Labor demand in the time of COVID-19: Evidence from vacancy postings and UI claims

Abstract

We use job vacancy data collected in real time by Burning Glass Technologies, as well as unemployment insurance (UI) initial claims and the more traditional Bureau of Labor Statistics (BLS) employment data to study the impact of COVID-19 on the labor market. Our job vacancy data allow us to track the economy at disaggregated geography and by detailed occupation and industry. We find that job vacancies collapsed in the second half of March. By late April, they had fallen by over 40%. To a first approximation, this collapse was broad based, hitting all U.S. states, regardless of the timing of stay-at-home policies. UI claims and BLS employment data also largely match these patterns. Nearly all industries and occupations saw contraction in postings and spikes in UI claims, with little difference depending on whether they are deemed essential and whether they have work-from-home capability. Essential retail, the "front line" job most in-demand during the current crisis, took a much smaller hit, while leisure and hospitality services and non-essential retail saw the biggest collapses. This set of facts suggests the economic collapse was not caused solely by the stay-at-home orders, and is therefore unlikely to be undone simply by lifting them.

Keywords: Covid-19; Job vacancies; Labor demand; Recessions; Unemployment.

Fig. 1

Labor Market Series by State Policy. Note: Vertical lines indicate the first date of stay-at-home orders in the state group, by color. The darkest line/circle includes the first group of states to issue stay-at-home orders, having done so by March 22 (California, Illinois, New York, and New Jersey). The next darkest line/cirlce includes the vast majority of states, those issuing stay-at-home orders between March 23 and 30, and the lighter line/circle includes states issuing stay-at-home orders most recently (from March 31). The dashed line/hollow circle shows the five states with no such order (Arkansas, Iowa, Nebraska, North Dakota, and South Dakota). All series are the per capita change in postings from the state group-specific average over January 19-Feb 29, 2020. CPS exits are moves from employment in the preceding month to non-employment in the current month.

Fig. 2

Labor market series by COVID spread. Notes: Variables are the per capita change in the state from January 19–February 29 and March 22–May 2, 2020. Claims are the sum of initial claims over the relevant time period. The best fit lines are population weighted. The X-axis is log (1 + cases) divided by population so that states with no cases as of March 14 are still included and indicated with hollow circles.

Fig. 3

Job postings by sector. Notes: Postings and employment are divided by the industry or occupation-specific average from February 2020. Categories are mutually exclusive and exhaustive. Nursing is occupation codes beginning in 291141 (it is not possible to measure occupations for CES employment). Health is NAICS industry code 62. Retail is NAICS code 44–45 and divided into our categorization of essential and non-essential based on New York State guidelines. Leisure and hospital are NAICS codes 71 and 72.

Fig. 4

Washington State initial UI claims (lines) and CPS exits (dots). Note: We normalize claims and exits by industry or occupation-specific employment and take the difference relative to the average from January 19–Feb 29, 2020. For CPS exits, groupings are mutually exclusive and exhaustive. For UI claims, the industries are mutually exclusive, but Nursing is occupation SOC 291 and also contained in the other groups. For comparison, the CPS employment-to-non-employment separation rates in March and April are converted to weekly rates and included as dots.

Fig. 5

Labor market outcomes by work from home capability. Notes: Postings (left panel) are divided by group-specific average from January 19–February 29, 2020. Categories are mutually exclusive and exhaustive. Work-from-home (wfh) measures are assigned at the occupation level using Dingel and Neiman (2020). Claims and exits (right panel) are computed as percent of employment in that occupation group and differenced from the group-specific average from January 19–Feb 29, 2020. Claims are not available for industry-by-occupation categories so we cannot break down wfh by whether the industry is essential. In the right panel, the CPS employment separation rates in March and April are converted to weekly rates and included as dots.