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Effect of Demand Volume on Forecasting Accuracy

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  • Jo C. Vu

    (School of Applied Economics, Victoria University, PO Box 14428 MC, Melbourne, Victoria 8001, Australia)

Abstract

The forecasting of international tourist arrivals is normally done on a per country basis. The volume of tourist flow varies widely among countries, largely depending on their population size but also on their openness to tourism. This paper uses data for Austria, China (PRC), Canada, the Cook Islands, Cyprus, Japan, the Maldives, Malta, New Zealand, Singapore, Slovenia and Thailand over a quarterly estimation period from 1995 to 1999 to forecast ahead for 2000 to 2002. In addition, the total arrivals to Japan from 24 different countries of origin are also examined with the same estimation and forecast periods. The topic explored is whether it is possible to examine the structure of the time-series data to determine why particular forecasting is more or less accurate. As a starting point, forecasts are obtained from larger data volumes relative to smaller volumes. The forecasting comparison uses the short-term time series methods of the basic structural model and the Holt–Winters model, with a comparison for base accuracy against the naïve model. The results show in the forecasting comparison that the volume of flow and volatility and seasonality do not directly influence the accuracy of the forecast.

Suggested Citation

  • Jo C. Vu, 2006. "Effect of Demand Volume on Forecasting Accuracy," Tourism Economics, , vol. 12(2), pages 263-276, June.
    • Handle: RePEc:sae:toueco:v:12:y:2006:i:2:p:263-276
    DOI: 10.5367/000000006777637412
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    References listed on IDEAS

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    1. Lindsay W. Turner & Stephen F. Witt, 2001. "Forecasting Tourism Using Univariate and Multivariate Structural Time Series Models," Tourism Economics, , vol. 7(2), pages 135-147, June.
    2. 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.
    3. 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.
    4. Harvey, A C & Todd, P H J, 1983. "Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 299-307, October.
    5. Harvey, A C & Todd, P H J, 1983. "Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study: Response," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 313-315, October.
    6. Lindsay W. Turner & N. Kulendran & H. Fernando, 1997. "Univariate Modelling Using Periodic and Non-Periodic Analysis: Inbound Tourism to Japan, Australia and New Zealand Compared," Tourism Economics, , vol. 3(1), pages 39-56, March.
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    Cited by:

    1. Peng, Bo & Song, Haiyan & Crouch, Geoffrey I., 2014. "A meta-analysis of international tourism demand forecasting and implications for practice," Tourism Management, Elsevier, vol. 45(C), pages 181-193.
    2. Anna Serena Vergori, 2017. "Patterns of seasonality and tourism demand forecasting," Tourism Economics, , vol. 23(5), pages 1011-1027, August.

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