主讲人：王宇龙 副教授（美国Lehigh大学）

主持人：谢聪 助理教授（辽宁大学中国经济研究院）

嘉宾介绍：马湘君 教授（辽宁大学中国经济研究院）

时间：2026年5月21日（周四） 14：00-15：30（北京时间）

地点：辽宁大学蒲河校区经济学部大楼112室

线上地址：腾讯会议377-781-126

语言：中文/英文

摘要：Conventional cluster-robust inference can be invalid when data contain clusters of unignorably large size. We formalize this issue by deriving a necessary and sufficient condition for its validity, and show that this condition is frequently violated in practice: specifications from 77% of empirical research articles in American Economic Review and Econometrica during 2020–2021 appear not to meet it. To address this limitation, we propose a genuinely robust inference procedure based on a new cluster score bootstrap. We establish its validity and size control across broad classes of data-generating processes where conventional methods break down. Simulation studies corroborate our theoretical findings, and empirical applications illustrate that employing the proposed method can substantially alter conventional statistical conclusions.

主讲人简介：

王宇龙，美国Lehigh大学副教授，美国普林斯顿大学经济学博士。英文期刊Econometric Reviews副主编。主要研究兴趣包括理论与应用计量经济学，统计学，国际贸易，健康经济学。研究成果曾发表在Journal of the American Statistical Association, Journal of Econometrics, Journal of Business & Economic Statistics, Econometric Theory, Journal of Applied Econometrics和Journal of Health Economics 等国外顶级学术刊物上。