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.

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

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?

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

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

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.

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.

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.

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.

Global Primary to Post-Secondary Non-Tertiary Education Expenditure from Public Sources by Country, 2023 Discover more data with ReportLinker!

Series Name: Proportion of total government spending on essential services education (percent)Series Code: SD_XPD_ESEDRelease Version: 2020.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.a.2: Proportion of total government spending on essential services (education, health and social protection)Target 1.a: Ensure significant mobilization of resources from a variety of sources, including through enhanced development cooperation, in order to provide adequate and predictable means for developing countries, in particular least developed countries, to implement programmes and policies to end poverty in all its dimensionsGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

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

The sample for the Global Education Policy Dashboard in SLE was based in part on a previous sample of 260 schools which were part of an early EGRA study. Details from the sampling for that study are quoted below. An additional booster sample of 40 schools was chosen to be representative of smaller schools of less than 30 learners.

EGRA Details:

"The sampling frame began with the 2019 Annual School Census (ASC) list of primary schools as provided by UNICEF/MBSSE where the sample of 260 schools for this study were obtained from an initial list of 7,154 primary schools. Only schools that meet a pre-defined selection criteria were eligible for sampling.

To achieve the recommended sample size of 10 learners per grade, schools that had an enrolment of at least 30 learners in Grade 2 in 2019 were considered. To achieve a high level of confidence in the findings and generate enough data for analysis, the selection criteria only considered schools that: • had an enrolment of at least 30 learners in grade 1; and • had an active grade 4 in 2019 (enrolment not zero)

The sample was taken from a population of 4,597 primary schools that met the eligibility criteria above, representing 64.3% of all the 7,154 primary schools in Sierra Leone (as per the 2019 school census). Schools with higher numbers of learners were purposefully selected to ensure the sample size could be met in each site.

As a result, a sample of 260 schools were drawn using proportional to size allocation with simple random sampling without replacement in each stratum. In the population, there were 16 districts and five school ownership categories (community, government, mission/religious, private and others). A total of 63 strata were made by forming combinations of the 16 districts and school ownership categories. In each stratum, a sample size was computed proportional to the total population and samples were drawn randomly without replacement. Drawing from other EGRA/EGMA studies conducted by Montrose in the past, a backup sample of up to 78 schools (30% of the sample population) with which enumerator teams can replace sample schools was also be drawn.

In the distribution of sampled schools by ownership, majority of the sampled schools are owned by mission/religious group (62.7%, n=163) followed by the government owned schools at 18.5% (n=48). Additionally, in school distribution by district, majority of the sampled schools (54%) were found in Bo, Kambia, Kenema, Kono, Port Loko and Kailahun districts. Refer to annex 9. for details on the population and sample distribution by district."

Because of the restriction that at least 30 learners were available in Grade 2, we chose to add an additional 40 schools to the sample from among smaller schools, with between 3 and 30 grade 2 students. The objective of this supplement was to make the sample more nationally representative, as the restriction reduced the sampling frame for the EGRA/EGMA sample by over 1,500 schools from 7,154 to 4,597.

The 40 schools were chosen in a manner consistent with the original set of EGRA/EGMA schools. The 16 districts formed the strata. In each stratum, the number of schools selected were proportional to the total population of the stratum, and within stratum schools were chosen with probability proportional to size.

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

Attitudes of students towards higher education. Topics: preference of selected statements: right of all qualified students to study vs. right only for very best students, admittance of all students to universities vs. right of universities to select, higher education free of charge vs. acceptability of student fees in combination with grants and loans; attitude towards the following statements on higher education institutions (HEIs): should provide more programmes for part time students, should promote activities to increase variety of social and cultural backgrounds of students, study programmes should focus on teaching specialized knowledge, study programmes should include generic competences; importance of each of the following purposes of higher education: provide students with skills to be successful on the labour market, enhance personal development, education for active citizenship; attitude towards selected statements regarding the choice of the institution where to study: choice on the basis of reputation of the institution and study programmes, choice on the basis of other factors (e.g. location, friends, cost, …), sufficient availability of information materials, need for quality reports on universities, need for performance rankings, involvement of students in quality reports and rankings; considerations to study abroad; importance of each of the following obstacles with regard to studying abroad: lack of information on study opportunities, lack of funds, difficulty to obtain recognition for periods spent abroad, different quality of education abroad, language barriers, lack of encouragement by home university; attitude towards the following statements: short study periods abroad are mostly recognised by home university, all study programmes should include short study periods abroad, most non-mobile students obtain ECTS credit points for studies completed at their institutions, most mobile students obtain ECTS credit points for studies abroad, possibility of work placements in private enterprises as part of study programme, importance for HEIs to foster innovation and entrepreneurial mindset among students and staff, provision of tailor-made study programmes for enterprises by HEIs, more involvement of enterprises in higher education; future plans after graduation. Demography: study institute; sex; age; country where upper secondary diploma was obtained; number of years in higher education; field of study; full time student; study status; obtainable degrees at institution. Additionally coded was: respondent ID; country; interviewer ID; language of the interview; date of interview; time of the beginning of the interview; duration of the interview; type of phone line; region. Einstellung von Studierenden zum Hochschulwesen. Ziele der Hochschulbildung. Kriterien der Studienortwahl. Auslandsstudium. Zusammenarbeit der Hochschule mit Unternehmen. Bachelor und Master. Themen: Einstellung zu einem Recht aller Abiturienten auf ein Studium oder nur der Allerbesten; Universitäten sollten ein Selektionsrecht haben; Akzeptanz von Studiengebühren; Zustimmung zu folgenden Aussagen (Skala): Hochschulen sollten mehr Programme für Teilzeitstudenten anbieten, Hochschulen sollten Studenten mit vielfältigem sozialen und kulturellen Hintergrund aufnehmen, Studienpläne sollten sich auf spezifisches Fachwissen oder auf die Vermittlung allgemeiner Kompetenzen konzentrieren; wichtigste Ziele der Hochschulbildung (Skala): Ausbildung für den Arbeitsmarkt, persönliche Entwicklung, Ausbildung zum aktiven Bürger; wichtigste Aspekte der Studienortwahl: erfolgt nach Ruf der Hochschule, nach Lage, in Hinblick auf Freunde und Kosten, unabhängige Berichte über die Qualität sowie Rankings über die Leistung von Universitäten dienen als Entscheidungshilfe, Mitarbeit von Studierenden bei der Erstellung von Qualitätsberichten und Rankings; beabsichtigtes Auslandsstudium; Hindernisse für ein Auslandsstudium (fehlende Informationen, Geldmangel, fehlende Möglichkeit der Leistungsanerkennung der bisherigen Studienzeit im Ausland, unterschiedliche Qualität der Bildung, Sprachbarrieren, keine Förderung durch Dozenten); Einstellung zum Auslandsstudium (Skala): Anerkennung kurzer Studienaufenthalte im Ausland durch die Heimatuniversität, Auslandstudium sollte Bestandteil eines jeden Studienplans sein, ECTS Credit Points für Kurse an eigener Hochschule und für Auslandsaufenthalte, Wunsch nach Praktika in Privatunternehmen als Teil des Studienplans, Wichtigkeit der universitären Förderung von Innovation und unternehmerischem Denken bei Studenten und Angestellten, Wunsch nach einem Angebot maßgeschneiderter Studienpläne für Unternehmen zur Förderung der Weiterleitung von Arbeitskräften; Unternehmen sollten stärker an Hochschulorganisation beteiligt sein; Zukunftspläne nach dem Abschluss des Studiums. Demographie: Einrichtung, an der der Befragte studiert; Geschlecht; Alter; Land, in dem Hochschulreife erlangt wurde; Studiendauer; Studienrichtung; Vollzeitstudent; Studienstatus; an der Universität vergebene Abschlüsse. Zusätzlich verkodet wurde: Befragten-ID; Land; Interviewer-ID; Interviewsprache; Interviewdatum; Interviewdauer (Interviewbeginn und Interviewende); Interviewmodus (Mobiltelefon oder Festnetz); Region. ProbabilityProbability WahrscheinlichkeitsauswahlProbability Face-to-face interview: Paper-and-pencil (PAPI)Interview.FaceToFace.PAPI Persönliches Interview : Papier-und-Bleistift (PAPI)Interview.FaceToFace.PAPI

Objective: The INVEDUC project analyses public attitudes and preferences of citizens regarding different aspects of education policy in eight Western European countries. It also studies to what extent and via which mechanisms public opinion influences processes of policy-making.

Method: The INVEDUC survey of public opinion on education policy was conducted in April in May 2014 in eight Western European countries: Denmark, France, Germany, Ireland, Italy, Spain, Sweden and the United Kingdom. The total number of observations is 8,905 (i.e. between 1,000 and 1,500 for the different countries), drawn from random samples of the respective populations. The interviews were conducted by native speakers via computer-assisted telephone interviewing (CATI) and implemented by TNS Infratest Sozialforschung, Munich.

Questionnaire content: The survey covers the following aspects related to education policy: support for education spending relative to spending for other social policies; preferences for the distribution of education spending across different sectors of the education system (early childhood education and care, general schools, vocational education and training, higher education); willingness to pay taxes for additional spending on education; support for education spending in the face of different fiscal and policy trade-offs (higher taxes, higher public debt, cutbacks in other parts of the welfare state); support for social investment policies vs. social transfers and workfare policies; attitudes and preferences regarding the governance of education (comprehensive education, decentralisation of education governance, division of labor between public and private provision of education, school competition, role of employers in VET). The survey contains a number of experimental components, in particular when measuring the effect of trade-offs on preferences.

Demography: national citizenship; other citizenship; city size; financial situation of household; age (year of birth); sex; highest educational attainment (country-specific); age at completion of full-time education; employment status or age at completion of full-time education; current situation; reasons for part-time employment; occupational status; occupation (ISCO 2008); public service employment; sector; likelihood of own unemployment; net household income (country specific, classified); net personal income; education-related debt; household size; number of children in household; number of children under 10 years of age in household; single parent; trade union membership; parents´ university degree.

Historical chart and dataset showing Singapore education spending by year from 1990 to 2022.

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 were 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

In order to visit two schools per day, we clustered at the sector level choosing two schools per cluster. With a sample of 200 schools, this means that we had to allocate 100 PSUs. We combined this clustering with stratification by district and by the urban rural status of the schools. The number of PSUs allocated to each stratum is proportionate to the number of schools in each stratum (i.e. the district X urban/rural status combination).

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.

Cleaning operations

Data quality control was performed in R and Stata Code to calculate all indicators can be found on github here: https://github.com/worldbank/GEPD/blob/master/Countries/Rwanda/2019/School/01_data/03_school_data_cleaner.R

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.

The variable Equal Resource Distribution denotes the best estimate of the extent to which all social groups benefit from public spending, and have equal access to education, healthcare, and the welfare state. The index reaches from 0 to 1 (most equal).

Series SD_XPD_ESED: Proportion of total government spending on essential services, education (%)

Indicator 1.a.2: Proportion of total government spending on essential services (education, health and social protection)

Target 1.a: Ensure significant mobilization of resources from a variety of sources, including through enhanced development cooperation, in order to provide adequate and predictable means for developing countries, in particular least developed countries, to implement programmes and policies to end poverty in all its dimensions

Goal 1: End poverty in all its forms everywhere

Release Version: 2018.Q2.G.01

The demographic ageing process in most industrialized countries will reverse the demographic pyramid within the next decades. While the fraction of young people in education will decrease, the fraction of people over the retirement age will almost double within the next forty years. Research in some countries has analyzed the effects these demographic changes will have on educational spending. For Switzerland there is evidence, that per-pupil spending declined significantly in response to the rise of the share of retired people. The existing body of empirical research has so far - with a few exceptions - analyzed the relationship between demographic change and educational spending with cross-sectional or panel analyses of educational spending. Although most results show a negative correlation between the share of elderly in the population and educational spending per pupil, these papers - due to the level of aggregation of the data and the limited number of observable characteristics - do not allow establishing a direct proof that the elderly are less inclined to spend money on education. Therefore, not surprisingly these findings have been challenged by a number of empirical and theoretical papers This study reassesses the question of an intergenerational conflict over educational spending by directly looking at the expressed differences in the preferences for public spending of Swiss voters. The data-set has been expressively made for the purpose of this analysis and simulates public votes on educational and public finance issues. The professional survey institute "Gesellschaft für praktische Sozialforschung" (GfS) was comissioned to collect data from a representative sample of Swiss citizens. The sample contains the data of 2025 Swiss citizens over the age of 25. The data was collected in May 2007 using Computed Assisted Telephone Interviewing (CATI). The interviews were held in German, French or Italian depending on the language region. Apart from individual socio-economic and family characteristics, respondents were asked to express their opinion on a series of question concerning education and education financing.

This table contains 770 series, with data for years 1990 - 1998 (not all combinations necessarily have data for all years), and was last released on 2007-01-29. This table contains data described by the following dimensions (Not all combinations are available): Geography (26 items: Belgium (Flemish speaking);Czech Republic; Canada; Belgium (French speaking) ...), Sex (2 items: Males; Females ...), Age group (3 items: 11 years;13 years;15 years ...), Time spent (5 items: Every day;4 to 6 days a week;2 to 3 days a week; Once a week or less ...).