The world’s poorest people don’t always live where you’d expect
7 January 2015
Poverty measures reported at the national level don’t provide a full picture of where the world’s poorest live. New research from the Oxford Poverty and Human Development Initiative (OPHI), based at the University of Oxford, has revealed that nearly 60 per cent of people living in the world’s poorest regions are not actually in the least developed countries.
Measuring the different things that people are deprived of, researchers have identified regions within countries where the poorest people live. The global Multi-dimensional Poverty Index (MPI) reflects the combined simultaneous disadvantages poor people experience across different areas of their lives, including education, health and living standards. If people are deprived in at least one-third of ten weighted indicators, they are identified as multi-dimensionally poor. This poverty measure, MPI, complements income poverty measures.
Using the January 2015 updates of the MPI released today, the study team looked at more than 230 regions within countries where multidimensional poverty is at least as high as the 25 poorest Least Developed Countries (LDCs) identified by the United Nations (Economic and Social Council). They found that nearly 60 per cent of the 768 million multi-dimensionally poor people in these subnational regions live in countries that are not classified as LDCs, and all but one non-LDC region were in countries classed as middle-income: India, Nigeria, Pakistan, Cameroon, Cote D’Ivoire, Ghana, Namibia and the Republic of Congo.
The findings show that pockets of deprivation are missed in aggregate statistics. For example, in Doula, the largest city in Cameroon, 6.7 per cent of people are multi-dimensionally poor; yet elsewhere in the same country, in the Extrême-Nord, nearly 87 per cent are measured as MPI-poor.
The researchers say the striking disparity would be hidden if we only relied on the figure for the national average, which shows that 46 per cent of the population in Cameroon are MPI-poor. While Niger has the highest percentage of MPI-poor, with 89.3 per cent of its entire population found to be living in multidimensional poverty, using the same MPI measure the five poorest regions in the world are in Chad and Burkina Faso. The OPHI researchers found that the very poorest region of all the 803 regions studied is Salamat in Chad, where nearly 98 per cent of its 354,000 inhabitants are measured as multi-dimensionally poor.
Dr Sabina Alkire, Director of OPHI, said: ‘The MPI enables us to examine poverty within regions of a country as well as nationally, and compare the interlocking deprivations people experience. It can reveal experiences across rural and urban areas, and across different ethnic populations. We measure different types of deprivation together – such as malnutrition, poor sanitation, a lack of housing or schooling – and every person matters.’
‘Our findings highlight the value of having good quality, up-to-date and detailed survey data to reveal what life is really like for the poorest section of populations. I'm particularly glad that of the 30 low income countries covered, we can compare the MPI across regions within countries for all but one.’
The United Nations has stressed the need to identify where the poorest live in order to ‘leave no-one behind’. The researchers argue that their poverty measure, the MPI, is essential to accurately target resources and policies where they are needed most.
The updated global Multidimensional Poverty Index now covers 110 developing countries, and 803 regions in 72 of these countries. The analysis is of data ranging from 2002 to 2014, mainly collected by UNICEF's Multiple Indicators Cluster Survey and USAID's Demographic and Health Survey. The MPI is published in UNDP's Human Development Reports.
For the briefing paper or more information, contact the University of Oxford News Office on +44 (0) 1865 280534 or email firstname.lastname@example.org
Alternatively, contact Claire Battye (Research Communications Officer, OPHI) on +44 (0)1865 271528 or email@example.com
Notes to Editors:
A briefing paper on the latest global MPI results, ‘High visibility: How disaggregated metrics help to reduce multidimensional poverty’, will be available to download from the OPHI website from 7 January 2015.
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 the World Health Organisation’s World Health Survey (WHS), and national surveys for six countries.
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 Dr 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 and the Philippines). For more information, 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., Conconi, A., Robles, G. and Seth, S. (2015) ‘Multidimensional Poverty Index January 2015: Brief Methodological Note and Results’, Oxford Poverty and Human Development Initiative, University of Oxford
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.