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Determining the number of breaks in a piecewise linear regression model

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  • Strikholm, Birgit

    ()
    (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

In this paper we propose a sequential method for determining the number of breaks in piecewise linear structural break models. An advantage of the method is that it is based on standard statistical inference. Tests available for testing linearity against switching regression type nonlinearity are applied sequentially to determine the number of regimes in the structural break model. A simulation study is performed in order to investigate the finite-sample behaviour of the procedure and to compare it with other alternatives. We find that our method works well in comparison for both single and multiple break cases.

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Bibliographic Info

Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 648.

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Length: 30 pages
Date of creation: 13 Dec 2006
Date of revision:
Handle: RePEc:hhs:hastef:0648

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Related research

Keywords: Model specification; multiple structural breaks.;

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References

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  1. Bai, Jushan & Lumsdaine, Robin L & Stock, James H, 1998. "Testing for and Dating Common Breaks in Multivariate Time Series," Review of Economic Studies, Wiley Blackwell, vol. 65(3), pages 395-432, July.
  2. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, vol. 62(2), pages 211-228, June.
  3. Strikholm, Birgit & Teräsvirta, Timo, 2005. "Determining the Number of Regimes in a Threshold Autoregressive Model Using Smooth Transition Autoregressions," Working Paper Series in Economics and Finance 578, Stockholm School of Economics, revised 11 Feb 2005.
  4. Prodan, Ruxandra, 2008. "Potential Pitfalls in Determining Multiple Structural Changes With an Application to Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 50-65, January.
  5. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-56, July.
  6. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
  7. Jushan Bai & Pierre Perron, 2003. "Critical values for multiple structural change tests," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 72-78, 06.
  8. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
  9. Timo Terasvirta & Andrés González, . "Modelling autoregressive processes with a shifting mean," Borradores de Economia 420, Banco de la Republica de Colombia.
  10. Eitrheim, Øyvind & Teräsvirta, Timo, 1995. "Testing the Adequacy of Smooth Transition Autoregressive Models," Working Paper Series in Economics and Finance 56, Stockholm School of Economics.
  11. Bai, Jushan, 1999. "Likelihood ratio tests for multiple structural changes," Journal of Econometrics, Elsevier, vol. 91(2), pages 299-323, August.
  12. repec:cup:etheor:v:13:y:1997:i:3:p:315-52 is not listed on IDEAS
  13. Jushan Bai, 1995. "Estimating Multiple Breaks One at a Time," Working papers 95-18, Massachusetts Institute of Technology (MIT), Department of Economics.
  14. Mohamed Safouane Ben Aissa & Mohamed Boutahar & Jamel Jouini, 2004. "Bai and Perron's and spectral density methods for structural change detection in the US inflation process," Applied Economics Letters, Taylor & Francis Journals, vol. 11(2), pages 109-115.
  15. Yao, Yi-Ching, 1988. "Estimating the number of change-points via Schwarz' criterion," Statistics & Probability Letters, Elsevier, vol. 6(3), pages 181-189, February.
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Cited by:
  1. Toriello, Alejandro & Vielma, Juan Pablo, 2012. "Fitting piecewise linear continuous functions," European Journal of Operational Research, Elsevier, vol. 219(1), pages 86-95.
  2. Hillebrand Eric & Medeiros Marcelo C. & Xu Junyue, 2013. "Asymptotic Theory for Regressions with Smoothly Changing Parameters," Journal of Time Series Econometrics, De Gruyter, vol. 5(2), pages 133-162, April.

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