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讲座:Matching Points: Supplementing Instruments with Covariates in Triangular Models

发布者:经济系    发布时间:2019-12-19

题 目:Matching Points: Supplementing Instruments with Covariates in Triangular Models

嘉 宾:Junlong Feng, Ph.D. Candidate, Columbia University

主持人:瞿茜   副教授  上海交通大学安泰经济与管理学院

时 间:2019 12 23 日(周一)  9:30-11:00

地 点:上海交通大学  徐汇校区包图  A407

内容简介:

We consider triangular models with a discrete endogenous variable and an instrumental variable (IV) taking on fewer values. Addressing the failure of the order condition, we develop the first approach to restore identification for both separable and nonseparable models in this case by supplementing the IV with covariates, allowed to enter the model in an arbitrary way. For the separable model, we show that it satisfies a system of linear equations, yielding a simple identification condition and a closed-form estimator. For the nonseparable model, we develop a new identification argument by exploiting its continuity and monotonicity, leading to weak sufficient conditions for global identification. Built on it, we propose a uniformly consistent and asymptotically normal sieve estimator. We apply our approach to an empirical application of the return to education with a binary IV. Though under-identified by the IV alone, we obtain results consistent with the literature using our approach.

演讲人简介

Junlong Feng is a Ph.D. candidate from the Department of Economics at Columbia University. His research interests lie in econometrics, applied microeconomics, causal inference and machine learning.

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