The Estimation and Interpolation of Inequality Measures

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Abstract
Alternative methods of computing estimates of inequality measures from grouped data are critically examined in terms of their theoretical and empirical properties. The use of a simple “split-histogram” technique of interpolation is explained and supported. Theoretical and empirical support is also provided for the “⅓/⅔ rule”—a simple computational procedure for a point estimate of an inequality measure derived from its standard grouping bounds.

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