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Univariate and multivariate forecasting of tourism demand using state-space models

Author

Listed:
  • Elisa Jorge-González

    (Universidad de La Laguna, Spain)

  • Enrique González-Dávila

    (Universidad de La Laguna, Spain)

  • Raquel Martín-Rivero

    (Universidad de La Laguna, Spain)

  • Domingo Lorenzo-Díaz

    (Universidad de La Laguna, Spain; Instituto Canario de Estadística (ISTAC), Spain)

Abstract
Tourism forecasting plays a major role in tourism planning and management and it is one of the main economic activities in many countries. For this reason, it is fundamental to provide several models that allow describing and forecasting the tourist demand. International visitants who arrive at a certain tourist destination may come from countries or regions with similar or different customs and behaviours and therefore be able to present correlated arrival patterns. Based on the state-space methods with time-varying parameters, this study develops the application and comparison of univariate and multivariate models in the applied case of German and British tourist at Canary Islands (Spain). The choice of model can be conditioned by the volume of tourists from one country with respect to the other. Structural models will be used incorporating intervention and exogenous variables, among which airline seat reservations for regular flights.

Suggested Citation

  • Elisa Jorge-González & Enrique González-Dávila & Raquel Martín-Rivero & Domingo Lorenzo-Díaz, 2020. "Univariate and multivariate forecasting of tourism demand using state-space models," Tourism Economics, , vol. 26(4), pages 598-621, June.
    • Handle: RePEc:sae:toueco:v:26:y:2020:i:4:p:598-621
    DOI: 10.1177/1354816619857641
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    References listed on IDEAS

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