Measuring Multidimensional Poverty: a Global Assessment of Data Availability and Data Gaps
Timely and disaggregated data are essential for effective policy-making, and achieving the ambitious goals outlined in Agenda 2030. To this date, over 30 countries launched national Multidimensional Poverty Indices (MPIs) to monitor SDG 1.2.2 and eradicate poverty in all its forms. In addition, figures on acute multidimensional poverty in over 100 developing countries are published regularly using the internationally comparable global Multidimensional Poverty Index. But there is a need to measure less acute forms of poverty, as well as to cover high income countries.
While advancements have been made on using administrative or census data for measuring multidimensional poverty, most national MPIs and the global MPI relies on household survey data for a comprehensive and timely assessment of poverty, and its changes over time. This presentation reviews the current data landscape with a focus on national and cross-national multi-topic household surveys that might be used to develop a genuinely global multidimensional index covering less acute forms of poverty. It presents a comprehensive and detailed overview of the available resources and identifies important gaps in existing survey data. In addition, the presentation assess the feasibility of a new global moderate multidimensional poverty index with expanded indicator coverage and the inclusion of developed countries, while retaining frequent updates and subnational disaggregation. The presentation proposes multiple options for a global ‘moderate MPI’ and evaluates each according to a set of common criteria. It also proposes a set of measures that could be developed exclusively for high-income countries. Last, the presentation will propose a set of recommendations for improving the availability and coverage of nationally representative household survey data – an essential resource for measuring poverty in all its dimensions, and achieving the overall goal of no poverty.
Fanni Kovesdi, Oxford Poverty and Human Development Initiative, University of Oxford
Timely and disaggregated data are essential for effective policy-making, and achieving the ambitious goals outlined in Agenda 2030. To this date, over 30 countries launched national Multidimensional Poverty Indices (MPIs) to monitor SDG 1.2.2 and eradicate poverty in all its forms. In addition, figures on acute multidimensional poverty in over 100 developing countries are published regularly using the internationally comparable global Multidimensional Poverty Index. But there is a need to measure less acute forms of poverty, as well as to cover high income countries.
While advancements have been made on using administrative or census data for measuring multidimensional poverty, most national MPIs and the global MPI relies on household survey data for a comprehensive and timely assessment of poverty, and its changes over time. This presentation reviews the current data landscape with a focus on national and cross-national multi-topic household surveys that might be used to develop a genuinely global multidimensional index covering less acute forms of poverty. It presents a comprehensive and detailed overview of the available resources and identifies important gaps in existing survey data. In addition, the presentation assess the feasibility of a new global moderate multidimensional poverty index with expanded indicator coverage and the inclusion of developed countries, while retaining frequent updates and subnational disaggregation. The presentation proposes multiple options for a global ‘moderate MPI’ and evaluates each according to a set of common criteria. It also proposes a set of measures that could be developed exclusively for high-income countries. Last, the presentation will propose a set of recommendations for improving the availability and coverage of nationally representative household survey data – an essential resource for measuring poverty in all its dimensions, and achieving the overall goal of no poverty.
Fanni Kovesdi, Oxford Poverty and Human Development Initiative, University of Oxford