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Variance estimation for a low income proportion

Variance estimation for a low income proportion
Variance estimation for a low income proportion
Proportions below a given fraction of a quantile of an income distribution are often estimated from survey data in comparisons of poverty. We consider the estimation of the variance of such a proportion, estimated from Family Expenditure Survey data. We show how a linearization method of variance estimation may be applied to this proportion, allowing for the effects of both a complex sampling design and weighting by a raking method to population controls.

We show that, for data for 1998–1999, the estimated variances are always increased when allowance is made for the design and raking weights, the principal effect arising from the design. We also study the properties of a simplified variance estimator and discuss extensions to a wider class of poverty measures.
0035-9254
457-468
Berger, Yves G.
8fd6af5c-31e6-4130-8b53-90910bf2f43b
Skinner, Chris J.
dec5ef40-49ef-492a-8a1d-eb8c6315b8ce
Berger, Yves G.
8fd6af5c-31e6-4130-8b53-90910bf2f43b
Skinner, Chris J.
dec5ef40-49ef-492a-8a1d-eb8c6315b8ce

Berger, Yves G. and Skinner, Chris J. (2003) Variance estimation for a low income proportion. Journal of the Royal Statistical Society, Series C (Applied Statistics), 52 (4), 457-468. (doi:10.1111/1467-9876.00417).

Record type: Article

Abstract

Proportions below a given fraction of a quantile of an income distribution are often estimated from survey data in comparisons of poverty. We consider the estimation of the variance of such a proportion, estimated from Family Expenditure Survey data. We show how a linearization method of variance estimation may be applied to this proportion, allowing for the effects of both a complex sampling design and weighting by a raking method to population controls.

We show that, for data for 1998–1999, the estimated variances are always increased when allowance is made for the design and raking weights, the principal effect arising from the design. We also study the properties of a simplified variance estimator and discuss extensions to a wider class of poverty measures.

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More information

Published date: 2003
Organisations: Social Statistics

Identifiers

Local EPrints ID: 34688
URI: http://eprints.soton.ac.uk/id/eprint/34688
ISSN: 0035-9254
PURE UUID: 06d4b173-af4c-465b-a8a5-e25adef7ca75
ORCID for Yves G. Berger: ORCID iD orcid.org/0000-0002-9128-5384

Catalogue record

Date deposited: 17 May 2006
Last modified: 16 Mar 2024 03:03

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Contributors

Author: Yves G. Berger ORCID iD
Author: Chris J. Skinner

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