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Estimation of Weak Factor Models

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  • Yoshimasa Uematsu
  • Takashi Yamagata

Abstract

This paper proposes a novel estimation method for the weak factor models, a slightly stronger version of the approximate factor models of Chamberlain and Rothschild (1983), with large cross-sectional and time-series dimensions (N and T, respectively). It assumes that the kth largest eigenvalue of data covariance matrix grows proportionally to N^ak with unknown exponents 0

Suggested Citation

  • Yoshimasa Uematsu & Takashi Yamagata, 2019. "Estimation of Weak Factor Models," ISER Discussion Paper 1053r, Institute of Social and Economic Research, Osaka University, revised Mar 2020.
    • Handle: RePEc:dpr:wpaper:1053r
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    File URL: https://www.iser.osaka-u.ac.jp/library/dp/2019/DP1053R.pdf
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    References listed on IDEAS

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    Cited by:

    1. Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2021. "Measurement of factor strength: Theory and practice," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 587-613, August.
    2. Yoshimasa Uematsu & Takashi Yamagata, 2020. "Inference in Weak Factor Models," ISER Discussion Paper 1080, Institute of Social and Economic Research, Osaka University.
    3. Bin Peng & Liangjun Su & Joakim Westerlund & Yanrong Yang, 2021. "Interactive Effects Panel Data Models with General Factors and Regressors," Monash Econometrics and Business Statistics Working Papers 23/21, Monash University, Department of Econometrics and Business Statistics.
    4. Freyaldenhoven, Simon, 2022. "Factor models with local factors — Determining the number of relevant factors," Journal of Econometrics, Elsevier, vol. 229(1), pages 80-102.
    5. Choi, In & Lin, Rui & Shin, Yongcheol, 2023. "Canonical correlation-based model selection for the multilevel factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 22-44.

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