(2 rânduri libere, 11p) Studies and Scientific Researches. Economics Edition, No 34, 2021 http://sceco.ub.ro 24 CONSIDERATIONS ON THE IMPACT OF HIGHER EDUCATION FROM AN ECONOMIC AND NON-ECONOMIC PERSPECTIVE Bogdan Vasile Nichifor ”Vasile Alecsandri” University of Bacau , bogdan.nichifor@ub.ro Laura Cătălina Ţimiraş ”Vasile Alecsandri” University of Bacau , timiras.laura@ub.ro Lumita Zaiț ”Vasile Alecsandri” University of Bacau , luminita.zait@ub.ro Abstract The impact of higher education is reflected in both individual and collective benefits, economic and non-economic. For example, if pursuing higher education means an increased chance of employment at the individual level and of being better paid, at the macroeconomic level, a higher share of the population with higher education is associated with lower unemployment rates, with an increase in productivity and, consequently, with an acceleration of economic growth. The economic advantages of higher education are complemented by non-economic advantages such as: increased manifestation of civic spirit, increased care and better health, a decrease in crime etc. among the population with higher education. This article aims to highlight some of the economic and non-economic benefits, individual or collective, of higher education, starting on the one hand from information in the literature and on the other hand from official statistical information, using EU statistical information. Keywords tertiary education; economic benefits; non-economic benefits JEL Classification I25, I29 Introduction The aim of this paper is to highlight some of the economic and non-economic benefits that higher education has for both society and the individual. Information on these benefits was collected on the one hand from the literature and, on the other hand, resulted from the analysis of relevant statistical data, using data at EU level. Economic and non-economic benefits of higher education at individual and collective level, as they result from the literature The literature abounds in theories and research approaches that highlight the favorable impact of higher education on economic development, at an aggregate level, on the one hand, and on individuals, on the other. Higher education is conventionally associated with three social key functions, namely: significant contribution in the field of education, high impact in the field of research and support in knowledge transfer. Nichifor, Țimiraș, Zaiț 25 The most important dimension of this impact, implicit and visible, is manifested in the area of economic benefits, being known the contribution of higher education in the economic growth of a state, respectively, at individual level, the intrinsic link between the degree of education and income. Particular attention should be paid to non-economic benefits, as it is known that the results of education translate, at the individual level, into knowledge, skills, attitudes, and values. In other words, as noted by Bynner, Schuller, and Feinstein (2003), non- economic benefits capture effects that cannot be directly measured in terms of income and productivity, their contribution being related to increasing quality of life. In this context, it is obvious that higher education also has an important cultural dimension (Barr, 2012), contributing, in addition to obtaining a high level of performance at the macroeconomic level, to promoting an extensive set of values. One of the non-economic benefits of higher education is the promotion of civic spirit. The specialized literature that highlighted the impact of higher education on the dissemination of civic spirit refers mainly to the attitude towards the exercise of the right to vote. Research in Europe and the United States has shown a direct link between education and voting (Milligana , 2004; Borgonovi and Miyamoto , 2010; Dee , 2004; Teen , 2007), the gap between individuals with higher education and those with a low level of education varying strongly, in the analyzed areas, from the perspective of voting participation. Moreover, we appreciate that this discussion can be extended to the area of influence exerted by the representatives of the political environment on the political choices of individuals, the practice proving that individuals with a low level of education are more easily oriented towards supporting a certain political current. On the other hand, individuals with higher education, beyond being more interested in the political life, have their own beliefs, being difficult to urge in the absence of strong rational arguments. Correlated with the benefit of manifesting the civic spirit, also in the non-economic area of the advantages provided by higher education is also found the one of increasing the civic commitment. In the field of civic engagement, the literature (Calhoun , 2006; Borgonovi and Miyamoto , 2010; Borgonovi , 2012; Ogg , 2006) includes values such as involvement in volunteering, participation in public debates, mutual trust and tolerance towards others. If Calhoun is the one who supports the theory that higher education institutions are accelerators in the development and increase of civic engagement, especially due to involvement in the public and professional areas, the rest of the mentioned works are focused on analyzing the relationship between education and tolerance to those around, namely trust in society. The liberalization of the labor market and the phenomenon of immigration from the European space were only 2 of the reasons that led to the conduct of research to highlight the link between the level of education and tolerance towards others. Thus, Bogronovi and Miyamoto (2010), studying the phenomenon in 21 European states, showed that highly educated individuals are much more tolerant with immigration than those with a low level of education. Practically, in the case of this dimension of civic engagement, it was observed that the marginal rate in the case of individuals with higher education is clearly higher than that of individuals with poor education (41%, compared to 18%). A possible interpretation of this phenomenon is that attitudes and beliefs about society as a whole end in the age range of 18-25 years, which is also the interval for pursuing higher education, when the ground is created for experiencing interaction with foreign students. There are a number of authors in the literature who have highlighted a direct link between the high level of education and the crime rate. For example, Machin (2010) and Feinstein (2008), respectively Zaback , Carlson and Crellin (2012) are the ones who mention that individuals with higher education are the least likely to commit CONSIDERATIONS ON THE IMPACT OF HIGHER EDUCATION FROM AN ECONOMIC AND NON-ECONOMIC PERSPECTIVE 26 crimes. Obviously, the direct link between education level and crime rate cannot be eloquent in the absence of a broader context, which includes both objective indicators (standard of living, job security, etc.) and subjective ones (personality, individual value system). etc.). The impact of the elevated level of studies on health is the area that has been much addressed in the literature. Thus, according to studies conducted over time, the following areas of favorable influence of the level of higher education: • individuals with higher education, due to their lifestyle, are likely to fit into the segment of the population with a longer lifespan (Chevalier, 2010; Hout , 2012); • the educated population, with higher education, is less prone to the assimilation of behaviors harmful to health ( tobacco consumption, alcohol consumption, inadequate quantitative and qualitative food consumption, which generates obesity - Cutler et all , 2010; Kuntsche , 2004), the effects are also felt in the mortality rate (reduction of the mortality rate due to cardiovascular diseases - Mackenback , 2006; reduction of the incidence of premature births and infant mortality rate, in the case of smoking mothers - Currie and Moretti , 2003); • the high level of preparation of the partners favors the manifestation of a balanced family climate (Feinstein and Sabates , 2006); • the high level of training is also correlated with the manifestation of an obvious behavior of prevention in the field of health (Fletcher and Frisvold , 2009; Feinstein and Sabates , 2004; Baum et all , 2010). The literature (Brennan et all , 2010; Pascarella and Terenzini , 2005) goes in depth and even mentions the impact of higher education in terms of individual changes. In other words, it has been observed that for individuals who have completed higher education, this experience is associated with changes in both cognitive and attitudinal, as well as in areas that contribute to increasing the quality of life. A summary of the influences attributed to higher education on individual changes is provided by Brennan , Durazzi , and Tanguy (2013), as follows: • cognitive changes associated with academic development (improvement of communication skills and development of specialized vocabulary; assimilation of skills and abilities in the field of analysis; assimilation of information in various fields; capacity for synthesis and critical thinking, improvement of skills to adapt to innovative technologies etc.) • attitudinal changes (development of civic spirit; high tolerance in relation to others and in relation to society; openness to diversity, etc.); • psychological changes (increased self-confidence; higher control over one's own existence and increased independence; assimilation of interpersonal communication skills, etc.); • changes in the economic and career plan (clearly higher employment opportunities; adequate employment status and high earnings; job satisfaction according to the preparation, respectively according to one's own projections and expectations; job stability; socio - economic positioning favorable, high rate of return on investment in education, etc.); • change in the quality of life (improving health and prevention in this area; increasing life expectancy; a substantial improvement in the ability to educate one's children; improving decision-making capacity in the field of private consumption; demonstrating buying behavior predominantly rational, with a tendency to save and invest in income-generating activities; openness to the lifelong learning / improvement process, etc.). Nichifor, Țimiraș, Zaiț 27 According to the theory launched by Lagemann and Lewis (2010), focused on highlighting the non-economic benefits of higher education, at the individual level, graduates must achieve the following results: skills in interpersonal relationships, multicultural understanding , skills in identifying and solving labor issues, consistency in setting and achieving their own goals and confidence to act in the direction and with the intention of making a difference . The impact of higher education on individual development in areas such as emotional skills, interpersonal skills, ethical behavior, and intellectual abilities has been highlighted by other authors (Maxwell, 2007; McHenry, 2007; Palmer, Zajonic , Scribner , & Nepo , 2010). Individual changes, because of higher education, have also been the subject of modeling processes, with Bynner, Schuller and Feinstein (2003) proposing the conceptualization of social benefits in three dimensions - identity capital, human capital and social capital. According to this triangular pattern, human capital captures the knowledge, skills and skill level assimilated by individuals in the formal learning process (changes in cognitive, economic and career development); the share capital overlaps with the changes in attitudes mentioned above; identity capital can be assimilated to psychological changes. Starting from the aspects mentioned above, which try to outline a framework of the economic and non-economic benefits of higher education at the individual level, we can identify the specific influences exerted at the macroeconomic level as well. If the effects of higher education on macroeconomic development are known in terms of economic benefits (accelerating economic growth, lowering the unemployment rate and increasing the employment rate, greater flexibility for the labor market, increasing labor productivity, reducing public spending, etc.), non-economic benefits issues are less visible (increased social cohesion, increased tolerance of society, political stability, better social mobility, reduced crime, etc.). Hout (2012), starting from the individual economic benefits, namely high incomes for people with higher education, points to the contribution of education in macroeconomic terms, emphasizing the impact on economic growth and the well-being of society. Beneficial results on the labor market, seen at the macroeconomic level, from the perspective of flexibility and high employment rate, have been mentioned in numerous studies (Hackman, Stixrud and Urzuna, 2006; Brennan, Kogan and Teichler, 1995; Stokes, 2015). Economic and non-economic benefits of higher education resulting from the analysis of EU-27 statistics At the level of the European Union, there is an increase in the population's interest in pursuing higher education, constantly increasing, in recent years, the share of those pursuing higher education in the total population of 18-39 years, as shown in table no. 1. Table 1. Students in tertiary education by age groups - as% of corresponding age population, at EU level - 27 Age 2015 2016 2017 2018 2019 18 years 16.0 17.2 19.1 19.9 20.7 20 years 37.1 37.8 40.7 41.3 41.9 22 years 34.2 33.6 36.0 36.4 35.0 24 years 23.0 22.7 24.5 24.7 23.6 26 years 13.2 13.0 14.0 14.2 13.8 28 years 8.3 8.1 8.7 8.9 8.8 CONSIDERATIONS ON THE IMPACT OF HIGHER EDUCATION FROM AN ECONOMIC AND NON-ECONOMIC PERSPECTIVE 28 From 30 to 34 years 3.9 3.8 4.2 4.2 4.2 From 35 to 39 years 2.0 1.9 2.1 2.2 2.2 Source: Eurostat ( https://ec.europa.eu/eurostat/web/main/data/database ) The interest of the population in the direction of graduating from higher education is obviously related to the potential benefits that they can generate. Thus, the statistical information for the period 2015-2020 on the labor market in the European Union shows that graduation is associated with a much lower unemployment rate, which shows increased employment opportunities for those who complete the level tertiary education. For example, in 2020, the unemployment rate in the tertiary education population was 4.7%, compared to 6.6% of the upper secondary and post- secondary non-tertiary education population and, respectively, 13.7% at the level of the one with less than primary, primary and lower secondary education. (Table 2) Table 2. Unemployment by educational attainment in the EU-27, at the level of the population aged 15 to 74, between 2015 and 2020 (percentage of population in the LABOR force) Level of education 2015 2016 2017 2018 2019 2020 Less than primary, primary, and lower secondary education (levels 0-2) 18.7 17.4 16.0 14.5 13.5 13.7 Upper secondary and post- secondary non- tertiary education (levels 3 and 4) 9.2 8.3 7.4 6.6 6.1 6.6 Tertiary education (levels 5-8) 6.1 5.4 4.8 4.4 4.2 4.7 Source: Eurostat ( https://ec.europa.eu/eurostat/web/main/data/database ) Figure 1. Unemployment by educational attainment in the EU-27, at the level of the population aged 15 to 74, in 2020 (percentage of population in the LABOR force) Source: Eurostat ( https: // ec .europa.eu / eurostat / web / main / data / database) Practically confirming the information presented above, the indicators that show the evolution of the employment level of the EU population, show that the population with higher education has a much higher level of employment compared to the categories of 13,7 6,6 4,7 0 4 8 12 16 Less than primary, primary and lower secondary education (levels 0-2) Upper secondary and post- secondary non-tertiary education (levels 3 and 4) Tertiary education (levels 5-8) https://ec.europa.eu/eurostat/web/main/data/database https://ec.europa.eu/eurostat/web/main/data/database https://ec/ Nichifor, Țimiraș, Zaiț 29 people with a lower level of education. For example, according to the data presented in Table 3, in 2020, 83.9% of the total population aged 15-64 with tertiary education they were employed, compared to 69.9% for those with upper secondary and post- secondary non- tertiary education and, respectively, 43.3% those with less than primary, primary and lower secondary education . Table 3. Employment by educational attainment level, in the EU-27, at the level of the population aged 15-64, between 2015 and 2020 (percentage of total population) Level of education 2015 2016 2017 2018 2019 2020 Less than primary, primary and lower secondary education (levels 0-2) 41.6 42.4 43.3 44.1 44.6 43.3 Upper secondary and post- secondary non- tertiary education (levels 3 and 4) 68.1 69.1 70.1 71.0 71.4 69.9 Tertiary education (levels 5-8) 82.3 83.1 83.9 84.4 84.9 83.9 Source: Eurostat ( https://ec.europa.eu/eurostat/web/main/data/database ) Figure 2. Employment by educational attainment level, in the EU-27, at the level of the population aged 15-64, in 2020 (percentage of total population) Source: Eurostat (https://ec.europa.eu/eurostat/web/main/data/database) From the point of view of income, the population with higher education enjoys a higher standard of living. Thus, the information regarding the mean nominal monthly level earnings of employees by employment at the level of some European Union countries, correlated with the distribution of the employed population by categories of studies according to occupation, highlights the increased degree of employment of the population with higher education (compared to other categories of population), at the level of those major occupational groups where higher incomes are recorded. Thus, according to the data for 2018 for which we have data for several EU countries, the groups of occupations at which the highest incomes are recorded are: ”Managers”, ”Professionals” and ”Technicians and associated professionals” (valid for all countries for which we have data). 43.3 69.9 83.9 0 20 40 60 80 100 Less than primary, primary and lower secondary education (levels 0-2) Upper secondary and post- secondary non-tertiary education (levels 3 and 4) Tertiary education (levels 5-8) % https://ec.europa.eu/eurostat/web/main/data/database CONSIDERATIONS ON THE IMPACT OF HIGHER EDUCATION FROM AN ECONOMIC AND NON-ECONOMIC PERSPECTIVE 30 Table 4. Mean nominal monthly earnings of employees by occupation, in 2018, at the level of some EU countries (US dollars) The country T ot al M an ag er s Pr of es si on al s T ec hn ic ia ns a nd a ss oc ia te d pr of es si on al s C le ri ca l s up po rt w or ke rs Se rv ic e an d sa le s w or ke rs Sk ill ed a gr ic ul tu ra l, fo re st ry an d fi sh er y w or ke rs K ra ft a nd re la te d tr ad es w or ke rs Pl an t a nd m ac hi ne o pe ra to rs , an d as se m bl er s E le m en ta ry o cc up at io ns Austria 3348 7773 4562 4105 2974 1964 1723 3455 3127 1736 Belgium 3793 8045 5464 4299 3346 2375 nd . 3311 3347 2326 Bulgaria 698 1970 1037 826 543 402 465 554 511 378 Cyprus 2090 6709 2936 2324 1559 1377 1386 1719 1757 1299 Czech 1550 3177 2181 1700 1279 1062 1064 1323 1290 913 Estonia 1541 2290 2054 1653 1360 1035 977 1416 1346 1001 Finland 3647 7429 4874 3785 3008 2558 2556 3277 3329 2244 Germany 3780 9074 5744 4199 3489 2617 2898 3494 3207 2262 Greece 1047 1845 1303 1206 1030 860 784 931 991 754 Hungary 1151 2231 1636 1206 1069 800 744 1001 959 672 Ireland 4270 6822 5982 4437 3481 2753 2852 3493 3439 2767 Latvia 1347 1972 1780 1422 1181 888 932 1201 1155 844 Lithuania 1122 1873 1402 1061 931 750 695 917 925 647 Luxembourg 4247 8520 5617 4177 3400 2729 2716 3178 3271 2002 Netherlands 2968 6317 4279 3310 2577 1717 2306 3066 2937 1239 Poland 1295 2497 1586 1315 1050 817 805 1080 1070 793 Portugal 1049 1920 1567 1151 886 798 713 877 866 633 Slovakia 1388 2922 1718 1515 1153 1020 986 1297 1216 782 Slovenia 2100 3398 2883 2260 1825 1518 1450 1675 1624 1319 Spain 2363 5347 3395 2879 2139 1678 1938 2226 2282 1493 Sweden 3980 6741 4694 4268 3336 3141 2980 3589 3440 2796 nd . - No date Source: ILOSTAT, International Labor Organization (https://ilostat.ilo.org/) On the other hand, at EU level, according to 2020, 76.7% of the tertiary education population falls into the groups ”Managers” (8.7%), ”Professionals” (48.8%) and ”Technicians and associated professionals” (19.2%); categories that at the level of the population with a lower level of education, are represented to a small extent (26, 3% at the level of the upper secondary and post-secondary non-tertiary education population and 10.2% in the lesser than primary, primary and lower secondary education population). Nichifor, Țimiraș, Zaiț 31 Table 5. Distribution of employment, 15 years and over, by categories by educational attainment level by occupation, in the EU-27, in 2020 (% in total category after education) Occupation Total population Tertiary education (levels 5- 8) Upper secondary and post- secondary non- tertiary education (levels 3 and 4) Less than primary, primary and lower secondary education (levels 0-2) Managers 5.0 8.7 3.3 2.3 Professionals 20.4 48.8 5.7 1.5 Technicians and associate professionals 16.2 19.2 17.3 6.4 Clerical support workers 9.7 8.0 12.3 5.7 Service and sales workers 15.8 6.8 21.0 20.6 Skilled agricultural, forestry and fishery workers 3.5 1.0 3.9 7.9 Craft and related trades workers 11.5 2.7 16.0 17.5 Plant and machine operators and assemblers 7.5 1.4 10.2 13.0 Elementary occupations 8.5 1.5 8.2 24.1 Other categories 1.9 1.9 2.0 1.2 Total 100 100 100 100 Eurostat own processing (https://ec.europa.eu/eurostat/web/main/data/database) A number of non-economic benefits are also associated with a higher level of training. Thus, comparing life expectancy to tertiary population categories education with those with a lower level of education finds a life expectancy associated with higher education. Thus, considering the information for the period 2015-2017 (the last years for which we have data for a large part of the EU countries) we find that at the level of the countries considered, the highest life expectancy is recorded in the tertiary education population, followed by the upper secondary and post- secondary non- tertiary education population, and the smallest life expectancy is registered by the less than primary, primary and lower secondary education population. Table 6. Life expectancy at less than 1 year, in some EU countries, between 2015 and 2017, by total population and by educational attainment level The country Total population Tertiary education (levels 5-8) Upper secondary and post- secondary non- tertiary education (levels 3 and 4) Less than primary, primary and lower secondary education (levels 0-2) 2015 2016 2017 2015 2016 2017 2015 2016 2017 2015 2016 2017 Bulgaria 74.7 74.9 74.8 76.2 75.9 76.8 74.6 75.1 74.8 72.2 72.4 72.4 Denmark 80.8 80.9 nd . 82.9 83.0 nd . 81.1 81.2 nd . 77.8 77.7 nd . Estonia 78.0 78.0 nd . 80.9 80.9 nd . 77.3 77.4 nd . 72.5 72.6 nd . Greece 81.1 81.5 81.4 81.9 81.9 82.5 80.9 81.7 81.2 80.4 80.3 80.2 Croatia 77.5 78.2 78.0 78.1 79.2 80.1 75.6 76.7 76.1 76.9 78.2 77.5 Italy 82.7 83.4 83.1 82.6 83.6 84.6 83.5 84.6 84.3 81.4 82.0 81.5 Hungary 75.7 76.2 76.0 78.0 78.3 79.1 75.6 76.8 76.3 72.6 72.6 72.0 Poland 77.5 78.0 77.8 80.9 81.1 81.7 76.5 77.2 77.0 74.2 74.1 72.8 CONSIDERATIONS ON THE IMPACT OF HIGHER EDUCATION FROM AN ECONOMIC AND NON-ECONOMIC PERSPECTIVE 32 Portugal 81.3 81.3 81.6 82.8 83.2 84.2 80.2 81.3 81.1 80.9 80.7 81.0 Romania 74.9 75.2 75.3 74.8 74.9 76.2 73.8 75.1 74.9 73.4 72.9 72.6 Slovenia 80.9 81.2 81.2 83.2 83.7 83.5 80.9 81.1 81.1 78.6 79.0 79.0 Slovakia 76.7 77.3 77.3 80.1 80.8 80.6 77.0 77.5 77.6 69.7 69.9 69.2 Finland 81.6 81.5 81.7 83.9 83.8 83.8 81.4 81.4 81.6 78.4 78.1 78.4 Sweden 82.2 82.4 82.5 84.0 84.2 84.3 82.2 82.3 82.3 80.0 80.1 80.2 Norway 82.4 82.5 82.7 84.1 84.1 84.3 82.5 82.8 82.8 79.7 79.5 80.0 Turkey 78.2 78.1 78.5 80.0 79.8 80.3 78.7 78.5 78.9 77.8 77.7 78.0 nd . - No date Source: Eurostat ( https://ec.europa.eu/eurostat/web/main/data/database ) Figure 3. Life expectancy at less gap than 1 year by population categories by educational attainment level, compared to the national average, at the level of some EU member states (+/- years compared to the average), in 2017 Eurostat own processing (https://ec.europa.eu/eurostat/web/main/data/database) Another indicator of the quality of life and which differs by population categories depending on the level of education is the number of births of minor mothers. Thus, based on data from 2019 in some EU countries, it is found that (except for cases for which the mother's studies are not known), mothers aged 10-14 were registered exclusively among the population with less than primary, primary and lower secondary education, and mothers aged 15-19 registered to the most extent in the same category by level of education. On the other hand, in the tertiary education category of population the phenomenon of birth at the age of 19 is extremely rare (in some EU countries there are 1 child with mothers aged 15-19). 2, 0 1, 1 2 ,1 1, 5 3, 1 3 ,9 2, 6 0, 9 2, 3 3 ,3 2, 1 1, 8 1, 6 1, 8 0, 0 -0 ,2 -1 ,9 1, 2 0, 3 -0 ,8 -0 ,5 -0 ,4 -0 ,1 0, 3 -0 ,1 -0 ,2 0, 1 0, 4 -2 ,4 -1 ,2 - 0, 5 -1 ,6 -4 ,0 -5 ,0 -0 ,6 -2 ,7 -2 ,2 -8 ,1 -3 ,3 - 2, 3 -2 ,7 -0 ,5 -10 -8 -6 -4 -2 0 2 4 6 B ul ga ri a G re ec e C ro at ia It al y H un ga ry Po la nd Po rt ug al R om an ia Sl ov en ia Sl ov ak ia Fi nl an d Sw ed en N or w ay T ur ke yy ea rs Tertiary education (levels 5-8) Upper secondary and post-secondary non-tertiary education (levels 3 and 4) Less than primary, primary and lower secondary education (levels 0-2) https://ec.europa.eu/eurostat/web/main/data/database Nichifor, Țimiraș, Zaiț 33 Table 7. Number of births with the mother's age of 10-14 years and 15-19 years respectively (Live births by mother's age) in some EU countries in total and by educational category attainment level, in 2019 The country Nr. born with the mother's age of 10- 14 years Nr. born with the mother's age of 15- 19 years T ot al T er tia ry e du ca tio n (l ev el s 5- 8) U pp er s ec on da ry a nd p os t- s ec on da ry no n- te rt ia ry e du ca tio n (l ev el s 3 an d 4) L es s th an p ri m ar y , p ri m ar y an d lo w er se co nd ar y ed uc at io n (l ev el s 0- 2) U nk no w n T ot al T er tia ry e du ca tio n (l ev el s 5- 8) U pp er s ec on da ry a nd p os t- s ec on da ry no n- te rt ia ry e du ca tio n (l ev el s 3 an d 4) L es s th an p ri m ar y, p ri m ar y an d lo w er se co nd ar y ed uc at io n (l ev el s 0- 2) U nk no w n Czech 22 0 0 22 0 2261 0 324 1697 240 Denmark 1 0 0 1 0 339 0 35 295 9 Estonia 2 0 0 2 0 258 0 45 213 0 Greece 97 0 0 77 20 2209 1 260 1478 470 Croatia 3 0 0 3 0 862 1 370 406 85 Latvia 2 0 0 2 0 546 0 101 444 1 Hungary 58 0 0 54 4 4991 0 694 4151 146 Poland 35 0 0 32 3 8242 0 2218 5861 163 Portugal 29 0 0 26 3 2048 0 425 1490 133 Romania 749 0 0 733 16 17933 0 3935 13410 588 Slovenia 3 0 0 3 0 206 0 50 156 0 Slovakia 38 0 0 38 0 3452 0 442 3010 0 Finland 1 0 0 1 0 592 0 129 463 0 Sweden 4 0 0 0 4 911 1 143 530 237 Norway nd. nd. nd. nd. nd. 350 1 30 275 44 Turkey 142 0 0 137 5 53189 13 5442 46505 1229 nd. - No data Source: Eurostat ( https://ec.europa.eu/eurostat/web/main/data/database ) Conclusions An entire range of benefits are associated with tertiary education of the population. These benefits are manifested in various areas of economic and social life, having an impact both individually and collectively. Thus, higher education is associated, among other things, with a higher employment rate and implicitly with a lower unemployment, higher salary income, higher life expectancy, better health, etc., aspects that also result from the information presented in the literature as well as from official statistics, in which case information on the European Union was used. https://ec.europa.eu/eurostat/web/main/data/database CONSIDERATIONS ON THE IMPACT OF HIGHER EDUCATION FROM AN ECONOMIC AND NON-ECONOMIC PERSPECTIVE 34 References Barr, N. (2012), The Economics of the Welfare State, 5th edition, Oxford, University Press. Baum, S., Ma, J., Payea, K. (2010), Education Pays 2010. The benefits of Higher Education for Individuals and Society, The College Board Advocacy and Policy Center. 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