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On SETAR non- linearity and forecasting

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Author Info

  • Clements, M.P.
  • Franses, Ph.H.B.F.
  • Smith, J.

Abstract

We consider the usefulness of the two-regime SETAR model for out-of-sample forecasting, and compare it with a linear AR model. A range of newly-developed forecast evaluation techniques are employed. Our simulation results show that time-series data need to exhibit a substantial degree of non-linearity before the SETAR model is favoured on some of these criteria. We find only weak evidence that a SETAR model of US GNP provides more accurate forecasts than a linear AR model.

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File URL: http://repub.eur.nl/pub/1567/feweco19990331092909.pdf
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Bibliographic Info

Paper provided by Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute in its series Econometric Institute Research Papers with number EI 9914-/A.

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Date of creation: 12 Mar 1999
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Handle: RePEc:ems:eureir:1567

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Keywords: SETAR model; linear AR model; out-of-sample forecasting;

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References

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  1. Kenneth D. West & Michael W. McCracken, 1998. "Regression-Based Tests of Predictive Ability," NBER Technical Working Papers 0226, National Bureau of Economic Research, Inc.
  2. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207, September.
  3. Simon M. Potter, 1993. "A Nonlinear Approach to U.S. GNP," UCLA Economics Working Papers 693, UCLA Department of Economics.
  4. David Peel & Alan Speight, 1994. "Testing for non-linear dependence in inter-war exchange rates," Review of World Economics (Weltwirtschaftliches Archiv), Springer, vol. 130(2), pages 391-417, June.
  5. Clements, Michael P & Smith, Jeremy, 1996. "A Monte Carlo Study of the Forecasting Performance of Empirical Setar Models," The Warwick Economics Research Paper Series (TWERPS) 464, University of Warwick, Department of Economics.
  6. repec:att:wimass:9417 is not listed on IDEAS
  7. 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.
  8. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-84, September.
  9. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  10. Chong, Yock Y & Hendry, David F, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Wiley Blackwell, vol. 53(4), pages 671-90, August.
  11. Donald W.K. Andrews & Werner Ploberger, 1992. "Optimal Tests When a Nuisance Parameter Is Present Only Under the Alternative," Cowles Foundation Discussion Papers 1015, Cowles Foundation for Research in Economics, Yale University.
  12. Philip Rothman, 1998. "Forecasting Asymmetric Unemployment Rates," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 164-168, February.
  13. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-62, November.
  14. 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.
  15. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
  16. Krager, Horst & Kugler, Peter, 1993. "Non-linearities in foreign exchange markets: a different perspective," Journal of International Money and Finance, Elsevier, vol. 12(2), pages 195-208, April.
  17. De Gooijer, Jan G. & Kumar, Kuldeep, 1992. "Some recent developments in non-linear time series modelling, testing, and forecasting," International Journal of Forecasting, Elsevier, vol. 8(2), pages 135-156, October.
  18. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
  19. 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.
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Citations

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Cited by:
  1. GIOT, Pierre & PETITJEAN, Mikael, 2006. "The information content of the Bond-Equity Yield Ratio: better than a random walk?," CORE Discussion Papers 2006089, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  2. Miguel Ángel Bermejo & Daniel Peña & Ismael Sánchez, 2009. "Graphical identification of TAR models," Statistics and Econometrics Working Papers ws097723, Universidad Carlos III, Departamento de Estadística y Econometría.
  3. Eleni Constantinou & Robert Georgiades & Avo Kazandjian & George Kouretas, 2005. "Regime Switching and Artificial Neural Network Forecasting," Working Papers 0502, University of Crete, Department of Economics.
  4. Siliverstovs, B. & van Dijk, D.J.C., 2003. "Forecasting industrial production with linear, nonlinear, and structural change models," Econometric Institute Research Papers EI 2003-16, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  5. Costas Milas & Phil Rothman, 2005. "Multivariate STAR Unemployment Rate Forecasts," Econometrics 0502010, EconWPA.
  6. Hui Feng & Jia Liu, 2002. "A SETAR Model for Canadian GDP: Non-Linearities and Forecast Comparisons," Econometrics Working Papers 0206, Department of Economics, University of Victoria.
  7. Duarte, A. & Venetis, I. & Payá, I., 2004. "Curva de rendimientos y crecimiento de la producción real en la UEM: eficiencia y estabilidad predictiva./Yield Curve and Real Output Growth in the EMU: Efficiency and Predictive Stability," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 22, pages 21, Abril.
  8. Gianna Boero & Emanuela Marrocu, 2005. "Evaluating non-linear models on point and interval forecasts: an application with exchange rates," BNL Quarterly Review, Banca Nazionale del Lavoro, vol. 58(232), pages 91-120.
  9. GIOT, Pierre & PETITJEAN, Mikael, 2005. "Dynamic asset allocation between stocks and bonds using the Bond-Equity Yield Ratio," CORE Discussion Papers 2005010, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  10. Angelos Kanas, 2003. "Non-linear forecasts of stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 299-315.
  11. Manzan, S. & Zerom, D., 2005. "A Multi-Step Forecast Density," CeNDEF Working Papers 05-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.

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