This paper uses factor models to identify and estimate distributions of counterfactuals. We extend LISREL frameworks to a dynamic treatment effect setting, extending matching to account for unobserved conditioning variables. Using these models, we can identify all pairwise and joint treatment...

This paper considers semiparametric identification of structural dynamic discrete choice models and models for dynamic treatment effects. Time to treatment and counterfactual outcomes associated with treatment times are jointly analyzed. We examine the implicit assumptions of the dynamic...

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 paper extends the widely used ordered choice model by introducing stochastic thresholds and interval-specific outcomes. The model can be interpreted as a generalization of the GAFT (MPH) framework for discrete duration data that jointly models durations and outcomes associated with...

The internal rate of return to schooling is a fundamental economic parameter that is often used to assess whether expenditure on education should be increased or decreased. This article considers alternative approaches to estimating marginal internal rates of return for different schooling...