Statistical Inference for Inequality and Poverty Measurement with Dependent Data*
针对同一家庭成员收入存在同期相依性的情况，提出无分布假设的统计推断方法，解决传统独立同分布假设导致的估计偏误和置信区间过窄问题，对使用PSID等家庭调查数据的研究者有用。
This article is about statistical inference for inequality and poverty measures when income data exhibit contemporaneous dependence across members of the same household. While much empirical research is based on household survey data such as the PSID, standard methods assume that income is an independent and identically distributed random variable. Applying them to contemporaneously dependent data produces biased results, and Monte Carlo experiments reveal that their confidence intervals are too narrow. By contrast, our proposed distribution-free estimators perform well.