Calculating a Standard Error for the Gini Coefficient: Some Further Results*
证明基尼系数的标准误可通过简单解析式精确计算，并利用似不相关回归框架检验基尼系数对数据变化的敏感性。
Abstract Several authors have suggested using the jackknife technique to approximate a standard error for the Gini coefficient. It has also been shown that the Gini measure can be obtained simply from an artificial ordinary least square (OLS) regression based on the data and their ranks. We show that obtaining an exact analytical expression for the standard error is actually a trivial matter. Further, by extending the regression framework to one involving seemingly unrelated regressions (SUR), several interesting hypotheses regarding the sensitivity of the Gini coefficient to changes in the data are readily tested in a formal manner.