We propose inverse probability weighted estimators for the distribution functions of the potential outcomes of a binary treatment under the unconfoundedness assumption. We also apply the inverse mapping on the distribution functions to obtain the quantile functions. We show that the proposed...

We construct a Kolmogorov-Smirnov test for the null hypothesis that the conditional average treatment effect is non-negative conditional on every possible value of the covariates. The null hypothesis can be characterized as a conditional moment inequality under the unconfoundedness assumption,...

This paper examines the distribution structural functions (DSFs) and quantile structural functions (QSFs) in a semiparametric treatment effect model. The DSF and QSF are defined as the distribution function and quantile function of the counterfactural outcome when covariates are exogenously...