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Recent Developments in Factor Models and Applications in Econometric Learning

Author

Listed:
  • Jianqing Fan

    (Department of Operations Research and Financial Engineering, Princeton University, Princeton, New Jersey 08544, USA)

  • 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)

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.

Suggested Citation

  • Jianqing Fan & Kunpeng Li & Yuan Liao, 2021. "Recent Developments in Factor Models and Applications in Econometric Learning," Annual Review of Financial Economics, Annual Reviews, vol. 13(1), pages 401-430, November.
    • Handle: RePEc:anr:refeco:v:13:y:2021:p:401-430
    DOI: 10.1146/annurev-financial-091420-011735
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    Citations

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    Cited by:

    1. Chen, Liang & Dolado, Juan José & Gonzalo, Jesús & Pan, Haozi, 2023. "Estimation of characteristics-based quantile factor models," UC3M Working papers. Economics 37095, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Giorgio Gnecco & Sara Landi & Massimo Riccaboni, 2024. "The emergence of social soft skill needs in the post COVID-19 era," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(1), pages 647-680, February.
    3. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A semiparametric approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Mar 2023.
    4. Sandro Heiniger, 2024. "Data-driven model selection within the matrix completion method for causal panel data models," Papers 2402.01069, arXiv.org.

    More about this item

    Keywords

    factor models; spiked low-rank matrix; matrix completion; unbalanced panel; factor adjustments; robustness; model selection; multiple testing; high-dimensional statistics;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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