Focus on Productivity: Elementary and Secondary Schools
Labor Productivity for Elementary and Secondary Schools Services
On February 23, 2018, the Bureau of Labor Statistics (BLS) updated measures of productivity and costs for Elementary and secondary schools (NAICS 6111) through 2014. Data through 2012 were originally released in June 2016 with the publication of an article in the Monthly Labor Review (MLR).
Education: learning to measure it
Elementary and secondary schools are critical to establishing the foundations of labor skills development in every sector of the U.S. economy. Typically, young Americans spend the better part of 13 years attending public or private schools at the K-12 level. Along the way, they acquire a broad range of general and practical knowledge needed to succeed in college, vocational schools, or the working world.
Schools do more than just educate millions of people; they employ millions, too. In 2016, eight million U.S. employees – 5.6 percent of all national employment – worked in elementary or secondary schools. Among these are teachers, guidance counselors, administrators, buildings and grounds staff, and several other categories of essential personnel. Total national expenditures on elementary and secondary educational school services for the 2014–15 school year, at an estimated $689 billion, equaled 4.0 percent of GDP.
The importance of getting a return on these substantial investments in education (monetary and otherwise) is clear. Less clear, however, is the most conceptually appropriate way to measure the results from such investments. BLS’s productivity measures follow a growing body of research suggesting that, in assessing the labor efficiency of K-12 education, it is not only the number of students educated that counts, but also the quality of education they receive. As described in the 2016 MLR article, our output measure adjusts enrollment figures by attendance rates and then applies weights based on Long-Term Trend (LTT) scores from the National Assessment of Educational Progress (NAEP). Furthermore, our labor input measure for this industry accounts for a variety of school occupational categories to acknowledge the many ways that schools contribute to the educational success of children.
Interactive Chart Dashboards
(Excel 2013 or later)
To create your own tables and charts by industry and indicator.
Studying the public school and private school trends
Chart 1 shows that from 1992 to 2009, both the output and labor input of public schools grew steadily, slowing down after 2001. Because labor input grew faster, labor productivity fell during this period. Since the economic recession ended in 2009, labor productivity growth has been slightly positive as steady output growth was met with a slight decline in labor input.
Chart 2 shows a different pattern for private schools. Labor input rose much faster than output for most of the time frame, resulting in a steeper decline of labor productivity through 2007. The labor input trend then reversed, allowing labor productivity to bottom out in 2009 and slowly recover through 2014.
The final examination: productivity of all schools
To construct indexes for all schools, BLS first builds the output and labor input indexes, separately, for public and private schools. The respective output and labor input indexes are then aggregated together, for all schools, using expenditure share weights. (See the BLS Handbook of Methods for more information on the aggregation methodology used by the BLS Productivity Program.) Lastly, we take a ratio of the output and labor indexes of all schools to yield the labor productivity index.
Chart 3 compares the change in the relative shares from 1992 to 2014 of expenditures, employment, and enrollment for public and private schools.
It is apparent in both the beginning and end years of our time series that the private schools’ share of the unadjusted total enrollment and employment are both larger than their share of total school expenditures. (Student enrollments are the primary component of the output measures, while total employment is closely related to the labor input measure.) The private schools’ share of all school expenditures decreased slightly during the 1992-2014 time period.
It is evident from Chart 4 that, despite the considerable variation between public school and private school trends in labor productivity and related variables, the overall productivity trend largely tracks public schools.
Recall from Chart 3 that the total expenditure shares, which are used to aggregate the output and labor input indexes, are dominated by public schools throughout our time series. As a result, the steeper decline in private school productivity has not greatly affected the overall industry trend. Nonetheless, it is possible to see a divergence beginning around 2003 when the effect of lower productivity in private schools brings down the overall index.
Frequently Asked Questions
Q: How is this industry defined?
A: The elementary and secondary schools industry includes both public and private schools providing educational and related services that constitute a basic preparatory education, typically from kindergarten through the 12th grade. Data for prekindergarten programs affiliated with K-12 schools are included in the output and labor input measures.
Q: What factors influence the output measure?
A: One factor that strongly affects the output measure is school enrollment. Variations in factors influencing student educational outcomes, such as teacher quality, student–teacher ratios, and curriculum quality, can also play a role in determining the output of educational services. In the future, BLS hopes to provide additional information on changes in these underlying factors and their quantitative impact on educational services. This new measure is a first step toward understanding the relationship between production of educational services and the labor inputs used in this production.
Q: How does the output measure account for quality of education?
A: The BLS output measure for elementary and secondary schools adopts an approach that relies on student performance on the NAEP Long-Term Trend (LTT) tests for capturing the effects of quality change. First, attendance-adjusted series on numbers of students in public and private schools are used as proxies for the volume of output. These series are then weighted according to the LTT mathematics and reading student test scores of public and private schools, which are used as output quality adjusters. According to the NCES, the LTT assessments are designed “to measure student progress over time … [by using] … substantially the same assessments decade after decade.”
Q: Where does BLS get raw data on school staff and students?
A: BLS obtains the majority of its data from the Digest of Educational Statistics which is published annually by the National Center for Education Statistics (NCES). Further data are obtained from BLS’s Occupational Employment Statistics program and from the National Association of Independent Schools (NAIS).
Q: How does BLS measure labor inputs for this industry?
A: BLS normally measures the labor input component of productivity in an industry as the total number of hours worked. However, data at this level of detail are not available for elementary and secondary schools. Instead, BLS measures labor inputs using data on the number of Full Time Equivalent (FTE) employees in various occupational categories, separately, for both public schools and private schools. These categories include not only teachers but also other school employees, such as librarians, guidance counselors, administrators, and student support staff. Changes in employment for occupational categories are weighted by expenditures. Then, BLS further aggregates the labor input indexes for public schools and private schools with the use of total school expenditure share weights. More information on the data sources and occupational categories is available in the MLR article.
Industries at a Glance: Educational Services NAICS 61
Overview of BLS Productivity Statistics
Last Modified Date: February 23, 2018