Judging Judge Fixed Effects
提出一个非参数检验，用于验证工具变量设计中基于法官随机分配的排他性和单调性假设，并在纽约审前拘留对被告结果影响的实证中应用。
We propose a nonparametric test for the exclusion and monotonicity assumptions invoked in instrumental variable (IV) designs based on the random assignment of cases to judges. We show its asymptotic validity and demonstrate its finite-sample performance in simulations. We apply our test in an empirical setting from the literature examining the effects of pretrial detention on defendant outcomes in New York. When the assumptions are not satisfied, we propose weaker versions of the usual exclusion and monotonicity restrictions under which the IV estimator still converges to a proper weighted average of treatment effects.