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Prediction with univariate time series models: The Iberia case

Author

Listed:
  • Ester Ruiz

    () (Departamento de Estadística y Econometría. Universidad Carlos III de Madrid)

  • Fernando Lorenzo

    (Departamento de Economía, Facultad de Ciencias Sociales, Universidad de Uruguay. Centro de Investigaciones Económicas (CINVE-Uruguay))

Abstract

In this paper we model the monthly number of passengers flying with the Spanish airline IBERIA from January 1985 to December 1992 and predict future values of the series up to October 1994. This series is characterized by strong seasonal variations and by having an upward trend which has a rupture during 1990 with the slope changing to be negative. We compare observed values with predictions made by a deterministic components model, the Holt-Winters exponential smoothing filter, an ARIMA model and a structural time series model. As expected, we show that the deterministic components model is too rigid in the presence fo breaks in trends although surprisingly the within-sample fit is better than for any of the other models considered. With respect to Holt-Winters predictions, they fail because they are not able to acommodate outliers. Finally, ARIMA and structural models are shown to have very similar prediction performance, being very flexible to predict reasonably well when there are changes in trend and outliers.

Suggested Citation

  • Ester Ruiz & Fernando Lorenzo, 1997. "Prediction with univariate time series models: The Iberia case," Documentos de Trabajo (working papers) 0298, Department of Economics - dECON.
  • Handle: RePEc:ude:wpaper:0298
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    File URL: http://decon.edu.uy/publica/1998/Doc0298.pdf
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    References listed on IDEAS

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    1. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    2. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 671-690.
    3. Nerlove, Marc & Grether, David M. & Carvalho, José L., 1979. "Analysis of Economic Time Series," Elsevier Monographs, Elsevier, edition 1, number 9780125157506 edited by Shell, Karl.
    4. Maravall, Agustin, 1985. "On Structural Time Series Models and the Characterization of Components," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(4), pages 350-355, October.
    5. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
    6. Clements, M.P. & Hendry, D., 1992. "On the Limitations of Comparing Mean Square Forecast Errors," Economics Series Working Papers 99138, University of Oxford, Department of Economics.
    7. Rappoport, Peter & Reichlin, Lucrezia, 1989. "Segmented Trends and Non-stationary Time Series," Economic Journal, Royal Economic Society, vol. 99(395), pages 168-177, Supplemen.
    8. Harvey, A C & Todd, P H J, 1983. "Forecasting Economic Time Series with Structural and Box-Jenkins Models: A Case Study," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(4), pages 299-307, October.
    9. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
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