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Full Details
Title: Inequality as experienced difference: A reformulation of the Gini coefficient
Author(s): Samuel Bowles and Wendy Carlin
Publication Date: September 2018
Keyword(s): Gini coefficient, inequality, Lorenz curve and relative mean difference
Programme Area(s): Development Economics and Public Economics
Abstract: We represent a population as a complete undirected network, the edges of which are the fundamental data on experienced disparities. This yields a Gini coefficient (for wealth, say) for finite populations that is based on the mean wealth difference between all pairs of individuals relative to the mean wealth, which we demonstrate is not the case for the conventional Lorenz curve representation and the algorithm widely-used to calculate it. Our method also provides simple and intuitive explanations of the effects on the Gini coefficient of changes in the wage share, the employment rate, and other macroeconomic and demographic variables.
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Bibliographic Reference
Bowles, S and Carlin, W. 2018. 'Inequality as experienced difference: A reformulation of the Gini coefficient'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=13211