Quantile‐Based Test for Heterogeneous Treatment Effects
提出一种基于分位数过程的置换检验方法，通过Khmaladze鞅变换解决参数估计干扰问题，在控制检验规模的同时保持良好功效，适用于福利改革等实验数据。
ABSTRACT We introduce a permutation test for heterogeneous treatment effects based on the quantile process. However, tests based on the quantile process often suffer from estimated nuisance parameters that jeopardize their validity, even in large samples. To overcome this problem, we use Khmaladze's martingale transformation. We show that the permutation test based on the transformed statistic controls size asymptotically. Numerical evidence asserts the good size and power performance of our test procedure compared to other popular quantile‐based tests. We discuss a fast implementation algorithm and illustrate our method using experimental data from a welfare reform.