In the 2024-25 school year, New York spent around ****** U.S. dollars per pupil on public elementary and secondary schools - the most out of any state. Vermont, the District of Columbia, Massachusetts, and New Jersey rounded out the top five states for elementary and secondary school expenditure per pupil.

This graph shows the average expenditure per pupil in U.S. public elementary and secondary schools in 2017. An average of 16,537 U.S. dollars was spent on each pupil in public schools in Wyoming in 2017.

An average of 15,362 U.S. dollars were spent on each pupil in public elementary and secondary schools in the United States in the academic year of 2021. This is an increase from 1980, when 2,272 U.S. dollars were spent per pupil.

This dataset contains school-level expenditures reported by major functional spending category starting with fiscal year 2019. It also includes school-level enrollment, demographic, and performance indicators as well as teacher salary and staffing data.

The dataset shows school-level per pupil expenditures by major functional expenditure categories and funding sources, including state and local funds (general fund and state grants) and federal funds.

School districts only report instructional expenditures by school. This report attributes other costs to each school on a per pupil basis to show a full resource picture. The three cost centers are:

1. Non-instructional per pupil spending reported at the school district level;
2. Instructional per pupil spending reported at the district level; and
3. Instructional per pupil spending reported at the school level

Economically Disadvantaged was used 2015-2021. Low Income was used prior to 2015, and a different version of Low Income has been used since 2022. Please see the DESE Researcher's Guide for more information.

This dataset is one of three containing the same data that is also published in the School Finance Dashboard: District Expenditures by Spending Category District Expenditures by Function Code School Expenditures by Spending Category

List of Indicators by Category

Student Enrollment

• In-District FTE Pupils
• Out-of-District FTE Pupils
• Total FTE Pupils

Student Demographics

• Student Headcount
• Low-Income % Headcount
• English Learner % Headcount
• Students with Disabilities % Headcount

Teacher Salaries

• Teacher FTE
• Teachers per 100 FTE Students
• Average Teacher Salary

Other Staff

• Instructional Coach FTE
• Instructional Support FTE
• Special Education Instructional Support FTE
• Paraprofessional FTE

MCAS Performance

• ELA Grades 3-8 % Meets Exceeds
• Math Grades 3-8 % Meets Exceeds
• ELA Grade 10 % Meets Exceeds
• Math Grade 10 % Meets Exceeds

District-Level FTE Pupils

District-Level State and Local Non-Instructional Expenditures Per Pupil

• Administration
• Benefits and Fixed Costs
• Operations and Maintenance
• Pupil Services

District-Level Federal Non-Instructional Expenditures Per Pupil

• Administration
• Benefits and Fixed Costs
• Operations and Maintenance
• Pupil Services

Sub-total A

District-Level State and Local Instructional Expenditures Per Pupil

• Guidance and Psychological Services
• Instructional Leaders
• Instructional Materials
• Other Teaching Services
• Professional Development
• Teachers

District-Level Federal Instructional Expenditures Per Pupil

• Guidance and Psychological Services
• Instructional Leaders
• Instructional Materials
• Other Teaching Services
• Professional Development
• Teachers

Sub-total B

School-Level State and Local Instructional Expenditures Per Pupil

• Guidance and Psychological Services
• Instructional Leaders
• Instructional Materials
• Other Teaching Services
• Professional Development
• Teachers

School-Level Federal Instructional Expenditures Per Pupil

• Guidance and Psychological Services
• Instructional Leaders
• Instructional Materials
• Other Teaching Services
• Professional Development
• Teachers

Sub-total C

Total A+B+C

During the academic year of 2021, around 18,614 constant 2022-23 U.S. dollars were spent on each pupil in public elementary and secondary schools in the United States. This is an increase from 1990, when 12,206 constant 2022-23 U.S. dollars were spent per pupil.

Out of the OECD countries, Luxembourg was the country that spent the most on educational institutions per full-time student in 2020. On average, 23,000 U.S dollars were spent on primary education, nearly 27,000 U.S dollars on secondary education, and around 53,000 U.S dollars on tertiary education. The United States followed behind, with Norway in third. Meanwhile, the lowest spending was in Mexico.

This map displays public school funding adequacy gap across the United States by county, state, and national levels, using the County Health Rankings 2022 layer hosted in the Living Atlas. School funding adequacy is defined as "the average gap in dollars between actual and required spending per pupil among public school districts. Required spending is an estimate of dollars needed to achieve US average test scores in each school district".School funding plays an important role in educational outcomes, and their distribution geographically by race/ethnicity. Research has shown that schools and districts with more funding are better able to provide higher-quality and deeper educational opportunities to students. Explore this map to see what the school funding adequacy gap is in your geography.The County Health Rankings, a collaboration between the Robert Wood Johnson Foundation and the University of Wisconsin Population Health Institute, measure the health of nearly all counties in the nation and rank them within states. This feature layer contains 2022 County Health Rankings data for nation, state, and county levels. The Rankings are compiled using county-level measures from a variety of national and state data sources. According to the County Health Rankings & Roadmaps site "By ranking the health of nearly every county in the nation, the County Health Rankings help communities understand what influences how healthy residents are and how long they will live. These comparisons among counties provide context and demonstrate that where you live, and many other factors including race/ethnicity, can deeply impact your ability to live a healthy life. The Rankings not only provide this snapshot of your county’s health, but also are used to drive conversations and action to address the health challenges and gaps highlighted in these findings."Web Map originally compiled by Summers Cleary

In 2018, the national average for spending on elementary and secondary education was 3.1 percent of the Gross Domestic Product (GDP). Vermont spent the most out of any state on elementary and secondary education, at 5.38 percent of its GDP.

description: The National Public Education Financial Survey, 2012-13 (NPEFS 2012-13), is a study that is part of the Common Core of Data's National Public Education Financial Survey program; program data is available since 1987 at https://nces.ed.gov/ccd/stfis.asp. CCD-NPEFS 2012-13 [https://nces.ed.gov/ccd/stfis.asp] is a cross-sectional survey that gathers data on the financing of education. NPEFS data are used in calculating states Title I grants. The study was conducted using responding agencies' existing administrative records. The universe of state education agencies was sampled. The study's response rate is TBD. Key statistics produced from CCD-NPEFS 2012-13 will collect data on attendance, revenue, and expenditure data from which NCES determines a State s 'average per-pupil expenditure' (SPPE) for elementary and secondary education.; abstract: The National Public Education Financial Survey, 2012-13 (NPEFS 2012-13), is a study that is part of the Common Core of Data's National Public Education Financial Survey program; program data is available since 1987 at https://nces.ed.gov/ccd/stfis.asp. CCD-NPEFS 2012-13 [https://nces.ed.gov/ccd/stfis.asp] is a cross-sectional survey that gathers data on the financing of education. NPEFS data are used in calculating states Title I grants. The study was conducted using responding agencies' existing administrative records. The universe of state education agencies was sampled. The study's response rate is TBD. Key statistics produced from CCD-NPEFS 2012-13 will collect data on attendance, revenue, and expenditure data from which NCES determines a State s 'average per-pupil expenditure' (SPPE) for elementary and secondary education.

The National Public Education Financial Survey, 2011-12 (NPEFS 2011-12), is a study that is part of the Common Core of Data's National Public Education Financial Survey program; program data is available since 1987 at https://nces.ed.gov/ccd/stfis.asp. CCD-NPEFS 2011-12 [https://nces.ed.gov/ccd/stfis.asp] is a cross-sectional survey that gathers data on the financing of education. NPEFS data are used in calculating states� Title I grants. The study was conducted using responding agencies' existing administrative records. The universe of state education agencies was sampled. The study's response rate has not been calculated as of May 2013. Key statistics produced from CCD-NPEFS 2011-12 will collect data on attendance, revenue, and expenditure data from which NCES determines a State�s 'average per-pupil expenditure' (SPPE) for elementary and secondary education.

Abstract This article aims to estimate the impact of lower tax revenues on the funding of basic education, in the context of the economic impact of the COVID-19 pandemic. Three hypothetical scenarios of lowering tax revenues are estimated and analyzed, along with their effects on the investment in education in the states and municipalities, per-pupil and overall, using a methodology that combines data on tax revenues, mandatory allocation in education, and enrollment numbers. In the most optimistic scenario, the reduction of 7% in the net tax revenues would lead to a decrease in investment in basic education of more than R$ 16.6 billion. The monthly per-pupil expenditure, which in 2018 was R$ 460 on average, could drop between 4.1% and 26.9% depending on which scenario is considered. This probable reduction in revenues requires urgent measures to attenuate the deepening of educational inequalities, converging to the transference of federal funds to sub-national governments. Finally, we highlight the economic virtue of investing in education, when considering the capillarity of education, and its character of intensive investment in personnel.

In 2023, the average education spending by pupils or students in France had increased since the eighties. In 1980, the French government spent approximately ***** euros per pupil/student, whereas the average amount of education expenditure per pupil/student was around ****** euros in 2023.

Graph and download economic data for Expenditures: Total Average Annual Expenditures by Composition of Consumer Unit: One Parent, at Least One Child Under 18 (CXUTOTALEXPLB0609M) from 1984 to 2023 about parent, consumer unit, average, expenditures, child, and USA.

In 2021/22, education spending per pupil at schools in England was highest in Inner London, with approximately ***** British pounds spent per pupil in this area. By contrast, pupils in the East of England had an expenditure per head of 6,049 pounds, which was the lowest in this academic year.

Important Note: This item is in mature support as of June 2023 and will be retired in December 2025. This map shows the average amount spent on child care per household in the U.S. in 2022 in a multiscale map (by country, state, county, ZIP Code, tract, and block group).The pop-up is configured to include the following information for each geography level:Average annual amount spent per household on child careAverage annual amount spent per household on different child care servicesPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

In 2024, parents expected to spend an average of just under *** U.S. dollars on back-to-school supplies per child, which is a very slight decrease compared to the previous year.

In 2021, Luxembourg was the OECD country that spent the highest amount on higher education per student, reaching roughly 35,000 U.S. dollars. This was even though it was the country that spent the lowest amount in terms of share of gross domestic product. The United States followed behind, with the United Kingdom in third. On the other hand, Mexico was the OECD country in which the lowest amount was spent per full-time student in higher education.

Abstract (en): This data collection provides the second wave of data in a longitudinal, multi-cohort study of American youth conducted by the National Opinion Research Center (NORC) on behalf of the National Center for Education Statistics. The first wave of data was collected in 1980 (ICPSR 7896) and the third wave was collected in 1984 (ICPSR 8443). Student identification numbers included in each record permit data from these surveys to be merged with other High School and Beyond files. The base-year (1980) study incorporated student data from both cohorts into one file. Due to the more complex design of the First Follow-Up and a resulting increase in the volume of available data, separate files have been created for the two cohorts. The sophomore cohort portion of this collection replicates nearly all of the types of data gathered in the base-year study (ICPSR 7896), including students' behavior and experiences in the secondary school setting, outside employment, educational and occupational aspirations and expectations, personal and family background, and personal attitudes and beliefs. Also, the same cognitive test was administered in the base-year and follow-up surveys. The senior cohort portion, in contrast, emphasizes postsecondary education and work experiences. Education data include the amount and type of school completed, school financing, aspirations, and non-school training. Information is also provided on labor force participation and aspirations, military service, and financial status. The senior cohort did not take the cognitive test for the follow-up survey. Both cohorts provide demographic data such as age, race, sex, and ethnic background. The Transcripts Survey provides information on individual students such as the type of high school program, the student's grade point average, attendance, class rank and size, and participation in special education programs, plus course-oriented data such as the year a course was taken, the type of course, credit earned, and grades received. The Offerings and Enrollments Survey file contains data on each school in the sample and include variables such as size and type of institution, type of schedule used, ethnic composition of the faculty and student body, busing, types of programs and specific courses offered, school facilities, number of handicapped students, and school staffing. In addition, information is provided on academic and disciplinary policies, and perceived problems in the school. The Local Labor Market Indicators file contains economic and labor market data for the geographical area of each school in the sample, given both by county and by Standard Metropolitan Statistical Area. The School Questionnaire file incorporates data elements from both the Base-Year School Questionnaire and the First Follow-up School Questionnaire, along with other information from sampling files, into a single record for each school. Topics include institutional characteristics such as total enrollment, average daily attendance rates, dropout rates, remedial programs, provisions for handicapped and disadvantaged students, participation in federal programs, teacher retention and absenteeism, per-pupil expenditures, school rules and policies, and ownership and funding of nonpublic schools. The universe for this collection consists of all persons in the United States who were high school sophomores or seniors in 1980. The base-year High School and Beyond Survey (ICPSR 7896) used a stratified, disproportionate probability sample of 1,122 schools selected from a sampling frame of 24,725 high schools. Within each school, 36 seniors and 36 sophomores were randomly chosen. For the First Follow-Up, the National Opinion Research Center attempted to survey all 1980 sophomores and a subsample of 1980 seniors who participated in the base-year survey. Supplementary questionnaires were utilized for those 1980 sophomores who were not currently attending any school, had transferred to other schools, or had graduated early. The Transcripts Survey includes every secondary-school course taken by a sub-sample of the sophomore cohort. The Course Offerings and Enrollments Survey contains data from schools that were selected as first-stage sample units (clusters) for the sampling of students in the base-year survey, and in which sophomore High School and Beyond students were actively enrolled during the 1981-1982 academic year. For the Local Labor Market Indicators file, economic variables were...

This statistic shows the average state and local higher education funding per full-time equivalent (FTE) student in the United States for the 2015/2016 academic year, by state. In the academic year 2015/2016, with ****** U.S. dollars per FTE student, Wyoming had the highest average state and local funding for higher education in the United States.

Abstract

Urban education is emerging as a significant topic of discussion in Tanzania and other Sub-Saharan African (SSA) countries, particularly focusing on the challenges faced by the population residing in impoverished urban areas. Learners from low-income households in urban settings encounter more difficulties in their educational journey compared to their more privileged counterparts. Tanzania, like many SSA nations, is undergoing substantial urbanization, marked by a notable rise in rural-to-urban migration, projected to reach approximately 55% of the country’s population by 2050. Understanding the current state of urban education is crucial for developing plans to address the escalating demands of urban education in the future. The study aimed to address these issues through the following research questions: 1. What are the schooling patterns among children living in urban poor households in Tanzania – including those with special needs? 2. How do urban poor communities perceive and understand education as a right in the context of urbanization in Tanzania? and, 3. What available education opportunities exist for children with special needs and living in poor urban households? In collaboration with HakiElimu and technical support from the National Bureau of Statistics, APHRC conducted a cross-sectional concurrent mixedmethods study. Quantitative data were gathered from 1,200 randomly selected low-income households in Dar es Salaam and Dodoma, along with input from 98 educational institutional heads from schools enrolling learners from the sampled households. Qualitative data were obtained through focus group discussions with caregivers/parents, in-depth interviews, and key informant interviews involving opinion leaders and policymakers. The study received ethical and administrative approvals from relevant authorities. Data analysis focused on 2,150 children aged 5-17, reflecting the basic education schooling age in Tanzania. A wealth score, derived from household belongings, was categorized into three equal tertiles for analysis purposes. The key results highlights have been presented below and thereafter a set of key study recommendations.

Schooling patterns: The findings indicate that 98.1% of children have attended school, with a slightly higher percentage among girls. Among learners with special needs (2.3% of the total), only 10% have received schooling, revealing an access gap for these vulnerable children. Six out of ten (60%) schools have provisions for learners with special needs, while those without reported inadequate facilities. In the academic year 2022, the majority of learners in pre-primary, primary, and ordinary level secondary education were enrolled in government schools (79.9%, 87.3%, and 90.6%, respectively). This underscores significant government control over enrollment spaces for learners from low-income urban households. The primary factor influencing school choice was the cost, suggesting the success of Tanzania’s free primary and secondary education initiatives. However, among the surveyed schools, the pupil-teacher ratio exceeded the government’s recommended number (40) across all levels. Additionally, the average class size surpassed 100 learners per class in primary school signaling quality issues.

Perceptions of Right to Education The right to education is categorized into three sub-themes: policy and strategies, law enforcement, and the school feeding program. 1. Policy and Strategies: Stakeholders acknowledged the state’s obligation to protect and promote the RTE. Examples cited included the Tanzania Education and Training Policy of 2014 (2023 edition) which cites the successes in the provision of the fee-free primary and secondary education, illustrating the government’s efforts to ensure universal access to education. 2. Law Enforcement: Local government authorities (LGAs) actively encourage parents to send their children to school. Those who fail to comply are presented to legal enforcement agencies, emphasizing the commitment to ensuring children’s attendance. However, implementation varies from one LGA to the other. 3. School Feeding Program (SFP): The government’s dedication to protecting the RTE is evident through the implementation of school feeding programs (SFPs).

Geographic coverage

Urban informal settlements of Tanzania, specifically in Dar es Salaam and Dodoma

Analysis unit

Households: The study analyzes household characteristics, such as size, head of household information, and wealth tertiles. Individuals (Children): The study focuses on children aged 3-19, specifically looking at their schooling patterns, participation, and characteristics. Schools: The study includes a school survey, analyzing school facilities, teacher qualifications, pupil-teacher ratios, and other school-level factors. Community: The study explores the perceptions and roles of community leaders and the community in relation to the right to education.

Universe

The survey covered households with school going children aged 3 to 19 years in selceted urban informal settlements in Dar esr Salaam and Dodoma

Sampling procedure

A sample of 1,200 households and 2,593 children aged 3 to 19 years was randomly selected through proportional allocation by region, ward, street, household head sex and age category.

The initial stage involved the listing of eligible households in the selected informal settlements. The initial criteria used was to ensure the household had at least one child who was aged 3-19 years. The listing exercise adopted a systematic approach: Starting from the furthest point of the enumeration areas, research assistants identified and listed the first eligible households. They would then skip to the fifth household. If the fifth household was not eligible, they would move to the next until they identified an eligible one. As a result, 3,567 households with 7,742 children aged 3-19 years were reached.

Using the data obtained from listing as a sampling frame, a sample of 1,200 households and 2,593 children aged 3 to 19 years was randomly selected through proportional allocation by region, ward, street, household head sex and age category. The household sample size was designed to allow estimation of key schooling indicators. The following indicators were considered in estimating the minimum sample size: enrollment, out of school, and attendance and primary and secondary school intake rates.

We utilised primary school net enrolment rate of 81.33%2 (World Bank 2018) for it gives the highest sample size.Besides, we made the following assumptions i) a design effect of 1.5 ii) average number of people aged between 3 and 19 years per household as two; iii) a 5% level of significance, which corresponds to 1.96 critical value for the standard normal distribution corresponding to a Type I error); and iv) a 5% margin of error respectively. The minimum estimated sample size was 2,389 children aged 3-19 years from 1,195 households after adjusting for a 90% response rate. The sample stratified proportionately between the two study sides based on their population and thereafter, randomly sampled households to participate in the study based on the listing.

Sampling deviation

The minimum estimated sample size was 2,389 children aged 3-19 years from 1,195 households after adjusting for a 90% response rate.

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire included household membership and their characteristics , social-economic characteristics, including food security, household shocks, household poverty well-being, and household schedule.

The individual schooling history questionnaire included detailed schooling information about individuals aged between 3 and 19 years, which consist of schooling information (enrolment, type of school enrolled, participation in preschool among others) for the year (2022), and 5 years retrospectively based on the age of the child.

The parental or guardian involment questionnaire helped sought information on parental involvement in their children's schooling including homework support, details of last schooling year(s), parental perception of student schooling experience, feeding and costs of schooling.

The institutional questionnaire contains information on institutional heads, staff and fees.

Cleaning operations

Data quality assessments continued during the data collection period by assessing for consistency of the responses as well as comparing data collected by field workers against spot check data collected by the senior research team and field supervisors.

Upon data collection completion, data were rigorously checked for consistency and outliers.

Data cleaning was carried out using Stata v.17.0.

Response rate

90%

Sampling error estimates

The following assumptions were made i) a design effect of 1.5 ii) average number of people aged between 3 and 19 years per household as two; iii) a 5% level of significance, which corresponds to 1.96 critical value for the standard normal distribution corresponding to a Type I error); and iv) a 5% margin of error respectively.

Therefore, the minimum estimated sample size was 2,389 children aged 3-19 years from 1,195 households after adjusting for a 90% response rate.