Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/259754 
Year of Publication: 
2020
Citation: 
[Journal:] Swiss Journal of Economics and Statistics [ISSN:] 2235-6282 [Volume:] 156 [Issue:] 1 [Article No.:] 12 [Publisher:] Springer [Place:] Heidelberg [Year:] 2020 [Pages:] 1-12
Publisher: 
Springer, Heidelberg
Abstract: 
The number of short-time workers from January to April 2020 is used to now- and forecast quarterly GDP growth. We purge the monthly log level series from the systematic component to extract unexpected changes or shocks to log short-time workers. These monthly shocks are included in a univariate model for quarterly GDP growth to capture timely, current-quarter unexpected changes in growth dynamics. Included shocks additionally explain 24% in GDP growth variation. The model is able to forecast quite precisely the decrease in GDP during the financial crisis. It predicts a mean decline in GDP of 5.7% over the next two quarters. Without additional growth stimulus, the GDP level forecast remains persistently 4% lower in the long run. The uncertainty is large, as the 95% highest forecast density interval includes a decrease in GDP as large as 9%. A recovery to pre-crisis GDP level in 2021 lies only in the upper tail of the 95% highest forecast density interval.
Subjects: 
Bayesian analysis
COVID-19
Two-step regression
Forecasting
JEL: 
E23
E27
C32
C53
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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