Quality of Education

OWID presents work from many different people and organizations. When citing this entry, please also cite the original data source. This entry can be cited as:

Max Roser, Mohamed Nagdy and Esteban Ortiz-Ospina (2017) – ‘Quality of Education’. Published online at OurWorldInData.org. Retrieved from: https://ourworldindata.org/quality-of-education [Online Resource]

Increases to the quantity of education – as measured for example by mean years of schooling – has, for a long time, been the central focus of policy makers and academic debate. While increasing the access to education is important, the the actual goal of providing schooling is to teach skills and transfer knowledge to students in the classroom. This entry focusses on the outcomes of schooling – the quality of education.

While we have good empirical data on the access to education we know much less about the quality of education. Unfortunately, the data on the skills and knowledge of students is sparse and has limited spatial and temporal coverage. This is in part due to the difficulty and cost of creating and implementing standardized assessments that can be compared across borders and time.

# Empirical View

# Results from the PISA study

The most widely discussed quantitative assessment of quality of education comes from the PISA study, which is run by the OECD. The Programme for International Student Assessment (PISA) assesses the performance of 15-year old school pupils’ performance on mathematics, reading and science examinations. The tests are designed to be comparable across countries and to assess students’ knowledge as well as problem solving skills. The first round of tests took place in 1997 and the study was repeated every three years since then.

The three maps below show the results for the three subjects in which students are assessed.

# TIMSS assessment

# PIRLS assessment

# Studies that combine educational outcome measures

# Quality of Education and Test Scores by Sex

In every country and in every year girls achieved higher PISA test scores in reading. The difference of sometimes more than 50 points is substantial as the test scores are standardized to have a standard deviation of 100 points.

In mathematics the difference between girls and boys is much more mixed than in the reading dimension. While in most countries boys tend to achieve better test scores there are also many countries and years in which girls performed better than boys.

# The variability of PISA outcomes within countries

The correlation of the test scores shown in the visualization below suggests that a good educational system matters across the entire distribution of outcomes. In those countries in which the top students perform better than in other countries, the worst students also perform better than in other countries.

# Change over time

Student Achievement in the United States over Time1

# High educational quality in East Asia

The OECD PISA rankings demonstrate the strength of education in East Asian countries. These results are broadly supported by similar research conducted by the International Association for the Evaluation of Educational Achievement (IEA) and Boston College. The IEA produces assessments of mathematics and science performance (TIMSS) as well as of reading and literacy (PIRLS). Countries that repeatedly rank among the top 5 in mathematics and the sciences are Singapore, South Korea, Hong Kong, Taiwan and Japan.

# Some results from other international assessments

The Latin American Laboratory for Assessment of the Quality of Education (LLECE) assessment: Mathematics score of 6th graders. More information on LLECE is published by the UNESCO here.

The OECD also surveys the skills of adults. This is done in the Programme for the International Assessment of Adult Competencies (PIAAC). Here is the world map showing the level of numeracy of adults. More information on PIAAC can be found here.

The Programme for the Analysis of Education Systems (PASEC) has assessed educational outcomes in 13 countries in Francophone West Africa. Here is a map of outcomes in French language.

SACMEQ reading and math assessments have been carried out in countries in Anglophone East Africa in 1995, 2000, and 2007. Here is a map of the outcome of the assessments of 6th graders on the mathematics scale.

EGRA and EGMA are the Early Grade Reading Assessment and Math Assessment which are simple, low-cost assessments of literacy and numeracy.

# Correlates, Determinants & Consequences

# The importance of culture

Another interesting aspect of school performance is the effect of family environments and culture on students exam performance. A study by John Jerrim finds that children of East Asian immigrants to Australia outperform their native counterparts in the PISA tests.2 In mathematics, he finds them to be ahead by 100 points representing two and a half years of education. This evidence suggests that the differences highlighted by PISA and the IEA may be driven by cultural or family factors rather than the schooling systems.

# Correlation with Overall Development

Indicators of skills and knowledge, such as the OECD PISA scores, are highly correlated with indicators of economic development. The following scatter plot shows the correlation between the PISA reading scores and the United Nations’ Human Development Index (HDI) for a select group of countries.

# Competition and School Quality

There exists a substantial literature on the effects of competition on school quality and performance. Whether choice improves school quality remains an open question in economics. In general we might expect that more schools might be better for outcomes through competitive forces, however this relies on both schools and parents responding to the increased competition/choice. On the demand side, parents need some way of observing school quality accurately as well as the ability to change schools. Meanwhile, schools need some incentive to respond to any increase in competition. This is especially important since most public school systems lack any profit motive.

Much of the research into the effects of competition rely on indirect measures of demand for high quality schools such as local rents and house prices. Disaggregating the willingness to pay for better schools from neighbourhood effects and sociodemographic factors is highly technical and relies on models of sorting. For more information on these models see Rothstein (American Economic Review, 2006), Bayer and McMillan (NBER, 2005), and Bayer et al. (NBER, 2007).3

An alternative approach has been to use variables correlated with school competition but independent of the other the demand and supply factors to disaggregate the different effects of choice (instrumental variables approach). For more information on this approach please see Hoxby (American Economic Review, 2000) and Rothstein (American Economic Review, 2007).4

# The Effect of Resources and Development

Recent research however suggests that the link between resources and school quality is not simple. The OECD looked into whether money can buy stronger PISA test performance. They concluded that the most important factor in PISA test performance is how resources are used: countries that prioritized the quality of teachers over class sizes performed much better. This view represents a growing consensus in the education literature that inputs such as class size and expenditure per pupil have little to no effect on the returns to schooling in the developed world.5

An argument made by Eric Hanushek and Ludger Woessmann is that the lack of any straightforward relationship between resources and school outcomes indicates a minimum resource requirement.6 Once the resource threshold has been reached, additional expenditure has little or no returns to school quality — instead, teacher quality and other constraints matter far more.

The following scatter shows average spending per student from the age of 6 to 15 against reading test scores in 2009.

# Average reading performance in PISA and average spending per student from the age of 6 to 15 – OECD7

Average reading performance in PISA and average spending per student

# Quality of education and prosperity

The education economists Eric Hanushek and Ludger Wößmann combined the results from educational achievement tests to investigate the question whether the quality of education has a causal influence on the growth of the economy.8

The visualization below shows the correlation between the quality of education, as measured by Hanushek and Woessmann, and the level of prosperity of the country in 2016.

# Data Quality & Definitions

# Data Sources

# UNESCO Institute of Statistics
  • Data: Comprehensive data on enrollments, out-of-school children, repetition, completion, gender, teachers, education expenditures, learning outcomes, educational attainment, education equality, literacy, population, labor, and EMIS.
  • Geographical coverage: Global by country
  • Time span: 1999-2015
  • Available at: http://data.uis.unesco.org/

# World Bank EdStats
  • Data: indicators on educational attainment, enrolment, attendance, teachers, financing and more
  • Geographical coverage: Global, over 200 countries
  • Time span: 1970 to most recent data year; Projections to 2050
  • Available at: It is online here

# OECD Programme for International Student Assessment (PISA)
  • Data: Standardised assessment scores for mathematics, reading and science
  • Geographical coverage: OECD countries and other partners
  • Time span: 2000-2012 (every three years)
  • Available at: http://www.oecd.org/pisa/