Statistical Testing in Forecasting Model Selection

The ability of various econometric and univariate time-series models to generate accurate forecasts of international tourism demand is evaluated. Accuracy is assessed in terms of error magnitude and also directional change error. Statistical testing for both forecasting bias and directional change f...

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Bibliographic Details
Published in:Journal of travel research 2003-11, Vol.42 (2), p.151-158
Main Authors: Witt, Stephen F., Song, Haiyan, Louvieris, Panos
Format: Article
Language:English
Subjects:
Accuracy
Demand analysis
Estimation bias
Forecasting
Studies
Time series
Tourism
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Summary:The ability of various econometric and univariate time-series models to generate accurate forecasts of international tourism demand is evaluated. Accuracy is assessed in terms of error magnitude and also directional change error. Statistical testing for both forecasting bias and directional change forecasting performance is introduced. The empirical results show that for 1-year-ahead forecasting, the time-varying parameter model performs consistently well. However, for 2- and 3-years-ahead forecasting, the best model varies according to the forecasting error criterion under consideration. This highlights the importance (for longer term forecasts) of selecting a forecasting method that is appropriate for the particular objective of the forecast user.
ISSN:0047-2875
1552-6763
DOI:10.1177/0047287503253941