报告人：严晓东
报告地点：腾讯会议ID:109 797 218
报告时间：2021年04月30日星期五10:00-11:00
邀请人：郑术蓉
报告摘要：
Heterogeneous panel data models that allow the coefficients to vary across individuals and/or change over time have received increasingly more attention in statistics and econometrics. This paper proposes a two-dimensional heterogeneous panel regression model with the extensivelyused group structure of individual heterogeneous effects coupled with cohort formation for their time-variations, which allows common coefficients between nonadjacent time points. We introduce a bi-integrative procedure that detects the information regarding group and cohort patterns simultaneously via a doubly penalized least square with concave fused penalties. We use an alternating direction method of multipliers (ADMM) algorithm that automatically bi-integrates the two-dimensional heterogeneous panel data model pertaining to a common one. We develop consistency and asymptotic normality for the proposed estimators, and show that the resulting estimators exhibit oracle properties, i.e., the proposed estimator is asymptotically equivalent to the oracle estimator obtained using the known group and cohort structures. Furthermore, the simulation studies provide supportive evidence that the proposed method has good finite sample performence. A real data empirical application has been provided to highlight the proposed method.
主讲人简介：
严晓东，山东大学金融研究院副研究员，山东大学未来学者，山东大学经济学院杰出青年，博士生导师，云南大学与香港理工大学联合培养博士，香港中文大学研究助理，中国现场统计研究会高维数据统计分会理事，山东省大数据专业建设委员会常务副秘书长，山东省应用统计学会副秘书长。在国际著名期刊The Annals of Statistics, Journal of the American Statistical Association，Journal of Econometrics，以及高水平期刊International Journal of forecasting， Statistica Sinica，Journal of Multivariate Analysis，Statistics in Medicine等发表论文十余篇。目前主持国家自然科学基金，国家博士后留学基金，山东省自然科学基金、山东省社科规划项目基金、山东省青年学者未来计划基金。
