An innovative approach to measure measuring multidimensional poverty: A synthesis method

Abstract

This paper presents a new approach to measure multidimensional poverty, combining the strengths of the Fuzzy Set method and the Alkire and Foster method, and addresses some of their limitations. The approach applies the Fuzzy Set method to resolve the discontinuity problem that arises when the latter is used in the Alkire and Foster method to identify the multidimensionally poor people. The resultant process satisfies poverty axioms of a good poverty measure. It also incorporates some s statistical techniques in selecting indicators and computing weights for the membership function. The empirical assessment is done to primary data, collected from the Uva province of Sri Lanka, an economically, neglected comprising of people representing various socio-economic backgrounds. This study examines poverty under three main dimensions; material, social dimensions and human capital. The results reveal that, 42.3 percent of people in the Uva province have a propensity to poverty. The incidence of multidimensional poverty is 56 percent and the intensity is 48.6 percent. The adjusted fuzzy headcount index is 27.2 percent. Interestingly, the highest contribution to overall poverty comes from deprivation by social dimensions. The application of the this method undoubtedly would encourage the analysis of further research on multidimensional poverty.