Statistics Seminar（2016-09）

Topic:Treatment Effects Estimators Under Misspecification

Speaker:Ping Yu, The University of Hong Kong

Time:Thursday, 26 May, 14:00-15:30

Place:Room 217, Guanghua Building 2

Abstract:

We conduct misspecification analysis for four treatment effects estimators, IVE, IV-QRE, LSE and QRE, in the framework of HV (2005). We ?first derive the pseudo-true values which shed more light on why the IVE and IV-QRE are consistent when the essential heterogeneity is absent and why the LSE and QRE are consistent when the selection effect is further excluded. For example, when the essential heterogeneity is absent, the IVE is consistent because of an offsetting property, while the IV-QRE is consistent due to a counterfactual-quantiles matching property inherited from rank similarity. We then check two responses to model misspecification. First, we conduct a local sensitivity analysis which provides a measure of sensitivity when the key identification assumption is locally perturbed along a prespecified direction. Second, we summarize the sharp bounds for the ATE in the literature and develop corresponding bounds for the QTE. We illustrate our analyses by studying the effect of veteran status on earnings in Angrist (1990).

Introduction:

Dr. Ping Yu graduated from Peking University in 2000 with B.S. in Mathematics and Economics and in 2002 with M.S. in Finance. He obtained his PhD in Economics from University of Wisconsin-Madison in 2009. Before joining the School of Economics and Finance at The University of Hong Kong as assistant professor in 2014, he was a lecturer at the University of Auckland, New Zealand. His research concentrates on microeconometrics especially in threshold regression and treatment effects evaluation.

//www.fbe.hku.hk/staff/academic/detail/ping-yu

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