Determining the number of factors in approximate factor models by twice K-fold cross validation

被引：14
|
作者：
Wei, Jie [1 ]
Chen, Hui [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Econ, Wuhan, Hubei, Peoples R China
来源：
ECONOMICS LETTERS | 2020年 / 191卷
基金：
美国国家科学基金会;
关键词：
Approximate factor models; K-fold cross validation; Consistency; Finite sample performance;
D O I：
10.1016/j.econlet.2020.109149
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
We propose a data driven determination method of the number of factors by cross validation (CV) in approximate factor models. A K-fold CV is applied along each of the two directions (individual and time) of a panel dataset. We prove the consistency of the proposed twice K-fold CV under mild conditions. Monte Carlo simulations demonstrate superior and robust performance of our selection method in comparison with existing approaches, especially at small panels with moderate units or time lengths. An empirical application to identify factor numbers in the UK is provided. (C) 2020 Elsevier B.V. All rights reserved.
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页数：6
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