A Multinomial Asymptotic Representation of Zenga's Discrete Index, its Influence Function and Data-driven Applications: Accepted - March 2023

Tchilabalo Abozou Kpanzou; Diam Ba; Gandasor Bonyiri Onesiphore Da; Gane Samb Lo

Forthcoming

A Multinomial Asymptotic Representation of Zenga's Discrete Index, its Influence Function and Data-driven Applications

Accepted - March 2023

Authors

Tchilabalo Abozou Kpanzou University of Kara https://orcid.org/0000-0003-3921-3962
Diam Ba Gaston Berger University
Gandasor Bonyiri Onesiphore Da Gaston Berger University
Gane Samb Lo Gaston Berger University https://orcid.org/0000-0002-8968-8109

Keywords:

inequality measures, asymptotic behaviour, asymptotic representations, functional empirical process

Abstract

In this paper, we consider the Zenga index, one of the most recent inequality indices. We keep the finite-valued original form and address the asymptotic theory. The asymptotic normality is established through a multinomial representation. The Influence function is also given. The results are simulated and applied to Senegalese income data.

Downloads

FP_REVSTAT-523-2023_mar4

Published

2023-03-28

How to Cite

Kpanzou, T. A., Ba, D., Da, G. B. O., & Lo, G. S. (2023). A Multinomial Asymptotic Representation of Zenga’s Discrete Index, its Influence Function and Data-driven Applications: Accepted - March 2023. REVSTAT-Statistical Journal. Retrieved from https://revstat.ine.pt/index.php/REVSTAT/article/view/523