Econ Papers Daily / 期刊论文
两种可调基尼型测度及其U统计量估计：理论、模拟与美洲人均GDP的实证应用
Two tunable Gini-type measures with U-statistic estimation: theory, simulation, and an empirical application to GDP per capita in the Americas
摘要
We introduce two families of inequality measures, $$G_p$$ G p and $$H_q$$ H q , that converge to the classical Gini coefficient as $$p,q\rightarrow \infty $$ p , q → ∞ . The tuning parameters $$p>1$$ p > 1 and $$q>0$$ q > 0 regulate the influence of disparities between observations. For each index we derive closed-form U -statistic plug-in estimators and establish strong consistency and asymptotic normality under mild moment conditions. A Monte Carlo study assesses finite-sample behavior across ( n , p , q ), and an empirical illustration with GDP per capita in the Americas shows how the tuning parameters influence the measure of inequality.
中文摘要
我们引入两族不等式测度，$$G_p$$ G p 与 $$H_q$$ H q ，当 $$p,q\rightarrow \infty $$ p , q → ∞ 时，它们收敛于经典基尼系数。调节参数 $$p>1$$ p > 1 和 $$q>0$$ q > 0 控制观测值之间差异的影响。对于每个指数，我们推导出闭式 U 统计量插入估计量，并在温和矩条件下建立强相合性与渐近正态性。一项蒙特卡洛研究评估了在 ( n , p , q ) 下的有限样本表现，而一项使用美洲人均 GDP 的实证示例展示了调节参数如何影响不平等测度。