Recent Developments in Factor Models and Applications in Econometric Learning

Jianqing Fan, Kunpeng Li and Yuan Liao
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Kunpeng Li: International School of Economics and Management, Capital University of Economics and Business, Beijing 100070, China
Yuan Liao: Department of Economics, Rutgers University, New Brunswick, New Jersey 08901, USA

Annual Review of Financial Economics, 2021, vol. 13, issue 1, 401-430

Abstract: This article provides a selective overview of the recent developments in factor models and their applications in econometric learning. We focus on the perspective of the low-rank structure of factor models and particularly draw attention to estimating the model from the low-rank recovery point of view. Our survey mainly consists of three parts. The first part is a review of new factor estimations based on modern techniques for recovering low-rank structures of high-dimensional models. The second part discusses statistical inferences of several factor-augmented models and their applications in statistical learning models. The final part summarizes new developments dealing with unbalanced panels from the matrix completion perspective.

Keywords: factor models; spiked low-rank matrix; matrix completion; unbalanced panel; factor adjustments; robustness; model selection; multiple testing; high-dimensional statistics (search for similar items in EconPapers)
JEL-codes: C01 C58 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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DOI: 10.1146/annurev-financial-091420-011735

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