0 20 Guinea-Bissau 5.8 1.5 4.3 26.3 73.7 33.4 55.8 0.0 12 Kenya 4.6 2.2 2.4 47.8 52.2 14.9 80.0 6.9 29 Lesotho 6.8 4.0 2.8 58.9 41.1 14.3 68.9 .. 51 Liberia 4.8 1.2 3.6 25.8 74.2 50.7 65.7 0.0 7 Madagascar 3.2 2.0 1.2 62.8 37.2 49.4 52.5 10.7 9 Malawi 12.9 8.9 4.0 69.0 31.0 59.6 28.4 15.7 21 Mali 5.8 2.9 2.9 49.6 50.4 17.6 99.5 0.5 31 Mauritania 2.2 1.5 0.7 69.5 30.5 18.0 100.0 0.0 19 Mauritius 3.9 2.0 1.9 51.1 48.9 1.0 80.6 10.0 230 Mozambique 5.0 3.5 1.5 70.8 29.2 60.3 40.6 0.6 16 Namibia 8.7 3.8 4.9 43.5 56.5 22.4 5.7 64.0 281 Niger 5.9 3.2 2.7 54.7 45.3 32.8 96.5 3.0 16 Nigeria 3.8 1.1 2.7 29.7 70.3 5.9 90.4 6.7 33 Rwanda 10.9 4.6 6.3 42.5 57.5 52.4 38.6 9.2 33 São Tomé and Príncipe 6.3 5.4 0.9 85.0 15.0 50.5 100.0 0.0 49 Senegal 5.8 3.3 2.5 56.9 43.1 12.3 77.0 19.5 44 Seychelles 6.3 4.7 1.6 75.1 24.9 3.4 62.5 0.0 565 Sierra Leone 4.0 1.5 2.5 36.4 63.6 33.5 56.4 3.7 12 Somalia .. .. .. .. .. .. .. .. .. South Africa 8.0 3.0 5.0 37.7 62.3 0.9 17.5 77.7 425 Sudan 3.8 1.4 2.4 36.8 63.2 6.5 100.0 .. 37 Swaziland 6.3 4.1 2.2 65.8 34.2 12.3 41.4 18.5 155 Tanzania 6.4 3.7 2.7 57.8 42.2 43.9 54.3 7.7 23 Togo 6.0 1.3 4.7 21.2 78.8 12.3 84.2 4.3 21 Uganda 7.0 1.8 5.2 25.4 74.6 31.2 51.0 0.2 24 Zambia 6.2 3.8 2.4 60.7 39.3 38.1 67.2 3.7 58 Zimbabwe 9.3 4.5 4.8 48.7 51.3 17.3 50.3 28.8 38 NORTH AFRICA 4.8 2.5 2.4 51.2 48.8 .. 88.6 .. 117 Algeria 4.2 3.4 0.8 81.1 18.9 0.1 94.6 5.2 148 Egypt, Arab Rep. 6.3 2.6 3.7 41.4 58.6 0.8 94.9 0.2 92 Libya 2.4 1.6 0.8 66.3 33.7 0.0 100.0 0.0 219 Morocco 5.3 1.4 3.9 26.2 73.8 2.5 77.3 22.7 113 Tunisia 5.1 2.3 2.8 44.2 55.8 0.9 81.7 16.6 156 a. Data are for the most recent year available during the period specified. b. Diphtheria, pertussis, and tetanus toxoid. c. Data are for 15 northern states only. 116 Part III. Development outcomes HUMAN DEVELOPMENT Participating in growth 8.1 Table Rural development Rural population density Share of rural population Rural population poverty gap Rural population (%) (rural population below the national poverty line (%) Share of total per sq. km of Surveys Surveys Surveys Surveys population Annual growth arable land) 1990­99a 2000­07a 1990­99a 2000­07a 2007 2008 2007 2008 2007 Year Percent Year Percent Year Percent Year Percent SUB­SAHARAN AFRICA 64.0 63.5 1.7 1.7 .. .. .. .. .. Angola 44.2 43.3 0.7 0.6 235.1 .. .. .. .. Benin 59.2 58.8 2.5 2.5 184.0 1999 33.0 2003 46.0 1999 9.4 2003 14.0 Botswana 41.2 40.4 ­0.6 ­0.6 309.9 .. .. .. .. Burkina Faso 80.9 80.4 2.4 2.4 229.8 1998 61.1 2003 52.4 .. 2003 17.6 Burundi 89.9 89.6 2.7 2.6 708.2 1998 64.6 .. .. .. Cameroon 44.1 43.2 0.1 0.1 137.0 1996 59.6 2007 55.0 .. 2007 17.5 Cape Verde 41.1 40.4 ­0.3 ­0.4 404.4 .. .. .. .. Central African Republic 61.6 61.4 1.6 1.6 138.9 .. .. .. .. Chad 73.8 73.3 2.2 2.2 184.7 1996 67.0 .. 1996 26.3 .. Comoros 72.0 71.9 2.3 2.3 565.4 .. .. .. .. Congo, Dem. Rep. 66.7 66.0 1.9 1.9 620.8 .. 2004 75.7 .. 2004 34.9 Congo, Rep. 39.0 38.7 0.9 0.8 280.1 .. 2005 49.2 .. .. Côte d'Ivoire 51.9 51.2 1.0 1.0 372.8 .. .. .. .. Djibouti 13.1 12.7 ­1.3 ­1.3 8,394.0 .. .. .. .. Equatorial Guinea 60.8 60.6 2.4 2.3 300.3 .. .. .. .. Eritrea 79.7 79.3 2.6 2.6 603.1 .. .. .. .. Ethiopia 83.3 83.0 2.2 2.2 466.7 1996 47.0 2000 45.0 .. 2000 12.0 Gabon 15.4 15.0 ­1.2 ­1.3 67.6 .. .. .. .. Gambia, The 44.4 43.6 0.9 0.8 206.2 1998 61.0 2003 63.0 .. .. Ghana 50.7 50.0 0.7 0.6 282.9 1997 49.6 2005 39.2 .. 2005 13.5 Guinea 66.0 65.6 1.4 1.5 288.6 .. .. .. .. Guinea-Bissau 70.2 70.2 2.1 2.1 360.8 .. .. .. .. Kenya 78.7 78.4 2.3 2.3 568.0 1997 52.9 2005 49.1 1997 19.3 2005 17.5 Lesotho 75.3 74.5 ­0.4 ­0.4 503.2 1994 68.9 2002 60.5 .. .. Liberia 40.5 39.9 2.7 2.8 381.9 .. 2007 67.7 .. 2007 26.3 Madagascar 70.8 70.5 2.2 2.2 446.6 1999 76.7 2005 68.7 1999 36.1 .. Malawi 81.7 81.2 1.9 1.9 379.1 1998 66.5 2004 55.9 .. 2004 8.6 Mali 68.4 67.8 2.2 2.2 173.9 1998 75.9 .. .. .. Mauritania 59.2 59.0 2.2 2.2 410.6 1996 65.5 2000 61.2 .. .. Mauritius 57.6 57.5 0.5 0.5 806.6 .. .. .. .. Mozambique 63.9 63.2 0.7 0.7 307.1 1996 71.3 2002 55.3 1996 29.9 2002 20.9 Namibia 63.7 63.2 0.7 0.7 165.7 .. .. .. .. Niger 83.5 83.5 3.2 3.2 80.6 1993 66.0 .. .. .. Nigeria 52.4 51.6 0.9 0.8 212.3 1992 36.4 2003 63.8 .. 2003 26.6 Rwanda 81.9 81.7 2.3 2.4 645.6 .. 2005 62.5 .. .. São Tomé and Príncipe 40.3 39.4 ­0.2 ­0.2 706.8 .. .. .. .. Senegal 57.9 57.6 2.2 2.2 230.6 1992 40.4 .. 1992 16.4 .. Seychelles 46.1 45.7 ­0.5 0.5 3,923.4 .. .. .. .. Sierra Leone 62.6 62.2 2.3 2.0 376.8 .. 2003 78.5 .. 2003 34.6 Somalia 63.9 63.5 2.2 2.2 555.8 .. .. .. .. South Africa 39.7 39.3 ­0.2 0.5 131.1 .. .. .. .. Sudan 57.4 56.6 0.7 0.7 120.2 .. .. .. .. Swaziland 75.3 75.1 0.9 1.0 487.3 .. 2001 75.0 .. .. Tanzania 74.9 74.5 2.3 2.3 343.6 1991 40.8 2007 37.6 .. .. Togo 58.7 58.0 1.3 1.3 150.3 .. .. .. .. Uganda 87.2 87.0 3.1 3.1 485.6 1999 37.4 2005 34.2 1999 11.2 2005 9.7 Zambia 64.7 64.6 2.2 2.2 151.5 1998 83.1 2006 76.8 .. 2006 38.8 Zimbabwe 63.1 62.7 ­0.8 ­0.7 243.4 1996 48.0 .. .. .. NORTH AFRICA 47.4 47.2 1.1 1.1 .. .. .. .. .. Algeria 35.4 34.8 ­0.3 ­0.3 160.5 1995 30.3 .. 1995 4.5 .. Egypt, Arab Rep. 57.3 57.3 1.8 1.7 1,520.6 1996 23.3 .. .. .. Libya 22.6 22.5 1.1 1.1 79.6 .. .. .. .. Morocco 44.3 44.0 0.4 0.4 169.6 1999 27.2 .. 1999 6.7 .. Tunisia 33.9 33.5 ­0.2 ­0.2 125.7 1995 13.9 .. 1990 3.3 .. (continued) AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT Part III. Development outcomes 117 Participating in growth 8.1 Table Rural development (continued) Share of rural population with sustainable access (%) To an improved To improved To transportation water source sanitation facilities (within 2 km of an all-season road) 2006 2006 2000­07a SUB­SAHARAN AFRICA 46 24 .. Angola 39 16 .. Benin 57 11 32 Botswana 90 30 .. Burkina Faso 66 6 25 Burundi 70 41 .. Cameroon 47 42 22 Cape Verde 73 19 .. Central African Republic 51 25 .. Chad 40 4 .. Comoros 81 26 .. Congo, Dem. Rep. 29 25 26 Congo, Rep. 35 21 .. Côte d'Ivoire 66 12 .. Djibouti 54 11 .. Equatorial Guinea 42 46 .. Eritrea 57 3 .. Ethiopia 31 8 33 Gabon 47 30 .. Gambia, The 81 55 .. Ghana 71 6 .. Guinea 59 12 37 Guinea-Bissau 47 26 .. Kenya 49 48 .. Lesotho 74 34 .. Liberia 52 7 .. Madagascar 36 10 22 Malawi 72 62 .. Mali 48 39 .. Mauritania 54 10 .. Mauritius 100 94 .. Mozambique 26 19 12 Namibia 90 18 .. Niger 32 3 33 Nigeria 30 25 .. Rwanda 61 20 .. São Tomé and Príncipe 83 18 .. Senegal 65 9 .. Seychelles 75 100 .. Sierra Leone 32 5 22 Somalia 10 7 .. South Africa 82 49 .. Sudan 64 24 .. Swaziland 51 46 .. Tanzania 46 34 16 Togo 40 3 .. Uganda 60 34 .. Zambia 41 51 51 Zimbabwe 72 37 .. NORTH AFRICA 87 59 .. Algeria 81 87 .. Egypt, Arab Rep. 98 52 .. Libya 68 96 .. Morocco 58 54 .. Tunisia 84 64 .. a. Data are for the most recent year available during the period specified. 118 Part III. Development outcomes AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT Participating in growth 8.2 Table Agriculture Agriculture Cereal Trade value Gross production index (1999­2001=100) (thousands of metric tons) Agricultural Food added Agriculture Exports Imports Exports Imports (% of GDP) total Crop Livestock Food Cereal Production Exports Imports ($ millions) ($ millions) ($ millions) ($ millions) 2008a 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 SUB­SAHARAN AFRICA 14.6 .. .. .. .. .. .. 2,983 24,224 20,746 25,711 12,052 20,894 Angola 10.1 151 179 99 153 133 731 1,519 616 7 1,556 6 1,155 Benin .. 104 102 124 109 120 1,221 1 983 217 908 69 846 Botswana 1.6 111 110 111 111 170 48 18 145 151 518 133 398 Burkina Faso .. 123 120 129 122 136 3,736 5 111 319 247 70 177 Burundi .. 100 102 79 101 113 279 17 87 56 87 1 78 Cameroon 19.1 109 111 103 113 119 1,567 0 558 802 510 511 433 Cape Verde 8.1 117 102 132 117 11 12 0 86 1 193 0 160 Central African Republic 50.3 100 101 99 104 133 201 0 44 43 38 16 31 Chad 19 105 100 114 110 166 3,083 0 151 110 93 55 88 Comoros 45.8 105 106 98 105 100 21 0 50 8 45 8 41 Congo, Dem. Rep. .. 96 96 96 96 96 1,522 0 429 42 542 5 491 Congo, Rep. .. 122 114 156 122 181 10 5 227 65 376 28 329 Côte d'Ivoire 23.7 107 107 110 115 97 1,396 0 1,200 3,476 949 2,594 804 Djibouti .. 153 101 167 153 90 0 25 123 58 368 57 274 Equatorial Guinea 2 95 95 102 95 .. .. 12 21 4 84 4 39 Eritrea .. 102 104 100 102 86 177 0 214 3 78 3 77 Ethiopia 39.8 135 134 137 135 138 13,666 3 694 1,028 526 353 462 Gabon 4.6 103 103 102 103 126 34 3 113 57 318 3 259 Gambia, The 24.7 69 64 108 69 81 281 0 153 34 142 32 114 Ghana 32.2 124 125 107 124 109 1,852 0 836 1,482 1,044 1,439 968 Guinea 7.5 127 125 142 129 145 2,601 0 463 98 368 43 309 Guinea-Bissau 51.5 114 114 118 114 123 203 2 47 65 75 65 61 Kenya 18.9 134 123 150 136 126 3,755 0 1,032 2,164 1,043 641 885 Lesotho 6.5 88 77 98 88 62 73 55 41 4 55 1 51 Liberia .. 114 113 124 119 132 155 0 209 95 161 3 141 Madagascar 23.4 119 124 109 121 145 4,109 1 347 185 284 146 227 Malawi 28.5 137 137 136 138 144 3,637 4 123 773 151 256 109 Mali .. 127 122 138 145 147 3,510 410 267 312 326 113 268 Mauritania .. 112 103 114 112 105 155 6 394 19 462 18 375 Mauritius 4 101 88 146 101 252 0 0 295 358 553 323 432 Mozambique 25.4 114 112 133 99 83 2,173 26 811 334 482 150 426 Namibia 7.5 100 128 93 100 115 114 22 69 231 581 163 377 Niger .. 145 151 137 146 138 3,840 5 294 84 232 79 185 Nigeria 31.9 119 118 119 119 126 30,850 17 3,582 564 2,712 419 2,384 Rwanda 34.6 120 120 122 120 167 341 16 117 76 101 5 87 São Tomé and Príncipe .. 114 113 126 114 144 3 3 13 4 23 4 18 Senegal 13.6 75 65 117 74 70 885 0 1,594 297 1,270 196 1,140 Seychelles 2.3 97 97 98 98 .. .. 95 20 4 101 2 84 Sierra Leone 41 182 188 141 185 323 739 0 155 25 150 20 130 Somalia .. 103 96 104 103 55 196 0 352 79 381 77 265 South Africa 2.3 107 93 126 109 80 9,547 0 3,379 4,109 4,333 2,676 2,922 Sudan 24.4 124 116 130 124 194 6,572 145 1,476 315 1,186 256 1,002 Swaziland 6.7 107 104 116 109 25 69 1,374 186 231 245 219 200 Tanzania .. 134 146 104 134 167 5,895 1,359 873 677 701 288 631 Togo .. 107 105 123 121 113 820 119 151 206 116 161 89 Uganda 20.8 105 104 111 105 121 2,631 2 500 674 477 160 418 Zambia 18.1 117 124 106 115 143 1,537 324 61 266 158 74 127 Zimbabwe .. 71 61 97 82 57 1,251 17 531 531 362 106 328 NORTH AFRICA 10.4 .. .. .. .. .. .. 104 29,423 4,426 18,330 3,799 15,745 Algeria 9.2 136 150 120 137 208 4,133 56 7,283 87 5,244 75 4,671 Egypt, Arab Rep. 14.3 115 114 117 116 113 22,059 1 10,509 1,503 5,440 1,245 4,732 Libya .. 102 103 101 102 94 209 1,464 2,357 10 1,734 1 1,587 Morocco 14.2 117 121 110 118 71 2,541 1 6,150 1,538 4,010 1,349 3,190 Tunisia 10 119 126 105 119 136 2,020 1,250 3,125 1,288 1,903 1,129 1,564 (continued) AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT Part III. Development outcomes 119 Participating in growth 8.2 Table Agriculture (continued) Fertilizer Agricultural Share of land area (%) consumption machinery Agricultural Agriculture (100 grams (tractors per employment value added Cereal yield Permanent Cereal Irrigated land per hectare of 100 sq km of (% of total per worker (kilograms cropland cropland (% of cropland) arable land) arable land) employment) (2000 $) per hectare) 2007 2007 2002­05b 2001­06b 2006 2000­07b 2005­06b 2007 SUB­SAHARAN AFRICA 1.0 3.9 3.5 111.9 13.1 .. 291 1,251 Angola 0.2 1.2 2.2 36.6 31.2 .. 208 490 Benin 2.4 8.8 0.4 ­ 0.7 .. 532 1,258 Botswana 0.0 0.2 0.3 230.0 250.0 29.9 333 555 Burkina Faso 0.2 11.9 0.5 73.7 4.0 .. 167 1,148 Burundi 13.6 8.4 1.5 ­ 1.7 .. 62 1,289 Cameroon 2.6 2.5 0.4 90.2 0.8 60.6 631 1,338 Cape Verde 0.7 3.7 6.1 48.6 11.6 .. 1,566 800 Central African Republic 0.1 0.3 0.1 3.1 0.2 .. 377 1,092 Chad 0.0 2.0 0.8 48.6 0.4 .. 215 1,211 Comoros 29.6 8.6 .. 37.5 0.8 .. 382 1,313 Congo, Dem. Rep. 0.4 0.9 0.1 2.9 3.6 .. 146 773 Congo, Rep. 0.1 0.0 0.4 94.4 14.1 .. .. 798 Côte d'Ivoire 13.2 2.6 1.1 227.7 33.4 .. 808 1,710 Djibouti .. 0.0 .. ­ 61.5 .. 63 1,667 Equatorial Guinea 3.2 .. .. ­ 18.5 .. 1,084 .. Eritrea 0.0 3.9 3.5 0.2 7.1 .. 96 454 Ethiopia 1.0 7.9 2.5 139.5 2.2 8.6 188 1,720 Gabon 0.7 0.1 1.4 84.6 29.2 .. 1,734 1,663 Gambia, The 0.6 21.6 0.6 5.0 3.2 .. 230 1,300 Ghana 10.5 6.1 0.5 126.5 8.8 .. 322 1,328 Guinea 2.7 7.4 5.4 13.3 26.5 .. 206 1,437 Guinea-Bissau 8.9 4.9 4.5 80.0 0.7 .. 252 1,472 Kenya 0.9 3.6 1.8 367.2 26.3 .. 338 1,857 Lesotho 0.1 5.2 0.9 343.7 66.7 .. 240 463 Liberia 2.2 1.2 0.5 ­ 8.4 .. .. 1,290 Madagascar 1.0 2.8 30.6 25.5 1.9 82.0 173 2,511 Malawi 1.3 19.8 2.2 182.9 4.8 .. 116 1,953 Mali 0.1 2.6 4.9 91.0 5.5 41.5 295 1,114 Mauritania 0.0 0.2 9.8 64.4 7.9 .. 384 844 Mauritius 2.0 0.0 20.8 2,581.2 59.8 9.1 5,226 7,667 Mozambique 0.4 2.9 2.6 49.5 14.2 .. 163 942 Namibia 0.0 0.3 1.0 28.7 38.7 29.9 1,484 412 Niger 0.0 7.1 0.5 ­ 0.1 .. 163 424 Nigeria 3.3 23.3 0.8 ­ 8.3 .. .. 1,453 Rwanda 11.1 13.2 0.6 3.0 0.5 .. 197 1,049 São Tomé and Príncipe 49.0 1.4 18.2 .. 138.9 27.9 .. 2,308 Senegal 0.3 5.6 4.8 73.3 2.3 33.7 203 823 Seychelles 10.9 .. .. 200.0 400.0 .. 556 .. Sierra Leone 1.1 10.2 4.7 6.0 1.1 68.5 .. 1,014 Somalia 0.0 0.7 15.7 4.8 12.1 .. .. 417 South Africa 0.8 2.8 9.5 475.6 43.4 8.8 2,470 2,796 Sudan 0.1 3.9 10.2 24.9 9.6 .. 684 708 Swaziland 0.8 3.5 26.0 393.3 223.3 .. 1,199 1,146 Tanzania 1.4 5.6 1.8 68.1 22.6 76.5 320 1,193 Togo 3.1 12.7 0.3 ­ 0.3 .. 346 1,187 Uganda 11.2 8.8 0.1 14.2 8.7 68.7 171 1,525 Zambia 0.0 1.3 2.9 138.9 11.4 71.6 208 1,542 Zimbabwe 0.3 5.0 5.2 410.7 74.3 .. 200 649 NORTH AFRICA 0.8 2.2 .. 893.4 142.5 35.00 2,211 2,483.8 Algeria 0.4 1.2 6.9 116.4 135.5 20.7 2,266 1,391 Egypt, Arab Rep. 0.5 2.9 100.0 4,455.3 329.6 31.2 2,213 7,663 Libya 0.2 0.2 21.9 421.4 227.1 .. .. 637 Morocco 2.0 10.9 15.4 559.3 61.5 43.3 2,047 521 Tunisia 14.0 9.1 7.4 387.9 140.4 .. 2,704 1,434 a. Provisional. b. Data are for the most recent year available during the period specified. 120 Part III. Development outcomes AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT Participating in growth 8.3 Table Environment Renewable internal Annual fresh water Water productivity (2000 $ per cubic fresh water resources withdrawals meter of fresh water withdrawal) Forest area Total (billions of Per capita (billions of cubic (% of land area) cubic meters) (cubic meters) meters) Total Agriculture Industry 1990 2007 2007 2007 2000­04a 2001­04a 2001­04a 2001­04a SUB­SAHARAN AFRICA 29.4 26.2 3,884 4,859 0.6 1.2 Angola 48.9 47.2 148 8,431 0.4 26.1 2.5 109.7 Benin 30.0 20.1 10 1,227 0.1 18.2 14.4 11.4 Botswana 24.2 20.7 2 1,276 0.2 31.8 1.7 97.3 Burkina Faso 26.1 24.7 13 846 0.8 3.3 1.0 100.6 Burundi 11.3 5.2 10 1,284 0.3 2.5 1.2 7.0 Cameroon 52.7 44.7 273 14,731 1.0 10.2 2.8 41.9 Cape Verde 14.3 21.0 0 610 .. .. .. .. Central African Republic 37.2 36.4 141 32,463 0.0 38.4 479.5 35.7 Chad 10.4 9.3 15 1,394 0.2 6.0 3.0 .. Comoros 6.4 2.4 1 1,910 .. .. .. .. Congo, Dem. Rep. 62.0 58.7 900 14,423 0.4 12.0 19.3 14.4 Congo, Rep. 66.5 65.7 222 62,516 0.0 76.1 .. .. Côte d'Ivoire 32.1 32.8 77 3,819 0.9 11.2 4.2 23.5 Djibouti 0.2 0.2 0 360 0.0 29.0 5.7 .. Equatorial Guinea 66.3 57.1 26 40,485 0.1 11.6 120.5 62.1 Eritrea .. 15.3 3 578 0.6 1.2 0.2 160.5 Ethiopia 16.7 12.7 122 1,551 5.6 1.6 0.8 51.2 Gabon 85.1 84.4 164 115,340 0.1 42.2 6.3 285.1 Gambia, The 44.2 47.5 3 1,857 0.0 13.8 6.6 13.5 Ghana 32.7 23.2 30 1,325 1.0 5.1 2.7 13.3 Guinea 30.1 27.1 226 23,505 1.5 2.1 0.4 31.7 Guinea-Bissau 78.8 73.0 16 10,383 0.2 1.2 0.8 3.2 Kenya 6.5 6.1 21 552 2.7 5.0 1.9 21.8 Lesotho 0.2 0.3 5 2,607 0.1 15.7 8.6 10.5 Liberia 42.1 31.5 200 55,138 0.1 5.1 .. .. Madagascar 23.5 21.9 337 18,114 15.0 0.3 0.1 2.2 Malawi 41.4 35.5 16 1,160 1.0 1.7 0.8 5.6 Mali 11.5 10.1 60 4,865 6.5 0.4 0.2 8.3 Mauritania 0.4 0.2 0 128 1.7 0.6 0.2 6.0 Mauritius 19.2 18.0 3 2,182 0.7 6.9 0.5 66.7 Mozambique 25.4 24.4 100 4,693 0.6 6.7 1.6 90.6 Namibia 10.6 9.1 6 2,961 0.3 13.0 2.0 71.1 Niger 1.5 1.0 4 247 2.2 0.8 0.3 31.9 Nigeria 18.9 11.3 221 1,493 8.0 5.7 .. .. Rwanda 12.9 21.7 10 1,005 0.2 11.6 6.3 19.6 São Tomé and Príncipe 28.5 28.5 2 13,796 .. .. .. .. Senegal 48.6 44.6 26 2,169 2.2 2.2 0.3 18.4 Seychelles 87.0 87.0 .. .. 0.0 46.5 19.1 48.6 Sierra Leone 42.5 37.9 160 29,518 0.4 1.7 .. .. Somalia 13.2 11.1 6 690 3.3 .. .. .. South Africa 7.6 7.6 45 936 12.5 10.6 0.5 50.8 Sudan 32.1 27.9 30 742 37.3 0.3 0.1 9.8 Swaziland 27.4 32.0 3 2,293 1.0 1.4 0.2 46.0 Tanzania 46.8 38.9 84 2,035 5.2 2.0 0.9 61.7 Togo 12.6 6.4 12 1,825 0.2 8.2 6.5 63.8 Uganda 25.0 17.5 39 1,273 .. .. .. .. Zambia 66.1 55.9 80 6,513 1.7 1.9 0.5 5.6 Zimbabwe 57.5 43.7 12 985 4.2 1.6 0.3 4.3 NORTH AFRICA 1.2 1.4 47 291 93.9 2.6 Algeria 0.8 1.0 11 332 6.1 9.0 1.2 38.0 Egypt, Arab Rep. 0.0 0.1 2 23 68.3 1.5 0.3 7.7 Libya 0.1 0.1 1 98 4.3 8.0 .. .. Morocco 9.6 9.8 29 940 12.6 2.9 0.4 26.6 Tunisia 4.1 7.0 4 410 2.6 7.4 1.1 50.5 (continued) AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT Part III. Development outcomes 121 Participating in growth 8.3 Table Environment (continued) Water pollution Energy Emissions of organic Combustible water pollutants Energy production Energy use renewables and waste (kilograms per day) (kilotons of oil equivalent) (kilotons of oil equivalent) (% of total energy use) 2000­05a 1990 2006 1990 2006 1990 2006 SUB­SAHARAN AFRICA Angola .. 28,652 79,158 6,285 10,264 68.8 63.9 Benin .. 1,774 1,720 1,678 2,815 93.2 61.1 Botswana 3,440 910 1,075 1,273 1,959 33.1 23.2 Burkina Faso .. .. .. .. .. .. .. Burundi .. .. .. .. .. .. .. Cameroon .. 10,976 10,314 5,032 7,083 75.9 79.2 Cape Verde .. .. .. .. .. .. .. Central African Republic .. .. .. .. .. .. .. Chad .. .. .. .. .. .. .. Comoros .. .. .. .. .. .. .. Congo, Dem. Rep. .. 12,019 17,822 11,907 17,513 84.0 92.4 Congo, Rep. .. 8,746 15,421 797 1,205 59.5 57.6 Côte d'Ivoire .. 3,382 9,338 4,413 7,287 72.0 63.8 Djibouti .. .. .. .. .. .. .. Equatorial Guinea .. .. .. .. .. .. .. Eritrea 2,871 .. 515 .. 704 .. 73.0 Ethiopia 24,137 14,052 20,357 15,045 22,319 92.8 90.0 Gabon .. 14,630 12,144 1,243 1,823 59.8 56.3 Gambia, The .. .. .. .. .. .. .. Ghana 15,419 4,392 6,504 5,338 9,503 73.1 63.3 Guinea .. .. .. .. .. .. .. Guinea-Bissau .. .. .. .. .. .. .. Kenya .. 9,013 14,258 11,220 17,948 75.9 73.6 Lesotho 13,153 .. .. .. .. .. .. Liberia .. .. .. .. .. .. .. Madagascar 88,887 .. .. .. .. .. .. Malawi 32,672 .. .. .. .. .. .. Mali .. .. .. .. .. .. .. Mauritania .. .. .. .. .. .. .. Mauritius 351 .. .. .. .. .. .. Mozambique .. 5,608 10,698 5,966 8,804 93.2 81.6 Namibia .. .. 317 .. 1,476 .. 12.7 Niger .. .. .. .. .. .. .. Nigeria .. 150,452 235,340 70,904 105,075 79.8 79.6 Rwanda .. .. .. .. .. .. .. São Tomé and Príncipe .. .. .. .. .. .. .. Senegal 6,621 964 1,231 1,840 3,016 52.0 39.6 Seychelles .. .. .. .. .. .. .. Sierra Leone .. .. .. .. .. .. .. Somalia .. .. .. .. .. .. .. South Africa 183,841 114,535 158,676 91,230 129,815 11.4 10.5 Sudan 38,567 8,775 30,701 10,661 17,713 81.5 77.5 Swaziland .. .. .. .. .. .. .. Tanzania .. 9,064 19,427 9,808 20,805 91.0 91.0 Togo .. 1,054 2,039 1,298 2,404 80.6 84.5 Uganda 2,105 .. .. .. .. .. .. Zambia .. 4,918 6,663 5,464 7,309 73.4 78.2 Zimbabwe .. 8,550 8,759 9,381 9,578 50.4 63.3 NORTH AFRICA 238,982 360,309 79,782 139,688 2.7 2.4 Algeria .. 104,439 173,207 23,919 36,700 0.1 0.2 Egypt, Arab Rep. .. 54,869 77,830 31,974 62,501 3.3 2.3 Libya .. 73,173 101,970 11,543 17,769 1.1 0.9 Morocco 72,779 773 670 7,206 13,977 4.4 3.2 Tunisia .. 5,728 6,632 5,140 8,741 12.4 13.3 a. Data are for the most recent year available during the period specified. b. Hydrofluorocarbons, perfluorocarbons, and sulphur hexafluoride. 122 Part III. Development outcomes AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT Greenhouse gas emissions Methane Nitrous oxide Other greenhouse ODA gross gasesb disbursements Total Total (thousands of ODA gross for general Carbon dioxide (kilotons of (metric tons of metric tons of disbursements environment (thousands of carbon dioxide Agricultural Industrial carbon dioxide Agricultural Industrial carbon dioxide for forestry protection metric tons) equivalent) (% of total) (% of total) equivalent) (% of total) (% of total) equivalent) ($ millions) ($ millions) 1990 2006 1990 2005 1990 2005 1990 2005 1990 2005 1990 2005 1990 2005 1990 2005 2008 2008 98.4 329.1 4,429 10,582 13,630 37,020 65.7 39.1 21.6 11.6 5,110 28,350 80.4 35.9 0.0 0.0 0 0 0.1 0.9 715 3,109 2,730 4,840 60.1 47.5 16.1 8.9 2,120 4,660 90.6 68.0 0.0 0.0 0 0 1.7 2.5 2,171 4,770 130 4,480 84.6 71.9 7.7 17.9 0 2,460 .. 96.3 .. 0.0 0 0 0.2 9.6 587 788 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.4 6.0 304 198 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 1.6 1,738 3,645 10,500 15,110 57.0 56.0 20.2 17.9 8,290 14,540 85.5 85.0 0.0 0.0 810 890 9.5 7.9 88 308 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.5 7.7 198 249 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 5.6 0.4 147 396 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.6 2.5 77 88 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 4,070 2,200 2,670 5,750 20.2 11.8 47.9 49.6 820 2,250 23.2 15.6 0.0 0.0 0 0 4.0 12.4 1,188 1,463 27,720 50,320 42.9 26.3 10.4 7.7 19,390 38,680 43.7 23.2 0.0 0.0 0 0 0.6 2.3 5,797 6,882 5,410 15,320 49.9 20.6 18.9 11.2 2,460 12,350 82.1 25.0 0.0 0.0 0 0 0.0 2.7 400 488 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 0.3 121 4,356 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 0.0 .. 554 2,090 2,410 75.6 77.6 11.0 7.5 1,340 2,350 97.0 99.1 0.0 0.0 0 0 0.0 0.6 3,018 6,006 39,110 47,740 78.4 77.2 9.3 10.0 50,730 63,130 97.9 98.6 0.0 0.0 0 0 5.0 8.8 6,087 2,057 3,120 2,040 6.7 4.4 46.5 79.9 1,850 420 13.0 57.1 0.0 0.0 0 0 2.1 4.6 191 334 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.1 0.0 3,931 9,240 5,310 8,630 42.7 49.6 13.7 10.7 4,540 10,520 84.1 88.6 0.0 0.0 190 170 10.8 4.9 1,056 1,360 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1.5 3.3 253 279 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.0 5,823 12,151 19,410 20,310 71.4 65.0 15.7 18.0 21,830 19,060 97.6 96.4 0.0 0.0 0 0 2.0 28.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.1 0.2 484 785 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.7 0.7 986 2,834 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.5 17.5 612 1,049 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 4.4 2.9 422 568 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.4 7.4 2,666 1,665 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 10.9 1,463 3,850 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.1 1,001 2,039 9,430 11,680 61.9 64.3 17.5 16.9 2,950 9,930 72.5 99.7 0.0 0.0 0 0 1.1 14.3 7 2,831 4,320 4,260 90.7 89.9 3.7 4.7 4,240 4,620 97.2 99.1 0.0 0.0 0 0 1.7 2.4 1,052 935 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.3 3.9 45,371 97,262 59,690 78,290 33.9 33.7 47.3 45.5 28,050 39,030 87.9 87.1 0.0 0.0 120 80 0.1 8.1 682 796 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.1 3.3 66 103 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 0.3 3,183 4,261 5,550 6,340 76.2 75.9 4.5 4.7 6,220 10,250 95.8 99.0 0.0 0.0 0 10 2.9 24.7 114 744 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.2 389 994 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 1.2 18 172 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.1 333,531 414,649 52,260 59,200 31.2 23.8 52.4 54.3 26,460 29,250 88.0 82.7 3.6 7.3 1,450 2,600 0.2 16.2 5,559 10,813 39,760 67,310 69.1 73.3 21.4 21.5 39,400 59,750 94.1 96.2 0.0 0.0 0 0 2.5 2.1 425 1,016 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 0.0 2,372 5,372 26,860 39,460 66.4 63.5 21.3 20.3 23,300 31,690 91.3 84.3 0.0 0.0 0 0 6.0 15.2 774 1,221 1,790 2,840 56.4 48.6 18.4 14.8 1,990 5,470 93.5 88.8 0.0 0.0 0 0 0.1 0.0 818 2,706 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.4 3.1 2,446 2,471 9,820 16,770 72.5 68.6 8.1 5.7 4,800 11,410 72.5 65.1 0.0 3.7 0 0 0.5 9.4 16,658 11,081 10,850 10,400 65.4 60.4 22.2 24.8 8,970 10,160 89.4 97.1 5.9 0.0 0 20 0.1 0.7 231,949 423,452 63,380 83,440 32.3 31.2 43.5 41.7 47,260 62,930 92.4 84.8 4.7 6.7 2,580 2,250 8.0 153.6 78,888 132,715 18,570 24,310 19.3 15.3 61.2 66.3 8,780 10,330 90.9 89.1 4.4 7.2 230 110 0.3 5.7 75,940 166,800 23,250 32,960 39.0 44.2 33.4 31.2 16,980 27,810 88.6 85.6 8.2 11.5 2,250 1,820 0.0 92.1 40,315 55,495 8,750 8,540 11.8 8.9 79.1 77.6 2,860 2,050 96.5 91.7 0.0 0.0 100 290 .. 0.0 23,540 45,316 9,070 13,240 57.6 41.6 6.2 2.6 14,380 15,510 98.5 75.2 0.0 0.0 0 0 2.3 8.2 13,266 23,126 3,740 4,390 42.2 34.2 26.2 32.1 4,260 7,230 87.1 94.2 10.6 4.1 0 30 5.4 38.2 AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT Part III. Development outcomes 123 Participating in growth 8.4 Table Fossil fuel emissions Carbon dioxide emissions from fossil fuel Carbon dioxide emissions (thousands of metric tons) Total Per capita Solid fuel (thousands of metric tons) (metric tons) Total consumption 1990 2005 2006 1990 2005 2006 1990 2005 2006 1990 2005 2006 SUB­SAHARAN AFRICA 463,488 649,627 641,720 0.9 0.9 0.8 130,131 181,797 179,591 111,351 143,525 144,853 Angola 4,429 9,856 10,582 0.4 0.6 0.6 1,208 2,688 2,886 0 0 0 Benin 715 2,567 3,109 0.1 0.3 0.4 195 700 848 0 0 0 Botswana 2,171 4,525 4,770 1.6 2.5 2.6 592 1,234 1,301 592 702 748 Burkina Faso 587 788 788 0.1 0.1 0.1 160 215 215 0 0 0 Burundi 304 169 198 0.1 0.0 0.0 83 46 54 4 2 2 Cameroon 1,738 3,718 3,645 0.1 0.2 0.2 .. .. .. .. .. .. Cape Verde 88 297 308 0.2 0.6 0.6 24 81 84 0 0 0 Central African Republic 198 235 249 0.1 0.1 0.1 54 64 68 0 0 0 Chad 147 392 396 0.0 0.0 0.0 40 107 108 0 0 0 Comoros 77 88 88 0.2 0.1 0.1 21 24 24 0 0 0 Congo, Dem. Rep. 4,070 2,145 2,200 0.1 0.0 0.0 1,110 585 600 209 273 287 Congo, Rep. 1,188 1,606 1,463 0.5 0.5 0.4 324 438 399 0 0 0 Côte d'Ivoire 5,797 8,166 6,882 0.5 0.4 0.3 1,581 2,227 1,877 0 0 0 Djibouti 400 473 488 0.7 0.6 0.6 109 129 133 0 0 0 Equatorial Guinea 121 4,341 4,356 0.3 7.1 7.0 33 1,184 1,188 0 0 0 Eritrea .. 752 554 .. 0.2 0.1 .. 205 151 .. 0 0 Ethiopia 3,018 5,489 6,006 0.1 0.1 0.1 823 1,497 1,638 0 0 0 Gabon 6,087 1,870 2,057 6.6 1.4 1.5 1,660 510 561 0 0 0 Gambia, The 191 319 334 0.2 0.2 0.2 52 87 91 0 0 0 Ghana 3,931 7,473 9,240 0.3 0.3 0.4 1,072 2,038 2,520 2 0 0 Guinea 1,056 1,360 1,360 0.2 0.1 0.1 288 371 371 0 0 0 Guinea-Bissau 253 271 279 0.2 0.2 0.2 69 74 76 0 0 0 Kenya 5,823 10,952 12,151 0.2 0.3 0.3 1,588 2,987 3,314 110 78 87 Lesotho .. .. .. .. .. .. .. .. .. .. .. .. Liberia 484 737 785 0.2 0.2 0.2 132 201 214 0 0 0 Madagascar 986 2,798 2,834 0.1 0.2 0.2 269 763 773 9 7 7 Malawi 612 1,049 1,049 0.1 0.1 0.1 167 286 286 13 43 36 Mali 422 568 568 0.1 0.0 0.0 115 155 155 0 0 0 Mauritania 2,666 1,650 1,665 1.4 0.6 0.5 727 450 454 4 0 0 Mauritius 1,463 3,410 3,850 1.4 2.7 3.1 399 930 1,050 54 264 350 Mozambique 1,001 1,855 2,039 0.1 0.1 0.1 273 506 556 42 0 0 Namibia 7 2,724 2,831 0.0 1.3 1.4 2 743 772 0 40 38 Niger 1,052 928 935 0.1 0.1 0.1 287 253 255 125 132 133 Nigeria 45,371 113,868 97,262 0.5 0.8 0.7 12,374 31,055 26,526 35 8 8 Rwanda 682 766 796 0.1 0.1 0.1 186 209 217 0 0 0 São Tomé and Príncipe 66 103 103 0.6 0.7 0.7 18 28 28 0 0 0 Senegal 3,183 5,577 4,261 0.4 0.5 0.4 868 1,521 1,162 0 110 121 Seychelles 114 697 744 1.6 8.4 8.8 31 190 203 0 0 0 Sierra Leone 389 1,005 994 0.1 0.2 0.2 106 274 271 0 0 0 Somalia 18 253 172 0.0 0.0 0.0 5 69 47 0 0 0 South Africa 333,531 409,090 414,649 9.5 8.7 8.7 90,963 111,570 113,086 72,365 96,006 96,887 Sudan 5,559 11,000 10,813 0.2 0.3 0.3 1,516 3,000 2,949 0 0 0 Swaziland 425 1,019 1,016 0.5 0.9 0.9 116 278 277 116 104 105 Tanzania 2,372 5,086 5,372 0.1 0.1 0.1 647 1,387 1,465 3 54 58 Togo 774 1,338 1,221 0.2 0.2 0.2 211 365 333 0 0 0 Uganda 818 2,339 2,706 0.0 0.1 0.1 223 638 738 0 0 0 Zambia 2,446 2,365 2,471 0.3 0.2 0.2 667 645 674 227 98 104 Zimbabwe 16,658 11,550 11,081 1.6 0.9 0.9 4,543 3,150 3,022 3,976 2,526 2,405 NORTH AFRICA 231,949 436,883 423,452 1.9 2.8 2.7 63,259 119,150 115,487 3,567 7,179 6,461 Algeria 78,888 138,178 132,715 3.1 4.2 4.0 21,515 37,685 36,195 825 666 759 Egypt, Arab Rep. 75,940 173,481 166,800 1.3 2.2 2.1 20,711 47,313 45,491 917 924 807 Libya 40,315 54,894 55,495 9.2 9.3 9.2 10,995 14,971 15,135 4 0 0 Morocco 23,540 47,531 45,316 1.0 1.6 1.5 6,420 12,963 12,359 1,278 4,610 4,014 Tunisia 13,266 22,799 23,126 1.6 2.3 2.3 3,618 6,218 6,307 72 0 0 124 Part III. Development outcomes AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT Carbon dioxide emissions from fossil fuel (thousands of metric tons) Liquid fuel consumption Gas fuel consumption Gas flaring Cement production 1990 2005 2006 1990 2005 2006 1990 2005 2006 1990 2005 2006 42,650 49,717 46,722 .. .. .. .. .. .. 2,906 5,050 5,284 489 1,717 1,882 276 383 408 409 409 409 35 179 187 154 666 814 0 0 0 0 0 0 41 34 34 0 532 553 0 0 0 0 0 0 0 0 0 160 211 211 0 0 0 0 0 0 0 4 4 79 44 52 0 0 0 0 0 0 0 0 0 .. .. .. .. .. .. .. .. .. .. .. .. 24 81 84 0 0 0 0 0 0 0 0 0 54 64 68 0 0 0 0 0 0 0 0 0 40 107 108 0 0 0 0 0 0 0 0 0 21 24 24 0 0 0 0 0 0 0 0 0 838 312 312 0 0 0 0 0 0 63 0 0 265 358 315 1 12 12 46 0 0 12 69 72 1,513 1,228 934 0 910 855 0 0 0 68 88 88 109 129 133 0 0 0 0 0 0 0 0 0 33 41 44 0 251 251 0 892 892 0 0 0 .. 199 145 .. 0 0 .. 0 0 .. 6 6 777 1,284 1,407 0 0 0 0 0 0 46 213 231 583 409 460 138 66 66 924 0 0 16 35 35 52 87 91 0 0 0 0 0 0 0 0 0 978 1,780 2,262 0 0 0 0 0 0 92 258 258 288 322 322 0 0 0 0 0 0 0 49 49 69 74 76 0 0 0 0 0 0 0 0 0 1,273 2,620 2,928 0 0 0 0 0 0 205 289 299 .. .. .. .. .. .. .. .. .. .. .. .. 125 181 193 0 0 0 0 0 0 7 20 21 252 736 746 0 0 0 0 0 0 8 20 20 141 221 223 0 0 0 0 0 0 13 22 27 112 155 155 0 0 0 0 0 0 3 0 0 709 409 403 0 0 0 0 0 0 14 41 51 345 666 699 0 0 0 0 0 0 0 0 0 220 392 414 0 38 44 0 0 0 11 76 98 2 703 733 0 0 0 0 0 0 0 0 0 159 115 116 0 0 0 0 0 0 3 7 7 9,823 13,074 8,939 2,041 5,048 5,621 0 12,600 11,549 476 326 408 177 195 203 0 0 0 0 0 0 8 14 14 18 28 28 0 0 0 0 0 0 0 0 0 801 1,047 643 3 7 6 0 0 0 64 357 392 31 190 203 0 0 0 0 0 0 0 0 0 106 251 239 0 0 0 0 0 0 0 23 32 0 69 47 0 0 0 0 0 0 5 0 0 16,596 11,526 12,046 940 2,269 2,384 0 0 0 1,062 1,768 1,768 1,493 2,955 2,922 0 0 0 0 0 0 23 45 27 0 173 172 0 0 0 0 0 0 0 0 0 571 962 1,018 0 185 196 0 0 0 73 186 193 157 256 224 0 0 0 0 0 0 54 109 109 219 552 652 0 0 0 0 0 0 4 86 86 381 488 508 0 0 0 0 0 0 59 59 61 471 542 522 0 0 0 0 0 0 95 82 95 34,171 62,318 59,847 17,482 39,130 37,748 .. .. .. 4,167 8,378 8,913 6,835 17,089 16,688 10,619 16,706 14,955 2,373 1,688 1,753 862 1,536 2,040 14,323 25,099 23,388 3,552 17,346 17,352 0 0 0 1,918 3,944 3,944 6,058 10,112 9,820 2,599 3,010 3,260 1,969 1,357 1,564 367 492 490 4,541 6,620 6,550 30 237 299 0 0 0 571 1,496 1,496 2,414 3,398 3,401 682 1,831 1,882 1 79 81 449 910 943 AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT Part III. Development outcomes 125 Participating in growth 9.1 Table Labor force participation Labor force ages 15 and older Total Male Female (thousands) (% of total labor force) (% of total labor force) 2000 2007 2000 2007 2000 2007 SUB­SAHARAN AFRICA 261,534 318,017 57.3 56.6 42.7 43.4 Angola 6,176 7,798 54.3 53.4 45.7 46.6 Benin 2,677 3,427 59.3 59.4 40.7 40.6 Botswana 631 690 57.3 56.4 42.7 43.6 Burkina Faso 5,259 6,648 52.4 52.9 47.6 47.1 Burundi 3,180 4,249 47.6 48.4 52.4 51.6 Cameroon 5,885 6,943 59.1 58.7 40.9 41.3 Cape Verde 150 184 60.5 58.4 39.5 41.6 Central African Republic 1,734 1,963 54.4 55.0 45.6 45.0 Chad 3,311 4,316 54.3 51.4 45.7 48.6 Comoros 237 284 56.9 56.6 43.1 43.4 Congo, Dem. Rep. 18,817 23,579 60.9 61.3 39.1 38.7 Congo, Rep. 1,202 1,452 58.8 59.3 41.2 40.7 Côte d'Ivoire 6,465 7,414 70.0 69.7 30.0 30.3 Djibouti 297 352 57.0 56.8 43.0 43.2 Equatorial Guinea 199 250 66.4 67.5 33.6 32.5 Eritrea 1,436 1,981 58.5 59.0 41.5 41.0 Ethiopia 29,025 37,435 54.6 52.6 45.4 47.4 Gabon 527 631 55.7 55.8 44.3 44.2 Gambia, The 575 713 54.2 53.6 45.8 46.4 Ghana 8,520 10,111 51.6 51.0 48.4 49.0 Guinea 3,968 4,601 53.0 52.9 47.0 47.1 Guinea-Bissau 542 631 60.6 61.8 39.4 38.2 Kenya 14,183 17,373 53.5 53.7 46.5 46.3 Lesotho 800 861 47.7 47.5 52.3 52.5 Liberia 1,095 1,442 60.0 59.7 40.0 40.3 Madagascar 6,904 8,934 51.8 51.4 48.2 48.6 Malawi 4,866 5,781 49.7 49.9 50.3 50.1 Mali 2,743 3,441 64.6 62.5 35.4 37.5 Mauritania 1,043 1,312 57.6 57.2 42.4 42.8 Mauritius 527 572 65.8 63.8 34.2 36.2 Mozambique 8,569 9,905 44.1 43.9 55.9 56.1 Namibia 620 695 55.0 53.4 45.0 46.6 Niger 3,632 4,558 68.5 68.5 31.5 31.5 Nigeria 38,597 46,114 66.0 64.2 34.0 35.8 Rwanda 3,632 4,374 47.1 46.9 52.9 53.1 São Tomé and Príncipe 44 52 63.7 61.3 36.3 38.7 Senegal 4,014 4,909 58.5 57.4 41.5 42.6 Seychelles .. .. .. .. .. .. Sierra Leone 1,654 2,039 51.0 48.8 49.0 51.2 Somalia 2,777 3,413 61.6 61.1 38.4 38.9 South Africa 15,543 17,620 56.1 54.9 43.9 45.1 Sudan 10,413 12,504 71.3 69.6 28.7 30.4 Swaziland 413 445 50.2 50.2 49.8 49.8 Tanzania 16,805 20,250 50.2 50.3 49.8 49.7 Togo 2,081 2,579 61.6 61.7 38.4 38.3 Uganda 10,636 13,388 52.2 52.2 47.8 47.8 Zambia 3,996 4,643 57.1 56.9 42.9 43.1 Zimbabwe 5,139 5,161 53.4 54.6 46.6 45.4 NORTH AFRICA 46,740 56,636 75.2 73.2 24.8 26.8 Algeria 11,061 13,907 71.7 67.9 28.3 32.1 Egypt, Arab Rep. 20,592 25,499 77.3 74.8 22.7 25.2 Libya 1,846 2,265 78.7 76.4 21.3 23.6 Morocco 10,011 11,225 74.4 75.2 25.6 24.8 Tunisia 3,230 3,740 75.0 73.3 25.0 26.7 126 Part III. Development outcomes L ABOR, MIGRATION, AND POPULATION Participation rate, ages 15 and older Participation rate, ages 15­64 (%) (%) Total Male Female Total Male Female 2000 2007 2000 2007 2000 2007 2000 2007 2000 2007 2000 2007 69.5 69.7 81.1 79.9 69.5 69.7 70.7 70.9 82.0 80.8 59.7 61.2 81.7 81.7 90.8 89.2 73.0 74.5 83.0 83.0 91.6 89.9 74.7 76.4 72.7 72.1 87.6 85.7 58.1 58.5 73.5 72.9 87.8 86.0 59.2 59.6 58.9 55.7 69.0 63.4 49.3 48.2 60.1 57.5 69.6 64.4 50.9 50.6 83.2 83.3 90.3 89.8 76.5 77.1 85.2 85.3 91.4 90.7 79.4 79.9 91.4 89.9 92.1 90.4 90.7 89.5 92.1 90.5 92.6 90.9 91.7 90.2 65.0 63.8 77.7 75.4 52.5 52.4 65.3 64.6 78.3 76.1 52.5 53.0 60.1 60.1 79.8 75.4 43.5 46.5 62.8 62.7 81.7 76.9 46.5 49.8 77.3 76.8 87.1 87.1 68.4 67.3 77.7 77.1 87.4 87.5 68.6 67.3 72.5 74.1 80.2 77.3 65.0 71.0 72.7 74.5 79.9 76.8 65.6 72.3 72.7 73.1 83.1 83.0 62.4 63.2 73.5 74.0 83.4 83.4 63.7 64.5 71.5 71.6 89.3 89.7 54.6 54.3 72.8 72.9 90.4 90.8 55.8 55.4 68.8 69.1 82.3 82.8 56.0 55.8 69.2 69.4 83.1 83.7 55.7 55.4 63.9 62.5 85.8 84.7 40.3 39.2 64.8 63.4 86.6 85.7 41.2 39.9 69.1 67.3 79.5 77.0 59.0 57.8 72.0 70.4 82.0 79.8 62.0 61.0 67.4 66.6 91.5 91.5 44.4 42.6 69.6 68.7 93.9 93.8 46.2 44.2 70.5 70.0 86.2 85.8 56.1 55.4 71.7 71.2 87.1 86.9 57.4 56.5 81.8 85.3 90.9 91.0 73.1 79.7 83.7 86.9 92.0 91.8 75.6 82.1 72.3 70.9 82.0 79.8 63.0 62.1 74.7 72.8 83.9 81.5 65.6 64.1 77.4 76.9 85.2 83.8 69.6 70.1 77.6 77.2 85.0 83.7 70.1 70.8 74.3 72.5 76.3 73.3 72.3 71.6 75.3 73.8 76.9 74.0 73.6 73.6 84.7 84.1 89.7 88.9 79.7 79.4 86.7 86.1 90.5 89.6 82.8 82.6 71.5 71.4 88.6 89.9 55.3 53.6 73.1 72.7 89.9 91.3 56.9 54.8 81.3 80.8 88.1 87.3 74.7 74.4 82.6 82.1 88.9 88.1 76.5 76.1 73.1 70.9 78.9 75.0 68.6 67.6 74.3 72.1 79.7 75.8 70.1 69.1 69.5 69.9 84.7 84.5 54.5 55.4 70.4 70.8 85.0 84.7 55.8 56.7 82.4 85.2 85.8 88.4 79.0 82.1 83.0 86.6 86.1 89.2 80.1 84.1 77.4 77.8 78.9 79.5 76.1 76.3 76.8 77.2 78.1 78.6 75.6 75.7 50.3 50.1 67.8 65.1 34.6 36.5 52.3 52.1 70.2 67.0 36.3 38.4 70.3 70.1 81.4 79.9 59.3 60.2 72.2 72.0 82.7 81.3 61.6 62.6 60.0 59.5 79.9 77.2 40.6 42.4 64.6 64.7 84.6 82.5 44.4 46.8 83.6 82.9 79.4 77.2 87.3 88.1 83.9 83.2 79.1 76.8 88.0 89.1 55.9 53.8 63.9 59.0 48.5 48.8 57.4 55.2 65.3 60.3 49.9 50.3 63.5 63.5 87.7 87.5 39.1 39.3 64.1 64.1 88.6 88.3 39.7 39.9 55.1 54.5 73.7 70.6 37.0 38.7 56.0 55.4 75.0 71.6 37.5 39.4 84.2 80.0 85.0 79.2 83.6 80.8 85.7 81.3 86.1 80.2 85.3 82.2 53.9 56.5 70.3 70.8 38.2 42.7 56.6 59.3 73.1 73.5 40.7 45.6 74.4 73.7 88.2 86.2 60.8 61.5 76.1 75.5 90.4 88.4 62.0 62.9 .. .. .. .. .. .. .. .. .. .. .. .. 67.4 66.1 71.6 67.4 63.4 64.9 69.2 67.9 72.7 68.1 65.9 67.7 70.5 71.1 88.6 88.5 53.1 54.3 71.7 72.4 90.0 89.8 54.0 55.4 53.2 53.4 61.5 60.2 45.4 47.0 55.8 55.7 63.7 61.8 48.2 49.8 51.6 51.5 73.7 71.6 29.6 31.3 52.4 52.3 73.8 71.7 30.9 32.8 68.9 65.1 74.3 68.5 64.2 62.0 70.5 66.8 74.8 69.2 66.8 64.7 89.1 88.6 91.2 90.3 87.1 87.0 90.3 90.2 91.5 91.2 89.0 89.3 69.5 68.9 87.3 86.7 52.4 51.8 70.5 69.8 88.0 87.4 53.4 52.7 86.1 85.9 90.9 90.3 81.3 81.6 87.5 87.2 91.5 90.8 83.5 83.6 69.7 70.1 80.9 80.5 58.9 59.8 70.0 70.5 81.2 80.8 59.2 60.3 71.4 69.7 79.1 79.7 64.0 59.9 72.0 71.1 79.6 80.9 64.6 61.4 49.9 50.5 75.5 74.4 49.9 50.5 52.3 53.2 78.5 77.8 26.2 28.8 55.0 57.3 78.8 77.5 31.2 36.9 57.2 59.7 81.9 80.7 32.1 38.1 46.5 47.3 72.1 71.2 21.1 23.8 49.0 50.2 75.2 74.8 22.7 25.7 50.9 52.7 76.0 77.5 22.9 25.9 52.4 54.8 78.0 80.0 23.9 27.3 53.0 51.4 80.9 79.8 26.5 24.7 55.4 53.9 83.7 82.8 28.3 26.6 48.3 48.3 72.5 70.9 24.2 25.7 51.1 51.2 76.0 74.3 26.1 27.9 L ABOR, MIGRATION, AND POPULATION Part III. Development outcomes 127 Participating in growth 9.2 Table Labor force composition Sectora Agriculture Industry Services Male (% of male Female (% of female Male (% of male Female (% of female Male (% of male Female (% of female employment) employment) employment) employment) employment) employment) 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b SUB­SAHARAN AFRICA Angola .. .. .. .. .. .. Benin .. .. .. .. .. .. Botswana 35.1 24.3 19.2 10.8 45.5 64.8 Burkina Faso .. .. .. .. .. .. Burundi .. .. .. .. .. .. Cameroon 53.1 68.4 14.1 3.9 25.5 22.5 Cape Verde .. .. .. .. .. .. Central African Republic .. .. .. .. .. .. Chad .. .. .. .. .. .. Comoros .. .. .. .. .. .. Congo, Dem. Rep. .. .. .. .. .. .. Congo, Rep. .. .. .. .. .. .. Côte d'Ivoire .. .. .. .. .. .. Djibouti .. .. .. .. .. .. Equatorial Guinea .. .. .. .. .. .. Eritrea .. .. .. .. .. .. Ethiopia 11.7 5.5 26.8 17.4 60.6 76.6 Gabon .. .. .. .. .. .. Gambia, The .. .. .. .. .. .. Ghana .. .. .. .. .. .. Guinea .. .. .. .. .. .. Guinea-Bissau .. .. .. .. .. .. Kenya .. .. .. .. .. .. Lesotho .. .. .. .. .. .. Liberia .. .. .. .. .. .. Madagascar 81.5 82.5 5.1 1.6 13.4 15.9 Malawi .. .. .. .. .. .. Mali 49.8 29.9 17.8 14.7 32.4 55.3 Mauritania .. .. .. .. .. .. Mauritius 9.9 7.6 35.5 25.8 53.9 66.1 Mozambique .. .. .. .. .. .. Namibia 33.7 25.2 19.1 9.3 47.1 65.4 Niger .. .. .. .. .. .. Nigeria .. .. .. .. .. .. Rwanda .. .. .. .. .. .. São Tomé and Príncipe 30.6 22.8 26.3 5.9 42.6 70.7 Senegal 34.1 33.0 20.2 4.9 32.5 42.0 Seychelles .. .. .. .. .. .. Sierra Leone 66 71.1 10.3 2.5 23.4 26.3 Somalia .. .. .. .. .. .. South Africa 10.6 6.5 35.3 13.5 53.8 79.7 Sudan .. .. .. .. .. .. Swaziland .. .. .. .. .. .. Tanzania 72.7 80.0 6.6 2.1 20.7 17.9 Togo .. .. .. .. .. .. Uganda 61.8 75.7 10.3 5.3 27.6 19.2 Zambia 65.2 78.6 8.8 2.0 26.0 18.4 Zimbabwe .. .. .. .. .. .. NORTH AFRICA Algeria 20.4 22.3 25.6 28.2 53.8 49.4 Egypt, Arab Rep. 28.3 43.3 25.8 6.0 45.6 50.6 Libya .. .. .. .. .. .. Morocco 36.7 61.3 22.4 14.5 40.8 24.1 Tunisia .. .. .. .. .. .. a. Components may not sum to 100 percent because of unclassified data. b. Data are for the most recent year available during the period specified. 128 Part III. Development outcomes L ABOR, MIGRATION, AND POPULATION Statusa Wage and salaried workers Self-employed workers Contributing family workers Total Male Female Total Male Female Total Male Female (% of total (% of males (% of females (% of total (% of males (% of females (% of total (% of males (% of females employed) employed) employed) employed) employed) employed) employed) employed) employed) 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 73.2 74.4 71.9 12.2 8.1 16.8 2.2 2.2 2.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 19.2 29.3 8.7 59.3 57.0 61.7 18.2 9.5 27.2 38.9 43.8 33.0 31.8 32.6 30.9 10.3 6.5 14.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 46.3 49.3 42.7 42.8 41.8 44.0 10.0 7.8 12.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 13.4 16.0 10.8 43.7 51.6 35.4 52.3 32.1 73.0 .. .. .. .. .. .. .. .. .. 13.6 15.2 11.4 71.4 66.4 78.4 15.0 18.4 10.2 .. .. .. .. .. .. .. .. .. 79.2 77.2 83.2 18.0 21.2 11.6 2.2 0.9 4.7 .. .. .. .. .. .. .. .. .. 72.8 76.0 68.8 22.3 20.4 26.6 4.4 3.2 5.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 7.6 11.3 3.7 .. .. .. 18.1 14.8 21.6 .. .. .. .. .. .. .. .. .. 82.4 83.5 80.8 17.0 16.0 18.3 0.4 0.3 0.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 10.5 15.3 6.1 78.1 75.0 80.9 11.4 9.7 13.0 .. .. .. .. .. .. .. .. .. 14.5 22.2 7.5 59.4 67.5 52.1 26.1 10.3 40.5 18.7 25.7 9.0 59.7 49.0 29.2 19.6 25.4 61.8 37.7 51.0 23.1 50.4 38.6 63.2 11.9 10.4 13.6 59.8 61.9 49.8 31.7 30.7 36.6 8.2 7.1 13.6 61.8 63.7 53.7 25.1 27.7 13.7 13.1 8.6 32.6 .. .. .. .. .. .. .. .. .. 43.2 46.8 33.4 29.3 36.1 11.1 27.4 17.0 55.3 64.3 .. .. 26.8 .. .. 8.7 .. .. L ABOR, MIGRATION, AND POPULATION Part III. Development outcomes 129 Participating in growth 9.3 Table Unemployment Unemployment Youth unemployment (% ages 15 and older) (% ages 15­24) Total Male Female Total Male Female 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b SUB­SAHARAN AFRICA Angola .. .. .. .. .. .. Benin 0.7 0.9 0.4 0.8 1.1 0.6 Botswana 17.6 15.3 19.9 39.7 33.9 46.1 Burkina Faso .. .. .. .. .. .. Burundi .. .. .. .. .. .. Cameroon 7.5 8.2 6.7 .. .. .. Cape Verde .. .. .. .. .. .. Central African Republic .. .. .. .. .. .. Chad .. .. .. .. .. .. Comoros .. .. .. .. .. .. Congo, Dem. Rep. .. .. .. .. .. .. Congo, Rep. .. .. .. .. .. .. Côte d'Ivoire .. .. .. .. .. .. Djibouti .. .. .. .. .. .. Equatorial Guinea .. .. .. .. .. .. Eritrea .. .. .. .. .. .. Ethiopia 5.4 2.7 8.2 24.9 19.5 29.4 Gabon .. .. .. .. .. .. Gambia, The .. .. .. .. .. .. Ghana .. .. .. 16.6 16.4 16.7 Guinea .. .. .. .. .. .. Guinea-Bissau .. .. .. .. .. .. Kenya .. .. .. .. .. .. Lesotho .. .. .. .. .. .. Liberia 5.6 6.8 4.2 4.7 5.7 3.7 Madagascar 2.6 1.7 3.5 2.3 1.7 2.8 Malawi 7.8 5.4 10.0 .. .. .. Mali 8.8 7.2 10.9 .. .. .. Mauritania 33.0 25.2 41.2 .. .. .. Mauritius 8.5 5.3 14.4 24.6 20.0 31.3 Mozambique .. .. .. .. .. .. Namibia 21.9 19.4 25.0 44.8 40.4 49.3 Niger 1.5 1.7 0.9 3.2 4.0 1.7 Nigeria .. .. .. .. .. .. Rwanda .. .. .. .. .. .. São Tomé and Príncipe 16.7 11.0 24.5 .. .. .. Senegal .. .. .. .. .. .. Seychelles 5.5 6.1 4.9 20.3 .. .. Sierra Leone 3.4 4.5 2.3 5.2 7.3 3.5 Somalia .. .. .. .. .. .. South Africa 23.0 20.0 26.6 46.9 43.0 52.0 Sudan .. .. .. .. .. .. Swaziland .. .. .. .. .. .. Tanzania 4.7 4.4 5.8 8.9 .. .. Togo .. .. .. .. .. .. Uganda 3.2 2.5 3.9 .. .. .. Zambia 12.9 14.1 11.3 21.4 23.1 19.5 Zimbabwe 4.2 4.2 4.1 24.9 28.2 21.4 NORTH AFRICA Algeria 12.3 17.5 18.1 24.3 42.8 46.3 Egypt, Arab Rep. 11.2 7.1 25.1 34.1 23.3 62.2 Libya .. .. .. .. .. .. Morocco 10.0 10.1 10.0 17.6 18.2 16.1 Tunisia 14.2 13.1 17.3 30.7 31.4 29.3 a. Components may not sum to 100 percent because of unclassified data. b. Data are for the most recent year available during the period specified. 130 Part III. Development outcomes L ABOR, MIGRATION, AND POPULATION Unemployment by education levela (% of total unemployed) Primary Secondary Tertiary Total Male Female Total Male Female Total Male Female 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b 2000­07b .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 65.5 64.4 66.3 27.3 23.9 30.2 .. .. .. 47.0 44.4 58.3 19.7 16.7 33.3 6.1 5.6 8.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 35.9 50.6 30.8 13.3 19.0 11.3 3.2 5.7 2.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 67.7 68.7 67.1 .. .. .. 9.3 14.0 6.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 44.2 49.5 39.7 48.5 41.4 53.2 6.4 8.1 3.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 60.7 62.8 59.4 24.1 23.0 24.9 5.9 0.5 9.4 .. .. .. .. .. .. .. .. .. 40.2 42.2 37.9 6.9 7.5 6.2 2.5 2.8 2.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 36.2 39.8 32.9 56.3 52.7 59.7 4.5 4.0 5.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 59.3 65.2 32.5 23.0 21.4 30.4 11.4 6.6 33.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 51.1 57.7 36.6 22.4 21.7 23.9 21.6 16.2 33.5 79.1 83.3 70.4 .. .. .. 13.6 9.0 23.3 L ABOR, MIGRATION, AND POPULATION Part III. Development outcomes 131 Participating in growth 9.4 Table Migration and population Population International migration Population dynamics Workers remittances, Migrant remittance Migrant stock received inflows Annual Fertility rate Share of Net Total Share of Total Share of Total Male Female growth (births per population (%) Total migration ($ millions) GDP (%) ($ millions) GDP (%) (millions) (% of total) (% of total) rate (%) woman) 2005 2005 2005 2007 2007 2007 2007 2008 2008 2008 2008 2007 SUB­SAHARAN AFRICA 2.15 16,338,433 ­1,599,939 18,615.4 2.2 819.3 49.8 50.2 2.5 5.1 Angola 0.34 56,055 175,000 .. .. .. .. 18.0 49.3 50.7 2.7 5.8 Benin 2.38 187,584 98,831 .. .. 224.0 4.1 8.7 50.4 49.6 3.2 5.5 Botswana 4.37 80,148 20,000 80.0 0.7 141.2 1.2 1.9 49.9 50.1 1.3 2.9 Burkina Faso 5.55 772,814 100,000 .. .. 50.0 0.7 15.2 49.9 50.1 2.9 6.0 Burundi 1.11 81,566 191,600 0.2 0.0 0.2 0.0 8.1 49.0 51.0 3.0 4.7 Cameroon 1.19 211,880 ­12,121 154.0 0.7 167.4 0.8 18.9 50.0 50.0 2.0 4.3 Cape Verde 2.34 11,183 ­12,500 138.5 9.6 138.9 9.6 0.5 47.8 52.2 1.4 2.8 Central African Republic 1.8 75,623 ­45,000 .. .. .. .. 4.4 49.1 50.9 1.8 4.6 Chad 3.53 358,446 218,966 .. .. .. .. 11.1 49.7 50.3 2.8 6.2 Comoros 2.27 13,661 ­10,000 .. .. 12.0 2.6 0.6 50.2 49.8 2.4 4.3 Congo, Dem. Rep. 0.82 480,105 ­236,676 .. .. .. .. 64.2 49.6 50.5 2.9 6.3 Congo, Rep. 3.77 128,838 3,527 .. .. 14.8 0.2 3.6 49.9 50.1 1.8 4.4 Côte d'Ivoire 12.32 2,371,277 ­338,732 .. .. 179.4 0.9 20.6 51.0 49.0 2.3 4.7 Djibouti 13.72 110,333 0 3.5 0.4 28.6 3.5 0.8 50.0 50.0 1.8 4.0 Equatorial Guinea 0.95 5,800 15,000 .. .. .. .. 0.7 49.6 50.4 2.7 5.4 Eritrea 0.32 14,612 229,376 .. .. .. .. 5.0 49.2 50.9 3.2 5.1 Ethiopia 0.74 554,021 ­340,460 355.9 1.8 357.8 1.8 80.7 49.7 50.3 2.6 5.4 Gabon 17.86 244,550 9,566 .. .. 11.0 0.1 1.4 49.9 50.1 1.9 3.4 Gambia, The 15.18 231,739 31,127 45.7 7.1 47.3 7.4 1.7 49.6 50.4 2.8 5.1 Ghana 7.62 1,669,267 11,690 117.4 0.8 117.4 0.8 23.4 50.7 49.3 2.1 4.3 Guinea 4.35 401,217 ­425,000 15.1 0.3 150.7 3.3 9.8 50.5 49.5 2.3 5.5 Guinea-Bissau 1.31 19,219 1,181 .. .. 29.0 7.6 1.6 49.5 50.5 2.2 5.7 Kenya 2.22 790,071 25,144 645.2 2.4 1,588.0 5.9 38.5 50.0 50.0 2.7 5.0 Lesotho 0.32 6,247 ­36,000 12.9 0.8 443.3 26.6 2.0 47.1 52.9 0.6 3.4 Liberia 2.9 96,793 62,452 .. .. 64.6 8.8 3.8 49.7 50.3 4.6 5.2 Madagascar 0.23 39,699 ­5,000 .. .. 11.0 0.2 19.1 49.8 50.2 2.7 4.8 Malawi 2.11 278,806 ­30,000 .. .. 1.0 0.0 14.3 49.7 50.3 2.6 5.6 Mali 1.42 165,448 ­134,204 323.1 4.7 343.9 5.0 12.7 49.4 50.6 3.1 6.5 Mauritania 2.23 66,053 30,000 .. .. 2.0 0.1 3.2 50.7 49.3 2.5 4.4 Mauritius 3.28 40,824 0 .. .. 215.0 3.2 1.3 49.6 50.4 0.7 1.7 Mozambique 1.98 406,075 ­20,000 30.9 0.4 99.4 1.2 21.8 48.6 51.4 1.9 5.1 Namibia 6.52 131,630 ­1,000 6.2 0.1 16.2 0.2 2.1 49.3 50.7 1.6 3.6 Niger 1.38 182,960 ­28,497 .. .. 78.1 1.8 14.7 50.1 49.9 3.3 7.0 Nigeria 0.69 972,126 ­170,000 17,945.9 10.8 9,221.0 5.6 151.3 50.1 49.9 2.3 5.3 Rwanda 4.85 435,749 5,931 28.3 0.8 51.3 1.5 9.7 48.4 51.6 2.8 5.4 São Tomé and Príncipe 3.53 5,387 ­7,000 2.0 1.4 2.0 1.4 0.2 49.5 50.5 1.9 3.9 Senegal 1.95 220,208 ­100,000 1,106.7 9.8 1,191.8 10.6 12.2 49.6 50.4 2.7 5.0 Seychelles 10.18 8,441 .. 10.9 1.2 11.2 1.2 0.1 .. .. 1.5 .. Sierra Leone 2.98 152,101 336,000 146.3 8.8 148.4 8.9 5.6 48.7 51.3 2.6 5.2 Somalia 0.26 21,271 ­200,000 .. .. .. .. 9.0 49.6 50.4 3.0 6.0 South Africa 2.66 1,248,732 700,001 .. .. 833.7 0.3 48.7 49.3 50.7 1.8 2.7 Sudan 1.65 639,686 ­531,781 1,766.7 3.8 1,769.2 3.8 41.3 50.4 49.7 2.3 4.2 Swaziland 3.43 38,574 ­46,077 1.5 0.1 100.5 3.5 1.2 48.8 51.2 1.4 3.6 Tanzania 2.05 797,701 ­345,000 8.3 0.1 14.3 0.1 42.5 49.8 50.2 2.9 5.6 Togo 3.05 182,823 ­3,570 .. .. 229.0 9.2 6.5 49.5 50.5 2.5 4.3 Uganda 2.27 652,408 ­5,000 451.6 3.8 451.6 3.8 31.7 50.1 49.9 3.3 6.4 Zambia 2.45 287,337 ­81,713 59.3 0.5 59.3 0.5 12.6 49.9 50.1 2.5 5.9 Zimbabwe 3.14 391,345 ­700,000 .. .. .. .. 12.5 48.4 51.7 0.1 3.5 NORTH AFRICA 0.76 1,192,628 ­1,048,004 18,238.0 4.2 163.7 50.2 49.8 1.6 2.6 Algeria 0.74 242,446 ­140,000 .. .. 2,120.0 1.6 34.4 50.5 49.5 1.5 2.4 Egypt, Arab Rep. 0.32 246,745 ­291,405 7,655.8 5.9 7,655.8 5.9 81.5 50.3 49.7 1.8 2.9 Libya 10.43 617,536 14,000 .. .. 16.0 0.0 6.3 51.7 48.3 2.0 2.7 Morocco 0.17 51,020 ­550,000 6,730.5 9.0 6,730.5 9.0 31.2 49.1 50.9 1.2 2.4 Tunisia 0.35 34,881 ­80,599 1,446.3 4.1 1,715.8 4.9 10.3 50.3 49.7 1.0 2.0 132 Part III. Development outcomes L ABOR, MIGRATION, AND POPULATION Population Age composition (% of total) Dependency Geographic distribution (%) ratio Ages 0­14 Ages 15­64 Ages 65 and older (% of Share of total population Annual growth working-age Rural Urban Rural Urban Total Male Female Total Male Female Total Male Female population) population population population population 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 2008 42.7 21.5 21.2 54.2 26.9 27.3 3.1 1.4 1.7 85 63.5 36.5 1.7 3.9 45.3 22.6 22.7 52.3 25.7 26.6 2.5 1.1 1.4 91 43.3 56.7 0.6 4.2 43.2 22.0 21.2 53.6 27.1 26.4 3.2 1.3 1.9 87 58.8 41.2 2.5 4.1 33.7 17.0 16.7 62.6 31.4 31.2 3.7 1.5 2.2 60 40.4 59.6 ­0.6 2.5 46.2 23.5 22.7 51.8 25.6 26.2 2.0 0.8 1.2 93 80.4 19.6 2.4 5.1 39.0 19.5 19.5 58.2 28.4 29.9 2.8 1.1 1.7 72 89.6 10.4 2.6 5.9 41.1 20.7 20.4 55.4 27.7 27.7 3.6 1.6 1.9 81 43.2 56.8 0.1 3.4 36.9 18.6 18.4 58.7 27.7 31.0 4.3 1.5 2.9 70 40.4 59.6 ­0.4 2.7 40.9 20.4 20.5 55.2 27.0 28.2 3.9 1.7 2.2 81 61.4 38.6 1.6 2.2 45.8 23.0 22.8 51.3 25.4 25.9 2.9 1.3 1.6 95 73.3 26.7 2.2 4.5 38.2 19.4 18.8 58.7 29.4 29.3 3.1 1.4 1.7 70 71.9 28.1 2.3 2.6 47.0 23.5 23.4 50.4 24.9 25.5 2.7 1.2 1.5 98 66.0 34.0 1.9 4.7 40.7 20.5 20.2 55.5 27.7 27.8 3.8 1.7 2.1 80 38.7 61.3 0.8 2.4 40.9 20.5 20.4 55.3 28.5 26.9 3.8 2.0 1.8 81 51.2 48.8 1.0 3.7 36.6 18.5 18.2 60.2 30.1 30.1 3.2 1.4 1.8 66 12.7 87.3 ­1.4 2.2 41.2 20.7 20.5 55.8 27.6 28.3 3.0 1.3 1.6 79 60.6 39.4 2.4 3.0 41.5 20.9 20.6 56.0 27.3 28.8 2.4 0.9 1.5 78 79.3 20.7 2.6 5.3 43.9 22.1 21.8 53.0 26.3 26.7 3.2 1.4 1.7 89 83.0 17.0 2.2 4.4 36.8 18.6 18.2 58.9 29.4 29.5 4.3 2.0 2.4 70 15.0 85.0 ­1.3 2.4 42.5 21.4 21.1 54.7 26.9 27.8 2.8 1.3 1.5 83 43.6 56.4 0.8 4.2 38.7 19.8 18.9 57.7 29.2 28.5 3.6 1.7 1.9 73 50.0 50.0 0.6 3.6 43.0 21.9 21.1 53.9 27.2 26.6 3.2 1.4 1.8 86 65.6 34.4 1.5 3.7 42.7 21.4 21.3 53.9 26.6 27.3 3.4 1.6 1.9 86 70.2 29.8 2.1 2.5 42.8 21.5 21.3 54.6 27.2 27.4 2.7 1.2 1.4 83 78.4 21.6 2.3 4.0 39.2 19.7 19.5 56.1 25.4 30.7 4.8 2.0 2.7 78 74.5 25.5 ­0.4 3.4 42.9 21.6 21.3 54.0 26.7 27.3 3.1 1.4 1.7 85 39.9 60.1 2.8 5.6 43.3 21.7 21.6 53.7 26.7 27.0 3.1 1.4 1.6 86 70.5 29.5 2.2 3.8 46.4 23.4 23.0 50.5 24.8 25.7 3.1 1.4 1.7 98 81.2 18.8 1.9 5.2 44.2 22.3 21.9 53.4 25.9 27.5 2.3 1.1 1.2 87 67.8 32.2 2.2 4.8 39.8 20.5 19.3 57.6 29.1 28.5 2.7 1.1 1.6 74 59.0 41.0 2.2 3.0 23.2 11.8 11.4 69.8 35.0 34.8 7.0 2.8 4.2 43 57.5 42.5 0.5 0.8 44.1 22.1 22.0 52.7 25.1 27.6 3.3 1.4 1.9 90 63.2 36.8 0.7 4.0 37.4 18.8 18.6 59.0 29.0 30.1 3.6 1.5 2.1 69 63.2 36.8 0.7 3.2 49.7 25.4 24.3 48.3 23.8 24.6 2.0 0.9 1.1 107 83.5 16.5 3.2 3.8 42.7 21.6 21.1 54.2 27.0 27.2 3.1 1.4 1.7 84 51.6 48.4 0.9 3.7 42.2 20.9 21.3 55.3 26.5 28.8 2.5 1.0 1.5 81 81.7 18.3 2.4 4.3 41.0 20.7 20.3 55.0 27.0 27.9 4.1 1.8 2.3 82 39.4 60.6 ­0.2 3.2 43.8 22.1 21.7 53.8 26.4 27.4 2.4 1.1 1.3 86 57.6 42.4 2.2 3.3 .. .. .. .. .. .. .. .. .. .. 45.7 54.3 0.5 2.4 43.3 21.5 21.7 54.9 26.3 28.6 1.9 0.9 1.0 82 62.2 37.8 2.0 3.4 44.9 22.5 22.4 52.4 25.8 26.6 2.7 1.2 1.5 91 63.5 36.5 2.2 4.1 30.8 15.5 15.3 64.9 32.1 32.8 4.4 1.7 2.7 54 39.3 60.7 0.5 2.5 39.5 20.1 19.4 56.9 28.6 28.3 3.6 1.6 1.9 76 56.6 43.4 0.7 4.3 40.0 20.1 19.9 56.7 27.4 29.4 3.3 1.4 1.9 76 75.1 24.9 1.0 2.6 44.7 22.5 22.2 52.3 26.0 26.3 3.1 1.4 1.7 91 74.5 25.5 2.3 4.6 40.3 20.1 20.1 56.3 27.8 28.4 3.5 1.5 2.0 78 58.0 42.0 1.3 4.2 49.0 24.7 24.3 48.4 24.2 24.2 2.6 1.2 1.4 106 87.0 13.0 3.1 4.5 46.3 23.3 23.0 50.7 25.2 25.5 3.0 1.4 1.6 97 64.6 35.4 2.2 2.9 40.2 20.2 20.1 55.7 26.4 29.3 4.0 1.8 2.3 79 62.7 37.3 ­0.7 1.4 30.1 15.4 14.7 65.1 32.6 32.5 4.8 2.2 2.6 54 47.2 52.8 1.1 2.0 27.8 14.2 13.6 67.6 34.2 33.4 4.6 2.1 2.5 48 34.8 65.2 ­0.3 2.5 32.5 16.6 15.9 63.0 31.6 31.4 4.5 2.1 2.5 59 57.3 42.7 1.8 1.9 30.2 15.4 14.7 65.7 34.3 31.5 4.1 2.1 2.1 52 22.5 77.5 1.1 2.2 28.8 14.6 14.2 65.9 32.1 33.8 5.3 2.4 2.9 52 44.0 56.0 0.4 1.8 23.7 12.2 11.5 69.6 34.9 34.7 6.7 3.2 3.6 44 33.5 66.5 ­0.2 1.6 L ABOR, MIGRATION, AND POPULATION Part III. Development outcomes 133 Participating in growth 10.1 Table HIV/AIDS Estimated number of people Estimated HIV prevalence rate (%) living with HIV/AIDS Adults (ages 15­49) (thousands) Point estimate Low estimate High estimate 1990 2005 2007 1990 2005 2007 1990 2005 2007 1990 2005 2007 SUB­SAHARAN AFRICA 22,000.0 20,300.0 22,000.0 2.1 5.1 5.0 .. 5.4 4.6 .. 6.8 5.4 Angola 15.0 170.0 190.0 0.3 2.0 2.1 <0.1 1.6 1.7 4.3 2.8 2.5 Benin 3.5 61.0 64.0 0.1 1.3 1.2 <0.1 1.1 1.1 0.7 1.5 1.4 Botswana 33.0 290.0 300.0 4.7 24.9 23.9 3.8 23.9 22.5 5.4 25.9 24.9 Burkina Faso 84.0 130.0 130.0 1.9 1.7 1.6 0.1 1.5 1.4 3.3 2.0 1.9 Burundi 51.0 120.0 110.0 1.7 2.4 2.0 1.4 1.7 1.3 2.3 3.0 2.5 Cameroon 49.0 540.0 540.0 0.8 5.4 5.1 0.6 4.7 3.9 1.4 6.1 6.2 Cape Verde .. .. .. .. .. .. .. .. .. .. .. .. Central African Republic 26.0 150.0 160.0 1.8 6.4 6.3 1.4 6.0 5.9 3.4 6.8 6.7 Chad 19.0 190.0 200.0 0.7 3.5 3.5 0.1 3.0 2.4 6.0 4.1 4.3 Comoros .. <0.2 <0.2 <0.1 <0.1 <0.1 .. .. .. <0.1 <0.1 <0.1 Congo, Dem. Rep. .. 1,000.0 .. .. 3.2 .. .. 1.8 1.2 .. 4.9 1.5 Congo, Rep. 62.0 80.0 79.0 5.1 3.7 3.5 3.0 3.2 2.8 7.0 4.3 4.2 Côte d'Ivoire 130.0 520.0 480.0 2.2 4.6 3.9 0.2 4.1 3.2 6.0 5.0 4.5 Djibouti <1 15.0 16.0 0.2 3.1 3.1 0.1 2.4 2.3 0.7 3.8 3.8 Equatorial Guinea 1.8 10.0 11.0 1.0 3.6 3.4 0.1 2.8 2.6 1.3 4.9 4.6 Eritrea 2.1 34.0 38.0 0.1 1.2 1.3 <0.1 0.9 0.8 1.0 1.7 2.0 Ethiopia 190.0 900.0 980.0 0.7 2.1 2.1 0.5 1.9 1.8 1.1 2.3 2.2 Gabon 4.0 46.0 49.0 0.9 6.0 5.9 0.5 4.6 4.4 1.4 8.2 8.3 Gambia, The <0.2 7.6 8.2 .. 0.9 0.9 .. 0.4 0.4 <0.1 1.3 1.3 Ghana 4.1 260.0 260.0 0.1 2.0 1.9 0.1 1.8 1.7 0.2 2.2 2.2 Guinea 6.3 78.0 87.0 0.2 1.5 1.6 0.1 1.3 1.3 0.8 1.9 2.2 Guinea-Bissau <1 16.0 16.0 0.2 1.9 1.8 0.1 1.3 1.3 0.3 2.6 2.6 Kenya .. .. .. .. .. .. 2.7 6.1 7.1 3.6 8.1 8.5 Lesotho 5.9 270.0 270.0 0.8 23.4 23.2 0.6 22.2 21.9 1.1 24.6 24.5 Liberia 4.2 29.0 35.0 0.4 1.5 1.7 0.1 1.2 1.4 5.3 1.9 2.0 Madagascar <0.1 12.0 14.0 .. 0.1 0.1 .. <0.1 <0.1 .. 0.2 0.2 Malawi 90.0 900.0 930.0 2.1 12.3 11.9 0.9 11.4 11.0 7.4 13.3 12.9 Mali 6.9 97.0 100.0 0.2 1.5 1.5 <0.1 1.3 1.2 0.3 1.8 1.8 Mauritania <0.1 13.0 14.0 <0.1 0.8 0.8 .. 0.5 0.5 0.1 1.5 1.5 Mauritius <0.1 9.4 13.0 <0.1 1.2 1.7 .. 0.8 1.0 0.1 2.2 3.6 Mozambique 94.0 1,300.0 1,500.0 1.4 12.2 12.5 0.4 10.7 10.9 5.4 14.1 14.7 Namibia 8.1 180.0 200.0 1.2 15.3 15.3 0.7 12.7 12.4 1.9 17.9 18.1 Niger 3.1 55.0 60.0 0.1 0.8 0.8 <0.1 0.6 0.6 0.2 1.0 1.1 Nigeria 340.0 2,500.0 2,600.0 0.7 3.2 3.1 0.1 2.7 2.3 8.7 3.7 3.8 Rwanda 260.0 160.0 150.0 9.2 3.1 2.8 8.0 2.8 2.4 10.5 3.5 3.2 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 2.4 49.0 67.0 0.1 0.8 1.0 <0.1 0.6 0.7 0.2 0.9 1.4 Seychelles .. .. .. .. .. .. .. .. .. .. .. .. Sierra Leone 3.4 50.0 55.0 0.2 1.6 1.7 <0.1 1.3 1.3 0.5 2.0 2.4 Somalia <1 23.0 24.0 <0.1 0.5 0.5 .. 0.3 0.3 0.2 1.0 1.0 South Africa 160.0 5,600.0 5,700.0 0.8 18.2 18.1 0.5 15.4 15.4 1.2 21.1 20.9 Sudan 100.0 300.0 320.0 0.8 1.4 1.4 0.1 1.0 1.0 1.8 1.9 2.0 Swaziland 3.9 180.0 190.0 0.9 26.4 26.1 0.7 25.3 25.1 1.3 27.4 27.1 Tanzania 610.0 1,400.0 1,400.0 4.8 6.4 6.2 4.3 6.0 5.8 5.0 6.7 6.6 Togo 14.0 120.0 130.0 0.7 3.4 3.3 0.3 2.9 2.7 1.7 4.1 4.1 Uganda 1,200.0 980.0 940.0 13.7 6.1 5.4 12.4 5.8 5.0 16.1 6.7 6.1 Zambia 360.0 1,000.0 1,100.0 8.9 15.0 15.2 5.1 14.1 14.3 13.1 16.3 16.4 Zimbabwe 710.0 1,500.0 1,300.0 14.2 19.0 15.3 13.1 18.3 14.6 15.0 19.9 16.1 NORTH AFRICA Algeria .. 19.0 21.0 .. 0.1 0.1 .. <0.1 <0.1 .. 0.2 0.2 Egypt, Arab Rep. <1 8.1 9.2 .. .. .. .. .. <0.1 0.1 0.1 0.1 Libya .. .. .. .. .. .. .. .. <0.2 .. .. 0.2 Morocco 1.9 18.0 21.0 .. 0.1 0.1 .. <0.1 <0.1 0.1 0.2 0.2 Tunisia <0.5 3.2 3.7 .. 0.1 0.1 .. <0.1 <0.1 0.1 0.2 0.2 134 Part III. Development outcomes HIV/AIDS Estimated HIV prevalence rate (%) Young men (ages 15­24) Young women (ages 15­24) Point estimate Low estimate High estimate Point estimate Low estimate High estimate 2005 2007 2005 2007 2005 2007 2005 2007 2005 2007 2005 2007 .. 1.1 1.3 0.8 1.7 1.4 .. 3.2 3.7 2.6 5.1 3.8 0.9 0.2 0.4 0.1 1.4 0.4 2.5 0.3 1.2 0.1 4.2 0.5 0.4 0.3 0.2 0.1 0.6 0.5 1.1 0.9 0.6 0.6 1.8 1.2 5.7 5.1 5.6 2.1 7.5 7.9 15.3 15.3 15.2 10.0 20.3 20.8 0.5 0.5 0.3 0.2 0.6 0.8 1.4 0.9 0.8 0.5 2.0 1.3 0.8 0.4 0.7 0.2 0.9 0.7 2.3 1.3 2.0 0.6 2.7 2.0 4.1 1.2 1.3 0.5 1.6 2.2 6.8 4.3 4.4 1.0 5.3 5.9 .. .. .. .. .. .. .. .. .. .. .. .. 2.5 1.1 0.9 0.5 4.5 1.5 7.4 5.5 2.7 4.1 13.1 7.0 0.9 2.0 0.4 0.9 1.6 2.9 2.2 2.8 0.9 1.3 3.9 4.1 <0.1 0.1 0.2 <0.1 0.2 0.2 <0.1 <0.1 0.2 0.1 0.2 0.1 0.8 .. 0.3 0.1 1.3 0.4 2.2 .. 1.0 0.7 3.8 1.2 1.2 0.8 0.6 0.3 1.9 1.1 3.7 2.3 1.9 1.3 5.7 3.3 1.7 0.8 0.9 0.3 2.7 1.3 5.1 2.4 2.6 1.0 7.9 3.4 0.7 0.7 0.2 0.3 1.6 1.1 2.1 2.1 0.5 1.4 4.6 3.0 0.7 0.8 0.6 0.4 0.9 1.4 2.3 2.5 1.8 1.7 2.7 3.7 0.6 0.3 0.3 0.1 1.0 0.6 1.6 0.9 0.7 0.4 2.7 1.6 .. 0.5 0.2 0.2 0.8 0.7 .. 1.5 0.5 1.1 2.3 1.9 1.8 1.3 0.9 0.6 3.0 2.4 5.4 3.9 2.7 2.0 8.7 6.3 0.6 0.2 0.2 0.1 1.0 0.4 1.7 0.6 0.7 0.3 2.9 1.0 0.2 0.4 0.2 0.2 0.3 0.6 1.3 1.3 1.1 0.9 1.5 1.7 0.5 0.4 0.4 0.2 0.5 0.6 1.4 1.2 1.1 0.9 1.6 1.8 0.9 0.4 0.4 0.2 1.5 0.8 2.5 1.2 1.1 0.3 4.3 2.5 1.0 .. 0.9 0.8 1.2 2.5 5.2 .. 4.5 4.6 6.0 8.4 5.9 5.9 5.5 2.5 6.2 9.6 14.1 14.9 13.3 10.6 15.0 18.4 .. 0.4 .. 0.2 .. 0.6 .. 1.3 .. 0.8 .. 1.7 0.6 0.2 0.2 0.1 1.3 0.3 0.3 0.1 0.1 <0.1 0.6 0.2 3.4 2.4 1.4 0.9 5.9 3.8 9.7 8.4 3.9 6.7 16.8 10.4 0.4 0.4 0.3 0.2 0.5 0.5 1.2 1.1 0.9 0.7 1.5 1.5 0.2 0.9 0.1 0.4 0.3 1.9 0.5 0.5 0.2 0.2 1.0 1.0 .. 1.8 .. 0.8 .. 4.5 .. 1.0 .. 0.5 .. 2.2 3.6 2.9 2.0 1.2 5.3 4.2 10.7 8.5 6.0 5.9 15.8 11.1 4.4 3.4 1.7 1.4 8.1 5.3 13.4 10.3 5.2 6.2 24.7 14.5 0.2 0.9 0.1 0.4 0.4 1.5 0.8 0.5 0.3 0.3 1.4 0.8 0.9 0.8 0.4 0.3 1.5 1.2 2.7 2.3 1.3 1.2 4.4 3.3 0.8 0.5 0.7 0.3 0.8 0.7 2.0 1.4 1.9 0.9 2.0 1.9 .. .. .. .. .. .. .. .. .. .. .. .. 0.2 0.3 0.1 0.1 0.4 0.5 0.6 0.8 0.2 0.5 1.1 1.2 .. .. .. .. .. .. .. .. .. .. .. .. 0.4 0.4 0.2 0.2 0.6 0.7 1.1 1.3 0.6 0.7 1.7 1.9 0.2 0.6 0.1 0.3 0.4 1.4 0.6 0.3 0.3 0.1 1.1 0.6 4.5 4.0 4.0 1.7 4.9 6.0 14.8 12.7 13.2 9.1 16.3 17.0 .. 0.3 .. 0.2 .. 0.5 .. 1.0 .. 0.6 .. 1.5 7.7 5.8 3.9 2.2 12.1 9.3 22.7 22.6 11.5 17.7 35.9 27.2 2.8 0.5 2.5 0.4 3.1 0.7 3.8 0.9 3.4 0.5 4.2 1.3 0.8 0.8 0.4 0.4 1.2 1.2 2.2 2.4 1.0 1.4 3.6 3.3 2.3 1.3 1.9 0.6 2.6 1.9 5.0 3.9 4.2 2.7 5.7 5.2 3.8 3.6 3.6 1.6 4.0 5.2 12.7 11.3 11.9 8.5 13.6 14.2 4.4 2.9 2.3 1.2 6.9 4.4 14.7 7.7 7.7 3.8 23.2 11.7 .. 0.1 .. <0.1 .. 0.3 .. 0.1 .. <0.1 .. 0.2 .. .. .. <0.1 .. <0.1 .. .. .. <0.1 .. <0.1 .. .. .. .. .. .. .. .. .. .. .. .. .. 0.1 .. <0.1 .. 0.2 .. 0.1 .. <0.1 .. 0.2 .. 0.1 .. <0.1 .. 0.2 .. <0.1 .. 0.1 .. 0.1 (continued) HIV/AIDS Part III. Development outcomes 135 Participating in growth 10.1 Table HIV/AIDS (continued) Deaths of adults and children due to HIV/AIDS AIDS orphans (thousands) (ages 0­17, thousands) Point estimate Low estimate High estimate Point estimate Low estimate High estimate 1990 2005 2007 1990 2005 2007 1990 2005 2007 2005 2007 2005 2007 2005 2007 SUB­SAHARAN AFRICA .. 2,000.0 1,500.0 .. .. 1,300.0 .. .. 1,700.0 12,000.0 11,600.0 .. 10,600.0 .. 15,300.0 Angola <1.0 9.9 11.0 <0.1 6.0 7.1 8.5 33.0 28.0 160.0 50.0 95.0 20.0 230.0 260.0 Benin <0.1 3.7 3.3 .. 3.0 2.7 1.7 4.6 4.4 62.0 29.0 38.0 22.0 89.0 40.0 Botswana <1.0 12.0 11.0 <0.5 9.4 6.6 <1.0 15.0 17.0 120.0 95.0 110.0 81.0 150.0 110.0 Burkina Faso 3.7 9.6 9.2 <0.1 7.2 7.4 7.3 12.0 11.0 120.0 100.0 89.0 62.0 150.0 130.0 Burundi 2.2 13.0 11.0 1.7 11.0 8.6 3.5 16.0 14.0 120.0 120.0 94.0 100.0 170.0 150.0 Cameroon 1.0 43.0 39.0 <1.0 34.0 33.0 1.9 52.0 45.0 122.7 300.0 200.0 230.0 290.0 390.0 Cape Verde .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Central African Republic <1.0 12.0 11.0 .. 10.0 9.5 1.0 13.0 12.0 140.0 72.0 62.0 58.0 200.0 86.0 Chad <1.0 12.0 14.0 <0.1 7.7 11.0 11.0 24.0 20.0 57.0 85.0 28.0 42.0 97.0 270.0 Comoros .. .. .. .. .. .. .. <0.1 <0.1 .. <0.1 .. 0.2 .. 0.2 Congo, Dem. Rep. .. 90.0 .. .. 47.0 24.0 .. 150.0 34.0 680.0 .. 380.0 270.0 1,000.0 380.0 Congo, Rep. 1.6 7.3 6.4 1.0 6.2 3.0 3.0 8.9 10.0 110.0 69.0 70.0 57.0 150.0 84.0 Côte d'Ivoire 3.3 48.0 38.0 <0.5 41.0 33.0 20.0 56.0 43.0 450.0 420.0 280.0 320.0 630.0 530.0 Djibouti .. 1.0 1.1 .. <1.0 <1.0 <0.1 1.3 1.3 5.7 5.2 1.9 1.9 12.0 9.6 Equatorial Guinea <0.1 .. .. .. .. .. <0.2 <1.0 <1.0 4.6 4.8 3.5 3.8 5.9 6.1 Eritrea <0.1 2.4 2.6 .. 1.6 1.8 <1 3.9 3.9 36.0 18.0 20.0 12.0 56.0 32.0 Ethiopia 3.7 80.0 67.0 2.3 69.0 57.0 6.7 91.0 77.0 .. 650.0 280.0 540.0 870.0 780.0 Gabon <0.1 2.1 2.3 .. 1.2 1.4 <0.2 3.3 3.7 20.0 18.0 13.0 11.0 29.0 28.0 Gambia, The .. <0.5 .. .. .. .. <0.1 <1.0 <1.0 3.8 2.7 2.2 1.3 6.0 4.7 Ghana .. 22.0 21.0 .. 19.0 18.0 <0.1 25.0 24.0 139.6 160.0 .. 130.0 139.6 200.0 Guinea <0.5 4.1 4.5 <0.2 2.8 3.3 2.1 5.6 5.9 28.0 25.0 18.0 15.0 43.0 39.0 Guinea-Bissau .. 1.1 1.1 .. <1.0 <1.0 <0.1 1.5 1.5 11.0 5.9 6.0 4.2 16.0 8.3 Kenya .. .. .. 5.6 110.0 85.0 8.5 160.0 130.0 1,100.0 .. 890.0 990.0 1,300.0 1,400.0 Lesotho .. 20.0 18.0 .. 17.0 16.0 <0.1 22.0 20.0 97.0 110.0 88.0 93.0 110.0 120.0 Liberia <0.1 2.1 2.3 .. 1.5 1.7 1.5 6.1 4.7 .. 15.0 .. 10.0 .. 87.0 Madagascar .. .. <1.0 .. .. .. <0.1 1.0 1.3 13.0 3.4 5.0 2.1 24.0 6.0 Malawi 1.5 71.0 68.0 <1.0 64.0 59.0 5.5 80.0 77.0 550.0 550.0 310.0 470.0 780.0 640.0 Mali <0.2 5.5 5.8 .. 4.0 46.0 <1.0 7.0 7.3 94.0 44.0 70.0 27.0 120.0 56.0 Mauritania .. 1.0 1.0 .. 0.5 0.5 0.1 1.0 1.3 6.9 3.0 3.9 1.5 10.0 5.9 Mauritius .. <0.2 <1.0 .. <0.5 <0.5 <0.1 <0.5 <0.5 .. <0.5 .. 1.0 .. 1.0 Mozambique 2.7 78.0 81.0 <1.0 62.0 67.0 36.0 98.0 98.0 510.0 400.0 390.0 280.0 670.0 590.0 Namibia <0.2 9.2 5.1 .. 7.0 3.1 0.5 12.0 7.1 85.0 66.0 42.0 50.0 120.0 85.0 Niger <0.1 3.4 4.0 .. 2.5 3.0 0.2 5.1 5.6 46.0 25.0 20.0 18.0 85.0 39.0 Nigeria 9.6 180.0 170.0 <1.0 130.0 130.0 280.0 390.0 270.0 930.0 1,200.0 510.0 640.0 1,300.0 4,100.0 Rwanda 12.0 14.0 7.8 7.1 12.0 5.7 22.0 16.0 10.0 210.0 220.0 170.0 190.0 260.0 250.0 São Tomé and Principe .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Senegal <0.2 1.1 1.8 .. 1.0 1.2 <0.5 1.8 2.6 25.0 8.4 14.0 4.6 39.0 14.0 Seychelles .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Sierra Leone <0.1 3.2 3.3 .. 1.7 2.3 <0.2 5.1 4.7 31.0 16.0 19.0 6.4 49.0 26.0 Somalia <0.1 1.4 1.6 .. <1.0 <1.0 <0.2 2.5 3.0 23.0 8.8 11.0 4.9 45.0 16.0 South Africa 2.6 330.0 350.0 1.5 260.0 270.0 4.7 420.0 420.0 1,200.0 1,400.0 970.0 1,100.0 1,400.0 1,800.0 Sudan 1.3 24.0 25.0 <0.1 16.0 17.0 3.2 33.0 32.0 .. .. .. .. .. .. Swaziland <0.1 10.0 10.0 .. 8.9 8.6 <0.2 12.0 12.0 63.0 56.0 45.0 48.0 77.0 65.0 Tanzania 18.0 120.0 96.0 14.0 110.0 86.0 23.0 130.0 110.0 1,100.0 970.0 910.0 850.0 1,200.0 1,100.0 Togo <0.5 8.6 9.1 <0.1 6.7 6.9 2.0 11.0 12.0 88.0 68.0 51.0 50.0 130.0 91.0 Uganda 57.0 89.0 77.0 39.0 77.0 68.0 150.0 110.0 89.0 1,000.0 1,200.0 870.0 1,100.0 1,300.0 1,400.0 Zambia 6.9 75.0 56.0 <1.0 67.0 47.0 12.0 86.0 66.0 710.0 600.0 630.0 530.0 830.0 660.0 Zimbabwe 19.0 160.0 140.0 15.0 150.0 130.0 24.0 180.0 150.0 1,100.0 1,000.0 780.0 920.0 1,300.0 1,100.0 NORTH AFRICA Algeria .. <1.0 <1.0 .. <0.5 <0.5 .. 1.4 1.6 .. .. .. .. .. .. Egypt, Arab Rep. .. <0.5 <0.5 .. .. .. <0.1 <1.0 <1.0 .. .. .. .. .. .. Libya .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Morocco .. <1.0 <1.0 .. <0.5 .. <0.1 1.3 1.5 .. .. .. .. .. .. Tunisia .. <0.2 <0.2 .. .. .. <0.1 <0.5 <0.5 .. .. .. .. .. .. 136 Part III. Development outcomes HIV/AIDS HIV-positive pregnant women receiving antiretrovirals to reduce the risk of mother-to-child transmission Share of total ODA gross disbursements (WHO/UNAIDS methodology, %) ($ millions) For social mitigation For STD control, Total Point estimate Low estimate High estimate of HIV/AIDS including HIV/AIDS 2005 2006 2005 2007 2005 2007 2005 2007 2005 2007 2005 2007 35.5 76.7 1,731.3 2,683.1 .. 1,645 2 9 2 7 3 13 0.7 1.8 24.9 19.2 1,214 1,830 27 40 23 35 31 47 .. 0.0 27.3 8.9 7,543 12,419 64 >95 59 >95 70 >95 0.1 2.3 17.8 43.1 937 1,480 11 18 9 15 13 22 0.4 1.0 24.7 18.7 .. .. .. .. .. .. .. .. 0.3 0.7 25.3 8.4 3,592 7,516 10 22 9 18 12 34 0.0 0.0 7.7 30.8 12 51 .. .. .. .. .. .. .. .. 6.3 0.0 803 3,714 7 34 7 30 8 38 .. 0.0 6.0 1.4 193 .. 1 1 <1 1 2 2 .. 0.0 19.4 3.5 .. ­ .. 0 .. .. .. .. .. .. 0.1 0.3 1,725 3,435 5 9 4 8 6 10 .. 1.2 31.0 34.8 1,093 240 23 5 20 4 28 7 .. .. 0.5 2.7 2,543 3,240 8 12 7 9 9 16 0.1 0.2 25.2 46.1 16 .. 2 .. 2 .. 3 .. 0.0 .. 10.7 4.8 .. .. .. .. .. .. .. .. .. .. 2.2 0.4 88 168 4 7 3 4 5 11 .. 0.0 8.3 7.8 2,341 4,888 4 7 3 7 4 8 0.3 1.4 152.3 245.0 90 494 4 21 3 14 5 32 .. 0.0 0.7 3.2 87 133 .. .. 11 17 37 58 .. 0.0 15.2 3.3 1,078 2,896 7 21 7 18 8 24 0.0 0.6 21.3 40.5 77 679 1 11 1 8 2 14 0.0 0.0 20.4 4.5 .. 349 20 24 .. 17 .. 34 .. 0.0 0.4 1.3 19,403 52,858 24 69 21 61 28 80 0.5 4.7 84.4 222.1 1,811 3,966 14 32 13 29 16 36 .. 2.7 8.1 18.5 130 224 5 7 4 6 6 9 .. .. 4.7 7.7 8 25 .. .. 1 3 3 9 0.0 0.0 16.9 10.5 5,076 23,158 7 32 6 28 8 36 1.0 3.8 64.7 147.3 415 1,018 .. .. 4 10 6 15 0.1 0.0 11.2 20.0 10 45 .. .. 1 6 4 20 .. 0.0 0.4 0.9 .. 19 .. .. .. 6 .. 23 .. .. 0.0 1.3 8,490 44,975 9 46 8 39 11 56 1.2 6.2 81.3 149.1 4,055 .. 43 64 36 53 52 80 0.2 0.0 29.0 83.9 57 1,006 .. .. 1 20 3 47 .. 0.0 12.1 5.7 532 12,278 <1 7 <1 5 <1 10 0.9 1.0 132.7 213.7 5,785 6,485 51 60 45 51 58 71 1.0 1.6 63.3 97.9 8 22 .. .. .. .. .. .. .. .. 0.1 0.3 57 264 .. .. 1 4 2 9 0.0 .. 24.4 16.5 .. .. >95 .. .. .. .. .. .. .. .. 0.0 57 919 1 21 1 15 2 29 .. 0.0 12.8 5.9 .. 11 3 .. .. 1 .. 2 .. 0.0 6.0 7.9 75,077 127,164 34 57 29 49 40 69 4.7 9.9 131.9 284.2 .. .. .. .. .. .. .. .. .. 0.2 11.0 14.4 4,780 8,772 36 67 33 60 40 74 0.1 0.2 22.7 20.1 .. .. .. .. .. .. .. .. 1.8 6.1 135.1 194.1 720 705 9 9 7 7 11 11 .. 0.0 6.6 11.6 12,073 26,484 15 34 13 29 17 39 0.8 5.4 141.1 241.3 14,071 35,314 19 47 17 41 22 52 0.8 1.6 121.0 141.1 8,461 15,381 13 29 12 27 14 32 0.1 2.4 64.1 97.5 0.5 0.0 5.6 15.5 .. 19 .. .. .. 3 .. 12 .. 0.0 1.1 1.7 .. 5 .. .. .. 2 .. 2 .. 0.0 0.6 1.4 .. .. .. .. .. .. .. .. .. 0.0 .. 1.5 .. 42 .. .. .. 8 .. 18 .. 0.0 3.9 5.8 .. 1 .. .. .. 1 .. 3 .. 0.0 0.0 5.1 HIV/AIDS Part III. Development outcomes 137 Participating in growth 11.1 Table Malaria Children Pregnant sleeping under Children with fever receiving women receiving Under-five insecticide- any antimalarial treatment (% of two doses of mortality treated nets children under age 5 with fever) intermittent Population Clinical cases of Reported deaths rate (% of children Same or Any preventive (millions) malaria reported due to malaria (per 1,000) under age 5) next day time treatment (%) 2007 2008 2007 2008 2007 2008 2007 2000­08a 2000­08 a 2000­08a 2000­08a SUB­SAHARAN AFRICA 799.5 819.3 38,610,206 25,729,664 104,199 91,244 146 Angola 17.6 18.0 1,295,535 1,377,992 9,812 9,465 158 17.7 18 28 3 Benin 8.4 8.7 .. .. 1,195 .. 123 20.2 42 54 3 Botswana 1.9 1.9 464 1,201 6 12 40 .. .. .. .. Burkina Faso 14.8 15.2 44,246 36,514 6,472 7,834 191 9.6 41 48 1 Burundi 7.8 8.1 860,606 876,741 167 226 180 8.3 19 30 .. Cameroon 18.5 18.9 313,083 1,650,749 1,811 7,673 148 13.1 38 58 6 Cape Verde 0.5 0.5 18 35 2 2 32 .. .. .. .. Central African Republic 4.3 4.4 119,477 152,260 578 456 172 15.1 42 57 9 Chad 10.8 11.1 58,288 57,644 617 1,018 209 .. .. 53 .. Comoros 0.6 0.6 .. .. .. 47 66 9.3 .. 63 .. Congo, Dem. Rep. 62.4 64.2 759,059 1,462,300 14,637 18,928 161 5.8 .. 30 5 Congo, Rep. 3.6 3.6 .. .. .. .. 125 6.1 22 48 .. Côte d'Ivoire 20.1 20.6 1,277,670 1,343,654 797 1,249 127 5.9 26 36 8 Djibouti 0.8 0.8 210 119 1 .. 127 1.3 3 10 .. Equatorial Guinea 0.6 0.7 .. 50,758 .. .. 206 0.7 .. 49 .. Eritrea 4.8 5.0 9,195 4,702 42 19 70 4.2 2 4 .. Ethiopia 78.6 80.7 451,816 458,561 991 1,169 119 33.1 4 10 .. Gabon 1.4 1.4 45,186 40,701 216 156 91 .. .. .. .. Gambia, The 1.6 1.7 439,798 10,910 424 403 109 49.0 52 63 33 Ghana 22.9 23.4 476,484 827,438 4,622 3,889 115 28.2 48 24 27 Guinea 9.6 9.8 28,646 33,405 .. 441 150 0.3 .. 44 .. Guinea-Bissau 1.5 1.6 14,284 11,299 370 487 198 39.0 27 46 7 Kenya 37.5 38.5 9,610,691 839,904 .. .. 121 6.0 15 24 13 Lesotho 2.0 2.0 .. .. .. .. 84 .. .. .. .. Liberia 3.6 3.8 492,272 606,952 310 345 133 3.0 26 59 12 Madagascar 18.6 19.1 43,674 89,138 428 276 112 0.2 .. 34 .. Malawi 13.9 14.3 4,442,197 4,986,779 8,541 7,748 111 23.0 20 24 45 Mali 12.3 12.7 1,291,853 .. 1,782 1,227 196 27.1 15 32 4 Mauritania 3.1 3.2 .. 302 .. .. 119 2.1 10 21 .. Mauritius 1.3 1.3 .. .. .. .. 15 .. .. .. .. Mozambique 21.4 21.8 6,155,082 4,831,491 5,816 4,424 169 22.8 8 23 16 Namibia 2.1 2.1 4,242 4,907 181 171 68 .. .. 10 0 Niger 14.2 14.7 138,902 413,252 1,420 2,691 176 7.4 25 33 .. Nigeria 148.0 151.3 2,969,950 143,079 10,289 8,677 189 1.2 15 33 .. Rwanda 9.5 9.7 382,686 228,015 1,772 563 181 24.0 8 6 17 São Tomé and Príncipe 0.2 0.2 2,080 1,572 3 16 99 54.0 17 25 .. Senegal 11.9 12.2 95,169 202,466 1,935 722 114 31.0 9 22 49 Seychelles 0.1 0.1 .. .. .. .. 13 .. .. .. .. Sierra Leone 5.4 5.6 653,987 154,459 324 871 262 25.9 45 30 2 Somalia 8.7 9.0 16,058 23,905 33 21 142 9.2 3 8 1 South Africa 47.9 48.7 6,327 7,796 37 43 59 .. .. .. .. Sudan 40.4 41.3 560,428b 457,362b 1,254b 1,125b 109 27.6 .. .. .. Swaziland 1.2 1.2 84 58 14 5 91 0.6 .. 1 .. Tanzania 41.3 42.5 293 67 12,593 29 116 25.7 51 57 22 Togo 6.3 6.5 221,110 273,471 1,236 2,663 100 38.4 38 48 18 Uganda 30.6 31.7 1,050,240 894,505 7,003 2,372 130 9.7 29 62 16 Zambia 12.3 12.6 4,248,295 3,080,301 6,183 3,781 170 41.1 29 43 63 Zimbabwe 12.4 12.5 30,521 92,900 285 .. 90 2.9 3 5 6 NORTH AFRICA 161.2 163.7 393 418 .. .. 35 Algeria 33.9 34.4 288 196 .. .. 37 .. .. .. .. Egypt, Arab Rep. 80.1 81.5 30 80 .. .. 36 .. .. .. .. Libya 6.2 6.3 .. .. .. .. 18 .. .. .. .. Morocco 30.9 31.2 75 142 .. .. 34 .. .. .. .. Tunisia 10.2 10.3 .. .. .. .. 21 .. .. .. .. a. Data are for the most recent year available during the period specified. b. Data are for 15 northern states only. 138 Part III. Development outcomes MALARIA Capable states and partnership 12.1 Table Aid and debt relief Net official development assistance ($ millions) From all donors From DAC donors From non-DAC donors From multilateral donors From other donors 2007 2008 2007 2008 2007 2008 2007 2008 2007 2008 SUB­SAHARAN AFRICA 32,332 35,689 19,668 21,254 316 406 12,349 14,029 39 41 Angola 246 369 86 184 18 34 142 151 0 0 Benin 474 641 238 303 3 7 233 331 0 0 Botswana 108 716 64 683 ­1 ­1 45 35 .. 0 Burkina Faso 951 998 412 475 15 7 524 515 1 0 Burundi 473 509 200 255 0 0 273 253 0 0 Cameroon 1,908 525 1,697 298 9 11 203 216 0 0 Cape Verde 165 219 114 163 1 0 50 55 0 .. Central African Republic 177 256 118 129 0 0 59 128 0 .. Chad 354 416 223 277 0 0 130 138 0 0 Comoros 44 37 20 21 0 1 25 15 .. .. Congo, Dem. Rep. 1,241 1,610 788 944 1 8 452 657 .. 0 Congo, Rep. 119 505 48 421 1 1 70 84 .. 0 Côte d'Ivoire 171 617 112 193 1 4 59 419 0 1 Djibouti 112 121 75 66 0 10 37 45 0 .. Equatorial Guinea 31 38 26 24 0 0 6 13 0 0 Eritrea 157 143 45 53 3 7 109 84 2 7 Ethiopia 2,563 3,327 1,242 1,839 34 35 1,287 1,453 24 20 Gabon 51 55 34 38 1 1 16 16 0 0 Gambia, The 73 94 33 28 3 4 37 62 0 0 Ghana 1,154 1,293 708 723 2 6 443 564 0 0 Guinea 228 319 122 209 10 2 96 109 0 0 Guinea-Bissau 122 132 44 53 0 1 78 78 .. 0 Kenya 1,323 1,360 824 951 3 4 496 405 0 1 Lesotho 129 143 62 66 ­1 0 67 78 0 0 Liberia 698 1,250 226 809 1 37 471 404 0 0 Madagascar 895 841 387 274 6 4 502 563 0 0 Malawi 742 913 401 432 11 9 330 471 0 0 Mali 1,020 964 558 531 4 0 458 432 1 0 Mauritania 342 311 133 139 1 24 208 147 1 0 Mauritius 69 110 44 16 ­2 ­2 28 95 0 0 Mozambique 1,778 1,994 1,073 1,340 22 4 682 650 2 0 Namibia 217 207 144 150 1 2 73 54 0 0 Niger 542 605 233 269 2 2 307 335 0 0 Nigeria 1,956 1,290 1,385 636 1 3 570 651 0 1 Rwanda 722 931 374 450 2 3 347 477 0 0 São Tomé and Príncipe 36 47 31 26 0 0 5 21 .. .. Senegal 872 1,058 451 544 32 48 390 465 1 0 Seychelles 9 12 1 5 ­1 0 8 7 0 0 Sierra Leone 545 367 381 175 0 ­1 164 193 0 0 Somalia 384 758 257 565 4 8 124 185 0 0 South Africa 810 1,125 597 881 1 2 213 242 1 1 Sudan 2,112 2,384 1,664 1,818 114 106 334 459 3 6 Swaziland 51 67 12 18 0 ­1 39 50 .. 0 Tanzania 2,820 2,331 1,831 1,366 8 5 981 960 0 0 Togo 121 330 65 176 ­1 ­1 58 154 0 0 Uganda 1,737 1,657 1,002 1,005 4 5 731 647 0 0 Zambia 998 1,086 713 703 1 1 284 382 1 0 Zimbabwe 479 611 371 530 1 2 106 79 1 0 NORTH AFRICA 2,911 3,420 1,913 2,113 199 168 798 1,139 2 1 Algeria 390 316 289 241 8 ­23 93 98 .. 0 Egypt, Arab Rep. 1,107 1,348 787 960 82 114 238 274 1 1 Libya 19 60 15 52 2 2 3 6 .. 0 Morocco 1,073 1,217 628 612 118 81 327 524 0 0 Tunisia 321 479 194 248 ­10 ­7 137 237 0 0 (continued) CAPABLE STATES AND PARTNERSHIP Part III. Development outcomes 139 Capable states and partnership 12.1 Table Aid and debt relief (continued) Net private official development assistance ($ millions) Net official development assistance Share of gross capital From all donors From DAC donors From non-DAC donors Share of GDP (%) Per capita ($) formation (%) 2007 2008 2007 2008 2007 2008 2007 2008 2007 2008 2007 2008 SUB­SAHARAN AFRICA 31,203 5,606 30,994 5,337 209 269 3.7 3.5 40.4 43.6 19.2 18.7 Angola 293 2,151 292 2,145 0 6 0.4 0.4 14.0 20.5 2.9 3.6 Benin 35 4 35 4 .. .. 8.7 9.6 56.5 74.0 .. .. Botswana 30 ­89 30 ­89 .. .. 0.9 5.5 57.2 376.1 2.1 12.3 Burkina Faso ­60 17 ­60 17 .. .. 14.1 12.6 64.4 65.6 .. .. Burundi 11 ­38 11 ­38 .. .. 48.3 43.7 60.4 63.0 .. .. Cameroon ­173 90 ­173 90 .. 0 9.2 2.2 103.0 27.8 53.3 12.0 Cape Verde ­10 45 ­10 45 .. .. 11.4 12.6 335.9 438.2 28.3 29.5 Central African Republic 15 ­22 15 ­22 .. 0 10.3 13 40.7 58.0 116.3 126.1 Chad 52 43 52 43 .. .. 5 5 32.8 37.6 26.2 33.1 Comoros ­76 1 ­76 1 .. .. 9.6 7 70.8 57.9 69.5 43.8 Congo, Dem. Rep. ­26 0 ­28 0 3 0 12.5 13.9 19.9 25.1 63.8 81.7 Congo, Rep. 777 124 776 123 0 1 1.6 4.7 33.4 139.7 5.7 .. Côte d'Ivoire 100 49 99 47 2 2 0.9 2.6 8.5 29.9 10.0 26.2 Djibouti 21 33 21 33 .. .. 13.7 13.8 135.0 142.6 35.4 .. Equatorial Guinea ­265 ­1,014 ­265 ­1,014 .. .. 0.2 0.2 48.8 57.1 0.7 0.8 Eritrea 2 ­6 2 ­6 .. .. 11.4 8.7 32.4 28.6 108.2 .. Ethiopia ­53 ­140 ­59 ­145 6 5 13.2 12.6 32.6 41.2 53.0 60.3 Gabon 638 ­241 638 ­241 .. .. 0.4 0.4 36.0 37.6 1.7 1.4 Gambia, The 32 3 32 3 .. .. 11.4 12 45.3 56.5 49.0 47.8 Ghana 571 206 570 190 2 15 7.7 8 50.5 55.4 22.6 25.1 Guinea 12 ­61 12 ­61 1 0 5 7.5 23.7 32.4 39.6 58.7 Guinea-Bissau ­20 ­15 ­20 ­15 .. .. 32 30.6 79.4 83.5 131.7 123.3 Kenya 1,113 ­25 1,113 ­25 0 .. 4.9 3.9 35.2 35.3 24.3 16.0 Lesotho ­9 ­5 ­9 ­5 .. .. 7.7 8.8 64.2 71.1 29.1 30.7 Liberia 1,427 829 1,427 828 0 0 95 143.7 192.5 329.6 475.1 .. Madagascar 278 206 144 96 134 110 12.2 9.4 48.1 44.0 44.3 26.3 Malawi ­18 ­5 ­18 ­5 .. .. 20.7 21.4 53.3 63.9 80.1 66.9 Mali 28 ­25 28 ­25 .. .. 14.9 11 82.7 75.8 63.9 .. Mauritania ­140 ­9 ­140 ­9 .. .. 12.9 10.9 109.5 97.1 49.9 .. Mauritius 11,684 1,237 11,684 1,140 .. 97 1 1.3 54.6 86.4 3.8 5.0 Mozambique 272 ­10 272 ­10 .. .. 22.2 20.5 83.2 91.5 119.0 88.9 Namibia ­37 317 ­37 317 .. .. 2.5 2.4 104.5 97.8 11.9 10.7 Niger ­221 ­26 ­221 ­26 .. .. 12.8 11.3 38.2 41.3 .. .. Nigeria ­544 1,845 ­569 1,835 26 10 1.2 0.6 13.2 8.5 .. .. Rwanda 47 10 47 10 .. 0 21.2 20.9 76.4 95.7 102.2 100.6 São Tomé and Príncipe ­17 ­5 ­17 ­5 .. .. 24.8 26.9 227.7 292.2 .. .. Senegal 127 163 127 163 0 1 7.7 8 73.3 86.6 25.0 26.5 Seychelles 128 35 128 35 .. .. 1 1.5 102.7 139.9 2.9 5.1 Sierra Leone ­96 2 ­96 2 .. .. 32.8 18.8 100.6 66.0 243.9 95.6 Somalia 7 4 7 4 .. .. .. .. 44.2 84.7 .. .. South Africa 11,415 5,735 11,385 5,718 30 17 0.3 0.4 16.9 23.1 1.3 1.8 Sudan 19 ­14 16 ­17 4 3 4.6 4.1 52.2 57.6 18.8 17.3 Swaziland ­5 2 ­5 2 .. .. 1.8 2.6 44.0 57.7 13.5 17.2 Tanzania ­447 123 ­449 122 2 1 16.8 11.4 68.3 54.9 .. .. Togo 82 32 82 32 .. .. 4.9 11.7 19.3 51.0 .. .. Uganda 38 112 38 112 .. .. 14.6 11.4 56.7 52.3 66.1 48.4 Zambia 169 399 169 399 0 0 8.8 7.6 81.1 86.0 36.5 34.1 Zimbabwe 46 19 46 19 .. .. .. .. 38.4 49.0 .. .. NORTH AFRICA 11,907 20,309 11,782 20,076 125 232 0.7 0.6 18.1 20.9 2.6 2.3 Algeria 1,874 222 1,874 218 1 4 0.3 0.2 11.5 9.2 0.9 0.5 Egypt, Arab Rep. 5,348 15,203 5,312 15,183 36 20 0.8 0.8 13.8 16.5 4.1 3.5 Libya 1,879 1,488 1,840 1,447 39 42 0 0.1 3.2 9.6 .. .. Morocco 1,495 1,584 1,495 1,579 0 5 1.4 1.4 34.8 39.0 4.4 4.2 Tunisia 931 1,367 881 1,206 50 161 0.9 1.2 31.4 46.4 3.7 4.8 a. As of 2009. 140 Part III. Development outcomes CAPABLE STATES AND PARTNERSHIP Net official development assistance Share of imports of goods Share of central government Cereal food aid shipments Heavily Indebted Poor Countries Debt service and services (%) expenditures (%) (thousands of metric tons) (HIPC) Debt Initiative relief committed 2007 2008 2007 2008 2005 2006 Decision pointa Completion pointa ($ millions)a 4.4 3.5 25.4 24.9 3,035 2,204 52,315 0.4 0.3 .. .. 38 7 .. .. .. .. 9 6 Jul. 2000 Mar. 2003 460 1.0 6.4 4.5 28.7 .. .. .. .. .. .. 28 24 Jul. 2000 Apr. 2002 930 .. .. .. .. 67 38 Aug. 2005 Jan. 2009 1,472 21.3 3.9 100.0 17.7 15 5 Oct. 2000 Apr. 2006 4,917 15.4 16.9 55.5 68.8 25 16 27.8 34.7 389.6 375.0 7 8 Sep. 2007 Jun. 2009 6.0 6.4 82.8 85.7 63 61 May 2001 260 19.3 14.1 77.6 58.2 .. .. 19.1 24.6 120.2 126.1 68 80 Jul. 2003 Floating 10,389 1.3 .. 11.0 .. 4 5 Mar. 2006 Floating 2,881 1.0 2.7 10.3 32.4 21 13 Mar. 1998/Mar. 2009 9.9 .. 52.8 .. 16 8 0.2 0.2 10.9 7.7 .. .. 28.1 .. 36.4 .. 91 10 29.3 31.2 124.6 110.9 699 504 Nov. 2001 Apr. 2004 3,275 0.4 0.3 5.0 4.8 .. .. 13.7 15.2 70.4 76.0 10 6 Dec. 2000 Dec. 2007 90 8.2 8.0 54.7 59.0 66 21 Feb. 2002 Jul. 2004 3,500 6.5 12.9 82.8 153.7 29 19 Dec. 2000 Floating 800 44.1 38.5 208.6 221.0 4 7 Dec. 2000 Floating 790 7.7 6.2 28.6 36.5 143 245 5.0 5.6 30.4 33.0 15 7 81.2 .. 652.4 .. 48 42 Mar. 2008 15.8 12.0 257.2 204.5 36 37 Dec. 2000 Oct. 2004 1,900 30.4 28.7 180.4 195.6 95 52 Dec. 2000 Aug. 2006 1,000 23.1 .. 138.8 .. 28 49 Sep. 2000 Mar. 2003 895 10.6 .. 64.4 .. 63 38 Feb. 2000 Jun. 2002 1,100 0.8 1.0 7.4 9.8 .. .. 27.1 27.7 188.2 166.8 119 81 Apr. 2000 Sep. 2001 4,300 2.6 2.8 13.0 13.4 1 0 .. .. .. .. 101 93 Dec. 2000 Apr. 2004 1,190 1.7 0.8 .. .. .. .. 56.6 58.6 198.6 228.6 29 19 Dec. 2000 Apr. 2005 1,316 .. .. .. .. 1 0 Dec. 2000 Mar. 2007 200 10.5 11.1 77.2 80.1 15 12 Jun. 2000 Apr. 2004 850 0.4 0.5 5.3 9.8 .. .. 66.5 30.3 312.3 147.7 27 19 Mar. 2002 Dec. 2006 950 .. .. .. .. 102 115 0.4 0.5 1.5 2.0 .. .. 10.4 9.1 30.9 24.8 541 425 1.1 1.6 11.7 10.9 15 4 .. .. .. .. 62 7 Apr. 2000 Nov. 2001 3,000 4.7 10.8 26.1 71.7 0 0 Nov. 2008 30.9 23.3 113.2 97.0 142 36 Feb. 2000 May 2000 1,950 11.3 10.7 83.9 84.0 74 19 Dec. 2000 Apr. 2005 3,900 .. .. .. .. 115 68 1.0 0.8 5.8 7.0 34 35 0.4 0.2 2.4 2.7 29 10 1.3 1.0 7.5 7.7 5 24 .. .. .. .. .. .. 1.8 1.6 7.8 9.1 .. .. 0.8 0.9 6.4 8.8 .. .. CAPABLE STATES AND PARTNERSHIP Part III. Development outcomes 141 Capable states and partnership 12.2 Table Status of Paris Declaration indicators PDI-1 PDI-2 PDI-3 PDI-4 PDI-5 Reliable Technical Aid for government Aid for government country Government assistance aligned sectors uses sectors uses Operational national Reliable public procure- budget estimates and coordinated country public of country development financial ment comprehensive with country financial manage- procurement strategiesa managementb systemsc and realistic (%) programs (%) ment systems (%) systems (%) 2005 2007 2005 2007 2007 2005 2007 2005 2007 2005 2007 2005 2007 SUB­SAHARAN AFRICA Angolad Benin C C 4.0 3.5 .. 46.7 28.5 56.3 53.9 51.8 47.5 64.1 63.3 Botswanad Burkina Faso C B 4.0 4.0 .. 67.5 92.2 3.4 56.4 44.5 43.2 60.4 53.8 Burundi D C 2.5 3.0 .. 39.3 53.9 42.6 41.0 24.5 32.7 19.4 34.6 Cameroon C C 3.5 3.5 B .. 85.7 .. 29.9 .. 53.1 .. 63.1 Cape Verde C C 3.5 4.0 .. 85.1 90.2 92.7 39.3 64.1 22.5 53.5 22.1 Central African Republic D D 2.0 2.0 .. .. 36.4 .. 36.5 .. 23.8 .. 10.2 Chad C C 3.0 9.0 .. .. 87.9 .. 64.4 .. 1.0 .. 10.6 Comorosd Congo, Dem. Rep. D D 2.5 2.5 .. 81.0 58.3 10.7 38.1 12.9 0.0 30.8 0.8 Congo, Rep. Côte d'Ivoire D E 2.5 2.0 .. .. 64.4 .. 30.9 .. 0.0 .. 9.3 Djiboutid Equatorial Guinead Eritread Ethiopia C B 3.5 4.0 .. 74.4 61.7 27.3 66.8 45.2 46.7 42.8 41.4 Gabon .. .. 9.0 9.0 .. .. 22.4 .. 70.4 .. 4.7 .. 32.3 Gambia, Thed Ghana C B 3.5 4.0 C 96.1 94.5 40.4 73.8 62.1 50.8 51.9 56.1 Guinead Guinea-Bissaud Kenya D C 3.5 3.5 .. 90.9 64.2 60.2 63.8 47.3 53.6 44.7 36.8 Lesothod Liberia D D 9.0 9.0 .. .. 0.0 .. 35.3 .. 32.0 .. 0.0 Madagascar C C 3.0 3.5 .. .. 87.0 .. 70.9 .. 21.5 .. 25.9 Malawi C C 3.0 3.0 C 53.6 63.7 46.6 52.3 54.7 49.9 35.0 35.4 Mali C C 4.0 3.5 .. 60.0 72.6 15.1 75.4 29.5 34.4 44.6 34.8 Mauritania B C 2.0 2.5 .. 65.4 57.4 19.5 53.4 4.4 8.3 19.7 22.2 Mauritiusd Mozambique C C 3.5 3.5 .. 83.3 82.5 38.1 26.9 35.8 43.5 38.0 53.8 Namibiad Niger C C 3.5 3.5 B 99.5 90.7 15.3 50.2 27.1 25.5 48.7 36.5 Nigeria .. C 3.0 3.0 .. .. 6.3 .. 70.6 .. 0.0 .. 0.0 Rwanda B B 3.5 4.0 B 49.0 51.0 57.8 83.6 39.2 42.0 46.0 42.9 São Tomé and Prínciped Senegal C C 3.5 3.5 B 88.9 87.7 18.1 54.1 22.7 19.0 28.9 41.3 Seychellesd Sierra Leone D C 3.5 3.5 B .. 53.6 .. 22.5 .. 20.1 .. 38.3 Somaliad South Africa .. .. .. .. .. 70.8 .. 95.1 .. 38.1 .. 43.7 .. Sudan D D 2.5 2.0 .. .. 84.6 .. 53.2 .. 3.1 .. 0.4 Swazilandd Tanzania B B 4.5 4.0 B 89.5 83.6 49.5 60.5 65.9 71.5 61.2 68.5 Togo .. .. 2.0 2.0 .. .. 68.9 .. 28.9 .. 4.4 .. 15.5 Uganda B B 4.0 4.0 B 79.1 98.4 41.6 58.1 60.2 57.0 54.2 36.9 Zambia C B 3.0 3.5 C 51.9 73.5 32.4 34.5 34.1 59.4 43.5 71.0 Zimbabwed NORTH AFRICA Algeriad Egypt, Arab Rep. .. .. 9.0 9.0 .. 58.2 57.4 76.3 86.2 28.2 12.0 24.9 22.7 Libya .. .. .. .. .. .. .. .. .. .. .. .. .. Morocco .. .. 9.0 9.0 .. .. 79.8 .. 82.2 .. 78.9 .. 81.1 Tunisiad Note: See Technical notes for further details. PDI is Paris Declaration Indicator. a. Ratings range from A to E, where A means the development strategy substantially achieves good practices; B means it is largely developed toward achieving good practices; C means it reflects action taken toward achieving good practices; D means it incorporates some elements of good practice; and E means it reflects little action toward achieving good practices. b. Ratings range from 1 (low) to 6 (high). c. Ratings range from A (high) to D (low). Indicator was not collected in 2005. d. Did not take part in the Survey on Monitoring the Paris Declaration. 142 Part III. Development outcomes CAPABLE STATES AND PARTNERSHIP PDI-6 PDI-7 PDI-8 PDI-9 PDI-10 PDI-11 PDI-12 Project Existence of implementation Aid disbursements Aid provided in a monitorable Existence units parallel to on schedule the framework of performance of a mutual country structures and recorded by Bilateral aid that program-based Donor missions Country analysis assessment accountability (number) government (%) is untied (%) approaches (%) coordinated (%) coordinated (%) frameworka reviewa 2005 2007 2005 2007 2005 2007 2005 2007 2005 2007 2005 2007 2005 2007 2005 2007 29.0 58.0 53.0 31.6 79.3 98.8 60.8 49.0 14.5 25.1 37.5 44.0 C C B B 131.0 102.0 91.7 91.6 92.4 91.8 45.3 57.2 16.8 12.8 45.2 39.0 C C B B 37.0 29.0 52.5 44.4 59.8 90.6 53.6 35.5 24.3 13.5 55.0 73.8 D D B A .. 38.0 .. 50.8 .. 98.5 .. 39.6 .. 25.8 .. 49.2 D D .. B 10.0 18.0 92.2 96.4 22.3 60.3 36.7 30.9 10.5 43.4 34.1 64.5 D C A B .. 11.0 .. 45.2 .. 86.7 .. 34.3 .. 9.8 .. 23.2 D D .. B .. 17.0 .. 0.0 .. 81.2 .. 1.5 .. 18.1 .. 35.0 D D .. .. 34.0 146.0 82.9 19.5 88.1 93.9 53.8 20.8 38.4 21.3 35.2 22.9 D D B B .. 29.0 .. 67.0 .. 91.7 .. 2.6 .. 65.0 .. 75.0 D E .. B 103.0 56.0 95.9 73.4 38.8 82.2 52.6 65.6 26.7 29.4 49.5 69.5 C C A A .. 5.0 .. 16.8 .. 99.7 .. 0.0 .. 4.7 .. 36.8 .. .. .. B 45.0 16.0 91.6 82.3 89.9 91.8 52.7 68.8 19.7 39.0 39.9 59.8 C C A A 17.0 21.0 44.0 46.5 78.3 84.5 44.6 30.5 9.2 48.4 32.3 78.0 C C B B .. 16.0 .. 0.0 .. 82.4 .. 21.3 .. 11.0 .. 65.6 D D .. B .. 48.0 .. 79.5 .. 83.9 .. 43.5 .. 23.8 .. 41.6 C C .. B 69.0 51.0 57.7 58.1 96.9 90.5 31.8 42.0 23.8 22.3 60.0 60.8 C C A A 65.0 60.0 70.7 68.2 95.0 93.4 48.1 40.6 7.4 15.2 30.0 39.3 D D B B 23.0 27.0 39.4 52.1 72.9 67.0 36.7 35.1 13.8 11.4 58.9 25.4 C C B B 40.0 26.0 70.1 73.7 89.0 90.8 46.3 46.4 46.5 16.8 63.2 31.7 C B A A 52.0 47.0 73.2 77.5 83.8 84.3 31.2 49.0 20.9 15.4 39.9 31.8 D D B B .. 23.0 .. 7.1 .. 99.2 .. 3.9 .. 19.1 .. 32.8 .. C .. B 48.0 41.0 65.6 66.8 81.6 95.1 41.5 38.4 8.5 20.8 36.4 42.0 C C B B 23.0 55.0 69.3 60.8 90.8 93.0 57.3 38.9 15.1 16.6 40.5 28.1 C C B B .. 2.0 .. 29.7 .. 91.6 .. 26.9 .. 27.1 .. 56.3 D D .. B 15.0 .. 44.2 .. 97.2 97.4 26.5 .. 18.8 .. 75.0 .. .. .. A .. .. 105.0 .. 51.6 .. 79.9 .. 19.2 .. 14.9 .. 44.7 D D .. B 56.0 28.0 70.2 60.8 94.6 98.9 55.5 60.8 17.3 15.8 38.3 64.9 B B A A .. 13.0 .. 14.3 .. 56.1 .. 38.9 .. 15.1 .. 20.7 .. .. .. B 54.0 55.0 84.0 74.4 81.0 85.4 49.9 65.7 17.2 21.0 40.1 54.0 B B B B 24.0 34.0 50.1 85.1 99.1 99.6 47.1 46.8 14.7 15.9 45.8 46.4 D C A B 100.0 32.0 29.2 78.9 46.7 75.0 61.2 48.9 18.1 21.6 40.0 56.1 .. .. A B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 47.0 .. 68.3 .. 90.1 .. 70.3 .. 11.7 .. 25.0 .. .. .. B CAPABLE STATES AND PARTNERSHIP Part III. Development outcomes 143 Capable states and partnership 12.3 Table Capable states Investment climate Firms that believe Viewed by firms as major or very the court system is severe constraints (% of firms) Enforcing contracts fair, impartial, and Crime, theft, Number of Time required Cost uncorrupt (%) Corruption and disorder procedures (days) (% of debt) 2007­09 b 2007­09 b 2007­09 b 2010 2010 2010 SUB­SAHARAN AFRICA .. .. .. 39 656 48.9 Angola .. .. .. 46 1,011 44.4 Benin .. .. .. 42 825 64.7 Botswana .. .. .. 29 687 28.0 Burkina Faso .. .. .. 37 446 83.0 Burundi .. .. .. 44 832 38.6 Cameroon .. .. .. 43 800 46.6 Cape Verde .. .. .. 37 425 21.8 Central African Republic .. .. .. 43 660 82.0 Chad .. .. .. 41 743 77.4 Comoros .. .. .. 43 506 89.4 Congo, Dem. Rep. .. .. .. 43 625 151.8 Congo, Rep. 32.3 65.0 44.1 44 560 53.2 Côte d'Ivoire 35.3 75.0 53.8 33 770 41.7 Djibouti .. .. .. 40 1,225 34.0 Equatorial Guinea .. .. .. 40 553 18.5 Eritrea .. .. .. 39 405 22.6 Ethiopia .. .. .. 37 620 15.2 Gabon 41.3 41.4 34.1 38 1,070 34.3 Gambia, The .. .. .. 32 434 37.9 Ghana 59.8 9.9 0.9 36 487 23.0 Guinea .. .. .. 50 276 45.0 Guinea-Bissau .. .. .. 41 1,140 25.0 Kenya 22.3 38.4 3.9 40 465 47.2 Lesotho 33.2 46.7 33.5 41 695 19.5 Liberia 44.3 31.2 26.8 41 1,280 35.0 Madagascar 28.8 42.7 48.1 38 871 42.4 Malawi .. .. .. 42 432 142.4 Mali 49.6 15.7 0.6 36 626 52.0 Mauritania .. .. .. 46 370 23.2 Mauritius 63.6 50.7 41.5 36 720 17.4 Mozambique 16.6 25.4 1.8 30 730 142.5 Namibia .. .. .. 33 270 35.8 Niger .. .. .. 39 545 59.6 Nigeria 53.5 24.7 4.1 39 457 32.0 Rwanda .. .. .. 24 260 78.7 São Tomé and Príncipe .. .. .. 43 1,185 50.5 Senegal 55.4 23.8 0.5 44 780 26.5 Seychelles .. .. .. 38 720 14.3 Sierra Leone 29.7 36.9 14.2 40 515 149.5 Somalia .. .. .. .. .. .. South Africa 59.6 16.9 1.0 30 600 33.2 Sudan .. .. .. 53 810 19.8 Swaziland .. .. .. 40 972 23.1 Tanzania .. .. .. 38 462 14.3 Togo .. .. .. 41 588 47.5 Uganda .. .. .. 38 510 44.9 Zambia 55.0 12.1 1.0 35 471 38.7 Zimbabwe .. .. .. 38 410 32.0 NORTH AFRICA .. .. .. 42 705 23.8 Algeria .. 64.3 0.9 46 630 21.9 Egypt, Arab Rep. .. 59.3 0.0 41 1,010 26.2 Libya .. .. .. .. .. .. Morocco 43.5 27.3 0.0 40 615 25.2 Tunisia .. .. .. 39 565 21.8 a. Average of the disclosure, director liability, and shareholder suits indexes. b. Data are for the most recent year available during the period specified. 144 Part III. Development outcomes CAPABLE STATES AND PARTNERSHIP Regulation and tax administration Protecting investors Time required (0 least desirable to 10 most desirable) to prepare, file, Extractive Industries Disclosure Director liability Shareholder Investor protection Number of tax and pay taxes Total tax rate Transparency index index suits index indexa payments (hours) (% of profit) Initiative status 2010 2010 2010 2010 2010 2010 2010 2009 5 3 5 4.4 38 302 66.8 5 6 6 5.7 31 272 53.2 6 1 3 3.3 55 270 73.3 7 8 3 6.0 19 140 17.1 6 1 4 3.7 46 270 44.9 4 1 5 3.3 32 140 278.6 Candidate 6 1 6 4.3 41 1400 50.5 1 5 6 4.0 56 100 49.7 Candidate 6 1 5 4.0 54 504 203.8 6 1 5 4.0 54 122 60.9 Candidate 6 1 5 4.0 20 100 41.1 3 3 4 3.3 32 308 322.0 6 1 3 3.3 61 606 65.5 Candidate 6 1 3 3.3 66 270 44.7 Candidate 5 2 0 2.3 35 114 38.7 Candidate 6 1 4 3.7 46 296 59.5 4 5 5 4.7 18 216 84.5 Candidate 4 4 5 4.3 19 198 31.1 6 1 3 3.3 26 272 44.7 Intent to implement 2 1 5 2.7 50 376 292.4 Candidate 7 5 6 6.0 33 224 32.7 6 1 1 2.7 56 416 49.9 Candidate 6 1 5 4.0 46 208 45.9 Candidate 3 2 10 5.0 41 417 49.7 2 1 8 3.7 21 324 18.5 4 1 6 3.7 32 158 43.7 5 6 6 5.7 23 201 39.2 Compliant 4 7 5 5.3 19 157 25.8 Candidate 6 1 4 3.7 58 270 52.1 5 3 3 3.7 38 696 86.1 Candidate 6 8 9 7.7 7 161 22.9 Candidate 5 4 9 6.0 37 230 34.3 5 5 6 5.3 37 375 9.6 Candidate 6 1 3 3.3 41 270 46.5 5 7 5 5.7 35 938 32.2 Candidate 7 9 3 6.3 34 160 31.3 Candidate 3 1 6 3.3 42 424 47.2 6 1 2 3.0 59 666 46.0 Candidate 4 8 5 5.7 16 76 44.1 6 7 6 6.3 29 357 235.6 .. .. .. .. .. .. .. Candidate 8 8 8 8.0 9 200 30.2 0 6 4 3.3 42 180 36.1 0 1 5 2.0 33 104 36.6 3 4 8 5.0 48 172 45.2 6 1 4 3.7 53 270 52.7 Candidate 2 5 5 4.0 32 161 35.7 3 6 7 5.3 37 132 16.1 8 1 4 4.3 51 270 39.4 Candidate 6 4 4 4.7 28 379 54.9 6 6 4 5.3 34 451 72.0 8 3 5 5.3 29 480 43.0 .. .. .. .. .. .. .. 6 2 1 3.0 28 358 41.7 5 5 6 5.3 22 228 62.8 .. CAPABLE STATES AND PARTNERSHIP Part III. Development outcomes 145 Capable states and partnership 12.4 Table Governance and anticorruption indicators Governance indicatorsa Political stability Voice and and absence Government Regulatory Control of accountability of violence effectiveness quality Rule of law corruption 1996 2008 1996 2008 1996 2008 1996 2008 1996 2008 1996 2008 SUB­SAHARAN AFRICA Angola ­1.5 ­1.1 ­2.3 ­0.4 ­1.3 ­1.0 ­1.4 ­0.9 ­1.5 ­1.3 ­1.0 ­1.2 Benin 0.7 0.3 1.0 0.4 0.0 ­0.5 0.2 ­0.5 ­0.3 ­0.5 .. ­0.4 Botswana 0.8 0.6 0.8 1.0 0.2 0.7 0.7 0.5 0.6 0.6 0.4 1.0 Burkina Faso ­0.3 ­0.3 0.1 ­0.1 ­0.7 ­0.7 ­0.1 ­0.3 ­0.3 ­0.4 ­0.3 ­0.4 Burundi ­1.5 ­0.7 ­2.0 ­1.4 ­1.0 ­1.2 ­1.6 ­1.2 ­0.9 ­1.1 .. ­1.0 Cameroon ­1.2 ­1.0 ­1.4 ­0.5 ­1.1 ­0.8 ­0.8 ­0.7 ­1.4 ­1.0 ­1.2 ­0.9 Cape Verde 0.8 1.0 1.0 0.9 ­0.1 0.1 ­0.8 0.0 0.5 0.5 .. 0.8 Central African Republic ­0.5 ­1.0 ­0.2 ­1.8 ­0.9 ­1.5 ­0.3 ­1.3 ­0.3 ­1.4 .. ­0.9 Chad ­0.9 ­1.5 ­0.6 ­1.9 ­0.7 ­1.5 ­0.9 ­1.3 ­0.9 ­1.6 .. ­1.5 Comoros 0.0 ­0.4 1.0 ­1.0 ­0.7 ­1.9 ­0.8 ­1.5 .. ­1.0 .. ­0.8 Congo, Dem. Rep. ­1.6 ­1.5 ­2.1 ­2.3 ­1.8 ­1.9 ­2.6 ­1.4 ­2.0 ­1.7 ­2.2 ­1.3 Congo, Rep. ­0.5 ­1.2 ­1.4 ­0.6 ­1.4 ­1.3 ­0.9 ­1.2 ­1.4 ­1.2 ­0.7 ­1.2 Côte d'Ivoire ­0.8 ­1.2 ­0.2 ­1.9 0.0 ­1.4 0.0 ­0.9 ­0.7 ­1.5 0.4 ­1.2 Djibouti ­0.7 ­1.1 0.2 ­0.1 ­1.0 ­1.0 0.2 ­0.8 ­0.3 ­0.5 .. ­0.3 Equatorial Guinea ­1.7 ­1.9 ­0.7 ­0.1 ­1.5 ­1.4 ­1.0 ­1.4 ­1.2 ­1.3 ­1.1 ­1.6 Eritrea ­1.1 ­2.2 0.3 ­0.8 ­0.4 ­1.4 0.0 ­2.1 ­0.3 ­1.2 .. ­0.4 Ethiopia ­0.8 ­1.3 ­1.0 ­1.8 ­0.9 ­0.4 ­1.8 ­0.9 ­0.9 ­0.6 ­1.1 ­0.7 Gabon ­0.4 ­0.8 ­0.6 0.2 ­0.8 ­0.7 0.0 ­0.7 ­1.0 ­0.6 ­1.4 ­1.1 Gambia, The ­1.3 ­1.0 0.1 0.1 ­0.4 ­0.8 ­1.8 ­0.4 0.4 ­0.3 0.4 ­0.8 Ghana ­0.3 0.5 ­0.2 0.1 ­0.4 ­0.1 0.1 0.1 ­0.4 ­0.1 ­0.5 ­0.1 Guinea ­1.1 ­1.3 ­1.5 ­1.9 ­1.1 ­1.4 0.2 ­1.2 ­1.4 ­1.6 0.4 ­1.4 Guinea-Bissau ­0.3 ­0.8 ­0.7 ­0.4 ­0.7 ­1.3 0.1 ­1.2 ­1.7 ­1.4 ­1.1 ­1.2 Kenya ­0.8 ­0.2 ­0.8 ­1.3 ­0.4 ­0.6 ­0.4 ­0.1 ­1.0 ­1.0 ­1.1 ­1.0 Lesotho ­0.2 0.0 0.5 0.0 0.1 ­0.3 ­0.6 ­0.6 ­0.3 ­0.3 .. 0.0 Liberia ­1.4 ­0.3 ­2.6 ­1.0 ­1.8 ­1.4 ­3.1 ­1.3 ­2.3 ­1.2 ­1.8 ­0.6 Madagascar 0.4 ­0.2 0.0 ­0.4 ­1.0 ­0.6 ­0.5 ­0.3 ­1.0 ­0.5 0.4 ­0.1 Malawi 0.0 ­0.2 ­0.3 0.1 ­0.6 ­0.7 ­0.2 ­0.4 ­0.6 ­0.3 ­0.5 ­0.6 Mali 0.7 0.3 0.4 ­0.2 ­0.8 ­0.8 0.0 ­0.3 ­0.6 ­0.4 ­0.3 ­0.5 Mauritania ­1.0 ­0.9 0.5 ­0.9 0.2 ­1.0 ­0.9 ­0.6 ­0.9 ­1.0 .. ­0.8 Mauritius 0.8 0.9 0.7 0.8 0.3 0.6 0.1 1.0 0.7 0.9 0.5 0.5 Mozambique 0.0 0.0 ­0.6 0.3 ­0.4 ­0.4 ­1.0 ­0.5 ­1.0 ­0.7 ­0.4 ­0.6 Namibia 0.6 0.6 0.4 1.0 0.5 0.3 0.1 0.1 0.4 0.4 0.7 0.6 Niger ­1.0 ­0.4 ­0.1 ­0.8 ­1.1 ­0.8 ­1.2 ­0.5 ­0.9 ­0.8 ­0.3 ­0.8 Nigeria ­1.8 ­0.6 ­1.6 ­2.0 ­1.4 ­1.0 ­1.1 ­0.6 ­1.4 ­1.1 ­1.3 ­0.9 Rwanda ­1.3 ­1.2 ­2.0 ­0.1 ­1.2 ­0.2 ­1.8 ­0.5 ­1.5 ­0.5 .. 0.0 São Tomé and Príncipe 0.5 0.2 1.0 0.3 ­0.7 ­0.7 ­0.3 ­0.7 .. ­0.5 .. ­0.4 Senegal ­0.1 ­0.2 ­0.6 ­0.2 ­0.2 ­0.1 ­0.4 ­0.3 ­0.5 ­0.3 ­0.5 ­0.5 Seychelles 0.0 0.0 1.0 0.9 ­0.6 0.0 ­1.4 ­0.7 .. 0.2 .. 0.2 Sierra Leone ­0.9 ­0.3 ­2.4 ­0.2 ­0.7 ­1.1 ­0.9 ­0.9 ­1.3 ­1.0 ­1.8 ­1.1 Somalia ­1.9 ­1.9 ­2.4 ­3.3 ­1.8 ­2.5 ­2.9 ­2.8 ­2.1 ­2.7 ­1.8 ­1.9 South Africa 0.9 0.7 ­1.1 0.0 0.6 0.8 0.0 0.6 0.2 0.1 0.6 0.3 Sudan ­2.0 ­1.8 ­2.6 ­2.4 ­1.5 ­1.4 ­1.9 ­1.4 ­1.6 ­1.5 ­1.1 ­1.5 Swaziland ­1.1 ­1.2 0.0 0.2 ­0.3 ­0.7 0.1 ­0.6 0.8 ­0.5 .. ­0.4 Tanzania ­0.7 ­0.1 ­0.3 0.0 ­1.0 ­0.5 ­0.1 ­0.4 ­0.4 ­0.3 ­1.1 ­0.5 Togo ­1.0 ­1.1 ­0.6 ­0.1 ­0.7 ­1.4 0.6 ­1.1 ­1.4 ­0.8 ­1.1 ­1.0 Uganda ­0.5 ­0.5 ­1.3 ­0.9 ­0.6 ­0.5 0.3 ­0.1 ­0.7 ­0.5 ­0.6 ­0.8 Zambia ­0.5 ­0.1 ­0.6 0.3 ­0.7 ­0.7 0.3 ­0.3 ­0.6 ­0.5 ­1.1 ­0.5 Zimbabwe ­0.6 ­1.5 ­0.7 ­1.6 ­0.3 ­1.6 ­0.8 ­2.2 ­0.7 ­1.8 ­0.2 ­1.4 NORTH AFRICA Algeria ­1.3 ­1.1 ­2.4 ­1.2 ­0.7 ­0.5 ­0.9 ­0.8 ­1.2 ­0.7 ­0.4 ­0.4 Egypt, Arab Rep. ­1.0 ­1.2 ­0.9 ­0.7 ­0.1 ­0.4 0.2 ­0.2 0.1 ­0.1 0.1 ­0.7 Libya ­1.8 ­1.9 ­1.6 0.5 ­0.7 ­0.8 ­2.1 ­0.9 ­1.3 ­0.7 ­1.0 ­0.8 Morocco ­0.6 ­0.7 ­0.7 ­0.5 ­0.2 ­0.1 0.2 0.0 0.2 ­0.1 0.3 ­0.3 Tunisia ­0.9 ­1.3 0.3 0.3 0.3 0.4 0.6 0.1 ­0.2 0.2 ­0.1 0.0 a. The rating scale for each criterion ranges from ­2.5 (weak performance) to 2.5 (very high performance). b. 0­20 indicates that budget documents provide scant or no information, 21­40 indicates minimal information, 41­60 indicates some information, 61­80 indicates significant information, and 81­100 indicates extensive information. In 2008 the International Budget Partnership made three changes in the methodology applied to its Open Budget Survey, which is the basis for the open budget index. c. Data are for the most recent year available during the period specified. 146 Part III. Development outcomes CAPABLE STATES AND PARTNERSHIP Share of firms (%) Expected to pay informal payment Expected to give Expected to give Expected to give Identifying Mean corruption perceptions to public officials gifts to obtain an gifts in meetings gifts to secure a corruption as a index score Open budget index to get things done operating license with tax officials government contract major constraint (0 low to 10 high) overall scoreb 2007­09 c 2007­09 c 2007­09 c 2007­09 c 2007­09 c 2007 2008­09 c 2008 .. .. .. .. .. 2.2 1.9 3.0 .. .. .. .. .. 2.7 3.1 .. .. .. .. .. .. 5.4 5.8 62.0 .. .. .. .. .. 2.9 3.5 14.0 .. .. .. .. .. 2.5 1.9 .. .. .. .. .. .. 2.4 4.0 5.0 .. .. .. .. .. 4.9 5.1 .. .. .. .. .. .. 2.0 2.0 .. .. .. .. .. .. 1.8 1.6 7.0 .. .. .. .. .. 2.6 2.5 .. .. .. .. .. .. 1.9 1.7 0.0 49.2 .. 37.1 75.2 65.0 2.1 1.9 .. 30.6 31.8 13.6 32.3 75.0 2.1 2.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1.9 1.7 0.0 .. .. .. .. .. 2.8 2.6 .. .. .. .. .. .. 2.4 2.6 .. 26.1 0.0 22.8 26.6 41.4 3.3 3.1 .. .. .. .. .. .. 2.3 1.9 .. 38.8 22.6 18.1 61.2 9.9 3.7 3.6 49.0 .. .. .. .. .. 1.9 1.6 .. .. .. .. .. .. 2.2 1.9 .. 79.2 28.8 32.3 71.2 38.4 2.1 3.5 57.0 14.0 3.3 9.2 26.4 46.7 3.3 3.2 .. 55.2 49.6 54.4 51.6 31.2 2.1 3.7 2.0 19.2 18.6 6.8 14.1 42.7 3.2 3.4 .. .. .. .. .. .. 2.7 2.8 29.0 28.9 24.0 31.1 80.4 15.7 2.7 3.1 .. .. .. .. .. .. 2.6 2.8 .. 1.6 0.0 0.3 8.8 50.7 4.7 5.5 .. 14.8 6.9 9.8 31.7 25.4 2.8 2.6 .. .. .. .. .. .. 4.5 4.5 47.0 .. .. .. .. .. 2.6 2.8 26.0 40.9 40.3 22.9 44.6 24.7 2.2 3.5 19.0 .. .. .. .. .. 2.8 3.0 0.0 .. .. .. .. .. 2.7 2.7 0.0 18.1 21.1 18.7 36.3 23.8 3.6 3.6 3.0 .. .. .. .. .. 4.5 4.8 .. 18.8 8.7 8.6 33.9 36.9 2.1 3.8 .. .. .. .. .. .. 1.4 1.0 .. 15.1 0.0 3.1 33.2 16.9 5.1 4.9 87.0 .. .. .. .. .. 1.8 1.6 0.0 .. .. .. .. .. 3.3 3.6 .. .. .. .. .. .. 3.2 3.0 35.0 .. .. .. .. .. 2.3 2.7 .. .. .. .. .. .. 2.8 3.2 51.0 14.3 2.6 4.9 27.4 12.1 2.6 3.2 47.0 .. .. .. .. .. 2.1 1.8 .. 64.7 7.3 15.0 40.6 64.3 3.0 3.2 1.0 7.3 13.7 14.1 92.2 59.3 2.9 2.8 43.0 .. .. .. .. .. 2.5 2.6 .. 13.4 0.0 10.7 6.4 27.3 3.5 3.6 27.0 .. .. .. .. .. 4.2 4.4 .. CAPABLE STATES AND PARTNERSHIP Part III. Development outcomes 147 Capable states and partnership 12.5 Table Country Policy and Institutional Assessment ratings Economic management CPIA overall rating (IDA Macroeconomic resource allocation index)a Averageb management Fiscal policy Debt policy 2005 2008 2005 2008 2005 2008 2005 2008 2005 2008 SUB­SAHARAN AFRICA Angola 2.7 2.7 2.5 3.0 3.0 3.0 2.5 3.0 2.0 3.0 Benin 3.7 3.6 4.0 4.0 4.5 4.5 4.0 4.0 3.5 3.5 Botswanac .. .. .. .. .. .. .. .. .. .. Burkina Faso 3.8 3.7 4.5 4.3 4.5 4.5 4.5 4.5 4.5 4.0 Burundi 3.0 3.0 3.3 3.3 3.5 3.5 3.5 3.5 3.0 3.0 Cameroon 3.3 3.2 3.3 3.7 4.0 4.0 3.5 4.0 2.5 3.0 Cape Verde 4.1 4.2 4.2 4.5 4.5 4.5 4.0 4.5 4.0 4.5 Central African Republic 2.4 2.5 2.5 2.8 3.0 3.5 3.0 3.0 1.5 2.0 Chad 2.9 2.5 3.3 2.7 4.0 2.5 3.0 2.5 3.0 3.0 Comoros 2.4 2.3 2.3 2.0 3.0 2.5 2.5 1.5 1.5 2.0 Congo, Dem. Rep. 2.8 2.7 3.2 3.2 3.5 3.5 3.5 3.5 2.5 2.5 Congo, Rep. 2.8 2.7 3.0 2.8 3.5 3.5 3.0 2.5 2.5 2.5 Côte d'Ivoire 2.5 2.7 2.0 2.5 2.5 3.0 2.0 2.5 1.5 2.0 Djibouti 3.1 3.1 3.2 3.0 3.5 3.5 3.0 3.0 3.0 2.5 Equatorial Guineac .. .. .. .. .. .. .. .. .. .. Eritrea 2.5 2.3 2.2 2.2 2.0 2.0 2.0 2.0 2.5 2.5 Ethiopia 3.4 3.4 3.7 3.3 3.5 2.5 4.0 4.0 3.5 3.5 Gabonc .. .. .. .. .. .. .. .. .. .. Gambia, The 3.1 3.2 3.0 3.5 3.5 4.0 3.0 3.5 2.5 3.0 Ghana 3.9 3.9 4.2 3.7 4.0 3.5 4.5 3.5 4.0 4.0 Guinea 3.0 3.0 2.7 3.0 2.5 3.0 3.0 3.5 2.5 2.5 Guinea-Bissau 2.7 2.6 2.3 1.8 2.5 2.0 2.5 2.5 2.0 1.0 Kenya 3.6 3.6 4.2 4.0 4.5 4.0 4.0 4.0 4.0 4.0 Lesotho 3.5 3.5 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 Liberiad .. 2.7 .. 2.7 .. 3.0 .. 3.0 .. 2.0 Madagascar 3.5 3.7 3.3 3.8 3.5 4.0 3.0 3.5 3.5 4.0 Malawi 3.4 3.4 3.0 3.3 3.0 3.5 3.0 3.5 3.0 3.0 Mali 3.7 3.7 4.3 4.3 4.5 4.5 4.0 4.0 4.5 4.5 Mauritania 3.2 3.3 2.8 3.5 2.0 3.5 2.5 3.0 4.0 4.0 Mauritiusc .. .. .. .. .. .. .. .. .. .. Mozambique 3.5 3.7 4.2 4.3 4.0 4.5 4.0 4.0 4.5 4.5 Namibiac .. .. .. .. .. .. .. .. .. .. Niger 3.3 3.3 3.3 3.7 3.5 4.0 3.0 3.5 3.5 3.5 Nigeria 3.1 3.4 3.8 4.3 4.0 4.0 4.0 4.5 3.5 4.5 Rwanda 3.5 3.7 3.5 3.8 4.0 4.0 3.5 4.0 3.0 3.5 São Tomé and Príncipe 3.0 3.0 2.8 2.8 3.0 3.0 3.0 3.0 2.5 2.5 Senegal 3.8 3.6 4.2 3.8 4.5 4.0 4.0 3.5 4.0 4.0 Seychellesc .. 2.9 .. 1.8 .. 2.0 .. 2.0 .. 1.5 Sierra Leone 3.1 3.1 3.7 3.7 4.0 4.0 3.5 3.5 3.5 3.5 Somaliad .. .. .. .. .. .. .. .. .. .. South Africac .. .. .. .. .. .. .. .. .. .. Sudan 2.6 2.5 2.8 2.7 3.5 3.5 3.5 3.0 1.5 1.5 Swazilandc .. .. .. .. .. .. .. .. .. .. Tanzania 3.9 3.8 4.5 4.3 5.0 4.5 4.5 4.5 4.0 4.0 Togo 2.5 2.7 2.0 2.7 2.5 3.0 2.0 3.0 1.5 2.0 Uganda 3.9 3.9 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 Zambia 3.3 3.5 3.3 3.7 3.5 4.0 3.5 3.5 3.0 3.5 Zimbabwe 1.8 1.4 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 NORTH AFRICA Algeriac .. .. .. .. .. .. .. .. .. .. Egypt, Arab Rep.c .. .. .. .. .. .. .. .. .. .. Libyac .. .. .. .. .. .. .. .. .. .. Moroccoc .. .. .. .. .. .. .. .. .. .. Tunisiac .. .. .. .. .. .. .. .. .. .. 148 Part III. Development outcomes CAPABLE STATES AND PARTNERSHIP Structural policies Averageb Trade Financial sector Business regulatory environment 2005 2008 2005 2008 2005 2008 2005 2008 2.8 2.8 4.0 4.0 2.5 2.5 2.0 2.0 4.0 3.7 4.5 4.0 3.5 3.5 4.0 3.5 .. .. .. .. .. .. .. .. 3.3 3.5 4.0 4.0 3.0 3.0 3.0 3.5 2.8 2.8 3.0 3.5 3.0 2.5 2.5 2.5 3.3 3.2 3.5 3.5 3.0 3.0 3.5 3.0 4.0 3.8 4.0 4.0 4.0 4.0 4.0 3.5 2.7 2.7 3.5 3.5 2.5 2.5 2.0 2.0 3.0 2.8 3.0 3.0 3.0 3.0 3.0 2.5 2.3 2.7 2.0 3.0 2.5 2.5 2.5 2.5 3.0 2.7 4.0 4.0 2.0 2.0 3.0 2.0 2.7 2.8 3.0 3.5 2.5 2.5 2.5 2.5 3.2 3.3 3.5 4.0 3.0 3.0 3.0 3.0 3.5 3.7 4.0 4.0 3.5 3.5 3.0 3.5 .. .. .. .. .. .. .. .. 1.8 1.5 1.5 1.5 2.0 1.0 2.0 2.0 3.2 3.2 3.0 3.0 3.0 3.0 3.5 3.5 .. .. .. .. .. .. .. .. 3.3 3.3 4.0 3.5 3.0 3.0 3.0 3.5 3.8 4.0 4.0 4.0 3.5 4.0 4.0 4.0 3.5 3.3 4.5 4.0 3.0 3.0 3.0 3.0 3.0 3.2 3.5 4.0 2.5 3.0 3.0 2.5 3.8 3.8 4.0 4.0 3.5 3.5 4.0 4.0 3.3 3.3 3.5 3.5 3.5 3.5 3.0 3.0 .. 2.8 .. 3.0 .. 2.5 .. 3.0 3.8 3.5 4.0 4.0 3.5 3.0 4.0 3.5 3.5 3.5 4.0 4.0 3.0 3.0 3.5 3.5 3.5 3.5 4.0 4.0 3.0 3.0 3.5 3.5 3.5 3.3 4.5 4.0 2.5 2.5 3.5 3.5 .. .. .. .. .. .. .. .. 3.2 3.7 4.0 4.5 2.5 3.5 3.0 3.0 .. .. .. .. .. .. .. .. 3.5 3.3 4.0 4.0 3.0 3.0 3.5 3.0 2.8 3.3 2.5 3.5 3.0 3.5 3.0 3.0 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.2 3.2 4.0 4.0 2.5 2.5 3.0 3.0 3.8 3.8 4.5 4.0 3.5 3.5 3.5 4.0 .. 2.7 .. 3.0 .. 2.0 .. 3.0 3.0 3.2 3.5 3.5 3.0 3.0 2.5 3.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.8 2.7 3.0 2.5 2.5 2.5 3.0 3.0 .. .. .. .. .. .. .. .. 3.7 3.8 4.0 4.0 3.5 4.0 3.5 3.5 3.2 3.2 4.0 4.0 2.5 2.5 3.0 3.0 3.8 3.8 4.0 4.0 3.5 3.5 4.0 4.0 3.3 3.7 4.0 4.0 3.0 3.5 3.0 3.5 2.2 1.5 2.0 2.0 2.5 1.0 2.0 1.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. (continued) CAPABLE STATES AND PARTNERSHIP Part III. Development outcomes 149 Capable states and partnership 12.5 Table Country Policy and Institutional Assessment ratings (continued) Policies for social inclusion and equity Policies and institutions for Equity of public Building human Social protection environmental Averageb Gender equality resource use resources and labor sustainability 2005 2008 2005 2008 2005 2008 2005 2008 2005 2008 2005 2008 SUB­SAHARAN AFRICA Angola 2.6 2.7 3.0 3.0 2.5 2.5 2.5 2.5 2.5 2.5 2.5 3.0 Benin 3.2 3.3 3.0 3.5 3.0 3.0 3.5 3.5 3.0 3.0 3.5 3.5 Botswanac .. .. .. .. .. .. .. .. .. .. .. .. Burkina Faso 3.6 3.6 3.5 3.5 4.0 4.0 3.5 3.5 3.5 3.5 3.5 3.5 Burundi 3.0 3.3 3.5 4.0 3.0 3.5 3.0 3.0 3.0 3.0 2.5 3.0 Cameroon 3.4 3.1 3.5 3.0 3.0 3.0 3.5 3.5 3.0 3.0 4.0 3.0 Cape Verde 4.3 4.3 4.5 4.5 4.5 4.5 4.0 4.5 4.5 4.5 4.0 3.5 Central African Republic 2.2 2.2 2.5 2.5 2.0 2.0 2.0 2.0 2.0 2.0 2.5 2.5 Chad 2.8 2.4 2.5 2.5 3.0 2.5 3.0 2.5 3.0 2.5 2.5 2.0 Comoros 2.7 2.5 3.0 3.0 3.0 2.5 3.0 2.5 2.5 2.5 2.0 2.0 Congo, Dem. Rep. 2.9 2.9 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 2.5 2.5 Congo, Rep. 2.9 2.7 3.0 3.0 3.0 2.5 3.0 3.0 2.5 2.5 3.0 2.5 Côte d'Ivoire 2.3 2.3 2.5 2.5 1.5 1.5 2.0 2.5 2.5 2.5 3.0 2.5 Djibouti 3.1 3.0 3.0 2.5 3.0 3.0 3.5 3.5 3.0 3.0 3.0 3.0 Equatorial Guineac .. .. .. .. .. .. .. .. .. .. .. .. Eritrea 3.2 3.0 3.5 3.5 3.0 3.0 3.5 3.5 3.0 3.0 3.0 2.0 Ethiopia 3.6 3.6 3.0 3.0 4.5 4.5 3.5 4.0 3.5 3.5 3.5 3.0 Gabonc .. .. .. .. .. .. .. .. .. .. .. .. Gambia, The 3.1 3.2 3.5 3.5 3.0 3.0 3.5 3.5 2.5 2.5 3.0 3.5 Ghana 3.7 4.0 4.0 4.0 4.0 4.0 3.5 4.5 3.5 4.0 3.5 3.5 Guinea 3.2 3.0 4.0 3.5 3.0 3.0 3.0 3.0 3.5 3.0 2.5 2.5 Guinea-Bissau 2.8 2.6 3.0 2.5 3.0 3.0 2.5 2.5 2.5 2.5 3.0 2.5 Kenya 3.1 3.2 3.0 3.0 3.0 3.0 3.5 3.5 3.0 3.0 3.0 3.5 Lesotho 3.3 3.3 4.0 4.0 3.0 3.0 3.5 3.5 3.0 3.0 3.0 3.0 Liberiad .. 2.4 .. 2.5 .. 3.0 .. 2.0 .. 2.5 .. 2.0 Madagascar 3.6 3.7 3.5 3.5 3.5 4.0 3.5 3.5 3.5 3.5 4.0 4.0 Malawi 3.5 3.4 3.5 3.5 3.5 3.5 3.5 3.0 3.5 3.5 3.5 3.5 Mali 3.4 3.4 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.0 3.0 Mauritania 3.4 3.5 3.5 4.0 3.0 3.5 3.5 3.5 3.5 3.0 3.5 3.5 Mauritiusc .. .. .. .. .. .. .. .. .. .. .. .. Mozambique 3.3 3.4 3.5 3.5 3.5 3.5 3.5 4.0 3.0 3.0 3.0 3.0 Namibiac .. .. .. .. .. .. .. .. .. .. .. .. Niger 3.0 3.0 2.5 2.5 3.5 3.5 3.0 3.0 3.0 3.0 3.0 3.0 Nigeria 3.1 3.2 3.0 3.0 3.5 3.5 3.0 3.0 3.0 3.5 3.0 3.0 Rwanda 3.6 3.9 3.5 3.5 4.0 4.5 4.0 4.5 3.5 3.5 3.0 3.5 São Tomé and Príncipe 2.8 2.8 3.0 3.0 3.5 3.0 2.5 3.0 2.5 2.5 2.5 2.5 Senegal 3.4 3.4 3.5 3.5 3.5 3.5 3.5 3.5 3.0 3.0 3.5 3.5 Seychellesc .. 3.6 .. 3.5 .. 3.0 .. 4.0 .. 3.5 .. 4.0 Sierra Leone 2.9 2.9 3.0 3.0 3.0 3.0 3.0 3.5 3.0 3.0 2.5 2.0 Somaliad .. .. .. .. .. .. .. .. .. .. .. .. South Africac .. .. .. .. .. .. .. .. .. .. .. .. Sudan 2.3 2.3 2.0 2.0 2.5 2.5 2.5 2.5 2.0 2.5 2.5 2.0 Swazilandc .. .. .. .. .. .. .. .. .. .. .. .. Tanzania 3.8 3.7 4.0 3.5 4.0 4.0 4.0 4.0 3.5 3.5 3.5 3.5 Togo 2.6 2.7 3.0 3.0 2.0 2.0 3.0 3.0 2.5 3.0 2.5 2.5 Uganda 3.9 3.8 3.5 3.5 4.5 4.0 4.0 4.0 3.5 3.5 4.0 4.0 Zambia 3.4 3.5 3.5 3.5 3.5 3.5 3.5 4.0 3.0 3.0 3.5 3.5 Zimbabwe 2.0 1.5 2.5 2.5 1.5 1.0 2.0 1.0 1.5 1.0 2.5 2.0 NORTH AFRICA Algeriac .. .. .. .. .. .. .. .. .. .. .. .. Egypt, Arab Rep.c .. .. .. .. .. .. .. .. .. .. .. .. Libyac .. .. .. .. .. .. .. .. .. .. .. .. Moroccoc .. .. .. .. .. .. .. .. .. .. .. .. Tunisiac .. .. .. .. .. .. .. .. .. .. .. .. Note: The rating scale for each indicator ranges from 1 (low) to 6 (high). The most recent external review of the CPIA ratings and methodology was in 2004. a. Calculated as the average of the average ratings of each cluster. b. All criteria are weighted equally. c. Not an International Development Association (IDA) member. d. Not rated in the IDA resource allocation index. 150 Part III. Development outcomes CAPABLE STATES AND PARTNERSHIP Public sector management and institutions Transparency, Property rights and Quality of budgetary and Efficiency of revenue Quality of public accountability, and Averageb rule-based governance financial management mobilization administration corruption in public sector 2005 2008 2005 2008 2005 2008 2005 2008 2005 2008 2005 2008 2.4 2.4 2.0 2.0 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 3.4 3.3 3.0 3.0 4.0 3.5 3.5 3.5 3.0 3.0 3.5 3.5 .. .. .. .. .. .. .. .. .. .. .. .. 3.6 3.5 3.5 3.5 4.0 4.0 3.5 3.5 3.5 3.5 3.5 3.0 2.7 2.6 2.5 2.5 2.5 3.0 3.0 3.0 2.5 2.5 3.0 2.0 3.1 2.9 2.5 2.5 3.5 3.0 4.0 3.5 3.0 3.0 2.5 2.5 3.9 4.0 4.0 4.0 3.5 4.0 3.5 3.5 4.0 4.0 4.5 4.5 2.2 2.3 2.0 2.0 2.0 2.0 2.5 2.5 2.0 2.5 2.5 2.5 2.4 2.2 2.0 2.0 3.0 2.0 2.5 2.5 2.5 2.5 2.0 2.0 2.3 2.2 2.5 2.5 2.0 1.5 2.5 2.5 2.0 2.0 2.5 2.5 2.3 2.2 2.0 2.0 2.5 2.5 2.5 2.5 2.5 2.0 2.0 2.0 2.6 2.6 2.0 2.5 3.0 2.5 3.0 3.0 2.5 2.5 2.5 2.5 2.5 2.5 2.0 2.0 2.5 2.0 4.0 4.0 2.0 2.0 2.0 2.5 2.8 2.8 2.5 2.5 3.0 3.0 3.5 3.5 2.5 2.5 2.5 2.5 .. .. .. .. .. .. .. .. .. .. .. .. 2.8 2.7 2.5 2.5 2.5 2.5 3.5 3.5 3.0 3.0 2.5 2.0 3.1 3.3 2.5 3.0 3.5 4.0 4.0 4.0 3.0 3.0 2.5 2.5 .. .. .. .. .. .. .. .. .. .. .. .. 2.9 2.9 3.5 3.0 2.5 3.0 3.5 3.5 3.0 3.0 2.0 2.0 3.7 3.9 3.5 3.5 3.5 4.0 4.5 4.5 3.5 3.5 3.5 4.0 2.7 2.6 2.0 2.0 3.0 3.0 3.0 3.0 3.0 3.0 2.5 2.0 2.6 2.6 2.5 2.5 2.5 2.5 3.0 3.0 2.5 2.5 2.5 2.5 3.3 3.3 3.0 2.5 3.5 3.5 4.0 4.0 3.0 3.5 3.0 3.0 3.4 3.4 3.5 3.5 3.0 3.0 4.0 4.0 3.0 3.0 3.5 3.5 .. 2.7 .. 2.5 .. 2.5 .. 3.0 .. 2.5 .. 3.0 3.4 3.6 3.5 3.5 3.0 3.5 3.5 4.0 3.5 3.5 3.5 3.5 3.4 3.4 3.5 3.5 3.0 3.0 4.0 4.0 3.5 3.5 3.0 3.0 3.6 3.4 3.5 3.5 4.0 3.5 4.0 3.5 3.0 3.0 3.5 3.5 2.9 3.0 3.0 3.0 2.0 3.0 4.0 3.5 3.0 3.0 2.5 2.5 .. .. .. .. .. .. .. .. .. .. .. .. 3.2 3.3 3.0 3.0 3.5 3.5 3.5 4.0 3.0 3.0 3.0 3.0 .. .. .. .. .. .. .. .. .. .. .. .. 3.2 3.2 3.0 3.0 3.5 3.5 3.5 3.5 3.0 3.0 3.0 3.0 2.8 2.9 2.5 2.5 3.0 3.0 3.0 3.0 2.5 3.0 3.0 3.0 3.3 3.5 3.0 3.0 3.5 4.0 3.5 3.5 3.5 3.5 3.0 3.5 3.1 3.1 2.5 2.5 3.0 3.0 3.5 3.5 3.0 3.0 3.5 3.5 3.6 3.4 3.5 3.5 3.5 3.0 4.5 4.0 3.5 3.5 3.0 3.0 .. 3.4 .. 3.5 .. 3.0 .. 3.5 .. 3.5 .. 3.5 2.9 2.7 2.5 2.5 3.5 3.5 3.0 2.5 3.0 2.5 2.5 2.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.4 2.3 2.0 2.0 2.5 2.0 3.0 3.0 2.5 2.5 2.0 2.0 .. .. .. .. .. .. .. .. .. .. .. .. 3.8 3.5 3.5 3.5 4.5 3.5 4.0 4.0 3.5 3.5 3.5 3.0 2.2 2.2 2.5 2.5 2.0 2.0 2.5 2.5 2.0 2.0 2.0 2.0 3.3 3.4 3.5 3.5 4.0 4.0 3.0 3.5 3.0 3.0 3.0 3.0 3.2 3.2 3.0 3.0 3.0 3.5 4.0 3.5 3.0 3.0 3.0 3.0 2.1 1.6 1.0 1.0 2.5 1.5 3.5 3.5 2.0 1.0 1.5 1.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. CAPABLE STATES AND PARTNERSHIP Part III. Development outcomes 151 Capable states and partnership 12.6 Table Polity indicators Combined polity score (­10 strongly autocratic to 10 Institutionalized democracy Institutionalized autocracy strongly democratic) (0 low to 10 high) (0 low to 10 high) 1995 2000 2008 1995 2000 2008 1995 2000 2008 SUB­SAHARAN AFRICA Angola ­2.0 ­3.0 ­2.0 .. 1.0 2.0 .. 4.0 4.0 Benin 6.0 6.0 7.0 6.0 6.0 7.0 0.0 0.0 0.0 Botswana 7.0 8.0 8.0 7.0 8.0 8.0 0.0 0.0 0.0 Burkina Faso ­5.0 ­3.0 0.0 0.0 0.0 2.0 5.0 3.0 2.0 Burundi 0.0 ­1.0 6.0 .. 1.0 7.0 .. 2.0 1.0 Cameroon ­4.0 ­4.0 ­4.0 1.0 1.0 1.0 5.0 5.0 5.0 Cape Verde .. .. .. .. .. .. .. .. .. Central African Republic 5.0 5.0 ­1.0 5.0 5.0 1.0 0.0 0.0 2.0 Chad ­4.0 ­2.0 ­2.0 0.0 1.0 1.0 4.0 3.0 3.0 Comoros 0.0 ­1.0 9.0 .. 1.0 9.0 .. 2.0 0.0 Congo, Dem. Rep. 0.0 0.0 5.0 .. .. 6.0 .. .. 1.0 Congo, Rep. 5.0 ­6.0 ­4.0 6.0 0.0 0.0 1.0 6.0 4.0 Côte d'Ivoire ­6.0 4.0 0.0 0.0 5.0 .. 6.0 1.0 .. Djibouti ­7.0 2.0 2.0 0.0 3.0 3.0 7.0 1.0 1.0 Equatorial Guinea ­5.0 ­5.0 ­5.0 0.0 0.0 0.0 5.0 5.0 5.0 Eritrea ­6.0 ­6.0 ­7.0 0.0 0.0 0.0 6.0 6.0 7.0 Ethiopia 1.0 1.0 1.0 3.0 3.0 3.0 2.0 2.0 2.0 Gabon ­4.0 ­4.0 ­4.0 0.0 0.0 0.0 4.0 4.0 4.0 Gambia, The ­7.0 ­5.0 ­5.0 0.0 0.0 0.0 7.0 5.0 5.0 Ghana ­1.0 2.0 8.0 1.0 3.0 8.0 2.0 1.0 0.0 Guinea ­1.0 ­1.0 ­1.0 1.0 1.0 1.0 2.0 2.0 2.0 Guinea-Bissau 5.0 5.0 6.0 5.0 5.0 6.0 0.0 0.0 0.0 Kenya ­5.0 ­2.0 7.0 0.0 2.0 7.0 5.0 4.0 0.0 Lesotho 8.0 4.0 8.0 8.0 .. 8.0 0.0 .. 0.0 Liberia 0.0 0.0 6.0 .. 3.0 7.0 .. 3.0 1.0 Madagascar 9.0 7.0 7.0 9.0 7.0 7.0 0.0 0.0 0.0 Malawi 6.0 6.0 6.0 6.0 6.0 6.0 0.0 0.0 0.0 Mali 7.0 6.0 7.0 7.0 6.0 7.0 0.0 0.0 0.0 Mauritania ­6.0 ­6.0 ­5.0 0.0 0.0 0.0 6.0 6.0 5.0 Mauritius 10.0 10.0 10.0 10.0 10.0 10.0 0.0 0.0 0.0 Mozambique 6.0 6.0 6.0 6.0 6.0 6.0 0.0 0.0 0.0 Namibia 6.0 6.0 6.0 6.0 6.0 6.0 0.0 0.0 0.0 Niger 8.0 5.0 6.0 8.0 6.0 7.0 0.0 1.0 1.0 Nigeria ­6.0 4.0 4.0 0.0 4.0 4.0 6.0 0.0 0.0 Rwanda ­6.0 ­4.0 ­3.0 0.0 0.0 0.0 6.0 4.0 3.0 São Tomé and Principe .. .. .. .. .. .. .. .. .. Senegal ­1.0 8.0 8.0 2.0 8.0 8.0 3.0 0.0 0.0 Seychelles .. .. .. .. .. .. .. .. .. Sierra Leone ­7.0 0.0 7.0 0.0 .. 8.0 7.0 .. 1.0 Somalia 0.0 0.0 0.0 .. .. .. .. .. .. South Africa 9.0 9.0 9.0 9.0 9.0 9.0 0.0 0.0 0.0 Sudan ­7.0 ­7.0 ­4.0 0.0 0.0 0.0 7.0 7.0 4.0 Swaziland ­9.0 ­9.0 ­9.0 0.0 0.0 0.0 9.0 9.0 9.0 Tanzania ­1.0 ­1.0 ­1.0 2.0 2.0 2.0 3.0 3.0 3.0 Togo ­2.0 ­2.0 ­4.0 1.0 1.0 1.0 3.0 3.0 5.0 Uganda ­4.0 ­4.0 ­1.0 0.0 0.0 1.0 4.0 4.0 2.0 Zambia 6.0 1.0 7.0 6.0 3.0 7.0 0.0 2.0 0.0 Zimbabwe ­6.0 ­3.0 ­4.0 0.0 1.0 1.0 6.0 4.0 5.0 NORTH AFRICA Algeria ­3.0 ­3.0 2.0 1.0 1.0 3.0 4.0 4.0 1.0 Egypt, Arab Rep. ­6.0 ­6.0 ­3.0 0.0 0.0 1.0 6.0 6.0 4.0 Libya ­7.0 ­7.0 ­7.0 0.0 0.0 0.0 7.0 7.0 7.0 Morocco ­7.0 ­6.0 ­6.0 0.0 0.0 0.0 7.0 6.0 6.0 Tunisia ­3.0 ­3.0 ­4.0 1.0 1.0 1.0 4.0 4.0 5.0 152 Part III. Development outcomes CAPABLE STATES AND PARTNERSHIP Technical notes 1. Basic indicators (one person has all the income or consump- tion, all others have none). Graphically, the Table .. Basic indicators Gini index can be easily represented by the Population is total population based on the de area between the Lorenz curve and the line facto definition of population, which counts of equality. all residents regardless of legal status or citi- Adult literacy rate is the percentage of zenship, except for refugees not permanent- adults ages 15 and older who can, with un- ly settled in the country of asylum, who are derstanding, read and write a short, simple generally considered part of the population statement on their everyday life. of their country of origin. The values shown Net official development assistance per are midyear estimates. capita is calculated by dividing net disburse- Land area is the land surface area of a coun- ments of loans and grants from all official try, excluding inland waters, national claims sources on concessional financial terms by to continental shelf, and exclusive economic midyear population. This indicator offers zones. some indication of the importance of aid Gross domestic product (GDP) per capita is flows in sustaining per capita income and gross domestic product divided by midyear consumption levels, although exchange rate population. GDP is the sum of gross value fluctuations, the actual rise of aid flows, added by all resident producers in the econ- and other factors vary across countries and omy plus any product taxes and minus any over time. subsidies not included in the value of the Regional aggregates for GNI per capita, life products. It is calculated without making de- expectancy at birth, and adult literacy rates ductions for depreciation of fabricated assets are weighted by population. or for depletion and degradation of natural resources. Growth rates are in real terms and Source: Data on population, land area, GDP have been calculated by the least-squares per capita, life expectancy at birth, under-five method using constant 2000 exchange rates mortality, Gini coefficient, and adult literacy (box 2). are from the World Bank's World Develop- Life expectancy at birth is the number of ment Indicators database. Data on aid flows years a newborn infant would live if pre- are from the Organisation for Economic Co- vailing patterns of mortality at the time of operation and Development's Geographic its birth were to remain the same through- Distribution of Aid Flows to Developing out its life. Countries database. Under-five mortality rate is the probability that a newborn baby will die before reaching 2. National and fiscal accounts age 5, if subject to current age-specific mor- Africa Development Indicators uses the 1993 Sys- tality rates. The probability is expressed as a tem of National Accounts (1993 SNA) to com- rate per 1,000. pile national accounts data. Botswana, Camer- Gini index is the most commonly used oon, Chad, the Democratic Republic of Congo, measure of inequality. The coefficient ranges Ethiopia, Kenya, Lesotho, Namibia, Senegal, from 0, which reflects complete equality, to Sierra Leone, and South Africa report data us- 100, which indicates complete inequality ing the 1993 SNA. Although more countries Technical notes 153 Box 2 Growth rates Growth rates are calculated as annual averages and represented as which is equivalent to the logarithmic transformation of the com- percentages. Except where noted, growth rates of values are com- pound growth equation, puted from constant price series. Rates of change from one period to the next are calculated as proportional changes from the earlier X t = Xo(1 + r)2 period. Least-squares growth rates are used wherever there is a suf- ficiently long time series to permit a reliable calculation. No growth where X is the variable, t is time, and a = lnXo and b = ln(1 + r) are rate is calculated if more than half the observations in a period are parameters to be estimated. If b* is the least squares estimate of missing. The least-squares growth rate, r, is estimated by fitting a lin- b, the average annual growth rate, r, is obtained as [exp(b*) ­ 1] ear regression trend line to the logarithmic annual values of the vari- multiplied by 100. The calculated growth rate is an average rate able in the relevant period. The regression equation takes the form that is representative of the available observations over the entire period. It does not necessarily match the actual growth rate be- ln Xt = a + bt tween any two points. are adopting the 1993 SNA, many still follow Table .. Gross domestic product, real the 1968 SNA, and some low-income coun- Gross domestic product (GDP), real, is ob- tries use concepts from the 1953 SNA. tained by converting national currency GDP series to U.S. dollars using constant (2000) Table .. Gross domestic product, exchange rates. For countries where the nominal official exchange rate does not effectively Gross domestic product (GDP), nominal, is the reflect the rate applied to actual foreign ex- sum of gross value added by all resident pro- change transactions, an alternative curren- ducers in the economy plus any product taxes cy conversion factor has been used. Growth and minus any subsidies not included in the rates are in real terms and have been cal- value of the products. It is calculated without culated by the least-squares method using making deductions for depreciation of fabri- constant 2000 exchange rates (see box 2). cated assets or for depletion and degradation of natural resources. GDP figures are shown Source: World Bank and Organisation for at market prices (also known as purchaser val- Economic Co-operation and Development ues) and converted from domestic currencies national accounts data. using single year official exchange rates. For a few countries where the official exchange rate Table .. Gross domestic product does not reflect the rate effectively applied to growth actual foreign exchange transactions, an al- Gross domestic product (GDP) growth is the av- ternative conversion factor is used. erage annual growth rate of real GDP (table The sum of the components of GDP by in- 2.2) at market prices based on constant local dustrial origin (presented here as value added) currency. Aggregates are based on constant will not normally equal total GDP for several 2000 U.S. dollars. reasons. First, components of GDP by expen- diture are individually rescaled and summed Source: World Bank and Organisation for to provide a partially rebased series for total Economic Co-operation and Development GDP. Second, total GDP is shown at purchaser national accounts data. value, while value added components are con- ventionally reported at producer prices. As Table .. Gross domestic product per explained above, purchaser values exclude net capita, real indirect taxes, while producer prices include Gross domestic product (GDP) per capita, real, is indirect taxes. Third, certain items, such as im- calculated by dividing real GDP (table 2.2) by puted bank charges, are added in total GDP. corresponding midyear population. Source: World Bank and Organisation for Source: World Bank and Organisation for Economic Co-operation and Development Economic Co-operation and Development national accounts data. national accounts data. 154 Africa Development Indicators 2010 Table .. Gross domestic product per GNI per capita in current prices, except that capita growth the use of three-year averages of exchange Gross domestic product (GDP) per capita growth rates smoothes out sharp fluctuations from is the average annual growth rate of real GDP year to year. per capita (table 2.4). Source: World Bank and Organisation for Source: World Bank and Organisation for Economic Co-operation and Development Economic Co-operation and Development national accounts data. national accounts data. Table .. Gross domestic product de- Table .. Gross national income, flator (local currency series) nominal Gross domestic product (GDP) deflator (local Gross national income, nominal, is the sum of currency series) is nominal GDP in current lo- value added by all resident producers plus any cal currency divided by real GDP in constant product taxes (less subsidies) not included in 2000 local currency, expressed as an index the valuation of output plus net receipts of with base year 2000. GDP is the sum of gross primary income (compensation of employees domestic and foreign value added claimed by and property income) from abroad. Data are residents plus net factor income from abroad converted from national currency in current (the income residents receive from abroad for prices to U.S. dollars at official annual ex- factor services including labor and capital) change rates. less similar payments made to nonresidents who contribute to the domestic economy, di- Source: World Bank and Organisation for vided by midyear population. It is calculated Economic Co-operation and Development by the World Bank Atlas method using con- (OECD) national accounts data. stant 2000 exchange rates (see box 1). Table . Gross national income, Atlas Source: World Bank and Organisation for method Economic Co-operation and Development Gross national income (GNI), Atlas method, is national accounts data. the sum of value added by all resident pro- ducers plus any product taxes (less subsidies) Table .. Gross domestic product not included in the valuation of output plus deflator (U.S. dollar series) net receipts of primary income (compensa- Gross domestic product (GDP) deflator (U.S. tion of employees and property income) from dollar series) is nominal GDP in current U.S. abroad. Data are converted from national dollars (table 2.1) divided by real GDP in con- currency in current prices to U.S. dollars us- stant 2000 U.S. dollars (table 2.2), expressed ing the World Bank Atlas method (see box 1). as an index with base year 2000. The series It is similar in concept to GNI in current pric- shows the effects of domestic price changes es, except that the use of three-year averages and exchange rate variations. of exchange rates smoothes out sharp fluc- tuations from year to year. Growth rates have Source: World Bank and Organisation for been calculated by the least-squares method Economic Co-operation and Development (see box 2). national accounts data. Source: World Bank and Organisation for Table .. Consumer price index Economic Co-operation and Development Consumer price index reflects changes in the national accounts data. cost to the average consumer of acquiring a basket of goods and services that may be fixed Table .. Gross national income per or changed at specified intervals, such as year- capita, Atlas method ly. The Laspeyres formula is generally used. Gross national income (GNI) per capita, Atlas method, is GNI, calculated using the World Source: International Monetary Fund In- Bank Atlas method (see box 1), divided by ternational Financial Statistics database and midyear population. It is similar in concept to data files. Technical notes 155 Table .. Price indexes Source: World Bank and Organisation for Inflation, GDP deflator, is measured by the an- Economic Co-operation and Development nual growth rate of the GDP implicit defla- national accounts data. tor and shows the rate of price change in the economy as a whole. Table .. Household final consump- Consumer price index is a change in the cost tion expenditure to the average consumer of acquiring a bas- Household final consumption expenditure (for- ket of goods and services that may be fixed or merly private consumption) is the market value changed at specified intervals, such as yearly. of all goods and services, including durable The Laspeyres formula is generally used. products (such as cars, washing machines, Exports of goods and services price index is and home computers), purchased by house- calculated by dividing the national accounts holds. It excludes purchases of dwellings but exports of goods and services in current U.S. includes imputed rent for owner-occupied dollars by exports of goods and services in dwellings. It also includes payments and fees constant 2000 U.S. dollars. to governments to obtain permits and licens- Imports of goods and services price index is es. Here, household consumption expendi- calculated by dividing the national accounts ture includes the expenditures of nonprofit imports of goods and services in current U.S. institutions serving households, even when dollars by imports of goods and services in reported separately by the country. constant 2000 U.S. dollars. Source: World Bank and Organisation for Source: World Bank and Organisation for Economic Co-operation and Development Economic Co-operation and Development national accounts data. national accounts data. Table .. Final consumption expendi- Table .. Gross domestic savings ture plus discrepancy Gross domestic savings is calculated by de- Final consumption expenditure plus discrep- ducting total consumption (table 2.17) from ancy (formerly total consumption) is the sum nominal gross domestic product (table 2.1). of household final consumption expendi- ture (table 2.16) and general government Source: World Bank and Organisation for final consumption expenditure (table 2.15) Economic Co-operation and Development shown as a share of gross domestic product. national accounts data. This estimate includes any statistical dis- crepancy in the use of resources relative to Table .. Gross national savings the supply of resources. Private consump- Gross national savings is the sum of gross do- tion, not separately shown here, is the value mestic savings (table 2.13), net factor income of all goods and services purchased or re- from abroad, and net private transfers from ceived as income in kind by households and abroad. The estimate here also includes net nonprofit institutions. It excludes purchases public transfers from abroad. of dwellings, but includes imputed rent for owner-occupied dwellings. In practice, it in- Source: World Bank and Organisation for cludes any statistical discrepancy in the use Economic Co-operation and Development of resources. national accounts data. Source: World Bank and Organisation for Table .. General government final Economic Co-operation and Development consumption expenditure national accounts data. General government final consumption expendi- ture is all current expenditure for purchases Table .. Final consumption expendi- of goods and services by all levels of gov- ture plus discrepancy per capita ernment, including capital expenditure on Final consumption expenditure plus discrepancy national defense and security. Other capital per capita is final consumption expenditure expenditure by government is included in plus discrepancy in current U.S. dollars (table capital formation. 2.17) divided by midyear population. 156 Africa Development Indicators 2010 Source: World Bank and Organisation for Source: World Bank and Organisation for Economic Co-operation and Development Economic Co-operation and Development national accounts data. national accounts data. Table .. Gross fixed capital Table . . Exports of goods and ser- formation vices, nominal Gross fixed capital formation consists of gross Exports of goods and services, nominal, represent domestic fixed capital formation plus net the value of all goods and other market servic- changes in the level of inventories. Gross es provided to the rest of the world. They in- capital formation comprises outlays by clude the value of merchandise, freight, insur- the public sector (table 2.20) and the pri- ance, transport, travel, royalties, license fees, vate sector (table 2.21). Examples include and other services, such as communication, improvements in land, dwellings, machin- construction, financial, information, busi- ery, and other equipment. For some coun- ness, personal, and government services. They tries the sum of gross private investment exclude labor and property income (formerly and gross public investment does not total called factor services) as well as transfer pay- gross domestic investment due to statistical ments, and expressed in current U.S dollars. discrepancies. Source: World Bank and Organisation for Source: World Bank and Organisation for Economic Co-operation and Development Economic Co-operation and Development national accounts data. national accounts data. Table .. Imports of goods and ser- Table .. Gross general government vices, nominal fixed capital formation Imports of goods and services, nominal, represent Gross general government fixed capital forma- the value of all goods and other market servic- tion is gross domestic fixed capital formation es received from the rest of the world. They in- (see table 2.19) for the public sector. clude the value of merchandise, freight, insur- ance, transport, travel, royalties, license fees, Source: World Bank and Organisation for and other services, such as communication, Economic Co-operation and Development construction, financial, information, busi- national accounts data. ness, personal, and government services. They exclude labor and property income (formerly Table .. Private sector fixed capital called factor services) as well as transfer pay- formation ments and expressed in current U.S dollars. Private sector fixed capital formation is gross domestic fixed capital formation (see table Source: World Bank and Organisation for 2.19) for the private sector. Economic Co-operation and Development national accounts data. Source: World Bank and Organisation for Economic Co-operation and Development Table .. Exports of goods and ser- national accounts data. vices as a share of gdp Exports of goods and services represent the value Table .. External trade balance of all goods and other market services provided (exports minus imports) to the rest of the world. They include the value External trade balance is the difference be- of merchandise, freight, insurance, transport, tween free on board exports (table 2.23) and travel, royalties, license fees, and other ser- cost, insurance, and freight imports (table vices, such as communication, construction, 2.24) of goods and services (or the difference financial, information, business, personal, and between gross domestic savings and gross government services. They exclude labor and capital formation). The resource balance is property income (formerly called factor servic- shown as a share of nominal gross domestic es) as well as transfer payments, and expressed product (table 2.1). as a proportion of real GDP. Technical notes 157 Source: World Bank and Organisation for payments on direct investment, portfolio in- Economic Co-operation and Development vestment, other investments, and receipts national accounts data. on reserve assets). Net current transfers are recorded in the Table .. Imports of goods and ser- balance of payments whenever an economy vices as a share of gdp provides or receives goods, services, income, Imports of goods and services represent the or financial items without a quid pro quo. value of all goods and other market services Current account balance is the sum of net received from the rest of the world. They in- exports of goods, services, net income, and clude the value of merchandise, freight, in- net current transfers. All transfers not con- surance, transport, travel, royalties, license sidered to be capital are current. fees, and other services, such as communi- Total reserves including gold are the holdings cation, construction, financial, information, of monetary gold, special drawing rights, business, personal, and government services. reserves of International Monetary Fund They exclude labor and property income (for- (IMF) members held by the IMF, and hold- merly called factor services) as well as trans- ings of foreign exchange under the control of fer payments and expressed as a proportion monetary authorities. of real GDP. Source: Data on exports and imports of Source: World Bank and Organisation for goods and services are from World Bank and Economic Co-operation and Development Organisation for Economic Co-operation and national accounts data. Development national accounts data. Data on net income, net current transfers, current Table .. Balance of payments and account balance, and total reserves are from current account the International Monetary Fund Interna- Exports of goods and services represent the val- tional Financial Statistics database and data ue of all goods and other market services pro- files. vided to the rest of the world. They include the value of merchandise, freight, insurance, Table .. Exchange rates and pur- transport, travel, royalties, license fees, and chasing power parity other services, such as communication, con- Official exchange rate is the exchange rate de- struction, financial, information, business, termined by national authorities or to the personal, and government services. They ex- rate determined in the legally sanctioned ex- clude labor and property income (formerly change market. called factor services) as well as transfer pay- Purchasing power parity (PPP) conversion ments, and expressed in current U.S. dollars factor is the number of units of a country's and as a proportion of real GDP. currency required to buy the same amount of Imports of goods and services represent the goods and services in the domestic market as value of all goods and other market services a U.S. dollar would buy in the United States. received from the rest of the world. They in- Ratio of PPP conversion factor to market ex- clude the value of merchandise, freight, in- change rate is the national price level, making surance, transport, travel, royalties, license it possible to compare the cost of the bundle fees, and other services, such as communi- of goods that make up gross domestic prod- cation, construction, financial, information, uct across countries. business, personal, and government services. Real effective exchange rate is the nominal They exclude labor and property income (for- effective exchange rate (a measure of the merly called factor services) as well as trans- value of a currency against a weighted aver- fer payments and expressed in current U.S. age of several foreign currencies) divided by a dollars and as a proportion of real GDP. price deflator or index of costs. Total trade is the sum of exports and im- Gross domestic product (GDP), PPP, is gross ports of goods and services. domestic product converted to international Net income is the receipts and payments of dollars using purchasing power parity rates. An employee compensation paid to nonresident international dollar has the same purchasing workers and investment income (receipts and power over GDP as the U.S. dollar has in the 158 Africa Development Indicators 2010 United States. GDP is the sum of gross value water, and gas (ISIC revision 3 divisions 10­ added by all resident producers in the economy 45) less the value of their intermediate inputs. plus any product taxes and minus any subsi- It is calculated without making deductions dies not included in the value of the products. for depreciation of fabricated assets or deple- It is calculated without making deductions for tion and degradation of natural resources For depreciation of fabricated assets or for deple- countries that report that report national ac- tion and degradation of natural resources. counts data at producer prices (Benin, the Re- Gross domestic product (GDP) per capita, public of Congo, Côte d'Ivoire, Gabon, Ghana, PPP, is GDP per capita based on purchasing Niger, Rwanda, Tanzania, Togo, and Tunisia), power parity (PPP). PPP GDP is gross domes- gross value added at market prices is used as tic product converted to international dollars the denominator. For countries that report using purchasing power parity rates. An in- national accounts data at basic prices (all oth- ternational dollar has the same purchasing er countries), gross value added at factor cost power over GDP as the U.S. dollar has in the is used as the denominator. United States. GDP at purchaser's prices is the sum of gross value added by all resident Source: World Bank and Organisation for producers in the economy plus any product Economic Co-operation and Development taxes and minus any subsidies not included national accounts data files. in the value of the products. It is calculated without making deductions for depreciation Table .. Services plus discrepancy of fabricated assets or for depletion and deg- value added radation of natural resources. Services plus discrepancy value added is the gross output of all other branches of economic ac- Source: International Monetary Fund In- tivity, including wholesale and retail trade (in- ternational Financial Statistics database. cluding hotels and restaurants), transport, and Data on PPP are from the World Bank's Inter- government, financial, professional, and per- national Comparison Program database. sonal services such as education, health care, and real estate services (ISIC revision 3 divi- Table .. Agriculture value added sions 50­99) less the value of their interme- Agriculture value added is the gross output of diate inputs. Also included are imputed bank forestry, hunting, and fishing, as well as cultiva- service charges, import duties, and any statis- tion of crops and livestock production (Interna- tical discrepancies noted by national compilers tional Standard Industrial Classification [ISIC] as well as discrepancies arising from rescaling. revision 3 divisions 1­5) less the value of their It is calculated without making deductions intermediate inputs. It is calculated without for depreciation of fabricated assets or deple- making deductions for depreciation of fabricat- tion and degradation of natural resources. For ed assets or depletion and degradation of natu- countries that report that report national ac- ral resources. For countries that report that re- counts data at producer prices (Benin, the Re- port national accounts data at producer prices public of Congo, Côte d'Ivoire, Gabon, Ghana, (Benin, the Republic of Congo, Côte d'Ivoire, Niger, Rwanda, Tanzania, Togo, and Tunisia), Gabon, Ghana, Niger, Rwanda, Tanzania, Togo, gross value added at market prices is used as and Tunisia), gross value added at market prices the denominator. For countries that report is used as the denominator. For countries that national accounts data at basic prices (all other report national accounts data at basic prices (all countries), gross value added at factor cost is other countries), gross value added at factor used as the denominator. cost is used as the denominator. Source: World Bank and Organisation for Source: World Bank and Organisation for Economic Co-operation and Development Economic Co-operation and Development national accounts data files. national accounts data files. Table .. Central government Table .. Industry value added finances, expense, and revenue Industry value added is the gross output of min- Revenue, excluding grants, is cash receipts ing, manufacturing, construction, electricity, from taxes, social contributions, and other Technical notes 159 revenues such as fines, fees, rent, and income as social security and pensions that provide from property or sales. Grants are also con- benefits to employees. sidered as revenue but are excluded here. Interest payments (expense) include interest Expense is cash payments for operating ac- payments on government debt--including tivities of the government in providing goods long-term bonds, long-term loans, and other and services. It includes compensation of debt instruments--to domestic and for- employees (such as wages and salaries), inter- eign residents, expressed as a proportion of est and subsidies, grants, social benefits, and expense. other expenses such as rent and dividends. Subsidies and other transfers include all unre- Cash surplus or deficit is revenue (including quited, nonrepayable transfers on current ac- grants) minus expense, minus net acquisition count to private and public enterprises; grants of nonfinancial assets. In the 1986 Govern- to foreign governments, international orga- ment Finance Statistics Manual nonfinancial nizations, and other government units; and assets were included under revenue and ex- social security, social assistance benefits, and penditure in gross terms. This cash surplus or employer social benefits in cash and in kind. deficit is closest to the earlier overall budget Other expenses are spending on dividends, balance (still missing is lending minus repay- rent, and other miscellaneous expenses, in- ments, which are now a financing item under cluding provision for consumption of fixed net acquisition of financial assets). capital. Net incurrence of liabilities is domestic fi- Interest payments (revenue) include interest nancing (obtained from residents) and for- payments on government debt--including eign financing (obtained from nonresidents) long-term bonds, long-term loans, and other and, or the means by which a government debt instruments--to domestic and for- provides financial resources to cover a budget eign residents, expressed as a proportion of deficit or allocates financial resources arising revenue. from a budget surplus. The net incurrence of Taxes on income, profits, and capital gains are liabilities should be offset by the net acqui- levied on the actual or presumptive net in- sition of financial assets (a third financing come of individuals, on the profits of corpo- item). The difference between the cash sur- rations and enterprises, and on capital gains, plus or deficit and the three financing items whether realized or not, on land, securities, is the net change in the stock of cash. and other assets. Intragovernmental pay- Total debt is the entire stock of direct gov- ments are eliminated in consolidation. ernment fixed-term contractual obligations Taxes on goods and services include general to others outstanding on a particular date. It sales and turnover or value added taxes, se- includes domestic and foreign liabilities such lective excises on goods, selective taxes on as currency and money deposits, securities services, taxes on the use of goods or prop- other than shares, and loans. It is the gross erty, taxes on extraction and production of amount of government liabilities reduced by minerals, and profits of fiscal monopolies. the amount of equity and financial deriva- Taxes on international trade include import tives held by the government. Because debt duties, export duties, profits of export or im- is a stock rather than a flow, it is measured port monopolies, exchange profits, and ex- as of a given date, usually the last day of the change taxes. fiscal year. Other taxes include employer payroll or la- Goods and services include all government bor taxes, taxes on property, and taxes not al- payments in exchange for goods and services locable to other categories, such as penalties used for the production of market and non- for late payment or nonpayment of taxes. market goods and services. Own-account Social contributions include social security capital formation is excluded. contributions by employees, employers, and Compensation of employees consists of all self-employed individuals, and other contri- payments in cash, as well as in kind (such as butions whose source cannot be determined. food and housing), to employees in return They also include actual or imputed contribu- for services rendered, and government con- tions to social insurance schemes operated tributions to social insurance schemes such by governments. 160 Africa Development Indicators 2010 Grants and other revenue include grants Gross national savings is the gross nation- from other foreign governments, interna- al income less total consumption, plus net tional organizations, and other government transfers. units; interest; dividends; rent; requited, nonrepayable receipts for public purposes Source: World Bank and Organisation for (such as fines, administrative fees, and entre- Economic Co-operation and Development preneurial income from government owner- national accounts data files. ship of property); and voluntary, unrequited, nonrepayable receipts other than grants. 3. Millennium Development Goals Source: International Monetary Fund, Gov- Table .. Millennium Development ernment Finance Statistics Yearbook and data Goal : eradicate extreme poverty and files, and World Bank and Organisation for hunger Economic Co-operation and Development Share of population below PPP $1.25 a day is GDP estimates. the percentage of the population living on less than $1.25 a day at 2005 international Table .. Structure of demand prices. As a result of revisions in purchasing Household final consumption expenditure (for- power parity (PPP) exchange rates, poverty merly private consumption) is the market rates in this edition cannot be compared with value of all goods and services, including those in editions before 2009. durable products (such as cars, washing ma- Poverty gap ratio at PPP $1.25 a day is the chines, and home computers), purchased by mean shortfall from the poverty line (count- households. ing the nonpoor as having zero shortfall), ex- General government final consumption expen- pressed as a percentage of the poverty line. diture (formerly general government consump- This measure reflects the depth of poverty as tion) is all government current expenditures well as its incidence. for purchases of goods and services. Share of population below PPP $2 a day is Gross fixed capital formation (formerly gross the percentage of the population living on domestic investment) consists of outlays on less than $2.00 a day at 2005 international additions to the fixed assets of the economy prices. As a result of revisions in PPP ex- plus net changes in the level of inventories. change rates, poverty rates in this edition Exports of goods and services represent the cannot be compared with those in editions value of all goods and other market services before 2009. provided to the rest of the world. They include Poverty gap ratio at PPP $2 a day is the mean the value of merchandise, freight, insurance, shortfall from the poverty line (counting the transport, travel, royalties, license fees, and nonpoor as having zero shortfall), expressed other services, such as communication, con- as a percentage of the poverty line. This mea- struction, financial, information, business, per- sure reflects the depth of poverty as well as sonal, and government services. They exclude its incidence. labor and property income (formerly called fac- Share of population below national poverty tor services) as well as transfer payments, and line (poverty headcount ratio) is the percentage expressed as a proportion of real GDP. of the population living below the national Imports of goods and services represent the poverty line. National estimates are based value of all goods and other market services on population-weighted subgroup estimates received from the rest of the world. They in- from household surveys. clude the value of merchandise, freight, in- Share of poorest quintile in national consump- surance, transport, travel, royalties, license tion or income is the share of consumption, or fees, and other services, such as communi- in some cases income, that accrues to the cation, construction, financial, information, poorest 20 percent of the population. business, personal, and government services. Prevalence of child malnutrition, under- They exclude labor and property income (for- weight, is the percentage of children under merly called factor services) as well as trans- age 5 whose weight for age is more than fer payments and expressed as a proportion two standard deviations below the median of real GDP. for the international reference population Technical notes 161 ages 0­59 months. The reference popula- Primary completion rate is the percentage of tion, adopted by the World Health Organiza- students completing the last year of primary tion in 1983, is based on children from the school. It is calculated as the total number of United States, who are assumed to be well students in the last grade of primary school nourished. minus the number of repeaters in that grade Population below minimum dietary energy divided by the total number of children of of- consumption (also referred to as prevalence of ficial graduation age. undernourishment) is the population whose Share of cohort reaching grade 5 is the per- dietary energy consumption is continuously centage of children enrolled in grade 1 of below a minimum dietary energy require- primary school who eventually reach grade ment for maintaining a healthy life and car- 5. The estimate is based on the reconstructed rying out a light physical activity with an ac- cohort method. ceptable minimum bodyweight for attained Youth literacy rate is the percentage of peo- height. ple ages 15­24 who can, with understanding, both read and write a short, simple statement Source: Data on poverty measures are about their everyday life. prepared by the World Bank's Development Research Group. The international poverty Source: Data are from the United Nations lines are based on nationally representative Educational, Scientific, and Cultural Organi- primary household surveys conducted by zation Institute for Statistics. Efforts have national statistical offices or by private agen- been made to harmonize these data series cies under the supervision of government with those published on the United Nations or international agencies and obtained from Millennium Development Goals website government statistical offices and World (www.un.org/millenniumgoals), but some Bank Group country departments. The na- differences in timing, sources, and defini- tional poverty lines are based on the World tions remain. Bank's country poverty assessments. Data have been compiled by World Bank staff from Table .. Millennium Development primary and secondary sources. Efforts have Goal : promote gender equality and been made to harmonize these data series empower women with those published on the United Nations Ratio of girls to boys in primary and secondary Millennium Development Goals website school is the ratio of female to male gross (www.un.org/millenniumgoals), but some enrollment rate in primary and secondary differences in timing, sources, and defini- school. tions remain. Data on child malnutrition and Ratio of literate young women to men is the population below minimum dietary energy ratio of the female youth literacy rate to the consumption are from the Food and Agricul- male youth literacy rate. ture Organization (www.fao.org/economic/ Women in national parliament are the per- ess/food-security-statistics/en/). centage of parliamentary seats in a single or lower chamber occupied by women. Table .. Millennium Development Share of women employed in the nonagri- Goal : achieve universal primary cultural sector is women wage employees in education the nonagricultural sector as a share of total Primary education provides children with ba- nonagricultural employment. sic reading, writing, and mathematics skills along with an elementary understanding of Source: Data on net enrollment and lit- such subjects as history, geography, natural eracy are from the United Nations Educa- science, social science, art, and music. tional, Scientific, and Cultural Organization Net primary enrollment ratio is the ratio of Institute for Statistics. Data on women in children of official primary school age based national parliaments are from the Inter- on the International Standard Classification Parliamentary Union. Data on women's em- of Education 1997 who are enrolled in pri- ployment are from the International Labour mary school to the population of the corre- Organization's Key Indicators of the Labour sponding official primary school age. Market, fourth edition. 162 Africa Development Indicators 2010 Table .. Millennium Development Source: Data on maternal mortality are Goal : reduce child mortality from AbouZahr and Wardlaw (2003). Data Under-five mortality rate is the probability on births attended by skilled health staff are that a newborn baby will die before reaching from the United Nations Children's Fund's age 5, if subject to current age-specific mor- State of the World's Children and Childinfo, tality rates. The probability is expressed as a and Demographic and Health Surveys by rate per 1,000. Macro International. Infant mortality rate is the number of in- fants dying before reaching one year of age, Table .. Millennium Development per 1,000 live births. Goal : combat HIV/AIDS, malaria, and Child immunization rate, measles, is the per- other diseases centage of children ages 12­23 months who Prevalence of HIV is the percentage of people received vaccinations for measles before 12 ages 15­49 who are infected with HIV. months or at any time before the survey. A Contraceptive use, any method, is the per- child is considered adequately immunized centage of women ages 15­49, married against measles after receiving one dose of or in union, who are practicing, or whose vaccine. sexual partners are practicing, any form of contraception. Source: Data on under-five and infant mor- Children sleeping under insecticide-treated tality are the harmonized estimates of the nets are the percentage of children under age World Health Organization, United Nations 5 with access to an insecticide-treated net to Children's Fund (UNICEF), and the World prevent malaria. Bank, based mainly on household surveys, Incidence of tuberculosis is the estimated censuses, and vital registration, supplement- number of new tuberculosis cases (pulmo- ed by the World Bank's estimates based on nary, smear positive, and extrapulmonary), household surveys and vital registration. per 100,000 people. Other estimates are compiled and produced Tuberculosis cases detected under DOTS are by the World Bank's Human Development the percentage of estimated new infectious Network and Development Data Group in tuberculosis cases detected under DOTS, the consultation with its operational staff and internationally recommended tuberculosis country offices. Data on child immunization control strategy. are from the World Health Organization and UNICEF. Source: Data on HIV prevalence are from the Joint United Nations Programme on Table .. Millennium Development HIV/AIDS and the World Health Organiza- Goal : improve maternal health tion's (WHO) Report on the Global AIDS Epi- Maternal mortality ratio, modeled estimate, is demic. Data on contraceptive use are from the number of women who die from preg- household surveys, including Demographic nancy-related causes during pregnancy and and Health Surveys by Macro International childbirth, per 100,000 live births. Data are and Multiple Indicator Cluster Surveys by the estimated by a regression model using in- United Nations Children's Fund (UNICEF). formation on fertility, birth attendants, and Data on insecticide-treated net use are from HIV prevalence. UNICEF's State of the World's Children and Maternal mortality ratio, national estimate, is Childinfo, and Demographic and Health Sur- the number of women who die during preg- veys by Macro International. Data on tuber- nancy and childbirth, per 100,000 live births. culosis are from the WHO's Global Tuberculo- Births attended by skilled health staff are the sis Control Report 2006. percentage of deliveries attended by person- nel who are trained to give the necessary su- Table .. Millennium Develop- pervision, care, and advice to women during ment Goal : ensure environment pregnancy, labor, and the postpartum period; sustainability to conduct deliveries on their own; and to Forest area is land under natural or planted care for newborns. stands of trees, whether productive or not. Technical notes 163 Nationally protected areas are totally or par- Forest Resources Assessment. Data on na- tially protected areas of at least 1,000 hect- tionally protected areas are from the United ares that are designated as scientific reserves Nations Environment Programme and the with limited public access, national parks, World Conservation Monitoring Centre. natural monuments, nature reserves or wild- Data on energy use are from electronic files life sanctuaries, and protected landscapes. of the International Energy Agency. Data on Marine areas, unclassified areas, and littoral carbon dioxide emissions are from the Car- (intertidal) areas are not included. The data bon Dioxide Information Analysis Center, also do not include sites protected under lo- Environmental Sciences Division, Oak Ridge cal or provincial law. National Laboratory, in the U.S. state of Ten- Gross domestic product (GDP) per unit of nessee. Data on access to water and sanita- energy use is the GDP in purchasing power tion are from the World Health Organization parity (PPP) U.S. dollars per kilogram of oil and United Nations Children's Fund's Prog- equivalent of energy use. PPP GDP is gross ress on Drinking Water and Sanitation (2008). domestic product converted to 2000 con- stant international dollars using purchasing Table .. Millennium Development power parity rates. An international dollar Goal : develop a global partnership has the same purchasing power over GDP as for development a U.S. dollar has in the United States. Heavily Indebted Poor Countries (HIPC) Debt Carbon dioxide emissions per capita are those Initiative decision point is the date at which stemming from the burning of fossil fuels a HIPC with an established track record of and the manufacture of cement divided by good performance under adjustment pro- midyear population. They include carbon di- grams supported by the International Mon- oxide produced during consumption of solid, etary Fund (IMF) and the World Bank com- liquid and gas fuels, and gas flaring. mits to undertake additional reforms and to Population with sustainable access to an im- develop and implement a poverty reduction proved water source is the percentage of the strategy. population with reasonable access to an ad- HIPC completion point is the date at which equate amount of water from an improved the country successfully completes the key source, such as a household connection, structural reforms agreed on at the decision public standpipe, borehole, protected well or point, including developing and implement- spring, or rainwater collection. Unimproved ing its poverty reduction strategy. The coun- sources include vendors, tanker trucks, and try then receives the bulk of debt relief under unprotected wells and springs. Reasonable the HIPC Initiative without further policy access is defined as the availability of at least conditions. 20 liters a person a day from a source within Debt service relief committed is the amount of one kilometer of the dwelling. debt service relief, calculated at the Enhanced Population with sustainable access to im- HIPC Initiative decision point that will allow proved sanitation is the percentage of the the country to achieve debt sustainability at population with at least adequate access to the completion point. excreta disposal facilities that can effectively Public and publicly guaranteed debt service is prevent human, animal, and insect contact the sum of principal repayments and interest with excreta. Improved facilities range from actually paid on total long-term debt (public simple but protected pit latrines to flush toi- and publicly guaranteed and private non- lets with a sewerage connection. The excreta guaranteed), use of IMF credit, and interest disposal system is considered adequate if it on short-term debt. is private or shared (but not public) and if it Youth unemployment rate is the percentage hygienically separates human excreta from of the labor force ages 15­24 without work human contact. To be effective, facilities but available for and seeking employment. must be correctly constructed and properly Definitions of labor force and unemployment maintained. may differ by country. Fixed-line and mobile telephone subscribers Source: Data on forest area are from the are subscribers to a fixed-line telephone ser- Food and Agricultural Organization's Global vice, which connects a customer's equipment 164 Africa Development Indicators 2010 to the public switched telephone network, or Time required to register property is the to a public mobile telephone service, which number of calendar days needed for a busi- uses cellular technology. ness to secure rights to property. Personal computers are self-contained com- Cost to register property is the official costs puters designed for use by a single individual. required by law to register a property, includ- Internet users are people with access to the ing fees, transfer taxes, stamp duties, and worldwide web. any other payment to the property registry, notaries, public agencies, and lawyers. Other Source: Data on HIPC countries are from taxes, such as capital gains tax or value added the IMF's "HIPC Status Reports." Data on tax, are excluded from the cost measure. Both external debt are mainly from reports to the costs borne by the buyer and those borne by World Bank through its Debtor Reporting the seller are included. If cost estimates differ System from member countries that have among sources, the median reported value is received International Bank for Reconstruc- used. It is reported as a percentage of prop- tion and Development loans or International erty value, which is assumed to be equivalent Development Association credits, as well as to 50 times income per capita. World Bank and IMF files. Data on youth Number of procedures to enforce a contract is unemployment are from the International the number of independent actions, mandat- Labour Organization's Key Indicators of ed by law or courts that demand interaction the Labour Market, fourth edition. Data on between the parties of a contract or between phone subscribers, personal computers, and them and the judge or court officer. Internet users are from the International Time required to enforce a contract is the Telecommunication Union's (ITU) World number of calendar days from the filing of Telecommunication Development Report the lawsuit in court until the final determina- database and World Bank estimates. tion and, in appropriate cases, payment. Cost to enforce a contract is court and attor- 4. Private sector development ney fees, where the use of attorneys is man- datory or common, or the cost of an adminis- Table .. Doing Business indicators trative debt recovery procedure, expressed as Number of startup procedures to start a business a percentage of the debt value. is the number of procedures required to start Number of procedures to deal with construc- a business, including interactions to obtain tion permits is the number of procedures necessary permits and licenses and to com- required to obtain construction-related plete all inscriptions, verifications, and noti- permits. fications to start operations. Time required to deal with construction per- Time required for each procedure to start a mits is the average wait, in days, experienced business is the number of calendar days need- to obtain construction-related permit from ed to complete each procedure to legally oper- the day the establishment applied for it to ate a business. If a procedure can be speeded the day it was granted. up at additional cost, the fastest procedure, Cost to deal with construction permits is all independent of cost, is chosen. the fees associated with completing the pro- Cost to start a business is normalized by cedures to legally build a warehouse, includ- presenting it as a percentage of gross nation- ing those associated with obtaining land use al income (GNI) per capita. approvals and preconstruction design clear- Minimum capital is the paid-in minimum ances; receiving inspections before, during capital requirement, which reflects the and after construction; getting utility con- amount that the entrepreneur needs to de- nections; and registering the warehouse posit in a bank or with a notary before reg- property. Nonrecurring taxes required for istration and up to three months following the completion of the warehouse project also incorporation. It is reported as a percentage are recorded. The building code, information of the country's income per capita. from local experts and specific regulations Number of procedures to register property is and fee schedules are used as sources for the number of procedures required for a busi- costs. If several local partners provide dif- ness to secure rights to property. ferent estimates, the median reported value Technical notes 165 is used. It is reported as a percentage of the 1 redundant worker, whether the employer country's income per capita. needs to notify a third party to terminate a Disclosure index measures the degree to group of 25 redundant workers, whether the which investors are protected through disclo- employer needs approval from a third party to sure of ownership and financial information. terminate 1 redundant worker, whether the Higher values indicate more disclosure. employer needs approval from a third party Director liability index measures a plain- to terminate a group of 25 redundant work- tiff 's ability to hold directors of firms liable ers, whether the law requires the employer to for damages to the company. Higher values reassign or retrain a worker before making indicate greater liability. the worker redundant, whether priority rules Shareholder suits index measures share- apply for redundancies, and whether priority holders' ability to sue officers and direc- rules apply for reemployment. For the first tors for misconduct. Higher values indicate question the answer yes is assigned a score greater power for shareholders to challenge of 10, and the rest of the questions do not transactions. apply. For the fourth question the answer yes Investor protection index measures the de- is assigned a score of 2, and the answer no a gree to which investors are protected through 0. For every other question the answer yes is disclosure of ownership and financial infor- assigned score of 1, and the answer no a 0. mation regulations. It is the average of the Firing cost indicates the notice require- disclosure, director liability, and shareholder ments, severance, payments, and penalties suits indexes. Higher values indicate better due when terminating a redundant worker, protection. expressed in weeks of salary. Rigidity of hours index, a measure of em- Rigidity of employment index measures the ployment regulation, is the average score in regulation of employment, specifically the five areas: whether night work is unrestrict- hiring and firing of workers and the rigidity ed, whether weekend work is unrestricted, of working hours. This index is the average of whether the work week can consist of 5.5 three subindexes: the rigidity of hours index, days, whether the workweek can extend to the difficulty of hiring index, and the diffi- 50 hours or more (including overtime) for culty of firing index. two months a year to respond to a seasonal increase in production, whether paid annual Source: Data are from the World Bank's Do- vacation is 21 working days or fewer. For each ing Business project (http://rru.worldbank. question the answer no is assigned a score of org/DoingBusiness/). 1, and the answer yes a 0. Difficulty of hiring index indicates the appli- Table .. Investment climate cability and maximum duration of fixed-term Private sector fixed capital formation is private contracts and minimum wage for trainee or sector fixed capital formation (table 2.21) first-time employee. It measures whether divided by nominal gross domestic product fixed-term contracts are prohibited for per- (table 2.1). manent tasks, the maximum cumulative du- Net foreign direct investment is investment ration of fixed-term contracts, and the ratio by residents of the Organisation for Econom- of the minimum wage for a trainee or first- ic Co-operation and Development's (OECD) time employee to the average value added per Development Assistance Committee (DAC) worker. member countries to acquire a lasting man- Difficulty of firing index indicates the extent agement interest (at least 10 percent of vot- of notification and approval requirements ing stock) in an enterprise operating in the for termination of a redundant worker or a recipient country. The data reflect changes group of redundant workers, obligation to re- in the net worth of subsidiaries in recipient assign or retrain, and priority rules for redun- countries whose parent company is in the dancy and reemployment. It has eight com- DAC source country. ponents: whether redundancy is disallowed Domestic credit to private sector is financial as a basis for terminating workers, whether resources provided to the private sector, such the employer needs to notify a third party as through loans, purchases of non-equity se- (such as a government agency) to terminate curities, and trade credits and other accounts 166 Africa Development Indicators 2010 receivable that establish a claim for repay- spent in a typical week dealing with require- ment. For some countries these claims in- ments imposed by government regulations clude credit to public enterprises. (for example, taxes, customs, labor regula- Firms that believe the court system is fair, tions, licensing, and registration), including impartial, and uncorrupt are the percentage dealings with officials, completing forms, and of firms that believe the court system is fair, the like. impartial, and uncorrupted. Average time to clear customs, direct exports, Corruption is the percentage of firms iden- is the number of days to clear direct exports tifying corruption as a major constraint to through customs. current operation. Average time to clear customs, imports, is Crime, theft, and disorder are the percentage the average number of days to clear imports of firms identifying crime, theft, and disorder through customs. as a major constraint to current operation. Interest rate spread is the interest rate Tax rates are the percentage of firms iden- charged by banks on loans to prime custom- tifying tax rates as a major constraint to cur- ers minus the interest rate paid by commer- rent operation. cial or similar banks for demand, time, or Finance is the percentage of firms identify- savings deposits. ing access to finance or cost of finance as a Listed domestic companies are domestically major constraint to current operation. incorporated companies listed on a coun- Electricity is the percentage of firms identi- try's stock exchanges at the end of the year. fying electricity as a major constraint to cur- They exclude investment companies, mu- rent operation. tual funds, and other collective investment Labor regulations are the percentage of vehicles. firms identifying labor regulations as a major Market capitalization of listed companies, constraint to current operation. also known as market value, is the share price Labor skills are the percentage of firms of a listed domestic company's stock times identifying skills of available workers as a the number of shares outstanding. major constraint to current operation. Turnover ratio for traded stocks is the total Transportation is the percentage of firms value of shares traded during the period di- identifying transportation as a major con- vided by the average market capitalization straint to current operation. for the period. Average market capitalization Customs and trade regulations are the per- is calculated as the average of the end-of- centage of firms identifying customs and period values for the current period and the trade regulations as a major constraint to previous period. current operation. Number of tax payments is the number of Source: Data on private sector fixed capital taxes paid by businesses, including electronic formation are from the World Bank's World filing. The tax is counted as paid once a year Development Indicators database. Data on even if payments are more frequent. net foreign direct investment are from the Time to prepare, file, and pay taxes is the World Bank's World Development Indica- number of hours it takes to prepare, file, and tors database. Data on domestic credit to pay (or withhold) three major types of taxes: the private sector are from the International the corporate income tax, the value added or Monetary Fund's International Financial sales tax, and labor taxes, including payroll Statistics database and data files, World Bank taxes and social security contributions. and OECD gross domestic product (GDP) Total tax rate is the total amount of taxes estimates, and the World Bank's World De- payable by the business (except for labor velopment Indicators database. Data on taxes) after accounting for deductions and investment climate constraints to firms are exemptions as a percentage of profit. based on enterprise surveys conducted by Highest marginal tax rate, corporate, is the the World Bank and its partners (http://rru. highest rate shown on the schedule of tax rates worldbank.org/EnterpriseSurveys). Data on applied to the taxable income of corporations. regulation and tax administration and high- Time dealing with officials is the average per- est marginal corporate tax rates are from the centage of senior management's time that is World Bank's Doing Business project (http:// Technical notes 167 rru.worldbank.org/DoingBusiness). Data on Real interest rate is the lending interest time dealing with officials and average time rate adjusted for inflation as measured by the to clear customs are from World Bank En- gross domestic product (GDP) deflator. terprise Surveys (http://rru.worldbank.org/ Domestic credit to private sector is financial EnterpriseSurveys/). Data on interest rate resources provided to the private sector, such spreads are from the IMF's International as through loans, purchases of nonequity Financial Statistics database and data files securities, and trade credits and other ac- and the World Bank's World Development counts receivable, that establish a claim for Indicators database. Data on listed domes- repayment. For some countries these claims tic companies and turnover ratios for traded include credit to public enterprises. stocks are from Standard & Poor's Emerging Interest rate spread is the interest rate Stock Markets Factbook and supplemental charged by banks on loans to prime custom- data and the World Bank's World Develop- ers minus the interest rate paid by commer- ment Indicators database. Data on market cial or similar banks for demand, time, or capitalization of listed companies are from savings deposits. Standard & Poor's Emerging Stock Markets Ratio of bank nonperforming loans to total Factbook and supplemental data, World gross loans is the value of nonperforming Bank and OECD estimates of GDP, and the loans divided by the total value of the loan World Bank's World Development Indicators portfolio (including nonperforming loans be- database. fore the deduction of specific loan-loss provi- sions). The loan amount recorded as nonper- Table .. Financial sector forming should be the gross value of the loan infrastructure as recorded on the balance sheet, not just the Foreign currency sovereign ratings are long- amount that is overdue. and short-term foreign currency ratings Listed domestic companies are domestically that assess a sovereign's capacity and will- incorporated companies listed on a coun- ingness to honor its existing and future try's stock exchanges at the end of the year. obligations issued in foreign currencies in They exclude investment companies, mu- full and on time. Short-term ratings have tual funds, and other collective investment a time horizon of less than 13 months for vehicles. most obligations, or up to three years for Market capitalization of listed companies, U.S. public finance, in line with industry also known as market value, is the share price standards, to reflect unique risk character- of a listed domestic company's stock times istics of bond, tax, and revenue anticipation the number of shares outstanding. notes that are commonly issued with terms Turnover ratio for traded stocks is the total up to three years. Short-term ratings thus value of shares traded during the period di- place greater emphasis on the liquidity nec- vided by the average market capitalization essary to meet financial commitments in a for the period. Average market capitalization timely manner. is calculated as the average of the end-of- Gross national savings is the sum of gross period values for the current period and the domestic savings (table 2.13) and net fac- previous period. tor income and net private transfers from abroad. The estimate here also includes net Source: Data on foreign currency sovereign public transfers from abroad. ratings are from Fitch Ratings. Data on gross Money and quasi money (M2) are the sum national savings are from World Bank coun- of currency outside banks, demand deposits try desks. Data on money and quasi money other than those of the central government, and domestic credit to the private sector are and the time, savings, and foreign currency from the IMF's International Financial Sta- deposits of resident sectors other than the tistics database and data files, World Bank central government. This definition of mon- and OECD estimates of GDP, and the World ey supply is frequently called M2 and cor- Bank's World Development Indicators data- responds to lines 34 and 35 in the Interna- base. Data on real interest rates are from the tional Monetary Fund's (IMF) International IMF's International Financial Statistics data- Financial Statistics. base and data files using World Bank data on 168 Africa Development Indicators 2010 the GDP deflator and the World Bank's World assets or depletion and degradation of natu- Development Indicators database. Data on ral resources. For countries that report that interest rate spreads are from the IMF's In- report national accounts data at producer ternational Financial Statistics database and prices (Benin, the Republic of Congo, Côte data files and the World Bank's World Devel- d'Ivoire, Gabon, Ghana, Niger, Rwanda, Tan- opment Indicators database. Data on ratios of zania, Togo, and Tunisia), gross value added bank nonperforming loans to total are from at market prices is used as the denominator. the IMF's Global Financial Stability Report For countries that report national accounts and the World Bank's World Development data at basic prices (all other countries), Indicators database. Data on bank branches gross value added at factor cost is used as the are from surveys of banking and regulatory denominator. institutions by the World Bank's Research Exports of goods and services represent the Department and Financial Sector and Opera- value of all goods and other market services tions Policy Department and the World De- provided to the rest of the world. They include velopment Indicators database. Data on list- the value of merchandise, freight, insurance, ed domestic companies and turnover ratios transport, travel, royalties, license fees, and for traded stocks are from Standard & Poor's other services, such as communication, con- Emerging Stock Markets Factbook and sup- struction, financial, information, business, plemental data and the World Bank's World personal, and government services. They ex- Development Indicators database. Data on clude labor and property income (formerly market capitalization of listed companies are called factor services) as well as transfer pay- from Standard & Poor's Emerging Stock Mar- ments, and expressed in current U.S. dollars kets Factbook and supplemental data, World and as a proportion of nominal GDP. Bank and OECD estimates of GDP, and the Imports of goods and services represent the World Bank's World Development Indicators value of all goods and other market services database. received from the rest of the world. They in- clude the value of merchandise, freight, in- 5. Trade and regional integration surance, transport, travel, royalties, license See box 3 for a discussion of the chal- fees, and other services, such as communi- lenges of measuring the impact of regional cation, construction, financial, information, integration. business, personal, and government services. They exclude labor and property income (for- Table .. International trade and merly called factor services) as well as trans- tariff barriers fer payments and expressed in current U.S. Total trade is the sum of exports and imports dollars and as a proportion of nominal GDP. of goods and services measured as a share of Annual growth of exports and imports is cal- gross domestic product. culated using real imports and exports. Merchandise trade is the sum of imports Terms of trade index measures the relative and exports of merchandise divided by nomi- movement of export and import prices. This nal gross domestic product. series is calculated as the ratio of a country's Services trade is the sum of imports and export unit values or prices to its import unit exports of wholesale and retail trade (includ- values or prices shows changes over a base ing hotels and restaurants), transport, and year (2000) in the level of export unit values government, financial, professional, and as a percentage of import unit values. personal services such as education, health Structure of merchandise exports and imports care, and real estate services (International components may not sum to 100 percent be- Standard Industrial Classification revision 3 cause of unclassified trade. divisions 50­99) less the value of their inter- Food comprises the commodities in Stan- mediate inputs. Also included are imputed dard International Trade Classification bank service charges, import duties, and any (SITC) sections 0 (food and live animals), 1 statistical discrepancies noted by national (beverages and tobacco), and 4 (animal and compilers as well as discrepancies arising vegetable oils and fats) and SITC division 22 from rescaling. It is calculated without mak- (oil seeds, oil nuts, and oil kernels). ing deductions for depreciation of fabricated Technical notes 169 Box 3 Measuring the impact of regional integration The simplest measure of regional integration is the share of im- Democratic Republic of Congo and Ethiopia are not party to the ports from regional partners in the total imports of a regional free trade agreement. group. Successful regional agreements may increase trade be- It is important to go beyond simple trade shares to identify the tween partners relative to their trade with the rest of the world, economic impact of regional trade agreements. For agreements in with four caveats. First, preferential trade agreements are an ex- Africa, where combined markets remain very small relative to the ample of a second-best economic policy, whereby the removal global market, it is equally important to ask how the agreement of one economic distortion (tariffs on imports from partners) is can be used as part of a broad approach to openness and espe- accompanied by a new distortion (discrimination against non- cially whether the agreement can provide a springboard to global members that still have to pay the tariff). A regional trade agree- markets for local exporters. ment that increases trade among members by diverting trade Regional agreements in Africa are typically associated with low away from nonmembers may not be economically benefi cial. shares of intraregional trade in total trade compared with groups Only when an agreement creates new trade among partners will in other regions. It is often suggested that this reflects the lack economic welfare increase. Second, successful regional inte- of complementarity between the production structures of Africa gration is typically accompanied by reductions in most favored countries with total exports being dominated by primary products nation tariffs on imports from nonmembers, so the share of re- that are not consumed locally. Export diversification is therefore a gional trade may not rise even though the volume of regional key priority for most Africa countries. Nevertheless, African coun- trade is increasing. Third, regional trade agreements may reduce tries trade much more with each other than is reflected in official trade costs other than those associated with formal trade poli- statistics. A range of surveys confirm that informal cross-border cies, such as improved customs procedures, which are likely to trade in a range of goods, such as processed and primary agricul- stimulate trade with all countries. Fourth, regional agreements tural products and simple manufactures, and services amounts to may cover issues not directly related to trade, such as movement a significant proportion of recorded trade. This indicates that the of capital and labor, that may have important benefits in terms of potential for growth of intraregional trade in Africa could be much growth and incomes. For these reasons another useful measure larger than official figures would suggest. of regional integration is the share of extra- and intra-regional In other regions, such as Southeast Asia, inward foreign direct trade in regional GDP. A declining share of extra-regional trade investment and the increasing importance of regional production in total trade will be less significant if the total value of trade is networks have been key drivers of the expansion of cross-border increasing. trade in parts and components. Such trade is very sensitive to Positive outcomes from regional integration depend on design trade costs, and a key reason for the lack of regional trade in Af- and implementation, so when assessing the impact of a regional rica is continued high trade costs. These encapsulate not only agreement, the nature and extent to which trade policy obligations the high costs of transportation (reflecting weak infrastructure) under the agreement are actually being applied must be checked. but also substantial policy related barriers to trade, including inef- Agreements that devote considerable resources to negotiating a ficient customs procedures, nontariff barriers and corruption as large range of product exclusions from liberalization and complex well as ineffective government responses to key market failures and restrictive rules of origin tend to limit the scope for gains. that limit exports, such as lack of information on overseas market Within the regional groupings in Africa not all members have made opportunities and requirements. In Africa reducing trade costs is a or implemented tariff commitments. For example, Angola has prerequisite for export diversification, increasing regional integra- signed the Southern African Development Community Trade Pro- tion and global competitiveness. tocol but has not submitted a market access schedule. Similarly, for the Common Market for Eastern and Southern COMESA, the Source: World Bank 2005. Agricultural raw materials comprise the Manufactures comprise the commodities in commodities in SITC section 2 (crude ma- SITC sections 5 (chemicals), 6 (basic manu- terials except fuels), excluding divisions 22, factures), 7 (machinery and transport equi- 27 (crude fertilizers and minerals excluding pment), and 8 (miscellaneous manufactured coal, petroleum, and precious stones), and 28 goods), excluding division 68. (metalliferous ores and scrap). Export diversification index measures the Fuel comprises SITC section 3 (mineral extent to which exports are diversified. It is fuels). constructed as the inverse of a Herfindahl Ores and metals comprise the commodities index, using disaggregated exports at four in SITC sections 27, 28, and 68 (nonferrous digits (following the SITC3). A higher index metals). indicates more export diversification. 170 Africa Development Indicators 2010 Export concentration index, part of the Binding coverage is the percentage of prod- Herfindahl-Hirschmann index, is calculated uct lines with an agreed bound rate. as Simple mean bound rate is the unweighted average of all the lines in the tariff schedule in which bound rates have been set. Simple mean tariff is the unweighted aver- age of effectively applied rates or most fa- vored nation rates for all products subject to tariffs calculated for all traded goods. Dispersion around the mean is calculated as where Xij is country j's exports of product i the coefficient of variation of the applied tariff (at the SITC 3-digit level, where the number rates, including preferential rates that a coun- of products imported and exported includes try applies to its trading partners available at only products whose value exceeds $100,000 the six-digit product level of the Harmonized or 0.3 percent of the country's total imports System in a country's customs schedule. and exports, whichever is smaller; the maxi- Weighted mean tariff is the average of ef- mum number of 3-digit products that could fectively applied rates or most favored nation be imported and exported is 261), Xj is coun- rates weighted by the product import shares try j's total exports, and n is the total number corresponding to each partner country. of 3-digit products. This type of concentra- Share of lines with international peaks is the tion indicator is vulnerable to cyclical fluc- share of lines in the tariff schedule with tariff tuations in relative prices, with commodity rates that exceed 15 percent. price rises making commodity exporters look Share of lines with domestic peaks is the more concentrated. share of lines in the tariff schedule with tar- Export destination index, part of the iff rates that are more than three times the Herfindahl-Hirschmann index, is calculated simple average tariff. as Share of lines that are bound is the share of lines in the country's tariff schedule bound subject to World Trade Organization negotia- tion agreements. Share of lines with specific rates is the share where Xij is country i's exports to country j of lines in the tariff schedule that are set on (at the SITC 3-digit level) and Xi is country i's a per unit basis or that combine ad valorem total exports to all trading partners. This type and per unit rates. of concentration indicator tends is vulnerable Primary products are commodities classi- to cyclical fluctuations in relative prices, with fied in SITC revision 2 sections 0­4 plus divi- commodity price rises making commodity sion 68. exporters look more concentrated. Manufactured products are commodities Competitiveness indicator has two aspects: classified in SITC revision 2 sections 5­8 ex- sectoral effect and global effect. To calculate cluding division 68. both indicators, growth of exports is decom- GATS commitments index measures the ex- posed into three components: the growth tent of General Agreement on Trade in Services rate of total international trade over the (GATS) commitments for all 155 services sub- reference period (2003­07); the sectoral ef- sectors as classified by the GATS and in the four fect, which measures the contribution to a modes of the GATS. Each entry in the country's country's export growth of the dynamics of schedule is assigned scores based on its rela- the sectoral markets where the country sells tive restrictiveness, using Bernard Hoekman's its products, assuming that sectoral market methodology. That resulted in 1,240 scores, shares are constant; and the competitiveness ranging from 0 (unbound or no commitments) effect, which measures the contribution of to 100 (completely liberalized), with an inter- changes in sectoral market shares to a coun- mediate value of 50 for partial commitments. try's export growth. A simple average of the subsectoral scores were Tariff barriers are a form of duty based on used to generate aggregate subsectoral scores the value of the import. (for the 12 main services sectors as classified Technical notes 171 by the GATS), modes scores, and market access level (following the Standard International and national treatment scores. The overall 12 Trade Classification revision 3). GATS commitment index is a simple average Number of exports accounting for 75 percent of the subsectoral indexes. of total exports is the number of exports in a Average cost to ship 20 ft container from port country that account for 75 percent of the to destination is the cost of all operations as- country's exports. sociated with moving a container from on- board a ship to the considered economic cen- Source: Organisation for Economic Co-op- ter, weighted based on container traffic for eration and Development data. each corridor. Average time to clear customs, direct exports, Table . Regional integration, trade is the number of days to clear direct exports blocs through customs. Type of most recent agreement includes cus- Average time to clear customs, imports, is toms union, under which members sub- the average number of days to clear imports stantially eliminate all tariff and nontariff through customs. barriers among themselves and establish a common external tariff for nonmembers; Source: Data on trade and services are from economic integration agreement, which lib- World Bank and Organisation for Economic eralizes trade in services among members Co-operation and Development national ac- and covers a substantial number of sectors, counts data. Data on merchandise trade are affects a sufficient volume of trade, includes from the World Trade Organization and World substantial modes of supply, and is nondis- Bank GDP estimates. All indicators in the ta- criminatory (in the sense that similarly situ- ble were calculated by World Bank staff using ated service suppliers are treated the same); the World Integrated Trade Solution system. free trade agreement, under which members Data on the export diversification index and substantially eliminate all tariff and nontariff the competitiveness indicator are from the barriers but set tariffs on imports from non- Organisation for Economic Co-operation and members; partial scope agreement, which is Development. Data on the export concentra- a preferential trade agreement notified to the tion index and destination index data are from World Trade Organization (WTO) that is not the United Nations Conference on Trade and a free trade agreement, a custom union, or an Development Statistical Office and Handbook economic integration; and not notified agree- of Statistics, various issues. Data on tariffs ment, which is a preferential trade arrange- are from the United Nations Conference on ment established among member countries Trade and Development and the World Trade that is not notified to the WTO (the agree- Organization. Data on global imports are ment may be functionally equivalent to any from the United Nations Statistics Division's of the other agreements). COMTRADE database. Data on merchandise Merchandise exports within bloc are the sum exports and imports are from World Bank of merchandise exports by members of a trade country desks. Data on shipping costs are bloc to other members of the bloc. They are from the World Bank's Sub-Saharan Africa shown both in U.S. dollars and as a percent- Transport Policy Program. Data on GATS com- age of total merchandise exports by the bloc. mitments are from the World Trade Organiza- Merchandise exports by bloc are the sum of tion, as scored by the World Bank Institute's merchandise exports within bloc and to the World Trade Indicators 2008 team. Scoring and rest of the world as a share of total merchan- subsectoral weights follow Hoekman (1995). dise exports by all economies in the world. Data on average time to clear customs are from World Bank Enterprise Surveys (http:// Source: Data on merchandise trade flows rru.worldbank.org/EnterpriseSurveys/). are published in the International Monetary Fund's (IMF) Direction of Trade Statistics Table . Top three exports and share Yearbook and Direction of Trade Statistics in total exports, Quarterly. The data in the table were calcu- Top exports and share of total exports are based lated using the IMF's Direction of Trade da- on exports disaggregated at the four-digit tabase. The United Nations Conference on 172 Africa Development Indicators 2010 Trade and Development publishes data on other donors. The release of funds to, or the intraregional trade in its Handbook of Inter- purchase of goods or services for a recipient; national Trade and Development Statistics. by extension, the amount thus spent. Dis- The information on trade bloc membership is bursements record the actual international from the World Bank. transfer of financial resources, or of goods or services valued at the cost of the donor. 6. Infrastructure Source: Data on fresh water resources are Table .. Water and sanitation from the World Bank's World Development Internal fresh water resources per capita are Indicators database. Data on access to water the sum of total renewable resources, which and sanitation are from the World Health include internal flows of rivers and ground- Organization and United Nations Children's water from rainfall in the country, and river Fund's Meeting the MDG Drinking Water flows from other countries. and Sanitation Target (www.unicef.org/wes/ Population with sustainable access to an im- mdgreport). Data on water supply failure are proved water source is the percentage of popu- from World Bank Enterprise Surveys (http:// lation with reasonable access to an adequate rru.worldbank.org/EnterpriseSurveys/). Data amount of water from an improved source, on committed nominal investment in potable such as a household connection, public water projects with private participation are standpipe, borehole, protected well or spring, from the World Bank's Private Participation or rainwater collection. Unimproved sources in Infrastructure database. Data on ODA dis- include vendors, tanker trucks, and unpro- bursements are from the Organisation for tected wells and springs. Reasonable access is Economic Co-operation and Development. defined as the availability of at least 20 liters a person a day from a source within one kilo- Table .. Transportation meter of the user's dwelling. Road network is the length of motorways, Population with sustainable access to im- highways, main or national roads, secondary proved sanitation is the percentage of the or regional roads, and other roads. population with at least adequate access to Rail lines are the length of railway route excreta disposal facilities that can effectively available for train service, irrespective of the prevent human, animal, and insect contact number of parallel tracks. with excreta. Improved facilities range from Road density, ratio to arable land, is the to- simple but protected pit latrines to flush toi- tal length of national road network per 1,000 lets with a sewerage connection. The excreta square kilometers of arable land area. The use disposal system is considered adequate if it of arable land area in the denominator focus- is private or shared (but not public) and if it es on inhabited sectors of total land area by hygienically separates human excreta from excluding wilderness areas. human contact. To be effective, facilities Road density, ratio to total land, is the total must be correctly constructed and properly length of national road network per 1,000 maintained. square kilometers of total land area. Water supply failure for firms receiving water Rural access is the percentage of the rural is the average number of days per year that population who live within 2 kilometers of firms experienced insufficient water supply an all-season passable road as a share of the for production. total rural population. Committed nominal investment in water proj- Vehicle fleet is the number of motor ve- ects with private participation is annual com- hicles, including cars, buses, and freight ve- mitted investment in water projects with hicles but not two-wheelers. private investment, including projects for po- Commercial vehicles are the number of com- table water generation and distribution and mercial vehicles that use at least 24 liters of sewerage collection and treatment projects. diesel fuel per 100 kilometers. Official development assistance (ODA) gross Passenger vehicles are road motor vehicles, disbursements for water supply and sanitation other than two-wheelers, intended for the sector are disbursements for water supply carriage of passengers and designed to seat no and sanitation by bilateral, multilateral, and more than nine people (including the driver). Technical notes 173 Road network in good or fair condition is the are from the World Bank's Private Participa- length of the national road network, includ- tion in Infrastructure database. Data on ODA ing the interurban classified network without disbursements are from the Organisation for the urban and rural network, that is in good Economic Co-operation and Development. or fair condition, as defined by each country's road agency. Table .. Information and communica- Ratio of paved to total roads is the length of tion technology paved roads--which are those surfaced with Telephone subscribers are subscribers to a main crushed stone (macadam) and hydrocarbon telephone line service, which connects a cus- binder or bituminized agents, with concrete, tomer's equipment to the public switched or with cobblestones--as a percentage of all telephone network, or to a cellular telephone the country's roads. service, which uses cellular technology. Price of diesel fuel and gasoline is the price as Unmet demand is the number of applica- posted at filling stations in a country's capi- tions for connection to the public switched tal city. When several fuel prices for major telephone network that have been held back cities were available, the unweighted aver- because of a lack of technical facilities (equip- age is used. Since super gasoline (95 octane/ ment, lines, and the like) divided by the num- A95/premium) is not available everywhere, ber of main telephone lines. it is sometime replaced by regular gasoline Households with own telephone are the (92 octane/A92), premium plus gasoline percentage of households possessing a (98 octane/A98), or an average of the two. telephone. Committed nominal investment in transport Average delay for firm in obtaining a mainline projects with private participation is annual phone connection is the average actual delay in committed investment in transport projects days that firms experience when obtaining with private investment, including projects a telephone connection, measured from the for airport runways and terminals, railways day the establishment applied to the day it (including fixed assets, freight, intercity pas- received the service or approval. senger, and local passenger), toll roads, bridg- Internet users are people with access to the es, and tunnels. worldwide network. Official development assistance (ODA) gross Telephone faults are the total number of re- disbursements for transportation and storage are ported faults for the year divided by the total disbursements for transportation and storage number of mainlines in operation multiplied by bilateral, multilateral, and other donors. by 100. The definition of fault can vary. Some Disbursements record the actual internation- countries include faulty customer equip- al transfer of financial resources or of goods ment; others distinguish between reported or services valued at the cost of the donor. and actual found faults. There is also some- times a distinction between residential and Source: Data on length of road network business lines. Another consideration is the and size of vehicle fleet are from the Inter- time period: some countries report this indi- national Road Federation's World Road Sta- cator on a monthly basis; in these cases data tistics. Data on rail lines and ratio of paved to are converted to yearly estimates. total roads are from the World Bank's World Telephone faults cleared by next working day Development Indicators database. Data are the percentage of faults in the public on road density and rural access to roads switched telephone network that have been are from the World Bank's Sub-Saharan Af- corrected by the end of the next working day. rica Transport Policy Program (SSATP) and Price basket for Internet is calculated based World Development Indicators database. on the cheapest available tariff for accessing Data on length of national network in good the Internet 20 hours a month (10 hours or fair condition and average time and costs peak and 10 hours off-peak). The basket does are from the World Bank's SSATP. Data on not include telephone line rental but does in- fuel and gasoline prices are from the German clude telephone usage charges if applicable. Agency for Technical Cooperation (GTZ). Data are compiled in the national currency Data on committed nominal investment in and converted to U.S. dollars using the an- transport projects with private participation nual average exchange rate. 174 Africa Development Indicators 2010 Cost of 3 minute fixed telephone local phone record the actual international transfer of call during peak hours is the cost of a three- financial resources or of goods or services minute local call during peak hours. Local call valued at the cost of the donor. refers to a call within the same exchange area using the subscriber's own terminal (that is, Source: Data on telephone subscribers, not from a public telephone). unmet demand, reported phone faults, and Cost of 3 minute cellular local call during peak cost of local and cellular calls are from the hours is the cost of a three-minute cellular lo- International Telecommunications Union. cal call during peak hours. Data on households with own telephone Cost of 3 minute phone call to the United are from Demographic and Health Surveys. States (US) during peak hours is the cost of a Data on delays for firms in obtaining a tele- three-minute call to the United States during phone connection are from World Bank En- peak hours. terprise Surveys (http://rru.worldbank.org/ Residential telephone connection charge is the EnterpriseSurveys/). Data on Internet users initial, one-time charge involved in applying for and pricing, telephone connection charges, basic telephone service for business purposes. and annual investment on telecommunica- Where charges differ by exchange areas, the tions are from the International Telecom- charge reported is for the largest urban area. munication Union, World Telecommunica- Business telephone connection charge is the tion Development Report and database, one-off charge involved in applying for busi- and World Bank estimates. Data on cost of a ness basic telephone service. Where charges call to the United States are from the World differ by exchange area, the charge reported Bank's Global Development Finance and is for the largest urban area. World Development Indicator databases. Mobile cellular connection charge is the ini- Data on committed nominal investment are tial, one-time charge for a new subscription from the World Bank's Private Participation to a cellular phone service. It includes the in Infrastructure database. Data on ODA dis- price of the subscriber identity module (SIM) bursements are from the Organisation for card but excludes refundable deposits. It also Economic Co-operation and Development. includes taxes. Annual investment in fixed telephone service Table .. Energy is the annual investment in equipment for Electricity production is measured at the termi- fixed telephone service. nals of all alternator sets in a station. In addi- Annual investment in mobile communication tion to hydropower, coal, oil, gas, and nuclear is the capital investment on equipment for power generation, it covers generation by mobile communication networks. geothermal, solar, wind, and tide and wave Annual investment in telecommunications is energy, as well as that from combustible re- the expenditure associated with acquiring the newables and waste. Production includes the ownership of telecommunication equipment output of electricity plants that are designed infrastructure (including supporting land to produce electricity only as well as that of and buildings and intellectual and non-tan- combined heat and power plants. gible property such as computer software). It Hydroelectric refers to electricity produced includes expenditure on initial installations by hydroelectric power plants. and on additions to existing installations. Coal refers to all coal and brown coal, both Committed nominal investment in telecom- primary (including hard coal and lignite- munication projects with private participation brown coal) and derived fuels (including is annual committed investment in telecom- patent fuel, coke oven coke, gas coke, coke munication projects with private investment, oven gas, and blast furnace gas). Peat is also including projects for fixed or mobile local te- included. lephony, domestic long-distance telephony, Natural gas refers to natural gas but ex- and international long-distance telephony. cludes natural gas liquids. Official development assistance (ODA) gross Nuclear refers to electricity produced by disbursements for communication are disburse- nuclear power plants. ments for communication by bilateral, mul- Oil refers to crude oil and petroleum tilateral, and other donors. Disbursements products. Technical notes 175 Electric power consumption is the produc- Firms that share or own their own generator tion of power plants and combined heat and are the percentage of firms that responded power plants, less distribution losses and "Yes" to the following question: "Does your own use by heat and power plants. establishment own or share a generator?" GDP per unit of energy use is nominal GDP Firms using electricity from generator are the in purchasing power parity (PPP) U.S. dollars percentage of firms using electricity supplied divided by apparent consumption, which is from a generator or generators that the firm equal to indigenous production plus imports owns or shares. and stock changes minus exports and fuels Committed nominal investment in energy supplied to ships and aircraft engaged in projects with private participation is annual international transport. committed investment in energy projects Solid fuels use is the percentage of the with private investment, including projects population using solid fuels as opposed to for electricity generation, transmission, and modern fuels. Solid fuels include fuel wood, distribution as well as natural gas transmis- straw, dung, coal, and charcoal. Modern fu- sion and distribution. els include electricity, liquefied petroleum Official development assistance (ODA) gross gas, natural gas, kerosene, and gasoline. The disbursements for energy are disbursements indicator is based on the main type of fuel for energy by bilateral, multilateral, and oth- used for cooking because cooking occupies er donors. Disbursements record the actual the largest share of overall household en- international transfer of financial resources ergy needs. However, many households use or of goods or services valued at the cost of more than one type of fuel for cooking and, the donor. depending on climatic and geographical con- ditions, heating with solid fuels can also con- Source: Data on electricity production tribute to indoor air pollution. are from the International Energy Agency's Firms identifying electricity as major or very Energy Statistics of Non-OECD Countries, En- severe obstacle to business operation and growth ergy Balances of Non-OECD Countries, Energy are the percentage of firms that responded Statistics of OECD Countries, and Energy Bal- "major" or "very severe" obstacle to the fol- ances of OECD Countries. Data on electric lowing question: "Please tell us if any of the power consumption and PPP GDP per unit following issues are a problem for the opera- of energy use are from the World Bank's tion and growth of your business. If an issue World Development Indicators database. (infrastructure, regulation, and permits) pos- Data on solid fuels use are from household es a problem, please judge its severity as an survey data, supplemented by World Bank obstacle on a five-point scale that ranges from Project Appraisal Documents. Data on 0 = no obstacle to 5 = very severe obstacle." firms identifying electricity as a major or Average delay for firm in obtaining electrical very severe obstacle to business operation connection is the average actual delay in days and growth, delays for firms in obtaining that firms experience when obtaining an elec- an electrical connection, electrical outages trical connection, measured from the day the of firms, firms that share or own their own establishment applied to the day it received generator, and firms using electricity from the service or approval. generator are from World Bank Enterprise Electric power transmission and distribution Surveys (http://rru.worldbank.org/En- losses are technical and nontechnical losses, terpriseSurveys/). Data on transmission including electricity losses due to operation and distribution losses are from the World of the system and the delivery of electricity Bank's World Development Indicators data- as well as those caused by unmetered supply. base, supplemented by World Bank Project This comprises all losses due to transport and Appraisal Documents. Data on committed distribution of electrical energy and heat. nominal investment are from the World Electrical outages of firms are the average Bank's Private Participation in Infrastruc- number of days per year that establishments ture database. Data on ODA disbursements experienced power outages or surges from are from the Organisation for Economic Co- the public grid. operation and Development. 176 Africa Development Indicators 2010 7. Human development patterns of mortality at the time of its birth were to remain the same throughout its life. Table .. Education Data are World Bank estimates based on data Youth literacy rate is the percentage of people from the United Nations Population Divi- ages 15­24 who can, with understanding, sion, the United Nations Statistics Division, both read and write a short, simple state- and national statistical offices. ment about their everyday life. Under-five mortality rate is the probability Adult literacy rate is the proportion of that a newborn baby will die before reaching adults ages 15 and older who can, with un- age 5, if subject to current age-specific mor- derstanding, read and write a short, simple tality rates. The probability is expressed as a statement on their everyday life. rate per 1,000. Primary education provides children with Infant mortality rate is the number of in- basic reading, writing, and mathematics skills fants dying before reaching one year of age, along with an elementary understanding of per 1,000 live births. such subjects as history, geography, natural Maternal mortality ratio, modeled estimate, science, social science, art, and music. is the number of women who die from preg- Secondary education completes the provi- nancy- related causes during pregnancy and sion of basic education that began at the pri- childbirth, per 100,000 live births. The data mary level and aims to lay the foundations are estimated by a regression model using in- for lifelong learning and human development formation on fertility, birth attendants, and by offering more subject- or skill-oriented in- HIV prevalence. struction using more specialized teachers. Prevalence of HIV is the percentage of peo- Tertiary education, whether or not at an ple ages 15­49 who are infected with HIV. advanced research qualification, normally Incidence of tuberculosis is the number of requires, as a minimum condition of admis- tuberculosis cases (pulmonary, smear posi- sion, the successful completion of education tive, and extrapulmonary) in a population at the secondary level. at a given point in time, per 100,000 people. Gross enrollment ratio is the ratio of total This indicator is sometimes referred to as enrollment, regardless of age, to the popu- "point prevalence." Estimates include cases of lation of the age group that officially corre- tuberculosis among people with HIV. sponds to the level of education shown. Clinical malaria cases reported are the sum Net enrollment ratio is the ratio of children of cases confirmed by slide examination or of official school age based on the Internation- rapid diagnostic test and probable and uncon- al Standard Classification of Education 1997 firmed cases (cases that were not tested but who are enrolled in school to the population treated as malaria). National malaria control of the corresponding official school age. programs often collect data on the number of Student-teacher ratio is the number of stu- suspected cases, those tested, and those con- dents enrolled in school divided by the num- firmed. Probable or unconfirmed cases are ber of teachers, regardless of their teaching calculated by subtracting the number tested assignment. from the number suspected. Not all cases re- Public spending on education is current and ported as malaria are true malaria cases; most capital public expenditure on education plus health facilities lack appropriate diagnostic subsidies to private education at the primary, services. The misdiagnosis may have led to secondary, and tertiary levels by local, region- under- or overreporting malaria cases and al, and national government, including munic- missing diagnosis of other treatable diseases. ipalities. It excludes household contributions. Reported malaria deaths are all deaths in health facilities that are attributed to malar- Source: United Nations Educational, Scien- ia, whether or not confirmed by microscopy tific, and Cultural Organization Institute for or by rapid diagnostic test. Statistics. Child immunization rate is the percentage of children ages 12­23 months who received Table .. Health vaccinations before 12 months or at any time Life expectancy at birth is the number of years before the survey for four diseases--measles a newborn infant would live if prevailing and diphtheria, pertussis (whooping cough), Technical notes 177 and tetanus (DPT). A child is considered ad- whether with bacteriologic evidence of success equately immunized against measles after re- ("cured") or without ("treatment completed"). ceiving one dose of vaccine and against DPT Children with fever receiving any antimalarial after receiving three doses. treatment same or next day are the percentage Stunting is the percentage of children un- of children under age 5 in malaria-risk areas der age 5 whose height for age is more than with fever being treated with any antimalar- two standard deviations below the median ial drugs. for the international reference population Population with sustainable access to an im- ages 0­59 months. For children up to age 2 proved water source is the percentage of the height is measured by recumbent length. For population with reasonable access to an ad- older children height is measured by stature equate amount of water from an improved while standing. The reference population source, such as a household connection, adopted by the World Health Organization public standpipe, borehole, protected well or (WHO) in 1983 is based on children from spring, or rainwater collection. Unimproved the United States, who are assumed to be sources include vendors, tanker trucks, and well nourished. unprotected wells and springs. Reasonable Underweight is the percentage of children access is defined as the availability of at least under age 5 whose weight for age is more 20 liters a person a day from a source within than two standard deviations below the me- one kilometer of the dwelling. dian reference standard for their age as es- Population with sustainable access to im- tablished by the WHO, the U.S. Centers for proved sanitation is the percentage of the Disease Control and Prevention, and the U.S. population with at least adequate access to National Center for Health Statistics. Data excreta disposal facilities that can effectively are based on children under age 3, 4, and 5, prevent human, animal, and insect contact depending on the country. with excreta. Improved facilities range from Births attended by skilled health staff are the simple but protected pit latrines to flush toi- percentage of deliveries attended by personnel lets with a sewerage connection. The excreta trained to give the necessary supervision, care, disposal system is considered adequate if it and advice to women during pregnancy, labor, is private or shared (but not public) and if it and the postpartum period; to conduct deliv- hygienically separates human excreta from eries on their own; and to care for newborns. human contact. To be effective, facilities Contraceptive use is the percentage of wom- must be correctly constructed and properly en ages 15­49, married or in union, who are maintained. practicing, or whose sexual partners are prac- Physicians are the number of physicians, ticing, any form of contraception. Modern including generalists and specialists. methods of contraception include female Nurses and midwives are professional nurs- and male sterilization, oral hormonal pills, es, auxiliary nurses, enrolled nurses, and oth- the intrauterine device, the male condom, in- er nurses, such as dental nurses and primary jectables, the implant (including Norplant), care nurses, and professional midwives, aux- vaginal barrier methods, the female condom, iliary midwives, and enrolled midwives. and emergency contraception. Community workers include various types Children sleeping under insecticide-treated of community health aides, many with nets are the percentage of the children under country-specific occupational titles such age 5 with access to an insecticide-treated net as community health officers, community to prevent malaria. health-education workers, family health Tuberculosis cases detected under DOTS are workers, lady health visitors, and health ex- the percentage of estimated new infectious tension package workers. tuberculosis cases detected under DOTS, the Total health expenditure is the sum of public internationally recommended tuberculosis and private health expenditure. It covers the control strategy. provision of health services (preventive and Tuberculosis treatment success rate is the curative), family planning activities, nutri- percentage of new smear-positive tubercu- tion activities, and emergency aid designated losis cases registered under DOTS in a given for health but does not include provision of year that successfully completed treatment, water and sanitation. 178 Africa Development Indicators 2010 Public health expenditure consists of recur- under DOTS, tuberculosis treatment success rent and capital spending from government rate, and children receiving antimalarial drugs (central and local) budgets, external borrow- are from World Bank staff estimates based on ings and grants (including donations from various sources, including census reports, the international agencies and nongovernmental United Nations Population Division's World organizations), and social (or compulsory) Population Prospects, national statistical offic- health insurance funds. es, household surveys conducted by national Private health expenditure includes direct agencies and Macro International, the World household (out-of-pocket) spending, private Health Organization (WHO), and the United insurance, charitable donations, and direct Nations Children's Fund. Data on clinical service payments by private corporations. malaria cases reported and reported malaria External resources for health are funds or deaths are from WHO's World Malaria Report services in kind that are provided by entities 2009. Data on physicians, nurses, and com- not part of the country in question. The re- munity health workers are from the WHO, Or- sources may come from international orga- ganisation for Economic Co-operation and De- nizations, other countries through bilateral velopment, and TransMONEE, supplemented arrangements, or foreign nongovernmental by country data. Data on access to water and organizations. These resources are part of to- sanitation are from the WHO and United Na- tal health expenditure. tions Children's Fund, Progress on Drinking Out-of-pocket expenditure is any direct out- Water and Sanitation (2008). Data on health lay by households, including gratuities and expenditure are from the WHO's World Health in-kind payments, to health practitioners and Report and updates and from the Organisation suppliers of pharmaceuticals, therapeutic ap- for Economic Co-operation and Development pliances, and other goods and services whose for its member countries, supplemented by primary intent is to contribute to the restora- World Bank poverty assessments and coun- tion or enhancement of the health status of try and sector studies, and household surveys individuals or population groups. It is a part conducted by governments or by statistical or of private health expenditure. international organizations. Private prepaid plans are expenditure on health by private insurance institutions. Pri- 8. Agriculture, rural development, and vate insurance enrolment may be contractual environment or voluntary, and conditions and benefits or basket of benefits are agreed on a voluntary Table .. Rural development basis between the insurance agent and the Rural population is the difference between the beneficiaries. They are thus not controlled by total population and the urban population. government units for the purpose of provid- Rural population density is the rural popula- ing social benefits to members. tion divided by the arable land area. Arable Health expenditure per capita is the total land includes land defined by the Food and health expenditure. It is the sum of public Agriculture Organization (FAO) as land un- and private health expenditures as a ratio der temporary crops (double-cropped areas of total population. It covers the provision are counted once), temporary meadows for of health services (preventive and curative), mowing or for pasture, land under market or family planning activities, nutrition activi- kitchen gardens, and land temporarily fallow. ties, and emergency aid designated for health Land abandoned as a result of shifting culti- but does not include provision of water and vation is excluded. sanitation. Data are in current U.S. dollars. Share of rural population below the national poverty line is the percentage of the rural popu- Source: Data on life expectancy at birth, un- lation living below the national poverty line. der-five mortality, infant mortality, maternal Rural population poverty gap is the mean mortality, prevalence of HIV, incidence of tu- shortfall from the poverty line (counting the berculosis, child immunization, malnutrition, nonpoor as having zero shortfall), expressed births attended by skilled health staff, contra- as a percentage of the poverty line. This mea- ceptive use, children sleeping under insecti- sure reflects the depth of poverty as well as cide-treated nets, tuberculosis cases detected its incidence. Technical notes 179 Share of rural population with sustainable ac- (International Standard Industrial Classifi- cess to an improved water source is the percent- cation [ISIC] revision 3 divisions 1­5) less age of the rural population with reasonable the value of their intermediate inputs. It is access to an adequate amount of water from calculated without making deductions for an improved source, such as a household depreciation of fabricated assets or depletion connection, public standpipe, borehole, pro- and degradation of natural resources. For tected well or spring, or rainwater collection. countries that report that report national Unimproved sources include vendors, tanker accounts data at producer prices (Benin, the trucks, and unprotected wells and springs. Republic of Congo, Côte d'Ivoire, Gabon, Reasonable access is defined as the availabil- Ghana, Niger, Rwanda, Tanzania, Togo, and ity of at least 20 liters a person a day from a Tunisia), gross value added at market prices source within one kilometer of the dwelling. is used as the denominator. For countries Share of rural population with sustainable ac- that report national accounts data at basic cess to improved sanitation facilities is the per- prices (all other countries), gross value added centage of the rural population with at least at factor cost is used as the denominator. adequate access to excreta disposal facilities Total agriculture gross production index is that can effectively prevent human, animal, total agricultural production relative to the and insect contact with excreta. Improved base period 1999­2001. facilities range from simple but protected Crop gross production index is agricultural pit latrines to flush toilets with a sewerage crop production relative to the base period connection. The excreta disposal system is 1999­2001. It includes all crops except fod- considered adequate if it is private or shared der crops. (but not public) and if it hygienically sepa- Livestock gross production index covers meat rates human excreta from human contact. To and milk from all sources, dairy products be effective, facilities must be correctly con- such as cheese, and eggs, honey, raw silk, structed and properly maintained. wool, and hides and skins. Share of rural population with access to trans- Food gross production index covers food portation is the percentage of the rural popu- crops that are considered edible and that con- lation who live within two kilometers of an tain nutrients. Coffee and tea are excluded all-season passable road as a share of the to- because, although edible, they have no nutri- tal rural population. tive value. Cereal gross production index covers cereals Source: Data on rural population are calcu- that are considered edible and that contain lated from urban population shares from the nutrients. United Nations Population Division's World Cereal production is crops harvested for dry Urbanization Prospects and from total popu- grain only. Cereal crops harvested for hay or lation figures from the World Bank. Data on harvested green for food, feed, or silage and rural population density are from the FAO and those used for grazing are excluded. World Bank population estimates. Data on ru- Cereal includes wheat, rice, maize, barley, ral population below the poverty line and rural oats, rye, millet, sorghum, buckwheat, and population poverty gap are national estimates mixed grains. based on population-weighted subgroup esti- Agricultural exports and imports are ex- mates from household surveys. Data on access pressed in current U.S. dollars at free on to water and sanitation are from the World board prices. The term agriculture in trade Health Organization and United Nations Chil- refers to both food and agriculture and does dren's Fund's Progress on Water and Sanitation not include forestry and fishery products. (2008). Data on rural population with access Food exports and imports are expressed in to transport are from the World Bank's Sub current U.S. dollars at free on board prices -Saharan Africa Transport Policy Program. for exports and cost, insurance, and freight prices for imports. Table .. Agriculture Permanent cropland is land cultivated with Agriculture value added is the gross output crops that occupy the land for long periods of forestry, hunting, and fishing, as well as and need not be replanted after each harvest, cultivation of crops and livestock production such as cocoa, coffee, and rubber. It includes 180 Africa Development Indicators 2010 land under flowering shrubs, fruit trees, nut cereal exports and imports, agricultural ex- trees, and vines, but excludes land under ports and imports, permanent cropland, trees grown for wood or timber. cereal cropland, and agricultural machinery Cereal cropland refers to harvested area, al- are from the FAO. Data on irrigated land are though some countries report only sown or from the FAO's Production Yearbook and cultivated area. data files. Data on fertilizer consumption are Irrigated land is areas equipped to provide from the FAO database for the Fertilizer Year- water to the crops, including areas equipped book. Data on agricultural employment are for full and partial control irrigation, spate from the International Labour Organization. irrigation areas, and equipped wetland or in- Data on agriculture value added per worker land valley bottoms. are from World Bank national accounts files Fertilizer consumption is the aggregate of ni- and the FAO's Production Yearbook and data trogenous, phosphate, and potash fertilizers. files. Agricultural machinery refers to the num- ber of wheel and crawler tractors (excluding Table .. Environment garden tractors) in use in agriculture at the Forest area is land under natural or planted end of the calendar year specified or during stands of trees, whether productive or not. the first quarter of the following year. Arable Renewable internal fresh water resources re- land includes land defined by the Food and fer to internal renewable resources (internal Agriculture Organization (FAO) as land un- river flows and groundwater from rainfall) in der temporary crops (double-cropped areas the country. are counted once), temporary meadows for Annual fresh water withdrawals refer to to- mowing or for pasture, land under market or tal water withdrawals, not counting evapora- kitchen gardens, and land temporarily fallow. tion losses from storage basins. Withdrawals Land abandoned as a result of shifting culti- also include water from desalination plants in vation is excluded. countries where they are a significant source. Agricultural employment includes people Withdrawals can exceed 100 percent of total who work for a public or private employer renewable resources where extraction from and who receive remuneration in wages, sal- nonrenewable aquifers or desalination plants ary, commission, tips, piece rates, or pay in is considerable or where there is significant kind. Agriculture corresponds to division 1 water reuse. Withdrawals for agriculture and (International Standard Industrial Classifica- industry are total withdrawals for irrigation tion, ISIC, revision 2) or tabulation categories and livestock production and for direct in- A and B (ISIC revision 3) and includes hunt- dustrial use (including withdrawals for cool- ing, forestry, and fishing. ing thermoelectric plants). Withdrawals for Agriculture value added per worker is the domestic uses include drinking water, munic- output of the agricultural sector (ISIC divi- ipal use or supply, and use for public services, sions 1­5) less the value of intermediate commercial establishments, and homes. inputs. Agriculture comprises value added Water productivity is calculated as gross do- from forestry, hunting, and fishing as well as mestic product in constant prices divided by cultivation of crops and livestock production. annual total water withdrawal. Sectoral wa- Data are in constant 2000 U.S. dollars. ter productivity is calculated as annual value Cereal yield is dry grain only and includes added in agriculture or industry divided by wheat, rice, maize, barley, oats, rye, millet, water withdrawal in each sector. sorghum, buckwheat, and mixed grains. Pro- Emissions of organic water pollutants are duction data on cereals relate to crops har- measured in terms of biochemical oxygen de- vested for dry grain only. Cereal crops har- mand, which refers to the amount of oxygen vested for hay or harvested green for food, that bacteria in water will consume in break- feed, or silage and those used for grazing are ing down waste. This is a standard water- excluded. treatment test for the presence of organic pollutants. Source: Data on agriculture value added Energy production refers to forms of pri- are from World Bank country desks. Data on mary energy--petroleum (crude oil, natural crop, livestock, food, and cereal production, gas liquids, and oil from nonconventional Technical notes 181 sources), natural gas, solid fuels (coal, lignite, and other donors. Disbursements record the and other derived fuels), and combustible re- actual international transfer of financial re- newables and waste--and primary electric- sources or of goods or services valued at the ity, all converted into oil equivalents. cost of the donor. Energy use refers to use of primary energy before transformation to other end-use fuels, Source: Data on forest area and deforestation which is equal to indigenous production plus are from the Food and Agriculture Organiza- imports and stock changes, minus exports tion's (FAO) Global Forest Resources Assessment. and fuels supplied to ships and aircraft en- Data on freshwater resources and withdraw- gaged in international transport. als are from the World Resources Institute, Combustible renewables and waste comprise supplemented by the FAO's AQUASTAT data. solid biomass, liquid biomass, biogas, indus- Data on emissions of organic water pollutants trial waste, and municipal waste, measured are from the World Bank. Data on energy pro- as a percentage of total energy use. duction and use and combustible renewables Carbon dioxide emissions are those stem- and waste are from the International Energy ming from the burning of fossil fuels and the Agency. Data on carbon dioxide emissions are manufacture of cement. They include carbon from Carbon Dioxide Information Analysis dioxide produced during consumption of sol- Center, Environmental Sciences Division, Oak id, liquid, and gas fuels and gas flaring. Ridge National Laboratory, in the U.S. state of Methane emissions, total, are those from hu- Tennessee. Data on methane emissions, ni- man activities such as agriculture and from trous oxide emissions, and other greenhouse industrial methane production. gas emissions are from the International Ener- Methane emissions, agricultural, are those gy Agency. Data on official development assis- from animals, animal waste, rice production, tance disbursements are from the Organisation agricultural waste burning (nonenergy, on- for Economic Co-operation and Development. site), and savannah burning. Methane emissions, industrial, are those Table .. Fossil fuel emissions from the handling, transmission, and com- Carbon dioxide emissions are those stemming bustion of fossil fuels and biofuels. from the burning of fossil fuels and the man- Nitrous oxide emissions, total, are those ufacture of cement. They include carbon di- from agricultural biomass burning, industrial oxide produced during consumption of solid, activities, and livestock management liquid, and gas fuels and gas flaring. Nitrous oxide emissions, agricultural, are Carbon dioxide emissions per capita are car- those produced through fertilizer use (syn- bon dioxide emissions divided by midyear thetic and animal manure), animal waste population. management, agricultural waste burning Fossil fuel is any hydrocarbon deposit that (nonenergy, on-site), and savannah burning. can be burned for heat or power, such as pe- Nitrous oxide emissions, industrial, are those troleum, coal, and natural gas. produced during the manufacturing of adipic Total carbon dioxide emissions from fossil fu- acid and nitric acid. els is the sum of all fossil fuel emissions (solid Other greenhouse gas emissions are by-prod- fuel consumption, liquid fuel consumption, uct emissions of hydrofluorocarbons, per- gas fuel consumption, gas flaring, and ce- fluorocarbons, and sulfur hexafluoride. ment production). Official development assistance (ODA) gross Carbon dioxide emissions from solid fuel con- disbursements for forestry are disbursements sumption refer mainly to emissions from use for forestry by bilateral, multilateral, and oth- of coal as an energy source and from second- er donors. Disbursements record the actual ary fuels derived from hard and soft coal international transfer of financial resources (such as coke-oven coke). or of goods or services valued at the cost of Carbon dioxide emissions from liquid fuel con- the donor. sumption refer to emissions from use of crude Official development assistance (ODA) gross petroleum and natural gas liquids as an ener- disbursements for general environment protec- gy source, and secondary fuels derived from tion are disbursements for general environ- oil (such as jet fuel). ment protection by bilateral, multilateral, 182 Africa Development Indicators 2010 Carbon dioxide emissions from gas fuel con- quarrying (including oil production), manu- sumption refer mainly to emissions from use facturing, construction, and public utilities of natural gas as an energy source and from (electricity, gas, and water). secondary fuels derived from natural gas Services correspond to divisions 6­9 (ISIC (such as blast furnace gas). revision 2) or tabulation categories G­P (ISIC Carbon dioxide emissions from gas flaring revision 3) and include wholesale and retail refer mainly to emissions from gas flaring trade and restaurants and hotels; transport, activities. storage, and communications; financing, Carbon dioxide emissions from cement produc- insurance, real estate, and business ser- tion refer mainly to emissions during cement vices; and community, social, and personal production. Cement production is a multi- services. step process, and carbon dioxide is actually Wage and salaried workers are workers who released from klinker production during the hold the type of jobs defined as paid employ- cement production process. ment jobs, where incumbents hold explicit (written or oral) or implicit employment con- Source: Data on carbon dioxide emissions tracts that give them a basic remuneration are from Carbon Dioxide Information Analy- that is not directly dependent on the revenue sis Center, Environmental Sciences Division, of the unit for which they work. Oak Ridge National Laboratory, in the U.S. Self-employed workers are self-employed state of Tennessee. workers with employees (employers), self-em- ployed workers with without employees (own- 9. Labor, migration, and population account workers), and members of producer cooperatives. Although the contributing fam- Table .. Labor force participation ily workers category is technically part of the Labor force is people ages 15 and older who self-employed according to the classification meet the International Labour Organization used by the International Labour Organiza- (ILO) definition of the economically active tion (ILO), and could therefore be combined population. It includes both the employed with the other self-employed categories to de- and the unemployed. While national prac- rive the total self-employed, they are reported tices vary in the treatment of such groups as here as a separate category in order to empha- the armed forces and seasonal or part-time size the difference between the two statuses, workers, the labor force generally includes since the socioeconomic implications associ- the armed forces, the unemployed, and first- ated with each status can be significantly var- time job seekers, but excludes homemakers ied. This practice follows that of the ILO's Key and other unpaid caregivers and workers in Indicators of the Labour Market. the informal sector. Contributing family workers (unpaid work- Participation rate is the percentage of the ers) are workers who hold self-employment population of the specified age group that is jobs as own-account workers in a market- economically active, that is, all people who oriented establishment operated by a related supply labor for the production of goods and person living in the same household. services during a specified period. Source: International Labour Organiza- Source: ILO's Estimates and Projections of tion, Key Indicators of the Labour Market the Economically Active Population database.. database. Table .. Labor force composition Table .. Unemployment Agriculture corresponds to division 1 (Inter- Unemployment is the share of the labor force national Standard Industrial Classification, of the specified subgroup without work but ISIC, revision 2) or tabulation categories A available for and seeking employment. and B (ISIC revision 3) and includes hunting, Primary education provides children with forestry, and fishing. basic reading, writing, and mathematics skills Industry corresponds to divisions 2­5 along with an elementary understanding of (ISIC revision 2) or tabulation categories C­F such subjects as history, geography, natural (ISIC revision 3) and includes mining and science, social science, art, and music. Technical notes 183 Secondary education completes the provi- Rural population is calculated as the differ- sion of basic education that began at the pri- ence between the total population and the mary level and aims to lay the foundations urban population. for lifelong learning and human development Urban population is midyear population of by offering more subject- or skill-oriented in- areas defined as urban in each country. struction using more specialized teachers. Tertiary education, whether or not at an Source: Data on migration and population advanced research qualification, normally are from the World Bank's World Develop- requires, as a minimum condition of admis- ment Indicators database. Data on workers sion, the successful completion of education remittances and migrant remittance flows at the secondary level. are from World Bank staff estimates based on the International Monetary Fund's Balance of Source: International Labour Organiza- Payments Statistics Yearbook 2008. tion, Key Indicators of the Labour Market database. 10. HIV/AIDS Table .. Migration and population Table .. HIV/AIDS Migrant stock is the number of people born in Estimated number of people living with HIV/ a country other than that in which they live. AIDS is the number of people in the relevant It includes refugees. age group living with HIV. Net migration is the net average annual Estimated HIV prevalence rate is the percent- number of migrants during the period, that age of the population of the relevant age sub- is, the annual number of immigrants less the group who are infected with HIV. Depending annual number of emigrants, including both on the reliability of the data available, there citizens and noncitizens. Data are five-year may be more or less uncertainty surrounding estimates. each estimate. Therefore, plausible bounds Workers remittances, received, comprise cur- have been presented for each subgroup rate rent transfers by migrant workers and wages (low and high estimate). and salaries by nonresident workers. Deaths of adults and children due to HIV/AIDS Migrant remittance flows are the sum of are the estimated number of adults and chil- worker's remittances, compensation of em- dren that have died in a specific year based on ployees, and migrants' transfers, as recorded the modeling of HIV surveillance data using in the International Monetary Fund's Balance standard and appropriate tools. of Payments. AIDS orphans are the estimated number of Population is total population based on children who have lost their mother or both the de facto definition of population, which parents to AIDS before age 17 since the epi- counts all residents regardless of legal status demic began in 1990. Some of the orphaned or citizenship, except for refugees not perma- children included in this cumulative total are nently settled in the country of asylum, who no longer alive; others are no longer under are generally considered part of the popula- age 17. tion of their country of origin. The values HIV-positive pregnant women receiving anti- shown are midyear estimates. retrovirals to reduce the risk of mother-to-child Fertility rate is the number of children that transmission are the number of pregnant would be born to a woman if she were to live women infected with HIV who received anti- to the end of her childbearing years and bear retrovirals during the last 12 months to reduce children in accordance with current age-spe- the risk of mother-to-child transmission. cific fertility rates. Share of HIV-positive pregnant women receiv- Age composition refers to the percentage ing antiretrovirals, World Health Organization/ of the total population that is in specific age Joint United Nations Programme on HIV/AIDS groups. (WHO/UNAIDS) methodology, is the percent- Dependency ratio is the ratio of dependents- age of pregnant women infected with HIV --people younger than 15 or older than who received antiretrovirals to reduce the 64--to the working-age population--those risk of mother-to-child transmission divided ages 15­64. by the total number of infected pregnant 184 Africa Development Indicators 2010 women infected with HIV in the last 12 unconfirmed cases (cases that were not test- months. The WHO/UNAIDS methodology ed but treated as malaria). National malaria may differ from country methodologies. control programs often collect data on the Official development assistance (ODA) gross number of suspected cases, those tested, and disbursements for social mitigation of HIV/AIDS those confirmed. Probable or unconfirmed are spending on special programs to address cases are calculated by subtracting the num- the consequences of HIV/AIDS, such as so- ber tested from the number suspected. Not cial, legal, and economic assistance to people all cases reported as malaria are true malaria living with HIV/AIDS (including food secu- cases; most health facilities lack appropriate rity and employment); spending on support diagnostic services. The misdiagnosis may to vulnerable groups and children orphaned have led to under- or overreporting malaria by HIV/AIDS; and spending on human rights cases and missing diagnosis of other treat- advocacy for people affected by HIV/AIDS. able diseases. Official development assistance (ODA) gross Reported malaria deaths are all deaths in disbursements for sexually transmitted dis- health facilities that are attributed to malar- eases (STDs) control, including HIV/AIDS, are ia, whether or not confirmed by microscopy spending on all activities related to STDs and or by rapid diagnostic test. HIV/AIDS control, such as information, edu- Under-five mortality rate is the probability cation, and communication; testing; preven- that a newborn baby will die before reaching tion; and treatment care. age 5, if subject to current age-specific mor- tality rates. The probability is expressed as a Source: Data on number of people living rate per 1,000. with HIV/AIDS, HIV prevalence rate, deaths Children sleeping under insecticide-treated due to HIV/AIDS, AIDS orphans, and HIV- nets is the percentage of children under age positive pregnant women receiving antiret- 5 with access to an insecticide-treated net to rovirals are from UNAIDS and WHO's Report prevent malaria. on the Global AIDS Epidemic. A more detailed Children with fever receiving any antimalarial explanation of methods and assumptions can treatment same or next day are the percentage be found on the UNAIDS reference group on of children under age 5 in malaria-risk areas estimates, modeling, and projections website with fever being treated with any antimalarial (www.unaids.org/en/KnowledgeCentre/HIV- drugs. Data/Epidemiology/) and in a series of papers Children with fever receiving any antimalarial published in Sexually Transmitted Infections, treatment any time are the percentage of chil- "Improved Methods and Tools for HIV/AIDS dren under age 5 in malaria-risk areas with Estimates and Projections," 2008, 84(Sup- fever being treated with any antimalarial pl I), 2006, 82(Suppl III), and 2004, 80(Sup- drugs. pl I). Data on official development assistance Pregnant women receiving two doses of inter- disbursements are from the Organisation for mittent preventive treatment are the number Economic Co-operation and Development. of pregnant women who receive at least two preventive treatment doses of an effective 11. Malaria antimalarial drug during routine antenatal clinic visits. This approach has been shown to Table .. Malaria be safe, inexpensive, and effective. Population is total population based on the de facto definition of population, which counts Source: Data on population are from the all residents regardless of legal status or citi- World Bank's World Development Indica- zenship, except for refugees not permanent- tors database. Data on clinical cases of ma- ly settled in the country of asylum, who are laria reported and reported malaria deaths generally considered part of the population are from the World Health Organization's of their country of origin. The values shown (WHO) World Malaria Report 2009. Data on are midyear estimates. children with fever receiving antimalarial Clinical malaria cases reported are the sum drugs, and pregnant women receiving two of cases confirmed by slide examination doses of intermittent preventive treatment or rapid diagnostic test and probable and are from Demographic Health Surveys, Technical notes 185 Multiple Indicator Cluster Surveys, and na- OECD's non-DAC donors, which include the tional statistical offices. Data on deaths due Czech Republic, Hungary, Iceland, Israel, the to malaria are from the United Nations Sta- Republic of Korea, Kuwait, Poland, Saudi tistics Division based on WHO estimates. Arabia, the Slovak Republic, Taiwan (China), Data on under-five mortality are harmo- Thailand, Turkey, the United Arab Emirates, nized estimates of the WHO, United Nations and other donors. Children's Fund, and the World Bank, based Net official development assistance (ODA) mainly on household surveys, censuses, and from multilateral donors is net ODA from mul- vital registration, supplemented by World tilateral sources, such as the African Devel- Bank estimates based on household surveys opment Fund, the European Development and vital registration. Data on insecticide- Fund for the Commission of the European treated bednet use are from Demographic Communities, the International Develop- and Health Surveys and Multiple Indicator ment Association, the International Fund for Cluster Surveys. Agricultural Development, Arab and OPEC financed multilateral agencies, and UN pro- 12. Capable states and partnership grams and agencies. Aid flows from the Inter- national Monetary Fund's (IMF) Trust Fund Table .. Aid and debt relief and Structural Adjustment Facility are also Official development assistance is flows to de- included. UN programs and agencies include veloping countries and multilateral institu- the United Nations Technical Assistance Pro- tions provided by official agencies, including gramme, the United Nations Development state and local governments, or by their ex- Programme, the United Nations Office of the ecutive agencies, that are administered with High Commissioner for Refugees, the United the promotion of the economic development Nations Children's Fund, and the World Food and welfare of developing countries as their Programme. Arab and OPEC financed mul- main objective and that are concessional in tilateral agencies include the Arab Bank for character and convey a grant element of at Economic Development in Africa, the Arab least 25 percent. Fund for Economic and Social Development, Net official development assistance (ODA) the Islamic Development Bank, the OPEC from all donors is net ODA from the Organi- Fund for International Development, the sation for Economic Co-operation and Devel- Arab Authority for Agricultural Investment opment's (OECD), Development Assistance and Development, the Arab Fund for Techni- Committee (DAC), non-DAC bilateral (Or- cal Assistance to African and Arab Countries, ganization of Petroleum Exporting Coun- and the Islamic Solidarity Fund. tries [OPEC], the former Council for Mutual Net private official development assistance Economic Assistance [CMEA] countries, and (ODA) is private ODA transactions broken, China [OECD data]), and multilateral do- which comprise direct investment, portfolio nors. OPEC countries are Algeria, Iran, Iraq, investment, and export credits (net). Private Kuwait, Libya, Nigeria, Qatar, Saudi Arabia, transactions are undertaken by firms and in- the United Arab Emirates, and Venezuela. dividuals resident in the reporting country. The former CMEA countries are Bulgaria, Portfolio investment corresponds to bonds Czechoslovakia, the former German Demo- and equities. Inflows into emerging countries' cratic Republic, Hungary, Poland, Romania, stocks markets, are, however, heavily under- and the former Soviet Union). stated. Accordingly, the coverage of portfolio Net official development assistance (ODA) investment differs in these regards from the from DAC donors is net ODA from OECD's coverage of bank claims, which include ex- DAC donors, which include Australia, Austria, port credit lending by banks. The bank claims Belgium, Canada, Denmark, Finland, France, data represent the net change in bank claims Germany, Greece, Ireland, Italy, Japan, Lux- after adjusting for exchange rate changes and embourg, the Netherlands, New Zealand, Nor- are therefore a proxy for net flow data but are way, Portugal, Spain, Sweden, Switzerland, the not themselves a net flow figure. They dif- United Kingdom, and the United States. fer in two further regards from other OECD Net official development assistance (ODA) data. First, they relate to loans by banks resi- from non-DAC donors is net ODA from dent in countries that report quarterly to the 186 Africa Development Indicators 2010 Bank for International Settlements. Second, aid refer to quantities of commodities that no adjustment has been made to exclude actually reached the recipient country during short-term claims. a given period. For cereals the period refers Net official development assistance (ODA) as to July­June, beginning in the year shown. a share of gross domestic product (GDP) is calcu- Heavily Indebted Poor Countries (HIPC) Debt lated by dividing the nominal total net ODA Initiative decision point is the date at which a from all donors by nominal GDP. For a given HIPC with an established track record of level of aid flows, devaluation of a recipi- good performance under adjustment pro- ent's currency may inflate the ratios shown grams supported by the International Mon- in the table. Thus, trends for a given country etary Fund and the World Bank commits to and comparisons across countries that have undertake additional reforms and to develop implemented different exchange rate policies and implement a poverty reduction strategy. should be interpreted carefully. HIPC Debt Initiative completion point is the Net official development assistance (ODA) per date at which the country successfully com- capita is calculated by dividing the nominal pletes the key structural reforms agreed on at total net ODA (net disbursements of loans the decision point, including developing and and grants from all official sources on con- implementing its poverty reduction strategy. cessional financial terms) by midyear popu- The country then receives the bulk of debt lation. These ratios offer some indication of relief under the HIPC Initiative without fur- the importance of aid flows in sustaining per ther policy conditions. capita income and consumption levels, al- Debt service relief committed is the amount though exchange rate fluctuations, the actual of debt service relief, calculated at the de- rise of aid flows, and other factors vary across cision point, that will allow the country to countries and over time. achieve debt sustainability at the comple- Net official development assistance (ODA) as tion point. a share of gross capital formation is calculated by dividing the nominal total net ODA by Source: Data on net official development gross capital formation. These data highlight assistance are from the Organisation for Eco- the relative importance of the indicated aid nomic Co-operation and Development. Data flows in maintaining and increasing invest- on food aid shipments are based on data ment in these economies. The same caveats compiled by from the Food and Agriculture mentioned above apply to their interpreta- Organization based on information from the tion. Furthermore, aid flows do not exclusive- World Food Programme. ly finance investment (for example, food aid finances consumption), and the share of aid Table .. Status of Paris Declaration going to investment varies across countries. indicators Net official development assistance (ODA) as The Paris Declaration is the outcome of the a share of imports of goods and services is calcu- 2005 Paris High-Level Forum on Aid Ef- lated by dividing nominal total net ODA by fectiveness, where 60 partner countries, imports of goods and services. 30 donor countries, and 30 development Net official development assistance (ODA) as agencies committed to specific actions to a share of central government expenditure is cal- further country ownership, harmonization, culated by dividing nominal total net ODA by alignment, managing for development re- central government expenditure. sults, and mutual accountability for the use Cereal food aid shipments are transfers of of aid. Participants agreed on 12 indicators. food commodities (food aid received) from These indicators include good national de- donor to recipient countries on a total-grant velopment strategies, reliable country sys- basis or on highly concessional terms. Pro- tems for procurement and public financial cessed and blended cereals are converted into management, the development and use of their grain equivalent by applying the conver- results frameworks, and mutual assessment sion factors included in the Rule of Proce- of progress. Qualitative desk reviews by the dures under the 1999 Food Aid Convention Organisation for Economic Co-operation to facilitate comparisons between deliveries and Development's Development Assistance of different commodities. Deliveries of food Committee and the World Bank and a survey Technical notes 187 questionnaire for governments and donors support of capacity development aligns with are used to calculate the indicators. countries' development objectives and strat- PDI-1 Operational national development egies), and harmonization (when more than strategies are the extent to which a country one donor is involved in supporting partner- has an operational development strategy to led capacity development, donors coordinate guide its aid coordination effort and overall their activities and contributions). development. The score is based on the World PDI-5a and 5b Aid for government sectors Bank's 2005 Comprehensive Development uses country public financial management and Framework Progress Report. An operational procurement systems is the percentage of do- strategy calls for a coherent long-term strat- nors that use country, rather than donor, sys- egy derived from it; specific targets serving a tems for managing aid disbursement. holistic, balanced, and well sequenced devel- PDI-6 Project implementation units parallel opment strategy; and capacity and resources to country structures is the number of parallel for its implementation. project implementation units, which refers to PDI-2a Reliable public financial management units created outside existing country insti- is the World Bank's annual Country Policy tutional structures. The survey guidance dis- and Institutional Assessment rating for the tinguishes between project implementation quality of public financial management. Mea- units and executing agencies and describes sured on a scale of 1 (worst) to 5 (best), its three typical features of parallel project im- focus is on how much existing systems ad- plementation units: they are accountable here to broadly accepted good practices and to external funding agencies rather than to whether a reform program is in place to pro- country implementing agencies (ministries, mote improved practices. departments, agencies, and the like), most of PDI-2b Reliable country procurement systems the professional staff is appointed by the do- measure developing countries' procurement nor, and the personnel salaries often exceed systems. Donors use national procurement those of civil service personnel. Interpreta- procedures when the funds they provide tion of the Paris Declaration survey question for the implementation of projects and pro- on this subject was controversial in a num- grams are managed according to the national ber of countries. It is unclear whether within procurement procedures as they were estab- countries all donors applied the same criteria lished in the general legislation and imple- with the same degree of rigor or that across mented by government. The use of national countries the same standards were used. In procurement procedures means that donors several cases the descriptive part of the sur- do not make additional, or special, require- vey results indicates that some donors ap- ments on governments for the procurement plied a legalistic criterion of accountability of works, goods, and services. (Where weak- to the formal executing agency, whereas the nesses in national procurement systems national coordinator and other donors would have been identified, donors may work with have preferred greater recognition of the partner countries to improve the efficiency, substantive reality of accountability to the economy, and transparency of their imple- donor. Some respondents may have confused mentation). The objective of this indicator is the definitional question (Is the unit "paral- to measure and encourage improvements in lel"?) with the aid management question (Is developing countries' procurement systems. the parallelism justified in terms of the devel- PDI-3 Government budget estimates compre- opmental benefits and costs?). hensive and realistic are the percentage of aid PDI-7 Aid disbursements on schedule and that is accurately recorded in the national bud- recorded by government are the percentage of get, thereby allowing scrutiny by parliaments. funds that are disbursed within the year they PDI-4 Technical assistance aligned and coordi- are scheduled and accurately recorded by nated with country programs is the percentage partner authorities. of technical cooperation that is free standing PDI-8 Bilateral aid that is untied is the per- and embedded and that respects ownership centage of aid that is untied. Tied aid is aid (partner countries exercise effective leader- provided on the condition that the recipient ship over their capacity development pro- uses it to purchase goods and services from grams), alignment (technical cooperation in suppliers based in the donor country. 188 Africa Development Indicators 2010 PDI-9 Aid provided in the framework of when both donors and partner governments program-based approaches is the percentage are accountable to their constituents for the of development cooperation that is based on use of resources to achieve development re- the principles of coordinated support for a sults and when they are accountable to each locally owned program of development, such other. The specific focus is mutual account- as a national development strategy, a sector ability for the implementation of the part- program, a thematic program or a program nership commitments included in the Paris of a specific organization. Program-based ap- Declaration and any local agreements on en- proaches share the following features: leader- hancing aid effectiveness. ship by the host country or organization, a single comprehensive program and budget Source: 2008 Survey on Monitoring the Paris framework, a formalized process for donor Declaration: Making Aid More Effective by coordination and harmonization of donor 2010. procedures for reporting, budgeting, financial management, and procurement, and efforts Table .. Capable states to increase the use of local systems for pro- Firms that believe the court system is fair, impar- gram design and implementation, financial tial, and uncorrupt are the percentage of firms management, monitoring, and evaluation. that believe the court system is fair, impar- PDI-10a Donor missions coordinated are the tial, and uncorrupted. percentage of missions undertaken jointly by Corruption is the percentage of firms iden- two or more donors and missions undertaken tifying corruption as a major constraint. by one donor on behalf of another (delegated Crime, theft, and disorder are the percentage cooperation). of firms identifying crime, theft, and disorder PDI-10b Country analysis coordinated is the as a major constraint to current operation. percentage of country analytic work that is Number of procedures to enforce a contract is undertaken by one or more donors jointly, the number of independent actions, mandat- undertaken by one donor on behalf of anoth- ed by law or courts, that demand interaction er donor (including work undertaken by one between the parties of a contract or between and used by another when it is co-financed them and the judge or court officer. and formally acknowledged in official docu- Time required to enforce a contract is the mentation, and undertaken with substantive number of calendar days from the filing of involvement from government. the lawsuit in court until the final determina- PDI-11 Existence of a monitorable performance tion and, in appropriate cases, payment. assessment framework measures the extent to Cost to enforce a contract is court and attor- which the country has realized its commitment ney fees, where the use of attorneys is man- to establishing performance frameworks. The datory or common, or the cost of an adminis- indicator relies on the scorings of the 2005 trative debt recovery procedure, expressed as Comprehensive Development Framework a percentage of the debt value. Progress Report and considers three crite- Protecting investors disclosure index mea- ria: the quality of development information, sures the degree to which investors are pro- stakeholder access to development informa- tected through disclosure of ownership and tion, and coordinated country-level monitor- financial information. Higher values indicate ing and evaluation. The assessments therefore more disclosure. reflect both the extent to which sound data on Director liability index measures a plain- development outputs, outcomes and impacts tiff 's ability to hold directors of firms liable are collected, and various aspects of the way for damages to the company. Higher values information is used, disseminated among indicate greater liability. stakeholders, and fed back into policy. Shareholder suits index measures share- PDI-12 Existence of a mutual accountability holders' ability to sue officers and direc- review indicates whether there is a mechanism tors for misconduct. Higher values indicate for mutual review of progress on aid effec- greater power for shareholders to challenge tiveness commitments. This is an important transactions. innovation of the Paris Declaration because Investor protection index measures the de- it develops the idea that aid is more effective gree to which investors are protected through Technical notes 189 disclosure of ownership and financial infor- workplan. Once a country has become a EITI mation regulations. Higher values indicate candidate, it has two years to be validated as better protection. compliant. Compliant indicates that a coun- Number of tax payments is the number of try has successfully undergone validation, an taxes paid by businesses, including electronic independent assessment of a country's prog- filing. The tax is counted as paid once a year ress toward the EITI goals by the EITI Inter- even if payments are more frequent. national Board. Validation is based on the Time required to prepare, file, and pay taxes country's work plan, the EITI validation grid is the number of hours it takes to prepare, and indicator assessment tools, and company file, and pay (or withhold) three major types forms that detail private companies' extrac- of taxes: the corporate income tax, the tive industry activities; it provides guidance value added or sales tax, and labor taxes, for countries' future activity related to EITI including payroll taxes and social security compliance. Countries must undergo valida- contributions. tion every five years or at the request of the Total tax rate is the total amount of taxes EITI International Board. payable by the business (except for labor taxes) after accounting for deductions and Source: Data on investment climate con- exemptions as a percentage of gross profit. straints to firms are based on enterprise For further details on the method used for surveys conducted by the World Bank and assessing the total tax payable, see the World its partners during 2001­05 (http://rru. Bank's Doing Business 2006. worldbank.org/EnterpriseSurveys). Data on Extractive Industries Transparency Initia- enforcing contracts, protecting investors, and tive (EITI) status refers to a country's imple- regulation and tax administration are from mentation status for the EITI, a multistake- the World Bank's Doing Business project holder approach to increasing governance (http://rru.worldbank.org/DoingBusiness/). and transparency in extractive industries. It Data on corruption perceptions index are includes civil society, the private sector, and from Transparency International (www. government and requires a work plan with transparency.org/policy_research/surveys_ timeline and budget to ensure sustainability, indices/cpi). Data on the EITI are from the independent audit of payments and disclo- EITI website, www.eitransparency.org. sure of revenues, publication of results in a publicly accessible manner, and an approach Table .. Governance and anti- that covers all companies and government corruption indicators agencies. The EITI supports improved gover- Voice and accountability measure the extent nance in resource-rich countries through the to which a country's citizens are able to par- verification and full publication of company ticipate in selecting their government and to payments and government revenues from enjoy freedom of expression, freedom of as- oil, gas, and mining. Intent to implement in- sociation, and a free media. dicates that a country intends to implement Political stability and absence of violence the EITI but have not yet met the four initial measure the perceptions of the likelihood requirements to join: an unequivocal public that the government will be destabilized statement of its intention to implement the or overthrown by unconstitutional or vio- EITI, a commitment to work with civil soci- lent means, including domestic violence or ety and companies on EITI implementation, terrorism. a senior official appointed to lead EITI imple- Government effectiveness measures the mentation, and a widely distributed, fully quality of public services, the quality and costed work plan with measurable targets, a degree of independence from political pres- timetable for implementation, and an assess- sures of the civil service, the quality of policy ment of government, private sector, and civil formulation and implementation, and the society capacity constraints. Candidate indi- credibility of the government's commitment cates that a country has met the four initial to such policies. requirements to join the EITI and has begun Regulatory quality measures the ability of a range of activities to strengthen revenue the government to formulate and implement transparency, as documented in the country's 190 Africa Development Indicators 2010 sound policies and regulations that permit participating countries from every conti- and promote private sector development. nent. In 2008, based on inputs received from Rule of law measures the extent to which researchers and extensive in-house reviews, agents have confidence in and abide by the the International Budget Partnership made rules of society, in particular the quality of three changes in its methodology. The first contract enforcement, the police, and the change concerns the timing of the release of courts, as well as the likelihood of crime and the eight key budget documents assessed by violence. the survey. The second is the inclusion of the Control of corruption measures the extent enacted budget in calculating country scores to which public power is exercised for private for the index. The third is revisions to the an- gain, including petty and grand forms of cor- swers of a few questions used to assess Brazil ruption, as well as "capture" of the state by and Nigeria. elites and private interests. Expected to pay informal payment to public Source: Data on governance indicators are officials to get things done is the percentage of from the World Bank Institute's Worldwide firms that expected to make informal pay- Governance Indicators database, which relies ments or give gifts to public officials to "get on 33 sources, including surveys of enterprises things done" with regard to customs, taxes, and citizens, and expert polls, gathered from licenses, regulations, services, and the like. 30 organizations around the world. Data on Expected to give gifts to obtain an operating corruption perceptions index scores are from license is the percentage of firms that expect- Transparency International (http://www. ed to give gifts or an informal payment to get transparency.org/policy_research/surveys_ an operating license. indices/cpi/2009). Data on the open budget Expected to give gifts in meetings with tax index are from www.openbudgetindex.org. officials is the percentage of firms that an- swered yes to the question "Was a gift or in- Table .. Country Policy and Institu- formal payment expected or requested dur- tional Assessment ratings ing a meeting with tax officials?" The Country Policy and Institutional Assessment Expected to give gifts to secure a government (CPIA) assesses the quality of a country's contract is the percentage of firms that ex- present policy and institutional framework. pected to make informal payments or give "Quality" means how conducive that frame- gifts to public officials to secure a govern- work is to fostering sustainable, poverty- ment contract. reducing growth and the effective use of de- Share of firms identifying control of corrup- velopment assistance. The CPIA is conducted tion as a major constraint measures the extent annually for all International Bank for Re- to which public power is exercised for private construction and Development and Interna- gain, including petty and grand forms of cor- tional Development Association borrowers ruption, as well as "capture" of the state by and has evolved into a set of criteria grouped elites and private interests. into four clusters with 16 criteria that reflect Mean corruption perceptions index score is the a balance between ensuring that all key fac- country's score in Transparency International's tors that foster pro-poor growth and poverty annual corruption perceptions index, which alleviation are captured, without overly bur- ranks more than 150 countries in terms of dening the evaluation process. perceived levels of corruption, as determined · Economic management by expert assessments and opinion surveys. · Macroeconomic management assess- Open budget index overall score is the coun- es the quality of the monetary, ex- try's score on a subset of 91 questions from change rate, and aggregate demand the open budget survey. The questions focus policy framework. on the public availability of eight key bud- · Fiscal policy assesses the short- and get documents (with a particular emphasis medium-term sustainability of on the executive's budget proposal) and the fiscal policy (taking into account information they contain. The open budget monetary and exchange rate policy index is calculated based on detailed ques- and the sustainability of the public tionnaires completed by local experts in 59 debt) and its impact on growth. Technical notes 191 · Debt policy assesses whether the · Equity of public resource use assesses debt management strategy is con- the extent to which the pattern of ducive to minimize budgetary public expenditures and revenue risks and ensure long-term debt collection affects the poor and is sustainability. consistent with national poverty re- · Structural policies duction priorities. The assessment · Trade assesses how the policy of the consistency of government framework fosters trade in goods. spending with the poverty reduc- It covers two areas: trade regime tion priorities takes into account restrictiveness--which focuses on the extent to which individuals, the height of tariffs barriers, the groups, or localities that are poor, extent to which nontariff barri- vulnerable, or have unequal access ers are used, the transparency and to services and opportunities are predictability of the trade regime, identified; a national development and customs and trade facilita- strategy with explicit interventions tion--which includes the extent to to assist those individuals, groups, which the customs service is free of and localities has been adopted; corruption, relies on risk manage- and the composition and incidence ment, processes duty collections of public expenditures are tracked and refunds promptly, and oper- systematically and their results fed ates transparently. back into subsequent resource allo- · Financial sector assesses the struc- cation decisions. The assessment of ture of the financial sector and the the revenue collection dimension policies and regulations that af- takes into account the incidence of fect it. It covers three dimensions: major taxes--for example, whether financial stability; the sector's ef- they are progressive or regressive-- ficiency, depth, and resource mo- and their alignment with the pov- bilization strength; and access to erty reduction priorities. When financial services. relevant, expenditure and revenue · Business regulatory environment as- collection trends at the national sesses the extent to which the legal, and sub-national levels should be regulatory, and policy environment considered. The expenditure com- helps or hinders private business in ponent receives two-thirds of the investing, creating jobs, and becom- weight in computing the overall ing more productive. The emphasis rating. is on direct regulations of business · Building human resources assesses activity and regulation of goods the national policies and public and factor markets. It measures and private sector service delivery three subcomponents: regulations that affect access to and quality of affecting entry, exit, and competi- health and nutrition services, in- tion; regulations of ongoing busi- cluding: population and reproduc- ness operations; and regulations of tive health; education, early child- factor markets (labor and land). hood development, and training · Policies for social inclusion and equity and literacy programs; and preven- · Gender equality assesses the extent tion and treatment of HIV/AIDS, to which the country has enacted tuberculosis, and malaria. and put in place institutions and · Social protection and labor assess programs to enforce laws and poli- government policies in the area of cies that promote equal access for social protection and labor market men and women to human capital regulation, which reduce the risk development, and to productive of becoming poor, assist those who and economic resources and that are poor to better manage further give men and women equal status risks, and ensure a minimal level of and protection under the law. welfare to all people. Interventions 192 Africa Development Indicators 2010 include social safety net programs, and effective arrangements for pension and old age savings pro- follow-up. grams, protection of basic labor · Efficiency of revenue mobilization as- standards, regulations to reduce sesses the overall pattern of reve- segmentation and inequity in la- nue mobilization--not only the tax bor markets, active labor market structure as it exists on paper, but programs (such as public works or revenue from all sources as they are job training), and community driv- actually collected. en initiatives. In interpreting the · Quality of public administration as- guidelines it is important to take sesses the extent to which civilian into account the size of the econo- central government staffs (includ- my and its level of development. ing teachers, health workers, and · Policies and institutions for envi- police) are structured to design ronmental sustainability assess the and implement government policy extent to which environmental and deliver services effectively. Ci- policies foster the protection and vilian central government staffs sustainable use of natural resourc- include the central executive to- es and the management of pollu- gether with all other ministries tion. Assessment of environmental and administrative departments, sustainability requires multidimen- including autonomous agencies. It sional criteria (that is, for air, water, excludes the armed forces, state- waste, conservation management, owned enterprises, and subnation- coastal zones management, and al government. natural resources management). · Transparency, accountability, and cor- · Public sector management and ruption in public sector assess the ex- institutions tent to which the executive branch · Property rights and rule-based gov- can be held accountable for its use of ernance assess the extent to which funds and the results of its actions private economic activity is facili- by the electorate and by the legisla- tated by an effective legal system ture and judiciary, and the extent to and rule-based governance struc- which public employees within the ture in which property and con- executive are required to account for tract rights are reliably respected the use of resources, administrative and enforced. Three dimensions are decisions, and results obtained. Both rated separately: legal basis for se- levels of accountability are enhanced cure property and contract rights; by transparency in decision-making, predictability, transparency, and public audit institutions, access to impartiality of laws and regula- relevant and timely information, tions affecting economic activity, and public and media scrutiny. and their enforcement by the legal and judicial system; and crime and Source: World Bank Group's CPIA database violence as an impediment to eco- (www.worldbank.org/ida). nomic activity. · Quality of budgetary and financial Table .. Polity Indicators management assesses the extent to Combined polity score is computed by sub- which there is a comprehensive and tracting the institutionalized autocracy score credible budget, linked to policy from the institutionalized democracy score; priorities; effective financial man- the resulting unified polity scale ranges from agement systems to ensure that the +10 (strongly democratic) to ­10 (strongly budget is implemented as intended autocratic). in a controlled and predictable way; Institutionalized democracy is conceived as and timely and accurate account- three essential, interdependent elements. ing and fiscal reporting, including One is the presence of institutions and pro- timely and audited public accounts cedures through which citizens can express Technical notes 193 effective preferences about alternative poli- autocracy is used and defined operationally in cies and leaders. Second is the existence of terms of the presence of a distinctive set of institutionalized constraints on the exercise political characteristics. In mature form au- of power by the executive. Third is the guar- tocracies sharply restrict or suppress compet- antee of civil liberties to all citizens in their itive political participation. Their chief execu- daily lives and in acts of political participa- tives are chosen in a regularized process of tion. Other aspects of plural democracy, such selection within the political elite, and once as the rule of law, systems of checks and in office they exercise power with few institu- balances, freedom of the press, and so on tional constraints. Most modern autocracies are means to, or specific manifestations of, also exercise a high degree of directiveness these general principles. Coded data on civil over social and economic activity, but this is liberties are not included. This is an additive regarded here as a function of political ide- eleven-point scale (0­10). The operational in- ology and choice, not a defining property of dicator of democracy is derived from codings autocracy. Social democracies also exercise of the competitiveness of political participa- relatively high degrees of directiveness. tion using some weights. Institutionalized autocracy is a pejorative Source: Data are from the Center for Sys- term for some very diverse kinds of politi- temic Peace's Polity IV Project Political Re- cal systems whose common properties are gime Characteristics and Transitions, 1800­ a lack of regularized political competition 2008 (http://www.systemicpeace.org/inscr/ and concern for political freedoms. The term inscr.htm). 194 Africa Development Indicators 2010 Technical notes references AbouZahr, Carla, and Tessa Wardlaw. 2003. "Maternal Mortality in 2000. Estimates Developed by WHO, UNICEF, and UNFPA." World Health Organization, Geneva. Chen, Shaohua, and Martin Ravallion. 2008. "The Developing World Is Poorer Than We Thought, But No Less Successful in the Fight Against Poverty." Policy Research Working Paper 4703. World Bank, Washington, D.C. Hoekman, Bernard. 2005. "Tentative First Steps: An Assessment of the Uruguay Round Agreement on Services." Paper presented at the World Bank Conference on the Uruguay Round and the Developing Economies, January 26­27, Washington, D.C. ILO (International Labour Organization). Various years. Key Indicators of the Labor Market. Geneva: International Labour Organization. WHO (World Health Organization). 2009. World Malaria Report 2009. Geneva: World Health Organization. World Bank. 2005. Global Economic Prospects 2005: Trade, Regionalism and Development. Washington, D.C.: World Bank. Technical notes references 195 Map of Africa Algiers Tunis Rabat TUNISIA Tripoli MOROCCO Cairo ALGERIA LIBYA ARAB REP. FORMER SPANISH OF EGYPT SAHARA CAPE VERDE MAURITANIA Nouakchott MALI NIGER ERITREA Dakar SENEGAL BURKINA Niamey CHAD Khartoum Asmara THE GAMBIA Banjul Bamako FASO SUDAN Bissau N'Djamena DJIBOUTI GUINEA-BISSAU GUINEA Ouagadougou Djibouti Conakry BENIN NIGERIA Freetown CÔTE TOGO Abuja Addis Ababa SIERRA LEONE D'IVOIRE ETHIOPIA Yamoussoukro GHANA Porto Novo CENTRAL Monrovia AFRICAN REPUBLIC LIBERIA Accra Lomé CAMEROON SOMALIA Bangui Malabo Yaoundé EQUATORIAL GUINEA Mogadishu UGANDA SÃO TOMÉ AND PRÍNCIPE Libreville CONGO Kampala KENYA São Tomé GABON DEM. REP. Nairobi OF RWANDA Kigali Brazzaville CONGO Bujumbura BURUNDI Kinshasa Victoria TANZANIA Luanda Dodoma SEYCHELLES COMOROS ANGOLA MALAWI Moroni Atlantic ZAMBIA Lilongwe Lusaka Ocean Harare MADAGASCAR MOZAMBIQUE ZIMBABWE Antananarivo MAURITIUS Port Louis NAMIBIA BOTSWANA Windhoek Gaborone Pretoria Maputo Mbabane Maseru SWAZILAND SOUTH LESOTHO Indian This map was produced by the Map Design Unit of The World Bank. AFRICA The boundaries, colors, denominations and any other information shown on this map do not imply, on the part of The World Bank Group, any judgment Ocean on the legal status of any territory, or any endorsement or acceptance of such boundaries. Map of Africa 197 Users Guide Africa Development Indicators 2010 CD-ROM Introduction all the troubleshooting steps you need to for defining reusable controls that perform This CD-ROM is part of the Africa resolve the issue. particular functions in Microsoft Windows. Development Indicators suite of products. It If you receive this security alert, please click was produced jointly by the Office of the Chief My Internet Explorer flickers when I try to "Yes" as the links are not a virus or security Economist and the Operational Quality and launch the application on my desktop risk to your computer. Knowledge Services Departments of the Africa You may experience this problem if you are For detailed instructions, refer to the Region in collaboration with the Development using Microsoft Vista. This occurs because on-screen Help menu or tool tips (on-screen Data Group of the Development Economics Internet Explorer 7 and higher versions block explanations of buttons that are displayed Vice Presidency. It uses the latest version of the application when there is an IP address when the cursor rolls over them). the World Bank's DataPlatform version 3.0. in the URL for security reasons. ADI 2010 is The CD-ROM contains about 1,600 a secured application. Please follow these Features and instructions macroeconomic, sectoral, and social directions to resolve this issue: ADI 2010 has two main screens--a text indicators, covering 53 African countries. 1. Go to Tools > Internet Options > Security window featuring the contents of the Africa Time series include data from 1961 to 2008. Tab Development Indicators 2010 book and A few macro indicators have provisional data 2. Select Local Intranet other related tables, and a separate window for 2008, and other indicators have data for 3. Check the Enabled Protected Mode featuring the ADI 2010 time series database. 2008­10. checkbox. The new DataPlatform version 3.0 has Home sophisticated features: enhanced mapping I am getting an Internet Explorer security On the opening text screen you can access and charting, a choice of data selection warning message. Is this a security risk? each element of the ADI 2010 CD-ROM. techniques and versatile display options. We This is not a security risk. ADI 2010 is a Use the browser controls to link to the Africa invite you to explore it. secure application. You can continue working Development Indicators 2010 book, time series if this message appears. To permanently database, and other related information. A note about the data disable this message, please follow these Users should note that the data for the Africa directions: Database Development Indicators suite of products are 1. Go to Tools > Internet Options > Security Select variables drawn from the same database. The general Tab 1. Click on each of the Country, Series, and cutoff date for data is September 30, 2009, 2. Select Local Intranet Year tabs and make your selections on except for data on official development 3. Check the Enabled Protected Mode each screen. There are many ways to assistance, for which the cutoff date is checkbox. make a selection--see below, or use December 8, 2009. the Help menu. A Search option is also I am getting the following message: "MSXML available. Help 5.0 from Microsoft Corporation. If you trust 2. Highlight the items you want. This guide explains how to use the main this website and the add-on and want to allow 3. Click on the Select button to move them functions of the CD-ROM. For details about it to run, click here." into the Selected box. additional features, click Help on the menu This message occurs the first time a web 4. Deselect items at any time by highlighting bar or the Help icon; or call one of the hotline page attempts to execute a higher version of them and clicking on the Remove icon. numbers listed in the Help menu and on the a plug-in in Internet Explorer. This is to alert 5. When selection is complete, click on Next copyright page of this booklet. the user the plug-in has been updated with to move to the next screen. a newer version and prompts this message Installation for user approval. Please right click on the Making selections As is usual for Windows® products, you message and run the plug-in. To permanently · Country: You can select countries and should make sure that other applications are disable this message, please follow these group aggregates from an alphabetical closed while you install the CD-ROM. directions: list, group hierarchies, or by Classification To install the single-user version: 1. Go to Tools > Internet Options > Security (region, income group, or lending 1. Insert the CD-ROM into your CD drive. Tab category). Aggregate data have been The installation window should open 2. Select Local Intranet calculated only when there were adequate automatically. 3. Check the Enabled Protected Mode country data. 2. If the installation window does not open, checkbox. · Series: You can choose from an click on Start, select Run. Type D:\run.bat This change requires Internet Explorer alphabetical list or by topic, or create and follow the instructions. to restart. Please close the existing browser your own custom indicators derived from 3. 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In the printing of the Africa Development Indicators 2010, we took the following measures to reduce our carbon footprint: · We used paper containing 50 percent recycled fiber made from post-consumer waste; each pound of postconsumer recycled fiber that replaces a ton of virgin fiber prevents the release of 2,108 pounds of greenhouse gas emissions and lessens the burden on landfills. · We used paper that is chlorine-free and acid-free. · We printed the Africa Development Indicators 2010 with vegetable-based inks that are made from renewable sources and that are easier to remove in the recycling process. For more information, visit www.greenpressinitiative.org. Saved: · 24 trees · 8 million BTUs of total energy · 2,325 lbs. of CO2 equivalent of greenhouse gases · 11,196 gallons of wastewater · 2,928 lbs. of solid waste 202 Africa Development Indicators 2010 2 0 1 0 Africa Development Indicators 2010 provides the most detailed collection of data on Africa available in one volume. It contains more than 450 macroeconomic, sectoral, and social indicators, covering 53 African countries. Additional data may be found on the companion CD-ROM, covering about 1,600 indicators from 1961 to 2008. Basic indicators National and fiscal accounts External accounts and exchange rates Millennium Development Goals Private sector development Trade and regional integration Infrastructure Human development Agriculture, rural development, and environment Labor, migration, and population HIV/AIDS and malaria Capable states and partnership Paris Declaration indicators Governance and polity Designed to provide all those interested in Africa with quick reference and a reliable set of data to monitor development programs and aid flows in the region, this is an invaluable reference tool for analysts and policy makers who want a better understanding of the economic and social developments occurring in Africa. ISBN 978-0-8213-8202-8 SKU 18202