Statistical Inference for Treatment Assignment Policies
2019/01/14
研討會日期 : 2019-01-14
時間 : 11:00
主講人 : Mr. Yoshiyasu Rai
主持人 : Professor Tzu-Ting Yang
地點 : Conference Room B110
演講者簡介 : Mr. Rai will receive his Ph.D. in Economics from University of Wisconsin-Madison in 2019. His research fields are Econometrics and Applied Econometrics. He is applying for a position of the Institute of Economics, Academia Sinica now.
演講摘要 : In this paper, I study the statistical inference problem for treatment assignment policies. In typical applications, individuals with different characteristics are expected to differ in their responses to treatment. Hence, treatment assignment policies that allocate treatment based on individuals’ observed characteristics can have a significant influence on outcomes and welfare. A growing literature proposes various approaches to estimating the welfare-maximizing treatment assignment policy. This paper complements this work on estimation by developing a method of inference for treatment assignment policies that can be used to assessing the precision of estimated optimal policies. In particular, for the welfare criterion used by Kitagawa and Tetenov (2018), my method constructs (i) a confidence set for the optimal policy and (ii) a confidence interval for the maximized welfare. By implementing a doubly robust form of the average outcome estimator, I allow for the possibility that nuisance parameters, such as the propensity score, could be estimated by high-dimensional machine learning methods. A simulation study indicates that the proposed methods work well with modest sample size. I apply the method to experimental data from the National Job Training Partnership Act study.
