Multidimensional Poverty Measures as Relevant Policy Tools

Poverty measurement is strewn with imperfection. And yet, even understanding limitations such as data quality and coverage, measures of multidimensional poverty have proven to be relevant policy tools. This paper first situates multidimensional poverty measures in the Sustainable Development Goals, which seek to End Poverty *in all its forms and dimensions*. It then explains a key distinguishing feature between multidimensional and monetary poverty measures, namely, that multidimensional poverty measures have an associated 'information platform' which provides the deprivations in each indicator, as well as the headcount ratio or poverty rate, and the intensity of poverty overall, and does so both nationally and for all groups by which the dataset can be disaggregated. Furthermore, multiple poverty lines are often set and reported. Bearing this informational richness in mind, the paper then canvasses the main ways that policy actors are using multidimensional poverty indices (MPIs) and their associated informational platform to shape policy. For example, a permanent official MPI complements the national monetary poverty measure, often drawing attention to different groups of poor persons. Also, the MPI design often includes participatory exercises and expert consultations, thus catalysing a national conversation about what is poverty. Like any national statistic, the MPI is used to monitor change and show the trend in a phenomenon of public importance. Further, the MPI, with its disaggregation by group and breakdown by indicator, is often used as part of the budget allocation formulae, for example, across subnational regions. The MPI is also used for targeting in two senses: targeting the poorest areas or social groups, and also (using a different dataset), targeting households that are eligible to benefit from certain schemes. One of the most powerful roles of the MPI is to support policy coordination which - in line with the SDG emphasis - facilitates integrated multisectoral policies that can be more cost-effective and high-impact methods for addressing interconnected deprivations and managing change. Finally, for many countries, the MPI is part of a new emphasis on the transparency and accountability of statistics, for example by posting data tables, or even datasets and computer algorithms online so students and researchers can fruitfully join the intellectual task of finding better ways to confront human disadvantage and suffering. The paper closes by referring to some new research areas that might further enrich this unfolding discipline.