Propensity score matching has become a popular method for the estimation of average treatment effects. In empirical applications, researchers almost always impose a parametric model for the propensity score. This practice raises the possibility that the model for the propensity score is...

In the context of a binary outcome, treatment, and instrument, Balke and Pearl (1993, 1997) establish that the monotonicity condition of Imbens and Angrist (1994) has no identifying power beyond instrument exogeneity for average potential outcomes and average treatment effects in the sense that...

In this paper, we consider the nonparametric identification and estimation of the average effect of a dummy endogenous regressor in models where the regressors are weakly but not additively separable from the error term. The model is not required to be strictly increasing in the error term, and...

We show the identification of important features of the model in a perfect information entry game with two players and asymmetric payoffs when there are no unbounded regressors and the distribution of the unobservables is not parametrically specified.

This paper unites the treatment effect literature and the latent variable literature. The economic questions answered by the commonly used treatment effect parameters are considered. We demonstrate how the marginal treatment effect parameter can be used in a latent variable framework to generate...

This paper formulates an econometric framework for studying the impact of interventions on discrete outcomes when responses to treatment vary among observationally identical persons. Using a latent variable model that can be linked to well-posed economic models, we show how to define and...

This paper exposits and relates two distinct approaches to bounding the average treatment effect. One approach, based on instrumental variables, is due to Manski (1990, 1994), who derives tight bounds on the average treatment effect under a mean independence form of the instrumental variables...

This chapter relates the literature on the econometric evaluation of social programs to the literature in statistics on "causal inference". In it, we develop a general evaluation framework that addresses well-posed economic questions and analyzes agent choice rules and subjective evaluations of...