Randomization Inference beyond the Sharp Null: Bounded Null Hypotheses and Quantiles of Individual Treatment Effects
超越尖锐零假设的随机化推断:有界零假设与个体处理效应分位数
Randomization inference (RI) is typically interpreted as testing Fisher's "sharp" null hypothesis that all unit-level effects are exactly zero. This hypothesis is often criticized as restrictive and implausible, making its rejection scientifically uninteresting. We show, however, that many randomization tests are also valid for a "bounded" null hypothesis under which the unit-level effects are all non-positive (or all non-negative) but are otherwise heterogeneous. In…