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A SETAR Model for Canadian GDP: Non-Linearities and Forecast Comparisons

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Abstract

In this paper we investigate the forecasting performance of the non-linear time series SETAR model by using Canadian GDP data from 1965 to 2000. Besides the with-in-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, 1-step-ahead and multi-step-ahead forecasting are compared for each type of model.

Suggested Citation

  • 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.
    • Handle: RePEc:vic:vicewp:0206
    Note: ISSN 1485-6441
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    Cited by:

    1. Hui Feng, 2009. "Real-time or current vintage: does the type of data matter for forecasting and model selection?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(3), pages 183-193.
    2. Cai, Yuzhi, 2007. "A quantile approach to US GNP," Economic Modelling, Elsevier, vol. 24(6), pages 969-979, November.
    3. Grabowski Daniel & Winker Peter & Staszewska-Bystrova Anna, 2017. "Generating prediction bands for path forecasts from SETAR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(5), pages 1-18, December.
    4. Miquel Clar & Juan-Carlos Duque & Rosina Moreno, 2007. "Forecasting business and consumer surveys indicators-a time-series models competition," Applied Economics, Taylor & Francis Journals, vol. 39(20), pages 2565-2580.
    5. Tarlok Singh, 2012. "Testing nonlinearities in economic growth in the OECD countries: an evidence from SETAR and STAR models," Applied Economics, Taylor & Francis Journals, vol. 44(30), pages 3887-3908, October.

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    More about this item

    Keywords

    Theshold model; non-linearities; forecasting; ARIMA model;
    All these keywords.

    JEL classification:

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

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