IMD World Talent Report 2015 - No Fleurs du Mal for Hungary? by Oliver Kovacs

IMD WORLD TALENT REPORT 2015 – NO „FLEURS DU MAL” FOR HUNGARY? Olivér Kovács1 2

Abstract This paper offers some ammunition to better understand Hungary’s position in the IMD World Talent Report 2015 (IMD WTR 2015). It gives a brief overview on the methodology of the IMD WTR by calling the attention to its main features. It then 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, that package is likely to be insufficient unless the economic policy addresses the relevant shortcomings of the Hungarian innovation ecosystem.

The views expressed in this study are those of the author and do not necessarily represent that of the ICEG European Center with which the author is affiliated. 2 Olivér Kovács, Research Fellow, ICEG European Center, Member of the Public Body of the Economics and Law Section of the Hungarian Academy of Sciences, Committee on World Economics and Development Studies. Contact: okovacs@icegec.hu, oliverkovacs.com

Table of Contents I. INTRODUCTION .................................................................................................................................... 3 II. METHODOLOGY................................................................................................................................... 4 III. RESULTS OF THE WORLD TALENT REPORT 2015................................................................................ 6 IV. HUNGARY IN THE IMD WTR 2015 ...................................................................................................... 7 4.1 The bird’s eye view on Hungary .................................................................................................... 7 4.2 A broader view on Hungary’s talent competitiveness ................................................................ 10 V. CONCLUDING REMARKS.................................................................................................................... 17 References ............................................................................................................................................. 18

I. INTRODUCTION On 18th of November 2015, IMD World Competitiveness Center published the 2015 edition of its wellknown World Talent Report (henceforward: IMD WTR 2015) which paints a general picture about the extent to which countries develop, attract and retain talent to sustain the talent pool available for enterprises operating in those economies. Despite the admitted weaknesses of any aggregated rankings regarding competitiveness that are published by various organisations around the world3, it is scientifically instructive to have a map on talent competitive countries in our turbulent time when the co-evolution of economic, social and environmental challenges are placing serious obstacles in front of achieving sustainable socioeconomic development. The dynamic configuration of the processes among public, private and civic 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 adopt to changes, to propel novelty along a learning curve and to gain more competitiveness at micro and macro levels alike. For example, talent is important not only in case of the real economy, but also in case of the financial sector. Although financial sector and the real economy are generally viewed as two coexisting and different worlds, they are 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 The issues of how to develop, how to attract, and how to keep top talent have become an important priority on the policy agenda. The quantity and quality of available talent dynamically determines the overall degree for extensive 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, new level of quality of life which is more sustainable, environment-aware and resistant to shocks.6 The structure of this short paper is as follows. Chapter 2 gives a brief overview on the methodology of the IMD WTR by calling the attention to its main features. Chapter 3 then presents the ranking of the IMD WTR 2015. Chapter 4 focuses on Hungary’s position and also offers some ammunition to get a better understanding over its declining trajectory. Finally, Chapter 5 concludes.

3 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? 4 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. 5 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). 6 There are various terms for such an ability: being resilient, being ‘antifragile’. See: Taleb (2014).

II. METHODOLOGY The IMD WTR 2015 includes a talent ranking for all countries that are part of the IMD World Competitiveness Yearbook (61 countries in 2015). The data are gathered from the Center’s extensive database, which encompasses 20 years of competitiveness-related data. All data employed in the development of the report can be accessed through the World Competitiveness Online website. The report assesses countries on three aggregated factors – investment and development; appeal and readiness – which in turn are derived from a much broader range of indicators: 



The first factor takes into account the investment in and development of home-grown talent. It traces the size of public investment on education by incorporating an indicator of public expenditure. It also looks at the quality of education through indicators related to pupil-teacher ratios. The development of talent is covered by variables related to the implementation of apprenticeship and the priority of employee training for companies. It also looks at the development of the female labour force. In addition, this factor takes into account the quality of the health infrastructure in terms of meeting the health needs of society. The appeal factor goes beyond the focus on the local labour force to incorporate the ability of a country to tap into the overseas talent pool. It does so by including indicators such as the cost of living and quality of life in a particular economy. Specifically, it examines the ability of a country to attract highly skilled foreign labour. In addition, it assesses the way enterprises prioritize the attraction and retention of talent. Another component of this factor evaluates the impact of brain drain on the competitiveness of countries. It also takes into account the level of worker motivation. Salary and taxation levels are important for an economy to be able to maintain an effective flow of talent. The appeal factor thus considers remuneration at the management and services professions levels and personal income tax rates. This factor also incorporates measures of personal security and the protection of private property rights because they play a key role in increasing the attractiveness of a particular economy. The success of the investment in and development of talent and the ability to attract and retain talent is reflected in the availability of skills and competencies to sustain an economy’s talent pool. The readiness factor looks at the context of the talent pool. It considers the growth of the labour force and the quality of the skills available. It also takes into consideration the experience and competencies of the existing senior managers’ pool. In addition, the readiness factor focuses on the ability of the educational system to meet the talent needs of enterprises. It examines the way in which the educational system fulfils the talent demands of the economy, the ability of higher education to meet that demand and the language skills available. Finally, it considers the mobility of students (inbound) and educational assessment (PISA) (IMD WTR 2015:6).

It is important to note that such ranking must be always judged and evaluated with meticulous care without neglecting two things. First, quantitative data are complemented with subjective judgements captured by the conducted survey (Executive Survey).7 Soft data (opinions from the survey) are dominating over hard data (statistics) both in case of the appeal and the readiness factors gathered from the executive survey conducted. It is well-known from psychological studies that the 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 uncertainty-generating or dampening impacts. By uncertainty we mean the Knightian definition For example, IMD WTR does not take into account in all cases 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). 7

(unknown risk) (Knight, 1921). Uncertainty can be associated with a decision’s exact outcome as well as with the issue of what shall a socio-economic actor (e.g. firm, government) 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. 8 The room for unfolding talent in a society inevitably relies on the trust infrastructure since knowledge sharing is promoted more in a higher trust base environment.9 Second, this is a relative ranking, a certain movement in case of a country does not necessarily caused by developments within that country but other countries have improved or declined in a greater or lesser extent. Box 1. Dominating soft factors in the Appeal and Readiness dimensions Investment and development factor (Share of subjective opinions: 37.5%): - Total public expenditure on education as percentage of GDP (STATISTICS); - Total public expenditure on education per pupil as percentage of GDP per capita (STATISTICS); - Ratio of students to teaching staff, primary school (STATISTICS); - Ratio of students to teaching staff, secondary school (STATISTICS); - Apprenticeship is sufficiently implemented (SOFT DATA); - Employee training is a high priority in companies (SOFT DATA); - Percentage of total labour force (STATISTICS); - Health infrastructure meets the needs of society (SOFT DATA). Appeal factor (Share of subjective opinions: 60%): - Cost of living (STATISTICS); - Attracting and retaining talents is a priority in companies (SOFT DATA); - Worker motivation (SOFT DATA); - Brain drain (SOFT DATA); - Quality of life (SOFT DATA); - Foreign skilled people (SOFT DATA); - Remuneration in services professions (STATISTICS); - Remuneration of management (STATISTICS); - Effective personal income tax rate (STATISTICS); - Personal security and private property rights (SOFT DATA). Readiness factor (Share of subjective opinions: 75%): - Labour force growth (STATISTICS); - Skilled labour (SOFT DATA); - Finance skills (SOFT DATA); - International experience (SOFT DATA); - Competent senior managers (SOFT DATA); - Educational system (SOFT DATA); - Science in schools (SOFT DATA); - University education (SOFT DATA); - Management education (SOFT DATA); - Language skills (SOFT DATA); - Student mobility inbound (STATISTICS); - Educational assessment – PISA (STATISTICS). Source: own compilation based on IMD WTR 2015.

8 The declining tendency in trust can be captured in many ways, for example, the trajectory of the number of emigrated young

and highly skilled career starters can be seen as a good proxy for that purpose. In case of Hungary, almost 400,000 young career starters left the country between 2010 and 2013 (See: Central Statistical Office of Hungary). 9 Trusting relationship is a hotbed for a more intensive sharing of useful and relevant knowledge. Novelty or new combination of old and well-known thoughts is expected to come when talent collaborate in the trust-base creative cultural environment. So, trust promotes social and emotional ties on the one hand and promotes professional collaboration on the other hand, both facilitators of knowledge sharing (Chowdhury, 2005).

III. RESULTS OF THE WORLD TALENT REPORT 2015 In the 2015 edition of the World Talent Report, Switzerland leads the way in meeting corporate needs through developing, attracting and retaining talent. The report ranks Denmark second and Luxembourg third, with Norway, the Netherlands, Finland, Germany, Canada, Belgium and Singapore completing the top 10. Several major economies fare less impressively, with the US languishing in 14th place, the UK 21st, France 27th and China Mainland far behind in the list (40th position). Table 1. World Talent Report 2015 – Changes in the ranking 2015 Country

2014 Change from 2014

Switzerland

Denmark

Luxembourg

+10

2015 Country

2014 Change from 2014

→

Korea Rep.

↗

→

Poland

↗

Estonia

-3

↘

Thailand

→

Norway

↗

Netherlands

↗

Greece

↗

Finland

-2

↘

Kazakhstan

-4

↘

Jordan

↗

Slovenia

+11

↗

Germany

-4

Canada

→

Belgium

↗

Spain

↗

Singapore

↗

China Mainland

↗

↘

Indonesia

-16

↘

Italy

↗

Sweden

-2

China Hong Kong

↗

Australia

↗

Chile

↗

USA

-2

↘

Philippines

-3

↘

Russia

↗

Turkey

-11

↘

Malaysia

-10

Ireland

-10

↘

Iceland

-3

↘

Slovak Republic

-1

↘

New Zealand

↗

Romania

-10

↘

Mexico

↗

Colombia

↗

Austria

-8

UAE

-5

↘

United Kingdom

-1

↘

South Africa

↗

Israel

-4

↘

India

-4

↘

↗

Argentina

↗

Mongolia

N/A

Taiwan

Lithuania

↗

Portugal

↗

Ukraine

-24

↘

Japan

↗

Hungary

-5

↘

Brazil

-5

↘

Croatia

→

France

-3

Latvia

-5

↘

Qatar

-7

↘

Peru

-2

↘

Czech Republic

↗

Venezuela

-1

↘

Bulgaria

-1

↘

Source: IMD WTR 2015

Brazil slips to 57th place while other Latin American economies also struggled, with Chile 43rd, Mexico 49th, Colombia 50th, Argentina 53rd, Peru 59th and Venezuela 60th. Although Mexico, Chile, Argentina and Colombia have slightly improved their positions this year, all Latin American countries in the study place in the bottom third of the ranking. Interestingly, Hungary is also at the bottom with its 56th position indicating that something deeper is amiss. Singapore claims 10th spot while other Asian economies enjoy mixed fortunes, with China Hong Kong rising from 21st to 12th. Similarly, Korea Rep. moves from the 40th to 31st position and Japan slightly improves from 28th to 26th. By contrast, Malaysia, which took fifth position last year, falls out of the top 10 and Indonesia ranks in the 41st place, both countries experiencing a decline in a number of relevant performance indicators. Philippines drops three places to the 44th rank while Thailand remains at the 34th spot. Europe emerges as a major source of, and a magnet for, business talent with eight countries in the top 10, followed by Sweden 11th, Ireland 16th and Iceland 17th. The report indicates that the key attribute among all the countries that rank highly is agility. This is shown in their capacity to adopt and shape policies that preserve their talent pipeline, which in turn makes them what the report describes as “talent-competitive.” These countries have consistently achieved a positive balance between encouraging local talent and tapping into top talent from other countries. IV. HUNGARY IN THE IMD WTR 2015 4.1 The bird’s eye view on Hungary Hungary has been ranked at the 56th place in the IMD WTR 2015 by showing a 5-places relative decline as compared to the 51st position in the previous in 2014. From a regional perspective, Hungary’s talent competitiveness has worsened the most among Visegrád countries (henceforward V4) since 2005 (Czech Republic, Hungary, Poland, and Slovakia) (Chart 1). The biggest decline was observable after 2012. Let us add immediately 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, simply because this type of process is an end result of longer term perceptions that manifested in negative opinions in the survey conducted. Chart 1. Ranking history of V4 countries in the IMD WTR (2005-2015) 0

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

10 20 30 40 50 60 Czech Republic

Hungary

Poland

Slovakia

Source: Own compilation based on IMD WTR 2015.

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) (Chart 2). With respect to appeal and readiness factors, Hungary can be regarded as a laggard even among V4 countries (Chart 3-4). In terms of appeal, Hungary is ranked at the bottom in the overall list, only Bulgaria and Venezuela had worse values. Chart 2. Investment and development factor in V4 countries Czech Republic

Hungary

Poland

Slovakia

0 10 20 30 40 50 2011

2015

Source: Own compilation based on IMD WTR 2015.

Chart 3. Appeal factor in V4 countries Czech Republic

Hungary

Poland

Slovakia

0 10 20 30 40 50 60 70 2011

2015

Source: Own compilation based on IMD WTR 2015.

Chart 4. Readiness factor in V4 countries Czech Republic

Hungary

Poland

Slovakia

0 10 20 30 40 50 60 2011

2015

Source: Own compilation based on IMD WTR 2015.

By taking a mere glimpse into the sub-indicators, at least the following smorgasbord of varied 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 is approximately at the average of the developed countries. (V4 positions in 2015: Czech Republic (25); Poland (23); Slovakia (47)). Hungaryâ&#x20AC;&#x2122;s expenditure is similar to that of Ireland. Note that the sheer volume of the total public expenditure on education as percentage of GDP per se does not automatically determine better positions in the rankings, however. For example, Singapore (56), Qatar (55) are at the end of the ranking in terms of this indicator, but these countries perform much better in the overall ranking with the places of 10th and 29th, respectfully. - in terms of public expenditure on education per pupil (secondary), Hungary has been at a relatively good position since it was 22nd in 2014, while it ended at the 32nd place in 2015. Such expenditure in Hungary exceeded that of Israel both in 2014 and 2015, still, Israel has been well above 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 of its 6th position after Luxembourg, Greece, Qatar, Iceland and Norway. - in terms of the pupil-teacher ratio (secondary education), Hungary was 14th in 2014, then it slipped to 22 in 2015. In this respect, the Czech Republic (18) and Poland (14) had better performance 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), the country 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). Behind the surface of this result, it seems that competent leadership/management lacks of relevant knowledge and commitment, not to mention their financial capacity to initiate employee trainings on the one hand, on the other hand the under motivation of workers (57) is another factor that stifles such trainings. - in terms of attracting and retaining talents, except the Czech Republic (41), other V4 countries seem to be ranked in a group of low performers (Hungary (57), Poland (61, Slovakia (58)). - 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 has changed since 2014 simply because the expansion of the Hungarian labour force has started to be based on real private sector employment rather than being driven by public work program. Thus, Hungaryâ&#x20AC;&#x2122;s position improved from the 39 th position of 2014 to the 13th place in 2015. Still, 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, they are considered as not readily available in Hungary (60) according to the opinions of executives, while they are better reached and utilised in the Czech 9

Republic (34), in Poland (20), and in Slovakia (49). The senior managers’ international experience in Hungary is, all the more, relatively low (Czech Republic (20); Hungary (43); Poland (17); and Slovakia (40)). In connection to this dimension, the 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 management education. - in terms of language skills, which is a glue of effective collaboration, has been considered as rather disquietingly problematic in case of Hungary (58). For comparison, the Czech Republic (32), Poland (17), and Slovakia (30) perform better. In sum, one can lead to the conclusion that Hungary has been losing ground in terms of talent competitiveness. Furthermore, the big picture is that, except Poland, V4 countries’ talent competitiveness has been decreasing since 2005.10 This issue indicates that something deeper is amiss impeding the healthy knowledge creation and knowledge transfer through enhancing the talent competitiveness. In an effort to get a better understanding over this issue we shortly address the question of what is the situation with innovation in the higher education systems of Central and Eastern European (CEE) EU member states, including V4 countries. Then we turn to the Hungarian case and elaborate our thinking further on the talent-endowment issue. 4.2 A broader view on Hungary’s talent competitiveness 4.2.1 The Hungarian reality Talent-endowment is more likely to be associated with a more pro-active, risk-taker entrepreneurial mind-set that can open the floodgates of innovation, ultimately that of longer term total factor productivity. 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, 2015:1132). It per se indicates that the innovation ecosystem of Hungary either lacks talent or at least utilise the talentbase in a rather inefficient way.11 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. The education system is responsible for In 2010, a comprehensive research revealed that the Hungarian higher education system and the academia were featured with the followings even after 20 years of the regime change: 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 of economic relevance.12 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 (zero-close potential economic growth, depressed investment activity, increasing poverty, heightening impoverishment, etc.). These are not conducive processes to breed and exploit talents.13

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 program were dedicated to attracting emigrated Polish people back into the 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. 11 Kónya (2015:1121) recalibrated the total factor productivity (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. 12 See: Polónyi (2010). 13 For example, according to Eurostat, 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. See: http://ec.europa.eu/eurostat/web/income-and-livingconditions/data/database Accessed on: 22.11.2015 10

Importantly, 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, and it education component in particular.14 (Chart 5). Chart 5. Education component of the Historical Index of Human Development (1870-2007) Western Europe

Central and Eastern Europe

OECD

0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 2007

2005

2000

1995

1990

1985

1980

1975

1970

1965

1960

1955

1950

1938

1933

1929

1925

1913

1900

1890

1880

1870

Note: The education component measures literary 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. Source: Historical Index of Human Development.

Although the education component for Hungary within the cited Historical Index of Human Development suggests that the Hungarian education converged to that of the OECD average up to 1965, then the convergence lost its élan (Chart 6); this component does not adequately capture the performance since it measures only literacy and enrolment. Historically, Hungary has been always at a position like in the IMD WTR 2015. Against the popular belief, the Hungarian education has never been a world class one, it has not even been a strong medium performer, either. 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 that can unfold talents – has been always rather polarised. 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 not necessarily the education per se is worse than in other countries but the variance of the PISA results is mainly higher based on 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 poor vocational school performance is mainly given because of the selective nature of the system: the students getting in vocational schools have inherently weak competencies being relevant for the purpose of PISA surveys. According to the PISA 2012 survey, 15-year-olds’ problem solving ability was the worst in Hungary among V4 countries (Chart 7) and it is in the last third of the countries listed.15

14 The Historical Index of Human Development (HIHD) is inspired in and adapts from a long run perspective The United Nations

Development Programme’s Human Development Index (HDI) (UNDP, 2014). A detailed explanation of the concept, computation procedures, and analysis of the results is provided in Prados de la Escosura (2015). 15 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

Chart 6. Education component of the Historical Index of Human Development (1850-2007) 1 0,8 0,6 0,4 0,2

Czech Republic

Hungary

Poland

Slovakia

Western Europe

Central and Eastern Europe

2007

2005

2000

1995

1990

1985

1980

1975

1970

1965

1960

1955

1950

1938

1933

1929

1925

1913

1900

1890

1880

1870

1860

1850

OECD Note: Data for the V4 countries are available as follows: Czech Republic (1990-2007), Hungary (1870-2007), Poland (18702007), Slovakia (1990-2007). Source: The Historical Index of Human Development, Prados de la Escosura (2015).

Chart 7. 15-year-olds’ problem solving proficiency Percentage of top performers in problem solving and at least one other

Level 5

Level 6

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… 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

Source: OECD, PISA 2012, Figure V. 2.7

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).

Graduated students from the vocational schools predominantly have low general literacy and they are the labour force for the Hungarian industry and services. It is hardly by chance that the executives from Hungary expressed that they almost always have to pay attention to further training and education.16 Higher education institutions are also weak, only a few universities are among the top 500-600 at the world ranking.17 Hungarian universities are even among the last ones among the Eastern European universities.18 One of the consequences of this is the relatively low share of adult population with advanced education. In 2013, that share was 19.4% within the total number of adult people which is slightly above that of the Moldovan 19%, and it was even below that of the Greek 22.3%!19 From a longer perspective, the share of people aged 30-34, who can be young innovative entrepreneurs, in Hungary with tertiary education has been converging to the EU28 average by reaching 89% in 2014; still it is well below that of the Polish 111% (Chart 8). As a corollary, the performance level of the Hungarian higher education is mainly at the bottom of the developed countries. These institutions are offering the Hungarian professional intellectual base.20 Chart 8. Share of people aged 30-34 with tertiary education (%, EU28=100) 120 100 80 60 40 20 0 2002

2003

2004

2005

2006

Czech Republic

2007

2008

Hungary

2009 Poland

2010

2011

2012

2013

2014

Slovakia

Source: Own compilation based on Eurostat data.

Interestingly, the Hungarian society seems to ignore these facts since the Hungarian parents want their child to be graduated from a university in a more vigorous way as compared to the German or Belgian parents (PISA 2012:22).

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. 17 Only four Hungarian universities were ranked in the QS World University Rankings 2014/2015, See: http://www.topuniversities.com/university-rankings/world-university-rankings/2014#sorting=rank+region=+country= +faculty=+stars=false+search Nonetheless, such rankings always have its distortions. These rankings are incapable of capturing the multiple the variety and size of universities, but their number. A substantial improvement can also be seen in case of a particular university when it â&#x20AC;&#x153;boughtâ&#x20AC;? 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. 18 See: QS EECA, or in Hungarian: http://hvg.hu/vilag/20141217_kelet_europai_egyetemi_rangsor/ Accessed on: 24.11.2015 19 See: ILOSTAT, Available: https://www.ilo.org/ilostat/faces/home/statisticaldata/ContryProfileId?_afrLoop= 26159967254892#%40%3F_afrLoop%3D26159967254892%26_adf.ctrl-state%3D9y4597a3m_171 Accessed on: 25.11.2015 20 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. 16

Nevertheless, the share of people aged 25-64 with tertiary education has been mainly stagnating only in Hungary among V4 countries between 2008 and 2014 (Chart 9). This graph pinpoints the halt of the human capital accumulation. Not to mention that this chart might also indicate that highly educated people have been more likely to go abroad and get job in this period. The major part of emigrants are typically active adults, people aged 25-34 (e.g. in 2013, their number was approx. 10,000).21 Chart 9. Share of people aged 25-64 with tertiary education (%, EU28=100) 100 90 80 70 60 50 40 30 20 10 0 2002

2003

2004

2005

2006

Czech Republic

2007

2008

Hungary

2009

2010

Poland

2011

2012

2013

2014

Slovakia

Source: Own compilation base on Eurostat data.

According to Eurostat statistics, the annual number of emigrated people from Hungary was between 2,500 and 3,100 in the period 1998-2003, then joining the EU accelerated the pace of emigration by reaching the annual number of 3,700-4,500 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 a yearly basis (more than 10,000 people emigrated per year between 2008 and 2010). In addition, as we mentioned earlier, the ruling cabinet of Hungary injected so much uncertainties over the present and the future that resulted in a more vehement and spectacular emigration trend from 2010 onwards. In 2010, the number of emigrant people was 13,365, while it more than doubled to 34,691 by 2013.22 The above considerations imply that history and legacy matters, especially in 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 we shed more lights on this issue. 4.2.2 Higher education, academia, and innovation in the CEE region In this section we argue that CEE member states are still coping with the heritage of past hampering the evolvement of a healthy innovative milieu in higher education and academia. This affects negatively the latitude of developing, attracting and keeping top talent by these knowledge creator and transfer institutions.

See: Eurostat, Emigration by five year age group, sex and citizenship, migr_emi1ctz database. Available: http://appsso.eurostat.ec.europa.eu/nui/submitViewTableAction.do Accessed on: 25.11.2015 22 See: http://appsso.eurostat.ec.europa.eu/nui/show.do, Emigration by age and sex, migr_emi2. Accessed on: 24.11.2015. 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 of 2008, that number was more than 131,000 even in 2013). http://appsso.eurostat.ec.europa.eu/nui/submitViewTableAction.do Immigration by age, sex and broad group of citizenship, migr_imm2ctz, Accessed on: 24.11.2015 21

Now 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 those of the competitiveness. Talents have a key role in this 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 European Union (EU) relates partly to the research performance in which the roles of academic sphere and higher education are crucial.23 Consequently, the 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 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 society regarding new technologies. This is what not has happened in the same vehement as in the main competitive partners of the EU like the US or South Korea by leading to 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 as well as Asia who 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, public-private 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 the issue of 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. From the supply-side of view, school attainment of the proportion of population ages 25-64 years in post-socialist CEE countries is substantially higher than in case of similarly developed countries. It reflects that the efficiency of education system is much worse comparing to traditionally marketoriented economies. From the demand-side of view, the epochal transformations took place in the 1990s calls 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 future’ in CEE countries. One of the fundamental leitmotifs behind the collapse of the 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 been 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 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. 23

extent, induced by the organisational, operational and managerial features of academic sphere. The structure and the motivation regime of the academy has not changed much and the formal (administrative) academic performances as well as the places in the hierarchy are dominating the real scientific performances. Higher education system, especially state universities in post-socialist countries are mainly selfmanaging 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. Government 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. As a consequence, organisations managed by non-market coordination are tend to be 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 experiments 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 system that affects negatively the decentralised initiations, because upper level representatives of the organisation incline to exercise control over the knowledge emerging in low level in order to benefit from it. Ambitious amount of reward for those who explicitly carry out innovations is principally outstanding. The employment system promises salient 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 scrolls easily obstacles towards the healthy competition. The career model narrows the latitude of opportunities for providing wide range of experiments, because the burdens on employees are the greatest when the intellectual conditions would be the best. As regards the flexibility of finance, the sources are planned on governmental instead of institutional level. It obviously questions that whether the sources inflowing to lower levels of organisations are sufficient. As a corollary, 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. STP and innovation policymakers should more vigorously take into consideration the repercussion of the industrial restructuring 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 paradigm 24 (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 basis 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 hightech 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 were not captured by the innovation policy adequately which neglected that the structural changes resulted in specialisation in lower end of value chains. In

On new techno-economic paradigm, see Perez (2009).

addition, this type of internal configuration did not provide a coercive power to bolster talent utilisation and education at a more professional quality level. Even the Europeanization of innovation policy in CEE countries, especially the availability to EU structural funds, had negative impact on innovation policy. There were not enough administrative capacity 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 arouse 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 coordination-ready 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 make enable both the unemployed and employed people to have better opportunity to maintain and upgrade their obtained skills. The ability of people to learn, apply and utilise new knowledge bears the torch of innovation and overall the human well-being at present and in the future alike. V. CONCLUDING REMARKS IMD World Talent Report 2015 is an alarming bell warning us that Hungary has been on a 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 happened or not happened 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 act to bridge the gap between well-endowed and developing and lagging behind education institutions that are lagging deeply behind. 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. Education system is an important but not the only one element in the innovation ecosystem of Hungary in which talents can be sparked or even stifle under some circumstances (e.g. increasing uncertainties because of the spectacular deterioration of formal institutions, and weakening checks and balances in the democratic system). This was documented in our forthcoming paper (Kovács, 2016). In that study, we illustrate that the ruling cabinet of Hungary has systematically broken down the quality of formal institutions in the aftermath of 2010.25 An autocratic regime has emerged (Kornai, 2015) pervaded by more nationalism and more macroeconomic populism. What is more, expenditures on education in Hungary was significantly decreased rather than increased being in the diametrical opposition of what happens in the advanced world.26 In an institutionally weak environment, talent’s 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.

This was also sensitively presented by Muraközy (ed.) (2012).

This argument was also confirmed by the latest OECD issue, Education at a Glance 2015, see: OECD (2015). 17

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