A functional derivative useful for the linearization of inequality indexes in the design-based framework
Methodology
2014-02-17 v1
Abstract
Linearization methods are customarily adopted in sampling surveys to obtain approximated variance formulae for estimators of nonlinear functions of finite population totals - such as ratios, correlation coefficients or measures of income inequality - which can be usually rephrased in terms of statistical functionals. In the present paper, by considering the Deville (1991) approach stemming on the concept of design-based influence curve, we provide a general result for linearizing large families of inequality indexes. As an example, the achievement is applied to the Gini, the Amato, the Zenga and the Atkinson indexes, respectively.
Keywords
Cite
@article{arxiv.1402.3478,
title = {A functional derivative useful for the linearization of inequality indexes in the design-based framework},
author = {Lucio Barabesi and Giancarlo Diana and Pier Francesco Perri},
journal= {arXiv preprint arXiv:1402.3478},
year = {2014}
}