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COVID-19 and Seasonal Adjustment

In: Seasonal Adjustment Without Revisions

Author

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

    (University of Groningen)

Abstract

In this chapter, we study the impact of COVID-19 on seasonal adjustment. We focus on whether special adjustments are required to treat the COVID-19 crisis as an outlier as suggested by Eurostat in the application of three seasonal adjustment procedures: X-13ARIMA-SEATS, the industry standard, STL (Seasonal-Trend decomposition based on Loess), and a new method CAMPLET, an acronym of its tuning parameters. In addition, we investigate whether revisions occur. We show results of seasonal adjustments for the quarterly series real GDP in the Netherlands and for the weekly series U.S. Initial Claims. Seasonal adjustment with X-13ARIMA-SEATS and CAMPLET requires modifications in the implementation of the standard procedure to treat the COVID-19 crisis as an outlier; STL can be applied straightforwardly. Differences in seasonally adjusted values are generally small around COVID-19. Finally, X-13ARIMA-SEATS and STL seasonal adjustments are subject to revision, which probably will lead to the COVID-19 crisis becoming less deep when new observations become available.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:spbchp:978-3-031-22845-2_5
    DOI: 10.1007/978-3-031-22845-2_5
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    References listed on IDEAS

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    1. Irma Hindrayanto & Jan Jacobs & Denise Osborn, 2014. "On trend-cycle-seasonal interactions," DNB Working Papers 417, Netherlands Central Bank, Research Department.
    2. 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.
    3. Hindrayanto, Irma & Jacobs, Jan P.A.M. & Osborn, Denise R. & Tian, Jing, 2019. "Trend–Cycle–Seasonal Interactions: Identification And Estimation," Macroeconomic Dynamics, Cambridge University Press, vol. 23(8), pages 3163-3188, December.
    4. Harvey, Andrew & Koopman, Siem Jan & Riani, Marco, 1997. "The Modeling and Seasonal Adjustment of Weekly Observations," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 354-368, July.
    5. Proietti, Tommaso & Pedregal, Diego J., 2023. "Seasonality in High Frequency Time Series," Econometrics and Statistics, Elsevier, vol. 27(C), pages 62-82.
    6. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino & Elmar Mertens, 2024. "Addressing COVID-19 Outliers in BVARs with Stochastic Volatility," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1403-1417, September.
    7. 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.
    8. Pierce, David A & Grupe, Michael R & Cleveland, William P, 1984. "Seasonal Adjustment of the Weekly Monetary Aggregates: A Model-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(3), pages 260-270, July.
    9. Ghysels,Eric & Osborn,Denise R., 2001. "The Econometric Analysis of Seasonal Time Series," Cambridge Books, Cambridge University Press, number 9780521565882.
    10. Daniel J. Lewis & Karel Mertens & James H. Stock & Mihir Trivedi, 2022. "Measuring real activity using a weekly economic index," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 667-687, June.
    11. 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.
    12. Hylleberg, Svend, 1986. "Seasonality in Regression," Elsevier Monographs, Elsevier, edition 1, number 9780123634559 edited by Shell, Karl.
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    Cited by:

    1. van Bergeijk, P.A.G., 2021. "The political economy of the next pandemic," ISS Working Papers - General Series 678, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    2. Lahiri, Kajal & Yin, Yimeng, 2024. "Seasonality in U.S. disability applications, labor market, and the pandemic echoes," Labour Economics, Elsevier, vol. 87(C).
    3. Simone di Paolo & Danilo Liberati, 2024. "Seasonal adjustment of credit time series in the Bank of Italy," Questioni di Economia e Finanza (Occasional Papers) 835, Bank of Italy, Economic Research and International Relations Area.
    4. William M. Doerner & Wenzhen Lin, 2022. "Applying Seasonal Adjustments to Housing Markets," FHFA Staff Working Papers 22-03, Federal Housing Finance Agency.

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

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