Society and Economy 38 (2016) 4, pp. 537–558 DOI: 10.1556/204.2016.38.4.6
TALENT-COMPETITIVENESS OF HUNGARY – DECLINE WITHOUT “FLEURS DU MAL”1 OLIVÉR KOVÁCS Research Fellow, ICEG European Center, Budapest, Hungary Email: okovacs@iceg.hu
This paper offers some ammunition to better understand Hungary’s position in the IMD World Talent Report 2015 (IMD WTR 2015). First, it gives a brief overview of the methodology of the IMD WTR by highlighting its main features. Second, it presents the 2015 ranking and puts the focus on Hungary’s withering talent competitiveness. The paper conveys the message that an overarching and consistent reform package is a must in the education system to foster talent utilisation. However, such a package is likely to be insufficient unless economic policy addresses the relevant shortcomings of the Hungarian innovation ecosystem. Keywords: talent, competitiveness, reform, education, academy JEL-codes: I23, I28, O20
1. INTRODUCTION
The fact that the performance of the Hungarian education system has been attracting increasing attention is understandable since the education system has always played a significant role in unfolding and developing the talent pool, which is the basis of socio-economic learning in terms of pursuing prosperity. The present paper is motivated by this devoted debate and by IMD World Competitiveness Center’s World Talent Report 2015 published in November 2015 (henceforward: IMD WTR 2015 or Report). The Report paints a general picture about the extent 1
The views expressed here are solely those of the author and do not in any way reflect the views of the organisation with which the author is affiliated. 1588-9726/$20.00 © 2016 Akadémiai Kiadó, Budapest
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to which countries develop, attract and retain talent to sustain the talent pool available for enterprises operating in those economies. Moreover, it points to a rather dispiriting tendency concerning Hungarian talent competitiveness. Despite the weaknesses of any competitiveness-related aggregated rankings published by various organisations around the world,2 it is scientifically instructive to have a map on talent competitive countries when the co-evolution of economic, social and environmental challenges is placing serious obstacles to sustainable socio-economic development. The dynamic configuration of the processes among public, private and civil sectors’ stakeholders within an innovation ecosystem exerts influence on the availability of talent, of which knowledge is a prerequisite of any value creation. Talent is crucial for adaptation, for propelling novelty along a learning curve, for coping with old and new (still unknown) challenges and for gaining more competitiveness on both micro and macro levels.3 For example, talent is not only important in case of the real economy, but also in case of the financial sector. While these spheres are generally viewed as coexisting and parallel to one another, they are in fact heavily intertwined and interconnected (Blanchard 2013) and are exerting influence on each other (Davis 2010). More talent in the real economy can lead to more output produced per unit of capital, while more talent in the financial sector is expected to foster more efficient allocation of financial resources (Shaknov 2014).4 It is hardly by chance that the issues of how to develop, attract, and keep top talent have become important priorities on the policy agenda. The quantity and quality of available talent dynamically determines the overall degree for exten2
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In the highly globalised world economy and in the era of knowledge economies interspersed with the dominance of services, there are at least two phenomena that are making the picture on talent competitiveness squishier: (1) work styles have been changing and remote working, mobile working gain momentum. In this light, talent can easily work even for foreign companies without emigrating. (2) Innovative places attract workers, expatriating workers are therefore more and more ubiquitous (e.g. from Central and Eastern Europe, from the countries of Eastern Partnership Countries like Moldova, Georgia, etc.). Accordingly, the ranking does not capture when talented workers emigrate to work for foreign companies. Additionally, and for instance, when a foreign subsidiary of Siemens improves the competitiveness of that country (Siemens is present in 200 countries), should its talent be omitted from the assessment of the mother country or should they be incorporated too? As Charles Baudelaire wrote in the Les Fleurs du Mal: Through the Unknown, we’ll find the New. Of course, the escalation of financial markets may be entailed with more opportunity for casino finance (i.e. financial solutions created in the spirit of obtaining higher gains in the short term by neglecting the real economic consequences of such financial behaviour over the medium term.
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sive experimentation in the innovation ecosystem of the given country.5 Experiments are of key importance for living organisms, such as the society, because experiments impel the system to improve and gain new competencies, a new level of quality of life which is more sustainable, environment-conscious and shock-resistant.6 The aim of this paper is to demonstrate how serious the declining tendency in the Hungarian talent competitiveness is by emphasising that there will be no significant improvements without strategic governmental actions, i.e. the flowers of decay, Fleurs du Mal, will not arise spontaneously. The structure of this paper is as follows. Section 2 gives a brief introductory overview on the methodology of the IMD WTR 2015 by highlighting its main features. Section 3 focuses on Hungary’s position in the ranking and offers some ammunition to get a better understanding of its declining trajectory. Finally, Section 4 concludes. 2. METHODOLOGICAL BACKGROUND OF THE IMD WORLD TALENT REPORT 2015
The paper is not aimed at exhaustively presenting the methodology of the IMD WTR 2015, rather it points to applying a holistic view when it comes to interpreting the results. The IMD WTR 2015 includes a talent ranking for all countries that are part of the IMD World Competitiveness Yearbook (i.e. 61 countries in 2015). IMD considers talent in a broader sense as the professional skills of the labour force in a country.7 The Report assesses countries on three aggregated factors – investment and development; appeal and readiness – which in turn are 5
6
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In respect to talent creation, let us note that evidence suggest that the real GDP growth is not associated primarily with the sheer number of educated people, but with the configuration of processes in the innovation ecosystem that can drive productivity. Cross-national data do not fully support the widely held belief that there is a strong positive correlation between increases in human capital attributable to the rising educational attainment of the labour force and the rate of growth of output per worker. On the contrary, there is no evidence about that, see the paper of Prichett (2001). There are various terms for such an ability: being resilient, being ‘antifragile’. See: Taleb (2014). Talent is the set of skills and capabilities necessary for enterprises, and the economy in general, to thrive in the performance of economic activities. IMD understands skills as traits of “hard” talent (e.g. physical abilities) and capabilities as elements of “soft” talent (e.g. knowledge). Talent development requires effective human resources assessment and planning, and comprises several essential components. These factors go beyond a mere increase in investment and include other elements that boost, for example, the motivation and productivity of the workforce through the provision of training. Society and Economy 38 (2016)
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Table 1. Components of the talent factors Investment and development factor Total public expenditure on education Total public expenditure on education (per pupil) Pupil-teacher ratio (primary) Pupil-teacher ratio (secondary) Apprenticeship Employee training Female labour force Health infrastructure
Appeal factor
Readiness factor
Cost of living Attracting and retaining Worker motivation Brain drain Quality of life Foreign skilled people Remuneration in services professions Remuneration of management Effective personal income tax rate Personal security and private property rights
L abour force growth S killed labour F inance skills I nternational experience C ompetent senior managers E ducational system S cience in schools U niversity education M anagement education L anguage skills S tudent mobility inbound E ducational assessment – PISA
Note: new indicators to the 2015 edition are in italic. Source: IMD World Talent Report 2015.
derived from a much broader range of indicators. Note that the methodology has been recently changed by including additional indicators as well (see Table 1). It is important to stress that at least three features should be kept in mind when it comes to interpreting the results. First, quantitative data are complemented with subjective judgements captured by the conducted survey.8 Soft data (opinions from the survey) are dominating over hard data (statistics) both in case of the appeal and the readiness factors.9 It is well-known from psychological studies that the 8
9
For example, IMD WTR does not always take into account the number of private higher education institutions beyond the public ones. In case of Finland, there are no public universities since 2010. This may distort the whole picture since the number of private institutions is traditionally high in Japan or in the Korea (Republic). In Hungary, the share of private education institutions at all levels is pretty much close to the OECD average. In addition, if one looks at the number of private universities or private higher education institutions in Armenia, Belarus, Georgia or in Ukraine, it can be concluded that they have relatively high numbers of those (e.g. to date, in Georgia, that number is double that of the public ones (53), while in Ukraine, the number of higher education institutions is 800! Data are from national statistical offices, GeoStat, UkrStat). The share of subjective opinions are as follows: 37.5% in case of investment and development factor; 60% in case of appeal factor; while 75% in case of the readiness factor. The Executive Opinion Survey of the IMD World Competitiveness Yearbook (henceforth: the Survey) tackles the relevant talent-related issues. The Survey was sent out in January 2015 and returned in April 2015; in 2015, IMD received 6,200 responses from the 61 economies worldwide covered by the IMD Competitiveness Yearbook and IMD World Talent Report. The respondents assess the competitiveness issues by answering the questions on a scale of 1 to 6. The average value for each economy is then calculated and converted into a 0 to 10 scale.
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time horizon of subjective opinions and perceptions spans over years instead of being based on only one year by representing tendencies, memories, and attitudes. These form the ‘psychic capital’, a term coined by Kenneth E. Boulding in 1950. This channel is heavily influenced by economic policy measures and their Knightian (1921) uncertainty-generating or dampening impacts. Uncertainty (unknown risk) can be associated with a decision’s exact outcome as well as with the issue of what a socio-economic actor (e.g. firm, government) shall do under the given complex circumstances. In this way, the ‘trust infrastructure’ is influenced in the society, importantly, the trust exuded by the citizens and firms towards the state and its institutions.10 The room for unfolding talent in a society inevitably relies on the trust infrastructure, since knowledge sharing is promoted more in a higher trust based environment.11 Second, this is a relative ranking, a certain movement of a country is not necessarily caused by developments within that country but may be the result of other countries’ change in ranking. Third, the availability of hard data is not outbalanced since some countries appear in the talent ranking only since they became part of the World Competitiveness Yearbook of which data the IMD WTR 2015 relies on (e.g. Latvia appeared in the ranking since 2013). In the 2015 edition of the World Talent Report, Switzerland leads the ranking in meeting corporate needs through developing, attracting and retaining talent in a more vigorous way than Denmark (2), Luxembourg (3), Norway (4), the Netherlands (5), Finland (6), Germany (7), Canada (8), Belgium (9) and Singapore (10). It implies that Europe can be seen as a major source of, and a magnet for, business talent. Interestingly, Hungary is at the bottom with its 56th position indicating that something deeper is amiss. 3. HUNGARY IN THE IMD WTR 2015
3.1 The bird’s eye view on Hungary Hungary is ranked at the 56th place in the IMD WTR 2015. This shows a 5-place relative decline compared to its 51st position in 2014. From a regional perspective, Hungary’s talent competitiveness deteriorated to the greatest extent among the Visegrád countries (Czech Republic, Hungary, Poland, and Slovakia; hence10
11
The trajectory of the number of emigrated young and highly skilled career starters can be seen as a good proxy for capturing the declining tendency in trust. In case of Hungary, almost 400,000 young career starters left the country between 2010 and 2013 (See Central Statistical Office of Hungary). See Chowdhury (2005). Society and Economy 38 (2016)
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2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 0 10 20 30 40 50 60 Czech Republic
Hungary
Poland
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Figure 1. Historical rankings of the V4 countries in the IMD WTR (2005-2015) Source: author’s compilation based on IMD WTR 2015.
forward V4) since 2005 (Figure 1). The biggest decline was observed after 2012. Let us note that the fact that the ranking position got impaired the most by 2013 does not necessarily mean that the complex set of causes had evolved during only the year 2012. This is an end result of longer term processes that manifested in negative opinions reflected in the survey. As far as investment and development is concerned between 2011 and 2015, Hungary was the only V4 country which deteriorated dramatically rather than improved talent development and increased the talent required investments (the most outstanding decline, –16 places, was between 2014 and 2015) (Figure 2). With respect to appeal and readiness factors, Hungary can be regarded as a laggard even among the V4 countries (Figures 3 and 4). In terms of appeal, Hungary is ranked at the bottom with only Bulgaria and Venezuela behind overall. If one takes a mere glimpse into the sub-indicators, at least the following smorgasbord of observations can be made regarding the Hungarian case: – in terms of total public expenditure on education as percentage of GDP, Hungary is in the middle field with its 30th (2014) and 32nd (2015) positions. The relative domestic expenditures on education represent an approximately average value among the developed countries (the respective positions of V4 in 2015: Czech Republic (25); Poland (23); Slovakia (47)). In general, Hungary’s expenditure on education is similar to that of Ireland. Note that the sheer volume of the total public expenditure on education set to the GDP does not automatically determine better positions in the rankings. For example, Singapore Society and Economy 38 (2016)
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Figure 2. Investment and development factor in V4 countries Source: author’s compilation based on IMD WTR 2015.
Figure 3. Appeal factor in V4 countries Source: author’s compilation based on IMD WTR 2015.
Figure 4. Readiness factor in V4 countries Source: author’s compilation based on IMD WTR 2015. Society and Economy 38 (2016)
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(56), Qatar (55) have worse positions in respect of expenditure on education, however, these countries have better positions in the overall ranking with their 10th and 29th places, respectively.12 in terms of public expenditure on education per pupil (secondary), Hungary has been at a relatively good 22nd position in 2014, but in 2015 this position sunk to 32nd place. Public expenditure on education in Hungary exceeded that of Israel both in 2014 and 2015, yet Israel has performed much better than Hungary in the overall ranking by reaching the 22nd place in the IMD WTR 2015. (V4 positions in 2015: Czech Republic (22); Poland (25); and Slovakia (38)). in terms of the pupil-teacher ratio (primary education), Hungary has an upscale place with its 6th position following Luxembourg, Greece, Qatar, Iceland and Norway. in terms of the pupil-teacher ratio (secondary education), Hungary was 14th in 2014, then it slipped to 22nd in 2015. In this respect, the Czech Republic (18) and Poland (14) performed better than Hungary, while Slovakia ended at the 35th place. Albeit Hungary outdid inter alia Israel (25), Sweden (27), Finland (31), Germany (37), Singapore (38), and the Netherlands (51); the fact that Kazakhstan (5) or Russia (10) are ahead of Hungary implies that ending at the top in terms of this indicator does not necessarily mean that the education system is a fertile ground for talent. The optimal rate of pupil-teacher at secondary education depends not only on the nature of education, but also on the versatility of institutions as well as on their size. in terms of apprenticeships, Hungary performs poorly (55), and is exceeded even by Malaysia. V4 countries are performing relatively worse in general in this respect (Czech Republic (50), Poland (32), and Slovakia (52)). in terms of employee training, Hungary (53) is even feebler as compared to the Czech Republic (40), Poland (42), and Slovakia (34). The reason behind this result may be that the competent leadership/management lacks relevant knowledge and commitment, their financial capacity to initiate employee trainings is limited and the employees are not properly motivated (57). in terms of attracting and retaining talents, except the Czech Republic (41), the rest of the V4 countries are ranked in a group of low performers (Hungary (57), Poland (61, Slovakia (58)).
12
Against this background, studying what and how our teachers are teaching seems to be one of the most instructive research programs because some argue that knowledge-based educational approach results in people with skills built on each other (increased vocabulary) leading to better learning abilities compared to the problem-solving oriented approach. See Hirsch (2003; 2013).
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– in terms of brain drain, the expressed opinions of Hungarian executives reflect the serious threat around this issue. Hungary is the 60th country in the ranking. Of course, brain drain is not an independent variable, it is fundamentally influenced by other factors such as the dissatisfaction with the quality of life in Hungary (56). – in terms of attracting foreign high-skilled people, Hungarian executives found it hard to attract such talents in a sustainable way. While attracting them was deemed as relatively easier in the Czech Republic (29) and Poland (42); Hungary (52) and Slovakia (53) are struggling in this respect. – in terms of labour force growth, opinions have changed since 2014 simply because the Hungarian labour force expansion shifted to the real private sector employment rather than being driven by public work program. Thus, Hungary’s position improved from the 39th position of 2014 to the 13th place in 2015. Despite the aforementioned, the availability of skilled labour force in Hungary remains a problematic factor (48th place in 2014, 53rd place in 2015), while other V4 countries can tap skilled labour relatively better (Czech Republic (33), Poland (19), and Slovakia (34)). – in terms of competent senior managers, according to the opinions of executives they are considered not to be available in Hungary (60) however, senior managers are more available and present in the Czech Republic (34), in Poland (20), and in Slovakia (49). The senior managers’ international experience in Hungary is relatively low (Czech Republic (20), Hungary (43), Poland (17), and Slovakia (40)). In connection with this dimension, the senior management education is surveyed as a field with significant shortcomings in Hungary (54). For comparison, the Czech Republic (30), Poland (24) and Slovakia (45) were deemed as places offering better senior management education. – in terms of language skills, which is a glue of effective collaboration, it is considered to be disquietingly problematic in case of Hungary (58). For comparison, the Czech Republic (32), Poland (17), and Slovakia (30) perform better. Overall one can come to the conclusion that Hungary has been losing its ground in terms of talent competitiveness. Furthermore, the big picture is that – except for Poland – V4 countries’ talent competitiveness have been decreasing since 2005.13 This fact raises concerns over the healthy knowledge creation and knowl13
The Polish case is somewhat different. Poland faced a serious and ever-increasing outflow of people after joining the European Union in 2004 (Kaczmarczyk – Okolski 2008). The cited author found that the share of tertiary educated emigrants of age group 25–29 increased from 21.6% to 33.7% after 2004, meaning that the drainage of highly educated people in younger working age bracket has increased considerably after Poland had joined the EU. After 2008, more and more programs were dedicated to attracting emigrated Polish people back into the Society and Economy 38 (2016)
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edge transfer through enhancing the talent competitiveness. In an effort to get a better understanding over this issue we first look at the Hungarian case from a broader perspective then we address the question of what is the situation with innovation in the higher education systems of Central and Eastern European (CEE) European Union (EU) member states, including V4 countries. 3.2 A broader view on Hungary’s talent competitiveness 3.2.1 The Hungarian reality Talent-endowment is more likely to be associated with a more pro-active, risktaker entrepreneurial mind-set that can open the floodgates of innovation, ultimately that of longer term total factor productivity (TFP). However, a growing number of studies have emphasised that productivity in case of Hungary has been either stagnating or slightly declining from 2006 onwards (Kónya 2015). It per se indicates that the innovation ecosystem of Hungary either lacks talent or at least utilises the talent-base in a rather inefficient way.14 Of course, talent can be interpreted in many ways, but in its core is that each individual has abilities and skills to be elaborated further and utilised. In this process, the responsibility of education system is enormous. In 2010, a comprehensive research revealed that the Hungarian higher education system and the academia, even after 20 years of the regime change, were still associated with the following features: lacking or stalled reforms; significant distortions in the fields of employment, scientific promotion and scientific performance evaluation methods; underdeveloped institutional and operational environment; academic view lacking economic relevance.15 In addition, as we documented elsewhere (Kovács 2015; 2016), after 2010, the Hungarian economic governance injected additional uncertainties into the innovation ecosystem through its autocratic (Kornai 2015) measures by leading to deteriorations in many aspects (close to zero potential economic growth, depressed investment
14
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country (e.g. ReturntoPoland.pl; “Masz PLan na powrót?” (Have you got a PLan to return?)). After all, in recent years, return migration has become a decisive feature of the Polish economy (Lesińska 2013). This huge wave of emigration was the root behind Poland’s worse place in the IMD WTR 2011, and the return migration has been a key driver of improvement. Kónya (2015: 1121) recalibrated TFP for Hungary by incorporating the human capital too and found that TFP has been stagnating since 2006 in spite of the fact that the number of primary school graduates has been shrinking and the proportion of higher education graduates has been increasing. See Polónyi (2010).
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Figure 5. Education component of the HIHD (1870–2007) Note: The education component measures literacy and enrolment. The rate of adult literacy is defined as the percentage of the population aged 15 years or over who is able to read and write. Gross total enrolment rate provides the percentage of population in the relevant age cohort enrolled in primary, secondary, and tertiary education. Higher the value, the better human development a country achieves. The index for each dimension ranges between 0 and 1. Source: Historical Index of Human Development.
activity, increasing poverty, heightening impoverishment, etc.). These processes are not conducive to breed and exploit talents.16 Importantly, a holistic view must recognise that our socio-economic innovation ecosystem is a complex, open, adaptive system in which path-dependent development is often the rule rather than the exception. With this view, one can note that CEE region’s education performance has been lagging behind that of the Western European countries since 1870 and a more observable divergence gained momentum after 1990. This can be justified by looking at the longue durée analysis of human wellbeing captured by the so-called Historical Index of Human Development (HIHD), and its education component in particular17 (Figure 5). Although the education component for Hungary suggests that the Hungarian education converged to that of the OECD average up to 1965, then the conver16
17
For example, according to Eurostat (2016), the share of children at risk of poverty or social exclusion has been on a growing trajectory only in Hungary among the EU member states. Let us remember one of the main findings of Ravallion (2015), that diffusion of knowledge is much more hampered in a country featured with relatively higher level of poverty or increasing impoverishment. This implies an even gloomier talent-outlook in Hungary. The Historical Index of Human Development (HIHD) is inspired in and adapts from a long run perspective of The United Nations Development Programme’s Human Development Index (HDI) (UNDP 2014). For a detailed explanation of the concept, see: Prados de la Escosura (2015). Society and Economy 38 (2016)
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Figure 6. Education component of the HIHD (1850–2007) Note: Data for the V4 countries are available as follows: Czech Republic (1990–2007), Hungary (1870–2007), Poland (1870–2007), Slovakia (1990–2007). Higher the value, the better human development a country achieves. The index for each dimension ranges between 0 and 1. Source: The Historical Index of Human Development, Prados de la Escosura (2015).
gence lost its élan (Figure 6). This component does not adequately capture the performance since it only measures literacy and enrolment. Historically, Hungary has always been at a position like in the IMD WTR 2015. Despite the popular belief, Hungarian education has never been world class. According to the PISA surveys, Hungary has been in the last third in the rankings of developed countries. The education system – which can be regarded as a stove of talent-creation – has been always rather polarised.18 The majority of children are absorbed by moderate or poor performing secondary grammar schools, poor secondary vocational schools, and very poor vocational schools. The main point here is that the education per se is not necessarily worse than in other countries, but the variance of the PISA results is higher mainly due to the students’ socio-economic backgrounds. In other words, the Hungarian education system cannot cope with the huge differences among students in terms of family, economic or urban situation, etc., while such variance is significantly lower in other countries. As a corollary, the students getting in vocational schools have inherently weak competencies being relevant for the purpose of PISA surveys. In 2012, the 15-year-old students’ problem solving ability was the worst in Hungary among the V4 countries (Figure 7) and was in the last third range of the countries
18
See Fazekas (2011); Gál (2014).
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listed.19 Graduated students from the vocational schools predominantly have low general literacy and they are the labour force for the Hungarian industry and services. Not surprisingly, the executives from Hungary expressed that they have to pay great attention to further training and education of their employees.20 Higher education institutions are also weak, only a few universities are among the top 500-600 in world rankings.21 Hungarian universities were not in the top 10 among Eastern European universities.22 One of the consequences of this is the relatively low ratio of advanced educated adult population. In 2013, the ratio was 19.4% within the total number of the adult population which is slightly higher than the Moldovan (19%), but below the Greek (22.3%).23 From this perspective the ratio of people aged 30–34 with tertiary education in Hungary – who can be young innovative entrepreneurs – has been converging to the EU28 average by reaching 89% in 2014; still it is below the Polish ratio of 111%. Consequently, the performance of the Hungarian higher education is mainly at the bottom of the developed countries.24 Interestingly, the Hungarian society seems to ignore these facts since the Hungarian parents want their child to graduate from a university in a more vigorous way as compared to the German or Belgian parents (PISA 2012: 22). 19
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According to Polónyi (2015), not only the PISA surveys, but also those that are to capture adult literacy and other skills (e.g. OECD’ ALL surveys) are conveying the message that Hungary has been on a declining trend. In addition, the proportion of illiterate people in Hungary has not basically changed since 1890! In this regard, Hungary continues to be one of the worst performers. See more on this issue: Sáska (2006: 11). There are multiple reasons behind the weak performance, the following is also crucial: 1) the salary of teachers with 15 years of experience (PPP, $) at all levels of education lags far behind the OECD average (lower than that of Mexico or Turkey). See: OECD Statistics. 2) Teachers with poorer skills and ability to teach have become decisive leading to low-skilled and poorly educated graduates. Only four Hungarian universities were ranked in the QS World University Rankings 2014/2015 (QS 2015). Nonetheless, these rankings are incapable of capturing the variety and size of universities, but their number. A substantial improvement can also be seen in case of a particular university when it “bought” professors having long publication lists that matters a lot, however, the quality of education does not necessarily improve in parallel. The teacher-student ratio is heavily dependent on the type of education, the nature of the offered courses. That number per se does not tell much about the quality level of education. Some Hungarian positions: University of Szeged (13th) in QS EECA among 150 universities, ELTE (16th), University of Debrecen (29th), BME (32nd), Corvinus (42nd). See QS EECA, or in Hungarian HVG (2015). See ILOSTAT (2016). For example, the best education of economics in Hungary was found to be at Corvinus University of Budapest, which is 700th in the QS World University Rankings, while in the ranking of University Ranking by Academic Performance, which measures the quality of research, was at a place of 2500th. Society and Economy 38 (2016)
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Percentage of top performers in problem solving and at least one other subject Singapore 25.0 Korea 20.9 Japan 16.0 Hong Kong-China 15.9 Chinese Taipei 17.1 Shanghai-China 17.9 Canada 12.0 Australia 12.0 Macao-China 12.6 Finland 12.0 Belgium 10.8 England (United Kingdom) 9.8 Netherlands 11.5 Norway 7.9 Germany 9.9 France 9.5 Czech Republic 9.0 Estonia 9.3 United States 7.5 OECD average 8.2 Austria 8.0 Italy 6.2 Ireland 6.8 Israel 6.6 Sweden 5.6 Denmark 5.6 Slovak Republic 6.0 Spain 4.4 Portugal 5.1 Russian Federation 4.2 Poland 5.7 Slovenia 5.3 Hungary 4.1 Serbia 2.8 Croatia 3.6 United Arab Emirates 1.7 Turkey 1.8 Chile 1.0 Brazil 0.7 Bulgaria 1.2 Uruguay 0.6 Colombia 0.3 Malaysia 0.5 Montenegro 0.4 0
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Figure 7. 15-year-olds’ problem solving proficiency Source: OECD, PISA 2012, Figure V. 2.7
Nevertheless, the ratio of people aged 25–64 with tertiary education has been mainly stagnating only in Hungary among V4 countries between 2008 and 2014. Figure 8 pinpoints the halt of the human capital accumulation. This chart might also indicate that highly educated people have been more likely to find employment abroad. The major part of emigrants are typically active adults, people aged 25–34 (e.g. in 2013, their number was approx. 10,000; see Eurostat 2015a). According to Eurostat statistics, the annual number of emigrating people from Hungary was between 2,500 and 3,100 in the period 1998–2003. The EU accession accelerated the pace of emigration by reaching 3,700–4,500 per year between 2004 and 2007. The advent of the Great Recession, due to the 2008 financial and economic crisis and its ensuing Eurozone sovereign debt crisis, triggered even more emigration on an annual basis (more than 10,000 people emigrated per year Society and Economy 38 (2016)
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100 80 60 40 20 0 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Czech Republic
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Figure 8. Share of people aged 25–64 with tertiary education (%, EU28=100) Source: author’s compilation base on Eurostat data.
between 2008 and 2010). In addition, as mentioned earlier, the ruling cabinet of Hungary injected so much uncertainty over the present and the future that resulted in a vehement and mass emigration trend from 2010 onwards. The number of emigrating people in 2010 (13,365) doubled in 2013 (34,691; see Eurostat 2015b).25 The above considerations imply that history and legacy matters, especially in the CEE region. This calls for differential diagnosis when it comes to fostering talent management and the ability of talent to prevail in CEE regions. In the following section we shed more lights on this issue. 3.2.2 Higher education, academia, and innovation in the CEE region In this section we argue that CEE member states are still struggling with the heritage of hampering the evolution of a healthy innovative milieu in higher education and academia. This has a negative effect on the latitude of developing, attracting and keeping top talent by these knowledge-creator and -transfer institutions. We are living in a ‘learning economy’ where the knowledge production and the ability of actors to rapidly gain new competences are the key driving forces of innovations and therefore of competitiveness. Talents play a key role in this 25
What is more, the share of people aged 25–64 with tertiary education in Poland was increasing between 2008 and 2014. This was the result of at least two contradictory processes: while more and more people emigrated from Poland after 2008 (more than 74,000 people emigrated in 2008, which rose to over 229,000 by 2009, and that number was more than 276,000 even in 2013), there was a growing number of Polish people who returned during this period (the number of returning Polish people was 142,348 in 2009, compared to the 35,891 in 2008, that number was more than 131,000 even in 2013; see Eurostat 2015c). Society and Economy 38 (2016)
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process as they can be both the sources of new knowledge and the translators of relevant knowledge into practice. The withering growth performance of the EU relates partly to the research performance in which the roles of academic sphere and higher education are crucial.26 Consequently, Science and Technology Policy (STP), as the accelerator of scientific and technological development and also as the institutional factor in the economic utilization of innovative outcomes, is a noteworthy field in the EU. Since new technology is not the panacea in itself, the raison d’être of higher education and the academic sphere is the provision of well-educated graduates with developed learning skills who are able to generate and use new knowledge in order to increase the absorption-capacity of the society regarding new technologies. This has yet not happened in the EU to the same degree as it did in the main competitive partners (i.e. the United States or South Korea). The consequence of this was the deceleration of total factor productivity growth over time (Halmai 2014; Dabla-Norris et al. 2015:7). While higher education reforms, invoked to encourage innovation, have been introduced across Europe during the last 25 years, the innovation gap has gently decreased between the EU and its traditional competitors, the US and Japan, and also Asia is catching up dynamically. South Korea, the US and Japan have innovation performances that dominate the EU in aspects like […] business activity as measured by R&D expenditures in the business sector, publicprivate co-publications and PCT patents, but also in educational attainment as measured by the share of population having completed tertiary education. Enterprises in these countries invest more in research and innovation, and collaborative knowledge-creation between public and private sectors is better developed. The skilled workforce in these countries is also relatively larger than in the EU” (European Commission 2015: 32).
Behind the curtain of this performance gap, a myriad of studies emphasised that the European universities have been underachieving due to their unsatisfactory autonomy and the lack of inevitable managerial approach (Aghion et al. 2007). Other equally important constituents of the gap are the relatively low investments in the university system, the perceivable shortcomings in monitoring and assessment, and the distorting incentives. STP and innovation policies should incorporate these imperfections and also have to be aware of the different situations decipherable in the case of CEE. 26
The weaving relation among the three depressing forces such as the 2008 financial and economic crisis, its ensuing sovereign debt crisis in the Euro area, and the lacklustre crisis management, triggered a recessionary effect. In a time of recession, risky undertakings like research and development and bigger scale innovations are doomed to be delayed or suspended resulting in an even more vulnerable growth potential.
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The epochal transformations that took place in the 1990s call our attention to the more complex set of issues in case of CEE countries. It seems that pathdependency played (is playing) a conspicuous role and this is why ‘the past has a great future’ in CEE countries. One of the fundamental leitmotifs behind the collapse of state socialism was the inability to innovate, which can be attributed to the characteristics of the institutional system rather than to the conventionally postulated dominancy of state ownership and to the absence of private ownership (or to its infinitesimal presence). With the benefit of hindsight, it can be easily justified by the relatively low innovation performance of the post-socialist EU member states conveying the message that the institutional features have not gone through significant changes. For example, the Hungarian path can be regarded as a more or less ubiquitous phenomenon in the CEE countries, which underpins that the lower-than-expected level of innovation-driven economic development is, to a non-negligible extent, induced by the organisational, operational and managerial features of academic sphere.27 The structure and the motivation regime of the academy has not changed much and the formal academic performances as well as the places in the hierarchy are dominating the real scientific performances. The higher education system, especially state universities in post-socialist countries are mainly self-managing and behave like socialist enterprises with the dominancy of bureaucratic coordination (Polónyi 2010). These peculiarities are unequivocally influencing their willingness to innovate. Owing to self-managing, the major aim is to maximise wages and salaries whereby they are to a large degree disposed to use their innovation ability primarily for reaching subsidies and allowances provided by the state. This kind of rent-seeking is extremely preferred in such a situation where the proper performance assessment structure is scantily working. Governments support R&D and innovation through various entitlements and define on what research and innovation should the financial sources be spent. The fathomable reason behind this is the government’s assumption regarding the universities that they would not be able to target the financial sources as efficiently as the government. Organisations managed by non-market coordination are thus condemned to low level of innovation efficiency. Taking into account the major prerequisites of impulsive innovation dynamism (decentralised initiation; high reward; competition; opportunity for wide experi27
Csaba et al. (2015) call the attention to the still observable hierarchical and cumbersome functioning of the academy, which inter alia tends to support the quantitative view along the qualification process as well. Albeit the use of summary measures (in which prestigious journals the author published, citation number, which institution the author is affiliated with) is a prevalent technique in the economic profession, this approach seems to be a rather poor signal of individual results. See more on this in Hamermesh (2015). Society and Economy 38 (2016)
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ments and the flexibility of financing), emphasised by Kornai (2010), the following observations can be made based upon the work of Polónyi (2010). State universities have hierarchical career systems that have a negative effect on decentralised initiations, because upper level representatives of the organisation are inclined to exercise control over the knowledge emerging in lower levels in order to benefit from it. Ambitious amount of reward for those who explicitly carry out innovations is principally outstanding. The employment system promises high incomes at the end of university (academic) career by utilising network capital, accumulating different leading positions in state organisations and concentrating on rent-seeking. As a result, this type of employment and income system easily scrolls obstacles towards healthy competition. The career model narrows the latitude of opportunities for providing a wide range of experiments, because the burdens on employees are the greatest when their intellectual conditions would be the best. Regarding the flexibility of finance, the sources are planned on governmental – instead of institutional level –, which obviously questions whether the sources inflowing to lower levels of organisations are sufficient.28 The clear inference is that differential diagnosis is a must when it comes to promoting talent-competitiveness by facilitating innovation at higher education and academia in the CEE countries, including Hungary.29 STP and innovation policymakers should more vigorously take into consideration the repercussion of the industrial restructuring that took place in the CEE countries in the 1990s (Rainer et al. 2009). Despite the rapid industrial restructuring, CEE countries have been more or less locked into low value added economic activity in contrast with the requirement of the new techno-economic paradigm30 (i.e. high value added products and services via knowledge management in companies instead of specialisation into lower end of value chain). The modular-production especially in ICT had distorting impact on the base of CEE countries’ innovation policy. The statistics took into account the low value added export products (e.g. screens of cell phones) as high technology products envisioning that the share of high-tech export is well-performing. Nonetheless the general expenditure on R&D and innovation as a percentage of GDP and the patent applications declined simultaneously in the aftermath of industrial restructuring. Accordingly, the industry needs 28
29
30
In such an environment, it is hardly by chance that knowledge transfer between universities and industrial players falls short. The share of co-publications with industrial partners is reported to be rather low even in case of Central European University. See: U-Multirank, the largest global university ranking for 2016/2017 initiated by the European Commission (2016). True, this view has been more and more incorporated into the EU policymaking regarding higher education. “[…] there is no one-size-fits-all approach.” (European Commission 2013: 4). On new techno-economic paradigm, see Perez (2009).
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were not captured by the innovation policy adequately which neglected that the structural changes resulted in specialisation in lower end of value chains. In addition, this type of internal configuration did not provide a coercive power to bolster talent utilisation and education. Even the Europeanization of innovation policy in the CEE countries, especially the availability to EU structural funds, had negative impact on innovation policy. There were not enough administrative capacities and experience with long-term planning, and the routine in cooperation and coordination of networks also suffered from hiatus. The processes were weak in terms of coercive power to raise the policymakers’ attention to the fact that the society’s absorption capacity mostly depends on such higher education system in which the structural lock-in effect of the past institutional settings and managerial attitude are converted into a coordinationready status, and to be complemented with the necessary autonomy. However, the EU’s aim to alleviate the weakness of labour market establishes a claim to these changes invoked to enable both the unemployed and employed people to have a better opportunity to maintain and upgrade their skills. The ability of people to learn, apply and utilise new knowledge bears the torch of innovation and overall the human well-being in the present and in the future alike. 4. CONCLUSIONS
The IMD WTR 2015 rings an alarm bell for Hungary about its deteriorating trend in terms of talent competitiveness. From a broader perspective, Hungary’s position can be seen as an unfortunate, but logical outcome by taking into account the historical performance of its education system as well as the changes happening or not happening during the last decades. On the one hand, the Hungarian education system needs a complex reform package spanning across the whole spectrum (primary, secondary, tertiary education levels, including the research sphere) through providing financial support, development programmes, new incentive regimes with performance monitoring and evaluation systems. Such development policy should also serve to bridge the gap between well-endowed, developing and lagging-behind education institutions. In addition, the academy needs to be streamlined in the sense that real scientific performances must be pursued and taken as guiding principle instead of building on administrative performances. On the other hand, with a more holistic approach, the above mentioned recommendations seem to be inevitable and necessary but by no means sufficient. The education system is an important but not the only element in the innovation Society and Economy 38 (2016)
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ecosystem of Hungary in which talent can be sparked or stifled under some circumstances (e.g. increasing uncertainties because of the spectacular deterioration of formal institutions, the weakening checks and balances in the democratic system (Kovács 2016)). In the cited paper, we illustrated that the ruling cabinet of Hungary has systematically broken down the quality of formal institutions after winning the elections in 2010.31 An autocratic regime has emerged (Kornai 2015), pervaded by more nationalism and more macroeconomic populism. What is more, expenditures on education in Hungary were significantly decreased rather than increased which is in diametrical opposition of what has been happening in the advanced world.32 In an institutionally weak environment, talent motivation can be easily fuelled by more lucrative rent-seeking activities as Arezki et al. (2012) documented. In this way, talent, at least, tends to shift out of private entrepreneurial activity into those fields, with detrimental implications for efficiency and sustainable economic growth. Institutions need to be redesigned in Hungary to guard against such developments by creating a more solid chance for fleurs du mal in Hungary. REFERENCES Aghion, P. – Dewatripon, M. – Hoxby, C. – Mas-Colell, A. – Sapir, A. (2007): Why Reform Europe’s Universities? Bruegel Policy Brief 4. Arezki, R. – Thorvaldur, G. – Amadou, S. (eds.) (2012): Beyond the Curse: Policies to Harness the Power of Natural Resources. Washington DC: International Monetary Fund. Blanchard, O. (2013): Five Lessons from the Financial Crisis. Speech at the What should economists and policymakers learn from the financial crisis? Conference, London School of Economics, 25 March. Boulding, K. E. (1950): A Reconstruction of Economics. New York: Wiley. Chowdhury, S. (2005): The Role of Affect- and Cognition-based Trust in Complex Knowledge Sharing. Journal of Managerial Issues 17(3): 310-326. Csaba, L. – Szentes, T. – Zalai, E. (2015): Mégis, kinek az Akadémiája? [Whose Academy Is It Anyway?] Magyar Tudomány 176(9): 1113-1137. Dabla-Norris, E. – Guo, S. – Haksar, V. – Kim, M. – Kochhar, K. – Wiseman, K. – Zdzienicka, A. (2015): The New Normal: A Sector-Level Perspective on Productivity Trends in Advanced Economies. IMF Staff Discussion Note 03 Davis, S. (2010): The Adverse Feedback Loop and the Effects of Risk in Both the Real and Financial Sectors. Federal Reserve Bank of Dallas Globalization and Monetary Policy Institute Working Paper No. 66. European Commission (2013): European Higher Education in the World. Brussels: European Commission, DG Education and Training. 31 32
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