Zenga’s new index of economic inequality, its estimation, and an analysis of incomes in Italy
AbstractFor 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 challenging 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, M. Zenga has recently 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 derive desired statistical inferential results, explore their performance in a simulation study, and then employ the results to analyze data from the Bank of Italy’s Survey on Household Income and Wealth.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 17147.
Date of creation: Aug 2009
Date of revision:
Zenga index; lower conditional expectation; upper conditional expectation; conﬁdence interval; Bonferroni curve; Lorenz curve; Vervaat process.;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-09-19 (All new papers)
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- Matti Langel & Yves Tillé, 2012. "Inference by linearization for Zenga’s new inequality index: a comparison with the Gini index," Metrika, Springer, Springer, vol. 75(8), pages 1093-1110, November.
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