Control interactive fixed effects with diversified projections
Holder： Hongjun, Li（Tsinghua University）
Time：2023-03-02 15:10-17:00
Location： Room 217, Guanghua Building No. 2
Abstract:
This paper considers estimation and inferential issues of panel data models with interactive fixed effects (IFE) using diversified projections (DP) method proposed recently by Fan and Liao (2022). In contrast with ordinary least square method in Bai (2009) and weighted least square method in Bai and Li (2021), our method enjoys some merits such as robustness to the pervasive conditions on factors, stationarity condition on data, or weak serial dependence. Under some regularity conditions, we prove that the DP estimators are \sqrt{NT}-consistent, and have asymptotically normal distribution. We run Monte Carlo simulations to investigate the finite sample properties of the DP estimators and find its superior performance under the setup alike to real data. We apply our method to the study on the nexus of GDP growth and financial development, and find that the estimate from the DP method is more reasonable than the alternatives in the sense that it is close to the prediction of the related economic theory.
About the Speaker:
李红军，清华大学社会科学学院经济学研究所副教授。现任Journal of Digital Economy副主编，清华大学社会科学学院数字经济专业硕士项目主任，清华大学计算社会科学平台副主任。博士就读于德州农工大学（Texas A&M University），主要从事非参数计量、机器学习、产业组织等领域的理论与实证研究，主持或参与多个国家级基金项目，已有多篇论文发表于Journal of Econometrics, China Economic Review, Economics Letters, Econometric Reviews和 Empirical Economics等经济学期刊。
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