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Testing for Factor Loading Structural Change under Common Breaks

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  • YAMAMOTO, Yohei
  • TANAKA, Shinya

Abstract

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.

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File URL: http://hermes-ir.lib.hit-u.ac.jp/rs/bitstream/10086/26010/1/070econDP13-17.pdf
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Bibliographic Info

Paper provided by Graduate School of Economics, Hitotsubashi University in its series Discussion Papers with number 2013-17.

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Length: [1], 48 p.
Date of creation: Dec 2013
Date of revision:
Handle: RePEc:hit:econdp:2013-17

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Related research

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

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References

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  1. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 943, Cowles Foundation for Research in Economics, Yale University.
  2. Bai, Jushan, 2010. "Common breaks in means and variances for panel data," Journal of Econometrics, Elsevier, Elsevier, vol. 157(1), pages 78-92, July.
  3. Liang Chen & Juan José Dolado & Jesús Gonzalo, 2011. "Detecting big structural breaks in large factor models," Economics Working Papers we1141, Universidad Carlos III, Departamento de Economía.
  4. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche, Universite de Montreal, Departement de sciences economiques 9552, Universite de Montreal, Departement de sciences economiques.
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  7. Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers, Econometric Society 1504, Econometric Society.
  8. Pierre Perron & Yohei Yamamoto, 2008. "On the Usefulness or Lack Thereof of Optimality Criteria for Structural Change Tests," Boston University - Department of Economics - Working Papers Series, Boston University - Department of Economics wp2008-006, Boston University - Department of Economics.
  9. Donald W.K. Andrews & Werner Ploberger, 1992. "Optimal Tests When a Nuisance Parameter Is Present Only Under the Alternative," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 1015, Cowles Foundation for Research in Economics, Yale University.
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  15. Perron, P., 1989. "Testing For A Unit Root In A Time Series With A Changing Mean," Papers, Princeton, Department of Economics - Econometric Research Program 347, Princeton, Department of Economics - Econometric Research Program.
  16. Alexei Onatski, 2005. "Determining the number of factors from empirical distribution of eigenvalues," Discussion Papers, Columbia University, Department of Economics 0405-19, Columbia University, Department of Economics.
  17. Ai Deng & Pierre Perron, 2005. "A Non-local Perspective on the Power Properties of the CUSUM and CUSUM of Squares Tests for Structural Change," Boston University - Department of Economics - Working Papers Series, Boston University - Department of Economics WP2005-047, Boston University - Department of Economics.
  18. Nelson, Forrest D & Savin, N E, 1990. "The Danger of Extrapolating Asymptotic Local Power," Econometrica, Econometric Society, Econometric Society, vol. 58(4), pages 977-81, July.
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  20. Breitung, Jörg & Eickmeier, Sandra, 2011. "Testing for structural breaks in dynamic factor models," Journal of Econometrics, Elsevier, Elsevier, vol. 163(1), pages 71-84, July.
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Cited by:
  1. Yamamoto, Yohei, 2014. "A Modified Confidence Set for the Structural Break Date in Linear Regression Models," Discussion Papers, Graduate School of Economics, Hitotsubashi University 2014-08, Graduate School of Economics, Hitotsubashi University.

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