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Nonparametric Tests for Equality of Conditional Distributions（条件分布等式的非参数检验？）
主讲人：Xingyu Li(National School of Development, Peking University)
主持老师：（北大经院）王熙
参与老师：（北大经院）王一鸣、刘蕴霆、王法
（北大国发院）黄卓、张俊妮、孙振庭
（北大新结构）胡博
时间：2023年9月22日（周五） 10:00-11:30
地点（线下）：8797威尼斯老品牌107会议室
报告摘要：
This paper proposes two easy-to-implement nonparametric tests for the equality of two conditional distributions. To avoid estimating conditional density functions, we transform the null hypothesis into an equivalent characterization. Based on two-sample U-process and weak convergence theory, we construct the Kolmogorov-Smirnov (KS) and Cramér-von Mises (CvM) statistics and find their asymptotic distributions. The critical values are constructed by a multiplier bootstrap method. The proposed KS and CvM tests are proved to be asymptotically size-controlled and consistent against each fixed alternative. A study on the local power of the tests is provided. Monte Carlo experiments illustrate good performance of the tests in finite samples.
主讲人简介：
Xingyu Li is currently a Ph.D. student at National School of Development, Peking University. His research fields include theoretical econometrics and applied econometrics.
