Statistical Inference for Inequality and Poverty Measurement with Dependent Data

16 Pages Posted: 14 Jan 2003

See all articles by Christian Schluter

Christian Schluter

University of Southampton - Division of Economics

Mark M. Trede

University of Muenster - Faculty of Economics

Abstract

This article is about statistical inference for inequality and poverty measures when income data exhibit contemporaneous dependence across members of the same household. While much empirical research is based on household survey data such as the PSID, standard methods assume that income is an independent and identically distributed random variable. Applying them to contemporaneously dependent data produces biased results, and Monte Carlo experiments reveal that their confidence intervals are too narrow. By contrast, our proposed distribution-free estimators perform well.

Suggested Citation

Schluter, Christian and Trede, Mark M., Statistical Inference for Inequality and Poverty Measurement with Dependent Data. International Economic Review, Vol. 43, pp. 493-508, 2002. Available at SSRN: https://ssrn.com/abstract=312679

Christian Schluter (Contact Author)

University of Southampton - Division of Economics ( email )

Southampton, SO17 1BJ
United Kingdom
+44 2380 59 5909 (Phone)
+44 2380 59 3858 (Fax)

HOME PAGE: www.economics.soton.ac.uk/staff/schluter/

Mark M. Trede

University of Muenster - Faculty of Economics ( email )

Universitätsstr. 14-16
48143 Munster
Germany

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