Statistical testing in forecasting model selection

Stephen F. Witt, Haiyan Song, Panos Louvieris

Research output: Journal article publicationJournal articleAcademic researchpeer-review

87 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)151-158
Number of pages8
JournalJournal of Travel Research
Issue number2
Publication statusPublished - 1 Jan 2003
Externally publishedYes


  • Econometric model
  • Forecast accuracy
  • Forecasting bias
  • Statistical testing
  • Time-series model

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Transportation
  • Tourism, Leisure and Hospitality Management


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