Robustness Properties of Inequality Measures

Abstract

Inequality measures are often used to summarize information about empirical income distributions. However the resulting picture of the distribution and of changes in the distribution can be severely distorted if the data are contaminated. The nature of this distortion will in general depend upon the underlying properties of the inequality measure. This issue is investigated theoretically using a technique based on the influence function, and the magnitude of the effect is illustrated using a simulation. Both direct nonparametric estimation from the sample, and indirect estimation using a parametric model are considered; in the latter case the application of a robust estimation procedure is demonstrated. The results are applied to two micro-data examples. Copyright 1996 by The Econometric Society.