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The Forecasting Performance of Seasonal and Nonlinear Models

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  • Houda Ben Hadj Boubaker

    (The Higher Institute of Management of Tunisia, Tunisia)

Abstract

In this paper, we compare the forecasting performance of seasonal and non linear autoregressive models in terms of point, interval, and density forecasts for the growth rates of the Tunisian industrial production, for the period 1976:1- 2006:2. Our results suggest that the point forecasts generated by the linear models perform better than those provided by the nonlinear models at all horizons. By contrast, the analysis of interval and density forecasts at horizons of one and three quarters provide an evident support for the nonlinear models, this result is in line with the literature. Thus, our findings assess the usefulness of nonlinear models to investigate the dynamic behavior of economic systems and to produce accurate forecasts.

Suggested Citation

  • Houda Ben Hadj Boubaker, 2011. "The Forecasting Performance of Seasonal and Nonlinear Models," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 1(1), pages 26-39, March.
  • Handle: RePEc:asi:aeafrj:2011:p:26-39
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    References listed on IDEAS

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    3. 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.
    4. 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 119-136, Suppl. De.
    5. Marcelo Cunha Medeiros & Álvaro Veiga & Carlos Eduardo Pedreira, 2000. "Modelling exchange rates: smooth transitions, neural networks, and linear models," Textos para discussão 432, Department of Economics PUC-Rio (Brazil).
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    Cited by:

    1. Lozano Carmen & Fuentes Federico, 2012. "Procedure for Creating a Virtual Multibank Agent," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 2(1), pages 163-170, March.

    More about this item

    Keywords

    Seasonality; Nonlinearity; Interval forecasts; Density forecasts; Forecast evaluation tests.;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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