The University of Southampton
University of Southampton Institutional Repository

A Note on the asymptotic equivalence of jackknife and linearization variance estimation for the Gini Coefficient

Record type: Monograph (Working Paper)

The Gini coefficient has proved valuable as a measure of income inequality. In cross-sectional studies of the Gini coefficient, information about the accuracy of its estimate 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 generalised jackknife estimator and the Taylor linearization estimator for the variance of the Gini coefficient. A brief simulation study supports our findings.

PDF 51201-01.pdf - Author's Original
Download (172kB)

Citation

Berger, Yves G. (2008) A Note on the asymptotic equivalence of jackknife and linearization variance estimation for the Gini Coefficient , Southampton, GB University of Southampton 22pp. (S3RI Methodology Working Papers, M08/04).

More information

Published date: 9 May 2008
Organisations: Statistical Sciences Research Institute

Identifiers

Local EPrints ID: 51201
URI: http://eprints.soton.ac.uk/id/eprint/51201
PURE UUID: ae7a890f-fa65-4199-b942-73d383cc7d38

Catalogue record

Date deposited: 09 May 2008
Last modified: 17 Jul 2017 14:49

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×