Quantile and Distribution Treatment Effects on the Treated with Possibly Non-Continuous Outcomes
可能非连续结局下处理组的分位数与分布处理效应
Applied Difference-in-Differences studies often involve outcomes that are discrete, mixed, censored, or otherwise non-continuously distributed, while policy questions frequently concern distributional effects rather than mean effects alone. This paper develops a distributional DiD framework for identifying and conducting uniform inference on distribution and quantile treatment effects on the treated in such settings under stated identifying and regularity conditions.…