The Consequences of the COVID-19 Job Losses: Who Will Suffer Most and by How Much?

Andreas Gulyas and Krzysztof Pytka

CRC TR 224 Discussion Paper Series from University of Bonn and University of Mannheim, Germany

Abstract: Using the universe of Austrian unemployment insurance records until May 2020, we document that the composition of UI claimants during the Covid-19 outbreak is sub- stantially di erent compared to past times. Using a machine-learning algorithm from Gulyas and Pytka (2020), we identify individual earnings losses conditional on worker and job characteristics. Covid-19-related job terminations are associated with lower losses in earnings and wages compared to the Great Recession, but similar employ- ment losses. We further derive an accurate but simple policy rule targeting individuals vulnerable to long-term wage losses.

Keywords: Covid-19; Job displacement; Earnings losses; Causal machine learning (search for similar items in EconPapers)
Pages: 39
Date: 2020-09
New Economics Papers: this item is included in nep-big and nep-ias
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Persistent link: https://EconPapers.repec.org/RePEc:bon:boncrc:crctr224_2020_212

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