Multidimensional Poverty Index

Multidimensional Poverty Index
Name	Multidimensional Poverty Index
Established	2010
Type	Index
Developed by	Oxford Poverty and Human Development Initiative; United Nations Development Programme
Area	International development; poverty measurement

Multidimensional Poverty Index The Multidimensional Poverty Index (MPI) is a composite measure designed to capture overlapping deprivations in health, education, and living standards across populations. It complements income-based metrics by integrating indicators that reflect material and human well-being, and it has been produced and promoted by research and policy institutions to inform global development efforts. The MPI has been used alongside major international processes and actors to target interventions and track progress toward development targets.

Overview

The MPI was developed by the Oxford Poverty and Human Development Initiative in collaboration with the United Nations Development Programme and has been discussed in venues involving World Bank, International Monetary Fund, World Health Organization, United Nations General Assembly, United Nations Children's Fund, and regional bodies like the African Union and Association of Southeast Asian Nations. It synthesizes indicators drawn from nationally representative surveys such as the Demographic and Health Surveys and the Multiple Indicator Cluster Surveys, and it complements metrics used in frameworks like the Sustainable Development Goals and analyses by institutions including United Nations Economic Commission for Europe and Economic Commission for Latin America and the Caribbean. The MPI has been cited in national policy debates in countries ranging from India and Brazil to Kenya and Philippines, and referenced in research from universities such as University of Oxford, Harvard University, London School of Economics, and Stanford University.

Methodology

The MPI aggregates deprivations across dimensions and indicators with a counting approach inspired by multidimensional measurement literature associated with scholars connected to Amartya Sen and institutions like the Institute for Development Studies and International Labour Organization. It assigns weights to indicators across dimensions—commonly health, education, and living standards—and classifies individuals or households as multidimensionally poor when their weighted deprivation score exceeds a predefined cutoff. The methodology builds on statistical techniques used by organizations such as United Nations Statistics Division, OECD, and analytical work from think tanks including Brookings Institution and Carnegie Endowment for International Peace. MPI calculations typically rely on survey modules developed by Measure DHS and the UNICEF MICS program, and the index has been adapted for subnational analysis by research centers like the Overseas Development Institute and policy units in ministries of finance and planning across countries like Mexico, South Africa, and Indonesia.

Global and Regional Findings

Global MPI reports have highlighted regional patterns and country-level heterogeneity, with large populations identified as multidimensionally poor in regions including Sub-Saharan Africa, South Asia, and parts of Latin America and the Caribbean. Country-specific findings have been discussed in policy forums such as the G20 and national planning commissions in India and Nigeria, and have informed regional strategies in the Economic Community of West African States and South Asian Association for Regional Cooperation. Comparative findings draw on data collated by agencies like the International Fund for Agricultural Development and the United Nations Population Fund, and have been referenced in analyses produced by the Asian Development Bank, Inter-American Development Bank, and European Commission to inform regional development programming.

Policy Use and Impact

Policymakers and international organizations have used MPI results to target social protection programs, guide budget allocations, and prioritize interventions in sectors overseen by ministries and agencies such as Ministry of Health (India), national education ministries, and social safety net agencies. MPI-informed approaches have influenced initiatives supported by Bill & Melinda Gates Foundation, Global Partnership for Education, and Gavi, the Vaccine Alliance, and have been included in evaluations by development funders like United Kingdom Department for International Development and United States Agency for International Development. Civil society organizations and advocacy groups such as Oxfam, CARE International, and Save the Children have used MPI evidence in campaigns and program design, while parliamentary committees and national audit offices in multiple countries have referenced MPI findings in oversight and accountability mechanisms.

Criticisms and Limitations

Critics from academic and policy communities including scholars affiliated with Massachusetts Institute of Technology, Princeton University, and Yale University have raised concerns about indicator selection, weighting schemes, and the normative choices underpinning the cutoff for poverty classification. Econometricians and statisticians from institutions like University of Chicago and Columbia University have debated the aggregation rules and the sensitivity of MPI rankings to alternate specifications. Other critiques concern comparability across countries highlighted by analysts at United Nations Educational, Scientific and Cultural Organization and International Labour Organization, and implementation challenges flagged by national statistical offices in countries such as Pakistan and Bangladesh. Civil society commentators from Amnesty International and Human Rights Watch have critiqued the index for not fully capturing rights-based dimensions emphasized in international treaties such as the Universal Declaration of Human Rights.

Data Sources and Measurement Challenges

MPI estimates depend on household surveys produced by programs like Measure DHS and UNICEF MICS, census data managed by national statistical offices, and administrative records held by ministries partnering with agencies such as World Food Programme and United Nations High Commissioner for Refugees. Data limitations include sampling gaps, recall bias, and infrequent survey rounds, issues also encountered in datasets curated by the International Household Survey Network and repositories maintained by World Bank Microdata Library. Measurement challenges include harmonizing indicator definitions across instruments, aligning survey modules used in countries such as Ethiopia and Venezuela, and integrating geospatial data streams employed by research teams from NASA and European Space Agency for subnational targeting. Methodological refinements have required collaborations with statistical authorities like the United Nations Statistics Division and capacity-building support from regional development banks including the African Development Bank and Asian Development Bank.

Category:Poverty measurement