Distribution-free estimation of the Gini inequality index: the kernel method approach

Abstract

In this paper a non-parametric approach to the estimation of the Gini inequality index is introduced. The basic idea consists in taking first a preliminary estimation of the population density function, and then in computing the corresponding inequality index. Statistical properties of the estimator introduced are studied, with particular reference to the case of large samples (usually available from statistical agencies). As a by-product, approximated confidence intervals are obtained.