A multi-step procedure to determine the number of factors in large approximate factor models

Ronghua Luo, Jiakun Jiang, Wei Lan, Chengliang Yan and Yue Ding

Communications in Statistics - Theory and Methods, 2021, vol. 50, issue 17, 3988-3999

Abstract: We propose in this article a multi-step procedure to determine the number of common factors in large approximate factor models (Chamberlain and Rothschild 1983) in the spirit of the eigenvalue ratio (ER) criterion of Ahn and Horenstein (2013). We show theoretically that this multi-step procedure can consistently identify the true number of factors while both relatively strong and weak factors simultaneously exist, which is not easy to perform with the ER criterion. Our extensive simulation results demonstrate that the proposed procedure has better finite sample properties compared with that of the ER criterion under certain cases.

Date: 2021
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DOI: 10.1080/03610926.2019.1710752

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