Statistical Inference Via Bootstrapping for Measures of Inequality

In this paper we consider the use of bootstrap methods to compute interval estimates and perform hypothesis tests for decomposable measures of economic inequality. The bootstrap potentially represents a significant gain over available asymptotic intervals because it provides an easily implemented solution to the Behrens-Fisher problem. Two applications of this approach, using the PSID (for the study of taxation) and the NLSY (for the study of youth inequality), to the Gini coefficient and Theil's entropy measures of inequality, are provided. The results suggest that (i) statistical inference is essential even when large samples are available, and (ii) the bootstrap appears to perform well in this setting.

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