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The tourism forecasting competition

Listed author(s):
  • George Athanasopoulos

    ()

  • Rob J Hyndman

    ()

  • Haiyan Song
  • Doris C Wu

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.

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File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2008/wp10-08.pdf
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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 10/08.

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Length: 34 pages
Date of creation: Dec 2008
Date of revision: Oct 2009
Handle: RePEc:msh:ebswps:2008-10
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Web page: http://business.monash.edu/econometrics-and-business-statistics
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  1. Kulendran, N. & King, Maxwell L., 1997. "Forecasting international quarterly tourist flows using error-correction and time-series models," International Journal of Forecasting, Elsevier, vol. 13(3), pages 319-327, September.
  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. Athanasopoulos, George & Ahmed, Roman A. & Hyndman, Rob J., 2009. "Hierarchical forecasts for Australian domestic tourism," International Journal of Forecasting, Elsevier, vol. 25(1), pages 146-166.
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  7. Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
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