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HLEG thematic workshop on Measurement of Well Being and Development in Africa, Sabina Alkire
- 1. Multidimensional Poverty in Sub- Saharan Africa: Measurement and Relevance Sabina Alkire, OPHI, U of Oxford and GWU Beyond GDP Conference, Durban South Africa, Nov 2015
- 2. Multidimensional Poverty Index (MPI) - acute poverty in developing countries - 1. MPI Methodology 2. MPI 2015 3. Overview of Results in SSA 4. MPI in the Sustainable Development Goals
- 3. METHODOLOGY
- 5. Order of Aggregation Income Education Shelter Water 1. D ND ND ND 2. ND D ND ND 3. ND ND D ND 4. ND ND ND D Income Education Shelter Water 1. ND ND ND ND 2. ND ND ND ND 3. ND ND ND ND 4. D D D D Joint Distribution I Joint Distribution II ND: Not Deprived D: Deprived
- 6. Order of Aggregation Income Education Shelter Water 1. D ND ND ND 2. ND D ND ND 3. ND ND D ND 4. ND ND ND D Income Education Shelter Water 1. ND ND ND ND 2. ND ND ND ND 3. ND ND ND ND 4. D D D D Joint Distribution I Joint Distribution II ND: Not Deprived D: Deprived
- 7. Who is poor? A person who is deprived in more than 1/3 of the weighted indicators is MPI poor. Nathalie is deprived in 2/3 of indicators. She is MPI poor.
- 8. What is the MPI? • The MPI (like FGT-1) is the product of two components: 1) Incidence ~ the percentage of people who are poor, or the headcount ratio H. 2) Intensity of people’s deprivation ~ the average share of dimensions in which disadvantaged people are deprived A. The global MPI uses the Alkire & Foster (2011) methodology. The structure is unchanged since 2010. MPI = H × A
- 9. Literature Review, AF Methodology, Measurement Design, Robustness, Statistics, Analysis: multidimensionalpoverty.org
- 11. What does the Global MPI add to a dashboard? A Dashboard: Across 101 countries and 5.2 billion people: • 53.2% of the considered population lack clean cooking fuel • 40.3% lack adequate sanitation by MDG definitions • 26.5% live in houses where floors are dirt, sand, or natural • 26.5% have someone in their household who is undernourished • 21.8% lack electricity • 17.0% of people live in houses where a child has died • 16.3% lack safe water by MDG definitions • 14.5% live in a household where a child is not attending school up to class 8. • 13.6% live in a household in which no member has completed five years of schooling. Totals 13.2 billion deprivations across 5.2 billion people. Simple question: How many people have more than one deprivation?
- 12. Looking Across Dimensions: Across 5.2 billion people: • 3.9 billion are deprived in at least one indicator – 75% • 2.3 billion are deprived in 20% or more of the weighted indicators • 1.6 billion are deprived in 33% or more of the weighted indicators • 800 million are deprived in 50% or more of the weighted indicators - For each of these we can then show how they are poor – the composition. • 1 billion are deprived in one indicator only – none of the others.
- 14. MPI 2010-2015: At-a-Glance • Since 2010: Global MPI estimations for 117 countries using 217 datasets fielded 2000-2014 • Since 2010: MPI estimations for 1362 sub-national regions in 100 country-periods • New Methods: Destitution, Inequality among the poor, Standard errors, Dynamic analysis • Data quality: In 2010 we had all 10 indicators for only 60% of countries; now it is 84%. Harmonization better. • Robustness: More Robust in 2015 than 2010. 14
- 15. MPI 2015
- 16. Global MPI 2015: Major Update 2015: Biggest update to date ~ countries & population • 37 countries: new or updated MPI estimations. • 2.1 billion people e.g. 43% of the population covered in Africa, 72% in Arab States and 82% in East Asia have new MPIs in 2015 – thanks to DHS and MICS survey data, & PAPFAM. The 2015 analysis covers 101 countries with data 2005-14. The countries have a total population of 5.2 billion people, 75% of the world’s population. (no imputations/extrapolations) 16
- 17. Global MPI 2015: SSA Data - The 2015 SS African MPI estimations cover 39 countries, housing 96% of the people – 812 out of 842 million. - We have disaggregated data for 391 subnational regions in 37 African countries – all except S Africa and Guinea Bissau. - In 34 SSA countries, data are from surveys fielded 2010-2014. - Between 2014 and 2015 OPHI have new or updated estimations for 30 of the 39 SS African countries. - All 39 SSA countries have all 10 MPI indicators. 17
- 18. Population Coverage by Region MPI 2015: Covers 5.2 billion people living in six world regions MPI countries by Region Population in MPI countries (million) Total Pop in regions % Pop covered 15 Europe and Central Asia 152 492 30.9 12 Arab States 263 352 74.9 18 Latin America & Caribbean 499 588 85 10 East Asia and the Pacific 1889 2041 92.6 7 South Asia 1608 1704 94.3 39 Sub-Saharan Africa 812 842 96.4 Europe and Central Asia 3% Latin America and Caribbean 10% East Asia and the Pacific 36% Arab States 5% South Asia 31% Sub- Saharan Africa 15%
- 19. 19 Across 101 countries & 5.2 billion people 30% of people are poor Aggregates use 2011 population data Global MPI =1.6 billion people
- 20. 31% of MPI poor people live in Sub-Saharan Africa, and 54% in South Asia MPI, H and A are highest in SS Africa In Sub-Saharan Africa 61% of people are MPI poor; average intensity is 56%
- 21. 0% 10% 20% 30% 40% 50% 60% 70% Europe and Central Asia Latin America and Caribbean East Asia and the Pacific Arab States South Asia Sub-Saharan Africa Censoredheadcountratiosintheregion: proportionwhoispooranddeprivedin... Composition of Poverty by Indicator Nutrition Child Mortality Years of Schooling Attendance Cooking Fuel Sanitation Water Electricity Floor Assets H (% MPI poor people)
- 22. st Asia and the Pacific Arab States South Asia Sub-Saharan Africa ty by Indicator Nutrition Child Mortality Years of Schooling Attendance Cooking Fuel Sanitation Water Electricity Floor Assets H (% MPI poor people) In Sub-Saharan Africa, on avg deprivations in all dimensions are >25% - LS highest
- 23. But H and A vary: Sub-Saharan Africa
- 24. 24 In Niger 89% of people are poor; in S Sudan, 91%
- 25. Where the MPI Poor People Live: 496 M (479-513) (0.05 sig) 2011
- 26. 26 In 53 subnational regions in Africa, more than 90% of people are poor.
- 27. Nigeria and South Sudan – no relationship? 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AverageIntensityofPoverty(A) Percentage of People Considered Poor (H) The size of the bubbles represent the total number of MPI poor in each country Nigeria MPI 0.303 H 53.2% A 56.8% South Sudan MPI 0.547 H 91.1% A 61.2%
- 28. Nigeria and South Sudan – no relationship? 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AverageIntensityofPoverty(A) Percentage of People Considered Poor (H) The size of the bubbles represent the total number of MPI poor in each country Nigeria has three regions with a higher MPI than South Sudan. They have 13.9 million MPI poor people. South Sudan has 9.5 million MPI poor people.
- 29. Nigeria and South Sudan – no relationship? 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AverageIntensityofPoverty(A) Percentage of People Considered Poor (H) The size of the bubbles represent the total number of MPI poor in each country South Sudan Is home to 9.5 million MPI poor people. Nigeria has more MPI poor people with the same intensity as S Sudan. Nigeria has three regions with a higher MPI than South Sudan. They have 13.9 million MPI poor people.
- 31. The Composition of Poverty: Nigeria
- 32. Subnational Estimations add precision Example: Nigeria
- 33. Cameroon 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AverageIntensityofPoverty(A) Percentage of People Considered Poor (H) Cameroon - National Level The size of the bubbles is a proportional representation of the total number of MPI poor in each country
- 34. Centre Douala Est Extrême-Nord Littoral Nord Ouest Sud-Ouest Yaoundé Cameroon 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AverageIntensityofPoverty(A) Percentage of People Considered Poor (H) Cameroon - Subnational Decomposition The size of the bubbles is a proportional representation of the total number of MPI poor in each country
- 35. Ethiopia 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AverageIntensityofPoverty(A) Percentage of People Considered Poor (H) Ethiopia - National Level The size of the bubbles is a proportional representation of the total number of MPI poor in each country
- 36. Addis Ababa Affar Amhara Dire Dawa GambelaHarari Oromiya Somali Tigray Ethiopia 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AverageIntensityofPoverty(A) Percentage of People Considered Poor (H) Ethiopia- Subnational Decomposition The size of the bubbles is a proportional representation of the total number of MPI poor in each country
- 37. Tanzania 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AverageIntensityofPoverty(A) Percentage of People Considered Poor (H) Tanzania - National Level The size of the bubbles is a proportional representation of the total number of MPI poor in each country
- 38. CentralEastern Lake Northern Southern Southern Highlands Western Zanzibar Tanzania 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AverageIntensityofPoverty(A) Percentage of People Considered Poor (H) Tanzania - Subnational Decomposition The size of the bubbles is a proportional representation of the total number of MPI poor in each country
- 39. Uganda 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AverageIntensityofPoverty(A) Percentage of People Considered Poor (H) Uganda- National Level The size of the bubbles is a proportional representation of the total number of MPI poor in each country
- 40. Central 1 Central 2 East Central EasternKampala Karamoja North Southwest West Nile Western Uganda 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% AverageIntensityofPoverty(A) Percentage of People Considered Poor (H) Uganda - Subnational Decomposition The size of the bubbles is a proportional representation of the total number of MPI poor in each country
- 41. The MPI: Data all online Burkino Faso
- 42. Adja Bariba Dendi Fon Yoa and Lopka Bétamaribe Peulh Yoruba -0.035 -0.030 -0.025 -0.020 -0.015 -0.010 -0.005 0.000 0.005 0.010 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 AnnualAbsoluteChangeinMPIT Multidimension Poverty Index (MPIT) at initial year Reduction in MPI Size of bubble is proportional to the number of poor in first year of the comparison. Over time – by ethnic group – Benin Poorest ethnic group saw no change in MPI. They are being left behind.
- 43. Kalenjin Kamba Kikuyu Kisii Luhya Luo Meru Mijikenda/Swahili Somali -0.035 -0.030 -0.025 -0.020 -0.015 -0.010 -0.005 0.000 0.005 0.010 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 AnnualAbsoluteChangeinMPIT Multidimension Poverty Index (MPIT) at initial year Reduction in MPI Size of bubble is proportional to the number of poor in first year of the comparison. Disaggregating by ethnic group - Kenya Poorest ethnic group reduced MPI the fastest. They are catching up.
- 44. 44 Level of MPI and Speed of Poverty Reduction in Africa
- 45. MPI vs. Income poverty for SSA countries If progress was only measured by reducing income poverty, the tremendous gains of Rwanda and Ghana would have been less visible.
- 46. CHINA
- 47. China’s Global MPI H: 5.5% A: 40.9% MPI=H*A=0.023 Data source: CFPS-2012 0 20 40 60 80 100 SouthSudan Ethiopia BurkinaFaso SierraLeone Mali Guinea-Bissau Congo,DemocraticRepublicofthe Uganda Rwanda Madagascar Afghanistan Benin Coted'Ivoire Senegal India Yemen Bangladesh Haiti Cameroon Nepal Namibia Comoros SaoTomeandPrincipe Ghana Zimbabwe Bhutan Swaziland Nicaragua Indonesia Tajikistan SouthAfrica Peru Guyana TrinidadandTobago Colombia Maldives Belize VietNam Ecuador Mexico Uzbekistan Jamaica Thailand Libya Ukraine SaintLucia Georgia Macedonia,TheformerYugoslav… Armenia Serbia Belarus China, 0.023 MPI in 101 countries
- 48. China’s Global MPI Overlap between income poor & MPI poor?
- 49. Relationship between Income Poor & MPI Poor 12.6% Income poor 5.5% MD poor 12.6% 5.5% 12.6% Income Poor 5.5% MPI Poor 1.6 %
- 50. GLOBAL: MPI ~ $1.90/DAY NATIONAL: nMPI ~ INCOME Both useful
- 51. National MPIs using AF methodology Chile Oct 29th 2015 Launch: Costa Rica & El Salvador
- 52. The Multidimensional Poverty Peer Network Launched in June 2013 at University of Oxford with President Santos and Amartya Sen: • 2014: Berlin • 2015: Colombia • 2015: Mexico 2017: China • Includes high level participation in 40+ countries • Side events at UN General Assembly, UN Stats Com
- 53. A Global MPI in the Sustainable Development Goals (SDGs) Target 1.2: by 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions. ‘Green’ Indicators: 1.2.1 – National Income and National MPIs 1.2.2 – MPI Sixty-Ninth Session of the UN General Assembly Dec 2014. (A/RES/69/238) 5. Underlines the need to better reflect the multidimensional nature of development and poverty... UNSG Synthesis Report Dec 2014: 5.1 Measuring the new dynamics ... Poverty measures should reflect the multi-dimensional nature of poverty.
- 57. 2011 Population Data High income: nonOECD 0% Upper middle income 40% Lower middle income 46% Low income 14% Total population by income category Middle Income 70% MPI poor people by income category Most poor people (70%) live in middle-income countries (MICS)