A SETAR model for Canadian GDP: non-linearities and forecast comparisons
AbstractThis paper investigates the forecasting performance of the non-linear time series SETAR model by using Canadian GDP data from 1965 to 2000. Besides the within-sample fit, the forecasting performance of a standard linear ARIMA model for the same sample has also been generated for comparative purposes. Two forecasting methods, one-step-ahead and multi-step-ahead forecasting, are compared for each type of model.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics.
Volume (Year): 35 (2003)
Issue (Month): 18 ()
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Other versions of this item:
- Hui Feng & Jia Liu, 2002. "A SETAR Model for Canadian GDP: Non-Linearities and Forecast Comparisons," Econometrics Working Papers 0206, Department of Economics, University of Victoria.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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