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 table contains 28 series, with data for years 2007/2008 - 2014/2015 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (14 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...) Statistics (2 items: Expenditure per capita; Index of change).

Global Primary Education Expenditure by Country, 2023 Discover more data with ReportLinker!

Most parents know instinctively that spending more time with their children and being actively involved in their education will give their children a good head-start in life. But since most parents have to juggle competing demands at work and home, there never seems to be enough time or they feel ill-equipped to help. This book from OECD's Programme for International Student Assessment (PISA) has some good news for concerned parents: it does not require a Ph.D or unlimited hours for parents to make a difference in their children's education. In fact, many parent-child activities that are associated with better reading performance among students involve relatively little time and no specialised knowledge. What these activities do demand is genuine interest and active engagement. "I enjoyed reading Let's Read Them a Story! The wide sample of countries shows the universality of the conclusions - conclusions which reassure parents that it is important to simply transmit the pleasure of reading to our children. No need to exhaust oneself finding the latest trendy children's books or educational toys; parents should simply read to children, enjoy reading themselves, and make family time to discuss what we've read."

Context

The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank

Content

This dataset combines key education statistics from a variety of sources to provide a look at global literacy, spending, and access.

For more information, see the World Bank website.

Fork this kernel to get started with this dataset.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:world_bank_health_population

http://data.worldbank.org/data-catalog/ed-stats

https://cloud.google.com/bigquery/public-data/world-bank-education

Citation: The World Bank: Education Statistics

Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by @till_indeman from Unplash.

Inspiration

Of total government spending, what percentage is spent on education?

At a time when OECD and partner countries are trying to figure out how to reduce burgeoning debt and make the most of shrinking public budgets, spending on education is an obvious target for scrutiny. Education officials, teachers, policy makers, parents and students struggle to determine the merits of shorter or longer school days or school years, how much time should be allotted to various subjects, and the usefulness of after-school lessons and independent study. This report focuses on how students use learning time, both in and out of school. What are the ideal conditions to ensure that students use their learning time efficiently? What can schools do to maximise the learning that occurs during the limited amount of time students spend in class? In what kinds of lessons does learning time reap the most benefits? And how can this be determined? The report draws on data from the 2006 cycle of the Programme of International Student Assessment (PISA) to describe differences across and within countries in how much time students spend studying different subjects, how much time they spend in different types of learning activities, how they allocate their learning time and how they perform academically.

This map shows the average amount spent on education 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 on education per householdAverage annual spending per household for tuition by education levelAverage annual spending per household for additional school necessitiesThis map shows Esri's 2022 U.S. Consumer Spending Data in Census 2020 geographies. The map adds increasing level of detail as you zoom in, from state, to county, to ZIP Code, to tract, to block group data.Esri's 2022 U.S. Consumer Spending database details which products and services consumers buy, including total dollars spent, average amount spent per household, and a Spending Potential Index. Esri's Consumer Spending database identifies hundreds of items in more than 15 categories, including apparel, food and beverage, financial, entertainment and recreation, and household goods and services. See Consumer Spending database to view the methodology statement and complete variable list.Additional Esri Resources:Esri DemographicsU.S. 2022/2027 Esri Updated DemographicsEssential demographic vocabularyThis item is for visualization purposes only and cannot be exported or used in analysis.Permitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

This data table presents education expenditure in Canada as a proportion of GDP.

Global Public Spending on Tertiary Education by Country, 2023 Discover more data with ReportLinker!

PLEASE READ THIS DATASET DESCRIPTION IN FULL BEFORE EXPORTING ANY DATA. This dataset provides transparency about the names and amounts of payments from county school boards to payees. More information about the statute for this dataset is under Maryland Education Article §5-115. https://mgaleg.maryland.gov/mgawebsite/Laws/StatuteText?article=ged&section=5-115&enactments=false Each county annually reports payment information about any payee who received an aggregate payment of $25,000 in a fiscal year from a school board. This started with Fiscal Year 2019 payments. We now have payments data through Fiscal Year 2024 (6/30/24). Baltimore County is also required to provide the purpose of the payment and whether the payee is a minority business enterprise. Montgomery County and Howard County data goes back to 2010. Baltimore County and Prince George’s County goes back to 2012. 2019 is the first year where are all counties were required to submit the data with payee names and amounts. Baltimore City data is missing for 2021 and 2023. Baltimore County data for 2023 needs further review. DBM will work on making these updates. Separately, Prince George’s County is required to provide additional detail from Education Article §5-101. That info is not part of this dataset. https://mgaleg.maryland.gov/mgawebsite/Laws/StatuteText?article=ged&section=5-101&enactments=False&archived=False

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

This table gives an overview of government expenditure on regular education in the Netherlands since 1900. All figures presented have been calculated according to the standardised definitions of the OECD. Government expenditure on education consists of expenditure by central and local government on education institutions and education. The government finances schools, colleges and universities. It pays for research and development conducted by universities. Furthermore it provides student grants and loans, allowances for school costs, provisions for students with a disability and child care allowances to households as well as subsidies to companies and non-profit organisations. Total government expenditure is broken down into expenditure on education institutions and education on the one hand and government expenditure on student grants and loans and allowances for school costs to households on the other. If applicable these subjects are broken down into pre-primary and primary education, special needs primary education, secondary education, senior secondary vocational and adult education, higher professional education and university education. Data are available from 1900. Figures for the Second World War period are based on estimations due to a lack of source material. The table also includes the indicator government expenditure on education as a percentage of gross domestic product (GDP). This indicator is used to compare government expenditure on education internationally. The indicator is compounded on the basis of definitions of the OECD (Organisation for Economic Cooperation and Development). The indicator is also presented in the StatLine table Education; Education expenditure and CBS /OECD indicators. Figures for the First World War and Second World War period are not available for this indicator due to a lack of reliable data on GDP for these periods. The statistic on Education spending is compiled on a cash basis. This means that the education expenditure and revenues are allocated to the year in which they are paid out or received. However, the activity or transaction associated with the payment or receipt can take place in a different year. Statistics Netherlands published the revised National Accounts in June 2024. Among other things, GDP has been adjusted upwards as a result of the revision. The revision has not been extended to the years before 1995. In the indicator 'Total government expenditure as % of GDP', a break occurs between 1994 and 1995 as a result of the revision. Data available from: 1900 Status of the figures: The figures from 1995 to 2022 are final. The 2023 figures are provisional. Changes on 31 December 2024: The final figures of 2021 and 2022 and the provisional figures of 2023 have been added. As a result of the revision of the National Accounts, among other things, GDP has been adjusted upwards. The indicator ‘Total government expenditure as % of GDP’ in this table has been updated on the basis of the revised figures for the entire time series since 1995. A break occurs in the indicator between 1994 and 1995. When will new figures be published? The final figures for 2023 and the provisional figures for 2024 will be published in December 2025. More information on the revision policy of National Accounts can be found under 'relevant articles' under paragraph 3.

Global General Government Expenditure on Education by Country, 2023 Discover more data with ReportLinker!

Analysis of ‘County Board of Education - Spending Disclosures’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/4c133a0c-a713-49f1-859f-647d3704e458 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

PLEASE READ THIS DATASET DESCRIPTION IN FULL BEFORE EXPORTING ANY DATA.

The data compiled in this dataset was provided by each County Board of Education. The data provides records of vendors that receive payments of $25,000 or more during a fiscal year from the County Board of Education. Chapter 541 of the Acts of 2019 requires each county school board must annually report (1) the name of a payee receiving a payment; (2) the location of a payee by postal zip code; (3) the amount of a payment; (4) for the Baltimore County Board of Education, the purpose for the payment and whether the payee is a minority business enterprise; and (5) for the Prince George’s County Board of Education, the budget data prepared under § 5-101 of the Education Article.

The bill defines a “payee” as any party who receives an aggregate payment of $25,000 in a fiscal year from a school board. A “payee” does not include (1) a public school employee with respect to the employee’s compensation; (2) a public school retiree with respect to the retiree’s retirement allowance; or (3) in Baltimore County, a third-party payee that accepts specified employee payroll-related payments.

All questions in regards to this data should be directed to the Maryland Department of Budget and Management or the individual county board of education(s).

--- Original source retains full ownership of the source dataset ---

Governments of developing countries typically spend between 20 and 30 percent of gross domestic product. Hence, small changes in the efficiency of public spending could have a major impact on aggregate productivity growth and gross domestic product levels. Therefore, measuring efficiency and comparing input-output combinations of different decision-making units becomes a central challenge. This paper gauges efficiency as the distance between observed input-output combinations and an efficiency frontier estimated by means of the Free Disposal Hull and Data Envelopment Analysis techniques. Input-inefficiency (excess input consumption to achieve a level of output) and output-inefficiency (output shortfall for a given level of inputs) are scored in a sample of 175 countries using data from 2006–16 on education, health, and infrastructure. The paper verifies empirical regularities of the cross-country variation in efficiency, showing a negative association between efficiency and spending levels and the ratio of public-to-private financing of the service provision. Other variables, such as inequality, urbanization, and aid dependency, show mixed results. The efficiency of capital spending is correlated with the quality of governance indicators, especially regulatory quality (positively) and perception of corruption (negatively). Although no causality may be inferred from this exercise, it points at different factors to understand why some countries might need more resources than others to achieve similar education, health, and infrastructure outcomes.

Abstract

The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

Geographic coverage

National

Analysis unit

Schools, teachers, students, public officials

Kind of data

Sample survey data [ssd]

Sampling procedure

The aim of the Global Education Policy Dashboard school survey is to produce nationally representative estimates, which will be able to detect changes in the indicators over time at a minimum power of 80% and with a 0.05 significance level. We also wish to detect differences by urban/rural location.

For our school survey, we will employ a two-stage random sample design, where in the first stage a sample of typically around 200 schools, based on local conditions, is drawn, chosen in advance by the Bank staff. In the second stage, a sample of teachers and students will be drawn to answer questions from our survey modules, chosen in the field. A total of 10 teachers will be sampled for absenteeism. Five teachers will be interviewed and given a content knowledge exam. Three 1st grade students will be assessed at random, and a classroom of 4th grade students will be assessed at random. Stratification will be based on the school’s urban/rural classification and based on region. When stratifying by region, we will work with our partners within the country to make sure we include all relevant geographical divisions.

For our Survey of Public Officials, we will sample a total of 200 public officials. Roughly 60 officials are typically surveyed at the federal level, while 140 officials will be surveyed at the regional/district level. For selection of officials at the regional and district level, we will employ a cluster sampling strategy, where roughly 10 regional offices (or whatever the secondary administrative unit is called) are chosen at random from among the regions in which schools were sampled. Then among these 10 regions, we also typically select around 10 districts (tertiary administrative level units) from among the districts in which schools werer sampled. The result of this sampling approach is that for 10 clusters we will have links from the school to the district office to the regional office to the central office. Within the regions/districts, five or six officials will be sampled, including the head of organization, HR director, two division directors from finance and planning, and one or two randomly selected professional employees among the finance, planning, and one other service related department chosen at random. At the federal level, we will interview the HR director, finance director, planning director, and three randomly selected service focused departments. In addition to the directors of each of these departments, a sample of 9 professional employees will be chosen in each department at random on the day of the interview.

Sampling deviation

For our school survey, we select only schools that are supervised by the Minsitry or Education or are Private schools. No schools supervised by the Ministry of Defense, Ministry of Endowments, Ministry of Higher Education , or Ministry of Social Development are included. This left us with a sampling frame containing 3,330 schools, with 1297 private schools and 2003 schools managed by the Minsitry of Education. The schools must also have at least 3 grade 1 students, 3 grade 4 students, and 3 teachers. We oversampled Southern schools to reach a total of 50 Southern schools for regional comparisons. Additionally, we oversampled Evening schools, for a total of 40 evening schools.

A total of 250 schools were surveyed.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

More information pertaining to each of the three instruments can be found below:

• School Survey: The School Survey collects data primarily on practices (the quality of service delivery in schools), but also on some de facto policy indicators. It consists of streamlined versions of existing instruments—including Service Delivery Surveys on teachers and inputs/infrastructure, Teach on pedagogical practice, Global Early Child Development Database (GECDD) on school readiness of young children, and the Development World Management Survey (DWMS) on management quality—together with new questions to fill gaps in those instruments. Though the number of modules is similar to the full version of the Service Delivery Indicators (SDI) Survey, the number of items and the complexity of the questions within each module is significantly lower. The School Survey includes 8 short modules: School Information, Teacher Presence, Teacher Survey, Classroom Observation, Teacher Assessment, Early Learner Direct Assessment, School Management Survey, and 4th-grade Student Assessment. For a team of two enumerators, it takes on average about 4 hours to collect all information in a given school. For more information, refer to the Frequently Asked Questions.

• Policy Survey: The Policy Survey collects information to feed into the policy de jure indicators. This survey is filled out by key informants in each country, drawing on their knowledge to identify key elements of the policy framework (as in the SABER approach to policy-data collection that the Bank has used over the past 7 years). The survey includes questions on policies related to teachers, school management, inputs and infrastructure, and learners. In total, there are 52 questions in the survey as of June 2020. The key informant is expected to spend 2-3 days gathering and analyzing the relavant information to answer the survey questions.

• Survey of Public Officials: The Survey of Public Officials collects information about the capacity and orientation of the bureaucracy, as well as political factors affecting education outcomes. This survey is a streamlined and education-focused version of the civil-servant surveys that the Bureaucracy Lab (a joint initiative of the Governance Global Practice and the Development Impact Evaluation unit of the World Bank) has implemented in several countries. The survey includes questions about technical and leadership skills, work environment, stakeholder engagement, impartial decision-making, and attitudes and behaviors. The survey takes 30-45 minutes per public official and is used to interview Ministry of Education officials working at the central, regional, and district levels in each country.

Sampling error estimates

The aim of the Global Education Policy Dashboard school survey is to produce nationally representative estimates, which will be able to detect changes in the indicators over time at a minimum power of 80% and with a 0.05 significance level.

Student Performance Dataset 2024 Overview This dataset comprises detailed information about high school students in China, collected from various universities and schools. It is designed to analyze the factors influencing student performance, well-being, and engagement. The data includes a wide range of features such as demographic details, academic performance, health status, parental support, and more. The participating institutions include prominent universities such as Tsinghua University, Peking University, Fudan University, Shanghai Jiao Tong University, and Zhejiang University.

Dataset Description Features Student ID: Unique identifier for each student. Gender: Gender of the student (Male/Female). Age: Age of the student. Grade Level: The grade level of the student (e.g., 9, 10, 11, 12). Attendance Rate: The percentage of days the student attended school. Study Hours: Average number of hours the student spends studying daily. Parental Education Level: The highest level of education attained by the student's parents. Parental Involvement: The level of parental involvement in the student's education (High, Medium, Low). Extracurricular Activities: Whether the student participates in extracurricular activities (Yes/No). Socioeconomic Status: Socioeconomic status of the student's family (High, Medium, Low). Previous Academic Performance: Previous academic performance level (High, Medium, Low). Class Participation: The level of participation in class (High, Medium, Low). Health Status: General health status of the student (Good, Average, Poor). Access to Learning Resources: Whether the student has access to necessary learning resources (Yes/No). Internet Access: Whether the student has access to the internet (Yes/No). Learning Style: Preferred learning style of the student (Visual, Auditory, Kinesthetic). Teacher-Student Relationship: Quality of the relationship between the student and teachers (Positive, Neutral, Negative). Peer Influence: Influence of peers on the student's behavior and performance (Positive, Neutral, Negative). Motivation Level: Student's level of motivation (High, Medium, Low). Hours of Sleep: Average number of hours the student sleeps per night. Diet Quality: Quality of the student's diet (Good, Average, Poor). Transportation Mode: Mode of transportation used by the student to commute to school (Bus, Car, Walk, Bike). School Type: Type of school attended by the student (Public, Private). School Location: Location of the school (Urban, Rural). Homework Completion Rate: The rate at which the student completes homework assignments. Reading Proficiency: Proficiency level in reading. Math Proficiency: Proficiency level in mathematics. Science Proficiency: Proficiency level in science. Language Proficiency: Proficiency level in language. Physical Activity Level: The level of physical activity (High, Medium, Low). Screen Time: Average daily screen time in hours. Bullying Incidents: Number of bullying incidents the student has experienced. Special Education Services: Whether the student receives special education services (Yes/No). Counseling Services: Whether the student receives counseling services (Yes/No). Learning Disabilities: Whether the student has any learning disabilities (Yes/No). Behavioral Issues: Whether the student has any behavioral issues (Yes/No). Attendance of Tutoring Sessions: Whether the student attends tutoring sessions (Yes/No). School Climate: Overall perception of the school's environment (Positive, Neutral, Negative). Parental Employment Status: Employment status of the student's parents (Employed, Unemployed). Household Size: Number of people living in the student's household. Performance Score: Overall performance score of the student (Low, Medium, High).

Data on annual expenditure by educational institutions per student, in Canadian and American dollars, reference year 2020/2021. At the primary/secondary level, the amount spent on educational core services and ancillary services is also presented.

Total general (local, regional and central) government expenditure on primary education (current, capital, and transfers), expressed as a percentage of GDP. It includes expenditure funded by transfers from international sources to government. Divide total government expenditure for a given level of education (ex. primary, secondary, or all levels combined) by the GDP, and multiply by 100. A higher percentage of GDP spent on education shows a higher government priority for education, but also a higher capacity of the government to raise revenues for public spending, in relation to the size of the country's economy. When interpreting this indicator however, one should keep in mind in some countries, the private sector and/or households may fund a higher proportion of total funding for education, thus making government expenditure appear lower than in other countries. Limitations: In some instances data on total public expenditure on education refers only to the Ministry of Education, excluding other ministries which may also spend a part of their budget on educational activities. For more information, consult the UNESCO Institute of Statistics website: http://www.uis.unesco.org/Education/

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_fa81cdad2b8e8d0d5ac6d97b992ea8e1/view