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Methodes De Lissage D’Une Serie Temporelle :Le Probleme Des Extremites

Author

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  • Michel Grun-Rehomme
  • OLGA VASYECHKO

Abstract

De nombreuses méthodes, basées sur les filtres, ont été développées pour estimer la composantetendance-cycle d’une série temporelle. Parmi ces outils, les moyennes mobiles demeurenttoujours efficaces. En particulier, la moyenne mobile symétrique d’Henderson est appliquéepour estimer la tendance-cycle dans le programme de désaisonnalisation X11. Mais pour lesobservations les plus récentes, il est nécessaire d’utiliser des filtres asymétriques. Dans cetarticle, une nouvelle méthode de lissage, basée sur le noyau d’Epanechnikov, est utilisée pourtraiter les extrémités d’une série temporelle. Cette méthode est comparée au filtre d’Hendersonsur des données de l’Indice de Production Industrielle.

Suggested Citation

  • Michel Grun-Rehomme & OLGA VASYECHKO, 2013. "Methodes De Lissage D’Une Serie Temporelle :Le Probleme Des Extremites," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 56(2), pages 163-174.
    • Handle: RePEc:bxr:bxrceb:2013/186521
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    References listed on IDEAS

    as
    1. Dagum, Estela Bee & Bianconcini, Silvia, 2008. "The Henderson Smoother in Reproducing Kernel Hilbert Space," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 536-545.
    2. Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-152, April.
    3. Theodore Alexandrov & Silvia Bianconcini & Estela Bee Dagum & Peter Maass & Tucker S. McElroy, 2012. "A Review of Some Modern Approaches to the Problem of Trend Extraction," Econometric Reviews, Taylor & Francis Journals, vol. 31(6), pages 593-624, November.
    4. Quenneville, Benoit & Ladiray, Dominique & Lefrancois, Bernard, 2003. "A note on Musgrave asymmetrical trend-cycle filters," International Journal of Forecasting, Elsevier, vol. 19(4), pages 727-734.
    5. Tommaso Proietti & Alessandra Luati, 2008. "Real Time Estimation in Local Polynomial Regression, with Application to Trend-Cycle Analysis," CEIS Research Paper 112, Tor Vergata University, CEIS, revised 14 Jul 2008.
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    More about this item

    Keywords

    Séries temporelles / Time Series Analysis; Méthode de lissage / Smoothing techniques; Moyennes mobiles asymétriques / Asymmetric Moving Average; Noyaux / Kernels;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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