A new fuzzy one-dimensional poverty index based on a relative entropy

In order to avoid the usual binary definition of poverty, a fuzzy set approach to poverty measurement has been used. The poor are typically analyzed by partitioning the total population in three mutually exclusive groups around the poverty line. This builds on fuzzy sets theory whereby the definition of the threshold of who is poor or non-poor, is fuzzy. This paper presents a method that consists, in the first step, of using a membership function and a confidence interval of poverty line to identify to what extent households can be considered as poor or non-poor. According to this membership function we propose a one-dimensional poverty index by using an information function. The methodology proposed here is illustrated by means of the Tunisia case.