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An Application of PAR Models for Tourism Forecasting

Author

Listed:
  • Paulo M.M. Rodrigues

    (Faculty of Economics, University of Algarve, Campus de Gambelas, 8000-117 Faro, Portugal)

  • Pedro M.D.C.B. Gouveia

    (University of Algarve, ESGHT, Largo Eng Sarrea Prado 21, 8500 Portimão, Portugal)

Abstract

This paper extends the existing literature on tourism forecasting by developing an application study based on periodic models. The need for this type of approach derives from the common procedure in tourism literature of classifying series into three seasons: peak, shoulder and off-peak. This classification is useful in identifying more parsimonious periodic models when compared with unrestricted periodic monthly models. The authors apply their proposed models on several tourism series collected and analysed from Portugal's southernmost province, Algarve. The economy of this region relies heavily on the tourism industry, catering largely for the European market. Besides statistically validating these models, the authors compare their forecasting ability with other models in the current literature. The results show that the models presented achieve a superior forecasting performance.

Suggested Citation

  • Paulo M.M. Rodrigues & Pedro M.D.C.B. Gouveia, 2004. "An Application of PAR Models for Tourism Forecasting," Tourism Economics, , vol. 10(3), pages 281-303, September.
    • Handle: RePEc:sae:toueco:v:10:y:2004:i:3:p:281-303
    DOI: 10.5367/0000000041895085
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    References listed on IDEAS

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    1. Franses, Philip Hans, 1996. "Periodicity and Stochastic Trends in Economic Time Series," OUP Catalogue, Oxford University Press, number 9780198774549.
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    3. Osborn, Denise R., 1991. "The implications of periodically varying coefficients for seasonal time-series processes," Journal of Econometrics, Elsevier, vol. 48(3), pages 373-384, June.
    4. Sims,Christopher A. (ed.), 1994. "Advances in Econometrics," Cambridge Books, Cambridge University Press, number 9780521444590, November.
    5. Wells, J. M., 1997. "Modelling seasonal patterns and long-run trends in U.S. time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 407-420, September.
    6. Clements, Michael P. & Hendry, David F., 1997. "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, Elsevier, vol. 13(3), pages 341-355, September.
    7. Osborn, Denise R & Smith, Jeremy P, 1989. "The Performance of Periodic Autoregressive Models in Forecasting Seasonal U. K. Consumption," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(1), pages 117-127, January.
    8. Smith, Richard J. & Taylor, A. M. Robert, 1998. "Additional critical values and asymptotic representations for seasonal unit root tests," Journal of Econometrics, Elsevier, vol. 85(2), pages 269-288, August.
    9. Franses, Philip Hans, 1994. "A multivariate approach to modeling univariate seasonal time series," Journal of Econometrics, Elsevier, vol. 63(1), pages 133-151, July.
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    Cited by:

    1. Biljana Petrevska, 2014. "Measuring Seasonal Concentration Of Tourism Demand: Comparative Study Of See Countries," Journal Articles, Center For Economic Analyses, pages 45-53, December.
    2. Khalid Khan & Chi-Wei Su & Yi-Dong Xiao & Haotian Zhu & Xiaoyan Zhang, 2021. "Trends in tourism under economic uncertainty," Tourism Economics, , vol. 27(4), pages 841-858, June.
    3. Cláudia Duarte & Sónia Cabral, . "Nowcasting Portuguese tourism exports," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.

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