Determining the number of factors in a large-dimensional generalised factor model

2022/03/27 by Rui Wang, Dandan Jiang, Wang, Rui +1
Economics, Econometrics and Finance · Mathematics · #Advanced Algebra and Geometry #C13 #C38 #C43 #FOS: Computer and information sciences #Methodology (stat.ME) #Random Matrices and Applications #Spatial and Panel Data Analysis

paper · pdf · doi:10.48550/arxiv.2203.14236

openalex publication_date 2022/03/27 · openalex created_date 2022/04/03 · openalex updated_date 2026/07/28

Abstract

This paper proposes new estimators of the number of factors for a generalised factor model with more relaxed assumptions than the strict factor model. Under the framework of large cross-sections N and large time dimensions T, we first derive the bias-corrected estimator σ²_* of the noise variance in a generalised factor model by random matrix theory. Then we construct three information criteria based on σ²_*, further propose the consistent estimators of the number of factors. Finally, simulations and real data analysis illustrate that our proposed estimations are more accurate and avoid the overestimation in some existing works.

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