Poverty index identifies ‘star’ developing countries in Africa and Asia

Reductions in income poverty in many developing countries are being outstripped by reductions in multidimensional poverty – overlapping deprivations in health, education and living standards. That’s according to a new study by Oxford University, which is the first to track multidimensional poverty over time. 

The study highlights the importance of measuring multidimensional as well as income poverty, in order to identify effective policy interventions and monitor progress towards targets such as the Millennium Development Goals. 

Nepal, Rwanda and Bangladesh were the ‘star performers’ of the 22-country study, with the largest absolute reductions in multidimensional poverty, followed by Ghana, Tanzania, Cambodia and Bolivia. 

Nepal made strong headway in reducing both multidimensional and income poverty, according to the Oxford Poverty and Human Development Initiative (OPHI), the research centre at Oxford University that conducted the study. And Rwanda, Bangladesh, Ghana and Bolivia all reduced multidimensional poverty faster than income poverty. 

Other countries, such as Cambodia, Uganda, and Armenia, saw income poverty cut faster than multidimensional poverty, demonstrating that the two do not necessarily move together. 

The poverty measure used by OPHI – the Multidimensional Poverty Index, or MPI – captures the overlapping deprivations that poor people face, for example in nutrition, education and sanitation. If people are deprived in a third or more of ten (weighted) indicators, the global index identifies them as ‘MPI poor’. 

The release of OPHI’s findings on changes in poverty over time follows the publication of the MPI in the UN Development Programme’s flagship Human Development Report (HDR) for 2013. The global MPI, which was developed by OPHI and the UNDP in 2010, has been published in the HDR ever since, and assesses multidimensional poverty in 104 countries for which data are available. 

In 2013, OPHI found that a total of 1.6 billion people are living in multidimensional poverty – more than 30% of the combined populations of the 104 countries analysed. 

The top performing countries in OPHI’s study reduced not only the number of people experiencing poverty, but also the intensity of their poverty, so that even poor people were on average less poor – deprived in fewer things at the same time – than they had been before. 

“Using this measure, we found that reductions in intensity – the percentage of deprivations people experience at the same time – were strongest in relatively poorer countries, such as Ethiopia, Malawi and Senegal,” said OPHI’s Director, Dr Sabina Alkire. “This highlights the vital importance of using MPI, not just the percentage of poor people, to incentivize and celebrate progress and provide a more balanced picture of poverty even in the poorest places.” 

Countries managed to reduce multidimensional poverty through tackling a range of different deprivations, with no single formula for success emerging from the study. Nepal did the best in areas like nutrition, child mortality, electricity, improved flooring and assets. Rwanda showed the biggest improvement in sanitation and water, and Bangladesh did best in improving sanitation and school attendance. 

The MPI can also be broken down to reveal the varying rates of progress in different regions of a country or among different social groups. For example, in Nepal, although it had an outstanding overall performance, three of the 13 regions lagged behind the rest of the country, with no statistically significant reduction in MPI poverty. By contrast, Rwanda and Bangladesh achieved significant reductions in both the scale and intensity of multidimensional poverty in every one of their regions. 

‘This ability of the MPI to reveal inequalities at a regional level, as well as between social groups, makes it a vital tool for policymakers,’ said Dr Suman Seth, one of OPHI’s research team. ‘The global MPI allows us to compare people’s poverty and see in what ways they are deprived, in order to address these interconnected deprivations and target interventions more accurately.’ 

Where is all this leading? The good news is that in some countries, if progress continues at the same rate, current generations may see the eradication of acute multidimensional poverty. For example, if the study’s 'star' countries, Nepal, Rwanda, and Bangladesh, continue to reduce poverty at the current rate, they will halve MPI in less than 10 years and eradicate it in 20. 

However, the picture in other countries looks much less positive. ‘At the current rate of reduction, it will take Ethiopia 45 years to halve multidimensional poverty; in other words, to achieve poverty levels equivalent to those Nigeria has now,’ said OPHI’s Dr José Manuel Roche, who calculated the predictions. 

‘Based on the same assumptions, it will take India 41 years and Malawi 74 years to eradicate acute poverty as measured by the MPI. But we hope that by providing a more complete and balanced picture, these measures will help spur the eradication of multidimensional poverty.’ 

For interviews and more information: 

University of Oxford Press Office: +44 (0)1865 280534, press.office@admin.ox.ac.uk 

Emma Feeny, Research Communications Officer, OPHI: +44 (0)1865 271528, emma.feeny@qeh.ox.ac.uk 

NOTES FOR EDITORS 

Story not to be published before embargo lifts at 0:01am (GMT) Monday 18 March 2013 

Data sources and constraints 

The MPI relies on the most recent data available, mainly from three datasets that are publicly available and comparable for most developing countries: USAID’s Demographic and Health Survey (DHS), UNICEF’s Multiple Indicators Cluster Survey (MICS), and the WHO’s World Health Survey (WHS). OPHI’s analysis of multidimensional poverty reduction in India was done using National Family Health Survey (NFHS) datasets. Unfortunately it is not currently possible to update this analysis because the dataset has not been repeated; nor do the National Sample Survey datasets include the required questions. 

Background to the Multidimensional Poverty Index (MPI) 

The MPI was created by OPHI Director Sabina Alkire and OPHI Research Associate Maria Emma Santos, now at Universidad Nacional del Sur and CONICET, Argentina. In 2013, the MPI has been widely updated and expanded, including substantial new analyses of changes to poverty over time and where the world’s poorest billion people really live. The MPI 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. For more information, including all MPI 2013 materials, please see www.ophi.org.uk/multidimensional-poverty-index. 

Calculation of poverty using the Multidimensional Poverty Index (MPI) 

A person is identified as ‘multidimensionally poor’ if he or she is deprived in one-third or more of ten (weighted) indicators. The MPI of a country or region is the product of the proportion of poor people (H) and 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, Conconi and Roche (2013) ‘Multidimensional Poverty Index 2013: Brief Methodological Note and Results’, at www.ophi.org.uk/multidimensional-poverty-index. 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. Alkire and James Foster (see above) developed the Alkire Foster counting approach to multidimensional measurement, which is used to calculate the MPI as well as to construct national measures of poverty (for example in Mexico and Colombia), of wellbeing (in Bhutan), and to measure women’s empowerment in agriculture. For more information about OPHI, please visit www.ophi.org.uk.