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Seasonal decomposition with a modified Hodrick-Prescott filter

Author

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  • Buss, Ginters

Abstract

I describe preliminary results for seasonal decomposition procedure using a modified Hodrick-Prescott (Leser) filter. The procedure is simpler to implement compared to two currently most popular seasonal decomposition procedures - X-11 filters developed by the U.S. Census Bureau and SEATS developed by the Bank of Spain. A case study for Latvia's quarterly gross domestic product shows the procedure is able to extract a stable seasonal component, yet allowing for structural changes in seasonality.

Suggested Citation

  • Buss, Ginters, 2010. "Seasonal decomposition with a modified Hodrick-Prescott filter," MPRA Paper 24133, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:24133
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    File URL: https://mpra.ub.uni-muenchen.de/24133/1/MPRA_paper_24133.pdf
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    References listed on IDEAS

    as
    1. Regina Kaiser & Agustín Maravall, 2000. "Notes on Time Series Analysis, ARIMA Models and Signal Extraction," Working Papers 0012, Banco de España.
    2. Kaiser Remiro, Regina & Maravall, Agustín, 2000. "Notes on time serie analysis, ARIMA models and signal extraction," DES - Working Papers. Statistics and Econometrics. WS 10058, Universidad Carlos III de Madrid. Departamento de Estadística.
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    Cited by:

    1. Puneet Vatsa & Dragan Miljkovic, 2022. "Energy and crop price cycles before and after the global financial crisis: A new approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 220-233, February.

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    More about this item

    Keywords

    seasonal decomposition; Hodrick-Prescott filter; quarterly GDP;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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