We will show that the regression approach to estimating the standard error of the Gini index can produce incorrect results as it does not account for the correlations introduced in the error terms once the data are ordered. To assess the effect of ignoring the correlation in the error terms we examined two distributions and show that the regression method overestimates the standard error of the Gini index. We recommend that the more mathematically complex or computationally intensive methods be used. Copyright 2006 Blackwell Publishing Ltd.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).
Related research
Keywords:
Cited by: (explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)