北航经管学院“经济统计论坛”系列讲座
（2023年第4期，总第15期）
讲座题目：A Tale of Two Types of Structural Instabilities in High Dimensional Factor Models
讲座时间：2023年5月19日（周五），16:00-17:30
会议地址：A949
讲座嘉宾：涂云东教授
讲座嘉宾
涂云东，北京大学光华管理学院和北京大学统计科学中心联席教授。入选“日出东方”北大光华青年人才，北京大学优秀博士学位论文指导教师，教育部高层次人才青年学者。2004年和2006年先后获武汉大学理学学士学位和经济学硕士学位，2012年获美国加州大学河滨分校经济学博士学位。亚太青年计量经济学者会议发起人和组织者。30余篇学术论文发表在多个国际国内知名专业杂志。主持多个国家自然科学基金项目，并担任自然科学基金匿名评审。曾获世界计量经济学会、加州计量经济学会议等学术组织提供的青年学者研究资助。研究领域涵盖时间序列分析、非参数计量方法、大数据分析、金融计量和预测等。
邀请人：康雁飞 副教授
讲座概要
With the increasing availability of large data sets in economics and finance, the large factor model has become one of the most important tools to achieve dimension reduction in the statistical and econometric analysis. To capture the instability caused by economic condition shifts or policy reforms, factor models with structural breaks in the factor loadings are accordingly developed. On the other hand, recurring regime shifts that relate to higher frequency recurring fluctuation arise in situation where “history repeats”, and are conveniently described by threshold factor models, which allow recurring regime shifts in the factor loadings according to the magnitude of a (continuous) threshold variable. In practice, it is often difficult to decide whether structural break or threshold effect, or both types of instabilities one should employ to portray the observed data. This talk shall discuss how to model each type of instability in factor analysis separately first, and then provide a solution to distinguish the two categories in a model that simultaneously allows both types of structural instabilities. The proposed models are estimated by machine learning techniques such as group Lasso, backward elimination algorithms and information criterion-based model selection methods. The associated asymptotic properties are established and are corroborated by finite sample simulation results and empirical examples. This talk is based on joint projects with Chenchen Ma, who is currently a Ph.D. candidate at the Center for Statistical Science, Peking University.
