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Covid-19 outbreak and beyond: a retrospect on the information content of short-time workers for GDP now- and forecasting

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  • Sylvia Kaufmann

    (Foundation of the Swiss National Bank
    University of Basel)

Abstract

We document whether a simple, univariate model for quarterly GDP growth is able to deliver forecasts of yearly GDP growth in a crisis period like the Covid-19 pandemic, which may serve cross-checking forecasts obtained from elaborate and expert models used by forecasting institutions. We include shocks to the log number of short-time workers as timely available current-quarter indicator. Yearly GDP growth forecasts serve cross-checking, in particular at the outbreak of the pandemic.

Suggested Citation

  • Sylvia Kaufmann, 2023. "Covid-19 outbreak and beyond: a retrospect on the information content of short-time workers for GDP now- and forecasting," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-10, December.
    • Handle: RePEc:spr:sjecst:v:159:y:2023:i:1:d:10.1186_s41937-023-00106-x
    DOI: 10.1186/s41937-023-00106-x
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    References listed on IDEAS

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    3. Wegmüller, Philipp & Glocker, Christian & Guggia, Valentino, 2023. "Weekly economic activity: Measurement and informational content," International Journal of Forecasting, Elsevier, vol. 39(1), pages 228-243.
    4. Nicola Fuchs-Schünde & Dirk Krueger & Alexander Ludwig & Irina Popova, 2022. "The Long-Term Distributional and Welfare Effects of Covid-19 School Closures," The Economic Journal, Royal Economic Society, vol. 132(645), pages 1647-1683.
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    8. Christina D. Romer & David H. Romer, 1989. "Does Monetary Policy Matter? A New Test in the Spirit of Friedman and Schwartz," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 121-184, National Bureau of Economic Research, Inc.
    9. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    10. Marc Burri & Daniel Kaufmann, 2020. "A daily fever curve for the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-11, December.
    11. Sylvia Kaufmann, 2020. "COVID-19 outbreak and beyond: the information content of registered short-time workers for GDP now- and forecasting," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-12, December.
    12. Ronald Indergand & Stefan Leist, 2014. "A Real-Time Data Set for Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(IV), pages 331-352, December.
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    More about this item

    Keywords

    Bayesian analysis; Covid-19; Pseudo-real-time; Ordinances; SECO; KOF;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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