This paper presents an econometric approach to estimate the behavioral effects of counterfactual policy experiments in the context of dynamic decision models where the current utility function and the distribution of unobservables are nonparametrically specified. Previous studies have shown that...

This paper proposes sequential matching and inverse selection probability weighting to estimate dynamic casual effects. The sequential matching estimators extend simple, matching estimators based on propensity scores for static causal analysis that have been frequently applied in the evaluation...

This paper proposes sequential matching and inverse selection probability weighting to estimate dynamic causal effects. The sequential matching estimators extend simple, matching estimators based on propensity scores for static causal analysis that have been frequently applied in the evaluation...

Researchers typically assume experimental subjects have rational expectations. If the object of the experiment is to learn the distibution of decision makers' types, then this amounts to assuming subjects' know the very thing the researcher wishes to learn. We propose a method of conducting...

This paper considers the problem of the identification of causal effects using instrumental variables. We are interested in the effects of some treatments on certain outcomes. First, we consider that a participation in a treatment or a program is only possible one time but we have the choice...