Abstract
This paper explores the impact of the COVID-19 lockdown on aggregate employment in Belgium. To this end, we use microdata of all Belgian firms and apply a machine learning-based approach to simulate the impact of the lockdown on employment growth under various economic scenarios. In doing so, we distinguish between start-ups and incumbent firms with both short and long-term effects. In the short term, we expect to see significant losses of employment coming mainly from mature incumbent firms. In the long term, the missing generation of start-ups formed during the lockdown will have a significant and growing effect of slowing down the employment growth even a decade after the lockdown.
| Original language | English |
|---|---|
| Pages (from-to) | 457-473 |
| Number of pages | 17 |
| Journal | International Economics and Economic Policy |
| Volume | 18 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Jul 2021 |
Funding
This work has benefited from the presentations at VIVES. Financial support of the “Methusalem” grant established by the Flemish government is gratefully acknowledged. Also, we want to thank Werner Roeger and participants of the EIIW digital workshop on “How will COVID-19 affect an already fragile global economy?” for their comments and discussion.
Keywords
- COVID-19
- Employment dynamics
- Machine learning
- Start-ups
ASJC Scopus subject areas
- Economics and Econometrics