Log-Skew-Normal and Log-Skew-t Distributions as Models for Family Income Data

Adelchi Azzalini, Thomas Del Cappello and Samuel Kotz

Journal of Income Distribution, 2002, vol. 11, issue 3-4, 2-2

Abstract: The U.S. family income data for the years 1970, 1975, 1978, 1980, 1985 and 1990 was fitted using the log-normal, Gamma, Singh-Maddala, Dagum type I and generalized Beta of second kind distributions, among others in earlier publications. Here we supplement these fittings by adding the log-skew-normal and log-skew-t distributions. In addition, we have performed similar numerical comparisons using 1997 income data collected in a sample survey from several European countries. The overall picture emerging from these numerical comparisons indicates that, while the log-skewed normal distribution provides a somewhat variable degree of goodness-of-fit, the log-skewed-t distribution seems to fit the data satisfactorily in a quite consistent way, and on the par with most creditable distributions.

Date: 2002
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://jid.journals.yorku.ca/index.php/jid/article/view/1249 (application/pdf)
Some fulltext downloads are only available to subscribers. See JID website for details.

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:jid:journl:y:2002:v:11:i:3-4:p:2-2

Access Statistics for this article

More articles in Journal of Income Distribution from Ad libros publications inc. Contact information at EDIRC.
Bibliographic data for series maintained by Timm Boenke ( this e-mail address is bad, please contact ).