Oxford poverty research pinpoints Africa’s “runaway” successes, yet underlines the stark scale of remaining poverty challenges

According to new analysis from the Oxford Poverty & Human Development Initiative (OPHI), University of Oxford, 30 of 35 Sub-Saharan African countries analysed for changes to poverty over time have reduced multidimensional poverty significantly. Rwanda has put in a stellar performance, showing the most comprehensive and equitable poverty reduction on the continent, but so have 19 sub-national regions in Africa, notably the department of Likouala in the Republic of Congo. 

The Global Multidimensional Poverty Index or MPI - unlike global monetary poverty measures - can break down poverty levels for regions within countries, as well as revealing the different dimensions in which people are poor. Hence we know that every MPI indicator was significantly reduced in Burkina Faso, Comoros, Gabon, Mozambique, and Rwanda, showing the impact of coordinated policy responses. All sub-national regions in Gabon, Ghana, Gambia, Liberia, Mozambique, Malawi, Niger, and Rwanda reduced poverty significantly. 

Sabina Alkire, Director of OPHI at the University of Oxford and the Oliver T Carr Professor of Economics and International Affairs at George Washington University, said: “While Rwanda was truly a star performer, a number of sub-national regions in Africa reduced the MPI even faster. We call these creative high performers the ‘runaway regions’ because they are small areas that did great things. The fastest MPI reduction was found in Likouala in the Republic of Congo”. 

Ayodele Odusola, Chief Economist for UNDP Africa, said: “The Global Multidimensional Poverty Index 2016 figures for Africa provide extensive detail as to variations in the composition of poverty within countries. They map multidimensional poverty for 475 subnational regions in Africa, providing an unprecedented level of clarity. Those working on Africa will wish to understand the comparative performance of different countries in multidimensional poverty, and study in particular the small regions that have creatively fought poverty with runaway success”. 

However, over half (54%) of people in the 45 African countries surveyed suffer from multidimensional poverty. In total over half a billion Africans (544 million people) are MPI poor. Unfortunately, the number of poor African people is not reducing as fast as the poverty rates. The number of poor people went down in only 12 African countries. In 18 countries, although the incidence of MPI fell, population growth led to an overall rise in the numbers of poor people. 

These latest figures from the Global Multidimensional Poverty Index (MPI) cover all 102 developing countries - some 5.2 billion people or 75% of the world’s population. Nearly 1.6 billion people are found to be living in multidimensional poverty around the world. The Global MPI complements measures based on income and reflects the hidden face of poverty. Overlapping disadvantages in terms of health, education and living standards are considered by the MPI, which makes it more receptive to capture the real barriers that prevent poor people from thriving. People are identified as multidimensional poor if deprived in at least one-third of ten weighted indicators. The index combines the percentage of people living in multidimensional poverty with the intensity of deprivations, or how much deprivation they experienced. 

Overall, South Asia is home to over half (53%) of the global MPI poor population, while 32% live in Sub-Saharan Africa. The Global MPI 2016 uses data ranging from 2005-2014, mainly collected by USAID's Demographic and Health Survey (DHS) and UNICEF's Multiple Indicators Cluster Survey (MICS), as well as PAPFAM and national surveys. 

Professor Alkire said: “The new Sustainable Development Goals, which have replaced the Millennium Development Goals, call on countries to halve poverty ‘in all its dimensions’. The MPI has been proposed as an indicator for monitoring progress toward this goal, as it can be of great use in tracking national multidimensional poverty reduction efforts. 

Alongside the Global MPI many countries are also developing national MPIs, as official national statistics, whose indicators and cutoffs are tailored to their contexts and priorities. An MPI can serve as a focal point for integrated policies, can be easily disaggregated, and can monitor changes quickly”.

NOTES FOR EDITORS 

Oxford Poverty and Human Development Initiative (OPHI) 

OPHI is a research centre within the Oxford Department of International Development at the University of Oxford. OPHI is led by Sabina Alkire and works to develop and apply new ways of measuring and analysing poverty, human development and welfare, drawing on the work of Nobel Laureate economist Amartya Sen. For more information about OPHI, please visit www.ophi.org.uk. 

Background to the Multidimensional Poverty Index (MPI) 

The MPI was created by OPHI Director Sabina Alkire and OPHI Research Associate Maria Emma Santos (now also at Universidad Nacional del Sur and the Consejo Nacional de Investigaciones Científicas y Técnicas (National Scientific and Technical Research Council), Argentina) in collaboration with the UNDP's Human Development Report Office, which also publishes the results. It is constructed using a methodology developed by Professor Alkire and Professor James Foster, an OPHI Research Associate and Professor of Economics and International Affairs at George Washington University. That methodology is also used to construct several national measures of poverty (for example in Mexico, Colombia, Bhutan, Chile, Costa Rica and El Salvador). 

For more information on the MPI, including infographics, briefings, data and other resources, please see www.ophi.org.uk/multidimensional-poverty-index. 

Visit OPHI’s online interactive databank for maps and graphs showing the level and composition of multidimensional poverty across countries and sub-national regions: http://www.ophi.org.uk/multidimensional-poverty-index/mpi-data-bank/. 

Calculation of poverty using the Multidimensional Poverty Index (MPI) 

A person is identified as ‘multidimensionally poor’ if she or he is deprived in one-third or more of ten (weighted) indicators. The MPI of a country or region is calculated by multiplying the proportion of poor people (H) by the average share of deprivations that poor people face at the same time, i.e. the average intensity of their poverty (A). In other words, MPI=HxA. By directly measuring the different types of poverty in each household, the MPI captures how people experience different deprivations simultaneously. See Alkire, S., Jindra, C., Robles, G. and Vaz, A. (2016). “Multidimensional Poverty Index - Summer 2016: Brief Methodological Note and Results.” OPHI Briefing number 40, University of Oxford, June. 

Data sources and constraints 

The MPI relies on the most recent data available, mainly from two datasets that are publicly available and comparable for most developing countries: USAID’s Demographic and Health Survey (DHS) and UNICEF’s Multiple Indicators Cluster Survey (MICS). It also uses national and PAPFAM and national surveys.