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The tourism forecasting competition

Author

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  • George Athanasopoulos

    ()

  • Rob J Hyndman

    ()

  • Haiyan Song
  • Doris C Wu

Abstract

We evaluate the performance of various methods for forecasting tourism demand. The data used include 380 monthly series, 427 quarterly series and 530 yearly series, all supplied to us by tourism bodies or by academics from previous tourism forecasting studies. The forecasting methods implemented in the competition are univariate time series approaches, and also econometric models. This forecasting completion differs from previous competitions in several ways: (i) we concentrate only on tourism demand data; (ii) we include econometric approaches; (iii) we evaluate forecast interval coverage as well as point forecast accuracy; (iv) we observe the effect of temporal aggregation on forecasting accuracy; and (v) we consider the mean absolute scaled error as an alternative forecasting accuracy measure.

Suggested Citation

  • George Athanasopoulos & Rob J Hyndman & Haiyan Song & Doris C Wu, 2008. "The tourism forecasting competition," Monash Econometrics and Business Statistics Working Papers 10/08, Monash University, Department of Econometrics and Business Statistics, revised Oct 2009.
  • Handle: RePEc:msh:ebswps:2008-10
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    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2008/wp10-08.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Tourism forecasting; ARIMA; Exponential smoothing; Time varying parameter model; Autoregressive distributed lag model; Vector autoregression;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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