Template-Type: ReDIF-Paper 1.0
Title: The Consequences of the COVID-19 Job Losses: Who Will Suffer Most and by How Much?
Author-Name: Andreas Gulyas
Author-Email: andreas.gulyas@gmail.com
Author-Name: Krzysztof Pytka
Author-Email:


Classification-JEL: 
Keywords: Covid-19 , Job displacement, Earnings losses, Causal machine learning

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 dierent 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.

Note: 
Length: 39
Creation-Date: 2020-09
Revision-Date: 
File-URL: https://www.crctr224.de/research/discussion-papers/archive/dp212
File-Format: application/pdf
Handle: RePEc:bon:boncrc:CRCTR224_2020_212