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Model selection when there are multiple breaks

  • Castle, Jennifer L.
  • Doornik, Jurgen A.
  • Hendry, David F.

We consider model selection facing uncertainty over the choice of variables and the occurrence and timing of multiple location shifts. General-to-simple selection is extended by adding an impulse indicator for every observation to the set of candidate regressors: see Johansen and Nielsen (2009). We apply that approach to a fat-tailed distribution, and to processes with breaks: Monte Carlo experiments show its capability of detecting up to 20 shifts in 100 observations, while jointly selecting variables. An illustration to US real interest rates compares impulse-indicator saturation with the procedure in Bai and Perron (1998).

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 169 (2012)
Issue (Month): 2 ()
Pages: 239-246

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Handle: RePEc:eee:econom:v:169:y:2012:i:2:p:239-246
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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  1. Garcia, R. & Perron, P., 1990. "An Anlysis Of The Real Interest Rate Under Regime Shifts," Papers 353, Princeton, Department of Economics - Econometric Research Program.
  2. Kevin Hoover & Stephen J. Perez, 2003. "Data Mining Reconsidered: Encompassing And The General-To-Specific Approach To Specification Search," Working Papers 9727, University of California, Davis, Department of Economics.
  3. David F. Hendry & Hans-Martin Krolzig, 2005. "The Properties of Automatic "GETS" Modelling," Economic Journal, Royal Economic Society, vol. 115(502), pages C32-C61, 03.
  4. Hannes Leeb & Benedikt M. Poetscher, 2000. "The Finite-Sample Distribution of Post-Model-Selection Estimators, and Uniform Versus Non-Uniform Approximations," Econometrics 0004001, EconWPA.
  5. BAI, Jushan & PERRON, Pierre, 1998. "Computation and Analysis of Multiple Structural-Change Models," Cahiers de recherche 9807, Universite de Montreal, Departement de sciences economiques.
  6. Castle Jennifer L. & Doornik Jurgen A & Hendry David F., 2011. "Evaluating Automatic Model Selection," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-33, February.
  7. Edward E. Leamer, 1982. "Let's Take the Con Out of Econometrics," UCLA Economics Working Papers 239, UCLA Department of Economics.
  8. David Hendry & Carlos Santos, 2010. "An Automatic Test of Super Exogeneity," Economics Series Working Papers 476, University of Oxford, Department of Economics.
  9. David F. Hendry & Bent Nielsen, 2007. "Preface to Econometric Modeling: A Likelihood Approach
    [Econometric Modeling: A Likelihood Approach]
    ," Introductory Chapters, Princeton University Press.
  10. David Hendry & Søren Johansen & Carlos Santos, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 337-339, April.
  11. Jurgen A. Doornik, 2008. "Encompassing and Automatic Model Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 915-925, December.
  12. Jerzy Mycielski & Michal Kurcewicz, 2004. "A Specification Search Algorithm for Cointegrated Systems," Computing in Economics and Finance 2004 321, Society for Computational Economics.
  13. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
  14. Leeb, Hannes & P tscher, Benedikt M., 2005. "Model Selection And Inference: Facts And Fiction," Econometric Theory, Cambridge University Press, vol. 21(01), pages 21-59, February.
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