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Testing for Factor Loading Structural Change under Common Breaks


  • YAMAMOTO, Yohei
  • TANAKA, Shinya


This paper proposes a new test for factor loading structural change in dynamic factor models. The proposed test is robust to the nonmonotonic power problem that occurs if the factor loadings exhibit structural changes at common dates over cross-sections. To illustrate the usefulness of our test, we first show that the leading test proposed by Breitung and Eickmeier (2011) exhibits nonmonotonic power, essentially because the breaks are considered as spurious factors with stable factor loadings. We use both local and non-local asymptotic frameworks to investigate the power of their test. The new test eliminates the effects of the spurious factors by maximizing the test statistic over possible numbers of the original factors. This approach is effective because the original factors are not identified under the alternative hypothesis. Monte Carlo simulations and an empirical example using U.S. Treasury yield curve data clearly illustrate the validity of the asymptotic power analysis and usefulness of the proposed test.

Suggested Citation

  • YAMAMOTO, Yohei & TANAKA, Shinya, 2013. "Testing for Factor Loading Structural Change under Common Breaks," Discussion Papers 2013-17, Graduate School of Economics, Hitotsubashi University.
  • Handle: RePEc:hit:econdp:2013-17

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    References listed on IDEAS

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    Cited by:

    1. repec:eme:aecozz:s0731-905320150000035011 is not listed on IDEAS
    2. Yamamoto, Yohei, 2014. "A Modified Confidence Set for the Structural Break Date in Linear Regression Models," Discussion Papers 2014-08, Graduate School of Economics, Hitotsubashi University.
    3. Pierre Perron & Tatsushi Oka, 2011. "Testing for Common Breaks in a Multiple Equations System," Boston University - Department of Economics - Working Papers Series WP2011-057, Boston University - Department of Economics.
    4. Laurent Callot & Johannes Tang Kristensen, 2016. "Regularized Estimation of Structural Instability in Factor Models: The US Macroeconomy and the Great Moderation," Advances in Econometrics,in: Dynamic Factor Models, volume 35, pages 437-479 Emerald Publishing Ltd.
    5. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    6. Massacci, Daniele, 2017. "Least squares estimation of large dimensional threshold factor models," Journal of Econometrics, Elsevier, vol. 197(1), pages 101-129.
    7. Luke Hartigan, 2015. "Changes in the Factor Structure of the U.S. Economy: Permanent Breaks or Business Cycle Regimes?," Discussion Papers 2015-17, School of Economics, The University of New South Wales.
    8. HORIE, Tetsushi & YAMAMOTO, Yohei, 2016. "Testing for Speculative Bubbles in Large-Dimensional Financial Panel Data Sets," Discussion Papers 2016-04, Graduate School of Economics, Hitotsubashi University.
    9. Matteo Barigozzi & Lorenzo Trapani, 2017. "Sequential testing for structural stability in approximate factor models," Papers 1708.02786,

    More about this item


    factor model; principal components; common breaks; spurious factors; local alternative asymptotics; fixed alternative asymptotics; nonmonotonic power; yield curve;

    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

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