By Miguel Faria-e-Castro, Economist
As state and local governments implement social-distancing measures to suppress and contain the spread of COVID-19, many businesses are faced with a large decrease in sales and revenue. This slowdown of economic activity could inevitably lead to solvency and liquidity problems that result in workers being laid off.
This negative shock does not equally affect all businesses, sectors or occupations. Many workers in professional services, for example, are able to work from home and continue their activities with minimal disruption. Others—who work in occupations that involve direct physical contact with customers, such as restaurant waiters—are likely to see their jobs affected by social-distancing measures.
In this blog post, we combine different types of statistics on industry and occupation composition to try to arrive at a back-of-the-envelope estimate for what the unemployment rate may be at the end of the second quarter of 2020.
Our starting point is the state of the U.S. economy as of February 2020. According to the Bureau of Labor Statistics (via FRED), the civilian labor force consisted of 164.5 million people, and the unemployment rate was 3.5%.These figures are available on the FRED pages for the Civilian Labor Force Level and the Unemployment Rate. This means that there were around 5.76 million unemployed people in the U.S. in February. In our calculation, we assumed that the labor force remains constant and that none of those 5.76 million people would be able to find a job in the second quarter of 2020.
The important question is: How many people, on net, will be laid off during Q2? To estimate this number, we combined data from two recent blog posts that tried to compute how many jobs are exposed to layoff risk due to social distancing.
In a recent blog post, Charles Gascon used 2018 occupational data from the BLS to estimate how many employees are at high risk of layoff due to social-distancing measures.COVID-19: Which Workers Face the Highest Unemployment Risk? Gascon classified 808 occupations according to three criteria:
He estimated that 66.8 million people are employed in occupations that are at high risk of layoff. These include occupations in sales, production, and food preparation and services, among others.
In another recent blog post, Matthew Famiglietti, Fernando Leibovici and Ana Maria Santacreu combined individual-level data from the 2017 American Community Survey with information on occupational contact intensity from O*NET to determine how many people work in occupations that require the worker to perform tasks in close physical proximity to other people. Social Distancing and Contact-Intensive Occupations They found that 27.3 million workers have occupations with a high contact intensity. These include barbers, hairstylists, food and beverage serving workers, and flight attendants, among others.
These two numbers were obtained by applying different methodologies and classifications to two different datasets. This means that while there may be significant overlap, each measure will also be capturing some aspects that the other ignores.
For this reason, we simply took the average of those two numbers as a point estimate for the total number of workers who will be laid off during the second quarter. This resulted in 47.05 million people being laid off during this period.
Summing to the initial number of unemployed in February, this resulted in a total number of unemployed persons of 52.81 million. Given the assumption of a constant labor force, this resulted in an unemployment rate of 32.1%.
It is worth emphasizing that this is a point estimate that makes several important assumptions. One way to think about how to bound this estimate is to take the Famiglietti-Leibovici-Santacreu number minus 10 million (workers in education and health care, who are less likely to be laid off) as an optimistic estimate for the number of layoffs during the second quarter and the Gascon number as a more pessimistic estimate. This results in unemployment rates between 10.5% and 40.6%.
There are other important caveats:
Moreover, one can argue that the expected duration of unemployment matters more than the unemployment rate itself, especially if the recovery is quick (and so duration is short). These are very large numbers by historical standards, but this is a rather unique shock that is unlike any other experienced by the U.S. economy in the last 100 years.
4 For examples of fiscal policies that can affect unemployment rates, see Dupor, Bill. “Possible Fiscal Policies for Rare, Unanticipated, and Severe Viral Outbreaks.” Economic Synopses, March 17, 2020.