数字经济与数据科学系列讲座（第1期）

报告题目：Identification and Estimation of the Marginal Treatment Effect without Instrumental Variable

报  告 人：潘哲文（浙江财经大学经济学院 副研究员）

主  持 人：程明勉（中山大学岭南学院 助理教授）

时       间：2023年10月27日（周五）14:30

地       址：岭南堂汪道涵会议室（101）

语       言：中文+英文

摘要：

This paper proposes a method of defining, identifying, and estimating the marginal treatment effect (MTE) without imposing instrumental variable (IV) assumptions of independence, exclusion, and separability. Under the novel definition of MTE based on normalized treatment error that is statistically independent of covariates, we find that the relationship between MTE and standard treatment parameters holds as well in the absence of IV. We provide a set of sufficient conditions ensuring identification of such defined MTE in an environment of essential heterogeneity. The key conditions include a linear restriction on potential outcome regression functions, a nonlinear restriction on the propensity score, and a conditional mean independence restriction that leads to additive separability. We prove identification following the notion of semiparametric identification based on functional form. Consistent semiparametric estimation procedures are suggested, and an empirical application to Head Start is provided to illustrate the usefulness of the proposed method in analyzing heterogenous causal effects when IV is elusive.

报告人介绍：

        潘哲文，浙江财经大学经济学院副研究员，2017年毕业于中山大学岭南学院，获数量经济学博士学位。研究领域为微观计量经济学理论与应用，包括受限因变量模型、因果推断方法等，研究成果发表于《Journal of Business & Economic Statistics》《Journal of Futures Market》《中国科学：数学》《管理科学学报》《统计研究》等国内外核心期刊，主持国家自然科学基金青年项目和面上项目。 

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