The impact of high fee-low-subsidy and low fee-high-subsidy higher education funding models on higher education access in European Union countries

Abstract

Introduction. Higher education funding is relevant topic and widely analysed by scientist all other the world. Nowadays there is very big difference between higher education funding models across European Union countries – students have to pay very high fees for their studies in one countries, while in other countries – students have no obligations to pay for their studies at all, or have to pay very low tuition fees. All EU member states declare importance of HE for the future of economic, individual and society wellbeing. With respect to cost-sharing principle in higher education funding, higher education funding models can be divided into four models: Low-fee-High-subsidy; Low-fees-Low-subsidy; High-fees-High-subsidy and High-fee-Low subsidy.
 Aim and tasks. The aim of this article is to perform comparative analysis of two extremely different higher education funding models, which are applied in European Union states – Low-fee-High-subsidy higher education funding model (LFHS model) and High-fee-Low-subsidy higher education funding model (HFLS model).
 Results. The results of scientific research shows, that LFHS and HFLS models, which were analysed, have a different impact on access to higher education (i.e. gross enrolment rate (GER), GER male, GER female and HE graduation rate (HEGR) in EU countries.
 Conclusions. Tuition fees (max., min., net, normative) have a statistically significant, but not only positive or negative impact on enrolment to HE and graduation of HE, as well as for women and men enrolment to HE (GER male, GER female) – it depends on funding model EU state applies. Max. need-based grants have positive impact only in LFHS model case as well as min. need-based grants. In addition, the results of research show, that there is gender inequality – women enrolment to HE exceed men enrolment at most in HFLS model. Men are more likely to study in countries with higher need-based grants (for instance, in LFHS model countries). Counties with higher GDP per capita are more likely to apply LFHS model, than countries with lower GDP per capita.

Statistical assesment of webometric rating indicators of Ukrainian higher education institutions

“…In the context of digitalization of all social processes, the role of the image component of modern HEI, the reputation and qualifications of its teachers and graduates, is growing. On the one hand, modern HEI face the task of providing qualitative education and meeting the needs of more educated and demanding consumers, and on the other hand, they must have a stable financial position as participants in the "educational" market, which will contribute to the development of the national economy (Bantash et al, 2020;Kučaidze, Jurgelevičius, 2020;Yankovyi et al, 2020).…”