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Modelling the Growth and Volatility in Daily International Mass Tourism to Peru

Author

Listed:
  • Jose Angelo Divino

    (Department of Economics Catholic University of Brasilia)

  • Michael McAleer

    (Universidad Complutense de Madrid.Department of Quantitative Economics)

Abstract

Peru is a South American country that is divided into two parts by the Andes Mountains. The rich historical, cultural and geographic diversity has led to the inclusion of ten Peruvian sites on UNESCO’s World Heritage List. For the potential negative impacts of mass tourism on the environment, and hence on future international tourism demand, to be managed appropriately require modelling growth rates and volatility adequately. The paper models the growth rate and volatility (or the variability in the growth rate) in daily international tourist arrivals to Peru from 1997 to 2007. The empirical results show that international tourist arrivals and their growth rates are stationary, and that the estimated symmetric and asymmetric conditional volatility models all fit the data extremely well. Moreover, the estimates resemble those arising from financial time series data, with both short and long run persistence of shocks to the growth rate in international tourist arrivals.

Suggested Citation

  • Jose Angelo Divino & Michael McAleer, 2009. "Modelling the Growth and Volatility in Daily International Mass Tourism to Peru," Documentos de Trabajo del ICAE 2009-15, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    • Handle: RePEc:ucm:doicae:0915
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    References listed on IDEAS

    as
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    7. W. K. Li & Shiqing Ling & Michael McAleer, 2002. "Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 245-269, July.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Daily International Tourim; Conditional Mean Models; Conditional Volatility Models.;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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