Linköping University | Department of Behavioural Sciences and Learning Master program Adult Learning and Global Change, 60 credits Spring 2019|ISRN-number: LIU-IBL/IMPALGC-A—19/002-SE
Tertiary education and
employment:
– Exploring the relationship between tertiary
education, employment and overqualification
across the EU
Maria Papadopoulou
Supervisor: Dr. Erik Nylander Examiner: Dr. Ronny Högberg
Linköpings universitet SE-581 83 Linköping 013-28 10 00, www.liu.se
Abstract
The dominant human capital theory-based perspective that education is crucial
for economic success and employment has affected national and regional policies in
education and employment worldwide. The present thesis critically assesses the target
for increased number of tertiary education graduates in the current EU agenda for
growth and employment (Europe 2020 Strategy). This target presumes that
employment is positively related with tertiary education qualifications, and that there
is an increasing demand for highly educated workers in the EU labour markets.
Based on Eurostat data, our findings indicate that (i) more public spending on
tertiary education does not seem to be associated with higher employment rates of
graduates in the EU countries; (ii) in more than half of the EU28 member states,
unemployment rates are not related with increased number of graduates; (iii) in most
of the remaining EU countries, the increase in graduates is associated with higher
graduates’ unemployment rates; (iv) increased number of tertiary education graduates
relates with higher overqualification rates in the majority of the EU countries.
These results accord with previous studies which find that investment in
education alone is inadequate to explain complex socio-economic phenomena, such as
graduates’ employment/unemployment. Moreover, they further support previous
research works, which question the proclaimed increased need for highly educated
workers in the EU labour markets. This, in turn, suggests that common European
policies which target at increasing horizontally the number of graduates may further
deteriorate the existing problem of overqualification in the EU.
Without downplaying the importance of education and skills in employment,
tertiary education in employment may falsely cultivate the perception that education
per se can be the main solution for unemployment. Thus, it is likely to conceal the
wider socio-economic reasons that influence a person’s ability to find, secure and
advance in his/her job. Last, but not least, this perspective narrows down the role of
tertiary education confining it to economic and employment purposes.
Keywords: human capital theory, Europe 2020 Strategy, tertiary education,
Acknowledgements
First of all, I would like to express my appreciation to my supervisor, Dr. Erik
Nylander, Senior Lecturer at the University of Linköping, for his valuable guidance
and support throughout the preparation of this thesis.
I would, also, like to thank the University of Linköping for having given me
the opportunity to participate in such an interesting master programme. I would like to
extend my sincere thanks to my tutors from the four participating Universities
(Linköping University, Sweden; University of British Columbia, Canada; University
of Western Cape, South Africa; and Australian Catholic University, Australia), as
well as to my fellow students for the inspiring, international learning environment.
Saving the most important for last, I owe special thanks to my husband Nikos,
and our daughters, Chrysa and Sofia. I would like to let them know that it would have
been impossible for me to complete the master programme and the present thesis
without their love, support, and encouragement. I deeply appreciate that they have
Contents
1. Introduction……… 1
2. Human Capital Theory……… 4
2.1 Foundations and basic principles………. 5
3. Literature Review……….. 7
3.1 The relationship between education and private labour market benefits……….. 8
3.2 The demand for educated workers in contemporary economies and the overqualification phenomenon……….. 15
4. Aim-Research Questions-Methodology……… 22
4.1 Aim and research questions……….. 23
4.2 Method and Methodology………. 23
4.3 Data……….. 25
5. Findings and Discussion……….. 29
5.1 Public expenditure on tertiary education and employment of graduates………. 29
5.2 Percentage of working age population with tertiary education and graduates’ unemployment and overqualification rates in the labour market……… 33
5.3 Discussion of findings and implications……….. 40
6. Concluding remarks……….. 43
1
1. Introduction
In the context of global economic competition, big emphasis has been placed
on the crucial role of education and skills in shaping a human capital that can foster
economic growth and competitiveness, as well as peoples’ income and employment
status. This perception, influenced by the principles of human capital theory, has put
education at the forefront of policy agendas of supranational organisations, such as
the Organisation for Economic Co-operation and Development (OECD) and the
European Union (EU) (Gillies, 2011). Both organisations stress the role of education
and educational systems in addressing the needs of economy, and in preparing
students for employment in a fluid working environment with a changing demand of
skills (CEDEFOP, 2012; OECD, 2011, 2015).
In the context of its economic strategy, the EU highlights the importance of
investing on education and skills of its human capital in order to: (i) achieve its vision
of becoming a knowledge based economy; (ii) ensure economic growth and global
competitiveness based on a high skill-high wage equilibrium; (iii) foster employment
and social inclusion; and (iv) recover from economic crisis (Andor, 2014). This
strategy calls for a close relationship between education and economy, whereby
educational systems play a decisive role in preparing highly-skilled and flexible
employees in order to better address labour market needs, and resolve employers’
persistent difficulties in finding candidates with the proper skills (Andor, 2014).
The EU policies have further promoted the link between tertiary education and
labour marker, by focusing on the employability of graduates (Prokou, 2008). In this
context, tertiary education is widely perceived as preparation for employment, which,
in turn, has changed the role of tertiary education institutions in Europe, and reduced their autonomy (Prokou, 2008; Sułkowski & Zawadzki, 2016).
2
Commenting about the crucial role of education in employment, OECD (1998,
p. 54) points out that “those with higher levels of education are more likely to
participate in the labour market, face lower risks of unemployment, and receive on
average higher earnings".
The decisive role of education in employment has been reaffirmed in the
current EU agenda for growth and jobs. One of the eight EU strategic targets for
fostering economic growth, employment and social inclusion in the EU is to raise the
number of tertiary education graduates to at least 40% in the age group of 30-34 by
2020 (Europe 2020 Strategy, 2019); a target which has already been met, or even
exceeded, in 18 EU member states (Eurostat newsrelease, 2019)1.The inclusion of this target in the EU agenda for employment presumes that employment is positively
related with tertiary education qualifications, and that there is an increasing demand
for highly educated workers in the EU labour markets.
Apart from the moral issues related to the economically-oriented perception of
education, the importance set on investing in tertiary education for boosting
employment in 28 member states with diverse economies, labour markets, and
educational systems, poses some additional concerns. First, it is questionable whether
investment in tertiary education, which mainly comes from the EU countries’ public
sector2, relates with increased graduates’ employment in the different EU member states. Second, some EU labour markets may not need additional number of
graduates, since they already experience phenomena of high graduates’
1
According to data published by Eurostat in late April 2019, the percentage of people aged 30-34 with tertiary education in the EU28 increased from 23.6% in 2002 to 40.7% in 2018 (Eurostat newsrelease, 2019).
2Financial investment/spending in tertiary education mainly comes from the public sector in the EU
3
unemployment and/or graduates’ underemployment3, in the form of unwilling part time employment and/or inadequate employment conditions, such as graduates being
employed in a job that requires less qualifications. As such, an increased number of
graduates might further worsen unemployment rates and/or the type of employment
graduates get, namely increasing the number of graduates who are employed in jobs
that require lower qualifications (overqualification phenomenon).
Based on these considerations, the aim of the present thesis is to assess the EU
target for increasing the number of tertiary education graduates. Specifically, it
empirically explores the homogeneity or heterogeneity in the interconnections
between investment in tertiary education, graduates’ employment and
overqualification rates in an EU cross-country context4 using data from the Eurostat database.
Therefore, we first empirically examine whether (and how) public investment
in tertiary education is associated with graduates’ employment rates in different EU
member states. We, then, examine whether increased numbers of graduates relate with
higher graduates’ unemployment and overqualification rates across the EU member
states. The results are expected to provide useful insights about country-specific
variations or possible general trends at the EU level regarding the interplay between
public investment on tertiary education and employment, as well as between the
number of graduates, graduates’ unemployment and overqualification rates.
3According to the International Labour Organization (ILO), underemployment can be distinguished as
time-related underemployment (such as part-time employment) or underemployment due to inadequate employment situations (such as underutilization of workers’ education and skills or low income jobs). They both “reflect an under-utilization of the worker's capacities (thus well-being)… [and] are defined in relation to an alternative work situation in which the person is willing and available to engage” (ILO, 2012, p. 10).
4The analysis includes 28 EU member states, since at the time of writing, despite Brexit, the United
4
The structure of our thesis is as follows: First, we present the human capital
theory to better comprehend its influence on the EU target, as well as on the
widespread/common perception about the role of education in employment. We, then,
discuss the wider academic debate about two interrelated issues: the role of education
in a person’s successful participation in the labour market, and the demand for highly
educated workers in the knowledge-based economies. Next, we present the aim,
research questions and empirical method employed in our thesis. Finally, we discuss
and relate our findings to the literature, address their possible implications, and
provide some concluding remarks.
2. Human Capital Theory
As mentioned earlier, the target for an increased number of tertiary education
graduates in the current EU agenda for growth and employmentis part of the wider
EU strategy, which reflects the impact of human capital theory principles on the EU
discourse and policy (Gillies, 2011).
Human capital theory is one of the most influential theories both in academia,
and in policy discourse and practice worldwide. In academia, it has been the basis for
a vast number of theoretical and empirical studies in the fields of economics of
education and labour economics, but also in other social sciences. It has been
primarily applied in the analysis of the relationship between education/learning and
private and social economic outcomes, as well as in other aspects of human
behaviour, such as family, fertility, discrimination, inequality etc. (Eide & Showalter,
2010). The ideas of human capital theory have been, also, highly influential in
policy-discourse and practice in economic and educational issues worldwide, emphasizing
5
legitimizing high public and private spending on it. Since it has significant
repercussions for the economy, it is not surprising that it has been very influential in
the discourse and policies of supranational organisations, such as the OECD and the
EU. Last, but not least, its ideas have been so pervasive that can be also traced in
widespread beliefs about the crucial role of education in a person’s employment,
earnings and socio-economic inclusion.
In order to better comprehend its influence on the logic behind the EU target
for increased graduates in the EU agenda for growth and employment, we go on by
presenting its foundations and basic principles.
2.1 Foundations and basic principles
The importance of human capital, that is the workers’ embedded productive
capabilities, had been acknowledged long before the late 1950s and early 1960s, when
academics from the University of Chicago started formulating it as a theory. Since
then, a number of scholars have contributed in the theoretical and empirical evolution
of the theory. The most prominent of them are: Jacob Mincer, who focused on the
returns to education in the form of wages; Theodore Shultz, who focused on the role
of education in the increased labour productivity; and Gary Becker who organized all
the relevant work into a coherent framework (Eide & Showalter, 2010). The theory
has evolved into one of the most influential economic theories, and two of its
prominent theorists receivedNobel awards in economics (Ted Schultz in1979 and
Gary Becker in 1992).
Human capital is multifaceted and includes a person’s “knowledge, skills,
6
16). The initial emphasis of human capital theorists on the quantity of education has
been later enriched with an additional concern about its quality, as measured by the
level of specific skills (Hanushek and Wößmann, 2010; Pritchett, 2001).However, the
quantitative aspect of education, measured by years of schooling or level of
qualifications, still remains focal in both policy and academic literature (i.e. Europe
2020 Strategy, 2019; Psacharopoulos and Patrinos, 2004).
According to Becker (1994), one of the most prominent human capital
theorists, a very distinctive element of the human capital theory is that it applies a
cost-benefit approach in its analysis, similar to the cost-benefit approach applied in
investments in traditional (physical or financial) capital. Moreover, it postulates that
investments in education and training are usually the result of rational decisions based
on calculations between costs and benefits (Becker, 1994). Investments in human
capital mainly refer to costs/expenditure on education and training, which result to a
wide range of private and social economic benefits, such as increased productivity,
economic growth, higher employment prospects and earnings (Becker, 1994). These
benefits are perceived to be in a linear positive relationship with investments in
education and skills, whereas deviations are justified on the basis of economic
fluctuations or difficulties in measuring/quantifying indirect effects of investments in
human capital (Becker, 1994).
According to Mincer (1991), which is also one of the leading human capital
theorists, educated workers are considered to have a number of positive private
benefits in the labour market that include higher wages, bigger employment stability
and higher upward mobility in employment and socio-economic status. As far as the
private benefits, human capital literature has extensively highlighted the positive
7
The basis for this estimation has been the human capital earnings function, introduced
by Mincer in 1974, according to which earnings through employment are associated
with the years of schooling and labour-market experience (Gunderson and
Oreopoulos, 2010).
Overall, human capital theory places education at the heart of its analytical
framework. According to it, expenditure on education and training results in a wide
range of social and private economic benefits, including higher economic growth for a
country or region, and a wide range of labour market benefits for educated people. In
the following section, we focus on the private labour market benefits, and review the
human capital perspective as well as its critiques about the role of education in
determining peoples’ employment and earnings.
3. Literature Review
As discussed earlier, the EU target for increased tertiary education graduates
by 2020 reaffirms the importance of the role of tertiary education for employment in
the contemporary EU Strategy. The inclusion of a target like this in the EU agenda for
employment presumes that employment is positively related with tertiary education
qualifications, and that there is an increasing demand for highly educated workers in
the EU labour markets. Since both of these presumptions are influenced by the human
capital perspective about the crucial role of education in contemporary
knowledge-based economies, we will now continue by reviewing the academic debate between
the human capital perspective advocates and their critics about these two interrelated
issues. We will first present the debate about role of education in labour market
8
then turn to the academic debate about the demand for highly educated and skilled
workers in contemporary knowledge-based economies.
3.1 The relationship between education and private labour market benefits
The impact of education on employment has been a matter of considerable
debate. Human capital theory, on the one hand, highlights the crucial positive role of
education and skills on a person’s successful participation in the labour market. On
the other hand, a number of scholars question this approach, and consider the
emphasis on education as inadequate for the explanation of such complex
socio-economic issues. In the following pages, we present this academic debate within a
wider debate about the role of education in a range of labour market benefits, i.e.
earned income, employment and socio-economic inclusion.
As we discussed earlier, human capital theory postulates that investments in
education and training are usually the result of rational decisions based on
calculations between costs and benefits (Becker, 1994). Based on this perception, one
may argue that this principle applies at all levels of decision making, including
individuals, firms and countries. As such, individuals make a decision about investing
on their education and training by calculating the costs against expected benefits, such
as better employment prospects, higher wages, and socio-economic inclusion. A firm
makes a decision about investing on the education and training of its workforce by
calculating the costs against expected benefits, such as higher productivity and
economic competitiveness. A country makes a decision about public spending on
education and training by calculating the costs against expected benefits, such as the
socio-9
economic inclusion for its population. In the following paragraphs, we focus on the
labour market benefits that derive from investments in education, as presented by
human capital theoretical and empirical studies.
Regarding the role of education for employment, one of the most prominent
human capital theorists, Mincer (1991, p. 2) points out that “educated workers enjoy
at least three basic advantages over less educated workers in the labour market: higher
wages, greater upward mobility in income and occupation, and greater employment
stability”. As such, the application of the cost-benefit analytical framework of human
capital theory means that investment in education and skills results in positive private
labour market benefits for educated people, namely enhanced possibilities to be
employed; employment stability; upward occupational mobility; higher earned
income from employment; and upward socio-economic mobility.
Brewer, Hentschke & Eide (2010, p. 193) stress that human capital theory
cost-benefit approach is indeed affirmed in practice, since “better-educated workers
have more favorable labor-market outcomes [and are] critical for a nation to compete
in an increasingly global economy that rewards knowledge and skills”.
Since the monetary aspects and benefits of education are easy to be quantified
and measured, they have been the prime focus of human capital theory (Becker,
1994). As such, most human capital theory-based studies about labour market benefits
have focused on the examination of the relationship between education and earnings
from employment. Their empirical findings indicate that, regardless of inter-county
variations, investments in education, either by measuring years of schooling or levels
of skills, definitely have a positive impact on wages. As far as the highly positive
impact of additional years of schooling on wages, Psacharopoulos and Patrinos (2004)
10
additional year of schooling. According to them, the latest analyses reiterate that in
advanced economies investments in education behave similarly to investments in
physical capital (cost-benefit approach), since the returns to both “tend to be equated
at the margin” (Psacharopoulos and Patrinos, 2004, p. 118).
This positive relationship is, also, supported by Gunderson and Oreopoulos
(2010), who found that, despite the rapid expansion of education, educational
attainment still exerts a positive impact on the wages of educated workers. According
to their study, wage differences between highly-educated and low-educated workers
are high in Canada and Europe, while they skyrocket in the USA (Gunderson and
Oreopoulos, 2010).
Hanushek, Schwerdt, Wiederhold, & Woessmann (2015) in a cross-country
analysis provided further evidence about the positive relationship between cognitive
skills and wages. They performed a survey with data from the 2011-2012 OECD
Programme for the International Assessment of Adult Competencies (PIAAC), and
concluded that, although there are considerable variations across countries (from 28%
in the USA to less than 15% in Nordic countries), “higher cognitive skills – measured
across numeracy, literacy, and problem-solving domains - are systematically related
to higher wages in all 23 participating countries” (Hanushek, et al., 2015, p. 123).
These works apply a human capital theory analytical framework, and indicate
that investment in education and skills increase the earnings of educated employees
and thus foster their general labour market benefits, such as successful participation in
the labour market, and upward socio-economic mobility. As discussed above, the
human capital theory posits that investment in education is a rational decision based
on the calculation between costs and benefits. Regarding the labour market benefits,
11
decisive role in the determination of a person’s successful participation in the labour
market: it enhances the possibilities of educated people to be employed; increases
their earnings from employment; reinforces their job stability; and promotes their
upward career and socio-economic mobility. Thus, the successful participation in the
labour market is primarily explained on the basis of a person’s education and skills,
which is a result of his/her decision to invest in education based on a calculation
between costs and expected benefits, in order to maximize his/her labour market
benefits.
A number of scholars, though, question the overemphasis on the role of
education and skills in the explanation of employment and income-related issues.
They argue that the human capital perspective, due to its overemphasis on education
and personal decision about investment in education, fails to address the wider social,
economic and political factors that influence a person’s successful participation in the
labour market. In the following paragraphs we present theoretical and empirical
studies that question the human capital perspective, and argue for the inclusion of
wider factors in the explanation of phenomena concerning employment and income
distribution.
Commenting on the adequacy of human capital perspective in explaining
socio-economic phenomena, Marginson (2019), argues that the favourable economic
and social conditions in the early years of the theory’s formulation provided
supporting empirical evidence, whereas the current socio-economic context of
growing income inequalities, unemployment, and underemployment question its
analytical validity. The growing income inequality (wage polarization) within the
12
questions the human capital theory, since higher wages are confined in a small
minority of workers.
Based on his findings about the earned income inequality over time, Piketty
(2014) also questions the learning for earning hypothesis of human capital theory. He
points out that although there has been a big increase in educational attainment
worldwide during the 20th century, this has not increased equality of income from employment, as human capital theorists suggest. According to him, the technological
evolution, along with its emphasis on human capital, has created the illusion that
human capital and talent play greater role in the economy than other forms of capital,
such as the industrial, financial or real-estate capital. This, in turn, has created the
illusion that human capital has fostered greater income equality based on one’s merit.
Empirical evidence, though, indicates that income inequality has increased in the
developed world, since “the top thousandth enjoyed spectacular increases in
purchasing power in 1990–2010, while the average person’s purchasing power
stagnated” (Piketty, 2014, p. 320). He demonstrates that income inequality has
skyrocketed in the USA, as well as in other Anglo-Saxon countries, such as the UK,
Canada and Australia. He warns that in continental Europe and Japan income
inequality has, also, increased significantly and, although lower than in the
Anglo-Saxon counties, the trend seems to be towards the same direction.
These studies indicate that although there has been a big increase in
educational attainment worldwide, this has not resulted in higher equality of income
from employment, as human capital theorists suggest. They rather indicate that
education per se may be inadequate to explain income distribution and inequalities in
13
criticized by a number of scholars, who argue for the inclusion of wider factors in the
explanation of employment, earned income and socio-economic status.
Commenting on this issue, Tan (2014) argues that human capital theory has
overemphasized the role of individual and the individual choice in making a rational
decision about his/her educational investment in order to maximize his/her personal
benefits. Similarly, Bourdieu (1986) points out that human capital theory puts an
excessive focus on personal ability or talent, whereas it disregards issues concerning
social class, and the role of education in social reproduction. Thus, according to
Gillies (2011, p. 235) “the overarching economic, social, and political system is
essentially absent from any analysis… [which] is indicative of a general approach that
sees market capitalism as an uncomplicated norm, a natural arrangement of affairs
above and beyond human concern”. Set within the same context, Marginson (2019)
claims that under human capital theory two heterogeneous fields, i.e. education and
work are treated as one field, whereas the social factors are not considered on their
own merits, but they are rather examined on the basis of how they may influence
individual behaviors and choices.
Based on his findings about increasing income inequality, Piketty emphasizes
that income distribution is a quite complex phenomenon, which is shaped by the
interplay between economic, political and social factors (Piketty, 2014). Fix (2008),
also, argues that there is a need for alternative explanations regarding the social
causes of differences in income distribution. The need for a thorough examination of
the influence of the wider social factors on employment and income is, also,
addressed by Marginson (2019). With respect to education-employment relationship,
Livingstone (2012, p. 109) suggests that it should be rather analyzed within a
14
haves and have-nots”. Gillies (2011), argues that investment in education per se is not
adequate for fostering employment, as it is evident in the countries, which although
invest in education and training, they are forced to export their human capital due to
the lack of jobs. Thus, he draws our attention to the importance of the wider economic
conditions in fostering employment.
As far as the influence of human capital perspective onthe discourse about the
successful participation in the labour market, McQuaid & Lindsay (2005) express
their concern that since the mid-90’s there has been an increased tendency to narrowly
focus on the role of individuals’ personal traits, such as education, skills or personal
attributes in a person’s ability to find, secure and advance at work (employability).
They argue that supranational organisations, such as OECD and the EU with their
emphasis on education and skills for employment have overstressed the supply side of
employability, while obscured the influence of wider contextual factors (McQuaid &
Lindsay, 2005). According to them, neither the emphasis on supply nor on demand
side of employability can provide a clear picture of what makes an individual able to
enter the labour market, and advance at his/her job. In contrast, they suggest that there
is a need for a more holistic and realistic approach to employability. This should rely
on the understanding of the “dynamic interaction of individual attributes, personal
circumstances, labour market conditions and other ‘context’ factors”, which include
macroeconomic factors, vacancy characteristics, recruitment and employment policy
factors (McQuaid & Lindsay, 2005, p. 207).
Likewise, Berntson, Sverke, & Marklund (2006), argue that besides the
influence of a person’s education, skills, experience and personal attributes on
employability, the influence of other contextual factors, such as the labour market
15
employability can be better understood when “both structural and individual
dimensions” are taken into consideration (Berntson et al., 2006, p. 223).
So far, we have presented the debate about the role of education in a person’s
employment and earned income. On the one hand, the human capital perspective
advocates argue that empirical evidence supports that investment in education and
skills has a positive relationship with increased earnings of educated employees, as
well as with wider concomitant labour market benefits, such as employment and
upward socio-economic mobility. On the other hand, a number of scholars, present
contrasting empirical findings, question the human capital perspective and argue for
the examination of wider social, economic and political factors that determine
employment and income distribution. After having reviewed the literature about the
role of education in employment and earned income, we now turn to the debate about
the demand for highly educated and skilled workers in contemporary
knowledge-based economies, since both issues relate with the logic of current EU target for
increased tertiary education graduates.
3.2 The demand for educated workers in contemporary economies and the
overqualification phenomenon
As discussed earlier, the EU target for increased tertiary education graduates
in the EU by 2020 draws our attention to two interrelated presuppositions. The first
one is that employment is positively related with investment in advanced education,
and the second one is that there is an increasing demand for highly educated workers
in the EU labour markets. After having reviewed the controversial literature about the
16
concerns the demand for educated workers in the contemporary knowledge-based
economies. In the following pages we first review the human capital perspective,
which claims that there is an increasing demand for educated workers in the
contemporary knowledge-based economies, and we then go on by presenting
contradictory approaches that question this perception, and emphasize the surplus of
qualifications (overqualification) in the current labour markets.
It is widely advocated that knowledge-based economies face, on the one hand,
an increasing demand for highly educated and skilled workers (Andor, 2014;
CEDEFOP, 2012; OECD, 2011, 2015), and, on the other hand, a decreasing demand
for low-educated and low-skilled workers (Wang, 2012).As such, education and skills
are considered to play a decisive role in employment, an assertion that, as we have
seen, complies with the principles of human capital theory. The increased demand for
highly educated workers and the widening of wage differences between highly
educated and low educated workersin contemporary knowledge-based economies are
strongly supported by a survey published by Gunderson and Oreopoulos in 2010.
Based on their empirical evidence, they conclude that, despite the big supply of
educated workers due to the rapid expansion of education, the demand for educated
workers in knowledge economies is so high, that it exceeds the supply (Gunderson
and Oreopoulos, 2010). The case of a surplus of educated people in the labour market
is, for human capital theorists, a temporary phenomenon attributed to the fluctuations
in economy, which, after some time will be resolved, and monetary benefits from
education will finally be higher than costs (Becker, 1994). As discussed above, the
human capital perspective argues that contemporary economies increasingly need a
highly educated and skilled workforce, and thus education plays a crucial role in
17
However, a number of scholars question the human capital theory-based
assumption that there has been an increasing need for advanced educated and skilled
workforce in the contemporary labour markets; consider it as exaggeration; and
provide contrasting evidence on this issue. In the following section, we present this
literature with an emphasis on the overeducation5/overqualification phenomenon in the contemporary labour markets.
With respect to the demand of advanced educated workers in modern
economies, Livingstone (2012) claims that a number of empirical studies, mostly
from the USA and Canada, indicate the absence of a major shift in the labour market.
In contrast, the findings show that despite the dramatic shift in the demand for
upgraded skills between 1940 and 1960, the trend has been stabilized since the 1960s
(Livingstone, 2012). Moreover, he points out that predominant fragmented production
process in the labour market, also, questions the claim for an increasing demand for
highly educated workers in the contemporary labour markets (Livingstone, 2012).
The idea that there has been a paradigm shift in capitalist labour markets
towards higher skills is, also, rejected by Lloyd and Payne (2002) and Wilby (2011),
who consider the proclaimed high need for educated workers as overestimation and
exaggeration. In fact, empirical data indicate that companies in the knowledge
economy era do not need more than 15% of highly skilled staff out of their total
workforce (Wilby, 2011), while in the 2000s “the share of jobs held by middle- and
high-skill workers declined…[whereas] low-skill, low-productivity and low-wage
service occupations have gained ground” (Economist, 2014).
The high demand for educated workers is, also, questioned by Manning
(2004), who suggests that the demand for the least-educated and skilled workers will
5Brown (2003, p. 163) warns that the term overeducation should be used very carefully, since it
conceals a “utilitarian view of education”, that is preparation for the labour market, whereas it dismisses “the value of education and learning as an end in itself”.
18
continue to grow, unless a major future technological change occurs. He claims that
the orthodoxy between economists that technology has uplifted the level of skills
needed in the labour market has created the impression that there is no demand for
low-skilled workers in the current and future labour markets. Although he
acknowledges that “the average job is more skilled now than it used to be”, he claims
that this orthodoxy has oversimplified the effects of technology in the skills demand
in the labour market (Manning, 2004, p. 30). Based on a research on occupational
changes in the UK and the USA over time, he provides a rather encouraging picture of
the future employment perspectives of the low-skilled workers.
The studies presented thus far question the proclaimed high need for educated
workforce, and provide evidence that there has not been a paradigmatic shift towards
higher education and skills in the contemporary labour markets. Furthermore, some
studies argue that the observed overeducation/overqualification6of a number of highly educated and skilled people, who, although in employment, occupy jobs that require
less education, further questions the increasing demand for educated workers.
Moreover, since their wages are not equivalent to their level of education and
qualifications, this phenomenon can also question the proclaimed positive relationship
between investment in education and labour market benefits. In the following
paragraphs, we present the scholarship that sheds light to the phenomenon of
overeducation/overqualification.
Analysing the phenomenon of overeducation/overqualification, McGuinness
(2006, p. 414-415) points out that it is mainly associated with insufficient demand for
6Both overeducation and overqualification refer to extra education [either in years of schooling
(overeducation) or in qualification level (overqualification)] than that required by the workers’ current job (CEDEFOP, 2010, p. 13). In this section we use the term “overeducation/overqualification” to encompass both situations of extra education, as presented in the relevant literature. In our empirical part, we focus at the level of qualifications (overqualification), since it relates to the EU target for increased number of graduates.
19
educated people, and the “inflexible labour market, whereby employers are either
unable or unwilling to alter their production processes to fully utilize the skills of their
overeducated workers”. He claims that the phenomenon of
overeducation/overqualification, as evidenced in “worker under-utilization and wage
rates below the marginal product” in a number of labour markets, poses some
questions about the validity of human capital theory (McGuinness, 2006, p. 390). In
contrast to the human capital theory assertion that overeducation/overqualification is a
temporary phenomenon, he indicates that evidence from a considerable number of
surveys suggest that overeducation/overqualification may be a long-term problem.
Moreover, he claims that overeducation/overqualification is not result of a “statistical
artefact generated by either inadequate measurement techniques or a lack of sufficient
controls within the standard wage equation framework”, as it may proposed by human
capital theorists (McGuinness, 2006, p. 388). He warns that the effects of
overeducation/overqualification constitute “an economic reality” (McGuinness, 2006,
p. 387), which may be detrimental and “costly” for individuals, companies and
economy, and therefore should be a matter of serious concern (McGuinness, 2006, p.
387). Following these considerations, he maintains that policies which aim at
increasing the number of university graduates may further deteriorate the problem.
Commenting on whether overeducation/overqualification is a temporary
phenomenon, Tan (2014, p. 430), also, argues that a series of empirical studies have
shown that “overeducation appears to be a substantive and durable phenomenon”, in
contrast to the human capital theory-based assertion that
overeducation/overqualification is a temporary phenomenon, and that education will
eventually provide good employment.
20
phenomenon of overeducation/overqualification in a number of contemporary labour
markets further questions the proclaimed increasing demand for educated workers, as
well as the proclaimed positive relationship between investment in education and
labour market benefits.
The presentation of the diverse theoretical and empirical studies in the
literature review chapter indicates that the education-employment relationship has
been a matter of high controversy. On the one hand, the adherents of human capital
theory claim that modern economies require advanced educated and skilled workers,
and provide empirical evidence on the positive role of education and skills in
employment, earned income, and socio-economic inclusion (see inter alia Becker,
1994; Gunderson and Oreopoulos, 2010; Hanushek, et al., 2015; Mincer, 1991;
Psacharopoulos and Patrinos, 2004). These empirical works are based on a calculation
between costs and benefits using either the quantitative dimension of education (years
of schooling, level of qualifications) or its qualitative dimension in terms of skills.
The main idea is that investment/expenditure on education and skills (cost) results in
positive outcomes (benefits) in terms of jobs, wages and upward socio-economic
mobility. No matter the wide variations in emphasis, the human capital theory asserts
that it is the personal traits in terms of education, skills, experience, etc. that primarily
determine a person’s ability to find and secure a job, earn money through employment
and move up the socio-economic ladder. Investments in education are considered to
be the result of a rational decision based on the calculation between educational costs
and labour market benefits. Cases of highly-educated people being unemployed or in
positions that do not require this high level of education are dealt as temporary
21
(Becker, 1994). In summary, according to the human capital theory, modern
economies require a high number of educated workers; investment in education and
skills are in linear positive relationship with labour market benefits; and phenomena
of overqualification are temporary, since educational investments always pay-off at
last in terms of good employment, high earnings and upward socio-economic
mobility.
Since, according to human capital theory, investments in education and skills,
play a decisive role both in labour market benefits, but also in a country’s economic
growth and competitiveness, education has been placed at the forefront of the
international, regional and national agendas. This perception has legitimized
countries’ high public expenditure on education for achieving economic growth, as
well as for fostering employment and socio-economic inclusion for their populations.
Moreover, its ideas about the connection between education and labour market
benefits can be traced in widespread beliefs about the crucial role of education in
employment, earnings and socio-economic inclusion.
Human capital theory critics, on the other hand, question the human capital
theory assumptions about the linear positive relationship between education and a
person’s labour market benefits, as well as the proclaimed increasing demand for
educated workers in the contemporary labour markets (see inter alia Brown and
Tannock, 2009; Gillies, 2011; Livingstone, 2012; Manning 2004; McGuinness, 2006;
Piketty, 2014). They point out that political, social, economic and labour market
factors are absent in the analytical framework of the human capital perspective, which
puts a disproportionate emphasis on education for the explanation of complex
socio-economic phenomena, such as employment, earned income, and socio-socio-economic
22
worldwide, and the long-lasting phenomena of highly-educated people being
unemployed or overqualified for their jobs in the contemporary labour markets reflect
the limitations of human capital theory in the explanation of employment-related
phenomena.
So far we have presented the diverse scholarship about two interrelated issues:
the education-employment relationship and the demand for advanced educated
workers in contemporary labour markets. We now go back to the EU target for
increased tertiary education graduates in the EU by 2020, and critically assess it
within the empirical part of our thesis. Our aim, research questions and methodology
are presented in the following section.
4. Aim-Research Questions-Methodology
Having reviewed the conflicting approaches in the literature about the
relationship between investment in education and employment benefits, as well as
about the demand for highly educated workers in the contemporary labour markets,
we return to the current EU target for increased number of tertiary education
graduates in the EU agenda for growth and employment. As discussed earlier, this
target presumes that employment is positively related with tertiary education
qualifications, and that there is an increasing demand for highly educated workers in
23
4.1 Aim and research questions
The aim of the present thesis is to assess this specific EU target by empirically
exploring the interconnections between investment in tertiary education, graduates’
employment and overqualification rates in an EU cross-country context7 using data from the Eurostat database.
The concomitant research questions posed in this thesis concern three closely
related issues across the EU member states: a) whether and how public expenditure on
tertiary education relates with graduates’ employment, b) whether increased numbers
of tertiary education graduates relate to higher graduates’ unemployment rates, and c)
whether increasing the number of tertiary education graduates relates to higher
overqualification rates. This quantitative evidence will provide useful insights about
country-specific variations or possible general EU trends in the associations between
public investment on tertiary education and employment, as well as between the
number of graduates and unemployment and overqualification rates across the EU. As
such, we will be able to draw conclusions on the viability of adopting a pan-European
educational target for increasing employment.
4.2 Method and Methodology
Since our aim is to examine our research questions in an EU cross-country
context, a quantitative research design has been selected. Furthermore, within the
context of the dominant “qualitative research paradigm” (Fejes & Nylander, 2019, p.
128), and the “limited availability of research drawing on secondary data analyses”
(Boeren, 2019, p. 151) in the field of adult education and learning, our quantitative
7The analysis includes 28 EU member states, since at the time of writing, despite Brexit, the United
24
analysis using data from the Eurostat, may provide an “evidence-base” for policy
debate (Boeren, 2019, p. 152), as far as the relevant issues in the EU sphere are
concerned. We should clarify that this study intends to investigate relationships
between variables (correlations), meaning “searching for evidence that the variation in
one variable coincides with variation in another variable” (Bryman, 2012, p. 339). We
opt for correlations, rather than using regression analysis, as the latter requires the determination of the direction of causality between variables (independent → dependent). The identification of causal effects in the explanation of social
phenomena, nevertheless, is very difficult, highly controversial (Aldridge & Levine,
2001), and beyond the scope of the present thesis8.
Therefore, the statistical analysis of our data is based on correlation
coefficients (Bryman, 2012). A correlation coefficient statistically measures the
degree of relationship between two variables and assumes values in the range from −1 to +1. A correlation coefficient equal to +1 indicates the strongest possible positive
relationship between the variables under investigation (the two variables consistently
vary together, e.g. as one variable increases, the other variable increases by the same
amount). In contrast, a correlation coefficient equal to -1 indicates the strongest
possible negative relationship between the two variables. Finally, a correlation
coefficient equal to 0 indicates the absence of any relationship between the two
variables. We report the correlation coefficients, along with their associated p-values,
to indicate the statistical significance of the correlation coefficients. P-values refer to
the confidence researchers can have in their results (Bryman, 2012). For instance, a
p-value = 0.10, indicates that the correlation coefficient is statistically significant at the
8For an extended critique about the human capital methodological flaws concerning regressions of
interdependent variables in the explanation of complex social phenomena related to education, work and earnings, see Marginson (2019).
25
10% level. This means that the researcher accepts a level of risk/probability that only
10 in 100 of his/her findings might have emerged by chance. As tools of analysis,
correlation coefficients are simple and easily understood. Yet, correlation coefficients
present certain problems, including the possibility of incorrectly being used to infer
a causal relationship between the variables (Bryman, 2012), which is, as mentioned
earlier, beyond the scope of our thesis. The empirical analysis employed in our thesis
does not claim to be a complex statistical exercise; yet it is suitable for exploring the
theoretical propositions of human capital theory which predicts linear relationships
between (investment in) education and positive labour market outcomes. As such, our
research design is expected to provide useful insights for the issue at hand.
4.3 Data
As mentioned before, our research questions will be explored in a cross
country setting using secondary data from Eurostat Statistics, which provide
high-quality and harmonized data for the EU area. Eurostat is the statistical office of the
European Union, whose “main role is to process and publish comparable statistical
information at European level… [through] a common statistical ‘language' that
embraces concepts, methods, structures and technical standards (Eurostat, 2019a). It
uses a “harmonized methodology” to “consolidate” the data from EU national
authorities and ensure that they are “harmonized” and “comparable” (Eurostat,
2019a). Thus, the Eurostat database is suitable for our investigation, since it covers a
large geographical area (the EU), and its rigorous procedures of collecting data ensure
a high level of data reliability and validity. Moreover, the databases can be accessed
26
We have selected a time frame from 2008 until 2017, which covers the first
ten years after the 2008 economic crisis and more than half of the implementation
period for Europe 2020 Strategy, which envisages the target for increased number of
tertiary education graduates. Our cross-country context covers all the 28 European
Union Member States.
We focus on the following variables:
Variables:
1. General government expenditure on tertiary education (as a share of GDP)
Our first variable measures government expenditure on tertiary education as a
percentage of Gross Domestic Product (GDP)9. The term tertiary education used in the four first variables refers to the UNESCO’s international educational
classification, as per Eurostat. Eurostat’s data are based on the International Standard
Classification of Education (ISCED), which ensures comparability between the
ISCED 1997, with 7 levels of education, and ISCED 2011 with 9 levels of education
(Eurostat, 2019b). In the currently used classification (ISCED 2011), tertiary
education includes educational levels from 5 to 8. ISCED 5 refers to short-cycle
tertiary education, ISCED 6 to Bachelor’s or equivalent level, ISCED 7 to Master’s or
equivalent level, and ISCED 8 to Doctoral or equivalent level10.
9 Public spending constitutes the biggest part of the general educational funding in the European Union
although significant variations exist among countries and levels of education (Eurydice, 2012).
10We use ISCED 2011 classification for tertiary education, as per Eurostat. Nevertheless, it should be
noted that measurements can be arbitrary, since there are variations in the classification of different programmes among countries, particularly as far as vocational programmes are concerned. For example, in some EU counties, professional and vocationally oriented post-secondary programmes, offered outside of higher education, may fall within ISCED 2011 Level 5 (e.g. Austria, Czech Republic, Greece, Spain, Ireland, Slovakia, Sweden, the United Kingdom) or 6 (Germany, Denmark, Estonia, the Netherlands) (For an extended discussion, see European Commission, 2016). Moreover, it should be, noted, that some vocational or occupational qualifications are not included and classified
27 2. Employment rates of tertiary education graduates (15-64 years)
Given our focus on tertiary education, we use the variable “employment rates
of tertiary education graduates” to distinguish the tertiary education graduates from
the more general Eurostat term “graduates”, which refers both to graduates from
upper secondary and tertiary levels (Eurostat, 2019c). The age group examined is
15-64 years old.
For Eurostat (2019d), individuals are classified in 3 distinct
categories: employed, unemployed, and economically inactive, applying
the International Labour Organisation (ILO)'s definitions of employment and
unemployment. Employed persons are the persons with minimum age of 15 years
who are in one of the following 2 categories: “(a) persons who during the reference
week worked for at least one hour for pay or profit or family gain, (b) persons who
were not at work during the reference week but had a job or business from which they
were temporarily absent”.
3. Percentage of working age population with tertiary education
This variable refers to the percentage of population with tertiary education (as
a % of the working age population: 15-64 years old) within a country.
4. Unemployment rates of tertiary education graduates in the working age population
according to ISCED levels, but are rather classified by the European Qualification Framework, which applies an outcome-based approach (European Commission, 2016).
28
This variable refers to the unemployment rates of tertiary education graduates
in the working age population (15-64 years old) within a country. For Eurostat
(2019d), unemployed persons are the persons with minimum age of 15 years who are
not employed according to the definition of employment above; are currently
available for work; and actively seek for work.
5. Overqualification rates (whole economy)
This variable is about overqualification rates in the labour market concerning
the whole economy. Overqualification rates refer to the share (%) of tertiary
education graduates (ISCED11 categories 5 to 8), aged 20-64, working in occupations
for which tertiary education is not required (categories 4 to 9 of the ISCO08
classification) over the total number of employed (tertiary education) graduates. We
acknowledge that this variable might raise some questions about its methodological
validity. Even though it is not yet considered as “methodologically grounded, Eurostat
uses it in its official statistics “as an experimental tool to measure over qualification”,
[because] it gives useful insight and… [because its] intuitive reasoning is
straightforward” (Eurostat, 2019e). Thus, Eurostat with its harmonised methodology,
gives us the opportunity to have comparable data and get useful insights about
overqualification across the EU member states.
In the context of our empirical analysis, we compute the correlation coefficients
(using Excel) for the following variables:
• General government expenditure on tertiary education (as a share of GDP) & Employment rates of tertiary education graduates (15-64 years old).
29
• Population with tertiary education (15-64 years) (as a % of the total population) & Unemployment rates of tertiary education graduates (15-64
years old).
• Population with tertiary education (15-64 years old) (as a % of the total population) & Overqualification rates (whole economy, aged 20-64).
5. Findings and Discussion
5.1 Public expenditure on tertiary education and employment of graduates
In Table 1 we explore the first research question. As such, we report the
correlation coefficients, along with their associated p-values, between public
expenditure on tertiary education and employment of graduates. The correlation
coefficient for the EU28 is negative (-0.62) and significant at the 10% level. However,
we observe that at the country level the correlation between the two variables is
statistically insignificant in 20 EU countries indicating the absence of any relationship
between public spending on tertiary education and graduates’ employment. In the
remaining EU countries, we observe a statistically significant negative correlation
coefficient in 7 out of 8 instances (Belgium, Czech Republic, Denmark, Lithuania,
Hungary, Poland, and Sweden). This finding suggests that an increase in public
expenditure on tertiary education is negatively associated with graduates’
employment. This, in turn, contradicts the investment-benefit hypothesis proposed by
human capital theory, according to which employment increases with investment in
education. The only country exhibiting a highly significant positive correlation
p-30
value=0.04), which indicates a positive link (and significant at the 4% level) between
spending on tertiary education and labour market outcomes. This may relate with the
country’s characteristics of the economy and labour market. It may, also relate with
the inclusion of professionally- and vocationally-oriented post-secondary programmes
31
Table 1. Correlation coefficients between public expenditure on tertiary education
and employment of graduates (years: 2008-2017)
Country Correlation between spending
and employment p-value EU-28 -0.62* 0.06 BE -0.90* 0.00 BG -0.02 0.95 CZ -0.75* 0.01 DK -0.70* 0.02 DE -0.13 0.72 EE -0.44 0.20 IE -0.27 0.44 EL 0.10 0.78 ES 0.17 0.64 FR -0.10 0.79 HR -0.54 0.11 IT -0.51 0.13 CY 0.07 0.85 LV -0.46 0.18 LT -0.73* 0.02 LU -0.06 0.86 HU -0.59* 0.07 MT 0.37 0.29 NL 0.65* 0.04 AT 0.10 0.78 PL -0.69* 0.03 PT -0.15 0.68 RO -0.03 0.93 SI -0.12 0.74 SK 0.16 0.66 FI -0.41 0.24 SE -0.77* 0.01 UK -0.36 0.31
Notes: * indicates statistically significant correlation coefficient at the 10%
significance level.
Overall, this preliminary statistical analysis indicates that more public
spending on tertiary education does not seem to be related with higher employment
rates for graduates. These findings do not support the application of the cost-benefit
framework of human capital theory, according to which investments in education are
32
expenditures on education) and benefits (such as higher employment prospects for
educated individuals) (Becker, 1994).
From a human capital perspective, these counterintuitive findings may stem
from methodological deficiencies, such as the omitted variables bias and the
simplicity of the statistical measure employed. It may be claimed that the
establishment of a robust relation between the two variables in question requires the
use of additional covariates and the application of more sophisticated statistical
techniques. Although we acknowledge that public spending on tertiary education as a
share of GDP is not the only variable that relates to graduates’ employment, such a
detailed examination lies beyond the scope of the current thesis.
Yet, this preliminary analysis indicates thatinvestment in education seems to
be inadequate for the explanation of complex socio-economic issues, such as
employment. This finding is in line with previous studies, which question the
overemphasis of the human capital theory on education and criticise it for ignoring the
role of wider social, political, and economic factors in determining labour market
participation (Gillies, 2011; Livingstone, 2012; Piketty, 2014; Marginson, 2019).
Moreover, it accords with the view that employment issues should be better
understood as an interplay between individual characteristics (e.g. education, skills or
personal attributes) and wider contextual factors (e.g. labour market and
macroeconomic factors) (Berntson et al., 2006; McQuaid & Lindsay,2005).
We should stress here that our empirical design does not imply that public
spending on tertiary education should be primarily evaluated on the grounds of its
impact on employment rates (as implied by the cost-benefit analytical framework of
human capital theory). In contrast, we believe that public spending on education is
33
5.2 Percentage of working age population with tertiary education and graduates’
unemployment and overqualification rates in the labour market
Next, we explore the second and third research questions which investigate the
relationship between the percentage of working age population with tertiary education
and graduates’ unemployment and overqualification rates in the labour market. To
this end, Table 2 reports the correlation coefficients between the number of tertiary
education graduates and graduates’ unemployment rates along with their associated
34
Table 2. Correlation coefficients between percentage of working age population
with tertiary education and graduates’ unemployment rates (years: 2008-2017)
Country Correlation between
percentage of working age population with tertiary education and graduates’ unemployment rates p-value EU-28 0.33 0.36 BE 0.37 0.29 BG 0.07 0.85 CZ -0.20 0.57 DK 0.58* 0.08 DE -0.89* 0.00 EE -0.36 0.30 IE -0.30 0.41 EL 0.81* 0.00 ES 0.47 0.17 FR 0.66* 0.04 HR 0.25 0.49 IT 0.71* 0.02 CY 0.85* 0.00 LV -0.56* 0.09 LT -0.60* 0.07 LU 0.71* 0.02 HU -0.59* 0.07 MT 0.27 0.46 NL 0.52 0.12 AT 0.80* 0.01 PL -0.38 0.27 PT 0.24 0.50 RO -0.06 0.87 SI 0.77* 0.01 SK 0.40 0.26 FI 0.88* 0.00 SE -0.08 0.82 UK -0.37 0.30
Notes: * indicates statistically significant correlation coefficient at the 10%
35
A number of interesting findings emerge from this exercise. First, we observe
that the correlation coefficients at the country level are statistically insignificant for
15 countries indicating the absence of any relationship between the percentage of
tertiary education graduates within the working age population and graduates’
unemployment rates in more than half of the EU countries. This finding also reflects
to the EU as a whole as the corresponding correlation for EU28 is statistically
insignificant at all conventional levels.
Second, we find statistically significant and positive correlation coefficients
in9 out of 13 instances (Denmark, 0.58; Greece, 0.81; France, 0.66; Italy, 0.71;
Cyprus, 0.85; Luxembourg, 0.71; Austria, 0.80; Slovenia, 0.77; Finland, 0.88). This,
in turn, suggests that in 9 countries the increase in graduates is associated with higher
graduates’ unemployment rates. A possible explanation for this positive association
might be the non-favorable economic and labour market conditions, especially in
Southern European countries which were severely hit by the late 2000seconomic
crisis (Greece, Italy and Cyprus). However, this explanation cannot fully justify the
evidence of a positive correlation between the variables under investigation in
Northern European countries which were much less affected by the crisis.
Furthermore, these results come at odds with Eurostat’s statistical data which show
that educational attainment level plays a crucial role in employment in most European
countries (Eurostat, 2019f). Specifically, these data show that those with a tertiary
level of educational attainment record the highest employment rates and are generally
better protected from the risks of unemployment compared to their peers who enter
the labour market with lower levels of educational attainment. As such, we argue that
our puzzling finding for Northern European countries may stem from the limitations
36
interpreted with caution.
Third, we observe a statistically significant negative correlation between the
percentage of working age population with tertiary education and graduates’
unemployment rates in four countries, namely Germany (-0.89), Latvia (-0.56),
Lithuania (-0.60) and Hungary (-0.59). Again, the diversity of the countries makes it
difficult to come up with common explanations. In any case, this finding might be
associated with the labour market needs in the specific countries and merits attention
for future research.
Table 3 reports the correlation coefficients between the percentage of working
age population with tertiary education and graduates’ overqualification rates in the
labour market (along with their p-values). We observe that the correlation coefficient
for the EU28 as a whole is positive and highly significant. This outcome is also
reflected at the country level since 20 EU member states exhibit a statistically
significant positive correlation coefficient between the two variables of interest
(Bulgaria, 0.66; Czech Republic, 0.93; Greece, 0.98; Spain, 0.93; France, 0.73;
Croatia, 0.84; Italy, 0.77; Cyprus, 0.75; Lithuania, 0.61; Hungary, 0.92; Malta, 0.96;
Netherlands, 0.70; Austria, 0.98; Poland, 0.90; Romania, 0.95; Slovenia, 0.98;
Slovakia, 0.96; Finland, 0.62; Sweden, 0.82; and the United Kingdom, 0.91).This
finding indicates that when the percentage of graduates in the working age population
increases, more graduates are employed in non-graduate posts in the majority of the
EU countries. This, in turn, suggests that common European policies which target at
increasing horizontally the number of graduates may further deteriorate the existing
problem of overqualification in the EU. This is in line with the studies that claim that
overqualification is not a temporary phenomenon, and therefore it should be a matter
