VoxEU Column Education

How do policies influence the investment in higher education?

OECD governments spend a lot on education, but are their investments paying off? This column analyses how public policy affects individuals’ decisions to invest in education and identifies opportunities for reform.

In many OECD countries, the quality of higher education has suffered from growing enrolments while public resources have been limited by other competing demands on social spending. Moreover, long courses increase the costs of education per individual while not really being suited for today's changing world. Public money is being spent to grant free access to universities to all, but is this public subsidy well-designed (Bagues, Labini, Zinovyeva 2008)? After all, future graduates can appropriate the benefits from their investment in education and many students would enrol in the university even without these subsidies. Public money might be better used to educate those who really need it. Moreover, how can national support for students be reconciled with increasingly internationally mobile skilled labour? In this context, what policies could governments adopt to increase graduation rates while improving higher education’s efficiency and equality of access?

In a recent OECD working paper (Oliveira Martins et al., 2007) we identify a number of policy levers to pursue these goals. We stress the need to introduce an efficient and accountable institutional set-up of higher education, the importance of providing attractive private returns to education to prospective students, and the need for individual funding mechanisms to help overcome liquidity constraints that may restrict access to higher education.

The rates of investment in higher education differ across OECD countries

As measured by the graduation ratios (e.g. the number of new graduates over the population 20-29), there are significant differences in higher education investment patterns across OECD (Figure 1). Korea, New Zealand and Japan record the highest graduation rates while Turkey, Mexico and Greece lag furthest behind. Graduation ratios have been growing steadily everywhere and much faster for females than males, almost converging to gender parity.

Figure 1. New tertiary graduates’ share of population aged 20-29 (1)



Notes: 1) Tertiary graduates cover all individuals, including individuals over 29. 2) For Mexico and New Zealand: 1996, for Iceland: 1998, Switzerland: 1999, Belgium and Poland: 2000.

What are the main determinants of investment in tertiary education?

The individual incentives to invest in higher education essentially consist of a higher future stream of earnings after graduation, often called wage premia (Becker 1967). In OECD countries, wage premia are close to 55% over secondary educated workers, ranging from around 20% for Spanish men and 30% for Austrian women to above 100% for both men and women in Hungary (Strauss and Maisonneuve, 2007).

A more comprehensive measure of incentives to undertake higher education is obtained by adjusting wage premia by a number of factors (taxation, employment probability, unemployment benefits, tuition fees, and opportunity costs of studying). The resulting calculation is the internal rates of return to education (Figure 2), which, from a life-cycle perspective, can be interpreted as the discount rate that equates the future benefits with the costs of higher education (Boarini and Strauss, 2007).

These rates vary from over 4% to nearly 14% in 2001 for the 21 OECD countries covered by our analysis, with an average return (across both countries and gender) of 8.5%, which is substantially higher than current real interest rates. Relatively low returns are found in Spain, Italy, Netherlands, Sweden and Belgium. They are driven by below average net labour market premia, despite low costs of education. In contrast, Ireland, the UK, and Portugal have high returns for all genders driven by high wage premia, reinforced either by high employability premia and/or low costs of education.

Figure 2. Private internal rates of return to education in the OECD, 2001

Note: The rates of return include labour market, employability, unemployment, and pension premia associated with tertiary education and are adjusted for taxation. They also include the opportunity and direct costs of education. They are calculated assuming that labour productivity grows at 1.75% per year in all countries. Data for Poland and Switzerland are from 2000 and for Hungary 1997.

Investment in higher education is also influenced by access to financing. The degree of financial and/or liquidity constraints faced by prospective students can be crudely approximated by the ratio of average annual expenses during study for a higher degree (tuition fees and living costs) to the sum of the available sources of financial support. These include available individual loans and grants and family resources, whose estimate requires less straightforward assumptions. Our calculations show that student financing varies greatly. Some countries have created universal loan systems (e.g. most English-speaking countries), while others provide generous grants (e.g. Nordic countries), but the majority of countries still rely mainly on family transfers, making students financially constrained. Even where tuition fees are heavily subsidised, living costs represent a significant share of resources for a median household.

On the supply side, university systems’ characteristics influence educational investment. For example, a system that better matches students’ preferences (e.g. offers more programme choices) is likely to attract more students. In addition, systems offering shorter courses and intermediate diplomas are more attractive since they provide students with the option of deciding when to stop the investment (see Heckman et al., 2005). For similar reasons, those systems may induce lower dropout rates when students are relatively impatient to start participating in the labour market.

Based on a survey of OECD countries, we constructed a summary indicator of the supply of higher education (Figure 3). The indicator covers three main categories: the flexibility and autonomy to manage inputs (e.g. sources of funding, staff) and outputs (e.g. short-term studies), and accountability (e.g. evaluation and funding rules). For example, funding rules based on outputs, such as graduation and quality rankings are supposed to generate more accountability than rules based on grandfathering or inputs (e.g. number of students). It is important that the three dimensions are well balanced, as providing autonomy without enough accountability mechanisms may generate dysfunctions in the system.

Figure 3. A composite supply indicator of higher education systems, 2005-2006

Note: Canadian provinces are: Al: Alberta, BC: British Columbia, Ma: Manitoba, NB: New Brunswick, On: Ontario, Qu: Québec and Sa: Saskatchewan. Belgian regions are: Fr: French Community, Fl: Flemish Community and D: German-speaking Community. The bars correspond to 95% confidence intervals obtained through a large number of simulated random weights. In interpreting this value for US federal provisions concerning supply flexibility and accountability it should be taken into account that federal funds only account for a small share of total funding of US tertiary education institutions.
Source: Authors’ calculations based on a survey on the institutional set-up of tertiary education

The composite indicator is significantly below average for Greece, Germany, Belgium (French-speaking regions), Turkey and France, indicating that these countries/regions have relatively centralised and administrative-based systems. The countries/regions with the more flexible and incentive-based systems are New Zealand, Australia, Texas, Ohio, three Canadian provinces, the UK and Mexico. The blue bands in Figure 3 correspond to a test of the sensitivity of the results to randomly selected weighting schemes.

Implications and avenues for reform

Our analysis suggests that demand and supply determinants account for the observed variability of graduation ratios over time, across countries and gender. Even if the mix and focus of higher education reform will depend on each country's specific conditions, the framework developed in our work enables policymakers to identify various options for reforming higher education systems, each of them requiring arbitration among a number of public policy objectives. These are general principles based on our empirical work, which may be complemented by more detailed institutional analysis and country-specific information (see Santiago et al., 2008).

The main reform avenues identified are:

i) Modify higher education systems to provide more autonomy and accountability to universities. Offering more diversified study programs, for instance shorter grades or two-tier modules, could help meeting individual demands for education more effectively.

ii) Make individuals aware of both the cost and the future returns of their investment, possibly by contributing to the financing of higher education

iii) Provide universal-based individual financing of higher education in order to ease liquidity constraints

Raising fees may improve incentives and reduce study duration, but it may also negatively impact returns and tighten liquidity constraints, jeopardising equality of access. Our numerical simulations stress the need to develop adequate individual financing systems for students when tuition policies are considered. Even with low tuition fees, a student loan system to finance the direct and living costs of higher education would help maintain equality of access.

In general, policies improving the dynamism of labour markets may improve educational attainment by making part-time work more accessible to students, thereby reducing the opportunity cost of studying and financial constraints. Finally, a less progressive tax system would increase average returns to higher education but also their variation, so that a greater dispersion of returns might increase the riskiness of investing in education. Thus, all these options have to be carefully gauged in a complementary way with other policies and within each country’s specific context.


Bagues, M.F., M.S. Labini, and N. Zinovyeva (2008), “Paying universities to lower their standards”, VoxEU, 10 September 2008.

Becker, G. (1967), Human Capital and the Personal Distribution of Income: An Analytical Approach, Ann Arbor, Michigan: University of Michigan Press.

Boarini, R. and H. Strauss (2007), "The Private Internal Rates of Return to Higher Education: New estimates for 21 OECD countries", OECD Economics Department Working Papers no. 591.

Heckman, J., L. Lochner and P. Todd (2005), “Earnings Functions, Rates of Return, and Treatment Effects: The Mincer Equation and Beyond”, NBER Working Paper No. 11544.

Oliveira Martins, J., R. Boarini, H. Strauss, C. de la Maisonneuve and C. Saadi (2007), "The Policy Determinants of Investment in Higher Education", OECD Economics Department Working Papers no. 576 (forthcoming in OECD Economic Studies).

Santiago, P., K. Tremblay, E. Basri and E. Arnal (2008), “Tertiary Education for a Knowledge Society”, Synthesis Report on OECD Thematic Review of Tertiary Education.

Strauss, H. and C. de la Maisonneuve (2007), "The wage premium on Tertiary Education: micro-data evidence for 21 OECD countries", OECD Economics Department Working Papers no. 589.

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