<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></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.

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

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

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

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Considering that many macroeconomic time series present changing seasonal behaviour, there is a need for filters that are robust to such changes. This article...

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

Published Online: Feb 21, 2017

Page range: 155 - 186

Received: Sep 01, 2015

Accepted: Sep 01, 2016

DOI: https://doi.org/10.1515/jos-2017-0009

Keywords
Moving seasonality, Filter design, Frequency domain, Time series decomposition, X-13A-S

© by Marcela Cohen Martelotte

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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

Published Online: Feb 21, 2017

Page range: 155 - 186

Received: Sep 01, 2015

Accepted: Sep 01, 2016

DOI: https://doi.org/10.1515/jos-2017-0009

KeywordsMoving seasonality, Filter design, Frequency domain, Time series decomposition, X-13A-S

© by Marcela Cohen Martelotte

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
Moving seasonality, Filter design, Frequency domain, Time series decomposition, X-13A-S