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

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

Author Info

Hui Feng () (Department of Economics, University of Victoria)
Jia Liu () (Department of Economics, University of Victoria)

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Hui Feng

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.

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Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0206.

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Length: 19 pages
Date of creation: 21 Oct 2002
Date of revision:
Handle: RePEc:vic:vicewp:0206

Note: ISSN 1485-6441
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Article
- Hui Feng & Jia Liu, 2003. "A SETAR model for Canadian GDP: non-linearities and forecast comparisons," Applied Economics, Taylor and Francis Journals, vol. 35(18), pages 1957-1964, December. [Downloadable!] (restricted)

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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Other versions:
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Other versions:
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Other versions:
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