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Estimation of High-Dimensional Matrix Factor Models with Change Points

Author

Listed:
  • Peng Lijie

    (College of Mathematics and Science, 12544 Shanghai Normal University , Shanghai 200234, China)

  • Zou Guchu

    (Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai, China)

  • Wu Jianhong

    (College of Mathematics and Science, 12544 Shanghai Normal University , Shanghai 200234, China)

Abstract

In this paper, we focus on the high-dimensional matrix factor models with change points. We first consider the matrix factor model with a single change point, and propose a least squares estimation method to identify the change point. When the number of change points is unknown, a two-step estimation procedure is developed to identify all the change points. Under some mild conditions, the estimator of the number of change points can be proved to be consistent, and the distance between the estimated and true change points can be proved to be stochastically bounded. Monte Carlo simulation study and real data analysis are carried out for illustration.

Suggested Citation

  • Peng Lijie & Zou Guchu & Wu Jianhong, 2026. "Estimation of High-Dimensional Matrix Factor Models with Change Points," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 30(2), pages 175-196.
    • Handle: RePEc:bpj:sndecm:v:30:y:2026:i:2:p:175-196:n:1003
    DOI: 10.1515/snde-2024-0044
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    Keywords

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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