NCES Blog

National Center for Education Statistics

Highlights of 2015–16 and 2016–17 School-Level Finance Data

NCES annually publishes comprehensive data on the finances of public elementary and secondary schools through the Common Core of Data (CCD). For many years, these data have been released at the state level through the National Public Education Financial Survey (NPEFS) and at the school district level through the Local Education Agency (School District) Finance Survey (F-33).

Policymakers, researchers, and the public have long voiced concerns about the equitable distribution of school funding within and across districts. School-level finance data provide reliable and unbiased measures that can be utilized to compare how resources are distributed among schools within districts.

Education spending data are now available for 15 states[1] at the school level through the School-Level Finance Survey (SLFS), which NCES has been conducting annually since 2014.[2] In November 2018, the Office of Management and Budget (OMB) approved changes to the SLFS wherein variables have been added to make the SLFS directly analogous to the F-33 Survey and to the Every Student Succeeds Act (ESSA) provisions on reporting expenditures per pupil at the school and district levels.

Below are some key findings from the recently released NCES report Highlights of School-Level Finance Data: Selected Findings From the School-Level Finance Survey (SLFS) School Years 2015–16 (FY 16) and 2016–17 (FY 17).

 

Eight of the 15 states participating in the SLFS are able to report school-level expenditure data requested by the survey for a high percentage of their schools.

The initial years of the SLFS have consistently demonstrated that most states can report detailed school‑level spending data for the vast majority of their schools. In school year (SY) 2016–17 (FY 2017), most states participating in the SLFS (8 out of 15) reported school-level finance data for at least 95 percent of their schools (figure 1). With the exception of New Jersey,[3] all states were able to report at least partial SLFS finance data for more than 78 percent of their schools, ranging from 79 percent of schools in Colorado to 99 percent of schools in Oklahoma. In addition, the percentage of students covered by SLFS reporting was more than 99 percent in 9 of the 15 participating states. 


Figure 1. Percentage of students covered and percentage of schools with fiscal data reported in the School-Level Finance Survey (SLFS), by participating state: FY 2017


 

The SLFS can be used to evaluate school-level expenditure data based on various descriptive school characteristics.

The SLFS allows data users to not only view comparable school-level spending data but also evaluate differences in school-level spending based on a variety of school characteristics. In the report, SY 2016–17 (FY 2017) SLFS data were evaluated by charter status and urbanicity. Key findings from this evaluation include the following:

  • Median teacher salaries[4] in charter schools were lower than median teacher salaries in noncharter schools in all 7 states that met the standards for reporting teacher salaries for both charter and noncharter schools (figure 2).
  • School expenditures were often higher in cities and suburbs than in towns and rural areas. Median teacher salaries, for example, were highest for schools in either cities or suburbs in 9 of the 10 states that met the standards for reporting teacher salaries in each of the urbanicities (city, suburb, town, and rural) (figure 3).  

Figure 2. Median teacher salary for operational public elementary and secondary schools, by school charter status and reporting state: FY 2017


Figure 3. Median teacher salary for operational public elementary and secondary schools, by school urbanicity and reporting state: FY 2017


Median technology‑related expenditures per pupil were also highest for schools in either cities or suburbs in 9 of the 11 states that met the standards for reporting technology-related expenditures in each of the urbanicities, with schools in cities reporting the highest median technology-related expenditures per pupil in 6 of those states.

 

The SLFS can be used to evaluate and compare school-level expenditure data by various poverty indicators.

The report also evaluates and compares school-level spending by school poverty indicators, such as Title I eligibility and school neighborhood poverty level. Key findings from this evaluation include the following:

  • In SY 2016–17 (FY 2017), median teacher salaries were slightly lower for Title I eligible schools than for non-Title I eligible schools in 7 of the 8 states where standards were met for reporting both Title I eligible and non-Title I eligible schools. However, median personnel salaries per pupil were slightly lower for Title I eligible schools than for non-Title I eligible schools in only 2 of the 8 states where reporting standards were met.    
  • Median personnel salaries per pupil for SY 2016–17 were higher for schools in high‑poverty neighborhoods than for schools in low-poverty neighborhoods in 7 of the 12 states where standards were met for reporting school personnel salaries.

 

To learn more about these and other key findings from the SY 2015–16 and 2016–17 SLFS data collections, read the full report. The corresponding data files for these collections will be released later this year.


[1] The following 15 states participated in the SY 2015–16 and 2016–17 SLFS: Alabama, Arkansas, Colorado, Florida, Georgia, Kentucky, Louisiana, Maine, Michigan, New Jersey, North Carolina, Ohio, Oklahoma, Rhode Island, and Wyoming.

[2] Spending refers to “current expenditures,” which are expenditures for the day-to-day operation of schools and school districts for public elementary/secondary education. For the SY 2015–16 and 2016–17 data collections referenced in this blog, the SLFS did not collect complete current expenditures; the current expenditures collected for those years included expenditures most typically accounted for at the school level, such as instructional staff salaries, student support services salaries, instructional staff support services salaries, school administration salaries, and supplies and purchased services. As of SY 2017–18, the SLFS was expanded to collect complete current expenditures.

[3] In New Jersey, detailed school-level finance reporting is required for only its “Abbott” districts, which comprised only 31 of the state’s 699 school districts in SY 2016–17.

[4] “Median teacher salaries” are defined as the median of the schools’ average teacher salary. A school’s average teacher salary is calculated as the teacher salary expenditures reported for the school divided by the number of full-time-equivalent (FTE) teachers at the school. Note that this calculation differs from calculating the median of salaries across all teachers at the school, as the SLFS does not collect or report salary data at the teacher level.

 

By Stephen Cornman, NCES

Accessing the Common Core of Data (CCD)

Every year, NCES releases nonfiscal data files from the Common Core of Data (CCD), the Department of Education’s (ED’s) primary longitudinal database on public elementary and secondary education in the United States. CCD data releases include directory data (location, status, and grades offered), student membership data (by grade, gender, and race/ethnicity), data on full-time equivalent staff and teachers, and data on the number of students eligible for the National School Lunch Program (NSLP)

This blog post, one in a series of posts about CCD data, focuses on how to access and use the data. For information on using NSLP data, read the blog post Understanding School Lunch Eligibility in the Common Core of Data

CCD Data Use

CCD data are used both internally by ED and externally by the public. For example, within ED, CCD data serve as the sample frame for the National Assessment of Educational Progress (NAEP) and are the mainstay of many tables in the Digest of Education Statistics and The Condition of Education. Outside of ED, CCD data are used by researchers, the general public (e.g., realtor sites, The Common Application, Great Schools), and teachers who need their school’s NCES school ID to apply for grants.

Data Structure and Availability

CCD data are available at the state, district, and school levels, using a nested structure: all schools are within a parent district and all districts are within a state. CCD does not include any student- or staff-level data.

Most CCD data elements are available for school year (SY) 1986‒87 to the present.    

Unique Identifiers Within CCD

NCES uses a three-part ID system for public schools and districts: state-based Federal Information Processing Standards (FIPS) codes, district codes, and school codes. Using these three parts, several IDs can be generated:

  • District IDs: 7-digit (FIPS + 5-digit District)
  • School IDs:
    • 12-digit (FIPS + District + School)
    • 7-digit (FIPS + School) (unique from SY 2016‒17 on)

NCES IDs are assigned to districts and schools indefinitely, making them useful for analyzing data over time. For example, for a longitudinal school-level analysis, a school’s 7-digit ID should be used, as it remains the same even if the school changes districts. These IDs can also be used to link CCD district and school data to other ED databases.

Accessing CCD Data

There are three ways to access CCD data: the CCD District and School Locators, the Elementary/Secondary Information System (ElSi), and the raw data files. Each approach has different benefits and limitations.

  • CCD District and School locators
    • Quick and easy to use
    • Many ways to search for districts and schools (e.g., district/school name, street address, county, state)
    • Provides the latest year of CCD data available for the selected district(s) or school(s)
    • Tips for optimal use:
      • If you are having difficulty finding a district or school, only enter a key word for the name (e.g., for PS 100 Glen Morris in New York City, only enter “Glen Morris” or “PS 100”)
      • Export search results to Excel (including all CCD locator fields)

  • Elementary/Secondary Information System (ElSi)
    • quickFacts and expressTables: view most-requested CCD data elements at multiple levels
    • tableGenerator: combine data across topic areas and years to create a single file
    • Create “tables” that act like databases and include all of the roughly 100,000 public schools or 20,000 districts
    • Export data to Excel or CSV
    • Tips for optimal use:
      • Save and edit queries using the navigation buttons at the top of the screen
      • popularTables provide links to frequently requested data

 

Interested in learning more about CCD or accessing CCD data at the state, district, or school level? Check out the CCD website and use the District and School locators, ElSi, or the raw data files to find the data you are looking for.

 

By Patrick Keaton, NCES

Building Bridges: Increasing the Power of the Civil Rights Data Collection (CRDC) Through Data Linking With an ID Crosswalk

On October 15, 2020, the U.S. Department of Education’s (ED) Office for Civil Rights (OCR) released the 2017–18 Civil Rights Data Collection (CRDC). The CRDC is a biennial survey that has been conducted by ED to collect data on key education and civil rights issues in our nation’s public schools since 1968. The CRDC provides data on student enrollment and educational programs and services, most of which are disaggregated by students’ race/ethnicity, sex, limited English proficiency designation, and disability status. The CRDC is an important aspect of the overall strategy of ED’s Office for Civil Rights (OCR) to administer and enforce civil rights statutes that apply to U.S. public schools. The information collected through the CRDC is also used by other ED offices as well as by policymakers and researchers outside of ED.  

As a standalone data collection, the CRDC provides a wealth of information. However, the analytic power and scope of the CRDC can be enhanced by linking it to other ED and government data collections, including the following:

A Crosswalk to Link CRDC Data to Other Data Collections

To facilitate joining CRDC data to these and other data collections, NCES developed an ID crosswalk. This crosswalk is necessary because there are instances when the CRDC school ID number (referred to as a combo key) does not match the NCES school ID number assigned in other data collections (see the “Mismatches Between ID Numbers” section below for reasons why this may occur). By linking the CRDC to other data collections, researchers can answer questions that CRDC data alone cannot, such as the following:



Mismatches Between ID Numbers

Mismatches between CRDC combo key numbers and NCES ID numbers may occur because of differences in how schools and districts are reported in the CRDC and other collections and because of differences in the timing of collections. Below are some examples.

  • Differences in how schools and school districts are reported in the CRDC and other data collections:
    • New York City Public Schools is reported as a single district in the CRDC but as multiple districts (with one supervisory union and 33 components of the supervisory union) in other data collections. Thus, the district will have one combo key in the CRDC but multiple ID numbers in other data collections.
    • Sometimes charter schools are reported differently in the CRDC compared with other data collections. For example, some charter schools in California are reported as independent (with each school serving as its own school district) in the CRDC but as a single combined school district in other data collections. Thus, each school will have its own combo key in the CRDC, but there will be one ID number for the combined district in other data collections.
    • There are differences between how a state or school district defines a school compared with how other data collections define a school.
  • Differences in the timing of the CRDC and other data collections:
    • There is a lag between when the CRDC survey universe is planned and when the data collection begins. During this time, a new school may open. Since the school has not yet been assigned an ID number, it is reported in the CRDC as a new school.


Interested in using the ID crosswalk to link CRDC data with other data collections and explore a research question of your own? Visit https://www.air.org/project/research-evaluation-support-civil-rights-data-collection-crdc to learn more and access the crosswalk. For more information about the CRDC, visit https://ocrdata.ed.gov/.

 

By Jennifer Sable, AIR, and Stephanie R. Miller, NCES

Understanding School Lunch Eligibility in the Common Core of Data

Every year in the Common Core of Data (CCD), NCES releases data on the number of students eligible for the National School Lunch Program (NSLP), a U.S. Department of Agriculture (USDA) meal program that provides nutritionally balanced low-cost or free meals to children during the school day. The program was established under the National School Lunch Act, signed into law by President Harry Truman in 1946, and currently serves nearly 30 million children.

This post highlights substantial changes to the NSLP and related changes in CCD reporting and provides guidance on how to use the NSLP data.

Free or Reduced-Price Lunch vs. Direct Certification

Historically, student eligibility for free or reduced-price lunch (FRPL) was determined through individual students submitting school meals application forms within school districts. In 1986, the USDA introduced a direct certification option to reduce participation barriers in the school meal program. Under direct certification, any child belonging to a household that participates in Supplemental Nutrition Assistance Program (SNAP), Temporary Assistance for Needy Families (TANF), Food Distribution Program on Indian Reservations (FDPIR), or (in some states) Medicaid—as well as children who are migrant, homeless, in foster care, or in Head Start—are categorically eligible to receive free meals at school.

The NSLP data included in CCD releases include school-level FRPL and direct certification eligibility counts for all public schools with students enrolled. These point-in-time counts are taken on or around October 1 of each school year and reported by the states based on the following guidance: 

  • FRPL-Eligible Students
    • Free lunch students: those eligible to participate in the Free Lunch Program (i.e., those with family incomes below 130 percent of the poverty level or who are directly certified)
    • Reduced-price lunch students: those eligible to participate in the Reduced-Price Lunch Program (i.e., those with family incomes between 130 and 185 percent of the poverty level)
    • Free and reduced-price lunch student: the total of free lunch students and reduced-price lunch students
  • Direct Certification
    • The number of students reported as categorically eligible to receive free meals to the USDA for the FNS 742. Students are categorically eligible to receive free meals if they belong to a household receiving the selected federal benefits noted above or are migrant, homeless, in foster care, or in Head Start.

The count of students eligible for free lunch includes students directly certified plus any students who qualified for free lunch by completing a school meals application. As such, the number of students reported as directly certified should always be less than or equal to the number of free lunch students.

Note that changes in SNAP (both legislated eligibility requirements and temporary changes such as national disasters) can have implications for reported NSLP eligibility as well.

The Healthy, Hunger-Free Kids Act of 2010

In 2010, the Healthy, Hunger-Free Kids Act (HHFKA) established national nutrition standards for food served and sold in schools and made changes to the NSLP to increase food access. These changes also impacted the NSLP data published through CCD:

  • While direct certification had been an option since 1986, HHFKA mandated that states directly certify NSLP eligibility for at least 95 percent of SNAP participants. With the mandated use of direct certification, several states stopped reporting FRPL eligibility entirely. 
  • HHFKA introduced the Community Eligibility Provision (CEP) to expand access to free meals to all students in low-income areas. Schools qualifying under CEP no longer count students who qualify for reduced-price lunch since all students are provided a free lunch. CEP schools may report all students as eligible for free lunch regardless of economic status, since all students are provided a free lunch.

Guidance for Data Users

The NSLP eligibility data published through CCD are often used by researchers as a proxy measure for the number of students living in poverty. However, there are limitations to the usefulness of these data that researchers should consider when using NSLP data.

The NSLP data published through CCD has changed over time. CCD published just FRPL counts through SY 2015–16. Starting in SY 2016–17, states can report FRPL and/or direct certification eligibility counts for each school, and CCD publishes both FRPL and direct certification, as reported by the states.[1]

When creating state and national estimates (including tables in the Digest of Education Statistics), NCES uses FRPL counts when they are available. If FRPL data are not available, direct certification data is used as a proxy. For this type of analysis, NCES includes all schools for which both student enrollment data and FRPL or direct certification were reported. States that only reported direct certification are footnoted. NCES recommends that data users be mindful of the reporting differences when analyzing or drawing conclusions with these data.

The NSLP data meet a variety of critical analysis needs to help policy makers, researchers, and the public target resources and answer policy questions. CCD is the only source of nationwide school-level NSLP data. Explore NSLP data as well as all of the other CCD data elements available either by using the CCD data query tool or by downloading data files directly.

 

By Beth Sinclair, AEM, and Chen-Su Chen, NCES

 


[1] In SY 2018–19, states reported FRPL counts for 95 percent of schools. Five states/jurisdictions reported solely the number of direct certification students (Delaware, the District of Columbia, Massachusetts, Tennessee, and American Samoa). The remaining states/jurisdictions were split: about half reported solely the number of FRPL students for each school and the other half reported both FRPL and direct certification for each school (or FRPL for some schools and direct certification for others).

Data Tools for College Professors and Students

Ever wonder what parts of the country produce the most English majors? Want to know which school districts have the most guidance counselors? The National Center for Education Statistics (NCES) has all the tools you need to dig into these and lots of other data!

Whether you’re a student embarking on a research project or a college professor looking for a large data set to use for an assignment, NCES has you covered. Below, check out the tools you can use to conduct searches, download datasets, and generate your own statistical tables and analyses.

 

Conduct Publication Searches

Two search tools help researchers identify potential data sources for their study and explore prior research conducted with NCES data. The Publications & Products Search Tool can be used to search for NCES publications and data products. The Bibliography Search Tool, which is updated continually, allows users to search for individual citations from journal articles that have been published using data from most surveys conducted by NCES.

Key reference publications include the Digest of Education Statistics, which is a comprehensive library of statistical tabulations, and The Condition of Education, which highlights up-to-date trends in education through statistical indicators.

 

Learn with Instructional Modules

The Distance Learning Dataset Training System (DLDT) is an interactive online tool that allows users to learn about NCES data across the education spectrum. DLDT’s computer-based training introduces users to many NCES datasets, explains their designs, and offers technical considerations to facilitate successful analyses. Please see the NCES blog Learning to Use the Data: Online Dataset Training Modules for more details about the DLDT tool.
 




Download and Access Raw Data Files

Users have several options for conducting statistical analyses and producing data tables. Many NCES surveys release public-use raw data files that professors and students can download and analyze using statistical software packages like SAS, STATA, and SPSS. Some data files and syntax files can also be downloaded using NCES data tools:

  • Education Data Analysis Tool (EDAT) and the Online Codebook allow users to download several survey datasets in various statistical software formats. Users can subset a dataset by selecting a survey, a population, and variables relevant to their analysis.
  • Many data files can be accessed directly from the Surveys & Programs page by clicking on the specific survey and then clicking on the “Data Products” link on the survey website.

 

Generate Analyses and Tables

NCES provides several online analysis tools that do not require a statistical software package:

  • DataLab is a tool for making tables and regressions that features more than 30 federal education datasets. It includes three powerful analytic tools:
    • QuickStats—for creating simple tables and charts.
    • PowerStats—for creating complex tables and logistic and linear regressions.
    • TrendStats—for creating complex tables spanning multiple data collection years. This tool also contains the Tables Library, which houses more than 5,000 published analysis tables by topic, publication, and source.



  • National Assessment of Educational Progress (NAEP) Data Explorer can be used to generate tables, charts, and maps of detailed results from national and state assessments. Users can identify the subject area, grade level, and years of interest and then select variables from the student, teacher, and school questionnaires for analysis.
  • International Data Explorer (IDE) is an interactive tool with data from international assessments and surveys, such as the Program for International Student Assessment (PISA), the Program for the International Assessment of Adult Competencies (PIAAC), and the Trends in International Mathematics and Science Study (TIMSS). The IDE can be used to explore student and adult performance on assessments, create a variety of data visualizations, and run statistical tests and regression analyses.
  • Elementary/Secondary Information System (ElSi) allows users to quickly view public and private school data and create custom tables and charts using data from the Common Core of Data (CCD) and Private School Universe Survey (PSS).
  • Integrated Postsecondary Education Data System (IPEDS) Use the Data provides researcher-focused access to IPEDS data and tools that contain comprehensive data on postsecondary institutions. Users can view video tutorials or use data through one of the many functions within the portal, including the following:
    • Data Trends—Provides trends over time for high-interest topics, including enrollment, graduation rates, and financial aid.
    • Look Up an Institution—Allows for quick access to an institution’s comprehensive profile. Shows data similar to College Navigator but contains additional IPEDS metrics.
    • Statistical Tables—Equips power users to quickly get data and statistics for specific measures, such as average graduation rates by state.