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Subsample Least Squares Estimator for Heterogeneous Effects of Multiple Treatments with Any Outcome Variable

作者: 发布时间:2024-01-05 点击数:
主讲人:Myoung-jae Lee
主讲人简介:

Professor Myoung-jae Lee is an econometrician/statistician in Korea University. He held regular positions in many universities around the world, including Penn State, Tilburg University, Chinese University of Hong Kong, and Australian National University. He published six single-authored books on micro-econometrics and treatment effect analysis, and more than 90 papers in SCI/SSCI-listed journals on economics, statistics, transportation, medicine, sociology and political science.

主持人:Yongmiao Hong
讲座简介:

For multiple treatments D=0,1,...,J, covariates X and outcome Y, the ordinary least squares estimator (OLS) of Y on {D(1),...,D(j),X} is widely applied to a constant-effect linear model, where D(j) is the dummy variable for D=j. However, the treatment effects are almost always X-heterogeneous in reality, or Y is noncontinuous, to invalidate such a linear model. The blind hope of practitioners is that the OLS "somehow" estimates a sensible average of the unknown X-heterogeneous effects. This paper shows that, unfortunately, the OLS is inconsistent unless all treatment effects are constant, because the estimand of the D(d)-slope involves the X-heterogeneous effects of all treatments, not just D(d). One way to overcome this "contamination" problem is the OLS of Y on D(d)-E{D(d)|X, D=0,d} using only the subsample D=0,d, and this paper proposes a modified version of the subsample OLS that is robust to misspecifications of E{D(d)|X, D=0,d}. The robustified subsample OLS is proven to be consistent for an "overlap weight" average of the X-heterogeneous effect of D(d) for any form of Y (continuous, binary, count, ...).

时间:2023-10-31 (Tuesday) 16:30-18:00
地点:Room N302, Economics Building (线下分会场), 腾讯会议:39337743329
讲座语言:English
主办单位:中国科学院大学经济与管理学院、中国科学院预测科学研究中心、永利集团3044官网欢迎您邹至庄经济研究院、NSFC“计量建模与经济政策研究”基础科学中心
承办单位:
期数:“邹至庄讲座”杰出学者论坛(第32期)
联系人信息:许老师,电话:0592-2182991,邮箱:ysxu@xmu.edu.cn
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