Income distribution in Italy: A nonparametric analysis

Maria Grazia Pittau and Roberto Zelli

Statistical Methods & Applications, 2001, vol. 10, issue 1, No 14, 175-189

Abstract: Abstract Using kernel density estimation, this paper describes the real income distribution and how it evolved over time in Italy. Data are cross-sectional samples from the population of Italian households during the period 1987–1998. A non parametric test is applied to asses whether the observed changes in the distribution are statistically significant, while the presence of more than one mode in the distributions is investigated by a bootstrap test. Empirical results show that the Italian income distribution significantly changed over time, accompanied by a decreasing inequality pattern until 1991 and a subsequent rise. No marked income gains were perceived, while the real “losers” of the decade seem to be households in the middle-upper income range.

Keywords: Income distribution; kernel density estimation; multimodality test (search for similar items in EconPapers)
Date: 2001
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://link.springer.com/10.1007/BF02511647 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:stmapp:v:10:y:2001:i:1:d:10.1007_bf02511647

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10260/PS2

DOI: 10.1007/BF02511647

Access Statistics for this article

Statistical Methods & Applications is currently edited by Tommaso Proietti

More articles in Statistical Methods & Applications from Springer, Società Italiana di Statistica
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().