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Combined Forecasts from Linear and Nonlinear Time Series Models

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Author Info
N. Terui (Tohoku University, Japan)
Herman K. van Dijk () (Econometric Institute, Erasmus University Rotterdam)

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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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Publisher Info
Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 00-003/4.

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Date of creation: 10 Feb 2000
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Handle: RePEc:dgr:uvatin:20000003

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Related research
Keywords: Combining forecasts; ExpAR model; Locally linear (or nonlinear) modeling; Threshold model; Time varying coefficient model;

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This paper has been announced in the following NEP Reports: References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. 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. [Downloadable!] (restricted)
  2. Nobuhiko Terui & Takeaki Kariya, 1997. "Gaussianity and Nonlinearity of Foreign Exchange Rates and Macroeconomic Time Series," Tinbergen Institute Discussion Papers 97-004/4, Tinbergen Institute.
  3. Peter C. Schotman & Herman K. van Dijk, 1991. "On Bayesian routes to unit roots," Discussion Paper / Institute for Empirical Macroeconomics 43, Federal Reserve Bank of Minneapolis. [Downloadable!]
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  4. 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.
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Todd E. Clark & Michael W. McCracken, 2004. "Improving forecast accuracy by combining recursive and rolling forecasts," Research Working Paper RWP 04-10, Federal Reserve Bank of Kansas City. [Downloadable!]
    Other versions:
  2. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics. [Downloadable!]
    Other versions:
  3. Costas Milas & Phil Rothman, 2005. "Multivariate STAR Unemployment Rate Forecasts," Econometrics 0502010, EconWPA. [Downloadable!]
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