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Estimation of high-dimensional factor models with multiple structural changes

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  • Wang, Lu
  • Wu, Jianhong

Abstract

This paper considers a high-dimensional factor model with unknown number of breaks. A simple two-step procedure is proposed to determine the number of breaks and identify break dates. It can be shown that the estimator of the number of breaks is consistent and the distance between the estimated and actual break dates is stochastically bounded under some mild conditions. Monte Carlo simulations demonstrate that the proposed method has desired performance in finite samples. Two real data are analyzed for illustrations. Overall, the proposed method could be expected to be more straightforward to determine the number of breaks in the underlying factor model.

Suggested Citation

  • Wang, Lu & Wu, Jianhong, 2022. "Estimation of high-dimensional factor models with multiple structural changes," Economic Modelling, Elsevier, vol. 108(C).
    • Handle: RePEc:eee:ecmode:v:108:y:2022:i:c:s0264999321003321
    DOI: 10.1016/j.econmod.2021.105743
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    References listed on IDEAS

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    Cited by:

    1. Zhou, Ruichao & Wu, Jianhong, 2023. "Determining the number of change-points in high-dimensional factor models by cross-validation with matrix completion," Economics Letters, Elsevier, vol. 232(C).

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    More about this item

    Keywords

    High dimensional factor models; Structural changes; The number of breaks; Break dates;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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