题目：Sharp Bounds on Treatment Effects for Policy Evaluation

主讲人： 杨珅珅，天津大学

时间：2023年5月11日下午14:00 – 15:30

地点： 暨南大学石牌校区中惠楼106室

主讲人简介：

Shenshen Yang is an assistant professor at Ma Yinchu School of Economics of Tianjin University. She graduated from the University of Texas at Austin in 2021. Her research interests are theoretical and applied econometrics, with a focus on identification of treatment effects in semi- and non-parametric models, and its application in policy evaluation. Her work on policy evaluation was published on Education, Urban Studies, and her most recent working paper regarding nonparametric extrapolation of local average treatment effect received R&R from Journal of Econometrics.

摘要：

For counterfactual policy evaluation, it is important to ensure that treatment parameters are relevant to the policies in question. This is especially challenging under unobserved heterogeneity, as is well featured in the definition of the local average treatment effect (LATE). Being intrinsically local, the LATE is known to lack external validity in counterfactual environments. This paper investigates the possibility of extrapolating local treatment effects to different counterfactual settings when instrumental variables are only binary. We propose a novel framework to systematically calculate sharp nonparametric bounds on various policy-relevant treatment parameters that are defined as weighted averages of the marginal treatment effect (MTE). Our framework is flexible enough to incorporate a large menu of identifying assumptions beyond the shape restrictions on the MTE that have been considered in prior studies. We apply our method to understand the effects of medical insurance policies on the use of medical services.