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Combined forecasts from linear and nonlinear time series models

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  • Terui, N.
  • van Dijk, H.K.

Abstract

Combined forecasts from a linear and a nonlinear model are investigated for time series with possibly nonlinear characteristics. The forecasts are combined by a constant coefficient regression method as well as a time varying method. The time varying method allows for a locally (non)linear model. The methods are applied to data from two kinds of disciplines: the Canadian lynx and sunspot series from the natural sciences, and Nelson-Plosser's U.S. series from economics. It is shown that the combined forecasts perform well, especially with time varying coefficients. This result holds for out of sample performance for the sunspot and Canadian lynx number series, but it does not uniformly hold for economic time series.

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File URL: http://repub.eur.nl/pub/1621/ei9949f.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 9949-/A.

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Date of creation: 08 Dec 1999
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Handle: RePEc:ems:eureir:1621

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Related research

Keywords: combining forecasts; expAR model; locally linear modeling; threshold model; time varying coefficient model;

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  1. 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), University of Warwick, Department of Economics 464, University of Warwick, Department of Economics.
  2. De Gooijer, Jan G. & Kumar, Kuldeep, 1992. "Some recent developments in non-linear time series modelling, testing, and forecasting," International Journal of Forecasting, Elsevier, Elsevier, vol. 8(2), pages 135-156, October.
  3. Terui, Nobuhiko & van Dijk, Herman K., 2002. "Combined forecasts from linear and nonlinear time series models," International Journal of Forecasting, Elsevier, Elsevier, vol. 18(3), pages 421-438.
  4. Clements, Michael P. & Smith, Jeremy, 1997. "The performance of alternative forecasting methods for SETAR models," International Journal of Forecasting, Elsevier, Elsevier, vol. 13(4), pages 463-475, December.
  5. Cooley, Thomas F & Prescott, Edward C, 1976. "Estimation in the Presence of Stochastic Parameter Variation," Econometrica, Econometric Society, Econometric Society, vol. 44(1), pages 167-84, January.
  6. Dwight B. Crane & James R. Crotty, 1967. "A Two-Stage Forecasting Model: Exponential Smoothing and Multiple Regression," Management Science, INFORMS, INFORMS, vol. 13(8), pages B501-B507, April.
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