统计与管理学院2018年学术报告第50期
【主 题】 Eigenvalue difference test for the number of common factors in the approximate factor models
【报告人】 吴鑑洪, 教授
上海师范大学
【时 间】 2018年12月24日（星期一）10:00-11:00
【地 点】 上海财经大学统计与管理学院大楼1208会议室
【摘 要】This paper proposes a new method for determining the number of common factors in the approximate factor models. Firstly, we construct a nonlinear and monotonous function of eigenvalues such that the function values of the first r largest eigenvalues are close to one and the rest are close to zero when both the number of cross-section units (N) and time series length (T) go to infinity, where $r$ is the real value of the number of common factors. Secondly, we obtain the estimator of the number of common factors by maximizing the difference of function values of two adjacent eigenvalues arranged in descending order. Under some mild conditions, the resulting estimator can be proved to be consistent. Monte Carlo simulation study shows that the new estimator has desired performance.
【嘉宾简介】吴鑑洪，2007年获华东师范大学博士学位，2007.6-2015.11任职于浙江工商大学统计与数学学院， 2012年晋升教授，2015.1聘为博士生导师， 2015.11起任职于上海师范大学数理学院，硕士点学位负责人。主要研究领域为高维因子分析、面板数据计量经济分析、高维时间序列分析、数理统计。
