GROWTH, STRUCTURAL TRANSFORMATION AND POVERTY REDUCTION IN AFRICA Johannesburg November 2014 Francisco H. G. Ferreira Chief Economist, Africa Region The World Bank
OUTLINE 1. Current economic performance a bird s eye view 2. Africa s uneven growth 3. Structural transformation and poverty 4. Conclusions
AFRICA RISING : TWO DECADES OF SUSTAINED ECONOMIC GROWTH 6.95 Real GDP per capita in US$ at 2005 prices (in logs) 6.90 6.85 6.80 6.75 6.70 6.65 6.60 6.55 6.50 6.45 Actual Trend reversing two lost decades from the mid-70s to the mid-90s.
WITH GDP GROWTH STABLE AT 4.6% P.A., SSA IS CURRENTLY THE WORLD S THIRD FASTEST-GROWING REGION IN 2013-14 Annual growth in GDP, 2013 and 2014: selected country groupings 8 2013 2014 6 Percent 4 2 0-2 East Asia & Pacific Europe & Central Asia Source: Global Economic Prospects (World Bank) Latin America & Caribbean Middle East & North Africa South Asia Sub-Saharan Africa
PER CAPITA GDP IS GROWING AT 2.1% PER YEAR AND HAS BEEN RISING STEADILY FOR TWO DECADES Annual growth in GDP per capita, 2013 and 2014: selected country groupings 8 2013 2014 6 4 Percent 2 0 East Asia & Pacific Europe & Central Asia Latin America & Caribbean Middle East & North Africa South Asia Sub-Saharan Africa -2 Source: Global Economic Prospects, and Health Nutrition and Population Statistics (World Bank)
IN A CONTEXT OF BROADLY STABLE INFLATION RATES (IN MOST CASES). Percent, y/y 25 20 Ghana Nigeria Zambia Kenya South Africa Sub-Saharan Africa 15 10 5 0 2010M01 2011M01 2012M01 2013M01 2014M01 Source: World Bank
POVERTY HAS FALLEN OVER THE LAST FIFTEEN YEARS, BUT MORE SLOWLY THAN ELSEWHERE, AND THAN NEEDED TO MEET MDG-1 Headcount ($1.25 a day) 0.3 Poverty Gap ($1.25 a day) 70% 60% 50% 0.2 40% 30% 20% 0.1 10% 0% 1990 1993 1996 1999 2002 2005 2008 2010 2011 SSA SSA Path to MDG 2015 Rest of the world Rest of the world Path to MDG 2015 0 1990 1993 1996 1999 2002 2005 2008 2010 2011 SSA Rest of the World Source: World Bank, Africa s Pulse vol. 10. PovcalNet (2014)
THIS REFLECTS THE REGION S LOW GROWTH ELASTICITY OF POVERTY REDUCTION Growth elasticity of poverty reduction, 2000-2010 Five most populous countries by region*, except Poland and Sri Lanka 4 2 0-2 -4-6 -8-10 -12-2.02-0.7-14 Thailand Egypt, Arab Rep. Kazakhstan Philippines Morocco Turkey Tunisia Argentina Nepal Pakistan Source: estimates based on PovcalNet (2014). *For which data is available Peru Vietnam Bangladesh Romania Other developing countries India Brazil Indonesia Mexico China Colombia Uganda South Africa Ethiopia Sub-Saharan Africa Iran, Islamic Rep. Tanzania Nigeria Ukraine Yemen, Rep.
WHICH IN TURN REFLECTS HIGH INEQUALITY, BOTH IN INITIAL LEVELS Most African countries have high levels of consumption or income inequality, relative to the rest of the world. Seven of the ten most unequal countries in the world today are in SSA. 70 60 Gini coefficient 50 40 30 20 10 0 MLI BDI ETH NER SDN SLE GNB TZA LBR BEN CMR TGO GIN NGA TCD BFA SEN MRT GAB CIV AGO GHA MDG MWI UGA ZAR MOZ GMB COG KEN CPV RWA STP SWZ LSO CAF ZMB BWA NAM ZAF COM SYC Consumption Survey Income Survey Sub Saharan Africa Source: PovcalNet, most recent survey available.
AND IN THE GROWTH PROCESS ITSELF. In Malawi, average p.c. household consumption grew by 6.5% between 2004-2010. But whereas the top 5% of the population experienced annual growth rates of almost 8%, the bottom 5% grew by between 1% and 3%. 9 Growth Incidence Curve, Malawi 2004-2010 Percent growth in consumption 8 7 6 5 4 3 2 1 0 1 8 16 23 31 38 46 53 61 68 76 83 91 98 Consumption expenditure percentile Source: estimates based on household surveys from Survey-based Harmonized Indicator Program (SHIP)
OUTLINE 1. Current economic performance a bird s eye view 2. Africa s uneven growth 3. Structural transformation and poverty 4. Conclusions
THE WEAK LINK FROM GROWTH TO POVERTY IS RELATED TO THE UNEVEN NATURE OF THE REGION S GROWTH Growth in GDP per capita in SSA by country groups, 1995-2013 (Output per capita index, 1995=1) 1.8 1.7 Output per capita index (1995=1) 1.6 1.4 1.2 1.4 1.2 1 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Sub-Saharan Africa Resource-rich Non-resource-rich Source: World Bank, Africa s Pulse vol. 10. World Development Indicators (2014) Note: The index presented in this figure depicts the cumulative growth in real per capita GDP from 1995 to 2013 in Sub-Saharan Africa and sub-groups. We use GDP in U.S. dollars at 2005 prices from the World Development Indicators,for 45 countries in SSA (16 resource rich, 29 non resource rich)
BOTH ACROSS COUNTRIES, AND ACROSS SECTORS AND REGIONS WITHIN COUNTRIES Growth in GDP per capita by sector, 1995-2011 (Output per capita index, 1995=1) 1.7 1.6 Output per capita index (1995=1) 1.5 1.3 1.1 1.5 1.1 0.9 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Sub-Saharan Africa Agriculture Industry Services Source: staff estimates based on WDI (2014). Note: Subset of 36 SSA countries for which sectoral value added data is available.
SERVICES AND THE NATURAL RESOURCE SECTOR ARE GROWING MUCH FASTER THAN AGRICULTURE AND MANUFACTURING Growth in GDP per capita by sector, 1995-2011 (Output per capita index, 1995=1) 1.7 Output per capita index (1995=1) 1.5 1.3 1.1 1.5 1.4 1.1 1.1 0.9 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Sub-Saharan Africa Agriculture Manufacturing Services Source: staff estimates based on WDI (2014). Note: Subset of 32 SSA countries for which sectoral value added data can be decomposed into manufacturing and other industry.
COMPARED TO OTHER LDCS, AFRICA S GROWTH IS RELATIVELY MORE DEPENDENT ON EXTRACTIVES, AND MUCH LESS ON MANUFACTURING Sectoral contribution to total cumulative growth 5% 4% 3% 2% 1% 0% -1% Average growth in GDP per capita by sector (1995-2011) Avg. growth: 2% Sub-Saharan Africa Agriculture Other industry Avg. growth: 4.4% Other Developing Countries Manufacturing Services Sectoral contribution to average growth in GDP per capita (1995-2011) 63% 27% 12% -2% Sub-Saharan Africa Agriculture Other industry 58% 18% 17% 7% Other Developing Countries Manufacturing Services Source: staff estimates based on World Development Indicators (2014) Note: Subset of 32 SSA and 56 developing countries for which sectoral value added data can be decomposed into manufacturing and other industry.
THE HUGE IMPORTANCE OF SERVICES IN AFRICA IS NOT EXCEPTIONAL The high share of extractives (and agriculture) and the low share of manufacturing are. Sub-Saharan Africa Other developing countries 60 60 55 50 52 Value added (%GDP) 40 20 20 15 10 Value added (%GDP) 40 30 20 10 23 15 10-0 1995 1997 1999 2001 2003 2005 2007 2009 2011 1995 1997 1999 2001 2003 2005 2007 2009 2011 Agriculture Manufacturing Services Other industry Agriculture Manufacturing Services Other industry Source: : staff estimates based on WDI (2014). Note: Subset of 32 SSA and 56 developing countries for which sectoral value added data can be decomposed into manufacturing and other industry.
THE SECTORAL COMPOSITION OF LABOR ALSO DIFFERS GREATLY IN AFRICA AND OTHER DEVELOPING COUNTRIES 32.1 40.8 8.7 24.1 59.2 35.0 Sub-Saharan Africa Other developing countries Total working Agriculture Industry Services Source: World Bank, Africa s Pulse vol. 10. International Income Distribution Database. Notes: The numbers correspond to working age (15-65) population weighted averages of the most recent survey between 2002 and 2012. Average of 33 (20) SSA countries and 66 (41) other developing countries for total working (working poor).
THE SECTORAL COMPOSITION OF LABOR ALSO DIFFERS GREATLY IN AFRICA AND OTHER DEVELOPING COUNTRIES ESPECIALLY AMONG THE POOR 16.4 21.8 32.1 40.8 5.4 8.7 18.5 24.1 78.2 59.2 59.7 35.0 Sub-Saharan Africa Total working Other developing countries Agriculture Industry Services Sub-Saharan Africa Working poor Other developing countries Agriculture Industry Services Source: World Bank, Africa s Pulse vol. 10. International Income Distribution Database. Notes: The numbers correspond to working age (15-65) population weighted averages of the most recent survey between 2002 and 2012. Average of 33 (20) SSA countries and 66 (41) other developing countries for total working (working poor).
OCCUPATIONAL COMPOSITION ALONG THE INCOME DISTRIBUTION CHANGING SECTORAL COMPOSITION OF LABOR: RWANDA Source: World Bank, Africa s Pulse vol. 10. Calculations using SHIP data. (z=$1.25 /day)
OCCUPATIONAL COMPOSITION ALONG THE INCOME DISTRIBUTION CHANGING SECTORAL COMPOSITION OF LABOR: SENEGAL Source: World Bank, Africa s Pulse vol. 10. Calculations using SHIP data. (z=$1.25/day)
OUTLINE 1. Current economic performance a bird s eye view 2. Africa s uneven growth 3. Structural transformation and poverty 4. Conclusions
DO SUCH DIFFERENCES IN THE PATTERN OF GROWTH OR IN THE NATURE OF STRUCTURAL TRANSFORMATION MATTER FOR POVERTY REDUCTION? International evidence on sector-specific growth impacts 4 Brazil China India Effect of growth on poverty reduction 2 0-2 -4-6 -8-10 Agriculture Industry Services Source: World Bank, Africa s Pulse vol. 10 (adapted from Ferreira et al. (2010), Ravallion and Chen (2007), an Ravallion and Datt (1996) Notes: The results refer to time periods of analysis from 1985 to 2004 for Brazil, 1981-2001 for China, and 1951 to 1991 for India. National poverty lines are used for all countries. Vertical axis measures regression coefficients (unadjusted by sector shares)
THERE IS SOME EVIDENCE THAT THE PATTERN OF GROWTH ALSO MATTERS IN AFRICA In Ethiopia, growth in agriculture has contributed most to poverty reduction since at least 2000-10 Sectoral contribution to poverty reduction (% points) -8-6 -4-2 0 2 1996-2000 2000-2005 2005-2011 Agriculture Manufacturing Construction Service Other Source: Hill & Tsehaye, 2014, Growth, Safety Nets and Poverty-Assessing Progress in Ethiopia from 1996 to 2011
Source: World Bank, Africa s Pulse vol. 10. Data from WDI (2014) on sectoral value added as a share of GDP and poverty data PovcalNet (2014) from 1990 to 2010. Note: The null hypothesis that the sectoral composition of growth does not matter is rejected at the 1% level for all the poverty measures (Headcount, Poverty Gap and Squared Poverty Gap). This is robust to the inclusion of controls. CROSS-COUNTRY REGRESSIONS SUGGEST THAT GROWTH PATTERNS DO MATTER FOR POVERTY REDUCTION Africa: agriculture and services most poverty reducing Elsewhere: industry and services most poverty reducing VARIABLES Sub-Saharan Africa Headcount Poverty Gap Sq. Poverty Gap Other Developing Countries Headcount Poverty Gap Sq. Poverty Gap Agriculture -0.668*** -1.025*** -1.322*** -1.224-0.752-2.411* (0.209) (0.318) (0.417) (1.268) (1.799) (1.333) Industry -0.086-0.078-0.115-1.864*** -2.595*** -3.079*** (0.301) (0.371) (0.434) (0.483) (0.624) (0.787) Services -0.963*** -1.233*** -1.493*** -1.881*** -1.899*** -1.195* (0.193) (0.254) (0.310) (0.507) (0.681) (0.683) Observations 228 228 228 240 240 239 Countries 29 29 29 31 31 31 R-squared 0.280 0.309 0.319 0.367 0.344 0.377 Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1
THIS IS ROBUST TO THE INCLUSION OF CONTROLS VARIABLES Sub-Saharan Africa Poverty Sq. Poverty Headcount Gap Gap Other Developing Countries Poverty Sq. Poverty Headcount Gap Gap Agriculture -0.673*** -1.024*** -1.316*** -1.033-0.545-2.321* (0.227) (0.337) (0.436) (1.305) (1.837) (1.338) Industry -0.084-0.088-0.140-1.934*** -2.665*** -3.156*** (0.341) (0.415) (0.479) (0.476) (0.618) (0.772) Services -0.940*** -1.229*** -1.516*** -1.931*** -1.963*** -1.226* (0.207) (0.271) (0.329) (0.526) (0.705) (0.717) CPI 0.015 0.000-0.021 0.008 0.013 0.015 (0.039) (0.048) (0.060) (0.017) (0.024) (0.032) Infant Mortality 0.022 0.007-0.005-0.532-0.676-0.498 (0.171) (0.250) (0.327) (0.800) (1.116) (1.429) Lag GDP per capita -0.008-0.007-0.005-0.067-0.069-0.120** (0.026) (0.035) (0.044) (0.040) (0.053) (0.050) Observations 228 228 228 240 240 239 Countries 29 29 29 31 31 31 R-squared 0.281 0.309 0.320 0.380 0.352 0.391 Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1 Source: World Bank, Africa s Pulse vol. 10. Data from WDI (2014) on sectoral value added as a share of GDP and poverty data PovcalNet (2014) from 1990 to 2010. Note: The null hypothesis that the sectoral composition of growth does not matter is rejected at the 1% level for all the poverty measures (Headcount, Poverty Gap and Squared Poverty Gap). This is robust to the inclusion of controls.
DIGGING DEEPER INTO THE INDUSTRY PUZZLE As the poverty line is raised, agriculture matters less and less, while industry gains importance (ever so slightly) The service elevator dominates throughout Sub-Saharan Africa 4 2.5 2 1.25 Poverty line (USD per day) -0.5-0.4-0.3-0.2-0.1 0 Growth elasticity of poverty reduction Agriculture Industry Services Source: World Bank, Africa s Pulse vol. 10. Note: the solid bars represent significant effects at 10% of significance or lower. Industry is not significant and agriculture loses its power as the poverty line increases (not significant for $4 a day).
DO WE NEED TO RETHINK HOW WE VIEW STRUCTURAL TRANSFORMATION? 60% of Africa s labor force, and almost 80% of the working poor are in agriculture. When it takes place, agricultural growth is effective at reducing poverty. But it takes place all too slowly. The evidence is suggestive of a service elevator out of poverty: The services sector has grown strongly. AND it has large effects on poverty. The manufacturing sector is in relative decline, and not effective against poverty. Africa s manufacturing weakness is not preordained, but endogenous Promoting agricultural productivity growth remains paramount How do people get on to it, and how can policy help? Three horizontal paths to giving African manufacturing a break
1. PROVIDE A SKILLED LABOR FORCE 12 10 8 6 4 2 Average years of schooling (age 15+) 2005 2010 0 East Asia & Pacific Europe & Central Asia Latin America & Caribbean Middle East & North Africa South Asia Sub-Saharan Africa Source: staff estimates based on Education Statistics, 2014. Robert J. Barro and Jong-Wha Lee: http://www.barrolee.com
2. PROVIDE RELIABLE AND AFFORDABLE POWER Industrial tariffs (US per kwh) inclusive of demand charges (where applicable), energy charges and applicable taxes and fees 0.6 0.5 0.51 Africa (10 MWH consumption / 100 kw capacity) Africa (750 MWH consumption / 2,000 kw capacity) Comparison countries (10MWH consumption, 100 kva capacity) 0.4 0.3 0.2 0.28 0.22 0.1 0.0 0.02 0.07 Liberia Cape Verde Chad Senegal Burundi Burkina Faso Madagascar Gambia, The Kenya Angola Benin Comoros Cameroon Lesotho Malawi Ghana Côte d'ivoire Guinea Botswana Zimbabwe Mauritius Mozambique Mauritania Ethiopia Honduras Chile India United States Yemen, Rep. Nepal Mongolia Armenia US per kwh Source: preliminary numbers for SSA from Electricity Subsidies Study, 2014. Comparison countries from Readiness for Investment in Sustainable Energy (RISE) 2014.
3. LOWER TRANSPORT, TRADING AND TRANSACTION COSTS 2.85 Logistics Performance Index 2.76 2.74 2.61 2.5 2.46 East Asia & Pacific Europe & Central Asia Latin America & Caribbean South Asia Middle East & North Africa Sub-Saharan Africa The LPI captures the quality of transport infrastructure, timeliness of shipments, the efficiency of border clearance processes, etc. It is based on a survey of 1000 respondents from 143 countries (69 in SSA), in Oct-Dec 2013. Source: Logistics Performance Index, World Bank,2014. Note: regional numbers are simple averages of country specific scores.
OUTLINE 1. Current economic performance a bird s eye view 2. Africa s uneven growth 3. Structural transformation and poverty 4. Conclusions
CONCLUSIONS 1. Africa continues to grow robustly above 4.5% per year in GDP, and above 2.0% in per capita terms. 2. That growth continues to be relatively ineffective in reducing poverty. 3. That is because most of Africa s poor people work in agriculture, but most of the growth takes place elsewhere. 4. Services sector growth is poverty-reducing and should be promoted and better understood. 5. Faster gains in agricultural productivity and a level playing field for African manufacturing are needed. 6. So are solid systems and institutions to face risks in health, macroeconomics and violent conflict.
THANK YOU