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Tourism Forecasting: Accuracy of Alternative Econometric Models Revisited

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  • Haiyan Song
  • Egon Smeral

    (WIFO)

  • Gang Li
  • Jason L. Chen

Abstract

This study evaluates the forecasting accuracy of five alternative econometric models in the context of predicting the quarterly international tourism demand in 25 countries or country groupings. Tourism demand is measured in terms of tourist expenditure by inbound international visitors in a destination. Two univariate time series models are included in the forecasting comparison as benchmarks. Accuracy is assessed in terms of error magnitude. Seasonality is an important feature of forecasting models and requires careful handling. For each of the 25 destinations, individual models are estimated over the 1980Q1-2005Q1 period, and forecasting performance is assessed using data covering the 2005Q2-2007Q1 period. The empirical results show that the time-varying parameter (TVP) model provides the most accurate short-term forecasts, whereas the naïve (no-change) model performs best in long-term forecasting up to two years. This study provides new evidence of the TVP model's outstanding performance in short-term forecasting. Through the incorporation of a seasonal component into the model, the TVP model forecasts short-run seasonal tourism demand well.

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Bibliographic Info

Paper provided by WIFO in its series WIFO Working Papers with number 326.

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Length: 33 pages
Date of creation: 13 Aug 2008
Date of revision:
Handle: RePEc:wfo:wpaper:y:2008:i:326

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Keywords: tourism forecasting; econometric models; time series models; forecasting accuracy;

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References

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  1. James H. Stock & Mark W. Watson, 1994. "Evidence on structural instability in macroeconomic times series relations," Working Paper Series, Macroeconomic Issues 94-13, Federal Reserve Bank of Chicago.
  2. Newey, Whitney K & West, Kenneth D, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Wiley Blackwell, vol. 61(4), pages 631-53, October.
  3. Song, Haiyan & Witt, Stephen F. & Jensen, Thomas C., 2003. "Tourism forecasting: accuracy of alternative econometric models," International Journal of Forecasting, Elsevier, vol. 19(1), pages 123-141.
  4. Darne, Olivier & Diebolt, Claude, 2004. "Unit roots and infrequent large shocks: new international evidence on output," Journal of Monetary Economics, Elsevier, vol. 51(7), pages 1449-1465, October.
  5. Greenslade, Jennifer V. & Hall, Stephen G., 1996. "Modelling economies subject to structural change: The case of Germany," Economic Modelling, Elsevier, vol. 13(4), pages 545-559, October.
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  7. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
  8. Haiyan Song & Peter Romilly & Xiaming Liu, 2000. "An empirical study of outbound tourism demand in the UK," Applied Economics, Taylor & Francis Journals, vol. 32(5), pages 611-624.
  9. Martin, Christine A. & Witt, Stephen F., 1989. "Forecasting tourism demand: A comparison of the accuracy of several quantitative methods," International Journal of Forecasting, Elsevier, vol. 5(1), pages 7-19.
  10. Ashley, Richard, 1988. "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 4(3), pages 363-376.
  11. Kim, Chang-Jin, 1993. "Sources of Monetary Growth Uncertainty and Economic Activity: The Time-Varying-Parameter Model with Heteroskedastic Disturbances," The Review of Economics and Statistics, MIT Press, vol. 75(3), pages 483-92, August.
  12. Brown, Jane P. & Song, Haiyan & McGillivray, Alan, 1997. "Forecasting UK house prices: A time varying coefficient approach," Economic Modelling, Elsevier, vol. 14(4), pages 529-548, October.
  13. Riddington, GL, 1993. "Time varying coefficient models and their forecasting performance," Omega, Elsevier, vol. 21(5), pages 573-583, September.
  14. McNees, Stephen K, 1986. "Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 5-15, January.
  15. Haiyan Song & Peter Romilly & Xiaming Liu, 1998. "The UK consumption function and structural instability: improving forecasting performance using a time-varying parameter approach," Applied Economics, Taylor & Francis Journals, vol. 30(7), pages 975-983.
  16. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
  17. Li, Gang & Song, Haiyan & Witt, Stephen F., 2006. "Time varying parameter and fixed parameter linear AIDS: An application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 22(1), pages 57-71.
  18. Witt, Stephen F. & Witt, Christine A., 1995. "Forecasting tourism demand: A review of empirical research," International Journal of Forecasting, Elsevier, vol. 11(3), pages 447-475, September.
  19. Makridakis, Spyros, 1986. "The art and science of forecasting An assessment and future directions," International Journal of Forecasting, Elsevier, vol. 2(1), pages 15-39.
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