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Structural Changes in High Dimensional Factor Models

Author

Listed:
  • Jushan Bai

    (Department of Economics, Columbia University, New York, NY 10027, USA; School of Finance, Nankai University, Tianjin 300071, China)

  • Xu Han

    (Department of Economics and Finance, City University of Hong Kong, Hong Kong, China)

Abstract

This paper provides a survey on recent developments in structural changes for high dimensional factor models. Compared with conventional low-dimensional time series, structural changes in factor models are more complicated due to the unobservability of factors and factor loadings. The following topics are covered in this survey: the identification conditions for the structural changes in the factor loadings, different impacts of big and small breaks in factor models, tests for structural changes in the factor loadings of a specific variable, tests for structural changes in the factor loading matrix, joint tests for structural changes in the factor loadings and coefficients in factor-augmented regressions, tests for smooth changes in the factor loadings, estimation of break dates, and model selection in factor models with structural changes via the shrinkage method.

Suggested Citation

  • Jushan Bai & Xu Han, 2016. "Structural Changes in High Dimensional Factor Models," Frontiers of Economics in China-Selected Publications from Chinese Universities, Higher Education Press, vol. 11(1), pages 9-39, March.
    • Handle: RePEc:fec:journl:v:11:y:2016:i:1:p:9-39
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    File URL: http://journal.hep.com.cn/fec/EN/10.3868/s060-005-016-0003-9
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    Citations

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    Cited by:

    1. Matteo Barigozzi & Daniele Massacci, 2022. "Modelling Large Dimensional Datasets with Markov Switching Factor Models," Papers 2210.09828, arXiv.org, revised Dec 2023.
    2. Duan, Jiangtao & Bai, Jushan & Han, Xu, 2023. "Quasi-maximum likelihood estimation of break point in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 233(1), pages 209-236.
    3. Bai, Jushan & Han, Xu & Shi, Yutang, 2020. "Estimation and inference of change points in high-dimensional factor models," Journal of Econometrics, Elsevier, vol. 219(1), pages 66-100.
    4. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Papers 1805.03807, arXiv.org.
    5. Baltagi, Badi H. & Kao, Chihwa & Wang, Fa, 2021. "Estimating and testing high dimensional factor models with multiple structural changes," Journal of Econometrics, Elsevier, vol. 220(2), pages 349-365.
    6. Duván Humberto Cataño & Carlos Vladimir Rodríguez-Caballero & Daniel Peña, 2019. "Wavelet Estimation for Dynamic Factor Models with Time-Varying Loadings," CREATES Research Papers 2019-23, Department of Economics and Business Economics, Aarhus University.
    7. Daniel Wochner, 2020. "Dynamic Factor Trees and Forests – A Theory-led Machine Learning Framework for Non-Linear and State-Dependent Short-Term U.S. GDP Growth Predictions," KOF Working papers 20-472, KOF Swiss Economic Institute, ETH Zurich.

    More about this item

    Keywords

    factor models; structural changes; break date;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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