Finland had the highest quality of primary education in the world in 2017, with an index score of ***. The index runs on a scale of one (low quality) to seven (very good). Switzerland, Singapore, the Netherlands, and Estonia rounded out the top five for countries with the highest quality of primary education. A solid foundation Primary school age children are generally between the ages of six and eleven years old. Primary school is the first stage of formal education and consists of general knowledge and fundamental skills in areas like mathematics, reading, writing, and science, with student enrollment rates being particularly high in advanced economies. This helps young students to form a solid base for further study as they get older. Primary education in the United States Primary schools in the United States, where they are called elementary schools, can be either private or public institutions, with enrollment in public schools generally higher than in private schools. Education from the age of five is mandatory in the U.S., whether that be through the state-funded public school system, private schooling, or through an approved home school program. Depending on state law, students can leave school between the ages of 16 and 18.

The average for 2021 based on 41 countries was 111.6 index points. The highest value was in Luxembourg: 422.59 index points and the lowest value was in Turkey: 10.85 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

The average for 2021 based on 10 countries was 51.18 index points. The highest value was in Singapore: 129.04 index points and the lowest value was in Laos: 16.79 index points. The indicator is available from 2017 to 2021. Below is a chart for all countries where data are available.

The real total consumer spending on education in Egypt was forecast to continuously increase between 2024 and 2029 by in total 8.5 billion U.S. dollars (+68.06 percent). After the eighth consecutive increasing year, the real education-related spending is estimated to reach 21.1 billion U.S. dollars and therefore a new peak in 2029. Consumer spending, in this case eduction-related spending, refers to the domestic demand of private households and non-profit institutions serving households (NPISHs). Spending by corporations and the state is not included. The forecast has been adjusted for the expected impact of COVID-19.Consumer spending is the biggest component of the gross domestic product as computed on an expenditure basis in the context of national accounts. The other components in this approach are consumption expenditure of the state, gross domestic investment as well as the net exports of goods and services. Consumer spending is broken down according to the United Nations' Classification of Individual Consumption By Purpose (COICOP).The shown data adheres broadly to group tenth As not all countries and regions report data in a harmonized way, all data shown here has been processed by Statista to allow the greatest level of comparability possible. The underlying input data are usually household budget surveys conducted by government agencies that track spending of selected households over a given period.The data has been converted from local currencies to US$ using the average constant exchange rate of the base year 2017. The timelines therefore do not incorporate currency effects. The data is shown in real terms which means that monetary data is valued at constant prices of a given base year (in this case: 2017). To attain constant prices the nominal forecast has been deflated with the projected consumer price index for the respective category.Find more key insights for the real total consumer spending on education in countries like Morocco and Sudan.

The real per capita consumer spending on education in Egypt was forecast to continuously increase between 2024 and 2029 by in total 60.5 U.S. dollars (+56.27 percent). After the eighth consecutive increasing year, the real education-related per capita spending is estimated to reach 167.96 U.S. dollars and therefore a new peak in 2029. Consumer spending, in this case education-related spending per capita, refers to the domestic demand of private households and non-profit institutions serving households (NPISHs). Spending by corporations and the state is not included. The forecast has been adjusted for the expected impact of COVID-19.Consumer spending is the biggest component of the gross domestic product as computed on an expenditure basis in the context of national accounts. The other components in this approach are consumption expenditure of the state, gross domestic investment as well as the net exports of goods and services. Consumer spending is broken down according to the United Nations' Classification of Individual Consumption By Purpose (COICOP). The shown data adheres broadly to group tenth As not all countries and regions report data in a harmonized way, all data shown here has been processed by Statista to allow the greatest level of comparability possible. The underlying input data are usually household budget surveys conducted by government agencies that track spending of selected households over a given period.The data has been converted from local currencies to US$ using the average constant exchange rate of the base year 2017. The timelines therefore do not incorporate currency effects. The data is shown in real terms which means that monetary data is valued at constant prices of a given base year (in this case: 2017). To attain constant prices the nominal forecast has been deflated with the projected consumer price index for the respective category.Find more key insights for the real per capita consumer spending on education in countries like Algeria and Sudan.

Countries from Natural Earth 50M scale data with a Human Development Index attribute for each of the following years: 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2013, 2015, & 2017. The Human Development Index measures achievement in 3 areas of human development: long life, good education and income. Specifically, the index is computed using life expectancy at birth, Mean years of schooling, expected years of schooling, and gross national income (GNI) per capita (PPP $). The United Nations categorizes the HDI values into 4 groups. In 2013 these groups were defined by the following HDI values: Very High: 0.736 and higher High: 0.615 to 0.735 Medium: 0.494 to 0.614 Low: 0.493 and lower

In 2015 & 2017 these groups were defined by the following HDI values: Very High: 0.800 and higher High: 0.700 to 0.799 Medium: 0.550 to 0.699 Low: 0.549 and lower

Human Development Index attributes are from The World Bank: HDRO calculations based on data from UNDESA (2013a), Barro and Lee (2013), UNESCO Institute for Statistics (2013), UN Statistics Division(2014), World Bank (2014) and IMF (2014). 2015 & 2017 values source: HDRO calculations based on data from UNDESA (2017a), UNESCO Institute for Statistics (2018), United Nations Statistics Division (2018b), World Bank (2018b), Barro and Lee (2016) and IMF (2018).

Population data are from (1) United Nations Population Division. World Population Prospects, (2) United Nations Statistical Division. Population and Vital Statistics Report (various years), (3) Census reports and other statistical publications from national statistical offices, (4) Eurostat: Demographic Statistics, (5) Secretariat of the Pacific Community: Statistics and Demography Programme, and (6) U.S. Census Bureau: International Database.

Montserrat: Education service price index, world average = 100: The latest value from 2017 is 52.1 index points, unavailable from index points in . In comparison, the world average is 75.67 index points, based on data from 167 countries. Historically, the average for Montserrat from 2017 to 2017 is 52.1 index points. The minimum value, 52.1 index points, was reached in 2017 while the maximum of 52.1 index points was recorded in 2017.

This statistic shows a ranking of the estimated real per capita consumer spending on education in 2020 in the Middle East and North Africa (MENA), differentiated by country. Consumer spending here refers to the domestic demand of private households and non-profit institutions serving households (NPISHs) in the selected region. Spending by corporations or the state is not included. Consumer spending is the biggest component of the gross domestic product as computed on an expenditure basis in the context of national accounts. The other components in this approach are consumption expenditure of the state, gross domestic investment as well as the net exports of goods and services. Consumer spending is broken down according to the United Nations' Classification of Individual Consumption By Purpose (COICOP). The shown data adheres broadly to group **. As not all countries and regions report data in a harmonized way, all data shown here has been processed by Statista to allow the greatest level of comparability possible. The underlying input data are usually household budget surveys conducted by government agencies that track spending of selected households over a given period.The data has been converted from local currencies to US$ using the average constant exchange rate of the base year 2017. The timelines therefore do not incorporate currency effects. The data is shown in real terms which means that monetary data is valued at constant prices of a given base year (in this case: 2017). To attain constant prices the nominal forecast has been deflated with the projected consumer price index for the respective category.The shown forecast is adjusted for the expected impact of the COVID-19 pandemic on the local economy. The impact has been estimated by considering both direct (e.g. because of restrictions on personal movement) and indirect (e.g. because of weakened purchasing power) effects. The impact assessment is subject to periodic review as more data becomes available.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than *** countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

Hungary Real Household Consumption Index: Education data was reported at 93.950 Prev Year=100 in 2017. This records a decrease from the previous number of 109.318 Prev Year=100 for 2016. Hungary Real Household Consumption Index: Education data is updated yearly, averaging 100.380 Prev Year=100 from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 111.823 Prev Year=100 in 2003 and a record low of 85.253 Prev Year=100 in 2008. Hungary Real Household Consumption Index: Education data remains active status in CEIC and is reported by Hungarian Central Statistical Office. The data is categorized under Global Database’s Hungary – Table HU.H017: Real Household Consumption Index.

Abstract

The SABER Service Delivery (SD) tool was developed in 2016 in the Global Engagement and Knowledge Unit of the Education Global Practice (GP) at the World Bank, as an initiative to uncover bottlenecks that inhibit student learning in low and middle-income countries and to better understand the quality of education service delivery in a country as well as gaps in policy implementation. This school survey is aligned to the latest education research on what matters for student learning and how best to measure it. Its main purpose is to provide a mechanism to assess these different determinants of learning through a diagnostic tool and also to uncover the extent to which policies translate into implementation and practice. As a global initiative, SABER SD provides data for the new global lead indicator on learning, which makes it easier to monitor the Sustainable Development Goal of achieving universal primary education. The foundations of the SABER SD survey build upon two pre-existing World Bank Group initiatives that produce comparative data and knowledge on education systems: SABER (System Approach for Better Education Results) and SDI (Service Delivery Indicators). It also draws upon earlier surveys, namely, QSDS (Quality of Service Delivery Surveys) and PETs (Public Expenditure Tracking). On the one hand, the SABER SD tool builds on the evidence base and captures policy implementation measures from the core SABER domains. On the other hand, the SABER SD tool adapts and extends the surveys that were developed and implemented under the SDI program, which provides a set of metrics for benchmarking service delivery performance in education and health in Africa. There are two main factors that distinguish the SABER SD tool from SDI: (i) it has expanded the measurement of service delivery in primary education outside Africa and into Asia through pilots in Afghanistan, Pakistan and Laos, and (ii) it has adapted and extended the SDI approach by including additional test items from TIMSS and PIRLS, different modality for test administration, different classroom observation modules, and additional questions on student background. In alignment with the World Development Report (WDR 2018), the SABER SD instrument collects information on the the four key elements of an education system, which are identified as the main determinants for student learning (teachers, school management, school infrastructure, student preparedness). This survey strategically collects information on the most important school inputs and processes that produce learning outcomes. The SABER SD instrument collects data at the school level and asks questions related to the roles of all levels of government (including local and regional). The tool provides comprehensive data on: teacher effort and ability; principal leadership; school governance, management, and finances; community participation; and student performance in Mathematics and Language which includes a classroom observation module.

Geographic coverage

The Afghanistan SABER SD survey was implemented across 21 provinces in Afghanistan in 200 primary schools, of which 170 are public schools and the remaining 30 are Community Based Education (CBE) schools. The sample of 170 public schools is nationally representative, to the extent possible, of the places in Afghanistan that were secure enough for the teams to visit. Since it was not possible to obtain the sample frame from the universe of CBE schools, the sample of 30 CBE schools is not representative of the universe of CBE schools, but only of on-budget CBE schools. The Afghanistan SABER SD survey covers the following 21 provinces: Balkh, Faryab, Ghazni, Ghor, Hilmand, Hirat, Jawzjan, Kabul City, Kabul Province, Kandahar, Khost, Kunar, Logar, Nangarhar, Nuristan, Paktia, Parwan, Sar i Pul, Sarepul, Takhar and Wardak.

Analysis unit

The unit of analysis varies for each of the modules. They are as follows: Module 1, the unit of analysis is the school. Module 2, the unit of analysis is the teacher. Module 3, the unit of analysis is the principal/school. Module 4, the unit of analysis is the classroom/school/teacher. Module 5, the unit of analysis is the student. Module 6, the unit of analysis is the teacher.

For modules where the unit of analysis is not the school (i.e., teachers and/or students), it is possible to create an average for the school based on groupings by the unique identifier - the school code.

Universe

The target was to have a nationally representative sample. The team had a list of public schools covering just over 1.1 million students in 34 provinces. The final pool of primary schools from which the sample was drawn included those with a Grade 4 population of students.

Kind of data

Sample survey data [ssd]

Sampling procedure

Using estimates of Grade 4 enrollment rates by gender, we used sampling with probability proportional to size for all public school sampling. For CBE schools, we did not have this information and therefore, this sample is not representative of the universe of CBE schools in Afghanistan.

First stage — provinces Six provinces were sampled mechanically: three because of their political importance (Kabul City and Kabul Province in the Central region; Nangarhar in the East region); and three because they represented such a disproportionate fraction of their region that a PPS (probability proportional to size) strategy would always sample them anyway (Balkh in the North; Khost in the South; and Hirat in the West). Of the remaining 28 provinces, 15 were randomly sampled via stratified PPS, with strata simply defined as regions, yielding a total of 21 sampled provinces.

Second stage — public schools Within the sampled provinces, we assigned public schools to strata defined by three characteristics: region (one of five); rural/urban; and gender (male, female, or coed). The gender category was defined empirically from enrollments reported in the sample frame: if the numbers of either males or females was zero or was very small in both absolute and proportional terms, we considered the school single-sex. If in either absolute or proportional terms neither sex dominated, we considered the school co-educational. We then did stratified PPS to sample 170 public schools, along with a number of replacements in case schools had been closed or the sample frame was in some other way erroneous.

Third stage — gender Within the sampled mixed (“coed”) schools, we had to decide in advance whether to sample girls or boys. We set the overall fraction of these schools in which we would sample girls (equivalently, boys) to be equal to the overall fraction of the enrollment across all these mixed sex schools that girls (equivalently, boys) comprised. We then randomized so that at each school, the probability of girls (equivalently, boys) being sampled was roughly proportional to the fraction of that school’s enrollment that girls (equivalently, boys) comprised.

Fourth step — CBE schools Six months after drawing the original sample, we received a final list of CBE schools in the relevant provinces. Unlike typical public data, and specifically unlike Afghanistan’s public school sample frame, this CBE school list did not include enrollments. We thus sampled 30 of these schools in numbers proportional to the number of CBE schools in each sampled province.

Fifth step — Revised security for CBE schools in Khost A few weeks after drawing the CBE sample, it was revealed that only one in every six CBE schools in Khost province was sufficiently safe for the field teams to visit. This meant re-drawing the CBE sample in Khost among the small minority of schools that were safe enough to visit.

Sampling deviation

Sampling in Afghanistan had several special features: high logistical costs, CBE schools, fluid security concerns, and a very specific type of gendered schools.

1. High Logistical costs. It was decided early in the process to sample a subset of provinces to be visited, since visiting every province would have implied high logistical costs that made little sense to incur for a relatively small number of schools.

2. CBE school sample frame. CBE schools were disproportionately important to SABER-SD (in relation to their actual numbers), so a portion of the sample was reserved for schools of this type. However, the sample frame for these non-public-operated schools came from disparate sources and could not be assembled until six months after the sample frame for the public schools. Since the team was unable to obtain the sample frame from the universe of CBE schools (on and off-budget), which would allow the proper random selection and representativeness, it is important to acknowledge that the sample of CBE schools in the SABER SD survey is not representative of all CBE schools, but only of on-budget CBE schools, which are managed by the Afghan Ministry of Education. The 2017 Afghanistan SABER SD surveyed 30 CBE schools: 6 located in the province of Ghor, 13 located in the province of Paktia and 11 located in the province of Khost.

3. Fluid security concerns. When the sampling process was completed, the team did not know which schools would be in areas safe enough to visit at the actual survey time. A few weeks after drawing the CBE sample, it was revealed that only one in every six CBE schools in the Khost province was sufficiently safe for the field teams to visit. This meant re-drawing the CBE sample in Khost among the small minority of schools that were safe enough to visit. Within these restrictions, the resulting CBE sample is representative of the parts of Afghanistan that were secure enough for teams to visit.

4. Gendered Schools. The fourth feature of this

Australia: Education service price index, world average = 100: The latest value from 2021 is 207.03 index points, an increase from 205.51 index points in 2017. In comparison, the world average is 72.61 index points, based on data from 165 countries. Historically, the average for Australia from 2017 to 2021 is 206.27 index points. The minimum value, 205.51 index points, was reached in 2017 while the maximum of 207.03 index points was recorded in 2021.

Argentina: Education service price index, world average = 100: The latest value from 2021 is 39.75 index points, a decline from 71.42 index points in 2017. In comparison, the world average is 72.61 index points, based on data from 165 countries. Historically, the average for Argentina from 2017 to 2021 is 55.59 index points. The minimum value, 39.75 index points, was reached in 2021 while the maximum of 71.42 index points was recorded in 2017.

Djibouti DJ: Gender Parity Index (GPI): Secondary School Enrollment: Gross data was reported at 0.835 Ratio in 2017. This records an increase from the previous number of 0.820 Ratio for 2016. Djibouti DJ: Gender Parity Index (GPI): Secondary School Enrollment: Gross data is updated yearly, averaging 0.698 Ratio from Dec 1971 (Median) to 2017, with 36 observations. The data reached an all-time high of 0.835 Ratio in 2017 and a record low of 0.365 Ratio in 1976. Djibouti DJ: Gender Parity Index (GPI): Secondary School Enrollment: Gross data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Djibouti – Table DJ.World Bank: Education Statistics. Gender parity index for gross enrollment ratio in secondary education is the ratio of girls to boys enrolled at secondary level in public and private schools.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

BI: School Enrollment: Primary: % Net data was reported at 92.805 % in 2018. This records a decrease from the previous number of 94.876 % for 2017. BI: School Enrollment: Primary: % Net data is updated yearly, averaging 49.163 % from Dec 1973 (Median) to 2018, with 25 observations. The data reached an all-time high of 95.374 % in 2010 and a record low of 17.146 % in 1978. BI: School Enrollment: Primary: % Net data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Burundi – Table BI.World Bank.WDI: Social: Education Statistics. Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.;UNESCO Institute for Statistics (http://uis.unesco.org/). Data as of February 2020.;Weighted average;

China: Education service price index, world average = 100: The latest value from 2021 is 138.22 index points, an increase from 117.38 index points in 2017. In comparison, the world average is 72.61 index points, based on data from 165 countries. Historically, the average for China from 2017 to 2021 is 127.8 index points. The minimum value, 117.38 index points, was reached in 2017 while the maximum of 138.22 index points was recorded in 2021.

Turkey: Education service price index, world average = 100: The latest value from 2021 is 10.85 index points, a decline from 17.13 index points in 2017. In comparison, the world average is 72.61 index points, based on data from 165 countries. Historically, the average for Turkey from 2017 to 2021 is 13.99 index points. The minimum value, 10.85 index points, was reached in 2021 while the maximum of 17.13 index points was recorded in 2017.

Sweden: Education service price index, world average = 100: The latest value from 2021 is 210.62 index points, a decline from 233.82 index points in 2017. In comparison, the world average is 72.61 index points, based on data from 165 countries. Historically, the average for Sweden from 2017 to 2021 is 222.22 index points. The minimum value, 210.62 index points, was reached in 2021 while the maximum of 233.82 index points was recorded in 2017.

India: Education service price index, world average = 100: The latest value from 2021 is 35.47 index points, a decline from 40.25 index points in 2017. In comparison, the world average is 72.61 index points, based on data from 165 countries. Historically, the average for India from 2017 to 2021 is 37.86 index points. The minimum value, 35.47 index points, was reached in 2021 while the maximum of 40.25 index points was recorded in 2017.

Serbia: Education service price index, world average = 100: The latest value from 2021 is 27.36 index points, an increase from 24.03 index points in 2017. In comparison, the world average is 72.61 index points, based on data from 165 countries. Historically, the average for Serbia from 2017 to 2021 is 25.7 index points. The minimum value, 24.03 index points, was reached in 2017 while the maximum of 27.36 index points was recorded in 2021.

Hungary: Education service price index, world average = 100: The latest value from 2021 is 68.25 index points, an increase from 65.51 index points in 2017. In comparison, the world average is 72.61 index points, based on data from 165 countries. Historically, the average for Hungary from 2017 to 2021 is 66.88 index points. The minimum value, 65.51 index points, was reached in 2017 while the maximum of 68.25 index points was recorded in 2021.