The National Center for Education Statistics recognizes the need to provide expanded economic data on education, including data about the education labor market. In this blog we will be presenting public education sector data from the February 2024 release of the Job Openings and Labor Turnover Survey (JOLTS) data produced by the Bureau of Labor Statistics. JOLTS data provide national monthly estimates of job openings, hires, and separations. These data can be used to monitor current labor market demand in education and to assess the presence or extent of labor shortages1.
JOLTS Design
JOLTS is a monthly survey of about 21,000 public and private employers across all nonagricultural industries in the 50 States and District of Columbia. JOLTS estimates are produced by industry sector, including education2. Additionally, JOLTS provides separate estimates for public and private education. This enables our analysis to focus on the public state and local education industry (“state and local government education” as referred to by JOLTS)3, which includes all persons employed by public elementary and secondary school systems and public postsecondary institutions.
The JOLTS program does not produce estimates by Standard Occupational Classification4. When reviewing these findings, please note occupations5 within the public state and local education industry vary6 (e.g., teachers and instructional aides, administrators, cafeteria workers, and transportation workers).
Analysis
This analysis of JOLTS data highlights key statistics describing employment availability, hiring, and turnover in public local and state education. Table 1 includes estimates on the number of job openings, hires, and separations from February 2020 through February 2024. Table 2 includes estimates on the corresponding rates of job openings, hires, separations, fill and churn rate measures from February 2020 through February 2024. The job openings rate is computed by dividing the number of job openings by the sum of employment and job openings. Metric rates for hires, total separations, quits, layoffs and discharges, and other separations are defined by taking the number of each metric and dividing it by employment. Fill rate and churn rates are calculated economic measures that are not readily available from the JOLTS database. Fill rate is defined as the ratio of the number of hires to the number of job openings and the churn rate is defined as the sum of the rate of hires and the rate of total separations7,8.
Table 1. Number of job openings, hires, separations, and net change in employment in public state and local education, in thousands: February 2020 through February 2024
|
Employment activity |
February 2020 |
February 2021 |
February 2022 |
February 2023 |
February 2024 |
|
Job openings |
259 |
170* |
322* |
314* |
226 |
|
Hires |
141* |
95 |
135 |
129 |
107 |
|
Total separations |
74 |
77 |
106 |
81 |
80 |
|
Quits |
49 |
54 |
75* |
54 |
56 |
|
Layoffs and discharges |
16 |
12 |
18 |
18 |
17 |
|
Other separations |
9 |
12 |
13 |
9 |
7 |
|
Net change in employment |
67* |
18 |
29 |
48 |
27 |
*Significantly different from February 2024 (p < .05).
NOTE: Data are not seasonally adjusted. Detail may not sum to totals because of rounding.
SOURCE: U.S. Department of Labor, Bureau of Labor Statistics, Job Openings and Labor Turnover Survey (JOLTS), 2020–2024, based on data downloaded April 2, 2024, from https://data.bls.gov/cgi-bin/dsrv?jt.
Table 2. Rate of job openings, hires, and separations in public state and local education and fill and churn rates: February 2020 through February 2024
|
Employment activity |
February 2020 |
February 2021 |
February 2022 |
February 2023 |
February 2024 |
|
Job openings |
2.3 |
1.6* |
3.0* |
2.8* |
2.0 |
|
Hires |
1.3* |
0.9 |
1.3* |
1.2 |
1.0 |
|
Total separations |
0.7 |
0.8 |
1.0* |
0.7 |
0.7 |
|
Quits |
0.4 |
0.5 |
0.7* |
0.5 |
0.5 |
|
Layoffs and discharges |
0.1 |
0.1 |
0.2 |
0.2 |
0.2 |
|
Other separations |
0.1 |
0.1 |
0.1 |
0.1 |
0.1 |
|
Fill Rate |
0.5 |
0.6 |
0.4 |
0.4 |
0.5 |
|
Churn Rate |
2.0 |
1.7 |
2.3* |
1.9 |
1.7 |
*Significantly different from February 2024 (p < .05).
NOTE: Data are not seasonally adjusted. Detail may not sum to totals because of rounding.
SOURCE: U.S. Department of Labor, Bureau of Labor Statistics, Job Openings and Labor Turnover Survey (JOLTS), 2020–2024, based on data downloaded April 2, 2024, from https://data.bls.gov/cgi-bin/dsrv?jt.
Overview of February 2024 Estimates
The number of job openings in public state and local education was 226,000 on the last business day of February 2024, which was higher than in February 2021 (170,000) and lower than in February 2022 (322,000) and February 2023 (314,000) (Table 1). In percentage rate terms, 2.0 percent of jobs had openings in February 2024, which was lower than in February of the previous two years (3.0 percent in 2022 and 2.8 percent in 2023) (Table 2). The number and percentage of job openings in February 2024 were not measurably different from the number and percentage in February 2020. The number of hires in public state and local education was 107,000 for February 2024, which was not measurably different from in February of the previous three years, but was lower than February 2020 (141,000) (Table 1). The number of job openings at the end of February 2024 (226,000) was nearly double the number of staff hired that month (107,000). In addition, the fill rate for that month (0.5) was less than 1, which suggests a need for public state and local government education employees that was not being filled completely by February 2024.
The number of total separations in the state and local government education industry in February 2024 (80,000) was not measurably different from in February of the previous four years. In February 2024, the number of quits (56,000) was higher than the number of layoffs and discharges (17,000). Layoffs and discharges accounted for 21 percent of total separations in February 2024 (which as not measurably different from the percentage of layoffs and discharges out of total separations in February 2023, 2022, 2021, or 2020) while quits accounted for 70 percent of total separations (which was not measurably different from the percentage of quits out of total separations in February 2023, 2022, 2021, or 2010).
This blog is part of NCES' effort to share more economic data from other federal statistical agencies that is relevant to education. We plan to provide regular updates to selected months from JOLTS to enable our data users to find and follow useful information about the education workforce.
By Josue DeLaRosa, NCES
1 “Job Openings and Labor Turnover Survey Overview Page.” BLS.gov. Last modified November 28, 2022. https://www.bls.gov/jlt/jltover.htm
2 For more information about these estimates, please see https://www.bls.gov/news.release/jolts.tn.htm.
3 JOLTS refers to this industry as state and local government education, which is designated as ID 92.
4 For more information on the reliability of JOLTS estimates, please see https://www.bls.gov/jlt/jltreliability.htm.
5 North American Industry Classification System (NAICS) is a system for classifying establishments (individual business locations) by type of economic activity. The Standard Occupational Classification (SOC) classifies all occupations for which work is performed for pay or profit. To learn more on the differences between NAICS and SOC, please see https://www.census.gov/topics/employment/industry-occupation/about/faq.html.
6 JOLTS data are establishment-based and there is no distinction between occupations within an industry. If a teacher and a school nurse were hired by an establishment coded as state and local government education, both would fall under that industry. (Email communication from JOLTS staff, April 7, 2023)
7 Skopovi, S., Calhoun, P., and Akinyooye, L. “Job Openings and Labor Turnover Trends for States in 2020.” Beyond the Numbers: Employment & Unemployment, 10(14). Retrieved on March 28, 2023, from https://www.bls.gov/opub/btn/volume-10/jolts-2020-state-estimates.htm.
8 Standard error estimates for fill rates, churn rates, and net employment were calculated using error propagation. The formulas used in deriving the standard errors for these estimates can be found in Taylor, J.R. (2022) “Propagation of Uncertainties,” in An introduction to error analysis: The study of uncertainties in physical measurements. New York: University Science Books, pp. 45–91.