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A New Logit-Based Gini Coefficient

Department of Economics, Chung Ang University, Seoul 156-756, Korea
Department of Economics, Southern Methodist University, Dallas, TX 75275, USA
Department of Political Science, Korea University, Seoul 136-701, Korea
Author to whom correspondence should be addressed.
Entropy 2019, 21(5), 488;
Received: 21 March 2019 / Revised: 29 April 2019 / Accepted: 9 May 2019 / Published: 13 May 2019
PDF [2833 KB, uploaded 13 May 2019]


The Gini coefficient is generally used to measure and summarize inequality over the entire income distribution function (IDF). Unfortunately, it is widely held that the Gini does not detect changes in the tails of the IDF particularly well. This paper introduces a new inequality measure that summarizes inequality well over the middle of the IDF and the tails simultaneously. We adopt an unconventional approach to measure inequality, as will be explained below, that better captures the level of inequality across the entire empirical distribution function, including in the extreme values at the tails. View Full-Text
Keywords: projection of share function; logit function; maximum entropy method; inequality measure projection of share function; logit function; maximum entropy method; inequality measure

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Ryu, H.K.; Slottje, D.J.; Kwon, H.Y. A New Logit-Based Gini Coefficient. Entropy 2019, 21, 488.

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