Resourcing Higher Education in Portugal

Report

19 December 2022

5. Resourcing accessible higher education

Abstract

This chapter examines the policies that Portugal has implemented to widen access to higher education. As discussed in Chapter 2, Portugal has succeeded in raising higher education attainment rates among young adults to a level that now exceeds the average of European Union countries. The government has committed to increasing participation in post-secondary education among young people following vocational pathways and adults in search of upskilling and reskilling opportunities. This chapter analyses the effectiveness of efforts to create an accessible network of higher education campuses across the Portuguese territory, the national financial support system for students and policies on student services and housing.

Policies to promote access to higher education

In the last decade, Portugal has succeeded in greatly increasing the proportion of the population acquiring higher education qualifications. In 2021, 44% of people in Portugal aged 30-34 – the age range used for European Union benchmarks – held a tertiary-education qualification, compared to only 28% a decade earlier and an average of 42% in the European Union as a whole (Eurostat, 2022[1]). Historically, Portugal’s efforts to widen access involved expanding the network of higher education institutions across the country, with the creation of new public universities and a new network of polytechnics, greatly increasing capacity in the system. More recently, efforts have focused on diversifying the educational offering delivered in this network of institutions and creating access routes for less-traditional student populations, including graduates from secondary-vocational tracks and adult learners, with a view to further widening access to higher education and increasing attainment.

The “Contract for the Legislative Term” (Contrato de Legislatura) for the period 2020-23 establishes ambitious goals to expand participation in higher education further, notably setting a target that 60% of 20‑year-olds should be enrolled in higher education and 50% of 30-34 year-olds hold a tertiary qualification in 2030 (Government of Portugal, 2019[2]). The Contrato de Legislatura also establishes targets are also established for the proportion of adults in the student population, for increasing participation in distance education provided by the Universidade Aberta and for increasing the supply of post-graduate programmes oriented towards adult learners. To achieve these overall goals, the Contrato de Legislatura identifies specific goals and targets, as summarised in Table 5.1. Alongside the diversification of educational supply and access routes, these goals also seek to improve the broader support framework for students, namely direct financial aid and student housing.

	Goal	Indicator	Situation in 2021	Target for 2023	Target for 2030
1.1	Increasing direct financial support for students (ação social direta)	Number of student grants per year	85 385	90 000	100 000
1.2	Increasing mobility of students (+Superior programme)	Number of new +Superior grants per year	2 230	2 000	5 000
1.3	Increasing supply of student accommodation at regulated prices	Number of beds	17 734	26 900	30 000
1.4	Increasing provision of short-cycle TeSP programmes in polytechnics	Number of new students	9 685	12 000	15 000
1.5	Stimulating knowledge exchange with society	Ciência Viva “Farms” (Quintas) (community engagement centres)	6	7	10
1.6	Guarantee access to higher education for secondary-vocational students	Number of enrolled students	6 938	10 000	15 000

Source: MCTES (2021[3]) Acompanhamento do “Contrato de Legislatura” assinado entre o Governo e as Instituições de Ensino Públicas para 2020-2023 (Monitoring of the Contract for the Legislative Term concluded between the government and public HEIS for 2020-2023), https://www.igefe.mec.pt/Page/Index/51 (accessed on 20 July 2022).

This chapter examines Portugal’s policies to widen access in three areas. First, it considers the legacy of the historical expansion of the public higher education network in Portugal, the effects this has had on participation in higher education across the national territory and the implications for future policy. Second, the chapter examines the system for financial support for students and the inter-relation of this system with regulated tuition fees in public HEIs. Finally, the chapter considers public support for investments in student services in HEIs, including student housing.

Creating an accessible higher education network

Proximity – or physical accessibility – affects participation in higher education, although it is less relevant than for other public services

In analysis of public-service provision, the proximity of services to the population served – or physical accessibility – is a particularly important factor in areas such as primary healthcare and basic education. In the case of higher education, the concept of physical accessibility is often considered to be less relevant. In contrast to primary healthcare, where citizens need to be able to call on the service throughout their lives or basic education, where “users” are children, the main “users” of higher education (students) access the service (higher education institutions) for a limited number of years as adults. Students often relocate from their place of residency, as provision is often concentrated in a small number of municipalities within countries. Moreover, the variety of programmes on offer, different admission requirements and variation in quality between HEIs mean that students may not always be able or willing to attend the higher education provider that is closest to their home.

Nevertheless, proximity is not an entirely irrelevant consideration in higher education. International evidence shows that, controlling for other factors, proximity to a higher education institution is related to a higher likelihood of entering and completing post-secondary education, (Sá, Florax and Rietveld, 2006[4]; Spiess and Wrohlich, 2010[5]), as well as the type of education chosen (Walsh, Flannery and Cullinan, 2015[6]). Moving location to attend higher education has significant financial and transaction costs and requires motivation and confidence. Studies in the United States have found that students living “out of commuting distance” are far less likely to attend university than students living “within commuting distance”, with students from lower‐income families are particularly disadvantaged by distance (Frenette, 2006[7]). The presence of an HEI in a locality may also generate peer effects and information exchange between students, academic staff and the local community, positively influencing decisions to attend higher education (Do, 2004[8]). It is thus likely that, on average, significant distance from a higher education provider – physical inaccessibility – compounds the negative effects of low socio-economic background on higher education attendance.

The proximity of higher education institutions to localities and regions also brings advantages that are not directly related to participation rates. HEIs are major employers and thus bring skilled populations of academic staff and students to the places where they are located – or retain the skilled populations if they are local. As discussed in Chapter 4, the extent to which institutions can attract students and staff – or indeed retain students and staff from their locality – depends significantly on the profile and quality of the institution. Equally, staff from HEIs can become important players in regional innovation ecosystems, contributing through their presence to the economic development of the localities and regions where the HEIs are located (Arbo and Benneworth, 2007[9]).

Measures of the concentration and accessibility of higher education institutions can give an indication of the capacity of higher education systems to serve the populations and regions of their country effectively. A high spatial concentration of HEIs may accentuate problems such as brain drain from provincial regions and population and price pressures in core urban areas and, ultimately lead to lower rates of participation in higher education owing to the cost and societal barriers highlighted above.

The population within a 30-minute travel time to a campus is one indicator of the physical accessibility of the higher education network

Portugal’s network of higher education institutions is the result of waves of expansion in previous decades resulting from the need to satisfy growing demand for higher education and diversify and modernise the range of study options on offer (Arbo and Benneworth, 2007[9]). As in other European countries, a substantial part of the territorial expansion of higher education in Portugal happened in the last 40 years, in Portugal’s case with the creation of new universities and the polytechnic sector (Bonaccorsi and Lepori, 2019[10]). The objective of bringing higher education to interior regions and the islands – away from the historical universities in the large cities and littoral regions – has been a constant feature of higher education policy in Portugal in recent decades.

Given this focus, it is legitimate to ask how the territorial coverage and physical accessibility of higher education in Portugal compares with that in other OECD countries. Measuring coverage and physical accessibility requires careful consideration of the geographic scales and territories taken into account. For example, a rough measure of physical accessibility is the number of higher education institutions in a given (administrative) region (Bonaccorsi and Lepori, 2019[10]). However, as students routinely access higher education institutions outside the administrative region where they live, measures of accessibility should not be limited by administrative boundaries, but rather reflect the real-world accessibility of higher education campuses taking into account the transport networks in place. To do this, it is possible to use two main measures of accessibility: 1) the population within a certain travel time of a higher education campus; and 2) the number of cumulative study opportunities (study places) available to the population in a given territorial area.

Accessibility measures that use facilities, such as higher education campuses, as the point of reference indicate the share of a given population that has access to a facility within a certain driving time (see Box 5.1). An example of such a measure would be the share of the national population residing within 30 minutes’ travel time of a higher education campus. If such measures are compared across regions or countries, observed differences in accessibility are likely due to factors such as the number and distribution of facilities in each area of study, the level of user (population) concentration in each territory or the state of the transport network.

Higher education campuses in Portugal are more evenly distributed across the country’s territory than is the case in most OECD countries

Data on the geographical location of higher education campuses from the OECD’s Analytical Database of Higher Education Providers (ADHEP) can be used to calculate share of national populations within 30 minutes and 45 minutes driving time of a campus. Driving time is used as relevant data are available for all countries and locations. However, many – in reality, most – students do not drive to campus, but rely on public transport or other means and, in rural areas, a 30-minute drive on clear roads may equate to a one to two-hour trip on public transport. As such driving-time indicators provide only a rough proxy for the real accessibility of campuses for students on the ground. On the other hand, data for some countries are only available for main locations, rather than all campuses, potentially leading to an over-estimation of driving time (and under-estimation of accessibility) in these cases.

As illustrated in Figure 5.2, the results of this international comparative analysis show that about 80% of the population of Portugal has access to a higher education campus within a 30-minute drive of their place of residency. This proportion is above the average of 73% across 31 OECD countries with available data. Predictability, the proportions of national populations within a 45-minute driving time of a campus are higher. However, the 30-minute threshold is probably a more valuable indicator for policy, given the probably longer travel times associated with other modes of transport.

Box 5.1. Measuring accessibility using facilities as the point of reference

Accessibility measures that take facilities as the point of reference calculate points representing the maximum distance that can be travelled in every direction from each facility within a certain travel time, usually using a pre-defined mode of travel1. The lines connecting these points are referred to as “isochrones” (from the Greek ʌɪsə/iso – same, krɒn/chronos: times). To obtain an accessibility measure, the next step is to identify the number of potential users located within isochrones – for instance the population or population within a certain age range – and then to express this number as a proportion of total potential users (for example, the share of the total population of a country or region within 30 minutes travel time of the facility).

Figure 5.1 shows an example of isochrones around the main campus of the Universidade de Lisboa for 30, 45 and 60 minutes driving time, together with the boundaries of the Lisbon functional urban area for reference. Travel times obtained through routing algorithms that rely on public road network data usually under-estimate user-experienced travel times because they do not take into account congestion (i.e. they assume travel happens at the maximum speed allowed by type of road). In most cases, travel times by car also under-estimate travel times by other modes, including public transport.

Figure 5.1. Isochrones for different driving times compared to FUA borders

1. Accessibility analyses usually focus on a single travel mode or compare different travel modes, as summarising all modes into a single time measure in a meaningful way is methodologically challenging.

Figure 5.2. Share of population with access to a higher education campus

The results shown in Figure 5.2 support previous evidence that has shown that higher education campuses a comparatively well dispersed across the national territory in Portugal. A study using ETER 2016 data for European countries showed that the share of population in regions with no HEI in Portugal was below 10%.1 The study also showed that the regions of Porto and the Lisbon Metropolitan Area concentrate a lower proportion of national higher education providers than cities such as London, Paris or Riga (Bonaccorsi and Lepori, 2019[10]).

The spatial concentration of higher education can be the result of urbanisation rates, as old higher education institutions expand and new ones are created to satisfy the needs of an increasing urban population. In countries with high rates of urbanisation, a higher proportion of the population tends to live within easy reach of a higher education institution. As illustrated in Figure 5.3, data show that Portugal achieves comparatively high levels of physical accessibility to higher education, despite having a comparatively low rate of urbanisation. About 80% of the population has access to a higher education campus within a 30-minute drive, but only 56% live in functional urban areas (FUAs). This pattern is similar to the situation in Denmark, but contrasts with the situation in Spain, which has higher rates of urbanisation (70% of the population lives in FUAs), but lower levels of physical accessibility to higher education campuses (only 67% of the population has access to a campus within a 30 minute-drive).

Figure 5.3. Accessibility of higher education and degree of urbanisation

Measures of accessibility to higher education should also take into account competition for study places

Accessibility measures that take areas as the unit of reference – such as the cumulative number of study opportunities (study places) available to the population in a given territorial area – can be used to measure the access to educational opportunities within countries in a way that accounts for both the number of opportunities in facilities and the level of competition in access. A commonly used measure of accessibility using areas as the unit of reference is the “cumulative opportunities index”. This counts the number of opportunities (e.g. available higher education study places) that are reachable to users living in a given area. The “competitive accessibility index” extends this measure to account for the level of competition for access to the same facility by “discounting” the number of opportunities accessible from each area by the number of potential users with access to the same opportunities (see Box 5.2).

The analysis conducted for this review uses data on the number of study places made available through the National Access Competition (vagas) in each municipality in Portugal. The “cumulative opportunities index” value for each municipality indicates the number of study places a potential higher education student can access within a 30 or 45 minute drive from that municipality. The “competitive accessibility index” uses the number of secondary-school students graduating from the scientific-humanistic track in each municipality as measure for the potential demand for study places, taking into account that students graduating from the professional track are currently far less likely to enter higher education (see Chapter 4).

Box 5.2. Opportunity and accessibility index definitions

Cumulative opportunities index

The cumulative opportunity index can be defined as:

${C O}_{i} = \sum_{j = 1}^{n} O_{j} f (C_{i j})$ , $f (C_{i j}) = {\begin{matrix} 1 i f C_{i j} \leq t \\ 0 i f C_{i j} > t \end{matrix}$

Where $O_{i}$ is the number of “opportunities” (e.g. higher education study places) available for users travelling from area i within a certain travel time threshold t by a pre-defined mode of transport. $C_{i j}$ is the travel time between area i and area j, and $f (C_{i j})$ is a weight function that takes the value of one if the travel time is equal or less than a pre-defined threshold t, and zero in other cases. The indicator can have values from 0 (no opportunities) to M (the maximum total number of opportunities in the study area).

Competitive accessibility index

The competitive accessibility index can be defined as:

${C A}_{i} = \sum_{j = 1}^{n} \frac{O_{j} f (C_{i j})}{\sum_{j = 1}^{n} T_{j} f (C_{i j})}$

With $f (C_{i j})$ defined as above. In this measure, the numerator counts how many opportunities can be reached from a given area i, and the denominator counts how many potential users can reach the same area. A value between 0 and 1 indicates that there is more potential demand than supply of opportunities (under-provision), and a value larger than 1 indicates that there is more supply than demand (over-provision).

Choice of area of reference

A methodological challenge of using area-based accessibility indicators is defining a reference point, that is, a single set of co-ordinates from which travel times can be calculated. The bias introduced by choosing a single point within an area will be larger for bigger and less evenly distributed regions.2 On the other hand, picking a very small area (e.g. a 1km² grid cell) implies an exponential increase in the number of pairs of distances that need to be calculated across the whole area of study. This review uses nationally available data at the campus level in mainland Portugal. The analysis is undertaken at the municipality level, an intermediate spatial unit with 308 areas between the parish and the TL3 divisions. The 1km²cell with highest (2015) population within the municipality was selected as the reference point for the measurement of accessibility per municipality. In practice, this means that the accessibility measure does not take into account the time it takes a person to travel from anywhere in the municipality to the main population centre within that municipality.

In the academic year 2019/20, accessibility study places (vagas) within a 30-minute or 45-minute drive ranges from zero to over 20 000 in the areas with largest access around Lisbon and Porto. Out of a total of 308 municipalities in the analysis, 150 municipalities, home to 17% of the total population in 2021, do not have access to any study places at bachelor’s level in public HEIs within a 30-minute drive. Expanding this range to a 45-minute drive lowers these figures to 70 municipalities and 5% of the total population of Portugal. As shown in Figure 5.4, the municipalities without access to higher education campuses within the 45-minute time threshold include clusters of low-density municipalities in lower and central Alentejo, interior areas in Centro, coastal and border areas in Algarve and interior regions close to the North-East border with Spain.

Figure 5.4. Cumulative access to study places in mainland Portugal

The “competitive accessibility index”, which takes into account competition for places from surrounding areas (see Box 5.2), reveals a different picture. As illustrated in Figure 5.5, in 2019/20, 23% of Portugal’s population lived in the 60 municipalities where the number of upper secondary graduates from the scientific-humanistic track was greater than the number of study places available within a 30 minute drive (i.e. they have competitive index values larger than zero and lower than 1) and 57% lived in municipalities where the offer of study places was larger than the local demand (i.e. they have competitive index values larger than 1). 64 municipalities, representing 4% of the total population, did not have any secondary students graduating from the scientific-humanistic track in 2019/20.

The competitive accessibility analysis reveals that the relatively high supply of higher education study places in and around Porto noted in Figure 5.4 aligns closely with the local demand within a 45-minute drive of local campuses. This contrasts with municipalities such as Bragança, where the offer of study places within a 45-minute drive is six times larger than the local demand within the same time range. IP Bragança must (and does) therefore attract students from elsewhere in Portugal and internationally to fill the study places available.

Figure 5.5. Competitive accessibility to study places in mainland Portugal

The distribution of physical access to higher education can be represented using common indicators of inequality

Area-based accessibility indices – such as the “competitive accessibility index” – can be used to show the level of territorial inequality in access to services using Lorenz curves to provide a graphical representation of the distribution of accessibility and the Gini coefficient to summarise the level of inequality in access into a single – and comparable – indicator. An unequal territorial distribution of higher education opportunities across the territory compared to student demand would be evidenced by a greater concentration of the distribution study places, which would be shown by a lower Gini coefficient or a more inward-bending Lorenz curve. Figure 5.6 shows that the spatial distribution of opportunities in Portugal, using the 30-minute driving-time threshold, is more concentrated (a Gini coefficient of 0.86) than the distribution of potential students (a Gini coefficient of 0.73). There is no evidence of a larger concentration of supply compared to demand when using a 45-minute threshold or the competitive index.

Figure 5.6. Inequality in access to higher education across municipalities in Portugal

In Portugal’s relatively dispersed higher education system, physical proximity to an HEI has comparatively limited influence on higher education attendance

As noted earlier in this chapter, international evidence has shown a correlation between proximity of a higher education institution and the chances of local people attending higher education. In Portugal, where the majority of the population lives relatively close to at least one higher education campus, the correlation between the physical accessibility of higher education institutions and participation rates in higher education is low. As shown in Figure 5.7, entry rates to higher education among secondary-school graduates from municipalities located relatively far from higher education institutions show a high dispersion. Many municipalities with notionally low accessibility to higher education study places have above-average shares of secondary graduates entering higher education, while other, similarly “remote”, municipalities show much lower entry rates.

Similarly, physical proximity to higher education provision does not necessarily translate into higher entry rates to higher education. Some municipalities – including many of those located in the functional urban areas of Lisbon and Porto – have comparatively low entry rates, despite the large number of study places available. These findings reflect the fact that a wide range of factors influence participation in higher education. For example, Portugal’s two largest cities concentrate a disproportionate share of the population from lower socio-economic backgrounds, who are less likely to achieve the school-leaving results necessary to access these cities comparatively selective higher education institutions.

Figure 5.7. Accessibility of study places and participation rates in higher education

However, those who graduate in places that concentrate large amounts of higher education provision have better employment outcomes

Students who attend higher education in locations with high concentrations of higher education (many study places) do appear to have better employment outcomes. The share of recent higher education graduates (from the academic years 2016/17 to 2019/20) that that were registered as unemployed in the second half of 2020 was lower for programmes located in municipalities with high accessibility to higher education study place, particularly in the Lisbon Metropolitan Area (Figure 5.8). The picture locations which concentrate fewer study places was highly variable, with graduates from HEIs in Santarém having comparatively low unemployment rates (as the same levels as municipalities in the Lisbon FUA), while graduates from HEIs in other locations, such as Idanha-a-Nova and Mirandela, had unemployment rates around twice those of institutions in the Lisbon FUA. Higher rates of unemployment could be related to a range of factors, including the quality of the programmes offered and the availability of suitable employment opportunities for graduates who chose to remain in the locality or region where they study.

Figure 5.8. Accessibility to study places and unemployed graduates

Tuition fees and student financial aid in Portugal

Portugal has reduced regulated tuition fees in public institutions in recent years

Public higher education institutions in Portugal charge tuition fees to all students. The level of fees in short-cycle programmes, bachelor’s programmes and master’s programmes is regulated by law, with maximum annual fees set at EUR 697 in the academic year 2021/22 (see Box 3.1 in Chapter 3). Tuition fees were originally introduced in 1941 at a level of 1 200 escudos (around 6 euros in nominal terms). As shown in Figure 5.9, tuition fees were first raised substantially from this low level in the early 1990s and then raised significantly in the academic year 2003/04 and thereafter increased gradually, reaching EUR 1 063.47 a year in 2018/19. Portugal’s government then made a commitment to reduce regulated fees – ostensibly as part of its agenda for widening access to higher education. Regulated fees were initially cut by 20% for the year 2019/20 and again by 20% for 2020/21. As noted in the discussion of institutional funding in Chapter 3, public higher education institutions received additional funds from the state budget designed to compensate for the loss of tuition-fee income.

Figure 5.9. Tuition fees in Portugal over time

In comparison to average tuition fees in public higher education institutions in other OECD jurisdictions where fees exist, the tuition fees charged in Portugal were comparatively modest, even before the recent cuts. Comparative data collected on average tuition fees for bachelor’s programmes in public HEIs in OECD jurisdictions for the academic year 2017/18 showed that the average level of fees in the 21 jurisdictions where fees were changed was USD 3 620, after adjusting for purchasing parity. This compared to purchasing-power-adjusted fees in Portugal for the same year of USD 1 529 (EUR 1 063 converted to dollars and purchasing power parity), equivalent to 42% of the average of OECD systems (OECD, 2020[17]). With the recent fee reductions, average tuition fees in Portugal are likely to have decreased to around 25% of the average of OECD systems. Nevertheless, public HEIs in some other OECD jurisdictions – notably the Nordic countries and Germany – do not charge any tuition fees to domestic undergraduate students.

The public student financial aid system in Portugal supports a comparatively small proportion of the student population

Alongside its policy of tuition-fee moderation, Portugal has a well-established system for providing means-tested student grants, administered by the Directorate-General for Higher Education (DGES) and 60% of which is funded with European Structural and Investment Funds. In 2022, students enrolled for at least 30 credits in their first short-cycle, bachelor’s or master’s programme were eligible for grants if the per-capita annual income in their household was less than EUR 8 962 (equating to a monthly income of EUR 640 in Portugal’s 14-month system of remuneration). This corresponds to a monthly income level for one person below the annual minimum wage in Portugal in 2022 (EUR 705 per month) and less than half the level of the EUR 1 361 average monthly wage in Portugal in 2021 (Statistics Portugal, 2022[18]). The threshold levels mean that grants are clearly targeted at students from low-income families. In 2021/22, only around one-quarter of all students in public higher education (in short-cycle to master’s level programmes) received a grant (DGES, 2022[19]).

In 2021/22, the minimum annual grant, which all students meeting the household-income and other basic criteria receive, was EUR 871. The theoretical maximum annual grant for full-time students is fixed at 11 times the national Social Support Index reference value (Indexante dos Apoios Sociais – IAS) plus the value of the maximum regulated annual tuition fee (In 2022: 11 x EUR 443.20 + EUR 697 = EUR 5 572). Students studying part-time (at least 30 credits) receive roughly half the grant of full-time students. To calculate the actual level of the grant, the authorities take into account the actual level of tuition fees paid by the student and deduct the average per-capita income of the student’s household from this reference maximum grant, taking into account that the minimum grant level is EUR 871. The result of this calculation method is that a large proportion of eligible students receive the minimum grant.

In addition to the basic grant, students in receipt of a grant that live away from home are entitled to a housing supplement, which can be significantly higher than the grant itself. In 2022, the level of this supplement was EUR 77 per month for students in an official (subsidised) student residence and EUR 219 per month for students living away from home outside a student residence. The value of the supplement for students living away from home but not in a student residence is increased to EUR 285 for students in Lisbon and EUR 263 for students in Porto, to take account of high housing prices in the large cities.

From an international perspective, Portugal has a public higher education system with moderate fees, but also a student-aid system with comparatively limited coverage and moderate grant levels. Figure 5.10 plots OECD jurisdictions based on the level of the average or most common tuition fees charged for bachelor’s programmes in public HEIs in 2019/20 (vertical axis) and the proportion of national students that receive direct public financial support (horizontal axis).

Figure 5.10. Tuition fees and financial support for students in OECD jurisdictions

Three main groups of system can be distinguished. First, those, like Portugal, but also Belgium, Germany, Austria and, to some extent, France, with comparatively low (or inexistent in the case of Germany) tuition fees and a direct student-support system that reaches a minority of the student population. Second, the systems in Denmark and Sweden where there are no tuition fees for domestic students in public HEIs, but where student support is accessed by nearly all students. In these countries, students are considered to be independent of their parents after the age of 18, so family income is not a factor in allocation of student support. Finally, systems in English-speaking countries with high tuition fees, but student-support systems that reach a high proportion of the student population. In England and Australia, the student-support systems as based on income-contingent, subsidised public loan systems, while a large proportion of students in the United States are eligible for federal (Pell) and state-level student grants.

No recent, comparable international data are available on the average level of student financial aid paid to individual students. Complex eligibility criteria also make it difficult to compare financial support systems across countries. Nevertheless, available information suggests that grant levels in Portugal are broadly comparable to those in France and the Flemish Community of Belgium, but lower than student grants in Italy and Germany. These are all systems, which, like Portugal, have low or no fees and where a minority of the student population receives student aid.

In 2022, the annual value of student grants in the Flemish Community of Belgium ranged from EUR 281.36 (the minimum level) to a maximum of EUR 2 613 for students living at home and up to EUR 4 354 for students living away from home (Flemish Government, 2022[21]). In France, the annual value of student grants in 2022 was between EUR 1 042 and EUR 5 736, depending on household income (Government of France, 2022[22]), while in Italy, minimum grant levels for students living at home were EUR 1 982, for students commuting to study EUR 2 899 and for students living away from home EUR 5 258 (Government of Italy, 2021[23]). The maximum student grant in Germany (referred to as “BAföG”, after the legislation establishing the system, the Bundesausbildungsförderungsgesetz) in 2022 for those living at home was EUR 592 per month (EUR 7 104 annually) and for students living away from home EUR 861 (EUR 10 332 annually). The average student grant paid in Germany is 2020 was EUR 574 per month (Destatis, 2021[24]). As shown in Figure 5.10, just over one-fifth of enrolled students receive student grants in Germany.

The proportion of students receiving grants varies considerably between public HEIs in Portugal, reflecting differences in the socio-economic profile of students

As shown in Figure 5.11, the proportion of enrolled students that receive a student grant varies considerably between public higher education institutions in Portugal. Whereas in the autonomous island regions of the Açores and Madeira, upwards of around 40% of students in eligible study levels receive a grant, this proportion is less than 20% in HEIs in the Lisbon Metropolitan Area and the Universidade do Porto. Three further universities outside metropolitan and littoral regions (Universidade de Trás-os-Montes e Alto Douro – UTAD, Universidade do Minho and Universidade da Beira Interior) have an above-average (>25%) proportion of grant beneficiaries, as do Porto’s school of nursing (ESEP) and polytechnic institutes in interior regions.

The patterns illustrated in Figure 5.11 reflect a combination of factors. As around two-thirds of students in public higher education institutions in Portugal attend a “local” HEI, variation in eligibility for grants is partly explained by differences in average income between regions. Households in Lisbon, for example, have, on average, higher incomes than households in Açores, Madeira or most interior regions, while household income thresholds for grant eligibility are set nationally. A second factor is the selectivity of institutions. As performance in secondary school is correlated with socio-economic status and entry to high-demand, prestigious institutions is substantially dependent on students’ grades school-leaving exams (which serve for the National Access Competition), it follows that a smaller proportion of students in comparatively selective institutions (such as those in Lisbon or the Universidade do Porto) is eligible for a grant than in institutions with lower demand for places. Finally, the mix of subjects offered by institutions also influences the socio-economic profile of students, although to a lesser extent that the first two factors. Thus, polytechnics and polytechnic schools serve, on average, a higher proportion of students from low socio-economic backgrounds than universities.

Figure 5.11. Proportion of students receiving a student grant by public HEI

The +Superior Programme provides additional mobility grants for low-income students to study in interior and island regions

Since the academic year 2014/15, Portugal has also used resources from the European Social Fund (one of the strands of European Union Structural and Investment Funds) to finance a complementary student‑grant programme to support students to study in higher education institutions with decreasing study demand. Since the academic year 2016/17, the grants have been targeted to students from low-income backgrounds. The +Superior (Mais Superior) programme has the explicit aim of contributing to territorial cohesion by encouraging students to move to regions that are affected by population decline and where HEIs may otherwise have difficulty in attracting students from other regions of Portugal. In the autonomous island regions of Açores and Madeira, Algarve and Alentejo all public HEIs are eligible for the programme. In the more diverse regions of Centro and Norte, which are home to highly prestigious and attractive HEIs, as well as institutions in more challenging situations, eligible students can only receive +Superior grants if they attend certain institutions in more remote parts of the regional territory.

To be eligible for a +Superior grant, students must have secured a place at an eligible HEI, have their habitual residence in a different NUTS III region from the HEI in question (i.e., they need to move locality to be eligible for a grant) and have been awarded a mainstream student grant (i.e., they must come from a low-income background). The standard value of the grant is (in 2021/22) EUR 1 700 per year, with a maximum number of grants fixed for each region, as shown in Table 5.2. The value of the grant is increased by 15% for students who enrol in short-cycle TeSP programmes, as well as students entering higher education through special entrance procedures for those over 23. Until 2022/23, candidates for +Superior grants were prioritised for the grant in ascending order of the per-capita income of their household (DGES, 2021[25]), but from 2022/23, the system was amended to make all students from low-income backgrounds eligible, without prioritisation.

Region where host HEIs are located	Grants available for the region	Number of candidates	Number of grants awarded	Proportion of total grants	Number of grant renewals
Alentejo	450	1 021	459	20.4%	711
Algarve	110	348	116	5.2%	147
Centro *	800	2 343	800	35.6%	1 295
Norte **	800	2 640	851	37.8%	892
Região Autónoma da Madeira	35	86	4	0.2%	5
Região Autónoma dos Açores	35	122	19	0.8%	14
Total	2 230	556	2 249	100%	1 769
Non-eligible regions	0	1 590	0	-	0

Note: * Eligible HEIs in Centro: IP Castelo Branco, IP Guarda, Universidade da Beira Interior, IP Tomar, Escola Superior de Tecnologia e Gestão de Oliveira do Hospital do IP Coimbra, IP Viseu. ** Eligible HEIs in Norte: IP Viana do Castelo, Universidade de Trás -os -Montes e Alto Douro (UTAD) and IP Bragança.

Source: DGES (2022[26]) Estatísticas – Programa +Superior (Statistics – +Superior Programme) https://www.dges.gov.pt/pt/pagina/estatisticas-programa-superior?plid=373, (accessed on 23 July 2022).

Portugal’s government has increased the number of +Superior grants funded in recent years and presents the programme as part of its wider efforts to promote widened access to higher education and promote territorial cohesion (MCTES, 2021[3]). To date, no external evaluation of the programme has been conducted to obtain a clear understanding of the impact of the programme on participation in higher education and students’ study choices.

Student services and housing

Responsibility for funding student services, including dedicated student housing, falls primarily to individual higher education institutions

In some OECD countries, non-academic services for students, such as student residences, catering and administration of student financial support, are administered by distinct entities, outside the organisational structures of individual HEIs. This is notably the case in France, where the Centres régionaux des œuvres universitaires et scolaires (Crous) provide these services, with a separate body for each educational district (académie), operating within a national network. Under this approach, students in localities with multiple HEIs can access a common set of services, independently of the specific institution in which they are enrolled. More commonly, however, student services and housing are the responsibility of individual HEIs, funded out of general revenue, with, in some systems, earmarked funds provided to institutions by government for provision of the services.

In Portugal, HEIs are responsible for funding and organising student services. Historically, institutions received an earmarked budget to fund their “Social Action Services” (SAS), responsible for student housing, catering and as a point of contact for financial support. In recent years, however, this budget has been mainstreamed into the main operating grant from the state budget (see Chapter 3), with institutions deciding on the internal allocation of funds to their Social Action Services and reporting this to the authorities. As illustrated in Figure 5.12, the level of resources per enrolled student allocated to the SAS varies considerably between public HEIs. While the SAS budget in the Universidade dos Açores in 2021 was the equivalent of over EUR 500 per enrolled student, the equivalent figure for several institutions, include polytechnic institutions in Lisbon, Porto and Setúbal was under EUR 200 per enrolled student.

Figure 5.12. Income of institutional “Social Action Services” (SAS)

While the level of investment required in the Social Action Services in individual HEIs will depend to some extent on the socio-economic profile of the student population (see Figure 5.12) and the proportion of students living away from home (and requiring housing), it is notable that certain polytechnic institutes – which would typically be expected to attract students from lower-income backgrounds – have the lowest rates of investment in their Social Action Services.

During discussions held for this review, some representatives of higher education institutions raised concerns that the end of earmarked funding for student-support services had reduced institutions’ willingness to share their student facilities with students from other HEIs located in the same city. This is primarily an issue in Lisbon, Porto and Coimbra which are home to multiple public HEIs. In such locations, it appears that is a case for greater pooling of student services between institutions.

Increasing the supply of student housing is a specific priority of Portugal’s government

Since 2018, Portugal’s government has mobilised additional resources to invest in student housing, one of the services co-ordinated and – in the case of dedicated student residences, operated – by institutions’ Social Actions Services. The National Plan for Housing in Higher Education (Plano Nacional para o Alojamento no Ensino Superior – PNAES) has provided funds to increase capacity to house students who move location to study (MCTES, 2022[28]). The main target audience for the increase in housing capacity is students aged 25 or less who attend an HEI more than 50km from their family home, officially referred to as estudantes deslocados (displaced students). The PNAES aims to increase the offer of student rooms in dedicated student residences, in accommodation provided by other public or private organisations and, in some cases, hotels and guesthouses.

As shown in Table 5.3, “displaced students” accounted for around one-third of students attending public higher education institutions in 2020/21 – more than double the proportion in the private higher-education sector. Among these “displaced students”, around 40% were defined as in financial need (in that they receive a student grant), representing a total of almost 43 000 students, or roughly 13% of total enrolment in public higher education institutions. As shown in Table 5.1, under 18 000 beds in subsidised student accommodation were available across Portugal in 2021, meaning there is significant unmet demand.

Sector of higher education	Total enrolment (headcount)	Students living away from home (deslocados)	Students living away from home as % all students	Students living away from home and in financial need	Students in financial need as % of those living away from home	Students living away and in financial need as % all students
Total	411 995	119 887	29%	44 752	37%	11%
Public	335 139	108 406	32%	42 915	40%	13%
Private	76 856	11 481	15%	1 837	16%	2%

Source: MCTES (2022[28]) Plano Nacional para o Alojamento no Ensino Superio (National Plan for Housing in Higher Education) https://pnaes.pt/ (accessed on 24.July 2022).

Analysis conducted in the preparation of the PNAES illustrated that greatest mismatch between the number of displaced students (overall) and available student rooms were in Lisbon, Porto and Coimbra, as well as at the Instituto Politécnico do Cávado e Ave (IPCA) (MCTES, 2022[28]). Under the Contrato de Legislatura for 2020-23, the government established the target of raising the number of student rooms available at regulated prices to 30 000 by 2030. As part of the “Resilience” strand of the EU-funded Recovery and Resilience Plan, a loan of EUR 375 million has been agreed to invest in student housing in the period up to 2026 (Government of Portugal, 2022[29]), with the objective of reaching the 30 000 target.

Policy issues and recommendations to Portugal

Taking into account the analysis above and the findings from the interviews conducted with representatives of higher education institutions and public authorities, this section identifies the main policy issues for related to creating an accessible network of higher education campuses across the Portuguese territory, the national financial support system for students and policies on student services and housing and provides recommendations.

Maintain a commitment to ensuring territorial coverage of higher education, but ensure a strong focus on quality and relevance in regional locations

In recent decades, Portugal has successfully – and substantially – increased the reach of its higher education system, initially expanding the network of public higher education institutions across the country and subsequently expanding participation through an increasingly diverse set of programme offerings. Compared to OECD countries of similar size, Portugal has a dense network of institutions that contributes to the accessibility its higher education system. Particularly for individuals from low-income backgrounds, for whom moving to attend higher education would be financially challenging, and those who lack the capacities and preparation needed to study successfully online, having a higher education campus in their home locality or region is likely to increase their chances of entering and completing higher education.

It is, therefore, appropriate for Portugal to maintain a commitment to the “physical accessibility” of higher education across the territory of the country. This is particularly the case for the offer of initial higher education programmes, such as short-cycle qualifications or professionally oriented bachelor’s programmes that attract large student numbers and that may be particularly well aligned with the needs of populations less able or willing to move further afield to study. Having high-quality opportunities to study in short-cycle TeSP and professionally oriented bachelor’s programmes in core subjects, such information technology, teacher education and certain areas of social care that are distributed across population centres and regions is particularly important, for example. As programmes become more advanced and more specialised, the case for concentration of offerings in a limited number of locations becomes stronger. Student demand for such programmes is more limited and specialist academic staff would ideally be concentrated in a small(er) number of centres, allowing sufficient critical mass and peer effects to deliver the quality of education and the learning environments that students require.

As discussed in Chapter 4, there is scope in Portugal for higher education institutions to sharpen their institutional profiles and to strengthen or create distinct centres of excellence providing specialised and advanced programmes, based on existing strengths in the areas of research and regional engagement. Equally, some existing provision, particularly at bachelor’s level and higher, may become surplus to requirements, as demographic trends evolve, and student demand falls further. This is likely to lead to institutional restructuring in some cases and may ultimately require some smaller institutions to work together as campuses within a single institutional structure. As shown by the development of branch campuses in higher education systems as diverse as Denmark and France, maintaining the territorial coverage of the higher education system does not imply higher education institutions need to be built or maintained in conventional forms. In some cases, there will be a trade-off to be made between maintaining “local” provision of higher education and ensuring sufficient critical mass, quality and relevance, including in terms of the employment opportunities offered to graduates in the region. In such cases, a careful evaluation of how students can best be served will be required.

Recommendations

1. Maintain physical accessibility of campuses as a criterion for planning the future of the higher education system, focusing on ensuring territorial coverage for entry-level tertiary programmes such as TeSP and other undergraduate programmes with strong student demand and high relevance to local and regional economies.

2. Recognise, in line with the recommendations above, that maintaining the territorial coverage of the higher education network does not imply maintaining the existing configuration of institutions. As part of strategic planning for the system it will be important to assess the role, in the medium term, of networked higher education campuses, exploiting the benefits of in-person and digital learning.

Consider linking tuition-fee levels to socio-economic criteria, while increasing the value of financial support to the students most in need, as public finances allow

Portugal has made considerable efforts in recent years to support low-income students to enter and complete higher education, through reducing study costs (with tuition-fee reductions) and increasing the reach of the student-grant system. From an international perspective Portugal is situated clearly in a cluster of European countries, which include Austria, Belgium, France and Italy, with comparatively low tuition fees in the public higher education sector and student financial aid systems focused exclusively on the lowest-income students. In light of the financial constraints facing Portugal’s government – like other OECD governments – in the coming years, it will be challenging to increase greatly the level of investment in existing student-grant mechanisms, which already depend for a majority of their resources on European funds.

The decision to cut regulated tuition fees in public HEIs for all students and compensate institutions for the lost revenue has absorbed significant public resources to pay for what is effectively an untargeted subsidy that benefits not only students from lower-income backgrounds, but also those from middle and high-income backgrounds. A more nuanced approach would involve a progressive system of tuition fees, with the lowest fees for students in receipt of a grant, mid-range fees for students that do not qualify for a grant but come close to the eligibility requirements and higher fees for other students from more affluent backgrounds. The Flemish Community of Belgium operates such a model. In 2021/22, grant recipients (beursstudenten) in the Flemish system paid annual tuition fees of EUR 113.20 to attend publicly funded HEIs full-time, those who nearly qualify for a grant (bijna-beursstudenten) paid EUR 505.90, while other students paid EUR 961.90 (Flemish Government, 2022[30]).

Portugal’s system of student grants already provides financial support for students in short-cycle TeSP programmes and provides for grants that are reduced pro-rata from students studying part-time, as long as they are enrolled for at least 30 credits per year. As the government and higher education institutions proceed with efforts to expand programme provision for adults seeking upskilling and reskilling opportunities, it would be appropriate to investigate whether the current grant system is sufficiently flexible to support a more diverse student population and whether it is most appropriate to support adult learners through the grant system or other mechanisms.

The +Superior programme continues to provide grants to low-income students studying in designated public higher education institutions in interior and island regions. To the knowledge of the OECD review team, since the inception of this programme in 2014, there has not been an independent evaluation of its effectiveness and efficiency. In order to plan for the future of this policy instrument, such an evaluation is required, in order to understand better which students take up +Superior grants and why, what they study, how successful they are in their studies and how they fare after obtaining qualifications. It is important that any future programme ensures the interests of students take absolute priority and that they are directed to study opportunities that are appropriate to their needs and offer them strong employment prospects. Low-income individuals should only be encouraged to move to study if these conditions are met.

Recommendations

3. Introduce a differentiated system of tuition fees, similar to the system used in the Flemish Community of Belgium, with the lowest fees for grant recipients, a medium fee level of lower-income students that do not qualify for grants and a return to higher fees for other students. Use resources freed up by such a policy to increase the eligibility threshold and level of student grants.

4. Conduct a review of the current eligibility criteria for student grants (such as the 30 credit enrolment requirement) to evaluate, in greater depth than was possible for this review, if the system is sufficiently flexible to support the increasingly diverse student population that the government aspires to achieve, whether changes are required or whether other policy instruments should be used to support adult learners.

5. Commission an independent evaluation of the +Superior programme to gain a better understanding of the profile of students supported, their rationale for their study choices and their study and employment outcomes. Use the findings from the evaluation to inform the future direction of this policy, ensuring the interests and outcomes of students take precedence over other considerations.

Explore methods to ensure more equitable investment in student services across the territory

Although it is difficult to compare investment levels in student services across HEIs that operate in different contexts and serve different student populations, the current variation in per-student investment in Social Actions Services does not appear to have a clear justification. More systematic analysis would be required to establish the causes and justification for the differences observed between institutions. While a return to earmarked funding of student services used previously in Portugal is likely to create administrative burden, reduce the flexibility of institutions and lead to inefficiencies, minimum national standards or guidelines may be required to ensure more uniform levels of student-service provision across the country. Moreover, in cities and towns where multiple HEIs are located, there is a strong case for pooling student services between the institutions to ensure accessibility and efficient use of resources. This could be guaranteed by co‑operation agreements between institutions or, potentially, the creation of legally separate, jointly owned student service operations.

The National Plan for Housing in Higher Education (PNAES) appears to respond to a real need for additional student accommodation in Portugal, particularly in larger cities where rental prices are increasingly unaffordable for students who move location to study. The allocation criteria for PNAES funding have sought to ensure investments are targeted in locations with greatest unmet need for subsidised student accommodation. Any future public investment in student housing should also ensure appropriate targeting on the localities with greatest unmet student need to avoid inefficient deployment of limited resources.

Recommendation

6. Analyse the factors that explain the current variation in the per-student levels of investment in student services between public HEIs in Portugal and the effects of this variation in selected locations. On this basis, evaluate the case for minimum national standards or guidelines – such as a minimum level of services that should be provided – for institutional Social Action Services, which could, in turn, be assessed through institutional audits.

7. In locations with multiple public HEIs, require HEIs to develop solutions that allow student services to be shared between institutions, where there is a rational justification for this, to increase access and improve efficiency.

8. Ensure that future investments in publicly funded student housing are targeted in locations with greatest unmet need for housing from students and are planned with future enrolment levels clearly in focus.

References

[9] Arbo, P. and P. Benneworth (2007), “Understanding the Regional Contribution of Higher Education Institutions: A Literature Review”, OECD Education Working Papers, No. 9, OECD Publishing, Paris, https://doi.org/10.1787/161208155312.

[10] Bonaccorsi, A. and B. Lepori (2019), The regional structure of European Higher Education, https://doi.org/10.5281/zenodo.5082998.

[24] Destatis (2021), BAföG-Statistik: 6,0 % weniger Geförderte im Jahr 2020 (Student grant statistics: 6% fewer students support in 2020), Statistisches Bundesamt, https://www.destatis.de/DE/Presse/Pressemitteilungen/2021/08/PD21_369_214.html (accessed on 24 July 2022).

[14] DGEEC (2022), “Vagas e Inscritos (inclui inscritos em mobilidade internacional) (Study places and enrolments (including enrolments involving international mobility)”, Direção-Geral de Estatísticas da Educação e Ciência (DGEEC), https://www.dgeec.mec.pt/np4/EstatVagasInsc/ (accessed on 12 January 2022).

[15] DGEEC (2021), Dados e Estatísticas de Cursos Superiores (Data and statistics on higher education programmes), Infocursos, https://infocursos.medu.pt/bds.asp (accessed on 10 July 2022).

[26] DGES (2022), Estatísticas - Programa +Superior (Statistics - +Superior Programme), Direção-Geral do Ensino Superior, https://www.dges.gov.pt/pt/pagina/estatisticas-programa-superior?plid=373 (accessed on 23 July 2022).

[19] DGES (2022), Informação Estatística - Bolsas de Estudo para Estudantes do Ensino Superior (Statistical information - Student Grants), Direção-Geral do Ensino Superior, https://www.dges.gov.pt/pt/pagina/informacao-estatistica-bolsas-de-estudo-para-estudantes-do-ensino-superior?plid=373 (accessed on 23 July 2022).

[25] DGES (2021), Despacho nº 11740-A/2021, de 26 de novembro Aprova o Regulamento do Programa +Superior para o Ano Letivo de 2021-2022 (Order approving the regulations for the +Superior programme for the academic year 2021/22), Direção-Geral do Ensino Superior, https://www.dges.gov.pt/pt/pagina/informacoes-1 (accessed on 12 July 2022).

[8] Do, C. (2004), “The effects of local colleges on the quality of college attended”, Economics of Education Review, Vol. 23/3, pp. 249-257, https://doi.org/10.1016/j.econedurev.2003.05.001.

[1] Eurostat (2022), Indicators, https://ec.europa.eu/eurostat/databrowser/ (accessed on 20 January 2022).

[21] Flemish Government (2022), Bedragen studietoelagen 2022-2023 (Value of student grants in 2022-23), https://www.studietoelagen.be/bedragen-studietoelagen-2021-2022 (accessed on 24 July 2022).

[30] Flemish Government (2022), Studiegelden (Tuition fees), https://onderwijs.vlaanderen.be/nl/studenten/kosten-toelagen-en-werken/studiegelden (accessed on 26 July 2022).

[11] Florczyk, A. et al. (2019), GHSL Data Package 2019, Publications Office of the European Union, https://doi.org/10.2760/290498.

[7] Frenette, M. (2006), “Too Far to Go On? Distance to School and University Participation”, Education Economics, Vol. 14/1, pp. 31-58, https://doi.org/10.1080/09645290500481865.

[22] Government of France (2022), Étudiant : bourse sur critères sociaux (Student: grant based on social criteria), Service Public - Le site officiel de l’administration française, https://www.service-public.fr/particuliers/vosdroits/F12214 (accessed on 24 July 2022).

[23] Government of Italy (2021), Decreto Ministeriale n. 157 del 12-02-2021 (Ministerial Decree 157 of 12-02-21)1, Ministero dell’Università e della Ricerca, https://www.mur.gov.it/it/atti-e-normativa/decreto-ministeriale-n-157-del-12-02-2021 (accessed on 24 July 2022).

[29] Government of Portugal (2022), Plano de Recuperação e Resiliência (Recovery and Resilience Plan), Recuperar Portugal, https://recuperarportugal.gov.pt/ (accessed on 24 July 2022).

[2] Government of Portugal (2019), Contrato de Legislatura entre o Governo e as Instituições de Ensino Superior Públicas 2020-2023 (Contract for the Legislative Period between the Government and public higher education institutions 2020-2023), https://www.igefe.mec.pt/Files/DownloadDocument/72?csrt=6785169830679341608 (accessed on 28 May 2020).

[27] IGeFE (2022), Data on institutional income and expenditure 2012-2021 (unpublished).

[13] Mapbox (2022), Navigation, https://docs.mapbox.com/api/navigation/ (accessed on 12 January 2022).

[28] MCTES (2022), Plano Nacional para o Alojamento no Ensino Superio (National Plan for Housing in Higher Education), Ministry of Science, Technology and Higher Education (MCTES), https://pnaes.pt/ (accessed on 24 July 2022).

[3] MCTES (2021), Acompanhamento do “Contrato de Legislatura” assinado entre o Governo e as Instituições de Ensino Públicas para 2020-2023 (Monitoring of the Contract for the Legislative Term concluded between the government and public HEIS for 2020-2023), Ministry of Science, Technology and Higher Education, https://www.igefe.mec.pt/Page/Index/51 (accessed on 20 July 2022).

[16] Morgado, R. (2018), “Sobre o valor das propinas (About the value of tuition fees)”, Diário de Noticias, https://www.dn.pt/opiniao/opiniao-dn/convidados/sobre-o-valor-das-propinas-10012407.html (accessed on 22 July 2022).

[12] OECD (2022), ADHEP database.

[20] OECD (2021), Education at a Glance 2021: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/19991487.

[17] OECD (2020), Education at a Glance 2020: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/69096873-en.

[4] Sá, C., R. Florax and P. Rietveld (2006), “Does Accessibility to Higher Education Matter? Choice Behaviour of High School Graduates in the Netherlands”, Spatial Economic Analysis, Vol. 1/2, pp. 155-174, https://doi.org/10.1080/17421770601009791.

[5] Spiess, C. and K. Wrohlich (2010), “Does distance determine who attends a university in Germany?”, Economics of Education Review, Vol. 29/3, pp. 470-479, https://doi.org/10.1016/j.econedurev.2009.10.009.

[18] Statistics Portugal (2022), Remuneração bruta mensal média por trabalhador - 4.º trimestre de 2021 (Gross monthly pay per worker - 4th Quarter 2021), Estatísticas do Emprego (Employment statistics), https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_destaques&DESTAQUESdest_boui=526268225&DESTAQUESmodo=2 (accessed on 24 July 2022).

[6] Walsh, S., D. Flannery and J. Cullinan (2015), “Geographic accessibility to higher education on the island of Ireland”, Irish Educational Studies, Vol. 34/1, pp. 5-23, https://doi.org/10.1080/03323315.2015.1010302.

Notes

← 1. Importantly, this study considers the presence of a HEI in a region but not the levels of accessibility to it, thus implicitly assuming people have access only to HEIs in their own TL3 region.

← 2. For instance, for a region stretching over thousands of kilometres with a single urban centre and a sparsely populated country side, a single point cannot possibly represent the level of access experience by both urban and rural inhabitants in the region.

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