COVID-19-Induced Automation: An Exploratory Study of Critical Occupations

Chun Song, Lionel J. Beaulieu, Indraneel Kumar and Roberto Gallardo

Economic Development Quarterly, 2023, vol. 37, issue 2, 183-197

Abstract: The COVID-19 pandemic may have spurred automation, especially in critical occupations. This article explores the potential of each detailed Standard Occupational Classification System (SOC) occupation being automated due to COVID-19. The authors explore two key elements of each occupation: its exposure to diseases such as COVID-19 and the probability of that occupation being automated. The results reveal that food preparation, service, and cleaning-related occupations have a higher chance of pandemic-induced automation. Using monthly U.S. job postings from 2016 to 2021, the estimates show that the potential pandemic-induced automation is associated with a statistically significant decrease in job postings. A higher Automation Index is associated with fewer job postings since the pandemic. Such trends remain robust after accounting for posting duration and excluding health-related occupations. These findings contribute to the early assessment of the impact of COVID-19 on the potential integration of automation in the labor force and offer insights into building a resilient and labor-centric post-pandemic labor market.

Keywords: COVID-19; pandemic-induced automation; occupation; labor market (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:ecdequ:v:37:y:2023:i:2:p:183-197

DOI: 10.1177/08912424231163151

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