Indexed by:Journal paper

Document Code:109149

First Author:Jie Wei

Correspondence Author:Hui Chen

Journal:Economics Letters

Included Journals:SCI

Affiliation of Author(s):Huazhong Univ. of S&T

Place of Publication:USA

Discipline:Economics

First-Level Discipline:Applied Economics

Funded by:Ministry of Education of Humanities and Social Sciences Project of China (No. 17YJC790159)

Document Type:J

Volume:191

Issue:6

ISSN No.:0165-1765

Key Words:Approximate factor models K-fold cross validation Consistency Finite sample performance

Date of Publication:2020-04-08

Abstract: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.

Links to published journals:https://doi.org/10.1016/j.econlet.2020.109149