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Seasonal Outliers in Time Series

Author

Listed:
  • Regina Kaiser
  • Agustín Maravall

Abstract

In the analysis of time series, it is frequent to classify perturbations as Additive Outliers (AO), Innovative Outliers (IO), Level Shift (LS) outliers or Transitory Change (TC) outliers. In this paper, a new outlier type, the Seasonal Level Shift (SLS), is introduced in order to complete the usual classification.

Suggested Citation

  • Regina Kaiser & Agustín Maravall, 1999. "Seasonal Outliers in Time Series," Working Papers 9915, Banco de España;Working Papers Homepage.
  • Handle: RePEc:bde:wpaper:9915
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    Citations

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    Cited by:

    1. Bernardí Cabrer Borrás & David Iranzo Pérez, 2007. "El Efecto De Los Atentados Del 11-s Sobre El Turismo En España," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 25, pages 365-386, Abril.
    2. Kaiser, Regina & Maravall, Agustín, 2000. "An application of tramo-seats: changes in seasonality and current trend-cycle assesment: the german retail trade turnover series," DES - Working Papers. Statistics and Econometrics. WS 10010, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Regina Kaiser & Agustín Maravall, 2000. "An Application of TRAMO-SEATS: Changes in Seasonality and Current Trend-Cycle Assessment: the German Retail Trade Turnover Series," Working Papers 0011, Banco de España;Working Papers Homepage.
    4. Luciana Crosilla, 2006. "The seasonality of ISAE business and consumer surveys: methodological aspects and empirical evidence," ISAE Working Papers 68, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).

    More about this item

    Keywords

    ECONOMETRICS ; TIME SERIES ; MATHEMATICAL ANALYSIS;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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