Some improvement on non-parametric estimation of income distribution and poverty index
Statistics Theory
2019-09-18 v2 Methodology
Statistics Theory
Abstract
In this paper, we propose an estimator of Foster, Greer and Thorbecke class of measures , where is the poverty line, is the probabily density function of the income distribution and is the so-called poverty aversion. The estimator is constructed with a bias reduced kernel estimator. Uniform almost sure consistency and uniform mean square consistenty are established. A simulation study indicates that our new estimator performs well.
Keywords
Cite
@article{arxiv.1909.06476,
title = {Some improvement on non-parametric estimation of income distribution and poverty index},
author = {Youssou Ciss and El hadji Deme and Hamza Dhaker},
journal= {arXiv preprint arXiv:1909.06476},
year = {2019}
}