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 investigates four topics. (1) It examines the different roles played by the propensity score (probability of selection) in matching, instrumental variable and control functions methods. (2) It contrasts the roles of exclusion restrictions in matching and selection models. (3) It...