【报告摘要】In this paper, we propose an easy-to-implement residual-based specification testing procedure for detecting structural changes in factor models, which is powerful against both smooth and abrupt structural changes with unknown break dates. The proposed test is robust to the over-specified number of factors, and serially and cross-sectionally correlated error processes. A new central limit theorem is given for the quadratic forms of panel data with dependence over both dimensions, thereby filling a gap in the literature. We establish the asymptotic properties of the proposed test statistic, and accordingly develop a simulation-based scheme to select critical value in order to improve finite sample performance. Through extensive simulations and a real-world application, we confirm our theoretical results and demonstrate that the proposed test exhibits desirable size and power in practice.

【报告人简介】严雅毅，上海财经大学统计与管理学院副教授，2022年获莫纳什大学计量经济学博士学位。主要研究领域为计量经济学理论、实证资产定价等，已在Journal of the American Statistical Association、Journal of Econometrics、Journal of Business & Economic Statistics、Econometric Theory等期刊发表10余篇论文。获国自然青年基金资助，并入选上海市领军人才（海外）青年项目。