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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 poverty comparisons. 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 1998-99 data, 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.
M03/03
University of Southampton
Berger, Yves G.
8fd6af5c-31e6-4130-8b53-90910bf2f43b
Skinner, Chris J.
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Berger, Yves G. and Skinner, Chris J. (2003) Variance estimation for a low-income proportion , Southampton, GB University of Southampton 21pp. (S3RI Methodology Working Papers, M03/03).

Berger, Yves G. and Skinner, Chris J. (2003) Variance estimation for a low-income proportion , Southampton, GB University of Southampton 21pp. (S3RI Methodology Working Papers, M03/03).

Record type: Monograph (Working Paper)

Abstract

Proportions below a given fraction of a quantile of an income distribution are often estimated from survey data in poverty comparisons. 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 1998-99 data, 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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Published date: 2003

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Local EPrints ID: 7792
URI: http://eprints.soton.ac.uk/id/eprint/7792
PURE UUID: 607e73e7-6324-486f-b759-ad9933e7e1f2

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Date deposited: 07 Jun 2004
Last modified: 17 Jul 2017 17:14

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Contributors

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

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