报告题目：Inference in Linear IV Regression That Is Robust to Weak IV's and Misspecification
主讲嘉宾：Xiaoxia Shi is honored to serve as the Lowell and Leila Robinson Chair Professor of Economics at the University of Wisconsin–Madison. She earned her Ph.D. from Yale University. Her research focuses on semi- and nonparametric estimation, IV regression, moment inequality models etc. Her work has been published in leading journals, including Review of Economic Studies, Econometrica, Journal of Political Economy, Econometric Theory, Journal of Econometrics, and Quantitative Economics. Currently, she serves as a co-editor of Econometric Theory and an associate editor of Quantitative Economics.
报告摘要：In this paper, we study the inference problem under misspecification in a linear instrumental variable (IV) regression with potential weak identification. Under weak IV, inference is typically done via hypothesis testing. Thus we first introduce the concept of pseudo-true parameter value for a test and investigate the pseduo-true value for the 2SLS-t test, the Anderson-Rubin (AR) test, the Lagrange Multiplier (LM), and the conditional likelihood ratio (CLR) test. We find that only the 2SLS-t test has a unique proper pseudo-true value that has an economic interpretation in a commonly considered scenario. We then focus attention on the 2SLS-t test pseudo-true value and design a group of tests that are robust to both weak IV and misspecification.
报告时间：2025年6月24日(周二)，16:30-18:00
线下地点：厦门大学经济楼C108
腾讯会议：535 594 690
