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Design of Seasonal Adjustment Filter Robust to Variations in the Seasonal Behaviour of Time Series

Author

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  • Martelotte Marcela Cohen

    (Department of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro. Rua Marquês de São Vicente, 225 - Gávea, Rio de Janeiro, Brazil)

  • Souza Reinaldo Castro

    (Department of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro. Rua Marquês de São Vicente, 225 - Gávea, Rio de Janeiro, Brazil)

  • Silva Eduardo Antônio Barros da

    (Electrical Engineering Program, Federal University of Rio de Janeiro. C.P. 68504, Rio de Janeiro, Brazil)

Abstract

Considering that many macroeconomic time series present changing seasonal behaviour, there is a need for filters that are robust to such changes. This article proposes a method to design seasonal filters that address this problem. The design was made in the frequency domain to estimate seasonal fluctuations that are spread around specific bands of frequencies. We assessed the generated filters by applying them to artificial data with known seasonal behaviour based on the ones of the real macroeconomic series, and we compared their performance with the one of X-13A-S. The results have shown that the designed filters have superior performance for series with pronounced moving seasonality, being a good alternative in these cases.

Suggested Citation

  • Martelotte Marcela Cohen & Souza Reinaldo Castro & Silva Eduardo Antônio Barros da, 2017. "Design of Seasonal Adjustment Filter Robust to Variations in the Seasonal Behaviour of Time Series," Journal of Official Statistics, Sciendo, vol. 33(1), pages 155-186, March.
    • Handle: RePEc:vrs:offsta:v:33:y:2017:i:1:p:155-186:n:9
    DOI: 10.1515/jos-2017-0009
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    References listed on IDEAS

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