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Modelling autoregressive processes with a shifting mean

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Author Info

  • Timo Terasvirta

    ()

  • Andrés González

    ()

Abstract

This paper contains a nonlinear, nonstationary autoregressive model whose intercept changes deterministically over time. The intercept is a flexible function of time, and its construction bears some resemblance to neural network models. A modelling technique, modified from one for single hidden-layer neural network models, is developed for specification and estimation of the model. Its performance is investigated by simulation and further illustrated by two applications to macroeconomic time series.

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File URL: http://www.banrep.gov.co/docum/ftp/borra420.pdf
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Bibliographic Info

Paper provided by BANCO DE LA REPÚBLICA in its series BORRADORES DE ECONOMIA with number 003230.

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Length: 25
Date of creation: 01 Dec 2006
Date of revision:
Handle: RePEc:col:000094:003230

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Related research

Keywords: deterministic shift; nonlinear autoregression; nonstationarity; nonlinear trend; structural change;

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References

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  1. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
  2. Kleiber, Christian & Zeileis, Achim, 2004. "Validating multiple structural change models : A case study," Technical Reports 2004,34, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  3. Michael Massmann & James Mitchell & Martin Weale, 2003. "Business Cycles and Turning Points: A Survey of Statistical Techniques," National Institute Economic Review, National Institute of Economic and Social Research, vol. 183(1), pages 90-106, January.
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  7. 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.
  8. James Morley & Charles Nelson & Eric Zivot, 2002. "Why Are Beveridge-Nelson and Unobserved-Component Decompositions of GDP So Different?," Working Papers UWEC-2002-01, University of Washington, Department of Economics.
  9. Racine, Jeff, 1997. "Feasible Cross-Validatory Model Selection for General Stationary Processes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 169-79, March-Apr.
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  13. Jansen, Eilev S. & Teräsvirta, Timo, 1995. "Testing Parameter Constancy and super Exogeneity in Econometric Equations," Working Paper Series in Economics and Finance 53, Stockholm School of Economics.
  14. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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  16. Racine, Jeff, 2000. "Consistent cross-validatory model-selection for dependent data: hv-block cross-validation," Journal of Econometrics, Elsevier, vol. 99(1), pages 39-61, November.
  17. Marianne Baxter & Robert G. King, 1995. "Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series," NBER Working Papers 5022, National Bureau of Economic Research, Inc.
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  19. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
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Citations

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Cited by:
  1. Cushman, David O. & Michael, Nils, 2011. "Nonlinear trends in real exchange rates: A panel unit root test approach," Journal of International Money and Finance, Elsevier, vol. 30(8), pages 1619-1637.
  2. Matthew T. Holt & Timo Teräsvirta, 2012. "Global Hemispheric Temperature Trends and Co–Shifting: A Shifting Mean Vector Autoregressive Analysis," CREATES Research Papers 2012-54, School of Economics and Management, University of Aarhus.
  3. Richard T. Baillie & Claudio Morana, 2007. "Modeling Long Memory and Structural Breaks in Conditional Variances: an Adaptive FIGARCH Approach," ICER Working Papers - Applied Mathematics Series 11-2007, ICER - International Centre for Economic Research.
  4. Strikholm, Birgit, 2006. "Determining the number of breaks in a piecewise linear regression model," Working Paper Series in Economics and Finance 648, Stockholm School of Economics.
  5. Enders, Walter & Holt, Matthew T., 2011. "Breaks, bubbles, booms, and busts: the evolution of primary commodity price fundamentals," MPRA Paper 31461, University Library of Munich, Germany.
  6. Andrés González & Kirstin Hubrich & Timo Teräsvirta, 2009. "Forecasting inflation with gradual regime shifts and exogenous information," CREATES Research Papers 2009-03, School of Economics and Management, University of Aarhus.
  7. Anders Bredahl Kock & Timo Teräsvirta, 2010. "Forecasting with nonlinear time series models," CREATES Research Papers 2010-01, School of Economics and Management, University of Aarhus.
  8. Håvard Hungnes, 2012. "Testing for co-non-linearity," Discussion Papers 699, Research Department of Statistics Norway.

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