Reza Modarres, Joseph L. Gastwirth
We will show that the regression approach to estimating the standard error of the Gini index can produce incorrect results as it does not account for the correlations introduced in the error terms once the data are ordered. To assess the effect of ignoring the correlation in the error terms we examined two distributions and show that the regression method overestimates the standard error of the Gini index. We recommend that the more mathematically complex or computationally intensive methods be used.
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