Abstract
Fuzzy set theory has become increasingly popular for deriving uni- and multi-dimensional poverty estimates. In recent years, various authors have proposed different approaches to defining membership functions, resulting in the development of various fuzzy poverty indices. This paper introduces a new R package called FuzzyPovertyR, designed for estimating fuzzy poverty indices. The package is demonstrated by using it to estimate three fuzzy poverty indices - one multi- and two uni-dimensional - at the regional level (NUTS 2) in Italy. The package allows users to select from a range of membership functions and includes tools for estimating the variance of these indices by the ad-hoc Jack-Knife repeated replication procedure or by naive and calibrated non-parametric bootstrap methods.