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

Sylvia Kaufmann

Swiss Journal of Economics and Statistics, 2023, vol. 159, issue 1, 1-10

Abstract: 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.

Keywords: Bayesian analysis; Covid-19; Pseudo-real-time; Ordinances; SECO; KOF (search for similar items in EconPapers)
JEL-codes: C32 C53 E23 E27 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1186/s41937-023-00106-x

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