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Risk Management for International Tourist Arrivals: An Application to the Balearic Islands, Spain

Author

Listed:
  • Ana Bartolome

    (Faculty of Economics and Business, University of the Balearic Islands)

  • Michael McAleer

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute and Center for International Research on the Japanese Economy (CIRJE), Faculty of Economics, University of Tokyo)

  • Vicente Ramos

    (Faculty of Economics and Business, University of the Balearic Islands)

  • Javier Rey-Maquieira

    (Faculty of Economics and Business, University of the Balearic Islands)

Abstract

Spain is a leader in terms of total international tourist arrivals and receipts. The Balearic Islands are one of the most popular destinations in Spain. For tourism management and marketing, it is essential to forecast tourist arrivals accurately. As it is important to provide sensible tourist forecast intervals, it is also necessary to model their variances accurately. Time-varying variances also provide useful information regarding the risk associated with tourist arrivals. This paper examines spatial aggregation across micro entities to more aggregated macro entities, in addition to temporal aggregation, for purposes of analyzing risk in tourism marketing and management. The paper examines four different types of asymmetric behaviour related to the effects of positive and negative shocks of equal magnitude on volatility. The paper analyzes daily air passenger arrivals from the Spanish National Airport Authority from 2001-06 to the Balearics, using time series models for the conditional mean and conditional volatility.

Suggested Citation

  • Ana Bartolome & Michael McAleer & Vicente Ramos & Javier Rey-Maquieira, 2009. "Risk Management for International Tourist Arrivals: An Application to the Balearic Islands, Spain," CIRJE F-Series CIRJE-F-665, CIRJE, Faculty of Economics, University of Tokyo.
    • Handle: RePEc:tky:fseres:2009cf665
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    File URL: http://www.cirje.e.u-tokyo.ac.jp/research/dp/2009/2009cf665.pdf
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    References listed on IDEAS

    as
    1. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
    2. Shiqing Ling & Michael McAleer, 2001. "On Adaptive Estimation in Nonstationary ARMA Models with GARCH Errors," ISER Discussion Paper 0548, Institute of Social and Economic Research, Osaka University.
    3. Michael McAleer & Les Oxley, 2002. "The Econometrics of Financial Time Series," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 237-243, July.
    4. Jeantheau, Thierry, 1998. "Strong Consistency Of Estimators For Multivariate Arch Models," Econometric Theory, Cambridge University Press, vol. 14(1), pages 70-86, February.
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    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. McAleer, Michael & Chan, Felix & Marinova, Dora, 2007. "An econometric analysis of asymmetric volatility: Theory and application to patents," Journal of Econometrics, Elsevier, vol. 139(2), pages 259-284, August.
    8. Pierre Perron & Serena Ng, 1996. "Useful Modifications to some Unit Root Tests with Dependent Errors and their Local Asymptotic Properties," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 63(3), pages 435-463.
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    10. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(1), pages 232-261, February.
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    12. Ling, Shiqing & McAleer, Michael, 2002. "Stationarity and the existence of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 109-117, January.
    13. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Medeiros, Marcelo C. & McAleer, Michael & Slottje, Daniel & Ramos, Vicente & Rey-Maquieira, Javier, 2008. "An alternative approach to estimating demand: Neural network regression with conditional volatility for high frequency air passenger arrivals," Journal of Econometrics, Elsevier, vol. 147(2), pages 372-383, December.
    2. Ana Bartolome & Michael McAleer & Vicente Ramos & Javier Rey-Maquieira, 2009. "Cruising is Risky Business," CIRJE F-Series CIRJE-F-664, CIRJE, Faculty of Economics, University of Tokyo.

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