Can COVID-19 Accelerate Technological Transformations?

33 Pages Posted: 10 Sep 2020 Last revised: 8 Dec 2020

See all articles by Pablo Egana-delSol

Pablo Egana-delSol

Adolfo Ibanez University - School of Business; MIT Sloan

Alejandro Micco

University of Chile

Date Written: September 8, 2020


In this paper, we present evidence about the short-term impact of COVID-19 on the labor market in the United States. During the second quarter of 2020, the pandemic destroyed 18 million jobs in the US private sector. For economics policies we inquire as to why some sectors, occupations, and demographic groups are more affected than others. We find that factors directly related to the epidemic are essential. Employees in occupations working in proximity to others are more affected, while occupations able to work remotely are less affected. We would expect that employment in these occupations should recover rapidly post-pandemic. But, we also find that sectors with a large fraction of occupations at risk of automation present a significantly higher contraction on employment. The contraction is mainly driven by sectors that underwent a capital deepening process in ICT and Software previous to the pandemic. A sector with one standard deviation higher in the share of employment in occupation at risk of automation cuts around 5 percentage points more employment during the second quarter of 2020. The same sector, but with one standard deviation higher increase in technology capital, cuts employment by around 7 percent. This evidence is in line with the similar cleansing process during the Great Recession. COVID-19 is catalyzing the automation process, and employment losses related to this phenomenon could be permanent.

Keywords: COVID-19, Adoption, Automation

JEL Classification: D2, J23, J24

Suggested Citation

Egana-delSol, Pablo and Micco, Alejandro, Can COVID-19 Accelerate Technological Transformations? (September 8, 2020). Available at SSRN: or

Pablo Egana-delSol

Adolfo Ibanez University - School of Business ( email )

Diagonal Las Torres

MIT Sloan ( email )

100 Main Street
Cambridge, MA 02142
United States

Alejandro Micco (Contact Author)

University of Chile ( email )

Pío Nono Nº1, Providencia
Santiago, R. Metropolitana 7520421

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