For at least a century academics and governmental researchers have been developing measures that would aid them in understanding income distributions, their differences with respect to geographic regions, and changes over time periods. It is a fascinating area due to a number of reasons, one of them being the fact that different measures, or indices, are needed to reveal different features of income distributions. Keeping also in mind that the notions of `poor' and `rich' are relative to each other, Zenga (2007) proposed a new index of economic inequality. The index is remarkably insightful and useful, but deriving statistical inferential results has been a challenge. For example, unlike many other indices, Zenga's new index does not fall into the classes of L-, U-, and V-statistics. In this paper we state desired statistical inferential results, explore their performance in a simulation study, and then use the results to analyze data from the Bank of Italy Survey on Household Income and Wealth (SHIW)

Greselin, F., Pasquazzi, L., Zitikis, R. (2010). Asymptotic Theory for Zenga's New Index of Economic Inequality. In Proceedings of the 45th Scientific Meeting of the Italian Statistical Society. Padua : CLEUP - Padova.

Asymptotic Theory for Zenga's New Index of Economic Inequality

Greselin, F;Pasquazzi, L;
2010

Abstract

For at least a century academics and governmental researchers have been developing measures that would aid them in understanding income distributions, their differences with respect to geographic regions, and changes over time periods. It is a fascinating area due to a number of reasons, one of them being the fact that different measures, or indices, are needed to reveal different features of income distributions. Keeping also in mind that the notions of `poor' and `rich' are relative to each other, Zenga (2007) proposed a new index of economic inequality. The index is remarkably insightful and useful, but deriving statistical inferential results has been a challenge. For example, unlike many other indices, Zenga's new index does not fall into the classes of L-, U-, and V-statistics. In this paper we state desired statistical inferential results, explore their performance in a simulation study, and then use the results to analyze data from the Bank of Italy Survey on Household Income and Wealth (SHIW)
Capitolo o saggio
Zenga index, confidence interval, Lorenz curve, Vervaat process, measuring poverty and inequality
English
Proceedings of the 45th Scientific Meeting of the Italian Statistical Society
2010
978-88-6129-566-7
CLEUP - Padova
Greselin, F., Pasquazzi, L., Zitikis, R. (2010). Asymptotic Theory for Zenga's New Index of Economic Inequality. In Proceedings of the 45th Scientific Meeting of the Italian Statistical Society. Padua : CLEUP - Padova.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/17702
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