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

## TL;DR

This paper develops an asymptotic normality framework for Zenga's inequality index using multinomial representation, providing influence functions and demonstrating applications with real data.

## Contribution

It introduces a multinomial asymptotic representation for Zenga's index, along with influence functions and data-driven applications, advancing the theoretical understanding of this inequality measure.

## Key findings

- Asymptotic normality of Zenga's index established
- Influence function derived for the index
- Applications demonstrated with Senegalese data

## Abstract

In this paper, we consider the Zenga index, one of the most recent inequality index. 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. Th results are simulated and applied to Senegalese data.