This chapter assesses whether promoting equity in opportunities to access and complete higher education remains a relevant objective across EU and OECD member countries. It also presents international evidence on three overarching factors that are important in influencing the educational opportunities of young people from lower-income backgrounds: prior achievement, financial support, and access to information. It subsequently constructs an analytical framework to structure an analysis of equity of opportunity in higher education systems.
Higher Education in Portugal
Policies for Access and Success
Abstract
The landscape of higher education has turned toward massification in recent decades, which means that participation in higher education has increased across social groups. Although the student body is more diverse today than in the past, it is not fully representative of the population of young people. This indicates that there are underlying inequities in the education system, which mean that certain groups of students face relative disadvantage in accessing and participating in higher education.
Improving equity in opportunity to pursue higher education helps to ensure that individuals with academic potential can access and complete higher education programmes and is an important part of delivering a highly skilled workforce. This is essential to stimulate higher innovation and economic growth, while also helping to make efficient use of public and private funds invested in the higher education system.
There is a growing international consensus on the importance of promoting equity in higher education. European countries involved in the Bologna Process, and thus members of the European Higher Education Area (EHEA), have committed to working on the “social dimension” of higher education. They have agreed to the objective that the higher education student body should be representative of wider society. Relatedly, the OECD Council has a legal Recommendation on Creating Better Opportunities for Young People that recognises that the successful engagement of young people in the labour market and society is crucial not only for their own personal economic prospects and well-being, but also for overall economic growth and social cohesion. The OECD Ministerial Declaration “on Building Equitable Societies Through Education” acknowledges the specific role of education and skills in strengthening economic and social outcomes across countries.
This report focuses on equity from the perspective of parental income and socio-economic status. Beyond parental income, other personal and demographic aspects can be important to analyse equity of opportunity, including, for example, variations by migrant background, ethnic minority background, disability and special educational needs. These relevant aspects warrant further analysis since remain outside the scope of this report. The report will adopt a more narrow understanding of equity of opportunity, focusing on whether the education system provides students with the support and resources they need to reach their full potential and allows them to compete with their peers on a level playing field no matter their parental income. Strengthening equity of access can create learning environments that open doors for all learners, giving them fair opportunities to succeed in future (OECD[1]).
More specifically, the report considers equity of opportunity related to widening the access for young people to public higher education, and the opportunities for public higher education students to succeed in their programmes. While it is recognised that the access of mature students to higher education is relevant from an equity perspective, the report has narrowed its scope to consider the opportunities of secondary education students to immediately transition to higher education following their graduation.
Much research has been undertaken to understand the factors that can influence the success of lower-income students in enrolling in and completing higher education programmes. Drawing on Boudon (1974[2]), a distinction can be made between differences in education outcomes by socio-economic background that are due to differences in ability or performance, and differences that are due to decisions made when holding ability constant. Differences in ability are often referred to in this literature as “primary effects” of parental income, while differences in decisions are referred to as “secondary effects”. This report is primarily interested in “secondary effects” of parental income on outcomes.
This report is the final output of a project funded and implemented with the European Union’s Technical Support Instrument (TSI) entitled “Making Higher Education in Portugal More Inclusive”. The project has analysed how to promote the equity of opportunity for lower-income students in higher education in Portugal. This final report is delivered alongside a more detailed policy action plan with concrete policy proposals, and a piloting roadmap with suggestions for how to implement these proposals and to monitor progress.
This chapter starts by demonstrating why countries need to continue to focus on promoting widened access and student completion rates, before noting the international consensus on the need for policy action in the field. Subsequently, the chapter summarises international research and describes some of the most important factors that influence opportunities to participate in higher education, and how they are systematically influenced by parental income and socio-economic background. Finally, it builds an analytical approach to assess inequities in access and completion of higher education, in order to provide a foundation for understanding the scope of further policy action.
Promoting widened access and supporting student success is important to help ensure that young people can thrive in a changing labour market and optimise the use of public funds when building a high-skilled workforce. It can also reinforce democratic values by ensuring equity of opportunity. There is a long-standing and broadly shared international consensus around the importance of ensuring equity of opportunity in education, which is highlighted through the Social Dimension of the Bologna Process, the European Union’s European Strategy for Universities and OECD Legal Instruments related to young people and equity in education.
International research identifies at least three key overarching factors that reinforce variations in access to, and completion of, higher education between students from different groups of parental income and socio-economic status: prior achievement, financial support and information.
In most higher education systems, applicants are required to fulfil certain criteria related to prior achievement to be eligible to participate in higher education, including attending the relevant study orientations and proving sufficient academic ability. However, achievement outcomes vary by socio-economic background and build over the course of children’s lives. Upper secondary education achievement, typically measured in terms of test scores, tends to be influenced by factors such as the quality of teaching, the type of school attended and access to tutoring, all of which tend to vary by parental income.
Financial costs associated with higher education studies can be substantial – in terms of tuition fees, living costs (especially for mobile students) and the opportunity cost of not working. The willingness and ability to cover these costs will depend directly on the financial capacity of students and their families to cover such costs but also indirectly on the foreseen risks and benefits, upfront cost and student finance system. Both direct and indirect factors vary by parental income.
Access to information about relevant opportunities shape aspirations and plans to attend higher education. The information received from school career guidance and higher education outreach is influenced by school-level policies and the geographic location of the family home. Social connections, including parental expectations and peer effects, also typically depend on parental income, and can shape aspirations.
Since these three factors strongly contribute to defining the opportunity sets of students as they approach the end of upper secondary education, they play a central role in the analytical framework developed for this report. Student outcomes across these three factors influence the outcomes of interest: access to higher education, access to the most selective programmes and completion rates.
Participation rates in higher education in developed economies have increased substantially in recent decades. The general expansion of higher education accelerated after 1960 with the development of welfare states, rising aspirations among a greater proportion of the population and increased labour-market demand for higher education graduates stemming from technological investment and increasingly advanced economies (OECD, 2020[3]). Government interventions have fuelled this expansion in efforts to promote economic development and equal opportunities, and enrolling over half of new secondary education graduates in higher education systems each year has become the norm in OECD member countries (Marginson, 2016[4]).
Although the student body in higher education across OECD member countries has become increasingly diverse, nowhere is it fully representative of the wider society in which the higher education system operates. The expansion of higher education has – to some extent at least – widened access to higher education for students from historically under-represented socio-economic groups, but, across countries, young people from lower-income backgrounds are still less likely to attend higher education programmes than their peers from higher-income families.
Continuing to strive for greater equity of opportunity may be viewed as important for at least three key reasons. First, most young people will need advanced skills from some post-secondary education – whether practical or academic – to thrive in a changing labour market. Second, it is valuable to ensure that student ability is well matched to educational opportunities to maximise human capital, notably by tapping the talents of groups that were traditionally under-represented in higher education. In turn, this contributes to an efficient use of public and private funds. Third, many see fairness and equity as intrinsically valuable and as fundamental tenets of democracy.
The aim of improving equity of opportunity in education is a key part of the objectives of the European Education Area (European Commission, 2024[5]) and the European Pillar of Social Rights (European Commission, 2024[6]) which stipulates, in its first principle, that “Everyone has the right to quality and inclusive education, training and life-long learning in order to maintain and acquire skills that enable them to participate fully in society and manage successfully transitions in the labour market”. Several international agreements and declarations also document cross-country political commitment to equity in education, including post-secondary and higher education. These include the Social Dimension of the Bologna Process (European Commission, 2020[7]), the European Union’s European Strategy for Universities (EUR-Lex, 2022[8]), and the OECD Legal Instruments related to young people and equity in education (OECD Legal Instruments, 2022[9]; OECD Legal Instruments, 2022[10])., which are summarised below.
1.3.1. The Social Dimension of the Bologna Process
European countries involved in the Bologna Process have committed to moving towards more equal representation of all sections of society in higher education. The “social dimension” of the Bologna Process was defined as the aspiration that the “student body entering, participating in and completing higher education at all levels corresponds to the heterogeneous social profile of society at large” in the member countries of the European Higher Education Area (EHEA) (Schmidt and Onita, 2023[11]). Since defining the concept of the “social dimension” in the 2007 London communiqué, the Bologna Process ministerial texts have increasingly moved from setting strategic objectives towards discussing practical considerations of the actions required to prioritise the social dimension (European Commission, 2020[7]).
In line with the objective to promote the social dimension, Eurydice (2024[12]) reports in their Bologna Process 2024 Implementation Report that several countries incorporate inclusion, diversity and equity in higher education in strategies concerning the education system as a whole (Albania, Armenia, Estonia, Georgia, Greece, Italy, Latvia, Montenegro, Romania and Türkiye), while others include it in higher education-specific strategies or policy plans (Bulgaria, Czechia, France, Hungary, Kazakhstan, Malta and Slovenia). Some countries have adopted specific strategies or policy plans on the social dimension of higher education (Austria, Croatia, Finland, Ireland, Lithuania, the Netherlands, Switzerland, and the United Kingdom). Meanwhile in Belgium (French Community), the inclusivity of higher education is the explicit aim of a government order (decree) on inclusive higher education, which contains a set of measures similar to that of a strategic document. Finally, five education systems (Liechtenstein, Norway, Portugal, Sweden, and Ukraine), mainstream inclusion or equity in higher education into strategies or plans for a broader range of policy objectives (Eurydice, 2024[12]).
Austria’s 2017-2025 National Strategy on the Social Dimension of Higher Education aims to mainstream the social dimension into education policy making. The national strategy resulted from a rigorous consultation phase involving over 800 experts representing over 80 organisations, undertaken over the course of a year. It defines several quantitative targets that aim to improve equity in higher education and sets out concrete points of action and stakeholders that are to take responsibility for implementation. These activities span three overarching target dimensions: 1) inclusive access; 2) drop-out and academic success; and 3) the regulation of higher education policy. A host of initiatives have been launched under each of these dimensions (Austrian Ministry of Science Research and Economy, 2017[13]).
The national approach is interesting in its potential to promote a joint up approach to widening access. An interim report shows that the social dimension has been anchored within the strategic documents in nearly all higher education institutions and several initiatives have already been launched.
However, there are challenges with monitoring progress. The interim report provides data on indicators for the quantitative targets included in the Strategy that indicate limited progress in achieving the broad targets to date by 2022. Recognising that many of the initiatives likely need more time to take effect, the final report will be more informative about the success of the Strategy in achieving progress. In addition, project-based evaluations might offer more specific insights into what policy actions have worked (Park and Preymann, 2022[14]).
1.3.2. The European Union’s European Strategy for Universities
The European Commission’s 2022 Communication on a European Strategy for Universities (COM/2022/16 final) aims to support universities to adapt to changing conditions and to contribute to Europe’s resilience and recovery, in part by promoting equity (EUR-Lex, 2022[8]). The Strategy recognises excellence and inclusion as distinctive features of European higher education and places particular emphasis on the need to foster diversity, inclusiveness and gender equality in the higher education sector.
The Strategy proposes to focus on achieving four joint key objectives by mid-2024. The first objective is to strengthen the European dimension in higher education and research by implementing a set of flagship initiatives to promote transnational co-operation with a European approach. The Strategy recognises that placing increased responsibilities on universities to support Europe’s economic and social recovery means they will need appropriate financial support. At the same time, it emphasises that any EU funds and programmes must not replace, but operate in addition to, sufficient national public funding and other public and private investments (EUR-Lex, 2022[8]).
The second objective is (particularly notably for the purpose of this report) to support higher education and research as conduits of a European way of life through their threefold focus on 1) quality and relevance for future-proof skills, 2) diversity and inclusion 3) democratic practices, fundamental rights and academic values and freedom of scientific research. The Strategy proposes that flexible and attractive academic careers, valuing teaching, research, entrepreneurship, management and leadership activities should be promoted. It is noteworthy that the Strategy encourages institutions to implement institutional change through concrete measures for diversity and inclusion, including voluntary, quantified targets for inclusion and inclusive gender equality plans, building on the Rome Communiqué (EUR-Lex, 2022[8]).
The third objective is to support the full engagement of higher education institutions in the unfolding green and digital transitions and the fourth objective is to support institutions in becoming more outward looking and competitive on the global scene (EUR-Lex, 2022[8]).
Initiatives to promote equity and inclusion across the EU are also backed by EU funding. First, in the Renewed EU agenda for higher education, the European Commission committed to providing direct Erasmus+ support to help higher education institutions develop and implement integrated institutional strategies for inclusion, gender equality and study success from admission to graduation, including through co-operation with schools and vocational education and training providers (EUR-Lex, 2017[15]). Second, the European Social Fund Plus (ESF+) is the EU’s main instrument for investing in people and focus on ensuring a fair and inclusive recovery from the COVID-19 crisis, giving priority to the objective to promote equal access to quality education and training (European Commission[16]). Finally, the Recovery and Resilience Facility (RRF) is a temporary instrument that is part of the EU’s approach to address the fallout of the COVID-19 crisis (NextGenerationEU). It supports initiatives in several pillars, where reforms and investment in policies for the next generation aim at improving access to general, vocational and higher education, as well as its quality and inclusiveness (European Commission[17]).
1.3.3. The OECD Legal Instruments related to young people and equity in education
In June 2022, the OECD Council adopted a legal Recommendation on Creating Better Opportunities for Young People (OECD/LEGAL/0474) (OECD Legal Instruments, 2022[9]). The Recommendation recognises that the successful engagement of young people in the labour market and society is crucial not only for their own personal economic prospects and well-being, but also for overall economic growth and social cohesion. It also recognises that young people are the backbone of prosperous societies, economies, and fit-for-future democracies. The Recommendation aims to ensure that young people can prosper by gaining adequate skills, employment, access to a social safety net and trust in their governments.
Two specific Recommendations in “Creating Better Opportunities for Young People” are directly relevant to this report on policies to enhance inclusion, widen access and increase student success in higher education (OECD Legal Instruments, 2022[9]):
Recommendation II.5. Provide learner orientation and career guidance, including by engaging with employers through workplace visits, career talks and job shadowing, and providing information on skills in demand in the world of work and the relationship between education and employment.
Recommendation II.6. Enable equitable access to pursue and continue post-secondary education and training by tackling financial and non-financial constraints, especially for young people from under-represented groups, including through reviewing existing financial aid systems for students and, where relevant, tuition fees and student loan forgiveness arrangements.
Following the OECD Council Recommendation on Creating Better Opportunities for Young People, the OECD Education Policy Committee (EDPC) adopted a specific Declaration on Building Equitable Societies Through Education (OECD/LEGAL/0485), at the December 2022 Ministerial meeting (OECD Legal Instruments, 2022[10]). The Declaration states that ministers and representatives of OECD countries call on the OECD to:
Support countries, based on sound evidence, in designing and implementing education and skills policies that recognise the diverse backgrounds and needs of learners, and provide them with effective and equitable opportunities to develop and maintain their potential, and contribute to society.
The OECD Youth Policy Toolkit provides hands-on practical guidance to improve the design and implementation of youth policies and will include good practice examples from OECD member countries (OECD, 2024[18]). These legal instruments and accompanying work at international level provide additional impetus for – and inputs to – this report.
Understanding and addressing inequities in access to and completion of higher education is not straightforward due to complex patterns of multidirectional causality. This section details the key outcome indicators of interest and explores international research on key factors influencing these outcomes.
1.4.1. Three outcome indicators are of key interest when considering the level of equity of opportunity in higher education
This report will focus on indicators that describe three key outcome areas. First, indicators that describe access to higher education for students from lower socio-economic backgrounds is valuable since it lays the foundation for population attainment rates and a high-skilled workforce. The indicators considered in this area focus primarily on students in upper secondary education, including prior achievement, financial support and information they have about their opportunities before applying to and entering higher education. It is also relevant to consider the ability for prospective applicants to plan for their student life, particularly in terms of predictable access to financial support and support to move out of the parental home if needed to access the most selective programme as feasible, considering their entry grades.
Second, indicators that describe access to the most selective programmes for students from lower-income backgrounds give a good indication of whether students from disadvantaged backgrounds are able to compete equitably with students from advantaged backgrounds for the most sought-after study places. The indicators relevant in this area focus on the representation of lower-income students in selective programmes and the quality of the match between students’ academic potential and measures of the quality of the programme they access. Many of the barriers to equitable access to the most selective programmes are similar to those discussed above in relation to entry rates for students in general programmes. However, there are some specificities that are worth highlighting, in particular with relation to the ability to relocate.
Finally, indicators that describe student completion rates are relevant to understand whether widened access fulfil its potential of increasing population education attainment rates. Supporting student completion rates through drop-out prevention and re-enrolment policies can be especially relevant among certain groups of students facing different types of challenges and is not isolated to students from lower-income backgrounds.
The three target outcome areas – deemed to be desirable from an equity perspective – are summarised below:
1. Access to higher education. The overall application, acceptance and enrolment rates are an indication of the degree of access for lower-income students. This outcome area focuses on the transition from secondary education to higher education for all lower-income students, but with a special focus on lower-income students from vocational secondary education programmes.
2. Access to the most selective programmes. The application, acceptance and enrolment rates observed in the most selective programmes are an indication of the degree to which lower-income students have been able to integrate into the most prestigious courses. This outcome area focuses primarily on academically talented lower-income students.
3. Higher education completion rates. The progression and completion rates are indications of the longer-term success of higher education enrolment for lower-income students. This outcome area focuses on all lower-income students who enrol in higher education.
1.4.2. Key factors that shape opportunities to access and complete higher education
This section summarises international research on key factors that shape opportunities to participate in higher education, focusing on the three outcome areas described above: access to higher education; access to the most selective programmes; and completion rates. In order to consider all three of these outcome areas in some detail, the report will assess outcomes in relation to young students only, focusing on the direct transition from secondary education to higher education without considering students who take one or several gap years. As such, access to higher education for mature students – while relevant from an equity perspective – is beyond the scope of this report.
Systemic differences in prior achievement across students from different socio-economic backgrounds
A large portion of inequalities in access to educational opportunities build over the course of childhood and result in great variation of outcomes in secondary education. While it is beyond the scope of this report to consider a life-cycle perspective of the reasons behind this variation in achievements, this section considers how upper secondary education achievements contribute to shaping inequities in accessing and completing higher education, including the most selective programmes. Specifically, this section considers how differences in achievement – typically measured in terms of test scores – can be influenced by the quality of teaching, access to tutoring, and attending the required secondary education orientation for eligibility to participate in higher education programmes.
Test scores in secondary education assessment and national examinations are one of the most important conditions for entering higher education. Passing final school and national exams are often central criteria for graduating from secondary education, as well as a prerequisite to apply to higher education. In nearly all (29) OECD jurisdictions participating in Education at a Glance, national examinations in general upper secondary programmes are intended to grant eligibility for tertiary education (OECD, 2023[19]).
Achieving excellent test scores is also a prerequisite for admission to the most selective higher education programmes. Using data from England, Chowdry et al. (2013[20]) find that test results from school also explain a large part of gaps in enrolment in elite universities. Similar trends have been highlighted in the United States with low grades in secondary school education driving a large part of the low representation of low-income students at elite universities (Chetty et al., 2020[21]).
Poor achievement and preparation in secondary education means that students – if they manage to enrol in higher education – may struggle to progress through their studies and complete their programmes. Student academic achievement in secondary education, measured for instance in terms of their test scores and courses passed during the beginning of academic studies have been shown to be strongly predictive of student success, particularly in the second and third years of programmes (Schmidt, Boero and Méndez Vera, 2023[22]; Delogu et al., 2024[23]; Gonzalez-Nucamendi, Noguez and Neri, 2023[24]). Results in certain particularly challenging courses can be especially important predictors for later success (da Silva et al., 2022[25]).
Yet, achievement gaps by socio-economic status are widely documented. For instance, socio-economic status explained 15% of the variation in mathematics performance within each country across the OECD’s Programme for International Student Assessment (PISA) data collected in 2022, and 14% of the variation in science performance. In the Slovak Republic, Hungary, Czechia, Belgium, France, and Switzerland, students’ socio-economic status accounts for 20% or more of the variation in performance (OECD, 2023[26]). Similarly, most of the socio-economic gap in higher education enrolment of English students in the United Kingdom is explained by academic test scores at age 18 (Chowdry et al., 2013[20]).
Students who attend a prestigious secondary education with high-quality teaching tend to have an advantage in achieving high test results, but also in terms of being better prepared for the requirements of higher education. For instance, secondary schools can provide a significant advantage by teaching useful soft skills, giving relevant and stretching career guidance, and act as a signalling effect for higher education admission offices. It has been shown that the secondary school attended is a major determinant of inequalities in outcomes between students with low- and high-income families in England.
Findings also indicate that attending a high-quality secondary school systematically helps students attend a highly selective higher education programme. Indeed, Campbell et al. (2022[27]) find that the socio-economic gap in how well students can match their academic achievement with a higher education programme is reduced by up to 79% when considering students from the same school. Similarly, Hoxby and Avery (2013[28]) use data from the United States to descriptively show that low-income but high-achieving students only tend to apply to selective higher education institutions if they are from schools in large cities with a critical mass of high achievers that tend to send many students to selective higher education institutions. By contrast, equally well-achieving students from academically weaker secondary schools tend to enrol in less selective institutions.
The inequities in access to education resulting from variations in performance across secondary schools is especially problematic where secondary school quality varies systemically with family income. For instance, the highest-quality secondary school may be fee-paying schools, require entry exams for prospective students, or have catchment areas where house prices are high. Such factors necessitate an elevated family income, and a parental will to invest in their children.
Higher family income can also support higher test scores by investment in additional tutoring, so called “shadow education”, beyond that provided in secondary education. Such private investment can generate high marginal returns in jurisdictions where scores from school-leaving examinations and separate entry examinations for higher education are important. Using cross-national data from the 2012 Programme for International Student Assessment, Zwier, Geven and Werfhorst (2021[29]) show that students from higher socio-economic backgrounds participate in more shadow education than their less well-off peers, and that this relationship tends to be stronger in jurisdictions with high-stakes testing. As such, contexts where there is a lot to gain from private investment in education foster possibilities for greater advantages for those with parental resources.
To achieve the right results, students also must take the required courses in secondary education in order to be eligible for higher education. Many education systems operate with different tracks of study orientations depending on whether students are foreseen to enter the labour market or further studies after secondary education. Students in secondary education programmes with vocational orientation tend to be disadvantaged relative to those in general programmes when applying to higher education, since courses in vocational programmes tend to be less academically rigorous.
While systems are technically designed to support students with higher vocational aptitude into vocational tracks and students with higher academic aptitude into general orientations, this division tends to be disproportionately influenced by the socio-economic background of students. In turn, this reinforces socio-economic gradients in educational opportunities (OECD, 2021[30]). For instance, in the Netherlands where students are sorted into different lower secondary programmes at the age of 12, based on test results and a teacher recommendation, students with high socio-economic status are more likely to enrol in pre-university schools and less likely to enrol in pre-vocational school than students with lower socio-economic status, even when standardised test scores and teacher recommendations are identical (Werfhorst, 2021[31]). Typically, the earlier that tracking happens, the more it depends on parental socio-economic status. This means that early selection into academically greater- and less-demanding orientations tend to mean lower social mobility (Godin and Hindriks, 2018[32]; European Commission, 2020[33]).
This disadvantage can accumulate over the course of a higher education programme. When students from vocational orientations do pursue higher education, they are less likely to complete their studies. OECD data illustrates that there is a gap in the completion rates of bachelor’s degrees (or equivalent) between those enrolling from vocational and general pathways in several jurisdictions. The gap is notable, for instance, in France, Belgium, and Slovenia (OECD, 2022[34]). Similarly, when comparing students with the same secondary education leaving diplomas in the United Kingdom, having vocational qualifications is associated with dropping out and receiving lower final grades in university (Dilnot, Macmillan and Wyness, 2023[35]). Dilnot, Macmillan and Wyness (2023[35]) also find that there is an additional penalty associated with having low socio-economic status and a vocational qualification.
The reliance on financial support systems makes access and completion more uncertain
Financial costs associated with higher education studies can be substantial; and the ability to cover these costs will factor into young peoples’ decision of whether to apply and enrol in higher education. The willingness of students and their parents to pay for these costs will depend on the foreseen benefits and risks, and existing financing opportunities (Box 1.2).
Investing in higher education would typically lead to higher lifetime earnings. There are significant average wage returns to undertaking a bachelor’s degree or equivalent compared to upper secondary attainment across OECD jurisdictions (OECD, 2024[36]). These benefits are greater for longer and higher-quality higher education programmes. For example, Suga (2019[37]) finds significant postgraduate wage premia for both men and women in Japan, even after taking account of self-selection bias. For instance, Canaan and Mouganie (2018[38]) use linked administrative data from France to show that attending higher-quality higher education entails significant earning potential for lower-income students as well as higher-income students.
However, upfront costs can be high for students and their families, particularly if they lack access to student grants or other student financing options. In higher education systems where tuition fees exist, they can be the main out-of-pocket cost experienced by students, along with any additional charges, such as laboratory fees, and costs of required books and supplies (OECD, 2020[3]).
Countries vary significantly in the share of the cost of higher education that is covered by private households, and to what extent private contributions and living cost expenses can be covered through public grants or subsidised, state-backed loans. For instance, the proportion of students who received public grant or loan support ranged from 70-100% in most Nordic and Anglophone systems, to fewer than 30% in Austria, Switzerland, and Portugal (OECD, 2020[3]).
Research indicates that student financial support systems can be effective in promoting enrolment in higher education. The reliance of lower-income students on student finance and scholarships has been shown, for instance, by Steiner and Wrohlich (2012[39]), who estimate the effect from means-tested student aid on enrolment in Germany and find a small but significant positive effect. Joensen and Mattana (2021[40]) use data from Sweden and find a larger effect of grants on student decisions, debt and human capital when alternative means of financing, including part-time work, are costlier. They also find that loan repayment conditions affect drop-out rates significantly more when the share of grants comprising total financing is smaller. Such liquidity constraints are disproportionately faced by families in lower-income brackets who are less likely to be able to put away the often-considerable savings required for tuition fees and living costs.
Costs related to studying may be particularly high for students who need to live away from their parental home, which is particularly relevant for the ability of talented students to move to attend selective programmes. It may therefore be particularly difficult to ensure an optimal matching of students and programme if such living costs need to be covered out of pocket. For example, Lovenheim and Reynolds (2012[41]) show a wealth effect to college attendance in the United States: when housing wealth increases as a child nears college age, the child is more likely to attend a more selective college. Similarly, it has been shown that housing prices play a significant role for students choosing to study abroad, as policy evaluations of the Erasmus+ programme in EU countries have reported (Beine, Noël and Ragot, 2014[42]). Since candidates from lower-income families face greater financial constraints, they are more likely to be required to opt for a local programme.
Higher parental financial resources during university have been shown to be associated with improved graduation rates (Hamilton, 2013[43]; DeAngelo and Franke, 2016[44]). Accessing financial support can therefore be a key factor contributing to higher education students dropping out and is a factor that is more relevant in systems where the costs of studying – including fees and living costs – are high. In the high-fee environment of the higher education system of the United States, research indicates that financial aid significantly affects retention, with varying impacts depending on the type of support and institution (Dynarski, 2003[45]; Singell, 2004[46]). There is more limited evidence from Europe, but Fack and Grenet (2015[47]) find that the eligibility for a EUR 1 500 needs-based cash allowance has a positive and significant impact on students’ persistence rates after the first year. Although the authors do not find significant effects on on-time degree completion for undergraduate students, they do find positive and significant completion effects among master’s students (Fack and Grenet, 2015[47]).
Lower-income students tend to be more likely than higher-income students to have to work long work hours during studies to finance them. Research indicates that high-school graduates from low-income families are more likely to need to work to cover costs related to studying, which can mean that they are at relatively greater risk of not being able to spend sufficient time on their studies (Cabrera, Nora and Castañeda, 1992[48]; Goldrick-Rab, Harris and Trostel, 2009[49]). A high number of hours spent in paid work during higher education studies tends to correlate with lower academic performance, as extra-curricular work hours place an additional burden on students. Research from a wide range of countries finds evidence in support for this link, for example from Portugal (Carreira and Lopes, 2021[50]), Germany (Behr and Theune, 2016[51]), Spain (Dolton, Marcenaro and Navarro, 2003[52]; Lassibille and Navarro Gómez, 2011[53]), the United States (Kim, 2007[54]), and the United Kingdom (Thomas, 2002[55]).
A broad geographical spread of higher education institutions can also serve as an indirect form of financial aid, as it helps lower mobility costs. In the 1990s, the Italian tertiary system increased the number of universities at the provincial level. By taking advantage of this shift and controlling for enrolment selection, Oppedisano (2011[56]) find that the establishment of a new university campus led a 6 percentage-point reduction in the drop-out rate within the legal duration of a degree.
The financial risk – both real and perceived – involved with investing in higher education may also vary depending on students’ socio-economic backgrounds (Outreville, 2015[57]). For instance, some courses may not generate expected returns that exceed the costs of undertaking studies. The costs associated with education may also involve more risk for first-generation students who cannot easily access information from their personal network about the potential reward of investing in post-secondary education, nor leverage their network for a job in their sector after their studies. For instance, research from Italy indicates that the expected probability of succeeding at university is lower, perceived returns to education and expected wages are lower, and the perceived costs of university are higher for students from lower socio-economic backgrounds (Barone, Triventi and Assirelli, 2018[58]). Similarly, research from the United Kingdom finds that 16 year-olds who agree that they knew someone who could help them get a job after leaving education went on to earn 4% more than comparable peers at age 26 (Mann, Kashefpakdel and Percy, 2017[59]).
Even when the post-secondary career path is well-known with career and earnings prospects understood, lifetime outcomes are uncertain and depend on factors like the ability to successfully complete studies and find an appropriate job (Blanden, Doepke and Stuhler, 2023[60]). This element of risk can be illustrated by research from Germany. Using 1984-2009 data of sons and fathers from the German Socio-Economic Panel Survey, Huebener (2012[61]) finds that sons with risk-taking fathers have a higher educational mobility and persistently higher income mobility than peers with risk averse fathers.
It should be the recognised that if the inequities in prior education and higher education systems are too strong, financial barriers will only be a secondary factor in student access to higher education. For instance, in Chile, the effect of the introduction of free tuition fee for first-generation students was not as impressive as expected, since entrenched inequalities in outcomes in prior education continue to limit the opportunities of lower-income students in the selection process (Espinoza et al., 2022[62]).
At the same time, it is not sufficient that financing options exist; students and their families need to be made aware of them and trust that they will receive support throughout their studies in order to utilise them. For instance, research from the Netherlands estimates that 24% of all eligible first-year students fail to apply to a means-tested student grant (Konijn, Visser and Zumbuehl, 2023[63]).
Incentives to invest in children’s education are stronger where the overall income inequality in societies is high, since the relative reward from the investment is greater (Blanden, Doepke and Stuhler, 2023[60]). In such cases, the long-run credit constraints faced by students from lower-income backgrounds means that the disadvantage from not investing can lead to accumulated disadvantage over the course of childhood (Lovenheim and Smith, 2023[64]; Andrews, Imberman and Lovenheim, 2020[65]).
Where inequality is high, intergenerational socio-economic mobility tends to be low. This means that when income inequalities are high, fewer children from lower-income families tend to earn higher incomes as adults, a cross-country trend often referred to as the “Great Gatsby curve” (Godin and Hindriks, 2018[32]; Björklund and Jäntti, 2009[66]; Corak, 2013[67]). One attempt to quantify this effect comes from Cingano (2014[68]), who finds that a rise in income inequality by 6 Gini points is accompanied by a 4% decrease in the probability of individuals with parents of low educational background being in higher education.
The uneven access to information contributes to defining students’ opportunities
It is relevant to consider aspirations to attend higher education since these have been shown to be predictive of enrolling in higher education, after taking into account academic ability. For instance, Brumley, Russel and Jaffee (2019[69]) find this trend using data from the United States, with the strongest association for students with high socio-economic status. In France, research also suggests that aspirations are predictive of future education achievement when taking into account academic ability and family socio-economic status (Guyon and Huillery, 2020[70]). Similarly, in Germany, the persistence of intergenerational income is significantly reduced when accounting for previous career preferences (Schüle, 2023[71]).
Research finds that students from families with lower incomes tend to have lower aspirations for higher education than students from higher-income families. For instance, research using data from Germany finds that preferences differ significantly by socio-economic background (Schüle, 2023[71]; Lergetporer, Werner and Woessmann, 2021[72]). Guyon and Huillery (2020[70]) analyse results from a survey in the Paris Metropolitan Area, France, and finds that the overall socio-economic differences in aspirations can be largely explained by social differences in awareness and self-assessment. Similar trends are seen across the OECD member countries.
A necessary condition for students to aspire to complete higher education is that they are aware that they can do so. Information about the often-complex higher education systems, costs and benefits, as well as requirements and application strategies, is not readily available to all young people and their families. Having access to relevant information is an important factor in students’ enrolment, programme match and completion rates. There are indeed socio-economic gaps in information and knowledge about requirements for a desired career. For instance, there is a socio-economic gap across OECD countries in the proportion of those aspiring to work in high-skilled occupations but do not expect to complete a tertiary degree (OECD, 2019[73]).
Higher education systems can be challenging to understand and the multitude of options to consider can mean that students and their families cannot get an accurate overview of their opportunity set (Lavecchia, Liu and Oreopoulos, 2016[74]). With too many choices, it is difficult to evaluate each relative to the constraints and desires that students face and so reach an optimised decision (Scott-Clayton, 2011[75]). Instead, students and their families tend to make decisions about further studies based on prior knowledge and readily available information (Hoxby and Avery, 2013[28]; Hoxby and Turner, 2013[76]).
When decisions about higher education are based on prior or readily available information, the students’ social interactions become particularly important (Carrell and Sacerdote, 2017[77]). Students look toward the career pathways and advice of the peers and adults in their social circle that they respect and trust. Young people in family and social circles where few, if any, individuals have pursued, or are planning to pursue, higher education, are therefore often facing an information gap compared to peers with several personal examples of opportunities and strategies to navigate the complex system of higher education admissions and financing.
Expectations from parents and other adults, such as teachers and extended family, have been shown to be relevant for young people’s decisions about education. Parental aspirations are shown to be strong predictors of the educational aspirations of their children in the United Kingdom, when controlling for the socio-economic status of the family parents and the cognitive and noncognitive skills of the child (Lekfuangfu and Odermatt, 2022[78]). Similarly, in the context of the German- and French-speaking parts of Switzerland, Buchmann, Grütter and Zuffianò (2021[79]) find positive and two-directional associations between parental educational aspirations and children’s belief in their own academic abilities.
Moreover, qualitative evidence from the United Kingdom suggest that the set of skills and social resources that influence how families engage with the world differ by socio-economic status in a way that means that young people from better-off backgrounds tend to consider higher education to more obviously be within the set of opportunities they have, while young people from lower-income backgrounds tend to be more likely to believe that higher education is not within their reach (Archer et al., 2012[80]). Similarly, in Australia, parents’ expectations of their children’s achievement are positively affected by their own education and their children’s enrolment in a private school, when controlling for children’s achievement in school (Dockery, Koshy and Li, 2022[81]).
Secondary schools can be important for subtle guidance and practices around university applications. Research using linked administrative data from the United Kingdom shows that school-level policies, practices and context may be influencing students’ decisions around whether or not to apply for higher education, regardless of the socio-economic background of students (Prior and Leckie, 2023[82]).
The information gap can also be illustrated by the effectiveness of providing information to young people from disadvantaged backgrounds who perform well in secondary education. Hoxby and Turner (2015[83]) consider the knowledge of low-income high achievers in the United States. They find that many students have significantly misunderstood aspects of the higher education system, including net prices, expected outcomes, suitable institutions and types of institutions. The authors find that targeted information helping to clear up relevant issues help students apply and enrol in programmes that are a better match to their skill sets (Hoxby and Turner, 2015[83]).
Importantly, aspirations not only affect whether students apply to and enrol in higher education, but also the programmes to which they apply. Students from low socio-economic backgrounds in the United States are less likely, compared with their better-off peers, to aspire to the most selective educational pathways, even when they have the same test scores (Hoxby and Avery, 2013[28]). Similar evidence is found in the Paris Metropolitan Area in France, where lower-income students are less likely to aspire than high-income students to ambitious educational pathways, even after controlling for academic ability (Guyon and Huillery, 2020[70]).
Receiving personalised information targeted to students’ abilities and financial needs can be effective in increasing enrolment in more selective programmes. The Expanding College Opportunities project targeted high-achieving, low-income students in the United States. They were mailed application fee waivers that did not require any paperwork, along with semi-customised information about the application process and students’ net cost of attending. An evaluation of the project found significant positive effects on enrolment in selective universities (Hoxby and Turner, 2013[76]).
Relatedly, students with lower socio-economic status may not be willing to move far away from their parental home, which may limit the programmes they have access to. First-generation higher education students in Germany are nearly 10 percentage points less likely to study at one of the top 200 institutions ranked in the QS World Ranking. On average, they study 80km closer to home than their non-first-generation peers and have a nearly 7 percentage point higher probability of studying in the same federal state as where they completed secondary education (Shure and Zierow, 2023[84]).
One explanation that has been offered for the aspirations gap is the theory of relative risk aversion. As put forward by Goldthopre (2010[85]), the rational action theory posits that participants in education systems will work toward avoiding negative relative social mobility. That means that families will try to achieve a similar educational attainment relative to their peers as their parents have relative to their peers. Van de Werfhorst and Hofstede (2007[86]) find some support for this theory. Using survey data from Amsterdam, in the Netherlands, they show that young people from all socio-economic backgrounds exhibit an aversion toward downward social mobility relative to their parents’ starting point.
It has also been suggested that aspirations and attitudes are important when considering completion rates. Academic research highlights the many multifaceted and interdependent reasons why students may decide to drop out of their higher education programmes (Gijón et al., 2023[87]; Aina et al., 2022[88]; Urbina-Nájera, Camino-Hampshire and Cruz, 2020[89]). For instance, in their comprehensive review of the socio-economic literature on student determinants of dropping out of higher education, Aina et al. (2022[88]) find that student persistence depends on a set of interlinked factors including student characteristics, factors related to socio-economic background, integration and commitment to studies, as well as institutional system design and labour-market characteristics (as explored in detail in the student tracking report delivered as part of this project). The authors argue that the effects of these factors on actual drop-out decisions are mediated by a students' abilities to integrate into the academic system.
Information about what can be expected, and knowledge of study field preferences are also important for student completion rates. Research from Germany shows that students who end up selecting programmes that do not match their preferred field of study are more likely to extend their time spent in education beyond the theoretical duration of their programmes or ultimately drop out compared to those who experienced a greater match. The authors find that these effects are particularly strong among lower-income students (Berlingieri, Diegmann and Sprietsma, 2023[90]). Similarly, a study from Portugal finds that students who enrol in a field of study that is not their first preference are more likely to leave after the first year of the programme, change field, delay graduation or drop out of higher education (Ferrão and Almeida, 2019[91])
The international research on factors that influence access to higher education, access to the most selective programmes, and completion rates, can be distilled into an analytical framework. This can help to disentangle key factors that contribute to inequities in higher education access and completion and investigate avenues for policy development. Three key overarching sets of factors – which form analytical themes – emerge as important for understanding key drivers of inequitable opportunities in higher education:
1. Prior achievement. This set of factors groups together challenges that students face in the transition from secondary education to higher education. This includes barriers related to obtaining eligibility to access higher education, such as achieving sufficiently high grades in secondary education exams and higher education entry exams and managing the admissions system. These barriers to achieve eligibility tend to be particularly high for lower-income students, students from schools in certain geographical areas, and students from vocational secondary education programmes.
2. Financial support. This set of factors includes challenges related to financial constraints. For example, students and their families must manage tuition fees, housing costs and other living costs given the available family income, student finance, and in-kind supports provided via welfare services or the education system. Financial barriers tend to be greater in families with lower incomes and be of particular relevance in cases where students want or need to live independently to attend a well-matched higher education programme.
3. Access to information. This set of factors refers to challenges that students face in obtaining understandable and pertinent information about their opportunities and the associated requirements. Within this set of factors, such information barriers are discussed together with issues related to the support students receive in discussing aspirations and encouraging plans that align students’ interests and academic abilities. There tends to be both information and aspiration gaps across students from families with different levels of income.
An analytical framework, including the three overarching factors and factors that contribute to these, as well as the key outcome areas is illustrated in Figure 1.1.
Note: Developed by the authors.
This report analyses the context of equity of opportunity in higher education by using the analytical framework presented in Figure 1.1 as a tool to structure its analysis. The assessment of current outcomes builds on research conducted in a diagnostic phase. Each section of the report proposes policy responses relevant to Portugal drawing on good or promising practice from international policy practice. The international good practice examples are selected from a more detailed good practice report delivered separately to the Portuguese authorities as part of the project. This report also integrates a summary of a detailed student tracking report that provides information on the use of analytical models in promoting student success, including promising policy examples relevant to Portugal.
The remainder of this report starts by taking stock of equity of opportunities to access higher education, to access the most selective programmes, and to complete programmes (Chapter 2). Subsequently, the report analyses outcomes in the policy areas that have been identified as important in determining opportunities to access and complete higher education from an equity perspective. First, it assesses the role of prior achievement, focusing on grades and admissions from different study orientations in secondary education (Chapter 3). Second, it assesses the adequacy of the system of direct and indirect financial support in Portugal, including the predictability of this support (Chapter 4). Third, it assesses access to information, considering in-school and out-of-school sources of information for students (Chapter 5). Finally, the report provides an overview of promising practices at the level of higher education institutions that promote study success and programme completion (Chapter 6). Table 1.1 summarises the key findings and recommendations included in the remaining chapters of this report.
References
[88] Aina, C. et al. (2022), “The determinants of university dropout: A review of the socio-economic literature”, Socio-Economic Planning Sciences, Vol. 79, https://doi.org/10.1016/j.seps.2021.101102.
[65] Andrews, R., S. Imberman and M. Lovenheim (2020), “Recruiting and supporting low-income, high-achieving students at flagship universities”, Economics of Education Review, Vol. 74, https://doi.org/10.1016/j.econedurev.2019.101923.
[80] Archer, L. et al. (2012), “Science Aspirations, Capital, and Family Habitus: How Families Shape Children’s Engagement and Identification With Science”, American Educational Research Association, Vol. 49/5, https://doi.org/10.3102/0002831211433290.
[13] Austrian Ministry of Science Research and Economy (2017), National strategy on the social dimension of higher education: Towards more inclusive access and wider participation, Austrian Ministry of Science Research and Economy, https://www.sozialerhebung.at/sozdim/strategiepapier/Strategie_2017_englisch.pdf.
[58] Barone, C., M. Triventi and G. Assirelli (2018), “Explaining Social Inequalities in Access to University: A Test of Rational Choice Mechanisms in Italy”, European Sociological Review, Vol. 34/5, pp. 554-569, https://doi.org/10.1093/esr/jcy028.
[51] Behr, A. and K. Theune (2016), “The causal effect of off-campus work on time to degree”, Education Economics, Vol. 24/2, pp. 189-209, https://doi.org/10.1080/09645292.2014.974509.
[42] Beine, M., R. Noël and L. Ragot (2014), “Determinants of the international mobility of students”, Economics of Education Review, Vol. 41, pp. 40-54, https://doi.org/10.1016/j.econedurev.2014.03.003.
[90] Berlingieri, F., A. Diegmann and M. Sprietsma (2023), “Preferred field of study and academic performance”, Economics of Education Review, Vol. 95, https://doi.org/10.1016/j.econedurev.2023.102409.
[60] Blanden, J., M. Doepke and J. Stuhler (2023), Chapter 6 - Educational inequality, Elsevier, https://doi.org/10.1016/bs.hesedu.2022.11.003.
[2] Boudon, R. (1974), Education, Opportunity, and Social Inequality: Changing Prospects in Western Society., Wiley-Interscience, https://eric.ed.gov/?id=ED091493.
[69] Brumley, L., M. Russell and S. Jaffee (2019), “College Expectations Promote College Attendance: Evidence From a Quasiexperimental Sibling Study”, Psychological Science, Vol. 30/8, https://doi.org/10.1177/0956797619855385.
[79] Buchmann, M., J. Grütter and A. Zuffianò (2021), “Parental educational aspirations and children’s academic self-concept: Disentangling state and trait components on their dynamic interplay”, Child Development, Vol. 93/1, https://doi.org/10.1111/cdev.13645.
[48] Cabrera, A., A. Nora and M. Castañeda (1992), “The role of finances in the persistence process: A structural model”, Research in Higher Education, Vol. 33/5, pp. 571-593, https://doi.org/10.1007/BF00973759.
[27] Campbell, S. et al. (2022), “Matching in the Dark? Inequalities in Student to Degree Match”, Journal of Labor Economics, Vol. 40/4, https://doi.org/10.1086/718433.
[38] Canaan, S. and P. Mouganie (2018), “Returns to Education Quality for Low-Skilled Students: Evidence from a Discontinuity”, Journal of Labor Economics, https://doi.org/10.1086/694468.
[50] Carreira, P. and A. Lopes (2021), “Drivers of academic pathways in higher education: traditional vs. non-traditional students”, Studies in Higher Education, Vol. 46/7, pp. 1340-1355, https://doi.org/10.1080/03075079.2019.1675621.
[77] Carrell, S. and B. Sacerdote (2017), “Why Do College-Going Interventions Work?”, American Economic Journal: Applied Economics, Vol. 9/3, https://doi.org/10.1257/app.20150530.
[21] Chetty, R. et al. (2020), “Income Segregation and Intergenerational Mobility Across Colleges in the United States”, The Quarterly Journal of Economics, Vol. 135/3, https://doi.org/10.1093/qje/qjaa005.
[20] Chowdry, H. et al. (2013), “Widening Participation in Higher Education: Analysis Using Linked Administrative Data”, Journal of the Royal Statistical Society Series A: Statistics in Society, Vol. 176/2, https://doi.org/10.1111/j.1467-985X.2012.01043.x.
[68] Cingano, F. (2014), “Trends in Income Inequality and its Impact on Economic Growth”, OECD Social, Employment and Migration Working Papers, OECD Publishing, Paris, https://doi.org/10.1787/5jxrjncwxv6j-en.
[67] Corak, M. (2013), “Income Inequality, Equality of Opportunity, and Intergenerational Mobility”, The Journal of Economic Perspectives, Vol. 27/3, https://www.jstor.org/stable/41955546.
[25] da Silva, D. et al. (2022), “Forecasting Students Dropout: A UTAD University Study”, Future Internet, Vol. 14/3, https://doi.org/10.3390/fi14030076.
[44] DeAngelo, L. and R. Franke (2016), “Social Mobility and Reproduction for Whom? College Readiness and First-Year Retention”, American Educational Research Journal, Vol. 53/6, pp. 1588-1625, https://doi.org/10.3102/0002831216674805.
[23] Delogu, M. et al. (2024), “Predicting dropout from higher education: Evidence from Italy”, Economic Modelling, Vol. 130, https://doi.org/10.1016/j.econmod.2023.106583.
[35] Dilnot, C., L. Macmillan and G. Wyness (2023), “The path increasingly travelled: Vocational entry qualifications, socioeconomic status and university outcomes”, British Educational Research Journal, Vol. 49/6, https://doi.org/10.1002/berj.3890.
[81] Dockery, A., P. Koshy and I. Li (2022), “Parental expectations of children’s higher education participation in Australia”, British Educational Research Journal, Vol. 48/4, https://doi.org/10.1002/berj.3786.
[52] Dolton, P., O. Marcenaro and L. Navarro (2003), “The effective use of student time: a stochastic frontier production function case study”, Economics of Education Review, Vol. 22/6, pp. 547-560, https://doi.org/10.1016/S0272-7757(03)00027-X.
[45] Dynarski, S. (2003), “Does Aid Matter? Measuring the Effect of Student Aid on College Attendance and Completion”, American Economic Review, Vol. 93/1, pp. 279-288, https://doi.org/10.1257/000282803321455287.
[62] Espinoza, O. et al. (2022), “Reducing inequality in access to university in Chile: the relative contribution of cultural capital and financial aid”, Higher Education, Vol. 83, pp. 1355-1370, https://doi.org/10.1007/s10734-021-00746-z.
[8] EUR-Lex (2022), The Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions on a European Strategy for Universities, European Union, https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=COM%3A2022%3A16%3AFIN.
[15] EUR-Lex (2017), Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions on a renewed EU agenda for higher education, European Union, https://eur-lex.europa.eu/legal-content/EN/TXT/?qid=1496304694958&uri=COM%3A2017%3A247%3AFIN.
[6] European Commission (2024), European Pillar of Social Rights - Building a fairer and more inclusive European Union, https://ec.europa.eu/social/main.jsp?catId=1226&langId=en.
[5] European Commission (2024), Inclusive education, https://education.ec.europa.eu/focus-topics/improving-quality/inclusive-education.
[33] European Commission (2020), Beyond averages: Fairness in an economy that works for people, Joint Research Centre, European Commission, https://doi.org/10.2760/261169.
[7] European Commission (2020), The European higher Education Areas in 2020: Bologna Process Implementation Report, Publications Office of the European Union, https://doi.org/10.2797/756192.
[16] European Commission (n.d.), European Social Fund Plus, https://european-social-fund-plus.ec.europa.eu/en.
[17] European Commission (n.d.), Pillar overview, https://ec.europa.eu/economy_finance/recovery-and-resilience-scoreboard/pillar_overview.html?lang=en.
[12] Eurydice (2024), The European Higher Education Area in 2024: Bologna Process Implementation Report, Eurydice, https://eurydice.eacea.ec.europa.eu/publications/european-higher-education-area-2024-bologna-process-implementation-report.
[47] Fack, G. and J. Grenet (2015), “Improving College Access and Success for Low-Income Students: Evidence from a Large Need-Based Grant Program”, American Economic Journal: Applied Economics, Vol. 7/2, pp. 1-34, https://doi.org/10.1257/app.20130423.
[91] Ferrão, M. and L. Almeida (2019), “Differential effect of university entrance score on first-year students’ academic performance in Portugal”, Assessment & Evaluation in Higher Education, Vol. 44/4, pp. 610-622, https://doi.org/10.1080/02602938.2018.1525602.
[87] Gijón, J. et al. (2023), “Dropout stories of Andalusian university students”, Frontiers in Education, Vol. 8, https://doi.org/10.3389/feduc.2023.1130194.
[32] Godin, M. and J. Hindriks (2018), “An international comparison of school systems based on social mobility”, LIDAM Reprints CORE 2951, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE), https://www.insee.fr/en/statistiques/fichier/3546955/499_Godin-Hindriks-EN.pdf.
[49] Goldrick-Rab, S., D. Harris and P. Trostel (2009), “Why Financial Aid Matters (or Does Not) for College Success: Toward a New Interdisciplinary Perspective”, https://doi.org/10.1007/978-1-4020-9628-0_1.
[85] Goldthorpe, J. (2010), “Class analysis and the reorientation of class theory: the case of persisting differentials in educational attainment. 1996”, The British Journal of Sociology, Vol. 61/1, pp. 311-335, https://doi.org/10.1111/j.1468-4446.2009.01248.x.
[24] Gonzalez-Nucamendi, A., J. Noguez and L. Neri (2023), “Predictive analytics study to determine undergraduate students at risk of dropout”, Frontiers in Education, https://doi.org/10.3389/feduc.2023.1244686.
[70] Guyon, N. and E. Huillery (2020), “Biased aspirations and social inequality at school: evidence from French teenagers”, The Economic Journal, Vol. 131/February, https://doi.org/10.1093/ej/ueaa077.
[43] Hamilton, L. (2013), “More Is More or More Is Less? Parental Financial Investments during College”, American Sociological Review, Vol. 78/1, pp. 70-95, https://doi.org/10.1177/0003122412472680.
[74] Hanushek, E., S. Machin and L. Woessmann (eds.) (2016), Chapter 1 - Behavioral Economics of Education: Progress and Possibilities, Elsevier, https://doi.org/10.1016/B978-0-444-63459-7.00001-4.
[28] Hoxby, C. and C. Avery (2013), “The Missing “One-Offs”: The Hidden Supply of High-Achieving, Low Income Students”, Brookings Papers on Economic Activity, https://www.brookings.edu/wp-content/uploads/2016/07/2013a_hoxby.pdf.
[83] Hoxby, C. and S. Turner (2015), “What High-Achieving Low-Income Students Know About College”, American Economic Review: Papers & Proceedings, Vol. 105/5, https://doi.org/10.1257/aer.p20151027.
[76] Hoxby, C. and S. Turner (2013), “Expanding College Opportunities for High-Achieving, Low-Income Students”, Stanford SIEPR Working Paper, https://siepr.stanford.edu/publications/working-paper/expanding-college-opportunities-high-achieving-low-income-students.
[61] Huebener, M. (2012), “The Role of Family Risk Attitudes in Education and Intergenerational Mobility: An Empirical Analysis”, SOEPpaper No. 529, https://doi.org/10.2139/ssrn.2197844.
[40] Joensen, J. and E. Mattana (2021), “Student Aid Design, Academic Achievement, and Labor Market Behavior: Grants or Loans?”, SSRN, https://doi.org/10.2139/ssrn.3028295.
[54] Kim, D. (2007), “The Effect of Loans on Students’ Degree Attainment: Differences by Student and Institutional Characteristics”, Harvard Educational Review, Vol. 77/1, pp. 64-100, https://doi.org/10.17763/haer.77.1.n14t69l0q8292784.
[63] Konijn, S., D. Visser and M. Zumbuehl (2023), “Quantifying the Non‑Take‑up of a Need‑Based Student Grant in the Netherlands”, De Economist 171, pp. 239-266, https://doi.org/10.1007/s10645-023-09423-1.
[53] Lassibille, G. and M. Navarro Gómez (2011), “How Long Does it Take to Earn a Higher Education Degree in Spain?”, Research in Higher Education, Vol. 52/1, pp. 63-80, https://doi.org/10.1007/s11162-010-9186-z.
[78] Lekfuangfu, W. and R. Odermatt (2022), “All I have to do is dream? The role of aspirations in intergenerational mobility and well-being”, European Economic Review, Vol. 148, https://doi.org/10.1016/j.euroecorev.2022.104193.
[72] Lergetporer, P., K. Werner and L. Woessmann (2021), “Does Ignorance of Economic Returns and Costs Explain the Educational Aspiration Gap? Representative Evidence from Adults and Adolescents”, Economica, Vol. 88/351, pp. 624-670, https://doi.org/10.1111/ecca.12371.
[41] Lovenheim, M. and C. Reynolds (2012), “The Effect of Housing Wealth on College Choice: Evidence from the Housing Boom”, NBER Working Paper No. 18075, https://www.nber.org/system/files/working_papers/w18075/w18075.pdf.
[64] Lovenheim, M. and J. Smith (2023), Chapter 4 - Returns to different postsecondary investments: Institution type, academic programs, and credentials, Elsevier, https://doi.org/10.1016/bs.hesedu.2022.11.006.
[59] Mann, A., E. Kashefpakdel and C. Percy (2017), “Socialised social capital? The capacity of schools to use careers provision to compensate for social capital deficiencies among teenagers”, in Essays on Employer Engagement, Routledge, London, https://doi.org/10.1080/13639080.2016.1177636.
[4] Marginson, S. (2016), “High Participation Systems of Higher Education”, The Journal of Higher Education, Vol. 87/2, pp. 243-271, https://doi.org/10.1080/00221546.2016.11777401.
[1] OECD (2025), “Education equity”, https://www.oecd.org/en/topics/education-equity.html (accessed on 2025).
[36] OECD (2024), Education at a Glance 2024: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/c00cad36-en.
[18] OECD (2024), OECD Youth Policy Toolkit, OECD Publishing, Paris, https://doi.org/10.1787/74b6f8f3-en.
[19] OECD (2023), Education at a Glance 2023: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/e13bef63-en.
[26] OECD (2023), PISA 2022 Results (Volume I): The State of Learning and Equity in Education, OECD Publishing, Paris, https://doi.org/10.1787/53f23881-en.
[34] OECD (2022), Education at a Glance 2022: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/3197152b-en.
[30] OECD (2021), Education at a Glance 2021: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/b35a14e5-en.
[3] OECD (2020), Resourcing Higher Education: Challenges, Choices and Consequences, OECD Publishing, Paris, https://doi.org/10.1787/735e1f44-en.
[73] OECD (2019), PISA 2018 Results (Volume II), OECD Publishing, Paris, https://www.oecd-ilibrary.org/sites/31156087-en/index.html?itemId=/content/component/31156087-en.
[10] OECD Legal Instruments (2022), Declaration on Building Equitable Societies Through Education, OECD Publishing, Paris, https://legalinstruments.oecd.org/en/instruments/OECD-LEGAL-0485.
[9] OECD Legal Instruments (2022), Recommendation of the Council on Creating Better Opportunities for Young People, OECD Publishing, Paris, https://legalinstruments.oecd.org/en/instruments/OECD-LEGAL-0474.
[56] Oppedisano, V. (2011), “The (adverse) effects of expanding higher education: Evidence from Italy”, Economics of Education Review, Vol. 30/5, pp. 997-1008, https://doi.org/10.1016/j.econedurev.2011.04.010.
[57] Outreville, J. (2015), “The Relationship between relative risk aversion and the level of education: a survey and implications for the demand for life insurance”, Journal of Economic Surveys, Vol. 29/1, pp. 97-111, https://doi.org/10.1111/joes.12050.
[14] Park, E. and S. Preymann (2022), Zwischenevaluierung der Nationalen Strategie zur sozialen Dimension in der Hochschulbildung, https://pubshop.bmb.gv.at/index.php?rex_media_type=pubshop_download&rex_media_file=strategie_sd_hsbildung.pdf.
[82] Prior, L. and G. Leckie (2023), “School differences on whether and where students apply to university”, British Journal of Sociology of Education, Vol. 44/7, pp. 1161-1181, https://doi.org/10.1080/01425692.2023.2244177.
[66] Salverda, W., B. Nolan and T. Smeeding (eds.) (2009), Intergenerational income mobility and the role of family background, Oxford University Press USA.
[22] Schmidt, B., P. Boero and J. Méndez Vera (2023), “Factors influencing university dropouts: the case of a Chilean state university”, Revista Portuguesa de Educacao, Vol. 36/1, https://doi.org/10.21814/RPE.23401.
[11] Schmidt, N. and H. Onita (2023), Principles, Guidelines and Indicators to Strengthen the Social Dimension of Higher Education in the European Higher Education Area, BFUG Working Group on Social Dimension, https://www.ehea.info/Upload/BFUG_ES_GA_86_6_4_1_WG_SD_Principles_Guidelines_Indicators.pdf.
[71] Schüle, P. (2023), “Career Preferences and Socio-Economic Background”, ifo Working Paper No. 395, https://www.ifo.de/en/publications/2023/working-paper/career-preferences-and-socio-economic-background.
[75] Scott-Clayton, J. (2011), “On money and motivation: A quasi-experimental analysis of financial incentives for college achievement”, Journal of Human Resources, Vol. 46/3, pp. 614-646, https://doi.org/10.3368/jhr.46.3.614.
[84] Shure, N. and L. Zierow (2023), “High Achieving First-Generation University Students”, IZA Discussion Paper No. 16654, https://doi.org/10.2139/ssrn.4656843.
[46] Singell, L. (2004), “Come and stay a while: does financial aid effect retention conditioned on enrollment at a large public university?”, Economics of Education Review, Vol. 23/5, pp. 459-471, https://doi.org/10.1016/j.econedurev.2003.10.006.
[39] Steiner, V. and K. Wrohlich (2012), “Financial Student Aid and Enrollment into Higher Education: New Evidence from Germany”, Scandinavian Journal of Economics, Vol. 114/1, pp. 124-147, https://www.jstor.org/stable/41407779.
[37] Suga, F. (2019), “Returns to Postgraduate Education in Japan”, The Japanese Economic Review, https://doi.org/10.1111/jere.12227.
[55] Thomas, L. (2002), “Student retention in higher education: the role of institutional habitus”, Journal of Education Policy, Vol. 17/4, pp. 423-442, https://doi.org/10.1080/02680930210140257.
[89] Urbina-Nájera, A., J. Camino-Hampshire and B. Cruz (2020), “University dropout: Prevention patterns through the application of educational data mining”, RELIEVE - Revista Electronica de Investigacion y Evaluacion Educativa, Vol. 26/1, pp. 1-19, https://doi.org/10.7203/relieve.26.1.16061.
[31] Werfhorst, H. (2021), “Sorting or mixing? Multi-track and single-track schools and social inequalities in a differentiated educational system”, British Educational Research Journal, Vol. 47/5, pp. 1209-1236, https://doi.org/10.1002/berj.3722.
[86] Werfhorst, H. and S. Hofstede (2007), “Cultural capital or relative risk aversion? Two mechanisms for educational inequality compared”, The British Journal of Sociology, Vol. 58/3, https://doi.org/10.1111/j.1468-4446.2007.00157.x.
[29] Zwier, D., S. Geven and H. Werfhorst (2021), “Social inequality in shadow education: The role of high-stakes testing”, International Journal of Comparative Sociology, Vol. 61/6, https://doi.org/10.1177/0020715220984500.