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The Impact of Seasonal Unit Roots and Vector ARMA Modelling on Forecasting Monthly Tourism Flows

Author

Listed:
  • Patrik Gustavsson

    (Trade Union Institute for Economic Research, Wallingatan 38, SE-111 24 Stockholm, Sweden)

  • Jonas Nordström

    (Department of Economics, Umeå University, SE-901 87 Umeå, Sweden)

Abstract

The effect of imposing different numbers of unit roots on forecasting accuracy is examined using univariate ARMA models. To see whether additional information improves forecasting accuracy and increases the informative forecast horizon, the authors cross-relate the time series for inbound tourism in Sweden for different visitor categories and estimate vector ARMA models. The mean-squared forecast error for different filters indicates that models in which unit roots are imposed at all frequencies have the smallest forecast errors. The results from the vector ARMA models with all roots imposed indicate that the informative forecast horizon is greater than for the univariate models. Out-of-sample evaluations indicate, however, that the univariate modelling approach may be preferable.

Suggested Citation

  • Patrik Gustavsson & Jonas Nordström, 2001. "The Impact of Seasonal Unit Roots and Vector ARMA Modelling on Forecasting Monthly Tourism Flows," Tourism Economics, , vol. 7(2), pages 117-133, June.
    • Handle: RePEc:sae:toueco:v:7:y:2001:i:2:p:117-133
    DOI: 10.5367/000000001101297766
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    Cited by:

    1. Chunla Liu & Yingjie Qin & Yufei Wang & Yue Yu & Guanghui Li, 2022. "Spatio-Temporal Distribution of Tourism Flows and Network Analysis of Traditional Villages in Western Hunan," Sustainability, MDPI, vol. 14(13), pages 1-16, June.

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