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Detecting big structural breaks in large factor models

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  • Liang Chen

    ()

  • Juan José Dolado

    ()

  • Jesús Gonzalo

    ()

Abstract

Time invariance of factor loadings is a standard assumption in the analysis of large factor models. Yet, this assumption may be restrictive unless parameter shifts are mild (i.e., local to zero). In this paper we develop a new testing procedure to detect big breaks in these loadings at either known or unknown dates. It relies upon testing for parameter breaks in a regression of the first of the r¯ factors estimated by PCA on the remaining r¯ - 1 factors, where r¯ is chosen according to Bai and Ng’s (2002) information criteria. The test fares well in terms of power relative to other recently proposed tests on this issue, and can be easily implemented to avoid forecasting failures in standard factor-augmented (FAR, FAVAR) models where the number of factors is a priori imposed on the basis of theoretical considerations.

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Bibliographic Info

Paper provided by Universidad Carlos III, Departamento de Economía in its series Economics Working Papers with number we1141.

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Date of creation: Dec 2011
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Handle: RePEc:cte:werepe:we1141

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Keywords: Structural break; Large factor model; Loadings; Principal components;

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References

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Citations

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Cited by:
  1. Chihwa Kao & Lorenzo Trapani & Giovanni Urga, 2012. "Testing for Breaks in Cointegrated Panels," Center for Policy Research Working Papers, Center for Policy Research, Maxwell School, Syracuse University 135, Center for Policy Research, Maxwell School, Syracuse University.
  2. Xu Cheng & Zhipeng Liao & Frank Schorfheide, 2014. "Shrinkage Estimation of High-Dimensional Factor Models with Structural Instabilities," NBER Working Papers 19792, National Bureau of Economic Research, Inc.
  3. YAMAMOTO, Yohei & TANAKA, Shinya, 2013. "Testing for Factor Loading Structural Change under Common Breaks," Discussion Papers, Graduate School of Economics, Hitotsubashi University 2013-17, Graduate School of Economics, Hitotsubashi University.
  4. Cheng, Xu & Liao, Zhipeng & Schorfheide, Frank, 2013. "Shrinkage estimation of high-dimensional factor models with structural instabilities," Working Papers 14-4, Federal Reserve Bank of Philadelphia.
  5. Chen, Liang, 2012. "Identifying observed factors in approximate factor models: estimation and hypothesis testing," MPRA Paper 37514, University Library of Munich, Germany.
  6. Lorenzo Trapani, 2014. "Comments on: Extensions of some classical methods in change point analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, Springer, vol. 23(2), pages 283-286, June.
  7. Corradi, Valentina & Swanson, Norman R., 2014. "Testing for structural stability of factor augmented forecasting models," Journal of Econometrics, Elsevier, Elsevier, vol. 182(1), pages 100-118.
  8. Xu Han & Atsushi Inoue, 2011. "Tests for Parameter Instability in Dynamic Factor Models," TERG Discussion Papers, Graduate School of Economics and Management, Tohoku University 306, Graduate School of Economics and Management, Tohoku University, revised May 2013.

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