We develop a novel test of the instrumental variable identifying assumptions for
heterogeneous treatment effect models with conditioning covariates. We assume …

In this paper we show that the distribution of treatment effects is point identified in a model
where the outcome equation is of unrestricted form and the selection equation contains …

Estimating heterogeneous treatment effects from observational data is a central problem in
many domains. Because counterfactual data is inaccessible, the problem differs …

In this paper, we present a systematic study of partial identification of two general classes of
functionals of the joint distribution of two “potential outcomes” when a bivariate sample from …

We study the problem of treatment effect estimation in randomized experiments with high-
dimensional covariate information and show that essentially any risk-consistent regression …

We study the causal interpretation of regressions on multiple dependent treatments and
flexible controls. Such regressions are often used to analyze randomized control trials with …

In heterogeneous treatment effect models with endogeneity, the identification of the local
average treatment effect (LATE) typically relies on an instrument that satisfies two …

Flexible estimation of heterogeneous treatment effects lies at the heart of many statistical
applications, such as personalized medicine and optimal resource allocation. In this article …

We aim to make inferences about a smooth, finite-dimensional parameter by fusing together
data from multiple sources. Previous works have studied the estimation of a variety of …