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An Alternative Approach to Modeling and Forecasting Seasonal Time Series

Author

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  • Canova, Fabio

Abstract

This article proposes an alternative methodology for modeling and forecasting seasonal series. The approach is in the Bayesian autoregression tradition pioneered by Doan, Litterman, and Sims and builds seasonality directly into the prior of the coefficients of the model by means of a set of uncertain linear restrictions. As an illustration, the method is applied to 10 U.S. quarterly macroeconomic series. For each series, the author compares the forecasting performance of a univariate time-varying autoregressive model with seasonality built in the prior of the coefficients with five other widely used models.

Suggested Citation

  • Canova, Fabio, 1992. "An Alternative Approach to Modeling and Forecasting Seasonal Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 97-108, January.
    • Handle: RePEc:bes:jnlbes:v:10:y:1992:i:1:p:97-108
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    Cited by:

    1. El Montasser, Ghassen, 2014. "The seasonal KPSS Test: some extensions and further results," MPRA Paper 54920, University Library of Munich, Germany.
    2. Ionel Birgean & Lutz Kilian, 2002. "Data-Driven Nonparametric Spectral Density Estimators For Economic Time Series: A Monte Carlo Study," Econometric Reviews, Taylor & Francis Journals, vol. 21(4), pages 449-476.
    3. Canova, Fabio, 2002. "G-7 Inflation forecasts," Working Paper Series 151, European Central Bank.
    4. El Montasser, Ghassen, 2012. "The seasonal KPSS Test: some extensions and further results," MPRA Paper 45110, University Library of Munich, Germany, revised 04 Mar 2014.
    5. Shipra Banik & Param Silvapulle, 1999. "Testing for Seasonal Stability in Unemployment Series: International Evidence," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 26(2), pages 123-139, June.
    6. Canova, Fabio, 2002. "G-7 Inflation Forecasts," CEPR Discussion Papers 3283, C.E.P.R. Discussion Papers.
    7. Enrique M. Quilis(1), "undated". "Modelos Bvar: Especificación, Estimación E Inferencia," Working Papers 8-02 Classification-JEL :, Instituto de Estudios Fiscales.

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