Pension Patterns and Challenges in Sub-Saharan Africa World Bank Pensions Core Course April 27, 2016

Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Pension Patterns and Challenges in Sub-Saharan Africa World Bank Pensions Core Course April 27, 2016 Mark C. Dorfman Pensions Global Solutions Group The World Bank d

Organization 1. Pension Patterns & Challenges a. Scheme Design b. Enabling conditions: Demographics, household composition, poverty and growth c. Coverage d. Adequacy and affordability e. Sustainability 2. Questions for discussion

Scheme Design 3

Scheme Design 1. National schemes A. Most (32) PAYG DB schemes B. 4 provident funds (Swaziland, Uganda, Kenya, The Gambia) C. 3 DC or Hybrid (Nigeria, Ghana, Malawi) D. 5 No national scheme (South Africa, Namibia, Botswana, South Sudan, Lesotho) 2. Civil Service schemes A. 14 integrated B. 25 separate C. 4 Occupational A. 31 PAYG DB B. 2 FDB (South Africa, Swaziland) C. 5 FDC (Nigeria, Ghana, Malawi, Namibia, Botswana) 3. Social Pensions (9) A. 4 universal B. 2 pensions tested C. 3 means tested

Enabling Conditions: Demographics, Household Composition, Poverty & Growth 5

Old Age Dependency Rates low but growing Projected Old Age Dependency Ratios (Age 65+/age 15-64) Source: World Bank database based on World Population Projections, 2010 revision. Note: Mauritius and Seychelles have not been included.

Total Depdency Rate Demographic window offers a positive environment for reform Total Dependency Ratio Projections (Percent) 120 100 2010 2050 80 60 40 20 0 Source: United Nations, Population Division, Population Projections, 2012 Revision,

Household composition 87% of elderly live with non-elderly 100.0% 90.0% Percent of elderly living in households with non-elderly Median = 86.7% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Source: World Bank ASPIRE database, accessed November 2014.

GDP Growth Growth Projections offer a Positive Environment for Most Recent and Projected Annual Real GDP Growth Rates 15.0% 1995-2009 2010-2014 Projected 2015-2019 12.1% 12.9% 13.2% 10.0% 6.6% 6.8% 6.8% 7.0% 7.1% 7.1% 7.2% 6.2% 6.0% 5.5% 5.7% 5.8% 8.9% 9.0% 9.0% 9.0% 9.3% 7.7% 7.8% 8.1% 8.1% 8.2% 8.2% 8.4% 8.4% 8.4% 8.6% 8.6% 8.7% 11.5%11.5% 10.8% 11.1% 10.5% 9.8% 9.9%10.0%10.0%10.1%10.1% 7.7% 5.6% 7.1% 5.0% 4.3% 4.6% 0.0% -5.0% Source: IMF World Economic Outlook Database, 2015.

GDP Per Capita - US$ - PPP 44.6 43.6 43.4 43.4 43.3 40.6 Poverty Headcount - % of Population ($1.25/day) High poverty levels < $1.25/day & weak correlation with GDP/capita 12,000 GDP per capita and Poverty Headcount (US$ left axis, percent right axis) GDP per Capita - US$ - PPP 100 10,000 87.7 83.8 81.3 74.5 72.1 Poverty Headcount (% of 'Poverty & Income per Capita (% of Population - US$1.25/day) 68.0 67.9 67.8 62.8 61.6 59.6 90 80 8,000 70 54.1 51.7 50.4 60 6,000 50 38.7 38.0 40 4,000 33.5 30.7 28.6 30 23.8 23.4 2,000 19.8 13.8 20 9.6 10-0 Source: World Economic Indicators, 2012. Note: Poverty headcount is from the most recent year between 2005 and 2012. The GDP per capita da from 2012. The lack of uniformity between the poverty headcount figures and the GDP per capita figur reflects the difference in data points.

Coverage 11

Pension benefit as a percent of individual pre-retirement wage What is the coverage gap? Coverage Gaps Social pensions in 8 of 47 countries + very weak SSNs Poor but improving regulation of occupational schemes. Occupational & Individual Pensions Savings Social assistance for households &/or elderly. Minimum Pension Mandatory, contributory scheme Individual pre-retirement wage as a % of the average wage in the economy

Angola Ethiopia 1/ ongo, Dem. Rep. Central African Niger Malawi Chad Burkina Faso Mozambique Tanzania Lesotho Togo Rwanda 1/ Sudan Uganda Senegal Liberia Madagascar Mali Benin Sierra Leone Congo, Rep. Burundi Cote d'ivoire Mauritania Ghana Kenya Cape Verde Namibia Zambia Cameroon Botswana Sao Tome and Nigeria Zimbabwe Gambia, The Swaziland South Africa Mauritius Seychelles % of Labor Force Covered Key Challenge Labor force coverage 60% 50% 70% Occupational Schemes Civil Service National Scheme 40% 60% 50% Civil Service Coverage as a % of Total 30% 20% 40% 30% 20% 10% 0% 51.6% 68.6% 10% 0% 0.8%0.8% 1.5%0.9% 2.0% 3.7% 2.1%1.7% 2.5% 4.8%4.9% 3.1% 4.2%4.5% 6.8% 5.0%5.0% 7.9% 8.8%9.4% 10.4% 10.0%10.4% 12.8% 11.4% 7.6% 4.9%5.2% 5.8% 18.8% 17.6% 25.5%

Active members (% Working Age Population) Coverage strongly correlated w/gdp per capita 60.0% National Scheme + Civil Service Scheme + Occupational Scheme Coverage (% of Labour Force) South Africa y = 3E-05x + 0.0159 R² = 0.6771 Mauritius 50.0% 40.0% 1 0.9 0.8 Active coverage vs Income per capita y = -5E-10x 2 + 4E-05x + 0.0198 R² = 0.807 Swaziland 0.7 0.6 0.5 United Kingdom Czech Republic 30.0% 0.4 Brazil 0.3 0.2 Mongolia Jordan The Gambia 0.1 India Ghana 20.0% Zimbabwe Nigeria 0 0 Niger 10000 20000 30000 40000 50000 60000 Income per capita (Thousands) 10.0% Malawi, DRC, Central African Republic, Niger Burundi Kenya Sierra Leone Sao Tome & Principe Mauritania Zambia Ghana Cote d' Ivoire Cape Verde Republic of Congo Namibia Botswana Liberia Ethiopia Senegal Lesotho Chad Sudan Tanzania, Burkina Faso, Togo, Rwanda Angola 0.0% - 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000

Contributory pensions generally cover those w/wage incomes & better off in retirement 40.0% 35.0% 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% Coverage in poorest quintile (%) - Old Age Contributory Coverage in 3rd quintile (%) - Old Age Contributory Coverage in richest quintile (%) - Old Age Contributory Coverage in 2nd quintile (%) - Old Age Contributory Coverage in 4th quintile (%) - Old Age Contributory Source: The World Bank, ASPIRE database, 2014

Percent (of elderly or labor force) Middle East Latin America and the Caribbean Asia and the Pacific Central and Eastern Europe North America Western Europe World Developing economies Developed economies Sierra Leone Sources: ILO, World Bank, country administrative data. Chad Gambia, The Benin Zambia Rwanda Burkina Faso Zimbabwe Burundi Cameroon Malawi Tanzania Sudan Ghana Mali Niger Median Togo Uganda Cote d'ivoire Kenya Guinea Mozambique Senegal Average Cape Verde South Africa Swaziland Lesotho Botswana Mauritius Namibia Seychelles Central African Republic Congo, Dem. Rep. Congo, Rep. Ethiopia Liberia Madagascar Mauritania Nigeria Sao Tome and Principe Elderly coverage weak (except in countries with non-contributory schemes) 100 90 80 98.5 94.3 89.2 93.0 92.4 Elderly and Labor Force Coverage (Late 2000s; percent of elderly over eligibility age; percent of labor force) 92.9 89.1 Elderly Coverage Labor Force Coverage 86.0 93.1 100.0100.0100.0100.0 70 69.7 73.4 60 65.0 57.5 50 40 30 20 10-56.1 51.5 47.0 41.4 44.3 37.1 38.0 39.0 34.0 33.6 29.5 29.5 25 20.1 16.6 17.4 11.0 11.8 9.3 7.4 7.7 8.8 8.9 10.09.8 5.5 12 5.2 4.2 4.5 3.2 0.9 1.6 2.0 2.7 2.7 3.1 3.2 3.7 3.8 4.1 4.1 4.4 4.6 5.4 5.7 6.1 6.5 6.6 7.7 7.9 9 9 1.5 1.7 3.6 4.5 5.4 6.3 7.3 6.1 5.8 5.6 5.3 2.8 3.2 4.0 3.4 1.3 2.3 2.7 1.3 0.0 1.0 0.7

What has contributed to the coverage challenge? Low, volatile & non-wage incomes (w/populations substantially rural and informal) Payroll-tax contributory schemes best aligned to formal sector employment Contribution rates may discourage coverage & compliance Vesting periods penalize informality Discretionary indexation creates uncertainty Compliance & enforcement costly Voluntary occupational & individual schemes offer options but need to be better regulated & supervised in many countries to ensure public confidence.

Adequacy & Affordability 18

Adequacy of non-contributory pensions tension with coverage and cost

Seychelles Central African Republic Zambia Mauritania Zimbabwe Togo Chad Congo, Dem. Rep. Madagascar Mozambique Liberia Cote d'ivoire Tanzania Ghana Sao Tome and Principe Ethiopia Burundi Benin Cameroon Cape Verde Mali Niger Rwanda Sierra Leone Burkina Faso Guinea Sudan Congo, Rep. Angola Senegal South Africa Gambia, The Lesotho Mauritius Swaziland Namibia Uganda Kenya Malawi Calculated Replacement Rate (30 years of covered service) target replacement rates in some cases too high to be widely afforded or sustained 100.00% 90.00% 80.00% National Scheme Civil Service Scheme Simulated Replacement Rates 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% Source: Social Security Programs throughout the World: Africa 2013; and Bank estimates.

Contribution rates linked to target income replacement & scope of benefits Namibia South Africa Botswana Lesotho Seychelles Zimbabwe Mozambique Mauritius Sao Tome and Principe Swaziland Angola Guinea-Bissau Cape Verde Liberia Kenya Zambia Gambia, The Ethiopia Malawi Sierra Leone Uganda Nigeria Ghana Tanzania Sudan Congo, Dem. Rep. Burundi Madagascar Cameroon Mauritania Chad Niger Guinea Benin Togo Burkina Faso Central African Republic Rwanda Cote d'ivoire Congo, Rep. Mali Senegal Average Median 35.0% 30.0% Contribution Rates 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% Southern Africa & Lusophone Countries English Speaking/ Former British Colonies Former French/Belgium Colonies Average & Median Sickness and Maternity Family Allowances Work Injury Old Age Dis & Survivorship Source: Social Security Programs throughout the World: Africa 2013.

uncertain indexation & vesting periods can discourage participation of some workers Indexation Contributory Pension Indexation Angola NA Benin Discretionary 25 Botswana 1/ Burkina Faso Discretionary (acc to wages, minimum wage & resources of the scheme) Discretionary (according to changes in the cost of living, depending on the financial resources of the Burundi system) Cameroon No explicit indexation Cape Verde Ad-hoc 20 Central African Republic No explicit indexation Chad Discretionary (by decree according to actuarial projections by the National Social Insurance Fund) Congo, Dem. Rep. Discretionary Congo, Rep. Price Vesting periods Cote d'ivoire Price (and according to changes in the cost of living, depending on the financial resources of the system) Ethiopia NA Gambia, The 2/ Ghana Wage indexation Guinea Wage, depending on the financial resources of the system Guinea-Bissau NA Kenya 2/ Lesotho 1/ Liberia NA Madagascar According to increases in the legal minimum wage Malawi 4/ Benefits are indexed (adjusted) by decree according to changes in the average salary and the legal Mali minimum wage, depending on the financial resources of the system. Mauritania Price, depending on the financial resources of the National Social Security Fund Mauritius NA Mozambique NA Namibia 1/ Niger 3/ Nigeria 4/ Rwanda Ad hoc on the basis of Presidential Decree Sao Tome and Principe Wages Senegal 3/ Periodically according to revisions in the regulations which specify the benefit scales and benefit Seychelles adjustments Sierra Leone Wages, depending upon the financial position of NASSIT South Africa 1/ South Sudan 1/ Sudan NA Swaziland 2/ Tanzania Discretionary, according to the recommendation of the actuary Togo Price Uganda 2/ Zambia Wages Zimbabwe No explicit indexation 15 10 5 0 Senegal Kenya Mauritania Liberia Congo, Dem. Rep. Equatorial Guinea Ethiopia Gambia Guinea-Bissau Mozambique Sao Tome and Principe Seychelles Zimbabwe Mali Angola Benin Burkina Faso Burundi Cape Verde Central African Republic Chad Cote d'ivoire Ghana Guinea Madagascar Rwanda Sierra Leone Tanzania Togo Zambia Cameroon Gabon Malawi Niger Nigeria Sudan Congo, Rep. 1/ No national scheme 2/ Provident Fund. 3/ Points scheme. 4/ Defined-contribution scheme Source: Pension Programs throughout the World, Africa, 2013; and Bank estimates.

Sustainability 23

Mapping contribution rates against full career replacement rates suggests that some countries may face sustainability challenges Old Age Contribution Rate Contribution Rates and Calculated Replacement Rates for Defined-Benefit Schemes 30.0% 25.0% Sudan 20.0% Tanzania Mali 15.0% 10.0% 5.0% Togo Cote d'ivoire Madagascar Zambia Mauritania Chad Zimbabwe Central African Republic Seychelles Ghana Sierra Leone Ethiopia Guinea Burkina Faso Sao Tome & Principe Burundi Moz. Cameroon Liberia Rwanda Rep. of Congo Angola 0.0% 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% Calculated Replacement Rate (after 30 years) Source: Social Security Programs throughout the World, Africa: 2013 and World Bank estimates.

and some countries have projected unsustainable fiscal burdens over the medium-term Tanzania: Pension Financing Gaps Tanzania Financing Gap Projections: 2010 0.8% 0.7% 0.6% The Gambia: Projected Expenditures for the Public Service Pension Fund 0.5% 0.4% 0.3% 0.2% 0.1% 0.0% 2006 2011 2016 2021 2026 2031 2036 2041 2046 2051 2056 2061 2066 2071 price indexation no indexation

Pension spending generally low compared to regional benchmarks yet understandable when considering dependency and coverage rates Pension Spending (% of GDP, % of Government Expenditure late 2000s) Liberia (2010) Ethiopia (2006) Eritrea (2001) Uganda (2011) Congo, Dem. Rep. (2005) Swaziland (2010) The Gambia (2006/2003) Sierra Leone (2009) Cameroon (2009) Mauritania (2007) Niger (2006) Cote d'ivoire (2006) Rwanda (2005) Central African Republic (2004) Burundi (2010) Burkina Faso (2009) Nigeria (2004) Zimbabwe (2011) Congo, Rep. Ghana (2010) Kenya (2010) Malawi (2012) Zambia (2008/2012) Benin (2008/2010) Mali (2010) Botswana (2009) Senegal (2010) Mozambique (2010) Tanzania (2010) Seychelles (2011) Lesotho (2009) Guinea-Bissau (2005) South Africa (2010) Togo (2010) Namibia (2011) Cape Verde (2013/2010) Mauritius (2011) 0.1% 0.4% 0.3% 0.3% 0.4% 0.4% 0.4% 1.7% 1.0% 2.0% 2.1% 1.2% 1.7% 0.5% 0.5% 0.5% 0.6% 0.7% 0.7% 0.8% 0.8% 0.9% 2.5% 2.3% 0.9% 0.9% 1.0% 1.0% 1.3% 1.3% 1.4% 1.4% 1.4% 1.6% 1.7% 1.8% 1.8% 1.9% 1.9% 2.0% 2.1% 2.2% 2.3% 2.9% 2.9% 2.8% 2.5% 3.5% 3.5% 3.5% 3.0% 3.3% 3.3% 3.2% 4.8% 4.6% 4.5% 4.8% 5.3% 5.2% 4.4% 5.0% 5.4% 6.5% 6.8% 6.3% 6.7% 7.0% Spending as a % of Government Expenditure Spending as a % of GDP 9.3% 9.1% 10.6% 13.0% World Middle East North America Latin America and the Caribbean Central and Eastern Europe Western Europe Asia and the Pacific Sub-saharan Africa North Africa Africa 1.1% 1.3% 2.0% 3.3% 3.3% 3.6% 4.6% 5.0% 6.6% 8.3% 11.1% 13.6% 0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% 16.0% Source: ILO, World Bank estimates, IMF World Economic Outlook Database, 2014.

US$ percent Efficiency can exact a high cost Administrative Expense Indicators (US$ or % of Benefits/Expenditures) $400.0 200.0% $350.0 180.0% $300.0 160.0% 140.0% $250.0 120.0% $200.0 100.0% $150.0 80.0% $100.0 60.0% 40.0% $50.0 20.0% $0.0 x x x x x x x 0.0% Botswana- POPE Namibia- GIPF Swaziland- PSPF South Africa- GEPF Uganda- NSSF Tanzania- PPF Burkina Faso-CNSS Ghana- SSNIT Kenya- NSSF Tanzania- GEPF Sierra Leone- NASSIT Rwanda- RSSB Kenya- CSPS Mauritius- MNPS Administrative Expense per Insurance Benefit- US$ - left axis Administrative Expense as % of Benefits percent right axis Administrative Expense as % of Revenues percent right axis Source: Oleksiy Sluchynsky, Defining, Measuring and Benchmarking Administrative Expenditures of Public Pension Programs. Draft mimeo, 2012. Note: An x above the scheme indicates that the actual costs of operation are more than 5 times the predicted levels based on the averages observed for 100 pension and social security programs throughout the world.

Rwanda Gambia, The Angola Burundi Chad Uganda Burkina Faso Niger Zambia Sierra Leone Kenya Nigeria Togo Mali Madagascar Congo, Dem. Rep. Guinea-Bissau Benin Senegal Liberia Guinea Cote d'ivoire Mauritania Malawi Cameroon Sudan Mozambique Tanzania Sao Tome and Principe Congo, Rep. Ethiopia Ghana Swaziland Namibia Botswana Central African Zimbabwe Lesotho Cabo Verde South Africa Seychelles Mauritius % of GDP Government Expenditure - % of GDP What are the costs of various social pension benefits? Cost Estimates for Elderly Assistance Schemes (% of GDP) 2.0% Cost of a benefit of 20% of GDP/capita for all age 65+ 28% 30.0% 1.8% Government Expense (right hand axis) 26% 1.6% 1.4% 1.2% 20% 22% Universal Benefit of $1.25 per day for all 65+ Cost of a Benefit based on Poverty Headcount at $1.25/day for all population under $1.25/day and over age 65 18% 17% 22% 20% 19% 17% 20% 20% 20% 22% 19% 25.0% 20.0% 1.0% 14% 15% 14% 15% 15% 14% 14% 14% 15.0% 0.8% 0.6% 7% 8% 8% 10% 8% 10% 11% 9% 12% 11% 10% 8% 12% 8% 8% 8% 10.0% 0.4% 5.0% 0.2% 3% 0.0% 0% 0.0% Sources: World Development Indicators, accessed 3/2015. Note: demographic data is from 2013; GDP data, government expense data, poverty gap data from 2008-2013 as applicable.

What contributes to potentially growing fiscal costs? National schemes maturing Early stage in demographic transition, but possibly more advanced in covered workforce Contr. rates & benefit formulas inconsistent w/long-run balances Administrative costs Civil servant schemes - Growth in system dependency ratios & some with inconsistent parameters. Transition costs for civil servant schemes adopting funding. Social pension costs increase w/growth in elderly populations & scheme expansion

Governance and Investment Management Some principles: 1. Separation of responsibilities & accountabilities 2. Board election, accountability, fiduciary responsibility Investment Management (intro.) Accountability & financial control systems Risk management framework Principles for public pension assets Financial market absorptive capacity Foreign exchange risk & macro/fiscal effects

Reform Principles 31

Age Reform Principles contributory schemes Explore new design options voluntary, liquid, & possibly with special subsidies for the poor to save. Parametric reforms - choices between years of work life, contribution rates and replacement rates - actuarial projections to guide reform options. Retirement age Contribution rate Accrual rate Wage base def. Vesting Minimum pension Indexation Harmonize & merge 80 70 60 50 40 30 20 10 0 20.3 22.8 23.6 16.8 18.2 19.7 20.4 20.9 21.8 18.5 16.9 12.3 14.3 14.8 15.0 15.1 15.3 15.3 15.4 15.4 15.5 15.5 15.5 15.7 16.1 16.1 16.3 16.3 16.6 16.6 17.2 17.3 17.4 18.4 19.1 19.1 19.4 16.0 Retirement Eligibility Age Life Expectancy at Retirement Age civil service & national schemes (w/occupational top-up as necessary). Strengthen regulation & supervision of occupational & individual schemes (esp. for self-employed, unemployed, informal workers). 16.4 11.6

Cost (% of GDP) Reform Principles non-contributory schemes Universal support for the elderly exclusion errors need to be weighed against fiscal costs. Cost-benefit analysis of targeting the elderly can be weighed against targeting poor households Matching contributions could be linked to worker savings & elderly assistance benefits. Infrastructure needed for public transfers - identification, targeting, record-keeping, disbursement. Cost of social pensions to eliminate poverty gap amongst the elderly 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2-50.0% 45.0% 40.0% 35.0% 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% Poverty headcount by age group Poverty Headcount (%< Bottom 40%) Women Men 0.0% Ghana Tanzania Mozambique Malawi Mauritius Zambia Rwanda Working Age Adults (25-59) Children (0-14) Youth (15-24) Elderly (60+)

Cost (% of GDP) Reform Principles non-contributory schemes Universal support for the elderly exclusion errors need to be weighed against fiscal costs. Cost-benefit analysis of targeting the elderly can be weighed against targeting poor households Matching contributions could be linked to worker savings & elderly assistance benefits. Infrastructure needed for public transfers - identification, targeting, record-keeping, disbursement. Cost of social pensions to eliminate poverty gap amongst the elderly 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2-50.0% 45.0% 40.0% 35.0% 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% Poverty headcount by age group Poverty Headcount (%< Bottom 40%) Women Men 0.0% Ghana Tanzania Mozambique Malawi Mauritius Zambia Rwanda Working Age Adults (25-59) Children (0-14) Youth (15-24) Elderly (60+)

Reform Principles non-contributory schemes

Possible Subsidies for the poorest incl. through a match Reform Principles Closing the Coverage Gaps (for informal workers & retirees) Social Micro-savings Social Assistance Insurance Savings/Ins. Instruments - Old Age, Disability, Survivors Health Insurance Mobile Payments & Micro-Savings Elderly Assistance Assistance to the Poorest Identification Data/Account Management Payments 36

Mobile payments platforms and micro-savings vehicles -> provide longer term financial planning & savings behavior for informal workers 37

Questions for Discussion 38

Closing the coverage gap Should a core focus of public transfers to social security be oriented towards increasing elderly poverty protection? What contributory designs and non-contributory support offer the strongest potential for scalability? Focusing on the poorest Should cash transfers target the poorest, including elderly in poor households? Alternatively, should universal support for the elderly be offered to avoid exclusion errors and labor market effects (or cases with a legacy schemes)? Aligning pensions to needs and enabling conditions Should payroll-based PAYG DB schemes in SSA depart from the scaledpremium approach adopting lower benefit levels where needed consistent with affordable long-term contributions and sustainable balances? Where in the region might the risks of pre-funding outweigh the benefits due to insufficient enabling conditions (incl. fiscal capacity to support transition costs, regulatory & institutional infrastructure)? What are some of the tradeoffs involved in coordinating or merging civil service and national schemes?

mdorfman@worldbank.org Further reading Thank you! Mark Dorfman, 2015. Pension Patterns in Sub-Saharan Africa. Social Protection Discussion Paper, World Bank.