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Abstract-We propose a first-order bias correction term for the Gini index to reduce the bias due to grouping. It depends on only the number of individuals in each group and is derived from a measurement error framework. We also provide a formula for the remaining second-order bias. Both Monte Carlo and EU and U.S. empirical evidence show that the first-order correction reduces a considerable share of the bias, but that some remaining second-order bias is increasing in the variance. We propose a procedure that addresses the remaining second-order bias by using additional information. © 2011 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Original publication

DOI

10.1162/REST_a_00103

Type

Journal article

Journal

Review of Economics and Statistics

Publication Date

01/08/2011

Volume

93

Pages

982 - 994