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Multivariate exponential smoothing for forecasting tourist arrivals to Australia and New Zealand

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  • George Athanasopoulos

    ()

  • Ashton de Silva

Abstract

In this paper we propose a new set of multivariate stochastic models that capture time varying seasonality within the vector innovations structural time series (VISTS) framework. These models encapsulate exponential smoothing methods in a multivariate setting. The models considered are the local level, local trend and damped trend VISTS models with an additive multivariate seasonal component. We evaluate their performances for forecasting international tourist arrivals from eleven source countries to Australia and New Zealand.

Suggested Citation

  • George Athanasopoulos & Ashton de Silva, 2010. "Multivariate exponential smoothing for forecasting tourist arrivals to Australia and New Zealand," Monash Econometrics and Business Statistics Working Papers 11/09, Monash University, Department of Econometrics and Business Statistics.
  • Handle: RePEc:msh:ebswps:2009-11
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    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2009/wp11-09.pdf
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    References listed on IDEAS

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    1. Peter R. Winters, 1960. "Forecasting Sales by Exponentially Weighted Moving Averages," Management Science, INFORMS, vol. 6(3), pages 324-342, April.
    2. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    3. Hyndman, Rob J. & Koehler, Anne B. & Snyder, Ralph D. & Grose, Simone, 2002. "A state space framework for automatic forecasting using exponential smoothing methods," International Journal of Forecasting, Elsevier, vol. 18(3), pages 439-454.
    4. Athanasopoulos, George & Hyndman, Rob J. & Song, Haiyan & Wu, Doris C., 2011. "The tourism forecasting competition," International Journal of Forecasting, Elsevier, vol. 27(3), pages 822-844, July.
    5. Phillip G. Enns & Joseph A. Machak & W. Allen Spivey & William J. Wrobleski, 1982. "Forecasting Applications of an Adaptive Multiple Exponential Smoothing Model," Management Science, INFORMS, vol. 28(9), pages 1035-1044, September.
    6. Ashton de Silva & Rob J. Hyndman & Ralph D. Snyder, 2007. "The vector innovation structural time series framework: a simple approach to multivariate forecasting," Monash Econometrics and Business Statistics Working Papers 3/07, Monash University, Department of Econometrics and Business Statistics.
    7. Hyndman, Rob J. & Koehler, Anne B., 2006. "Another look at measures of forecast accuracy," International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
    8. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
    9. Gonzalez, Pilar & Moral, Paz, 1995. "An analysis of the international tourism demand in Spain," International Journal of Forecasting, Elsevier, vol. 11(2), pages 233-251, June.
    10. 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.
    11. 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.
    12. Rob Hyndman & Muhammad Akram & Blyth Archibald, 2008. "The admissible parameter space for exponential smoothing models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(2), pages 407-426, June.
    13. Pfeffermann, D. & Allon, J., 1989. "Multivariate exponential smoothing: Method and practice," International Journal of Forecasting, Elsevier, vol. 5(1), pages 83-98.
    14. du Preez, Johann & Witt, Stephen F., 2003. "Univariate versus multivariate time series forecasting: an application to international tourism demand," International Journal of Forecasting, Elsevier, vol. 19(3), pages 435-451.
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    Citations

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    Cited by:

    1. Dimitrios D. Thomakos & Konstantinos Nikolopoulos, 2015. "Forecasting Multivariate Time Series with the Theta Method," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(3), pages 220-229, April.
    2. Svetunkov, Ivan & Kourentzes, Nikolaos, 2015. "Complex Exponential Smoothing," MPRA Paper 69394, University Library of Munich, Germany.

    More about this item

    Keywords

    Holt-Winters’ method; Stochastic seasonality; Vector innovations state space models.;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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