Partial Distributional Policy Effects
提出一种评估单个协变量分布变化对结果变量分布影响的方法，涵盖连续和离散协变量情形，并给出离散情形下的识别边界及推断方法。
In this paper, we propose a method to evaluate the effect of a counterfactual change in the unconditional distribution of a single covariate on the unconditional distribution of an outcome variable of interest. Both fixed and infinitesimal changes are considered. We show that such effects are point identified under general conditions if the covariate affected by the counterfactual change is continuously distributed, but are typically only partially identified if its distribution is discrete. For the latter case, we derive informative bounds, making use of the available information. We also discuss estimation and inference.