Multidimensional Poverty Measures: New Potential

Draft: please do not cite without permission. When poverty measures reflect the experiences of poor people, then this empowers those working to reduce poverty to do so more effectively and efficiently. The literature on Multidimensional Poverty Measures has surged forward in the last decade. This paper describes the broad directions of change, then presents a new and very simple measurement methodology for multidimensional poverty. It illustrates its application for poverty measurement, for targeting of social protection programmes, for monitoring and evaluation, and for poverty analysis. It also identifies how participatory input from communities can be directly reflected in the poverty measure. The concept of multidimensional poverty has risen to prominence among researchers and policymakers. The compelling writings of Amartya Sen, participatory poverty exercises in many countries, and the Millennium Development Goals (MDGs) all draw attention to the multiple deprivations suffered by many of the poor and the interconnections between these deprivations. A key task for research has been to develop a coherent framework for measuring multidimensional poverty that builds on the techniques developed to measure unidimensional (monetary) poverty and that can be applied to data on other dimensions. Effective multidimensional poverty measures have immediate practical applications. They can be used: to replace, or supplement, or combine with the official measures of income poverty that are reported each year, and so to provide an annual summary measure of all relevant goals at a time. This would redefine who is poor and directly affect government services to reduce poverty. to monitor the level and composition of poverty, and the reduction of poverty, over time. The measure not only provides a change in aggregate, but can also be broken down by dimension to identify the dimensions in which deprivations have been reduced the most. This would lead to better understanding of what policies work and what practical applications need to be modified. to evaluate the impact of programmes. A multidimensional measure can provide a summary of trend information for the selected dimensions across different project areas – and again the summary measure can be decomposed easily. This would lead to better evaluation data of programme results. to target the poorest more effectively. The new multidimensional measures are very well designed for targeting social protection schemes to families that suffer multiple deprivations. 1 This is accomplished by identifying the families that are multiply deprived. Given that data are often of poor quality, these methods …