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 derive 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). Zenga's new index of economic inequality, its estimation, and an analysis of incomes in Italy. JOURNAL OF PROBABILITY AND STATISTICS, 2010 [10.1155/2010/718905].
|Citazione:||Greselin, F., Pasquazzi, L., & Zitikis, R. (2010). Zenga's new index of economic inequality, its estimation, and an analysis of incomes in Italy. JOURNAL OF PROBABILITY AND STATISTICS, 2010 [10.1155/2010/718905].|
|Tipo:||Articolo in rivista - Articolo scientifico|
|Carattere della pubblicazione:||Scientifica|
|Presenza di un coautore afferente ad Istituzioni straniere:||Si|
|Titolo:||Zenga's new index of economic inequality, its estimation, and an analysis of incomes in Italy|
|Autori:||Greselin, F; Pasquazzi, L; Zitikis, R|
|Data di pubblicazione:||2010|
|Rivista:||JOURNAL OF PROBABILITY AND STATISTICS|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1155/2010/718905|
|Appare nelle tipologie:||01 - Articolo su rivista|
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