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:

Mohamed Nagdy and Max Roser (2016) – ‘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 by mean years of schooling, has, for a long time, been the central focus of policy makers and academic debate. While expanding education and increasing access is important, the actual skills acquired by students in the classroom are arguably a more important determinant of individual and social returns to education. This section focusses on the quality of education; more information on the global rise of education can be found here.

# Empirical View

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 standardised assessments that can be compared across borders and time.

# Quality of Education and Test Scores

The most widely discussed quantitative assessment of quality of education is the Programme for International Student Assessment (PISA) by the OECD. The PISA study assess 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 2000 and is repeated every three years.

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). The countries that consistently make up the top 5 in mathematics and the sciences are Singapore, South Korea, Hong Kong, Taiwan and Japan. The strength of this group of countries could be the result of their education systems or cultural difference that affect student behaviour in the absence of any schooling effects.

# Resources

Schools require many different inputs to produce educated individuals, of which teachers and textbooks are the most fundamental. In addition to these basic resources, better schools often have better facilities and equipment. Access to the internet and computers is also increasingly important in education. Given this, it is common to consider school quality through proxies like expenditure per student, or the pupil-teacher ratio of a school. It is important to note that the link between resources and school quality is not simplistic, for more information see the Data Quality & Definitions section.

# Correlates, Determinants & Consequences

# Teacher Quality

Research by Raj Chetty, John Friedman and Jonah Rockoff supports the idea that the quality of teachers make a significant difference to the performance of students on tests. Chetty et al. look at the impact on test scores of the entry and exit of high or low value added teachers on students performance in examinations. They find that not only does the entry of a high quality teacher improve the results of students, the presence of ‘bad teachers’ negatively impacts the performance of students. In addition to this, they also report that this improvement in test scores corresponds to long-term improvements in the outcomes of students.

# Impacts of teacher entry and exit on test scores – Chetty et al. (2014)1

Impacts of teacher entry and exit on test scores - Chetty et al.

# Early Intervention, Family Environment and Culture

James Heckman makes the point that education is a continuous process. He writes, “Skill formation is a dynamic process with strong synergistic components. Skill begets skill. Early investment promotes later investment. Non-cognitive skills and motivation are important determinants of success and these can be improved more successfully and at later ages than basic cognitive skills.” The following summary of the research into early intervention programmes in the US by James Heckman suggests that the effects of such programmes are significant and have long-lasting effects.2

Disadvantaged subnormal I.Q. children in Ypsilanti, Michigan were randomly assigned to the Perry Pre-school programme and administered intensive treatment at ages 4–5. Treatment was then discontinued and the persons were followed over their life cycle. These people are now about 35 years old. Evidence indicates that those enrolled in the programme have higher earnings and lower levels of criminal behaviour in their late 20s than do comparable children randomized out of the programme. Reported cost–benefit ratios for the programme are substantial. Measured through age 27, the programme returns $5.70 for every dollar spent. When returns are projected for the remainder of the lives of programme participants, the return on the dollar rises to $8.70. As with the Job Corps, a substantial fraction (65%) of the return to the programme has been attributed to reductions in crime (Schweinhart, Barnes & Weikart, 1993). The Syracuse Pre-school programme provided family development support for disadvantaged children from prenatal care through to age five. Reductions in problems with probation and criminal offences 10 years later were as large as 70% among children randomly assigned to the programme. Girls who participated in the programme also showed greater school achievement (Lally, Mangione & Honig, 1988). Studies of early intervention programmes have found short-term increases in test scores, less grade retention, and higher high school graduation rates among enrolled children. Of those studies that examine pre-delinquent or criminal behaviour, most have found lower rates of deviant behaviour among programme participants.

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.3 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).4

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).5

# Data Quality & Definitions

# The Effect of Resources and Development

Recent research however suggests that the link between resources and school quality is not so simplistic. 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 prioritised 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.6 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

A more sophisticated argument is 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.8 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.

# 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/