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Disentangling Structural Breaks in High Dimensional Factor Models

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Listed:
  • Bonsoo Koo
  • Benjamin Wong
  • Ze-Yu Zhong

Abstract

We disentangle structural breaks in dynamic factor models by establishing a projection based equivalent representation theorem which decomposes any break into a rotational change and orthogonal shift. Our decomposition leads to the natural interpretation of these changes as a change in the factor variance and loadings respectively, which allows us to formulate two separate tests to differentiate between these two cases, unlike the pre-existing literature at large. We derive the asymptotic distributions of the two tests, and demonstrate their good finite sample performance. We apply the tests to the FRED-MD dataset focusing on the Great Moderation and Global Financial Crisis as candidate breaks, and find evidence that the Great Moderation may be better characterised as a break in the factor variance as opposed to a break in the loadings, whereas the Global Financial Crisis is a break in both. Our empirical results highlight how distinguishing between the breaks can nuance the interpretation attributed to them by existing methods.

Suggested Citation

  • Bonsoo Koo & Benjamin Wong & Ze-Yu Zhong, 2023. "Disentangling Structural Breaks in High Dimensional Factor Models," CAMA Working Papers 2023-15, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2023-15
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    File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2023-03/15_2023_koo_wong_zhong.pdf
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    References listed on IDEAS

    as
    1. Han, Xu & Inoue, Atsushi, 2015. "Tests For Parameter Instability In Dynamic Factor Models," Econometric Theory, Cambridge University Press, vol. 31(5), pages 1117-1152, October.
    2. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    3. Chen, Liang, 2015. "Estimating the common break date in large factor models," Economics Letters, Elsevier, vol. 131(C), pages 70-74.
    4. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    factor space; structural instability; breaks; principal components; dynamic factor models;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • 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
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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