Impact of coronavirus (COVID-19) pandemic on Job Openings and Labor Turnover data for April 2020

The Job Openings and Labor Turnover Survey (JOLTS) national estimates of job openings, hires, and separations have been affected by the coronavirus (COVID-19) pandemic. This page provides further information on the effects of the COVID-19 pandemic for the April 2020 JOLTS News Release.

Although the impact cannot be precisely quantified for April, it is clear that decreasing job openings, hires, and quits, and continuing high levels of layoffs and discharges can be attributed to the effect of the pandemic. More information on the JOLTS methodology can be found in the JOLTS Handbook of Methods chapter.

Collection mode

Data collection for JOLTS was affected by the COVID-19 pandemic. Prior to the pandemic, JOLTS collected 42 percent of data by phone at the JOLTS data collection center on average. Most phone respondents were asked to report electronically through our data collection website. However, data collection was adversely impacted by the inability to reach some respondents that normally respond by phone.

Response rates

The preliminary JOLTS response rate for April 2020 was 44 percent. In March, the final response rate was 51 percent. In the year prior to the pandemic, the preliminary response rate averaged 54 percent, and the final response rate averaged 58 percent.

In April, JOLTS response rates declined in all industries and size classes. The industry most impacted was mining and logging. The industries least affected were retail trade and finance and insurance.

Imputation

JOLTS imputation for April resulted in very few cells with more imputation relative to the previous year. The two industries which generally experienced more imputation were retail trade and professional and business services.

Cell, series, index, or observation suppression

JOLTS did not suppress publication cells for April 2020.

Measures of error

Since the JOLTS program uses the median standard error over 5 years, the observed effect of April 2020 on the 5-year median is not likely to be large. JOLTS will not have error measures that include data from the current year until annual processing in March 2021.

Changes to methods

In anticipation of issues due to the pandemic, the JOLTS program reviewed all estimation and methodological procedures. An adjustment has been made to the JOLTS estimation methodology in order to more accurately reflect the effects of the coronavirus (COVID-19) pandemic. Adjustments were also made to the seasonal adjustment process.

Estimation

BLS modified the JOLTS estimates for April to better reflect the impact of the coronavirus (COVID-19) pandemic. The estimation process usually includes an alignment of monthly hires minus separations to the over-the-month change in the Current Employment Statistics (CES) employment estimates. For April estimates, however, BLS suspended the alignment process because the differing reference periods for the CES employment estimates (pay period including the 12th of the month) and the JOLTS hires and separations estimates (the entire reference month) led to substantially different measurement outcomes. Hires and separations during the latter half of April were not included in the CES employment change for April, but were included in the JOLTS data for the month.

The alignment portion of the JOLTS estimation process was designed to correct a long-term divergence between the JOLTS implied employment change and the CES employment change. JOLTS hires minus separations and CES employment change generally approximate one another. Alignment was developed to correct small monthly discrepancies between the two series that build up over time; it was not designed to address a substantial one-month divergence between the two series. The alignment process was suppressed in order to produce the highest quality JOLTS estimates possible in this unique situation.

Seasonal Adjustment

Seasonal adjustment factors can be either multiplicative or additive. A multiplicative seasonal effect is assumed to be proportional to the level of the series. A sudden large increase in the level of the series will be accompanied by a proportionally large seasonal effect. In contrast, an additive seasonal effect is assumed to be unaffected by the level of the series. In times of relative economic stability, the multiplicative option is generally preferred over the additive option. However, in the presence of a large level shift in a time series, multiplicative seasonal adjustment factors can result in systematic over- or under-adjustment of the series; in such cases, additive seasonal adjustment factors are preferred since they tend to more accurately track seasonal fluctuations in the series and have smaller revisions.

In April, most of the JOLTS series will retain the additive designation. In accordance with the survey’s usual practice, the seasonal adjustment models and factors will be reviewed at the end of the calendar year, when 5 years of seasonally adjusted estimates will be subject to revision.

Questions and answers specific to April

1. How are people who were laid off counted by JOLTS? The reference periods of the Job Openings and Labor Turnover Survey (JOLTS) are the pay period that includes the 12th of the month for employment, the last business day of the month for job openings, and the entire calendar month for hires and separations. The JOLTS program does not estimate employment, but does collect employment during the collection process to validate reported job openings, hires, and separations. Employees who are laid off from their job at any time during the month are reported in the layoff and discharges measure, and in total separations. See the JOLTS frequently asked questions for detailed information on the data definitions.
2. How did the April estimates compare with the monthly estimates for past JOLTS data? While April estimates still reflected the impact of the pandemic, the March over-the-month declines were the largest in the series for all JOLTS data elements.

Last Modified Date: June 9, 2020