The short-term economic consequences of COVID-19: Exposure to disease, remote work and government response

Abstract

We examine the determinants of the consequences of COVID-19 on employment and wages in the United States. Guided by a pre-analysis plan, we investigate whether the economic consequences of COVID-19 were larger for certain occupations, using four indexes: workers relatively more exposed to disease, workers that work with proximity to coworkers, essential/critical workers and workers who can easily work remotely. We find that individuals that work in proximity to others are more affected while individuals able to work remotely and essential workers are less affected by the pandemic. We also present suggestive evidence that our indexes are likely explanations why certain demographic groups such as younger and minority workers have worse labor market outcomes during the pandemic.

Fig 1. Physical proximity, exposure to the disease and remote work by occupation.

Notes: Each circle represents an occupation. The size of each circle represents the number of CPS respondents employed in that occupation–the larger the circle, the greater the number of people employed in that occupation. The x-axis plots each occupation’s physical proximity to coworkers, measured by O*NET’s index. The further to the right, the closer in proximity employees in that occupation work with their coworkers. The y-axis plots each occupation’s exposure to infection and disease, also measured by O*NET’s index. The further up, the more frequently employees in that occupation are exposes to infection and disease. The color of the circles corresponds to the whether or not the occupation can be performed remotely via [1].

Fig 2. Exposure to infection/disease by county.

Notes: Each county is assigned the average value of the exposure index based on the distribution of employment across occupations using 2018 American Community Survey (ACS) data. Endpoints correspond to quartiles. Person weights from the ACS are used.

Fig 3. Proximity to coworkers by county.

Notes: Each county is assigned the average value of the proximity index based on the distribution of employment across occupations using 2018 American Community Survey (ACS) data. Endpoints correspond to quartiles. Person weights from the ACS are used.

Fig 4. Essential workers by county.

Notes: Each county is assigned the average value of the critical index based on the distribution of employment across occupations using 2018 American Community Survey (ACS) data. Endpoints correspond to quartiles. Person weights from the ACS are used.

Fig 5. Remote workers by county.

Notes: Each county is assigned the average value of the remote worker index based on the distribution of employment across occupations using 2018 American Community Survey (ACS) data. Endpoints correspond to quartiles. Person weights from the ACS are used.

Fig 6. Unemployment by index and occupation.

Notes: Unemployment data are from Current Population Survey, indexes are calculated by authors using data from O*NET, LMI, and [1]. The x-axis indicates the index value while the y-axis indicates the average unemployment rate from March 2020 through June 2020. Each dot is a major occupation category (a two digit SOC code). Index values are normalized to mean 0 and standard deviation 1.

Fig 7. Unemployment rate by exposure to disease, proximity to coworkers, remote work, and essential work.

Notes: Authors’ calculations. Data from the Current Population Survey. The time period is January 2016 to June 2020. Each panel plots the unemployment rate. Panel A for individuals in occupations above and below the median for our index of exposure to the disease. Panel B for individuals in occupations above and below the median for our index of proximity to coworkers. Panel C for individuals in occupations designated by [1] as being able to be done remotely. Panel D for individuals in occupations designated as essential and non-essential by the Labor Market Information Institute.

Fig 8. Labor force participation by exposure to disease, proximity to coworkers, remote work, and essential work.

Notes: Authors’ calculations. Data from the Current Population Survey. The time period is January 2016 to June 2020. Each panel plots the monthly labor force participation rate. Panel A for individuals in occupations above and below the median for our index of exposure to the disease. Panel B for individuals in occupations above and below the median for our index of proximity to coworkers. Panel C for individuals in occupations designated by [1] as being able to be done remotely. Panel D for individuals in occupations designated as essential and non-essential by the Labor Market Information Institute. Individuals in the labor force were at work; held a job but were temporarily absent from work due to factors like vacation or illness; were seeking work; or were temporarily laid off from a job during the reference period.

Fig 9. Hourly wages by exposure to disease, proximity to coworkers, remote work, and essential work.

Notes: Authors’ calculations. Data from the Current Population Survey. The time period is January 2016 to June 2020. Each panel plots the monthly average hourly wage. Panel A for individuals in occupations above and below the median for our index of exposure to the disease. Panel B for individuals in occupations above and below the median for our index of proximity to coworkers. Panel C for individuals in occupations designated by [1] as being able to be done remotely. Panel D for individuals in occupations designated as essential and non-essential by the Labor Market Information Institute. Hourly wages: civilians aged 16–70 currently employed as wage/salary workers, paid hourly, and were in outgoing rotation groups. Excludes self-employed persons. Trimmed to exclude values below 1st percentile and above 99th percentile. Reported in 2018 constant dollars.

Fig 10. Hours worked by exposure to disease, proximity to coworkers, remote work, and essential work.

Notes: Authors’ calculations. Data from the Current Population Survey. The time period is January 2016 to June 2020. Each panel plots the average weekly hours worked. Panel A for individuals in occupations above and below the median for our index of exposure to the disease. Panel B for individuals in occupations above and below the median for our index of proximity to coworkers. Panel C for individuals in occupations designated by [1] as being able to be done remotely. Panel D for individuals in occupations designated as essential and non-essential by the Labor Market Information Institute. Hours worked: civilians aged 16–70 who are employed and either at work or absent from work during the survey week, all jobs. Trimmed to exclude values below 1st percentile and above 99th percentile.

Fig 11. Percentage point change in unemployment (january 2020 to may 2020) by index and occupation.

Notes: Unemployment data are from Current Population Survey, indexes are calculated by authors using data from O*NET, LMI, and [1]. The x-axis indicates the index value while the y-axis indicates the change in unemployment rate from January 2020 through May 2020. Each dot is a major occupation category (a two digit SOC code). Index values are normalized to mean 0 and standard deviation 1.

Fig 12. Percentage point change in unemployment (january 2020 to may 2020) by index and demographics.

Notes: Unemployment data are from Current Population Survey, indexes are calculated by authors using data from O*NET, LMI, and [1]. The x-axis indicates the index value while the y-axis indicates the change in unemployment rate from January 2020 through May 2020. Each dot is a demographic characteristic. Index values are normalized to mean 0 and standard deviation 1.