Zenga′s New Index of Economic Inequality, Its Estimation, and an Analysis of Incomes in Italy
Author(s) -
Francesca Greselin,
Leo Pasquazzi,
Ričardas Zitikis
Publication year - 2010
Publication title -
journal of probability and statistics
Language(s) - English
Resource type - Journals
eISSN - 1687-9538
pISSN - 1687-952X
DOI - 10.1155/2010/718905
Subject(s) - index (typography) , inequality , estimation , econometrics , economic inequality , statistical inference , economics , income distribution , distribution (mathematics) , mathematics , statistics , computer science , mathematical analysis , management , world wide web
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)
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom