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Seasonal Adjustment of Daily Data with CAMPLET

In: Seasonal Adjustment Without Revisions

Author

Listed:
  • Barend Abeln
  • Jan P. A. M. Jacobs

    (University of Groningen)

Abstract

In the last decade, large data sets have become available, both in terms of the number of time series and with higher frequencies (weekly, daily, and even higher). All series may suffer from seasonality, which hides other important fluctuations. Therefore, time series are typically seasonally adjusted. However, standard seasonal adjustment methods cannot handle series with higher than monthly frequencies. Recently, Abeln et al. (2019) presented CAMPLET, a new seasonal adjustment method, which does not produce revisions when new observations become available. The aim of this chapter is to show the attractiveness of CAMPLET for seasonal adjustment of daily time series. We apply CAMPLET to daily data on the gas system in the Netherlands.

Suggested Citation

  • Barend Abeln & Jan P. A. M. Jacobs, 2023. "Seasonal Adjustment of Daily Data with CAMPLET," SpringerBriefs in Economics, in: Seasonal Adjustment Without Revisions, chapter 0, pages 63-78, Springer.
    • Handle: RePEc:spr:spbchp:978-3-031-22845-2_6
    DOI: 10.1007/978-3-031-22845-2_6
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    as
    1. Barend Abeln & Jan P. A. M. Jacobs, 2023. "CAMPLET: Seasonal Adjustment Without Revisions," SpringerBriefs in Economics, in: Seasonal Adjustment Without Revisions, chapter 0, pages 7-29, Springer.
    2. Proietti, Tommaso & Pedregal, Diego J., 2023. "Seasonality in High Frequency Time Series," Econometrics and Statistics, Elsevier, vol. 27(C), pages 62-82.
    3. Schipperus, Ouren T. & Mulder, Machiel, 2015. "The effectiveness of policies to transform a gas-exporting country into a gas-transit country: The case of The Netherlands," Energy Policy, Elsevier, vol. 84(C), pages 117-127.
    4. Ghysels,Eric & Osborn,Denise R., 2001. "The Econometric Analysis of Seasonal Time Series," Cambridge Books, Cambridge University Press, number 9780521565882.
    5. Ollech Daniel, 2021. "Seasonal Adjustment of Daily Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 13(2), pages 235-264, July.
    6. Siem Jan Koopman & Marius Ooms, 2003. "Time Series Modelling of Daily Tax Revenues," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 57(4), pages 439-469, November.
    7. Ollech, Daniel, 2018. "Seasonal adjustment of daily time series," Discussion Papers 41/2018, Deutsche Bundesbank.
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    Cited by:

    1. Barend Abeln & Jan P. A. M. Jacobs, 2023. "COVID-19 and Seasonal Adjustment," SpringerBriefs in Economics, in: Seasonal Adjustment Without Revisions, chapter 0, pages 53-61, Springer.

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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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