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The Impact of Seasonal Unit Roots and Vector ARMA Modeling on Forecasting Monthly Tourism Flows

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Author Info

  • Gustavsson, Patrik

    (Trade Union Institute for Economic Research)

  • Nordström, Jonas

    () (Department of Economics, Umeå University)

Abstract

The effect of imposing different numbers of unit roots on forecasting accuracy is examined using univariate ARMA models. To see whether additional information improves forecasting accuracy and increases the informative forecast horizon, we cross-relate the time series for inbound tourism in Sweden for different visitor categories and estimate vector ARMA models. The mean-squared forecast error for different filters indicates that models in which unit roots are imposed at all frequencies have the smallest forecast errors. The results from the vector ARMA models with all roots imposed indicate that the informative forecast horizon is greater than for the univariate models. Out-of-sample evaluations indicate, however, that the univariate modelling approach may be preferable.

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Bibliographic Info

Paper provided by Trade Union Institute for Economic Research in its series Working Paper Series with number 150.

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Length: 22 pages
Date of creation: 01 Apr 1999
Date of revision: 01 Jul 2000
Publication status: Published in Tourism Economics, 2001, pages 117-133.
Handle: RePEc:hhs:fiefwp:0150

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Keywords: Seasonality; Tourism; Demand Analysis; VARMA; Forecasting;

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References

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  1. Philip Hans Franses & Timothy J. Vogelsang, 1998. "On Seasonal Cycles, Unit Roots, And Mean Shifts," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 231-240, May.
  2. Saikkonen, Pentti & Luukkonen, Ritva, 1997. "Testing cointegration in infinite order vector autoregressive processes," Journal of Econometrics, Elsevier, vol. 81(1), pages 93-126, November.
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  4. Witt, Stephen F. & Witt, Christine A., 1995. "Forecasting tourism demand: A review of empirical research," International Journal of Forecasting, Elsevier, vol. 11(3), pages 447-475, September.
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  6. Perron, Pierre, 1990. "Testing for a Unit Root in a Time Series with a Changing Mean," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 153-62, April.
  7. Franses, Philip Hans, 1996. "Periodicity and Stochastic Trends in Economic Time Series," OUP Catalogue, Oxford University Press, number 9780198774549, September.
  8. Oke, Timothy & Öller, Lars-Erik, 1997. "Testing for Short Memory in a VARMA Process," Working Paper 56, National Institute of Economic Research.
  9. Granger, Clive W J, 1996. "Can We Improve the Perceived Quality of Economic Forecasts?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 455-73, Sept.-Oct.
  10. 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.
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  12. Paap, Richard & Franses, Philip Hans & Hoek, Henk, 1997. "Mean shifts, unit roots and forecasting seasonal time series," International Journal of Forecasting, Elsevier, vol. 13(3), pages 357-368, September.
  13. Saikkonen, Pentti, 1992. "Estimation and Testing of Cointegrated Systems by an Autoregressive Approximation," Econometric Theory, Cambridge University Press, vol. 8(01), pages 1-27, March.
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  17. repec:cup:etheor:v:8:y:1992:i:1:p:1-27 is not listed on IDEAS
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Citations

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Cited by:
  1. Arai, Mahmood & Skogman Thoursie, Peter, 2001. "Incentives and Selection in Cyclical Absenteeism," Working Paper Series 167, Trade Union Institute for Economic Research.
  2. Juncal Cuñado & Luis A. Gil-Alaña, 2007. "Tourism in the Canary Islands: Forecasting Using Several Seasonal Time Series Models," Faculty Working Papers 02/07, School of Economics and Business Administration, University of Navarra.
  3. Strauss, Tove, 2000. "Economic Reforms and the Poor," Working Paper Series 164, Trade Union Institute for Economic Research.
  4. Strauss, Tove, 2000. "Structural Reforms, Uncertainty, and Private Investment," Working Paper Series 165, Trade Union Institute for Economic Research.

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