COVID-19-Induced Automation: An Exploratory Study of Critical Occupations. Issue 2 (May 2023)

• Record Type: Journal Article
• Authors: Song, Chun; Beaulieu, Lionel J.; Kumar, Indraneel; Gallardo, Roberto
• Is Part Of: Economic development quarterly. Volume 37:Issue 2(2023)
• Page Start: 183
• Page End: 197
• Publication Date: 2023-05
• Subjects: COVID-19 -- pandemic-induced automation -- occupation -- labor market; Economic development -- Periodicals; Economics -- Periodicals; United States -- Economic conditions -- Periodicals; 330.973
• DOI: 10.1177/08912424231163151
• Languages: English
• ISSNs: 0891-2424

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.