Fuzzy set theoretic applications in poverty research.

The logic of fuzzy sets derived from the mathematical theory developed by Zadeh (1965) has not only influenced the development of fuzzy set qualitative comparative analysis (fs/QCA), but has also found entry into poverty research. The aim of this paper is to point the reader to these parallel developments. Poverty researchers necessarily have to make two methodological choices which are always contestable: the identification of a poverty line or threshold, the identification problem, and the choice of a unit of analysis as well as of a measure, the aggregation problem. Current theoretical and practical contributions to poverty research have pointed to the vagueness of the concept itself and the complexity of its measurement and have made use of fuzzy set logic to address these challenges. As shall be argued, fuzzy set theory provides a solution or at least a less arbitrary way forward to address these problems and is particularly suitable for the analysis of multidimensional poverty. Using unique household level data from two villages of Andhra Pradesh, India from 2007, the paper provides an illustrative example of what steps to take to derive a multidimensional poverty index based on fuzzy set theory and discusses the distinct advantages such a procedure offers for policy analysis and evaluation purposes. [ABSTRACT FROM AUTHOR]