Distribution-Free Inference for Welfare Indices Under Complete and Incomplete Information

The Journal of Economic Inequality, Vol. 1, No. 3, pp. 191-219, 2003

30 Pages Posted: 15 Feb 2011

See all articles by Frank Cowell

Frank Cowell

London School of Economics & Political Science (LSE) - Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)

Maria-Pia Victoria-Feser

University of Geneva - HEC

Date Written: January 29, 2003

Abstract

The data available for estimating welfare indicators are often inconveniently incomplete data: they may be censored or truncated. Furthermore, for robustness reasons, researchers sometimes use trimmed samples. By using the statistical tool known as the Influence Function we derive distribution-free asymptotic variances for wide classes of welfare indicators not only in the complete data case, but also in the important cases where the data have been trimmed, censored or truncated.

Keywords: censoring, income distribution, inequality measurement, influence function, Lorenz curve, sampling variance, trimming

Suggested Citation

Cowell, Frank A. and Victoria-Feser, Maria-Pia, Distribution-Free Inference for Welfare Indices Under Complete and Incomplete Information (January 29, 2003). The Journal of Economic Inequality, Vol. 1, No. 3, pp. 191-219, 2003. Available at SSRN: https://ssrn.com/abstract=1761503

Frank A. Cowell

London School of Economics & Political Science (LSE) - Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD) ( email )

Houghton Street
London WC2A 2AE
United Kingdom
+44 (0)171-955 7277 (Phone)
+44 (0)171-242 2357 (Fax)

Maria-Pia Victoria-Feser (Contact Author)

University of Geneva - HEC ( email )

40 Boulevard du Pont d'Arve
Geneva 4, 1211
Switzerland

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