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The Forecasting Performance of Seasonal and Nonlinear Models

机译：季节和非线性模型的预测性能

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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.
机译：在本文中，我们从点，区间和密度的角度比较了突尼斯工业生产在1976：1-2006：2期间的季节性，非线性自回归模型的预测性能。我们的结果表明，线性模型生成的点预测在所有范围内的性能均优于非线性模型提供的点预测。相比之下，对四分之三和四分之一的视距的间隔和密度预测的分析为非线性模型提供了明显的支持，这一结果与文献一致。因此，我们的发现评估了非线性模型对调查经济系统动态行为并产生准确预测的有用性。

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