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Education Spending

How is education financed? How much do we spend on it? What are the returns?

In most countries basic education is nowadays perceived not only as a right, but also as a duty – governments are typically expected to ensure access to basic education, while citizens are often required by law to attain education up to a certain basic level.1

This was not always the case: the advancement of these ideas began in the mid-19th century, when most of today’s industrialized countries started expanding primary education, mainly through public finances and government intervention. Data from this early period shows that government funds to finance the expansion of education came from a number of different sources, but taxes at the local level played a crucial role. The historical role of local funding for public schools is important to help us understand changes – or persistence – in regional inequalities.

The second half of the 20th century marked the beginning of education expansion as a global phenomenon. Available data shows that by 1990 government spending on education as a share of national income in many developing countries was already close to the average observed in developed countries.2

This global education expansion in the 20th century resulted in a historical reduction in education inequality across the globe: in the period 1960-2010 education inequality went down every year, for all age groups and in all world regions. Recent estimates of education inequality across age groups suggest that further reductions in schooling inequality are still to be expected within developing countries.3

Recent cross-country data from UNESCO tells us that the world is expanding government funding for education today, and these additional public funds for education are not necessarily at the expense of other government sectors. Yet behind these broad global trends, there is substantial cross-country – and cross-regional – heterogeneity. In high-income countries, for instance, households shoulder a larger share of education expenditures at higher education levels than at lower levels – but in low-income countries, this is not the case.

Following the agreement of the Millennium Development Goals, the first decade of the 21st century saw an important increase in international financial flows under the umbrella of development assistance. Recent estimates show that development assistance for education has stopped growing since 2010, with notable aggregate reductions in flows going to primary education. These changes in the prioritization of development assistance for education across levels and regions can have potentially large distributional effects, particularly within low-income countries that depend substantially on this source of funding for basic education.4

When analyzing correlates, determinants and consequences of education consumption, the macro data indicates that national expenditure on education does not explain well cross-country differences in learning outcomes. This suggests that for any given level of expenditure, the output achieved depends crucially on the mix of many inputs.

Available evidence specifically on the importance of school inputs to produce education, suggests that learning outcomes may be more sensitive to improvements in the quality of teachers, than to improvements in class sizes. Regarding household inputs, the recent experimental evidence suggests that interventions that increase the benefits of attending school (e.g. conditional cash transfers) are particularly likely to increase student time in school; and that those that incentivize academic effort (e.g. scholarships) are likely to improve learning outcomes.

Policy experiments have also shown that preschool investment in demand-side inputs leads to large positive impacts on education – and other important outcomes later in life. The environment that children are exposed to early in life, plays a crucial role in shaping their abilities, behavior, and talents.

Historical perspective on financing education

When did the provision of education first become a public policy priority?

Governments around the world are nowadays widely perceived to be responsible for ensuring the provision of accessible quality education. This is a recent social achievement. The advancement of the idea to provide education for more and more children only began in the mid-19th century, when most of today’s industrialized countries started expanding primary education.

The following visualization, plotting public expenditure on education as a share of Gross Domestic Product (GDP) for a number of early-industrialized countries, shows that this expansion took place mainly through public funding. Our topic page on global education provides details regarding how this expansion in funding materialized in better education outcomes for these countries.

How did the US finance the expansion of public education?

Public schools in the US educate more than 90% of all children enrolled in elementary and secondary schools.5

This is the result of a process of education expansion that relied heavily on public funding, particularly from local governments. The visualization shows the sources of revenues for public schools in the US over the last 120 years.

As can be seen, states and localities are – and have always been – the main sources of funding for public primary education in the US. In fact, we observe three broad periods in this graph: there is first a period of stable revenues until 1920, then a period of sharp growth and decline during the interwar years, and then a period of substantial growth since the Second World War, slowing down in the 1970s. In all these periods, federal funding was always very small.

Disaggregated data from the last couple of decades gives further insights into the specific sources of local revenues for schools in the US: the largest part comes from property taxes (about 80% of local revenues came from property taxes in 2013), while only a very small part comes from fees and donations (private funding for public schools, which is considered a local revenue, amounted to less than 2% of total public school revenues in 2013). This heavily decentralized system relying on property taxes has the potential to create large inequalities in education since public schools in affluent urban areas are able to raise more funding from local revenues. Indeed, a significant part of the debate on education inequalities in the US today focuses on the importance of increasing progressive federal spending to reduce inequalities in public school funding.6

How did France finance the expansion of public education?

The case of the US above shows that funding for public schools has been historically a responsibility of local governments. In other countries, such as France, the expansion of public education also took place initially with resources from local governments, but relatively quickly the fiscal burden was shifted to the national level. In France, this transition was associated with a sharp jump towards universal access and a concomitant reduction in regional inequalities.

The following visualization from Lindert (2004)7 provides evidence of the French experience. As we can see there are three distinct periods: education spending was initially low and mainly private, then in 1833 funding began growing with local resources after the introduction of a law liberating communes to raise more local taxes for schools, and finally in 1881 the national government took over most of the financial responsibility after the introduction of a new law that abolished all fees and tuition charges in public elementary schools. In the source book, Lindert (2004) provides further evidence of how this transition towards centrally funded public education reduced north-south inequalities in France.

Lindert (2004) France_EarlyEducation_Breakdown
Sources of funds for France’s public primary schools, 1820–1913 – Figure 5.5 in Lindert (2004)8

In the US growth in education expenditure was characterized by growth specifically in the public sector

A comparison of expenditure between public and private education institutions is helpful to contextualize the role the public sector played in the process of education expansion in industrialized countries. The following graph does this using data from the National Center for Education Statistics in the US.

It shows that during the years 1950-1970 – a period of substantial growth in education expenditure in the US – expenditure grew specifically in the public sector.9

When did the expansion of basic education become a global phenomenon?

The second half of the 20th century marked the beginning of education expansion as a global phenomenon. The visualization shows government expenditure on education as a share of national income for a selection of low and middle-income countries, together with the corresponding average for high-income countries, for more than the last half-century. As can be seen, spending on education in many developing countries has become similar to the average observed in developed countries in recent decades.

It is important to point out that the remark above makes reference to convergence in expenditure relative to income. To the extent that low-income countries remain poorer than high-income countries, gaps in levels of expenditure per pupil are persistently large. Indeed, cross-country heterogeneity in education expenditure per pupil is currently much higher than heterogeneity in expenditure as a share of GDP.10 One factor contributing to the slower convergence of expenditure per pupil in real terms is the fact that teachers' salaries – the main component of education expenditure, as discussed below – are much higher in high-income countries because labor has a higher opportunity cost in these countries. In general, the opportunity cost of labor is a key variable that governments in developing countries should factor in when deciding whether to expand education now, rather than later.

Education inequality is falling around the world

An important consequence of the global education expansion is a reduction in education inequality across the globe. The following visualization shows this through a series of graphs plotting changes in the Gini coefficient of the distribution of years of schooling across different world regions. The Gini coefficient is a measure of inequality and higher values indicate higher inequality – you can read about the definition and estimation of Gini coefficients in our related article. The time-series chart shows inequality by age group.

It can be seen that as inequality is falling over time, the level of inequality is higher for older generations than it is for younger generations. We can also see that in the reference period education inequality went down every year, for all age groups and in all world regions.

Have gains from historical education expansion fully materialized? The breakdown by age gives us a view into the future: as inequality is lower among today's younger generations, we can expect the decline of inequality to continue in the future. Thus, further reductions in education inequality are still to be expected within developing countries; and if the expansion of global education can be continued, we can speed up this important process of global convergence.

Cuaresma etal(2013) edu_gini_1960_2010
Education Gini coefficients by world region for selected age groups, 1960- 2010 – Figure 4 in Crespo Cuaresma et al. (2013)11

Education inequality can decline rapidly across all levels of education – South Korea is an example

The experience of South Korea shows that it is possible to reduce education inequality rapidly across all levels of education.

The following visualization shows two graphs comparing the concentration of years of education in South Korea between the years 1970 and 2010. To be precise, each of these graphs shows an education Lorenz curve: a plot showing the cumulative percentage of the schooling years across all levels of education on the vertical axis, and the cumulative percentage of the population on the horizontal axis.

As can be seen, in 2010 education was much less concentrated than in 1970, not only because there was a smaller share of individuals without schooling (shown at the bottom of the chart), but also because there was a smaller share of individuals concentrating large proportions of school-years at higher levels of education. Indeed, in only 40 years South Korea was able to double the mean years of schooling (from 6 to 12 years) and at the same time get remarkably close to the 45-degree line marking the hypothetical scenario of perfect equality of schooling.

inequality-of-education-south-korea-lorenz-curves
Inequality of Educational Attainment in South Korea 1970 and 201012

Financing of education across the world

Is funding for education expanding?

The last two decades have not a clear trend in the share of income that countries devote to education.

The following chart plots trends in public expenditure on education as a share of GDP. We can see an upward trend in some countries, but a downward trend in others.

However, as incomes – measured by GDP per capita – are generally increasing around the world, this means that the total amount of global resources spent on education is increasing in absolute terms.

Is additional funding for education taking resources from other sectors?

The following visualization shows government expenditure on education as a share of total government expenditure. The available data also does not suggest a discernible global pattern here.

The data does suggest, however, that there is large and persistent cross-country heterogeneity in the relative importance of education vis-a-vis other sectors, even within developing countries.

European countries tend to assign a lower share of public budgets to education, relative to the amount of their income that is devoted to education

Generally speaking, countries that spend a large share of their income on education also tend to prioritize education highly within their budgets.

The following visualization presents a snapshot of government spending on education around the world. Specifically, this graph plots government expenditure on education as a share of GDP on the horizontal axis, and government expenditure on education as a share of total government expenditure on the vertical axis.

As we can see, there is a positive correlation, but regional differences are stark: for almost every level of spending as a share of GDP along the horizontal axis, countries in Europe spend a smaller budget share on education.

In European countries the weight of primary education within total education spending is lower than in other countries

In comparison to countries where education started expanding later, European countries tend to assign relatively more of their government education budgets to the secondary and tertiary levels, while at the same time devoting relatively less of their general government budgets to education as a whole.

This can be appreciated in the following visualization, where the prioritization of primary education (i.e. the share of primary education within the education budget) is plotted against the overall prioritization of education (i.e. the share of education within the entire government budget).

It can be seen that European countries are mostly located in the upper left. There is a weak positive correlation between the variables, both across all countries and across European countries.

In high-income countries, households shoulder a larger share of education expenditures at higher education levels than at lower levels – but in low-income countries, this is not the case

The following visualization shows the percentage of total education expenditures contributed directly by households in 15 high-income countries and 15 low or middle-income countries.

The top chart in this figure, corresponding to high-income countries, shows a very clear pattern: households contribute the largest share of expenses in tertiary education, and the smallest share in primary education. Roughly speaking, this pattern tends to be progressive, since students from wealthier households are more likely to attend tertiary education, and those individuals who attend tertiary education are likely to perceive large private benefits.13

In contrast, the bottom chart shows a very different picture: in several low-income countries households contribute proportionally more to primary education than to higher levels. Such distribution of private household contributions to education is regressive.

UNICEF Private Education Expenditure Levels
Percentage of total education expenditures contributed directly by households in 30 countries, grouped by country income – Figure 32 in The Investment Case for Education and Equity (UNICEF - 2015)

Recent funding structures in OECD countries

Primary education continues to be publicly funded in industrialized countries

We have already mentioned that those countries that pioneered the expansion of primary education in the 19th century – all of which are current OECD member states – relied heavily on public funding to do so. Today, public resources still dominate funding for the primary, secondary, and post-secondary non-tertiary education levels in these countries.

The visualization presents OECD-average expenditure on education institutions by source of funds.14

Publicly funded pre-primary education is more strongly developed in the European countries of the OECD

High-income countries tend to have better-developed pre-primary education systems than lower-income countries. However, within high-income countries, there is substantial heterogeneity in the extent to which pre-primary education is publicly financed.

The visualization presents expenditure on pre-primary educational institutions as a share of GDP across the OECD.

As can be seen, publicly funded pre-primary education tends to be more strongly developed in Europe than in the non-European countries of the OECD.

OECD_Expenditure_Pre-primary
Expenditure on pre-primary educational institutions (% of GDP), OECD, 2012 – Figure C2.4 in Education at a Glance (2015)

Where does funding for education go to?

The largest part of funding devoted to education in OECD countries goes to finance current expenditures, mainly compensation of staff – specifically, teachers. The following two charts, taken from the OECD's report Education at a Glance (2015), highlight the labor-intensive nature of education. In the lower levels of education (i.e. primary, secondary, and post-secondary non-tertiary) the share of current expenditure is very large and exhibits little cross-country variation – between 90 and 97 percent of total expenditure corresponds to current expenditure across all of the OECD countries. In higher levels of education (i.e. tertiary) there is more cross-country variation, but current expenditure still dominates by a large margin across all countries.

OECD_Expenditure_Education_Resources
Distribution of current and capital expenditure on educational institutions – Figure B6.2 in Education at a Glance (2015)

What drives current expenditure on education?

In the figures above we noted the importance of current expenditure in the production of education. The following table provides further details regarding the type of expenditures that comprise current spending. Specifically, this chart shows a breakdown of expenditure for tertiary-level institutions in the US (public and private), during the period 1980-1997. It shows that instruction accounts for almost half of expenditure; and while there are some small differences across sectors, there is a fair amount of stability in expenditures across time. This serves as a benchmark for lower education levels, where instruction takes an even larger share of expenditure.15

US_CurrentExpenditure_Types
Percent distribution of college and university current expenditures in the US, by control over time – Table 8 in Welch and Hanushek (2006)16

International financing flows

Education financing in developing countries has been bolstered by development assistance

Following the agreement of the Millennium Development Goals, the first decade of the 21st century saw an important increase in international financial flows under the umbrella of development assistance (often also called development aid, or simply 'aid').

The following chart shows total OECD development assistance flows for education by level, in constant 2013 US dollars, for the period 2002-2013. As it can be seen, there are two distinct periods: in 2003-2010 flows for education increased substantially, more than doubling in real terms across all levels of education; and in the years 2010-2013 funding for basic education decreased, while funding for secondary and post-secondary education remained relatively constant. For many low-income countries, where development assistance contributes a substantial share of funding for education, this marked change in trends is important. As a reference, in 2012 development assistance accounted for more than 20 percent of all domestic spending on basic education in recipient low-income countries.17

EducationAidWatch_ODA_Education
Total development assistance for education by level, 2003-2013 – Figure 5 in the report Education Aid Watch 2015

The share of development assistance for education going to Sub-saharan Africa has decreased

The reductions in development assistance funds for primary education have been coupled with important changes in regional priorities. Specifically, the share of development assistance for primary education going to sub-Saharan Africa has been decreasing sharply since the agreement of the Millennium Development Goals.

The following chart shows this: sub-Saharan Africa’s share in total aid to primary education declined from 52 percent in 2002 to 30 percent in 2013, while the continent’s share in the total number of out-of-school children rose from 46 percent to 57 percent.

Brookings_ODA_EduAfrica
Share of primary education disbursements from development assistance going to Sub-Saharan Africa, 2002-2013 – Figure 2.6 in Steer and Smith (2015)17

This pattern is something specific to the education sector within the broader development assistance landscape: in the healthcare sector, the overall slowdown of flows started a couple of years later, was less abrupt, and affected proportionally less the sub-Saharan countries.18

Indeed, recent studies further highlight that development assistance for education is significantly different from assistance for healthcare in other ways: the education sector attracts less earmarked funding through multilaterals, and includes a smaller proportion of resources that developing governments can directly control for programming.19

You can read more about development assistance for healthcare in our article on healthcare spending.

Development assistance priorities have the ability to increase or reduce expenditure inequalities

We mentioned above that public spending on education has translated, in the long run, into lower inequality in education outcomes across most of the world. But for any given country, with a given income distribution and demographic structure, the extent to which public spending on education contributes to reducing inequality depends crucially on the way in which spending is focused across education levels.

The recent UNICEF report The Investment Case for Education and Equity shows that in low-income countries, on average 46 percent of public resources are allocated to the 10 percent of students who are most educated – while this figure goes down to 26 and 13 percent in lower-middle and upper-middle income countries respectively.

The following visualization shows further details on the concentration of public spending across different countries. The vertical axis shows the percentage of public education resources going to the 10% most educated or 10% least educated students – as we can see expenditure is heavily concentrated at the top in many low-income countries.

The earlier remarks about trends in international education financing flows (namely that aid is very important in low-income countries, and that a relatively low and shrinking share of aid is going to primary levels), suggest that inequality in public spending may worsen in low-income countries. Yet development assistance priorities have the ability to change this.20

UNICEF Education Expenditure Concentration
Percentage of public education resources going to the 10% most educated or 10% least educated students – Figure 29 in The Investment Case for Education and Equity (UNICEF - 2015)

What determines educational finance?

The big picture

Why do governments finance education?

One of the reasons to justify government intervention in the market for education, is that education generates positive externalities.21 This essentially means that investing in education yields both private and social returns. Private returns to education include higher wages and better employment prospects. Social returns include pro-social behavior (e.g. volunteering, political participation) and interpersonal trust.

The following chart uses OECD results from the Survey of Adult Skills to show how self-reported trust in others correlates with educational attainment. More precisely, this chart plots the percentage-point difference in the likelihood of reporting to trust others, by education level of respondents. Those individuals with upper secondary or post-secondary non-tertiary education are taken as the reference group, so the percentage point difference is expressed in relation to this group.

As we can see, in all countries those individuals with tertiary education were by far the group most likely to report trusting others. And in almost every country, those with post-secondary non-tertiary education were more likely to trust others than those with primary or lower secondary education. The OECD's report Education at a Glance (2015) provides similar descriptive evidence for other social outcomes.

The conclusion is that adults with higher qualifications are more likely to report desirable social outcomes, including good or excellent health, participation in volunteer activities, interpersonal trust, and political efficacy. These results hold after controlling for literacy, gender, age, and monthly earnings.

OECD_Education_Trust
Likelihood of reporting to trust others, by educational attainment, OECD 2012 – Figure A8.4 in Education at a Glance (2015)22

Do countries that spend more public resources on education tend to have better education outcomes?

Education outcomes are typically measured via 'quantity' output (e.g. years of schooling) and 'quality' output (e.g. learning outcomes, such as test scores from the Programme for International Student Assessment – PISA).

The following visualization presents three scatter plots using 2010 data to show the cross-country correlation between (i) education expenditure (as a share of GDP), (ii) mean years of schooling, and (iii) mean PISA test scores.

At a cross-sectional level, expenditure on education correlates positively with both quantity and quality measures; and not surprisingly, the quality and quantity measures also correlate positively with each other.

But obviously correlation does not imply causation: there are many factors that simultaneously affect education spending and outcomes. Indeed, these scatterplots show that despite the broad positive correlation, there is substantial dispersion away from the trend line – in other words, there is substantial variation in outcomes that does not seem to be captured by differences in expenditure.

Edu_OutcomesVsExpenditure
Correlation between education outcomes and education expenditure (2010 data)23

Does cross-country variation in government education expenditure explain cross-country differences in education outcomes?

The following visualization presents the relationship between PISA reading outcomes and average education spending per student, splitting the sample of countries by income levels.

It shows that income is an important factor that affects both expenditure on education and education outcomes: we can see that above a certain national income level, the relationship between PISA scores and education expenditure per pupil becomes virtually nonexistent.

Average reading performance in PISA and average spending per student
Average reading performance in PISA and average spending per student from the age of 6 to 15 - Figure 1 in OECD (2012)24

Several studies with more sophisticated econometric models corroborate the fact that expenditure on education does not explain well cross-country differences in learning outcomes.25

School inputs

Each education system is different, but improving teacher quality is often more effective in improving learning outcomes than increasing the number of teachers per pupil

A vast number of studies have tried to estimate the impact of classroom resources on learning outcomes.

The following table summarizes results from the systematic review in Hanushek (2006).26 In this table, the left-hand side summarizes results from econometric studies focusing on developing countries, while the right-hand side presents evidence from the US (where studies have concentrated extensively).

We can see that for all listed inputs and across all countries, the share of studies that have found a positive effect is small – in fact, the majority of studies find either no effect or a negative effect. This clearly does not mean that these classroom resources are not important, but rather that it is very difficult to know with confidence when and where they are a binding constraint to improve learning outcomes.

A first conclusion, therefore, seems to be that context and input mix are fundamental to improving outcomes – even in developing countries where the expected returns to additional resources is large across the board.

Taking the ratio of positive to negative effects detected in the literature as a proxy for what tends to work best, we can derive a second conclusion from the table: spending more resources on better teachers (i.e. improving teacher experience and teacher education) tends to work better to improve learning outcomes than simply increasing the number of teachers per pupil. This seems to be true both in developed and developing countries.

This last conclusion is consistent with the main message from the OECD's report Does money buy strong performance in PISA?, which points out that countries that prioritized the quality of teachers over class sizes performed better in PISA tests.27

This is is also consistent with a recent high-quality study on the impact of teacher quality on test scores using data from the US, which suggests that improvements in teacher quality can causally raise students’ test scores.28

Hanushek_Supply_Interventions
Percentage distribution of the estimated effect of selected key resources on student performance – based on Tables 3 and 6 in Hanushek (2006)29

Remedial teaching can yield substantial improvements in learning outcomes

Education in low-income countries is particularly difficult because there is substantial heterogeneity in the degree of preparation that children have when they enter school – much more so than in high-income countries.

Evidence from policy 'experiments' in developing countries suggests remedial teaching, in the form of assistants teaching targeted lessons to the bottom of the class, can yield substantial improvements in learning outcomes.

The following visualization summarizes the effects of four different policy treatments within the so-called Teacher Community Assistant Initiative (TCAI) in Ghana – this is an initiative that evaluated four different such remedial teaching interventions.30

The units in this figure are standard deviations of test results. The first two sets of estimates correspond to the test-score impacts of enabling community assistants to provide remedial instruction specifically to low-performing children, either during school or after school. The third set of estimates corresponds to test-score impacts of providing a community assistant and reducing class size, without targeting instruction to low-performing pupils. The last set of results corresponds to testing the effect of training teachers to provide small-group instruction targeted at pupils’ actual learning levels.

As we can see, while all interventions had a positive effect, the lowest impacts – across all tests – come from the non-targeted 'normal curriculum' intervention that reduced class sizes, and from the intervention that provided training to teachers on how to engage in targeted remedial teaching themselves. This suggests that the improvements in outcomes were caused by the combination of targeted instruction and TCAs who, unlike teachers, were specifically dedicated to this purpose. These results are consistent with findings from across Africa, suggesting that teaching at the right level causes better learning outcomes in a cost-effective way.31

TCAI_RemedialTeaching_JPAL
Summary of treatment effects from the Teacher Community Assistant Initiative (TCAI) in Ghana (estimates by test subject in standard deviations) – Page 2 in Innovations for Poverty Action (2014)32

Are pay-for-performance teacher contracts an effective instrument to improve learning outcomes?

We have already made the point that the bulk of education expenditure goes specifically towards financing teachers. We have also pointed out that improving teacher quality may be a particularly good instrument to improve teaching outcomes. This leads to a natural question: are pay-for-performance teacher contracts an effective instrument to improve learning outcomes? A growing body of literature in the economics of education has started using randomized control trials (i.e. policy 'experiments') to answer this question. Glewwe and Muralidharan (2016) provide the following account of the available evidence:

"Results suggest that even modest changes to compensation structures to reward teachers on the basis of objective measures of performance (such as attendance or increases in student test scores) can generate substantial improvements in learning outcomes at a fraction of the cost of a "business as usual" expansion in education spending. However, not all performance pay programs are likely to be effective, so it is quite important to design the bonus formulae well and to make sure that these designs reflect insights from economic theory." 33

The conclusion is that well-designed pay-for-performance contracts are a cost-effective instrument to boost test scores; but this does not mean that they are necessarily effective at achieving other – perhaps equally important – objectives of time spent in school. In simple words, it is possible that pay-for-performance yields 'teaching to the test'.

Other incentive mechanisms, such as community-based monitoring of teachers, have been proposed as an alternative. Glewwe and Muralidharan (2016) also provide a review of the – somewhat limited – available evidence on such alternative incentive mechanisms.34

Household inputs

School attendance and student effort are responsive to incentives

Demand-side inputs are as important as supply-side inputs to produce education. Attending school and exerting effort are perhaps the most obvious examples: without these inputs, even the best-endowed schools will fail to deliver good outcomes.

The table summarizes information on different demand-side investments that have been shown to successfully improve quality and quantity outcomes. More precisely, this table gathers evidence from randomized control trials in developing countries, as per the review in Glewwe and Muralidharan (2016). The reported figures correspond to positive/negative significant/insignificant estimates across a set of available experimental studies (bear in mind some studies estimate more than one effect – e.g. by measuring outcomes at several points in time).

As we can see, the evidence suggests interventions that increase the benefits of attending school – such as conditional cash transfers – are likely to increase student time in school. And those that increase the benefits of higher effort and better academic performance – such as merit scholarships – are likely to improve learning outcomes.35.

Glewwe2016_DemandInterventions_RCTs
Summary of impacts for selected demand-side interventions on education outcomes in developing countries – based on Tables 4 and 5 from Glewwe and Muralidharan (2016)36

Targeting health problems can be a particularly cost-effective way of increasing school attendance

In many low-income countries, health problems are an important factor preventing children from attending school.

The following visualization presents a comparison of the impact that a number of different health interventions have achieved in different countries – together with some non-health-related interventions that serve as references. The height of each bar in this graph reflects the additional school years achieved per hundred dollars spent on the corresponding intervention; so these estimates can be interpreted as a measure of how cost-effective the different interventions are.37

We see that treating children for intestinal worms (labeled 'deworming' in the chart) led to an additional 13.9 years of education for every $100 spent in Kenya; while a program targeting anemia (labeled 'iron fortification') led to 2.7 additional years per $100 in India. These interventions seem to be much more cost-effective in improving test scores than conditional cash transfers, free school uniforms, or merit scholarships.38

Of course, ranking these interventions is not trivial since most programs achieve multiple outcomes – indeed, we have already discussed that remedial teaching is generally effective to increase test-scores, although here we see a particular instance where it had no impact on school attendance.

Nevertheless, health interventions seem to be particularly interesting, since they lead to substantial achievements in both education and health outcomes.39

CEA_SchoolParticipationRCTs_JPAL
Impact of selected demand-side interventions on school participation in developing countries (Additional years of student participation per $100) – Figure 8.1 in Dhaliwal et al. (2012)40

How important are pre-school investments?

The environment that children are exposed to early in life plays a crucial role in shaping their abilities, behavior, and talents. To a great extent, this is what drives large and remarkably persistent gaps in education achievement between individuals in the same country, but in different socioeconomic environments. Cunha et al. (2006) provide a detailed account of the theory and evidence behind this claim and discuss its implications for the design of education policies.

In the chart, we see the impacts of the Perry Preschool Program – a flagship experimental intervention study, designed to test the impact of preschool education on subsequent education outcomes.41

The chart shows disadvantaged children participating in the preschool program (the 'treatment group') had higher grades and were more likely to graduate from high school than the reference control group. Moreover, they spent substantially less time in special education. Other programs have similarly shown evidence of very large and persistent returns to early education interventions.

Cunha2006_Preschool_Impact
Educational effects from participating in the Perry Preschool Program – Figure 14B in Cunha et al (2006)42

Interactive Charts on Education Spending

Endnotes

  1. See the Wikipedia entry on compulsory education for a table of the ages of compulsory schooling around the world.

  2. As per estimates from Adam Szirmai, (2015) The Dynamics of Socio-Economic Development.

  3. As per estimates of Gini coefficients for the distribution of school years in Crespo Cuaresma, J., KC, S., & Sauer, P. (2013). Age-specific education inequality, education mobility and income growth (No. 6). WWWforEurope.

  4. As per estimates reported in Steer L. and K. Smith (2015), Financing education: Opportunities for global action. Center for Universal Education.

  5. As per 2015 enrolment estimates from the NCES.

  6. An article from the Huffington Post highlights this point, including interesting visualizations documenting the important role that federal funding plays in reducing expenditure inequalities.

  7. Lindert, Peter H. Growing public: Volume 1, the story: Social spending and economic growth since the eighteenth century. Vol. 1. Cambridge University Press, 2004.

  8. Lindert, Peter H. Growing Public: Volume 1, the story: Social spending and economic growth since the eighteenth century. Vol. 1. Cambridge University Press, 2004.

  9. Bear in mind that the estimates from the National Center for Education Statistics are not broken down by source of funds. Rather, they show expenditure by type of institution – which is not equivalent, since public institutions may spend private resources, and vice versa.

  10. In 2010, high-income countries spent 6721 US PPP dollars per primary school pupil. Low-income countries, in contrast, spent 115 US PPP dollars per pupil (UNESCO EFA Global Monitoring Report 2014).

  11. Jesus Crespo Cuaresma, Samir K.C., and Petra Sauer (2013) – Age-Specific Education Inequality, Education Mobility and Income Growth. WWWforEurope working paper; Working Paper no 6.

  12. Data from Petra Sauer (2016) – The Role of Age and Gender in Education Expansion. Working Paper.

  13. Strictly speaking, for this spending pattern to be truly progressive there must be subsidies or income-contingent loans to guarantee that low-income students can also access tertiary education and reap the private benefits from this type of investment.

  14. The OECD provides country-specific figures. However, there is relatively little variation across OECD countries in this respect. This is explained by near-universal enrolment rates at these levels of education and the demographic structure of the population.

  15. This is a stylized fact of OECD education spending. In all the OECD countries, the share of spending devoted to the compensation of teachers is by far the largest component of current expenditure. Moreover, expenditure on teachers' compensation is larger at the combined primary, secondary, and post-secondary non-tertiary levels of education than at the tertiary level. See Table B6.2 in Education at a Glance (2015) for details on the breakdown of current expenditure across all OECD countries by education level.

  16. Welch, F., & Hanushek, E. A. (2006). Handbook of the Economics of Education, Two Volumes. North Holland.

  17. Steer L. and K. Smith (2015), Financing education: Opportunities for global action. Center for Universal Education. Available Online from the Brookings Institution

  18. The share of development assistance going to sub-Saharan Africa has decreased as a whole – from 55 percent in 2002 to 40 percent in 2013 –, but as we note the drop specifically for primary education has been steeper.

  19. Steer L. and K. Smith (2015), Financing education: Opportunities for global action. Center for Universal Education.

  20. The conclusion from these figures is that, while public spending does reduce education inequality in low-income countries, remaining inequalities could be further reduced by shifting resources towards lower levels of education. This evidently does not mean that resources should be shifted – low-income countries and aid donors may have other objectives apart from reducing inequality. But the case for reducing inequality at the bottom is very strong, and some studies suggest that returns to education at the primary level might be higher than at post-primary levels in low-income countries (for a discussion of the vast literature on returns to education, and the ongoing debate on the validity of estimates, see Heckman, J. J., Lochner, L. J., & Todd, P. E. (2006). Earnings functions, rates of return and treatment effects: The Mincer equation and beyond. Handbook of the Economics of Education, 1, 307-458. ).

  21. That positive externalities justify government intervention in the provision of education is essentially an efficiency argument. The logic is that individuals may not spend enough on education because they fail to internalize the positive effect that their education has on other people. But there are, of course, also equity arguments to justify government intervention in the provision of education – for instance, reducing inequality in education may be of intrinsic value, or may be instrumental in reducing inequalities in other outcomes.

  22. As per the source notes: "Percentage-point difference reflects the relative change of reporting to trust others compared to the reference category. For example, in Norway, the percentage of individuals with tertiary education reporting to trust others increases by 20 percentage points compared to someone who has upper secondary or post-secondary non-tertiary education. Similarly, after accounting for literacy proficiency, the percentage of individuals with tertiary education increases by 16 percentage points compared to someone who has upper secondary or post-secondary non-tertiary education."

  23. Data on expenditure corresponds to 2010 total government education expenditure across all levels, as a share of GDP (source: World Bank Education Statistics). Data on PISA scores corresponds to 2010 mean average test scores across categories – mathematics, reading, and science (source: OECD PISA). Data on years of schooling corresponds to 2010 mean years of schooling for the population aged 15 and over (source: Barro Lee Education dataset)

  24. Does money buy strong performance in PISA? - OECD. Available online here.

  25. For a discussion of the evidence supporting this claim, see Hanushek, E. A., (2006). School Resources. Handbook of the Economics of Education, 2.

  26. Hanushek, E. A., (2006). School Resources. Handbook of the Economics of Education, Volume 2. Elsevier.

  27. This claim is clearly only descriptive since there are many underlying variables that simultaneously drive teacher characteristics and student outcomes in any particular country. Indeed, most of the available evidence on whether teacher quality and quantity matters is difficult to interpret causally, as it is hard to find instances where teacher quality/quantity varies exogenously. A recent study concludes on the topic: "teachers vary in many ways, but we found no high-quality studies that have examined the impact of teacher characteristics on student learning or time in school" (source: page 696, Glewwe, P. and Muralidharan, K. (2016) Improving Education Outcomes in Developing Countries: Evidence, Knowledge Gaps, and Policy Implications. Handbook of the Economics of Education, Volume 5. )

  28. Chetty, Raj, John N. Friedman, and Jonah E. Rockoff. 2014. “Measuring the Impacts of Teachers I: Evaluating Bias in Teacher Value-Added Estimates.” American Economic Review, 104(9): 2593-26

  29. Hanushek, E. A., (2006). School Resources. Handbook of the Economics of Education, 2.

  30. Further details in Innovations for Poverty Action, 2014. Implementation Lessons: The Teacher Community Assistant Initiative (TCAI).

  31. For further details, see: Glewwe, P. and Muralidharan, K. (2016) Improving Education Outcomes in Developing Countries: Evidence, Knowledge Gaps, and Policy Implications. Handbook of the Economics of Education, Volume 5. Elsevier. (Link to working paper)

  32. Innovations for Poverty Action (2014). Implementation Lessons: The Teacher Community Assistant Initiative (TCAI).

  33. Glewwe, P. and Muralidharan, K. (2016) Improving Education Outcomes in Developing Countries: Evidence, Knowledge Gaps, and Policy Implications. Handbook of the Economics of Education, Volume 5. Elsevier.

  34. They conclude that "evidence on the impact of monitoring on time in school is scarce and not encouraging...[while] the evidence of the impact of monitoring on student learning is only somewhat more encouraging"

  35. See Glewwe and Muralidharan 2016 for further details on the underlying policy interventions, plus further evidence and discussion of results

  36. Glewwe, P. and Muralidharan, K. (2016) Improving Education Outcomes in Developing Countries: Evidence, Knowledge Gaps, and Policy Implications. Handbook of the Economics of Education, Volume 5. Elsevier. (Link only to working paper)

  37. Bear in mind that the reported gains in school years are a measure of the total impact of the program across the treated population, rather than impact per treated student. Further information on cost-effectiveness analysis is available from the source of the graph.

  38. Further details on all interventions available in: Dhaliwal, I., Duflo, E., Glennerster, R., & Tulloch, C. (2013). Comparative cost-effectiveness analysis to inform policy in developing countries: a general framework with applications for education. Education Policy in Developing Countries, 285-338.

  39. For an analysis of the literature on the impacts of mass deworming see: Croke, Kevin, Joan Hamory Hicks, Eric Hsu, Michel Kremer, and Edward Miguel. 2016. “Does Mass Deworming Affect Child Nutrition? Meta-analysis, Cost-effectiveness, and Statistical Power.” Working Paper.

  40. Dhaliwal, I., Duflo, E., Glennerster, R., & Tulloch, C. (2013). Comparative cost-effectiveness analysis to inform policy in developing countries: a general framework with applications for education. Education Policy in Developing Countries, 285-338.

  41. More specifically, the Perry preschool 'experiment' consisted of enrolling 65 randomly selected black children in a pre-school program, and comparing their outcomes later in life against those achieved by a control group of roughly the same size. The treatment consisted of a daily 2.5-hour classroom session on weekday mornings and a weekly 90-minute home visit by the teacher on weekday afternoons to involve the mother in the child's educational process. More information and details on the intervention are available in Cunha et al. (2006).

  42. Cunha, F., Heckman, J. J., Lochner, L., & Masterov, D. V. (2006). Interpreting the evidence on life cycle skill formation. Handbook of the Economics of Education, 1, 697-812.

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Max Roser and Esteban Ortiz-Ospina (2016) - “Education Spending” Published online at OurWorldInData.org. Retrieved from: 'https://ourworldindata.org/financing-education' [Online Resource]

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@article{owid-financing-education,
    author = {Max Roser and Esteban Ortiz-Ospina},
    title = {Education Spending},
    journal = {Our World in Data},
    year = {2016},
    note = {https://ourworldindata.org/financing-education}
}
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