报告题目： The Use of Machine Learning in Treatment Effect Estimation
报告人：许育进 Institute of Economics，Academia Sinica
报告时间：2022年11月22日(周二) 16:30-18:00
报告地点：中科院数学与系统科学研究院南楼N204；
腾讯会议 ID：375-8612-5504
内容摘要
We present recent developments in double machine learning (DML) approach. The DML approach is concerned primarily with selecting the relevant control variables and functional forms necessary for the consistent estimation of an average treatment effect. We explain why the use of orthogonal moment conditions is crucial in this setting. We also discuss how DML approach can be applied to estimate the conditional average treatment effect (CATE) function conditional on a pre-specified coordinate.
主讲人简介
Yu-Chin Hsu is a research fellow in Institute of Economics, Academia Sinica. His research focuses on econometrics.
