Pareto's Law of Income Distribution: Evidence for Grermany, the United Kingdom, and the United States

Fabio Clementi and Mauro Gallegati

Microeconomics from University Library of Munich, Germany

Abstract: We analyze three sets of income data: the US Panel Study of Income Dynamics (PSID), the British Household Panel Survey (BHPS), and the German Socio-Economic Panel (GSOEP). It is shown that the empirical income distribution is consistent with a two-parameter lognormal function for the low-middle income group (97\%-99\% of the population), and with a Pareto or power law function for the high income group (1\%- 3\% of the population). This mixture of two qualitatively different analytical distributions seems stable over the years covered by our data sets, although their parameters significantly change in time. It is also found that the probability density of income growth rates almost has the form of an exponential function.

Keywords: Personal income; Lognormal distribution; Pareto's law; Income growth rate (search for similar items in EconPapers)
JEL-codes: D1 D2 D3 D4 (search for similar items in EconPapers)
Pages: 16 pages
Date: 2005-05-18
New Economics Papers: this item is included in nep-mic
Note: Type of Document - ps; pages: 16
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (40)

Downloads: (external link)
https://econwpa.ub.uni-muenchen.de/econ-wp/mic/papers/0505/0505006.ps.gz (application/postscript)

Related works:
Working Paper: Pareto's Law of Income Distribution: Evidence for Germany, the United Kingdom, and the United States (2006)
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:wpa:wuwpmi:0505006

Access Statistics for this paper

More papers in Microeconomics from University Library of Munich, Germany
Bibliographic data for series maintained by EconWPA ( this e-mail address is bad, please contact ).