This paper examines the properties of the Gini coefficient estimator for gamma mixture populations and reveals the presence of bias. In contrast, we show that sampling from a gamma distribution yields an unbiased estimator, consistent with prior research (Baydil et al., 2025). We derive an explicit bias expression for the Gini coefficient in gamma mixture populations, which serves as the foundation for proposing a bias-corrected Gini estimator. We conduct a Monte Carlo simulation study to evaluate the behavior of the bias-corrected Gini estimator.

翻译：本文研究了伽马混合总体中基尼系数估计量的性质，揭示了其中存在的偏差。与此相反，我们证明了从单一伽马分布抽样得到的估计量是无偏的，这与先前研究（Baydil 等人，2025）的结论一致。我们推导出了伽马混合总体中基尼系数的显式偏差表达式，并以此为基础提出了一种偏差校正的基尼估计量。我们通过蒙特卡洛模拟研究评估了该偏差校正基尼估计量的表现。