Multiple Testing and the Distributional Effects of Accountability Incentives in Education
提出基于自助法的多重检验程序，用于检测分位数处理效应的异质性，并应用于巴基斯坦学校报告卡实验数据，发现信息干预对学生成绩存在政策相关的异质性影响，且63%的显著效应在多重检验校正后不再显著。
This article proposes bootstrap-based multiple testing procedures for quantile treatment effect (QTE) heterogeneity under the assumption of selection on observables, and shows its asymptotic validity. Our procedure can be used to detect the quantiles and subgroups exhibiting treatment effect heterogeneity. We apply the multiple testing procedures to data from a large-scale Pakistani school report card experiment, and uncover evidence of policy-relevant heterogeneous effects from information provision on child test scores. Furthermore, our analysis reinforces the importance of preventing the inflation of false positive conclusions because 63% of statistically significant QTEs become insignificant once corrections for multiple testing are applied.