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Implications of not controlling for known events in seasonal adjustment

Author

Listed:
  • Håvard Hungnes

    (Statistics Norway)

  • Terje Skjerpen

    (Statistics Norway)

  • Jørn Ivar Hamre

    (Statistics Norway)

  • Xiaoming Chen Jansen

    (Statistics Norway)

Abstract

Seasonal patterns in time series can change due to important events, such as legislative changes. If not taken into account, seasonal adjustment can produce misleading results. Two legal changes in Norway in 2022 and 2023 boosted house prices at the start of the year. If no adjustment is made for this, an enhanced seasonal pattern appears, which implies a slight increase in house prices in late 2023. This prompted the Norwegian central bank to raise the key interest rate in December 2023. But house prices adjusted for the legislative changes actually show a decline in the second half of 2023.

Suggested Citation

  • Håvard Hungnes & Terje Skjerpen & Jørn Ivar Hamre & Xiaoming Chen Jansen, 2024. "Implications of not controlling for known events in seasonal adjustment," Economics Bulletin, AccessEcon, vol. 44(3), pages 975-982.
    • Handle: RePEc:ebl:ecbull:eb-24-00068
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    File URL: http://www.accessecon.com/Pubs/EB/2024/Volume44/EB-24-V44-I3-P74.pdf
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    More about this item

    Keywords

    Outliers; X11; ARIMA; Seasonal filters; House prices; Legislative changes;
    All these keywords.

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

    Statistics

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