Inference on Optimal Treatment Assignments∗

We consider inference on optimal treatment assignments. Our methods allow for inference on the treatment assignment rule that would be optimal given knowledge of the population treatment effect in a general setting. The procedure uses multiple hy-pothesis testing methods to determine a subset of the population for which assignment to treatment can be determined to be optimal after conditioning on all available infor-mation, with a prespecified level of confidence. A monte carlo study confirms that the inference procedure has good small sample behavior. We apply the method to study the Mexican conditional cash transfer program Progresa.