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Tourism in the Canary Islands: Forecasting Using Several Seasonal Time Series Models

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  • Juncal Cuñado

    ()
    (Universidad de Navarra)

  • Luis A. Gil-Alaña

    ()
    (Universidad de Navarra)

Abstract

This paper deals with the analysis of the number of tourists travelling to the Canary Islands by means of using different seasonal statistical models. Deterministic and stochastic seasonality is considered. For the latter case, we employ seasonal unit roots and seasonally fractionally integrated models. As a final approach, we also employ a model with possibly different orders of integration at zero and the seasonal frequencies. All these models are compared in terms of their forecasting ability in an out-of-sample experiment. The results in the paper show that a simple deterministic model with seasonal dummy variables and AR(1) disturbances produce better results than other approaches based on seasonal fractional and integer differentiation over short horizons. However, increasing the time horizon, the results cannot distinguish between the model based on seasonal dummies and another using fractional integration at zero and the seasonal frequencies.

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File URL: http://www.unav.es/facultad/econom/files/workingpapersmodule/@random45ab5988c3bf2/1171283617_wp0207.pdf
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Bibliographic Info

Paper provided by School of Economics and Business Administration, University of Navarra in its series Faculty Working Papers with number 02/07.

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Length: 32 pages
Date of creation: 2007
Date of revision:
Publication status: Published in Journal of Forecasting 27, 621-636 (2008)
Handle: RePEc:una:unccee:wp0207

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Web page: http://www.unav.es/facultad/econom

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  1. William R. Parke, 1999. "What Is Fractional Integration?," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 632-638, November.
  2. Todd E. Clark & Michael W. McCracken, 2000. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Econometric Society World Congress 2000 Contributed Papers 0319, Econometric Society.
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  4. Ray, Bonnie K., 1993. "Long-range forecasting of IBM product revenues using a seasonal fractionally differenced ARMA model," International Journal of Forecasting, Elsevier, vol. 9(2), pages 255-269, August.
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  6. Brannas, Kurt & Hellstrom, Jorgen & Nordstrom, Jonas, 2002. "A new approach to modelling and forecasting monthly guest nights in hotels," International Journal of Forecasting, Elsevier, vol. 18(1), pages 19-30.
  7. Ashley, Richard, 1998. "A new technique for postsample model selection and validation," Journal of Economic Dynamics and Control, Elsevier, vol. 22(5), pages 647-665, May.
  8. Philip Hans Franses & Bart Hobijn, 1997. "Critical values for unit root tests in seasonal time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(1), pages 25-48.
  9. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
  10. Gil-Alana, Luis A., 2002. "Seasonal long memory in the aggregate output," Economics Letters, Elsevier, vol. 74(3), pages 333-337, February.
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  12. Ghysels, Eric & Lee, Hahn S. & Noh, Jaesum, 1994. "Testing for unit roots in seasonal time series : Some theoretical extensions and a Monte Carlo investigation," Journal of Econometrics, Elsevier, vol. 62(2), pages 415-442, June.
  13. J. Joseph Beaulieu & Jeffrey A. Miron, 1992. "Seasonal Unit Roots in Aggregate U.S. Data," NBER Technical Working Papers 0126, National Bureau of Economic Research, Inc.
  14. Carlin, J. B. & Dempster, A. P. & Jonas, A. B., 1985. "On models and methods for Bayesian time series analysis," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 67-90.
  15. Christine Lim & Michael McAleer, 2001. "Time Series Forecasts of International Tourism Demand for Australia," ISER Discussion Paper 0533, Institute of Social and Economic Research, Osaka University.
  16. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
  17. Gustavsson, Patrik & Nordström, Jonas, 1999. "The Impact of Seasonal Unit Roots and Vector ARMA Modeling on Forecasting Monthly Tourism Flows," Working Paper Series 150, Trade Union Institute for Economic Research, revised 01 Jul 2000.
  18. Canova, Fabio & Hansen, Bruce E, 1995. "Are Seasonal Patterns Constant over Time? A Test for Seasonal Stability," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 237-52, July.
  19. Franses, Philip Hans, 1991. "Seasonality, non-stationarity and the forecasting of monthly time series," International Journal of Forecasting, Elsevier, vol. 7(2), pages 199-208, August.
  20. 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 117-27, January.
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Cited by:
  1. Arias Martín, Pedro, 2013. "La situación del empleo en turismo rural en España/The Employment Situation in Rural Tourism in Spain," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 31, pages 257 (22pags, Enero.
  2. Andrawis, Robert R. & Atiya, Amir F. & El-Shishiny, Hisham, 2011. "Combination of long term and short term forecasts, with application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 27(3), pages 870-886, July.
  3. Juncal Cuñado & Alberiko Gil-Alana, Luis & Perez De Gracia, Fernando, 2011. "Modelling International Monthly Tourist in Spain/Modelización de llegadas mensuales de turistas a España," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 29, pages 723-736, Diciembre.

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