JOS

Abstract
Journal of Official Statistics, Vol.24, No.4, 2008. pp. 541555

Contents
Current Issue
Personal Reference Library (PRL)
Personal Page
Archive
Search
Home


A Note on the Asymptotic Equivalence of Jackknife and Linearization Variance Estimation for the Gini Coefficient

Abstract:
The Gini coefficient (Gini 1914) has proved valuable as a measure of income inequality. In cross-sectional studies of the Gini coefficient, information about the accuracy of its estimates is crucial. We show how to use jackknife and linearization to estimate the variance of the Gini coefficient, allowing for the effect of the sampling design. The aim is to show the asymptotic equivalence (or consistency) of the generalized jackknife estimator (Campbell 1980) and the Taylor linearization estimator (Kovačević and Binder 1997) for the variance of the Gini coefficient. A brief simulation study supports our findings.

Keywords:
Inclusion probability, linearization, survey weight, sampling design

Copyright Statistics Sweden 1996-2017.  Open Access
ISSN 0282-423X
Created and Maintained by OKS Group