We propose inverse probability weighted estimators for the distribution functions of the
potential outcomes under the unconfoundedness assumption and apply the inverse …

We are interested in estimating the average effect of a binary treatment on a scalar outcome.
If assignment to the treatment is exogenous or unconfounded, that is, independent of the …

We introduce a class of instrumental quantile regression methods for heterogeneous
treatment effect models and simultaneous equations models with nonadditive errors and …

Donald and Hsu (2014) studied the estimation and inference for the counterfactual
distribution and quantile functions in a binary treatment model. We extend their work to the …

This paper proposes new estimators for the propensity score that aim to maximize the
covariate distribution balance among different treatment groups. Heuristically, our proposed …

I show that standard instrumental variables estimators, applied to an equation containing
levels and interactions, consistently estimate the average treatment effect under weaker …

This note derives simply computed closed-form expressions for the average treatment effect,
the effect of treatment on the treated, the local average treatment effect, and the marginal …

I propose a general framework for instrumental variables estimation of the average treatment
effect in the correlated random coefficient model, focusing on the case where the treatment …

This paper develops estimators for quantile treatment effects under the identifying restriction
that selection to treatment is based on observable characteristics. Identification is achieved …

This paper proposes estimators of unconditional distribution functions in the presence of
covariates. The conditional distribution is estimated by (parametric or nonparametric) …