This paper develops a nonparametric methodology for treatment evaluation with multiple
outcome periods under treatment endogeneity and missing outcomes. We use instrumental
variables, pre-treatment characteristics, and short
-term (or intermediate) outcomes to identify
the average treatment effect on the outcomes of compliers (the subpopulation whose
treatment reacts on the instrument) in multiple periods based on inverse probability
weighting. Treatment selection and attrition may depend on both observed characteristics
and the unobservable compliance type, which is possibly related to unobserved factors. We
also provide a simulation study and apply our methods to the evaluation of a policy
intervention targeting college achievement, where we find that controlling for attrition
considerably affects the effect estimates.
Dieser Eintrag ist Teil der Universitätsbibliographie.
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