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If Nonlinear Models Cannot Forecast, What Use Are They?

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  • Ramsey James B.

    ()
    (New York University)

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    Abstract

    This paper begins with a brief review of the recent experience using nonlinear models and ideas of chaos to model economic data and to provide forecasts that are better than linear models. The record of improvement is at best meager. The remainder of the paper examines some of the reasons for this lack of improvement. The concepts of "openness" and "isolation" are introduced, and a case is made that open and nonisolated systems cannot be forecasted; the extent to which economic systems are closed and isolated provides the true pragmatic limits to forecastability. The reasons why local "overfitting," especially with nonparametric models, leads to worse forecasts are discussed. Models and "representations" of data are distinguished and the reliance on minimum mean-square forecast error to choose between models and representations is evaluated.

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    File URL: http://www.degruyter.com/view/j/snde.1996.1.2/snde.1996.1.2.1013/snde.1996.1.2.1013.xml?format=INT
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    Bibliographic Info

    Article provided by De Gruyter in its journal Studies in Nonlinear Dynamics & Econometrics.

    Volume (Year): 1 (1996)
    Issue (Month): 2 (July)
    Pages: 1-24

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    Handle: RePEc:bpj:sndecm:v:1:y:1996:i:2:n:1

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    Web page: http://www.degruyter.com

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    Web: http://www.degruyter.com/view/j/snde

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    Cited by:
    1. Buncic, Daniel, 2009. "Understanding forecast failure of ESTAR models of real exchange rates," MPRA Paper 16526, University Library of Munich, Germany.
    2. repec:ebl:ecbull:v:7:y:2005:i:1:p:1-6 is not listed on IDEAS
    3. Golan, Amos & Perloff, Jeffrey M, 2002. "Superior forecasts of the U.S. unemployment rate using a nonparametric method," CUDARE Working Paper Series 956, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
    4. Costas Milas & Jesus Otero & Theodore Panagiotidis, 2001. "Forecasting the spot prices of various coffee types using linear and non-linear error correction models," BORRADORES DE INVESTIGACIÓN 002737, UNIVERSIDAD DEL ROSARIO.
    5. Teräsvirta, Timo, 2005. "Forecasting economic variables with nonlinear models," Working Paper Series in Economics and Finance 598, Stockholm School of Economics, revised 29 Dec 2005.
    6. Ilias Lekkos & Costas Milas & Theodore Panagiotidis, 2007. "Forecasting interest rate swap spreads using domestic and international risk factors: evidence from linear and non-linear models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(8), pages 601-619.
    7. Rapach, David E. & Wohar, Mark E., 2006. "The out-of-sample forecasting performance of nonlinear models of real exchange rate behavior," International Journal of Forecasting, Elsevier, vol. 22(2), pages 341-361.
    8. Sekioua, Sofiane H., 2006. "Nonlinear adjustment in the forward premium: evidence from a threshold unit root test," International Review of Economics & Finance, Elsevier, vol. 15(2), pages 164-183.
    9. Simpson, Paul W & Osborn, Denise R & Sensier, Marianne, 2001. "Forecasting UK Industrial Production over the Business Cycle," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(6), pages 405-24, September.

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