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Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting

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  • Michael Dueker
  • Martin Sola

    ()

  • Fabio Spagnolo

Abstract

This paper proposes a contemporaneous smooth transition threshold autoregressive model (C-STAR) as a modification of the smooth transition threshold autoregressive model surveyed in Teräsvirta (1998), in which the regime weights depend on the ex ante probability that a latent regime-specific variable will exceed a threshold value. We argue that the contemporaneous model is well-suited to rational expectations applications (and pricing exercises), in that it allows the initial regimes does not require to be predetermined. We investigate the properties of the model and evaluate its finitesample maximum likelihood performance. We also propose a method to determine the number of regimes based on a modified Hansen (1992) procedure. Furthermore, we construct multiple-step ahead forecasts and evaluate the forecasting performance of the model. Finally, an empirical application of the short term interest rate yield is presented and discussed.

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Bibliographic Info

Paper provided by Universidad Torcuato Di Tella in its series Department of Economics Working Papers with number 2006-04.

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Length: 37 pages
Date of creation: Apr 2006
Date of revision:
Handle: RePEc:udt:wpecon:2006-04

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Web page: http://www.utdt.edu/ver_contenido.php?id_contenido=439&id_item_menu=568
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Keywords: Smooth Transition Threshold Autoregressive; Forecasting; Nonlinear Models.;

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References

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  1. Pfann, Gerard A. & Schotman, Peter C. & Tschernig, Rolf, 1996. "Nonlinear interest rate dynamics and implications for the term structure," Journal of Econometrics, Elsevier, vol. 74(1), pages 149-176, September.
  2. Fair, Ray C & Shiller, Robert J, 1989. "The Informational Context of Ex Ante Forecasts," The Review of Economics and Statistics, MIT Press, vol. 71(2), pages 325-31, May.
  3. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  4. Michael P. Clements & Hans-Martin Krolzig, 1998. "A comparison of the forecast performance of Markov-switching and threshold autoregressive models of US GNP," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages C47-C75.
  5. Seo, Byeongseon, 2003. "Nonlinear mean reversion in the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11), pages 2243-2265.
  6. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-66, July.
  7. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-89, June.
  8. Dueker, Michael J. & Sola, Martin & Spagnolo, Fabio, 2007. "Contemporaneous threshold autoregressive models: Estimation, testing and forecasting," Journal of Econometrics, Elsevier, vol. 141(2), pages 517-547, December.
  9. Potter, Simon M, 1995. "A Nonlinear Approach to US GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 109-25, April-Jun.
  10. Zacharias Psaradakis & Nicola Spagnolo, 2003. "On The Determination Of The Number Of Regimes In Markov-Switching Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 237-252, 03.
  11. Hansen, B.E., 1991. "Inference when a Nuisance Parameter is Not Identified Under the Null Hypothesis," RCER Working Papers 296, University of Rochester - Center for Economic Research (RCER).
  12. Obstfeld, Maurice & Taylor, Alan M., 1997. "Nonlinear Aspects of Goods-Market Arbitrage and Adjustment: Heckscher's Commodity Points Revisited," Journal of the Japanese and International Economies, Elsevier, vol. 11(4), pages 441-479, December.
  13. Hamilton, James D., 1988. "Rational-expectations econometric analysis of changes in regime : An investigation of the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 385-423.
  14. Potter, Simon M, 1999. " Nonlinear Time Series Modelling: An Introduction," Journal of Economic Surveys, Wiley Blackwell, vol. 13(5), pages 505-28, December.
  15. Gonzalo, Jesus & Pitarakis, Jean-Yves, 2002. "Estimation and model selection based inference in single and multiple threshold models," Journal of Econometrics, Elsevier, vol. 110(2), pages 319-352, October.
  16. Terasvirta, T & Anderson, H M, 1992. "Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S119-36, Suppl. De.
  17. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
  18. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-83, November.
  19. van Dijk, Dick & Strikholm, Birgit & Teräsvirta, Timo, 2001. "The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series," Working Paper Series in Economics and Finance 0429, Stockholm School of Economics, revised 16 May 2002.
  20. Lubrano, M., 1996. "Bayesian Analysis of Nonlinear Time Series Models with Threshold," G.R.E.Q.A.M. 96a12, Universite Aix-Marseille III.
  21. Ait-Sahalia, Yacine, 1996. "Testing Continuous-Time Models of the Spot Interest Rate," Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 385-426.
  22. Caner,M. & Hansen,B.E., 1998. "Threshold autoregression with a near unit root," Working papers 27, Wisconsin Madison - Social Systems.
  23. De Gooijer, Jan G. & De Bruin, Paul T., 1998. "On forecasting SETAR processes," Statistics & Probability Letters, Elsevier, vol. 37(1), pages 7-14, January.
  24. Gray, Stephen F., 1996. "Modeling the conditional distribution of interest rates as a regime-switching process," Journal of Financial Economics, Elsevier, vol. 42(1), pages 27-62, September.
  25. Clements, Michael P & Smith, Jeremy, 1999. "A Monte Carlo Study of the Forecasting Performance of Empirical SETAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(2), pages 123-41, March-Apr.
  26. Enders, Walter & Granger, Clive W J, 1998. "Unit-Root Tests and Asymmetric Adjustment with an Example Using the Term Structure of Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 304-11, July.
  27. Philip Rothman, 1998. "Forecasting Asymmetric Unemployment Rates," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 164-168, February.
  28. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages S61-82, Suppl. De.
  29. Seo, Byeongseon, 2003. "Nonlinear mean reversion in the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 27(11-12), pages 2243-2265, September.
  30. Bruce E. Hansen, 1995. "Erratum: The Likelihood ratio Test Under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Boston College Working Papers in Economics 296., Boston College Department of Economics.
  31. Mehmet Caner & Bruce E. Hansen, 2001. "Threshold Autoregression with a Unit Root," Econometrica, Econometric Society, vol. 69(6), pages 1555-1596, November.
  32. Robert B. Davies, 2002. "Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case," Biometrika, Biometrika Trust, vol. 89(2), pages 484-489, June.
  33. Clements, Michael P. & Smith, Jeremy, 1997. "The performance of alternative forecasting methods for SETAR models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 463-475, December.
  34. Zacharias Psaradakis & Nicola Spagnolo, 2006. "Joint Determination of the State Dimension and Autoregressive Order for Models with Markov Regime Switching," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(5), pages 753-766, 09.
  35. Kapetanios, G., 1999. "Model Selection in Threshold Models," Cambridge Working Papers in Economics 9906, Faculty of Economics, University of Cambridge.
  36. Sola, Martin & Driffill, John, 1994. "Testing the term structure of interest rates using a stationary vector autoregression with regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 18(3-4), pages 601-628.
  37. Koop, Gary & Potter, Simon M, 1999. "Dynamic Asymmetries in U.S. Unemployment," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 298-312, July.
  38. Pesaran, H.M. & Potter, S.M., 1995. "A Floor and Ceiling Model of U.S. Output," Cambridge Working Papers in Economics 9407, Faculty of Economics, University of Cambridge.
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Citations

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Cited by:
  1. Dueker, Michael J. & Sola, Martin & Spagnolo, Fabio, 2007. "Contemporaneous threshold autoregressive models: Estimation, testing and forecasting," Journal of Econometrics, Elsevier, vol. 141(2), pages 517-547, December.
  2. Michael Dueker & Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2009. "Contemporaneous-Threshold Smooth Transition GARCH Models," Department of Economics Working Papers 2009-06, Universidad Torcuato Di Tella.
  3. Dueker, Michael J. & Psaradakis, Zacharias & Sola, Martin & Spagnolo, Fabio, 2011. "Multivariate contemporaneous-threshold autoregressive models," Journal of Econometrics, Elsevier, vol. 160(2), pages 311-325, February.
  4. Bel, K. & Paap, R., 2013. "Modeling the impact of forecast-based regime switches on macroeconomic time series," Econometric Institute Research Papers EI 2013-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  5. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CEIS Research Paper 294, Tor Vergata University, CEIS, revised 15 Oct 2013.
  6. Chen, Haiqiang & Chong, Terence Tai Leung & Bai, Jushan, 2012. "Theory and Applications of TAR Model with Two Threshold Variables," MPRA Paper 54527, University Library of Munich, Germany.
  7. Francesco Battaglia & Mattheos Protopapas, 2012. "Multi–regime models for nonlinear nonstationary time series," Computational Statistics, Springer, vol. 27(2), pages 319-341, June.
  8. Paulo M.M. Rodrigues & Nazarii Salish, 2011. "Modeling and Forecasting Interval Time Series with Threshold Models: An Application to S&P500 Index Returns," Working Papers w201128, Banco de Portugal, Economics and Research Department.
  9. repec:wyi:journl:002152 is not listed on IDEAS
  10. Francesco Battaglia & Mattheos Protopapas, 2012. "An analysis of global warming in the Alpine region based on nonlinear nonstationary time series models," Statistical Methods and Applications, Springer, vol. 21(3), pages 315-334, August.

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