
arXiv: 1510.06085
The classical Lorenz curve is often used to depict inequality in a population of incomes, and the associated Gini coefficient is relied upon to make comparisons between different countries and other groups. The sample estimates of these moment-based concepts are sensitive to outliers and so we investigate the extent to which quantile-based definitions can capture income inequality and lead to more robust procedures. Distribution-free estimates of the corresponding coefficients of inequality are obtained, as well as sample sizes required to estimate them to a given accuracy. Convexity, transference and robustness of the measures are examined and illustrated.
28 pages, 9 figures
quantile density, influence function, Gini index, Mathematics - Statistics Theory, robustness, Statistics Theory (math.ST), Nonparametric tolerance and confidence regions, inequality measures, FOS: Mathematics, Nonparametric regression and quantile regression, Statistical methods; economic indices and measures, Applications of statistics to economics
quantile density, influence function, Gini index, Mathematics - Statistics Theory, robustness, Statistics Theory (math.ST), Nonparametric tolerance and confidence regions, inequality measures, FOS: Mathematics, Nonparametric regression and quantile regression, Statistical methods; economic indices and measures, Applications of statistics to economics
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