Policy Analysis Using Multilevel Regression Models with Group Interactive Fixed Effects
报告人: 龚桢皓 (山西财经大学)
时间:2024-02-22 15:10-17:00
地点:Room 217, Guanghua Building 2
Abstract:
The use of multilevel regression models is prevalent in policy analysis to estimate the effect of group level policies on individual outcomes. In order to allow for the time varying effect of group heterogeneity and the group specific impact of time effects, we propose a group interactive fixed effects approach that employs interaction terms of group factor loadings and common factors in this model. For this approach, we consider the least squares estimator and associated inference procedure. We examine their properties under the large n and fixed T asymptotics. The number of groups, G, is allowed to grow but at a slower rate. We also propose a test for the level of grouping to specify group factor loadings, and a GMM approach to address policy endogeneity with respect to idiosyncratic errors. Finally, we provide empirical illustrations of the proposed approach using two empirical examples.
About the Speaker:
龚桢皓,美国康涅狄格大学(University of Connecticut)经济学博士,山西财经大学经济学院和智能管理会计研究院助理教授。主要研究方向为计量经济学、劳动经济学、大数据分析及机器学习在经济学的应用。论文在《Journal of Business & Economic Statistics》和《Empirical Economics》上发表。

Your participation is warmly welcomed!

欢迎扫码关注北大统计科学中心公众号,了解更多讲座信息!