In this paper we present some nonparametric bootstrap methods to construct distribution-free confidence intervals for inequality indices belonging to the Gini family. These methods have a coverage accuracy better than that obtained with the asymptotic distribution of their natural estimators, typically the standard normal. The coverage performances of these methods are evaluated for the index R by Gini with a Monte Carlo experiment on samples simulated from the Dagum income model (Type I), which is usually used to describe the income distribution.
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Volume (Year): 16 (2000) Issue (Month): 1/2 (October) Pages: 137-147 Download reference. The following formats are available: HTML
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