Education and Unemployment in European Union ... - ScienceDirect

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ScienceDirect Procedia - Social and Behavioral Sciences 213 (2015) 211 – 216

20th International Scientific Conference Economics and Management - 2015 (ICEM-2015)

Education and unemployment in European Union economic cycles Vytautas Snieskaa, *, Gitana Valodkieneb, Asta Daunorienec, Aura Draksaited a, b, c, d

Kaunas University of Technology, K. Donelaicio str. 73, Kaunas LT-44239, Lithuania

Abstract Dominating in scientific literature position is that the level of education has direct influence to the unemployment level and this influence is as high as up to five times lower unemployment rate for professional degree holders than the workers having no high school diploma. The EU statistics shows much weaker interaction between these two variables. The objectives of the paper are to assess influence of education level to the employment level dynamics in different stages of EU economic cycles and to reveal factors, influencing difference of the correlation of these two economic indicators in separate groups of EU countries. The findings may be used for the decision making in higher education systems development based on the efficiency criterion, which is directly and indirectly coherent to the factors influencing the unemployment levels and employment creation, evaluating specific for the EU countries factors. © 2015 2015The TheAuthors. Authors.Published Published Elsevier © by by Elsevier Ltd.Ltd. This is an open access article under the CC BY-NC-ND license Peer-review under responsibility of Kaunas University of Technology, School of Economics and Business. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of Kaunas University of Technology, School of Economics and Business Keywords: Education; Economic cycles; European Union; Employment; Unemployment.

Introduction The brief look at the scientific discussions about the possibility to enhance the chances to avoid being unemployed gives the impression that the position based on the assumption that the education level significantly increases the employment level prevail. The analysis of recent data shows that in the after crisis period from 2008 until now the importance of the education level for being employed is not as straightforward as it looks like.

* Corresponding author. Tel.: +370-37-300576. E-mail address: [email protected]

1877-0428 © 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of Kaunas University of Technology, School of Economics and Business doi:10.1016/j.sbspro.2015.11.428

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Vytautas Snieska et al. / Procedia - Social and Behavioral Sciences 213 (2015) 211 – 216

The research questions are three. The first – what are the main groups of theories explaining the interaction between the education level and the unemployment level? The second – what factors may influence the interaction between the education level and the unemployment level? The third – what factors determine the differences of the influence of the education level on the unemployment level in separate groups of EU countries in relation to different stages of economic cycles? The research purpose of the paper is to assess influence of education level to the employment level dynamics in different stages of EU economic cycles and to reveal factors, influencing difference of correlation of these two economic indicators in separate groups of EU countries. Methodology. The analysis of influence of education level on the unemployment level is carried on by means of statistical processing of primary and secondary data and constructing an applying model of interactions between the education level and the employment level in some groups of EU countries. Comparative and logical research of scientific literature, analysis, deduction and other methods are applied. 1. Interaction of education and unemployment level Biagi & Lucifora (2008) found that “changes in the education structure show a negative effect on the unemployment of the more educated. Labor market institutions also influence unemployment rates in different ways. Employment protection for regular workers increases unemployment rates, while temporary employment provisions reduce it. Unemployment benefits are found to have a displacement effect on unemployment, while corporatism of wage bargaining improves employment performance” (Biagi & Lucifora, 2008). Being absolutely right about most of the listed factors influencing unemployment level the authors didn’t explained how the education structure shows a negative effect on the unemployment of higher educated population. We found that this factor often may increase the unemployment of the more educated if there is a significant mismatch between the structure of education and that of the employment. From that point of view interesting findings were received from China where “China's expansion policy has sharply increased the unemployment rate among young college graduates, and that the unemployment rate for college graduates increases more in non-coastal (especially central) regions than in large coastal cities” (Li, Whalley & Xing, 2014). Pluemper & Schneider (2007) argue that governments do use higher education for manipulation of opinion on the unemployment level by advertising their policy for the increase of enrolment during times of economic crises and by using the education policy for the diminishing of the unemployment level (Pluemper & Schneider, 2007). The question which remains unanswered remains – how in such situation to find new employment possibilities for high educated? Clark (2011) argues that a subsidy to continue in education might be expected to increase enrolment but possibly resources currently devoted to increasing enrolment in full-time education may be more fruitfully spent improving and expanding the range of work based training options open to young people (Clark, 2011). Special group of population are minorities arrived from less-developed countries normally having lower education, poorer access to the labor market. Disadvantages are most visible in test results in schools (Heath, Rothon & Kilpi, 2008). Similar attitude on the minorities role in unemployment express other authors pointing out, that graduate level ethnic employment penalties remain important to the employment possibilities of minority graduates (Rafferty 2012). From the other side it is argued that in the poorer region may be found both higher unemployment rates and lower wages and migrants to the wealthy region are strangely skilled. “The brain drain from the poor to the rich region is accompanied by stronger incentives to acquire skills even for immobile workers. Regional shocks tend to affect both regions in a symmetric fashion, and skill-biased technological change reduces wages of the unskilled. Both education and migration decisions are distorted by a uniform unemployment compensation, which justifies a corrective subsidization” (Eggert, Krieger & Meier, 2010). A research provided on Turkish economy has showed that the increase of the level of education is one of the factors which raise the unemployment rate in Turkey in the long-run and that “there is a bi-directional causality between higher education and unemployment in Turkish economy. According to the causality test results, it seems that unemployment is a cause and a result of higher education in Turkey…we can conclude that unemployment in Turkey increases the demand for using higher education as a tool for the sake of solving the problems of the labor


market in the short-run which in turn creates a greater unemployment problem in the long-run” (Erdem, & Tugcu, 2012). In situation of “caeteris paribus” the level of unemployment of high skilled will depend on the rigidity of real wage. In high rigidity of real wage conditions an increase in quantity of high educated workers in the economy may wash out unskilled workers so increasing the unemployment level of the less educated. The consequence of this will be increasing returns to education (Stpaul, 1994). To investigate how changes in youth labor market performance can influence new EU member states future economic and social development is possible only taking account of the current conditions (Dimian, 2011). One of factors what directly influences the labor mobility of educated workers is gender. Men are more mobile when changing jobs and women more often leave employment positions (Theodossiou & Zangelidis, 2009). The question how the structure of higher education system and labor market policies influence the risk of unemployment of an individual with higher education was analyzed in 26 European countries. “Particular attention was paid to the effects of the country-level characteristics on the labor-market performance of graduates of different fields of study” (Tarvid & Univ, 2011). Very interesting results are from the analysis of interaction between labor market and shocks of wages and employment in different education groups. The rate of the reaction of labor supply to the increase or the decline of wages and employment in separate low unemployment groups defines the fluctuations dynamics. Sometimes it may take from 5 to10 years because of rather long study span. That is why when searching for the reasons of unemployment dynamics the comparisons of the dynamics of groups’ size is necessary to perform. High cost of training a given higher educated worker—for the less educated should reduce wages and raise quits at a given level of unemployment and benefits. This causes the natural rate to be higher for the less educated (Francesconi, et.al, 2000). In Spain, the 2008 financial crisis has sharply affected unemployment and forced the Spanish government urgently shift to austerity what squeezed possibilities to get education. The combination of lower wages and lower job opportunities together with raising taxes has plunged income hardly (Guardiola & Guillen-Royo, 2015). From the other hand, if the labor market is dynamic it is important for the employer to increase the ability to adjust to employment shocks. That is why according to some estimates “graduating from high school increases the probability of re-employment by around 40 percentage points” (Riddell & Song, 2011). Specifically, high unemployment rates prolong the time needed to find a job, whereas low unemployment rates make the transition shorter (Salas-Velasco, 2007). The global economic recession in many countries has coincided with the end of expansion in higher education and this has created overproduction of people with higher education and growing competition in labor market. Numerous governments in many countries used to manipulate expansion of higher education as a method for hiding failure of their policies aimed at the increase of international competitiveness of their economies. But from the other hand “during economic downturns, the government should increase its higher education investment rather than shifting funds from the higher education budget to other public sectors” (Wu, 2011). Often are a "push" and "pull" (business increases or reduces unemployment) effects and their influence on the economy depend upon the business cycles (Startiene & Remeikiene, 2009). Structural unemployment may be influenced by applying such measures as labor education, change of unemployment benefits, change of the labor market flexibility, by affecting the bargaining power of labor unions, etc. (Marjanovic & Mihajlovic, 2014). Higher education in Europe is still oriented to one country needs and this determines huge differences in the structure of education between European countries. Higher education in Europe is by the graduate’s structure heterogeneous in yet heterogeneous but developing toward homogenous after removing the borders between the countries EU internal market. This is the main reason of huge differences between the EU countries by the influence of the education level and also by the influence of the specialty on the unemployment level. These cross countries differences on the significance of education level on the prospects of the employment may also be explained by the level of labor market stratification – that is, transition to the labor market should be more successful in countries where stratification is higher and less successful in countries where labor stratification is lower. Some researchers have discovered stronger stratification and specificity in Northern continental European countries and found that the risk of short term unemployment is generally higher in (less stratified) Southern European countries (Nunez & Livanos, 2010).

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The main engine of unemployment dynamics is macroeconomic cycle. Fig. 1 shows that the general unemployment level in the US and in EU have synchronously reached peak at about 10% at the end of the 2009. The US after the implementation of successful macroeconomic measures and microeconomic stimulus gradually has diminished the level of unemployment to about 5%. EU with its less efficient central banking system aimed at achieving stable Euro with very limited capabilities to stimulate the aggregate demand in EU in after crisis period had to suffer further increase of the unemployment growth up to 12% in the middle of the 2013 and a very modest progress later on.

Fig. 1. Unemployment rates EU-28, EA-19, US and Japan, seasonally adjusted, January 2000 - March 2015 (%). (Eurostat. Unemployment statistics, 2015)

Unemployment in ISCED Levels 0-2 and 3-4 education EU, GR, IT, ES

Unemployment, %

40,0 35,0

Euro area 0-2

30,0

Euro area 3-4

25,0

Greece 0-2

20,0

Greece 3-4

15,0

Italy 0-2

10,0

Italy 3-4

5,0

Spain 0-2 Spain 3-4

0,0 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Fig. 2. Unemployment in EU, Greece, Italy and Spain population possessing ISCED level 0-2 or level 3-4 education.

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For the analysis of the influence of education on the level of unemployment we have analyzed data from two groups of countries – one group – three rather seriously damaged by the 2008 crisis Southern European countries – Greece, Italy and Spain and the other group – three Baltic countries – Lithuania, Latvia and Estonia. Data for the analysis is selected using two the most numerous according to ISCED education groups - level 0-2 and level 3-4. As we see from Fig. 2 higher education in Greece gives very small advantage in perspectives to be employed. Much greater difference in corresponding unemployment levels is in Italy and the greatest is observed in Spain. Our data confirms that the smallest labor market stratification level in this group of countries is in Greece and the highest is in Spain. One of the severest among the EU countries austerity policies implemented by Greece also has played a significant role in pushing up the unemployment level up to 30% in both education groups. In Spain the labor market was severely hit by the real estate bubble and level 0-2 education group unemployment has reached even 35%, but the difference from the more educated was much higher than in Greece. Unemployment in ISCED Levels 0-2 and 3-4 education EU, EE, LV, LT

Unemployment, %

50,0

Estonia 0-2

40,0

Estonia 3-4

30,0

Euro area 0-2

20,0

Euro area 3-4 Latvia 0-2

10,0

Latvia 3-4 0,0 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Lithuania 0-2

Fig. 3. Unemployment in EU, Estonia, Latvia, and Lithuania population possessing ISCED level 0-2 or level 3-4 education.

As we see from Fig. 3 higher education in the Baltic countries with rather stratified economies demonstrate obvious advantages in employment for population with the level 3-4 education. Particularly high this difference is in Lithuania where the labor market was maybe severest in the EU hit by the real estate bubble. In this country level 02 education group unemployment has reached even 40% in 2010 comparing with only 22% for the level 3-4 education group. Similar, though not as severe situation was in this year in Latvia and Estonia. Having in mind that in the Baltic countries in the period of the extreme growth from 2005 till 2008 were insignificant differences in the employment levels of separate groups of education, the reason of the growing advantage of the more educated is hidden in the higher inclination to emigrate inherent for more educated people. From 2002 till 2014 year 483 thousands of the population from Lithuania has emigrated what equals to 37% of the total amount of the employment in 2014. Conclusions The education level does have significant influence to the employment level in most EU countries, but the differences of this influence vary crucially among the countries due to some historical reasons, labor market structural differences and unemployment insurance system peculiarities. Global economic cycles influence on EU labor market has multidimensional effects due to the specific influence of economic cycles to economic structure almost each enterprise and particularly small and middle enterprises in financial crunch face the basic problem – the lack of circulating assets and investments for innovations development, what negatively affects the employment of highly skilled workers. Contraction of employment in the crisis period has hit the quantity of often unique working places for highly skilled employees. This problem became much more evident when economy was in recession. For the Baltic countries huge level of emigration has helped to maintain better employment prospects for higher

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educated population especially in the period soon after the crisis. The findings explaining interactions between the education level and the employment level in some groups of EU countries and the dynamics of this process in economic cycle has been developed. The results are especially important for the economic and education policy shaping. The empirical findings are useful for the reshaping of education systems in the EU countries using the efficiency criterion, based on the factors influencing the unemployment level and employment creation, evaluating features of the EU countries labor market in economic cycles. Acknowledgements This research is funded by the grant (No. IEP-01/2012) from the Research Council of Lithuania. References Biagi, F., & Lucifora, C. (2008). Demographic and education effects on unemployment in Europe. Labor Economics, 15(5), 1076-1101. doi: 10.1016/j.labeco.2007.09.006 Clark, D. (2011). Do Recessions Keep Students in School? The Impact of Youth Unemployment on Enrolment in Post-compulsory Education in England. Economica, 78(311), 523-545. doi: 10.1111/j.1468-0335.2009.00824.x Dimian, G. (2011). Education and youth unemployment in 10 new eu member states. Efficiency and Responsibility in Education 2011 Eggert, W., Krieger, T., & Meier, V. (2010). Education, unemployment and migration. Journal of Public Economics, 94(5-6), 354-362. doi: 10.1016/j.jpubeco.2010.01.005 Erdem, E., & Tugcu, C. T. (2012). Higher Education and Unemployment: a cointegration and causality analysis of the case of Turkey. European Journal of Education, 47(2), 299-309. doi: 10.1111/j.1465-3435.2012.01526.x Eurostat. Unemployment statistics (2015) http://ec.europa.eu/eurostat/statistics-explained/index.php/Unemployment_statistics Francesconi, M., Orszag, J. M., Phelps, E. S., & Zoega, G. (2000). Education and the natural rate of unemployment. Oxford Economic PapersNew Series, 52(1), 204-223. doi: 10.1093/oep/52.1.204 Guardiola, J., & Guillen-Royo, M. (2015). Income, Unemployment, Higher Education and Wellbeing in Times of Economic Crisis: Evidence from Granada (Spain). Social Indicators Research, 120(2), 395-409. doi: 10.1007/s11205-014-0598-6 Heath, A. F., Rothon, C., & Kilpi, E. (2008). The second generation in Western Europe: Education, unemployment, and occupational attainment Annual Review of Sociology, 34, 211-235. Li, S., Whalley, J., & Xing, C. (2014). China's higher education expansion and unemployment of college graduates. China Economic Review, 30, 567-582. doi: 10.1016/j.chieco.2013.08.002 Marjanovic, G., & Mihajlovic, V. (2014). Analysis of Hysteresis in Unemployment Rates with Structural Breaks: the Case of Selected European Countries. Inzinerine Ekonomika-Engineering Economics, 25(4), 378-386. doi: 10.5755/j01.ee.25.4.5263 Nunez, I., & Livanos, I. (2010). Higher education and unemployment in Europe: an analysis of the academic subject and national effects. Higher Education, 59(4), 475-487. doi: 10.1007/s10734-009-9260-7 Pluemper, T., & Schneider, C. J. (2007). Too much to die, too little to live: unemployment, higher education policies and university budgets in Germany. Journal of European Public Policy, 14(4), 631-653. doi: 10.1080/13501760701314458 Rafferty, A. (2012). Ethnic penalties in graduate level over-education, unemployment and wages: evidence from Britain. Work Employment and Society, 26(6), 987-1006. doi: 10.1177/0950017012458021 Riddell, W. C., & Song, X. (2011). The impact of education on unemployment incidence and re-employment success: Evidence from the US labor market. Labor Economics, 18(4), 453-463. doi: 10.1016/j.labeco.2011.01.003 Salas-Velasco, M. (2007). Graduates on the labor market: Formal and informal post-school training investments. Higher Education, 54(2), 227245. doi: 10.1007/s10734-005-3092-x Startiene, G., & Remeikiene, R. (2009). The Influence of Demographical Factors on the Interaction between Entrepreneurship and Unemployment. Inzinerine Ekonomika-Engineering Economics(4), 60-70. Stpaul, G. (1994). Unemployment, wage rigidity, and the returns to education. European Economic Review, 38(3-4), 535-543. Tarvid, A., & Univ, L. (2011). Field of higher education and unemployment risk in european countries. New Socio-Economic Challenges of Development in Europe 2010, 87-96. Theodossiou, I., & Zangelidis, A. (2009). Should I stay or should I go? The effect of gender, education and unemployment on labor market transitions. labor Economics, 16(5), 566-577. doi: 10.1016/j.labeco.2009.01.006 Wu, C.-C. (2011). High graduate unemployment rate and Taiwanese undergraduate education. International Journal of Educational Development, 31(3), 303-310. doi: 10.1016/j.ijedudev.2010.06.010