The Forecasting Performance of Seasonal and Nonlinear Models
AbstractIn 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.
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Bibliographic InfoArticle provided by Asian Economic and Social Society in its journal Asian Economic and Financial Review.
Volume (Year): 1 (2011)
Issue (Month): 1 (March)
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Seasonality; Nonlinearity; Interval forecasts; Density forecasts; Forecast evaluation tests.;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull 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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