The Regional Economics Applications Laboratory
Announces a Seminar by:

Carlos Hurtado

PhD Student - Department of Economics

Sources of Inequality:
Additive Decomposition of the Gini Coefficient





Davenport Hall


Abstract: Understanding the impacting factors of inequality is important from a policy-maker perspective because it makes possible to target the programs to reduce disparity among the society. Comprehending how measurements of inequality vary as function of the factors is important from an applied point of view. This paper uses the link between the Gini Index and the quantile function to propose a new methodology for the measurement of the impact of individual characteristics in the distribution of wages or income. The method uses polynomial approximations of the quantile regression coefficients of a positive random variable to additively decompose the factors that contribute most to the inequality of a distribution. The 2014 Annual Social and Economic Supplement of the Current Population Survey is used to exemplify the procedure and determine the factors impact the distribution of wages in the United States.
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