Recent Developments in Factor Models and Applications in Econometric Learning

Jianqing Fan, Kunpeng Li, Yuan Liao

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)401-430
Number of pages30
JournalAnnual Review of Financial Economics
Volume13
DOIs
StatePublished - Nov 1 2021

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics and Econometrics

Keywords

  • Factor adjustments
  • Factor models
  • High-dimensional statistics
  • Matrix completion
  • Model selection
  • Multiple testing
  • Robustness
  • Spiked low-rank matrix
  • Unbalanced panel

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