Log-Transform Kernel Density Estimation of Income Distribution

Arthur Charpentier and Emmanuel Flachaire

No 1506, AMSE Working Papers from Aix-Marseille School of Economics, France

Abstract: Standard kernel density estimation methods are very often used in practice to estimate density function. It works well in numerous cases. However, it is known not to work so well with skewed, multimodal and heavy-tailed distributions. Such features are usual with income distributions, defined over the positive support. In this paper, we show that a preliminary logarithmic transformation of the data, combined with standard kernel density estimation methods, can provide a much better fit of the density estimation.

Keywords: nonparametric density estimation; heavy-tail; income distribution; data transformation; lognormal kernel (search for similar items in EconPapers)
JEL-codes: C15 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2015-02
New Economics Papers: this item is included in nep-ecm and nep-pbe
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.amse-aixmarseille.fr/sites/default/files/_dt/2012/wp_2015_-_nr_06.pdf (application/pdf)

Related works:
Journal Article: LOG-TRANSFORM KERNEL DENSITY ESTIMATION OF INCOME DISTRIBUTION (2015)
Working Paper: Log-Transform Kernel Density Estimation of Income Distribution (2015)
Working Paper: Log-Transform Kernel Density Estimation of Income Distribution (2014)
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:aim:wpaimx:1506

Access Statistics for this paper

More papers in AMSE Working Papers from Aix-Marseille School of Economics, France AMU-AMSE - 5-9 Boulevard Maurice Bourdet, CS 50498 - 13205 Marseille Cedex 1. Contact information at EDIRC.
Bibliographic data for series maintained by Gregory Cornu ().