主讲人简介: | Liangjun Su is Chair Professor of Economics in the School of Economics and Management, Tsinghua University. He earned his PhD in economics at the University of California, San Diego in 2004 and spent his first four years as assistant and associate professor in the Guanghua School of Management, Peking University before moving to the Singapore Management University (SMU) in 2008. He became a full professor of economics at SMU in July 2012 and one of the first named chair professors of economics at SMU in July 2016. He decided to move back to China and join Tsinghua University in 2020. Professor Su’s main research interests include econometric theory, nonparametric econometrics, panel data models, factor models, big data analysis, and machine learning. He has published more than 70 papers on top international economics, statistics and informatics journals such as Econometrica, Econometric Theory, IEEE Transactions on Information Theory, Journal of Machine Learning Research, Journal of Applied Econometrics, Journal of Econometrics, Journal of the American Statistical Association, Journal of Business & Economic Statistics, and Quantitative Economics. |
讲座简介: | This paper studies uniform inference in a linear panel data model when the slope coefficients may exhibit heterogeneity over both the individual and time dimensions and they can be correlated with the regressors. We propose a generalized fixed effects (GFE) estimation procedure to estimate the model under suitable identification restrictions. To establish the asymptotic properties of the GFE estimators, we invert a number of large dimensional square matrices by approximating them with quasi-Kronecker structured matrices. We establish the asymptotic normality of our GFE estimators and show that their convergence rates depend on the unknown degree of parameter heterogeneity. To make a uniform inference on the common slope component, we propose a novel triple-bootstrap procedure and a hybrid procedure to estimate the asymptotic variance. |