Fuzzy Targeting Indices and Orderings

The targeting efficiency and the coverage of social programs for the poor are typically analyzed by partitioning the total population in four mutually exclusive groups: the poor who benefit from a program or policy, the poor who do not benefit, the non-poor who benefit, and the non-poor who do not benefit. While useful, this partition into crisp sets may not capture the difficulty of identifying the poor. This paper presents a method that consists of using a membership function to identify to what extent households can be considered as poor or non-poor. The method builds on fuzzy sets theory whereby the definition of the boundaries of a set, say the poor or the non-poor, is fuzzy. We characterize the properties that membership functions should have, and we test for the robustness of targeting performance comparisons to the choice of the membership function