| 主讲人简介： | Professor Qi Li is a tenured chair professor at Texas A&M University in the United States. His main research field is econometrics. He has made significant contributions to theoretical econometrics, and his main contributions include econometric model testing and nonparametric/semiparametric model estimation. Since 1991, Professor Li has published more than 150 papers on international journals of economics and statistics, including Econometrica, Review of Economics and Statistics, Journal of Economic Theory, Journal of Econometrics, Economtric Theory, Journal of the American Statistical Association, Annals of Statistics, and Journal of Multivariate Analysis, etc. His book "Nonparametric Econometrics" has become a standard textbook in the field of nonparametric econometrics. In the past few years, he has also served as a co-editor or associate editor of several academic journals such as Journal of Econometrics, Econometric Theory, Econometrics Journal, Econometric Reviews, Economics Letters, Journal of Nonparametric Statistics, etc. |
| 讲座简介： | This paper considers the estimation and inferential of a panel data model with interactive fixed effects using the diversified projections method recently proposed by Fan and Liao (2020). In contrast with existing methods, our estimation method uses cross-sectional weighted averages to project off the unobservable factors, it enjoys merits such as robustness to the pervasive conditions on factor loadings, serial dependent levels, and over-estimating the number of factors. Under some regularity conditions, we prove that the diversified projections estimator is consistent, and has an asymptotic normal distribution. Simulations show that our method performs well in finite samples. An empirical application studying the nexus of GDP growth and financial development further demonstrates that our method leads to more reasonable estimation results compared with the principal component and two-way fixed effects methods. |
