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http://dx.doi.org/10.5351/CSAM.2017.24.4.339

A comparative study of the Gini coefficient estimators based on the regression approach  

Mirzaei, Shahryar (Department of Statistics, Payame Noor University)
Borzadaran, Gholam Reza Mohtashami (Department of Statistics, Ferdowsi University of Mashhad)
Amini, Mohammad (Department of Statistics, Ferdowsi University of Mashhad)
Jabbari, Hadi (Department of Statistics, Ferdowsi University of Mashhad)
Publication Information
Communications for Statistical Applications and Methods / v.24, no.4, 2017 , pp. 339-351 More about this Journal
Abstract
Resampling approaches were the first techniques employed to compute a variance for the Gini coefficient; however, many authors have shown that an analysis of the Gini coefficient and its corresponding variance can be obtained from a regression model. Despite the simplicity of the regression approach method to compute a standard error for the Gini coefficient, the use of the proposed regression model has been challenging in economics. Therefore in this paper, we focus on a comparative study among the regression approach and resampling techniques. The regression method is shown to overestimate the standard error of the Gini index. The simulations show that the Gini estimator based on the modified regression model is also consistent and asymptotically normal with less divergence from normal distribution than other resampling techniques.
Keywords
bootstrap technique; Gini coefficient; jackknife method; Lorenz curve; modified regression model; resampling techniques;
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