Composition of the workforce during the COVID-19 pandemic

Examining the ins and outs of the workforce is essential to understanding labor market dynamics, especially during the COVID-19 pandemic. This article focuses on two dimensions of the workforce, both in the Eighth District and nationally. The first is the demographic composition of who is in the labor force (ie, people employed or unemployed) versus not in the labor force. The second is the industrial composition of employment and unemployment.

We found that, compared to the US as a whole, the Eighth District experienced a slightly milder recession in 2020-21. Although the number of people leaving the workforce in the Eighth District resembles the nation, job recovery in the hardest-hit industries has moved faster in the Eighth District.

What Labor Force Participation Reveals

We begin by looking at labor force participation. A person is considered out of the labor force, or non-participant, if they are not currently looking for work. Although workers outside the labor force do not contribute to the unemployment rate, they do contribute to the shortfall in the number of jobs the US has seen since early 2020.

We use microdata from the Current Population Survey (CPS), which is a source of official employment reports from the Bureau of Labor Statistics. In this survey, respondents can be tracked from month to month (in blocks of four months), which means we can track changes in the state of the workforce.

In the first figure, we report the number of workers leaving the workforce each month for the entire US and the Eighth District. In all cases, the series is normalized to 100 in February 2020, immediately before the pandemic hit the economy.

The figure shows that, relative to pre-pandemic levels, labor force departures increased for the remainder of 2020, with the largest peak early on. Compared to the US as a whole, the Eighth District had a lower dropout rate initially, but has since followed a similar path.

Labor force exits are now slightly lower in the Eighth Ward. Keep in mind that these departures are not necessarily permanent, but once someone leaves, their likelihood of future reemployment decreases relative to someone who remains unemployed but is still actively looking for work. Therefore, the pattern of exits is relevant to how quickly the recovery unfolds.

Next, we examine who remained out of the labor force from May to August 2021. Specifically, we look at how an individual’s demographics relate to whether they are in or out of the labor force. The second figure shows the probability that a member of each demographic group was out of the labor force.

The general trends are similar in the US as a whole and in the Eighth Ward. Women, workers with less education, and those not of working age are more likely to be out of the labor force. These facts are robust and have generally held true over the past several decades, regardless of the state of the business cycle.

The likelihood of being out of the labor force is similar for people inside and outside the Eighth Ward, with the exception of a few groups: Blacks, other races, high school dropouts, and workers age 55 and older have slightly more likely to be out of the labor force. labor in the Eighth District; Asians and Pacific Islanders, as well as workers under the age of 25, are more likely to be in the workforce in the Eighth Ward.

Industry Specific Statistics During COVID-19

Below, we take a look at how different industries have been affected by the pandemic. CPS microdata allowed us to look at the most recent industries for respondents who reported being unemployed. Using these answers, we calculated the percentage of unemployed workers who were previously in each industry.

The results are shown in the third figure below. The industry composition of the unemployed partly reflects the number of jobs in each industry: For example, across the country, there were many unemployed healthcare workers because there are many healthcare jobs. Relative to the rest of the US, the Eighth District had more unemployed workers in the manufacturing industry; transportation and storage; administrative and support services and waste management. It had fewer unemployed workers in accommodation and food services; healthcare and social assistance; retail trade; and educational services.

How quickly these workers are reabsorbed into jobs will depend on several factors: demand for each industry’s output, recovery from pandemic-related shutdowns, and the wages offered. Note also that the facts reported in the third figure do not account for new entrants to the labor market (who, by definition, do not have a prior industry of employment) and may not be indicative of the industries in which they may be. workers are really focusing their work. search efforts.

We can get an idea of ​​how quickly each industry is recovering by looking at the evolution of employment for different industries during the pandemic. This gives a fuller picture of what has been happening over time. These employment changes also reflect people who have left the labor force and are not listed on the unemployment pool. This data comes from the Quarterly Census of Employment and Wages (QCEW), which aggregates employer-related employment and wage counts.

The results for general employment, as well as for some selected industries, are shown in the table. Each column shows the percentage drop in employment relative to February 2020. The table shows that in the US as a whole, employment had fallen to 84% of its pre-pandemic level in April 2020, a decrease of 16%. The decline was similar but slightly milder in the Eighth Ward, which saw only a 13% decline. Since then, both have been recovering at similar rates, but the Eighth District remains slightly ahead of the US as a whole, with 3% fewer jobs compared to 5% nationally.

Breaking these numbers down by industry helps to understand where deficiencies persist and why the Eighth District looks different from US retail, which is a large industry containing a mix of essential and non-essential services, which evolved similarly to aggregate employment. Health care, another sector at the forefront of the pandemic, saw smaller initial declines and has since rebounded similarly across the country and in the Eighth Ward. Both industries have nearly returned to pre-pandemic levels.

The biggest drops in employment and the biggest gaps between the Eighth District and the rest of the country are in the following industries: arts, entertainment and recreation; accommodation and food services; and other services (including repair services and personal services, such as salons and dry cleaning).

In general, these industries were less affected in the Eighth Ward compared to other places. An interesting case in point is the arts, entertainment, and recreation industry: in the Eighth Ward, it had a larger initial decline, but now remains closer to pre-pandemic levels than the US as a whole. These hardest-hit industries are where the gaps between the US and the Eighth District remain the largest today.

Conclution

We find that the demographic characteristics of those who have left the workforce are similar in the Eighth Ward and elsewhere. However, the Eighth Ward experienced a milder slowdown compared to the rest of the country. This was driven by differing responses in the Eighth Ward for sectors of the economy hardest hit by the pandemic.

These differences may be related to less restrictive economic policies implemented to combat the pandemic, rather than the course of the virus itself. It’s also important to note that the workforce composition characteristics examined here are only one dimension of how the Eighth District has fared; just a few others include differences in health outcomes, wages, and business closures.

final notes

1. As of August 2021, employment remained 5.3 million below its value in February 2020.
2. Due to the high incidence of missing values ​​in the CPS county variable, we classified a respondent as a resident of the Eighth District if he or she reported living in one of its metropolitan statistical areas; people living outside of District MSAs were excluded from this study.
3. Note that there is overlap between the different bars on this chart. For example, if a given gender, education, or racial group is disproportionately made up of workers of working age, the bar will show a lower probability that those workers are out of the labor force.
4. However, employment is reported monthly in the QCEW.