A new methodology for multidimensional poverty measurement based on the capability approach

• We deal with the issues of several different dimensions of uncertainty and we solve the aggregation issues.
• We assess people's capabilities in order to make well-informed decisions about policies, programs and projects.
• Meaningful measurement allows to design and identify preferable alternatives with respect to complex policy issues.
• We deal with the issue of different poverties and develop a better operational definition of poverty.
• Poverty measurement is a decision problem.

We propose a methodology based on the use of clustering techniques derived from data analysis and multi-attribute decision analysis methods aiming at purposeful multidimensional poverty measurement. Our contribution to methodological knowledge insists on the necessity to build “meaningful measurements” for policy making and policy implementation. Our standpoint underlines the necessity to consider the problem of poverty measurement as a decision problem and to tackle its measurement issue with that in mind. We also show that such an exercise can be useful to develop a better operational definition of poverty and to solve the aggregation issues.