时间：2026年4月17日（周五）10：00-11:30

地点：北京大学经济学院107会议室

主持老师：（北大经院）王法

参与老师：（北大经院）王一鸣、刘蕴霆、王熙、李少然、巩爱博

（北大国发院）黄卓、沈艳、张俊妮、常晋源

主讲人：

Junlong Feng（香港科技大学助理教授）

报告摘要：

We propose a new factor analysis framework and estimators of the factors and loadings that are robust to weak factors in a large N and large T setting. Our framework, by simultaneously considering all quantile levels of the outcome variable, induces standard mean and quantile factor models, but the factors can have an arbitrarily weak influence on the outcome’s mean or quantile at most quantile levels. Our method estimates the factor space at the root-N-rate without requiring the knowledge of weak factors’ presence or strength, and achieves root-N and root-T-asymptotic normality for the factors and loadings based on a novel sample splitting approach that handles incidental nuisance parameters. We also develop a weak-factor-robust estimator of the number of factors and consistent selectors of factors of any tolerated level of influence on the outcome’s mean or quantiles. Monte Carlo simulations demonstrate the effectiveness of our method. 

主讲人简介：

Junlong Feng is an assistant professor at the Hong Kong University of Science and Technology. He received his PhD in Economics at Columbia University in 2020. His primary research interest is econometric theory and his papers appear on Journal of Econometrics and Econometric Theory.