NCES Blog

The Digest of Education Statistics recently debuted 13 new tables on K–12 employment and wages from a data source that is new to the Digest—the Occupational Employment Wage Statistics (OEWS) program of the Bureau of Labor Statistics (BLS). NCES’s Annual Reports and Information Staff conducted an extensive review of existing and emerging data sources and found that BLS’s OEWS program provides high-quality, detailed, and timely data that are suitable to inform policymaking in education and workforce development.¹ In this blog post, we share why we added this new data source, how we evaluated and prepared these data, and our future plans to expand on these efforts.

Need for Education Workforce Data

NCES recognized that education stakeholders need more granular and timely data on the condition of the education workforce to inform decisionmaking. In the wake of the coronavirus pandemic, school districts are looking to address critical staffing needs. According to NCES’s School Pulse Panel, entering the 2023–24 school year (SY), just under half of U.S. public schools reported feeling understaffed and had a need for special education teachers, transportation staff, and mental health professionals.

Since staffing needs and labor markets vary from district to district and state to state, it is important that we create national- and state-level tabulations for specific occupations, including those of special interest since the pandemic, like bus drivers, social workers, and special education teachers. Similarly, we want to be able to provide annual data updates so stakeholders can make the most up-to-date decisions possible.

Annual Digest table updates, coupled with detailed occupational and state-level data, will provide relevant and timely information on employment and wage trends that will be valuable in current and future efforts to address teacher and staff retention and recruitment. See below for a list of the new Digest tables.

• National-level employment and annual wages

• Selected teaching occupations (211.70)
• Selected noninstructional occupations (213.70)

• State-level employment and annual wages

• Preschool teachers (211.70a)
• Kindergarten teachers (211.70b)
• Elementary school teachers (211.70c)
• Middle school teachers (211.70d)
• Secondary school teachers (211.70e)
• Kindergarten and elementary special education teachers (211.70f)
• Middle school special education teachers (211.70g)
• Secondary school special education teachers (211.70h)
• Substitute teachers (211.70i)
• Teaching assistants (211.70j)
• All occupations in the Elementary and Secondary Education industry (213.75)

Strengths of OEWS

OEWS and the Digest tables are aligned with the Federal Committee on Statistical Methodology’s Data Quality Framework, specifically the principles of objectivity (standardization), utility (granularity and timeliness), and integrity (data quality).

Standardization

OEWS produces employment and wage estimates using standardized industry and occupational classifications. Using the North American Industry Classification System, establishments are grouped into categories—called industries—based on their primary business activities. Like industries, occupations are organized into groups or categories based on common job duties (using the Standard Occupational Classification). Occupations that are common to K–12 schools can also be found in other industries, and the OEWS provides both cross-industry estimates and industry-specific estimates for just Elementary and Secondary Education industry. To provide the most relevant and comparable data for education stakeholders, NCES chose to focus on distinct occupational estimates for the Elementary and Secondary Education industry, since all establishments (e.g., school boards, school districts) provide the same services: instruction or coursework for basic preparatory education (typically K–12).²     

Another advantage of the OEWS data is the ability to examine specific detailed occupations, like elementary school teachers, secondary school teachers, and education administrators. Digest tables include estimates for specific instructional and noninstructional occupations, which allows users to make comparisons among teachers and staff with similar job responsibilities, providing opportunities for more targeted decisionmaking.

Granularity

In addition to data on detailed occupations, OEWS data provide data at national and state and levels, allowing for comparisons across geographies. National-level Digest tables include estimates for public and private education employers.³ Publicly funded charter schools run by private establishments are included in private ownership estimates, as they can be managed by parents, community groups, or private organizations. Public ownership is limited to establishments that are run by federal, state, or local governments. State-level Digest tables provide more localized information covering labor markets for the 50 states, the District of Columbia, Puerto Rico, Guam, and the U.S. Virgin Islands.
   

Timeliness and Data Quality

OEWS data are updated annually from a sample of about 1.1 million establishments’ data collected over a 3-year period. The OEWS sample is drawn from an administrative list of public and private companies and organizations that is estimated to cover about 95 percent of jobs.⁴ When employers respond to OEWS, they report from payroll data that are maintained as a part of regular business operations and typically do not require any additional collections or calculations. Payroll data reflect wages paid by employers for a job, which has a commonly accepted definition across employers or industries. This allows for more accurate comparisons of annual wages for a particular job. In contrast, when wages are self-reported by a respondent in person-level or household surveys, the reported data may be difficult to accurately code to a specific industry or detailed occupation, and there is greater chance of recall error by the respondent. Additionally, OEWS provides specialized respondent instructions for elementary and secondary schools and postsecondary institutions that accommodate the uniqueness of what educators do and how they are paid. These instructions enable precise coding of the occupations commonly found in these industries and a more precise and consistent reporting of wages of workers with a variety of schedules (e.g., school year vs. annual, part time vs. full time).   

OEWS uses strict quality control and confidentiality measures and strong sampling and estimation methodologies.⁵ BLS also partners with state workforce agencies to facilitate the collection, coding, and quality review of OEWS data. States’ highly trained staff contribute local knowledge, establish strong respondent relationships, and provide detailed coding expertise to further ensure the quality of the data. 

After assessing the strengths of the OEWS data, the Digest team focused on the comparability of the data over time to ensure that the data would be best suited for stakeholder needs and have the most utility. First, we checked for changes to the industrial and occupational classifications. Although there were no industrial changes, the occupational classifications of some staff occupations—like librarians, school bus drivers, and school psychologists—did change. In those cases, we only included comparable estimates in the tables.

Second, all new Digest tables include nonoverlapping data years to account for the 3-year collection period. While users cannot compare wages in 2020 with 2021 and 2022, they can explore data from 2016, 2019, and 2022. Third, the Digest tables present estimates for earlier data years to ensure the same estimation method was used to produce estimates over time.⁶ Finally, we did not identify any geographical, scope, reference period, or wage estimation methodology changes that would impact the information presented in tables. These checks ensured we presented the most reliable and accurate data comparisons.

Next Steps  

The use of OEWS data in the Digest is a first step in harnessing the strength of BLS data to provide more relevant and timely data, leading to a more comprehensive understanding of the education workforce. NCES is investigating ways we can partner with BLS to further expand these granular and timely economic data, meeting a National Academies of Science, Engineering, and Medicine recommendation to collaborate with other federal agencies and incorporate data from new sources to provide policy-relevant information. We plan to explore the relationship between BLS data and NCES data, such as the Common Core of Data, and increase opportunities for more detailed workforce analyses.

NCES is committed to exploring new data sources that can fill important knowledge gaps and expand the breadth of quality information available to education stakeholders. As we integrate new data sources and develop new tabulations, we will be transparent about our evaluation processes and the advantages and limitations of sources. We will provide specific examples of how information can be used to support evidence-based policymaking. Additionally, NCES will continue to investigate new data sources that inform economic issues related to education. For example, we plan to explore Post-Secondary Employment Outcomes to better understand education-to-employment pathways. We are investigating sources for building and land use data to assess the condition and utilization of school facilities. We are also looking for opportunities to integrate diverse data sources to expand to new areas of the education landscape and to support timelier and more locally informed decisionmaking.
 

How will you use the new Digest tables? Do you have suggestions for new data sources? Let us know at [email protected].

As the primary statistical agency of the U.S. Department of Education, the National Center for Education Statistics (NCES) is mandated to report complete statistics on the condition of American education. While the condition of an education system is often assessed through indicators of achievement and attainment, NCES is also mandated to report on the conditions of the education workplace.

As such, NCES has reported timely information from schools. For example, this past December, NCES released data that indicated that public schools have experienced difficulty filling positions throughout the COVID-19 pandemic.¹ In order to understand the broader labor situation, NCES is utilizing the Job Openings and Labor Turnover Survey to describe the tightness of the job market.

JOLTS Design

The Job Openings and Labor Turnover Survey (JOLTS), conducted by the U.S. Bureau of Labor Statistics (BLS), provides monthly estimates of job openings, hires, and total separations. The purpose of JOLTS data is to serve as demand-side indicators of labor shortages at the national level.²

The JOLTS program reports labor demand and turnover estimates by industry, including education.³ As such, this analysis focuses on the public state and local education industry (“state and local government education” as referred to by JOLTS),⁴ which includes all persons employed by public elementary and secondary school systems and postsecondary institutions.

The JOLTS program does not produce estimates by Standard Occupational Classification.⁵ When reviewing these findings, please note occupations⁶ within the public state and local education industry vary⁷ (e.g., teachers and instructional aides, administrators, cafeteria workers, transportation workers). Furthermore, as the JOLTS data are tabulated at the industry level, the estimates are inclusive of the elementary, secondary, and postsecondary education levels.

Analysis

In this blog post, we present selected estimates on the number and rate of job openings, hires, and total separations (quits, layoffs and discharges, and other separations). The job openings rate is computed by dividing the number of job openings by the sum of employment and job openings. All other metric rates (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 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 separations.⁸

Table 1. Number of job openings, hires, and separations and net change in employment in public state and local education, in thousands: January 2020 through January 2023

*Significantly different from January 2023 (p < .05).
¹ Net employment changes are calculated by taking the difference between the number of hires and the number of separations. When the number of hires exceeds the number of separations, employment rises—even if the number of hires is steady or declining. Conversely, when the number of hires is less than the number of separations, employment declines—even if the number of hires is steady or rising.
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), 2020–2023, based on data downloaded April 5, 2023, from https://data.bls.gov/cgi-bin/dsrv?jt.

[2] U.S. Bureau of Labor Statistics. Job Openings and Labor Turnover Survey. Retrieved March 28, 2023, from https://www.bls.gov/jlt/jltover.htm.

[3] For more information about these estimates, see https://www.bls.gov/news.release/jolts.tn.htm.

[4] JOLTS refers to this industry as state and local government education, which is designated as ID 92.

[5] For more information on the reliability of JOLTS estimates, see https://www.bls.gov/jlt/jltreliability.htm.

[6] 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, see https://www.census.gov/topics/employment/industry-occupation/about/faq.html.

[7] 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. (From email communication with JOLTS staff, April 7, 2023.)

[8] 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 March 28, 2023, from https://www.bls.gov/opub/btn/volume-10/jolts-2020-state-estimates.htm.

The Job Openings and Labor Turnover Survey (JOLTS),¹ conducted by the U.S. Bureau of Labor Statistics (BLS), provides monthly estimates of job openings, hires, and total separations (quits, layoffs and discharges, and other separations) for major industry sectors, including education. BLS JOLTS data and other survey data can be used to track the recovery of the labor market since the spring of 2020, when the coronavirus pandemic resulted in job losses on a scale not seen since the Great Depression.²

This analysis is the first in a of series of analyses of the public state and local education industry³ during the 2021–22 school year. This industry includes all persons employed by public elementary and secondary school systems and postsecondary institutions, including a variety of occupations, such as teachers and instructional aides, administrators and other professional staff, support staff, maintenance personnel, cafeteria workers, and transportation workers.⁴ The JOLTS data are tabulated at this sector level and do not permit separate detailed analyses at the elementary and secondary level or at the postsecondary level. To put the scope of this group in context, 48 percent of the staff employed by public elementary and secondary school systems were teachers, and 37 percent of full-time-equivalent (FTE) postsecondary staff within public degree-granting institutions were instructional faculty in 2019.⁵

This snapshot is focused on the December 2021 reporting period. To provide context for this period, estimates will be compared with the previous month’s estimates, as well as with December 2019 (before the pandemic) and December 2020. Subsequent analysis will review the cumulative change from July 2021 through June 2022.

Overview of December 2021 Estimates

The number of job openings in public state and local education was 320,000 on the last business day of December 2021, which was higher than in December 2019 or December 2020 (table 1). In percentage terms, 2.9 percent of jobs had openings in December 2021, which was higher than 2.0 percent in December 2019 and 1.9 percent in December 2020. This suggests a greater need for public state and local education employees in December 2021 than in December 2019 or December 2020. Additionally, the number of separations⁶ (126,000) in December 2021 exceeded the total number of hires (91,000), indicating a net decrease in the number of public state and local education employees from the number in the month before. The number of job openings at the end of December 2021 (320,000) was 3.5 times larger than the number of staff actually hired that month (91,000). This December 2021 ratio of openings to hires was higher than the ratio in December 2020 (2.9) and the ratio in December 2019 (2.6).

Hiring in the education sector happens on a cyclical basis with the academic calendar, meaning that patterns will differ between months.⁷ November 2021 data are also provided in table 1 to provide a sense of the month-to-month change in employment data. In November 2021, the number of job openings outpaced the number of hires by a margin of 167,000 positions, representing a ratio of job openings to hires of 2.3.