Keywords

5.1 Introduction

Getting a foothold in the labour market (LM) represents a significant shift in young adulthood – labour market entry process affects further careers and tends to relate closely to transitions in other life domains (Kieselbach et al. 2001). However, life course is not anymore a predetermined sequence of first leaving school and then entering work, but rather a series of different activities where youth is growingly exposed to the phases of unemployment or jobs with precarious contract conditions which call for a dynamic view. Previous literature, focusing mostly on school-to-work transition in the Western societies, has established that individual agency is shaped by various institutional factors (Breen 2005): (1) education system, which determines the link and the pathways between the education system and the labour market; (2) the employment systems (employment protection), which shape the contractual possibilities of the youth entering labour market; and (3) the employment policies, which define and shape the possibilities to (re-)enter labour market through various measures, programmes, subsidies, trainings or benefits targeted at youth.

The current chapter aims at providing a comprehensive review of the youth labour market issues specific to countries of Central and Eastern Europe (CEE) . The first part of the chapter presents an analytical framework how institutions frame the transitions outlining also transition regimes. Thereafter, it provides an overview of existing institutions relevant for youth labour markets and their variation across the CEE countries. In the second part, we offer a descriptive analysis of the microdata from the EU statistics on income and living conditions (EU-SILC ) datasets , both with time dynamics and in comparison with selected EU benchmark countries – Finland, Austria, the UK and Italy – representing different transition regimes. In particular, we focus on labour market transitions of youth with different educational resources.

5.2 Institutional Features Framing Youth Labour Market Transitions

5.2.1 Educational and Training Systems

Education is the central resource for young people entering the labour market (LM). The role of educational qualifications in job allocation process relates to country-specific institutional structure of education and training system. Most theories about cross-country variation in school-to-work transition assume some type of clustering of education and labour market systems (Allmendinger 1989; Marsden 1990; Shavit and Müller 1998). However, it has been also suggested that the existing classifications may be too crude to capture the complexity of the institutional arrangements of modern education systems. Moreover, it may be more informative to analyse specific education system characteristics (Bol and van der Werfhorst 2011, 2013; Müller and Gangl 2003). The most commonly used characteristics of the education system that are relevant for explaining youth LM entry are the type of stratification,Footnote 1 standardisationFootnote 2 and organisation of vocational training and institutional linkages (Allmendinger 1989; Shavit and Müller 1998; Levels et al. 2014). For example, the educational systems in the traditionally vocation-oriented Germany and Austria feature extensive vocational training through large-scale apprenticeship programmes (Müller and Gangl 2003). In general, if the educational system provides standardised qualifications with occupation-specific skills and the job matching is based mainly on qualifications, young people have easier time entering the LM (Müller 2005). However, youth without secondary education are especially disadvantaged in such countries. If most youth graduate with general secondary education and acquire further training in the workplace, then job matching is more related to experience. Thus, the difference in the labour market chances between those with and without secondary education becomes less pronounced once the low educated have managed to obtain the first work experience. As job matching can be most successful in systems with high vocational orientation, shorter work periods and therefore higher mobility of youth would be expected in educational and training systems providing mainly general skills. At tertiary level, the smaller the group of graduates, the better chances they face in the labour market. However, in the context of expansion of higher education, the labour market chances of graduates become more heterogeneous (Shavit et al. 2007).

5.2.2 Labour Market Regulations

While the education system affects youth transition process to LM by shaping the supply of labour in terms of skill levels of the entrants and the role of educational certificates in labour allocation process, the structure of the labour demand in the labour market is affected by the labour market regulation, such as employment protection legislation (EPL) . It sets the rules for processes of hiring and firing in any given country. The rigid EPL has been blamed as the main cause of youth labour market integration problems in Europe. For example, previous research has shown that stricter EPL tends to result in higher youth unemployment relative to that in adult population (Breen 2005; de Lange et al. 2014). However, vocational orientation of educational system may counterbalance this negative effect (Breen 2005; van der Velden and Wolbers 2003). Still, some research shows the lack of clear association between the youth labour market entry and the EPL (Müller and Gangl 2003; O’Higgins 2012), while others found that the association varies across educational groups. For example, in the study by Wolbers (2007), the EPL index has a significant positive association for upper secondary education level, whereas there is no effect for tertiary education level. This suggests that youth with different educational attainment might be affected differently by the institutional context. Confirming this, Gebel and Giesecke (2016) demonstrate that temporary contract deregulation increases the likelihood of temporary employment among youth but does not reduce the risk of unemployment risks for all educational groups. On the contrary, for low-educated young men, it increased the risk of unemployment.

5.2.3 Labour Market Policies

The institutional sphere , which relates most directly to cushioning the market effects, is the welfare state. The relation between the youth LM entry chances and the generosity of the unemployment benefits is not clear as youth is generally not eligible for the unemployment benefits due to their short work careers. However, active labour market (ALM) measures are claimed to play a positive role, especially for disadvantaged groups, in helping youth to get the foothold in the labour market (Card et al. 2015). A study by Russell and O’Connell (2001) demonstrates that the level of expenditure on active labour market policies has a strong positive effect on chances of getting a job for unemployed young people. Others have established that the introduction of fairly large-scale ALM programmes has affected the structure of the transition processes in many European countries due to the institutional lock-in effects (e.g. Ryan 2001), particularly among the less qualified and disadvantaged youth (Müller and Gangl 2003).

5.2.4 Labour Market Entry Regimes

For analytical purposes it is useful to distinguish different institutional dimensions affecting youth transitions; however, institutional setups form an interrelated ‘institutional package’. One starting point for youth transition regimes by Walther (2006) has been the model of welfare regimes (Esping-Andersen 1990) but apart from different structures of welfare also including structures of education systems and youth policies.

Walther (2006) has distinguished four clusters of transition systems: the universalistic regime in the Scandinavian countries is characterised by an extended welfare provision combined with an inclusive schooling system. The focus is on education and activation. The liberal regime in the Anglo-Saxon countries is characterised by an adaptive and versatile education and training system combined with open, easy access to employability accompanied with high risk and low access to welfare. The employment-centred regime in the continental countries has more selective and standardised educational and training frameworks. The focus is mostly on vocational training. Access to social assistance is selective. The familistic or subprotective regime in the Mediterranean countries is characterised by a nonselective educational system combined with low-standardised training schemes. Access to the labour market is challenging, with high rates of informal and precarious jobs. The role of the family in these countries is prominent, with high levels of dependency among youth.

The model is limited as it does not include Central and Eastern European (CEE) transformation societies which could either fit to existing regime types or in the development of new ones. Saar et al. (2008) conclude in their analysis that the attempt to classify institutional patterns in the CEE countries into different institutional regimes so far indicated the contradictions and inherent dissonance of institutional rules operating in the educational system and labour market. The CEE countries have tended to borrow models and practices from different types on institutional packages, creating a certain inconsistency of new institutional packages. Due to the variety and inconsistency of institutional systems, it is hard to predict the way these systems will shape the process of labour market entry.

5.3 The Role of Institutions in the CEE Countries

Educational institutions in the CEE countries to a varying degree combine some of the features from the socialist past with some of the new developments. Research has demonstrated that the earlier students are directed towards different tracks, the higher the diversity of their knowledge and competences later (Kogan et al. 2008) which translates into different labour market outcomes. A first serious decision, selection of gymnasium is taken in Hungary, the Czech Republic and Slovakia at the age of 10–11 (ibid), in the other CEE countries, first tracking takes place in age 14–15 (see Table 5.1). At the secondary level, there is availability of vocational/technical and general tracks in all CEE countries, but clear differences emerge. Some systems provide more places in general secondary schools, while others are more vocationally orientated. In the CEE countries that are geographically and historically closer to Germany or Austria, a vocationally oriented secondary education has maintained its dominance over a more general curriculum. In the Baltic countries, most pupils opt for general secondary education, whereas especially in the Czech Republic, but also in Slovenia, Poland vocational secondary education has high enrolment rates. Hungary used to have high enrolments into vocational secondary education till 2005, but it has decreased considerably. In terms of organisation of vocational education, the Czech Republic, Hungary and Slovenia have preserved or reintroduced the elements of enterprise-based apprentice training, whereas the Baltic states, Poland and Bulgaria have shifted to increasingly school-based vocational education (Kogan 2008: 30; Baranowska 2008: 276). The educational expansion is more prevalent in countries where general secondary education prevails. At least 40% of people aged 25–29 across all the Baltic states and Poland have tertiary education, which is above the average in the EU-28 (Rokicka et al. 2015: 21). Bulgaria differs from the above-mentioned countries. Its system of secondary education combines both general and vocational elements, whereas tertiary educational attainment lags behind the rest of the CEE countries and in Europe in general being at the same level as in Austria and Italy (ibid).

Table 5.1 Labour market characteristics of selected CEE and other EU countries, 2012–2014
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Specific features of the EPL aiming at protection of permanent workers against individual dismissalFootnote 3 do not allow drawing very clear country groups. Most of the CEE countries have introduced changes to the EPL after 2008 due to the last recession, which had led to an increased risk of dismissal of regular workers. Bulgaria, Romania, Hungary, Slovakia and Estonia have a weaker employment protection than the OECD average making it similar to the UK in 2013. A weaker EPL is usually associated with lower firing and hiring costs for employers, which in turn can promote youth LM mobility. In all the other CEE countries, Latvia, Lithuania, Poland and Slovenia, despite of a relative reduction in the protection, the EPL is still clearly stronger than the OECD average – at the same level as in Germany or Finland. The Czech Republic has not reformed its legislation during the last crisis and, therefore, has one of the toughest protective legislations towards regular workers in Europe, similar to Portugal. However, we have to note that in all CEE countries including the Czech Republic, trade union density is very low which makes it questionable if high protection in legislation translates to everyday reality as social structures supporting the voice of workers are weak.

While several Western European countries have opted for a partial deregulation lowering the protection of employees with temporary contracts, this has not been the case in the CEE countries. In general, since the introduction of temporary contracts, their regulation has been quite liberal, and most above-mentioned CEE countries have even increased the protection for temporary workers. Despite that, in all the CEE countries , with the exception of Estonia and Lithuania, temporary workers are on average less protected than in the OECD countries. However, most young workers in the region have permanent contracts. While on average 26% of young European employees held a fixed-term position in 2013, the corresponding number in Romania, Lithuania, Bulgaria, Ukraine, Latvia and Estonia was only around 10% and under 20% in the Slovak Republic, Hungary and the Czech Republic. The only exceptions are Slovenia and Croatia, where over 40% of the recent school leavers had a temporary job in 2013 (Rokicka et al. 2015: 53).

Labour market policies in the CEE countries receive a much smaller allocation of government spending as compared to the EU average both for passive and for active labour market measuresFootnote 4 making the CEE countries similar to the liberal UK or to Italy. For instance, around 0.37% of GDP in the Czech Republic and Slovenia is spent on ALMP, similar to Italy (0.36% of GDP) which is characteristed by lowe investments into the ALMPs (see Table 5.1). Baltic countries and Slovakia spend even less on the ALMPs (0.17–0.24%). PolandFootnote 5 and especially Hungary spend more – 0.49% and 0.86% of GDP, respectively, similar to Germany and Austria, but lagging behind the Northern Europe where more than 1% of GDP is invested into the ALMPs. However, these investments are not necessarily youth specific as Walther (2006) has pointed out. Coverage of ALMP for long-term youth unemployment has been assessed high in three of our reference countries: the UK, Finland and Austria (ibid). In contrast, in Bulgaria, Poland, Romania and Slovakia, the coverage is assessed low similarly to Italy. The exception is Slovenia which stands out with higher coverage of ALMP. Unfortunately, youth-specific data is missing for Baltics, Hungary and the Czech Republic.

Despite all the institutional settings that shape the school-to-work transition process, the importance of economic situation of a country in the process of youth labour market entry cannot and should not be underestimated (Gangl 2002; de Lange et al. 2014; Wolbers 2007). During the economic downturn, the competition had tightened among the school leavers, making transitions to work more challenging and increasing the risk of dismissal due to the association with one of the least protected groups in the LM. In 2013 the Czech Republic had one of the lowest youth unemployment rates among the CEE countries together with Estonia (Rokicka et al. 2015: 22). While Baltic states had the worst situation with youth unemployment in 2010, it returned to lower than the EU average unemployment rate for 15–29-year-olds already by 2012. Youth unemployment is around the EU average in Hungary, Poland and Slovenia, still being alarmingly high (almost 20%). In Bulgaria and Slovakia, youth unemployment rate is slightly higher than 20%. The unemployment rate in the CEE countries exhibits a clear gradient in educational attainment (Fig. 5.1). Moreover, the visible differences in unemployment rates by educational attainment exist in majority of CEE countries: moderate variation in Baltic states is followed by much larger differences of labour market situation of youth from Poland, Slovakia and Bulgaria.

Fig. 5.1
figure 1

Unemployment rate by educational levels and age groups (%, 2014) (Sources: Own calculations based on Eurostat (yth_empl_090), and EU-SILC cross-sectional UDB(ver 2014-1). Country code used: BG Bulgaria, SI Slovenia, PL Poland, HU Hungary, CZ Czech Republic, LT Lithuania, LV Latvia, EE Estonia, UK United Kingdom, IT Italy, FI Finland, AT Austria)

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5.4 Analytic Strategy

5.4.1 Data and Sample

Our study is based on the most recent wave of the longitudinal data from the EU statistics on income and living conditions (EU-SILC), which is the only longitudinal dataset which allows for between-countries comparison, as the harmonisation and standardisation of the data is implemented centrally by the Eurostat. We rely on this longitudinal dataset to describe the path of youth labour market transitions between different forms of economic activities by reconstructing individual LM path during 36 months after entering LM first time. The main aim of this empirical analysis is to compare the individual labour market trajectory of youth from the CEE and the benchmarking EU countries. As the educational attainment is the central resource for young people, and it is an important determinant of the LM entry and school-to-work transition (Wolbers 2007), we also examine the labour market trajectories for groups across different educational levels.

The analysis is based on eight CEE countries, for which the data is available: Bulgaria (BG), the Czech Republic (CZ), Estonia (EE), Hungary (HU), Lithuania (LT), Latvia (LV), Poland (PL) and Slovenia (SI). As a benchmark, we use four, distinctive, EU countries as representative cases of different LM entry regimes: the United Kingdom (UK) for liberal, Italy (IT) for subprotective, Finland (FI) for universalistic and Austria (AT) for employment-centred.

As we are interested in the LM situation of youth who already completed education, we limit our sample to those aged 16–30 in 2012, which in the first reported month were not in education, and to those who were present in at least three waves of the survey. We exclude those who were in compulsory military service, permanently disabled or unfit to work. Using these definitions our sample sizes for the CEE countries vary from 500 up to 1480 individuals (for a balanced sample). There is a minor overrepresentation of men (53% in the overall sample for the CEE) especially in Bulgaria (56%), the Czech Republic (55%) and Estonia (57%). However, as we are examining the trends among youth, who finished education (was not in education, while observed in January 2012), the lower representation of women can be related to their larger participation in education, which is a general trend in the CEE and the EU (OECD 2016a). The average age of the respondents from the CEE is 26 years; 25% respondents are younger than 25 and 50% are at least 27 years old. There is no significant variation in this respect among the CEE countries, yet in the sample of the benchmarking EU countries, the respondents are slightly younger.

5.4.2 Analysis

Empirical part of this chapter illustrates the labour market transitions and the most recent situation of youth in selected CEE countries. We distinguished between five labour market statuses. Each of the respondents in the given month could be either at work (employed or self-employed), unemployed, in education (except in the first observance) or in inactivity (fulfilling domestic tasks and care responsibilities, or in other inactivity). This information is used to construct the sequences of monthly labour market statuses between January 2012 and December 2014, similar to that provided for the other EU member states by Brzinsky-Fay (2007) based on the ECHP. A monthly labour market status is based on a retrospective question about the labour market situation in each month of the previous year. The sequence analysis, first developed for the genetics studies in medical and biological sciences, is now more commonly used in social research context in a life-course and time-use research. In this chapter we use it as a graphic tool for describing the order of labour market statuses (Graph 2) and also as a descriptive method for the analysis of LM transitions (Table 5.1).

We rely on the International Standard Classification of Education (ISCED) classification to distinguish between three educational groups, but due to data limitations, we cannot distinguish vocational qualifications. The first group consists of those with education no higher than the ISCED 2 level, lower secondary education (approximately 16% of the total sample); the second group ISCED 3, those with the upper secondary education (the most numerous group comprising around 60% of our sample); and the third group ISCED 4–6 consisting of university graduates (around 24% of our sample).Footnote 6 As mentioned above, a common distinctive feature of the CEE countries is the relatively low number of young people with the lowest level of education – the proportion of youth with no more than lower secondary education is below the EU-28 average (respectively, 10% versus 17%). This characteristic has to be kept in mind when comparing the relative findings of CEE against benchmark countries in general and across educational groups.

As concerns labour market mobility, we use a volatility indicator (Brzinsky-Fay 2007) that depicts the share of the number of episodes in employment and education to the number of episodes in unemployment and inactivity. Higher values of this indicator are associated with more favourable labour market situation of youth.

5.5 Youth Labour Market Transition Patterns

The results of the sequence analysis show (Table 5.1) that between 2012 and 2014 young people spent most time in employment, and this is a common pattern for all observed countries. However, the aggregated employment indicator shows a considerable variation across the CEE countries – while in Bulgaria, during the observed period, youth spent on average 19 months at work, and their counterparts from the Czech Republic spent in employment almost 28 months. In the benchmark countries, in Austria and the UK, youth spend on average 26–27 months in employment during the first 3 years compared to 24 and 20 months in Finland and Italy. The countries having a high enrolment into vocational education at secondary level accompanied by a highly protective labour market for regular workers similar to Austria stand out from the CEE countries. Namely, Czech Republic, Slovenia and Poland are the most successful in terms of high average duration in employment. However, the less regulated labour market does not give a visible better employment chances for youth in the CEE countries differently from the UK. Compared to the EU benchmark countries, the figures place the other CEE countries somewhere in the middle, below the employability of youth in the UK or Austria, but better than in the Southern Europe.

As one could expect, there exists a considerable variation across educational groups in terms of employment chances, with the lowest educated being consistently worst and higher educated the best off in all countries. The school leavers having the secondary level education spent 26–27 months out of 36 in employment on average in Austria and the UK, while in Italy on average only 20 months. Those having lower education level (ISCED 0–2) spent in employment about one fifth times less (relative duration compared to ISCED 3 was 0.7–0.8) and those in higher education (ISCED 4), respectively, about 1.1–1.2 times more time.

The relative differences in employment between educational groups are very similar in the benchmark countries, but much more variety exists between the different CEE countries. The relative differences among school leavers with different educational resources are similar in Estonia, Latvia and Slovenia. However, educational resources play stronger role in some of the CEE countries, where low educated are especially at risk. In Bulgaria, Hungary and Lithuania, the situation of low-educated youth in comparison to medium-educated youth was almost twice as bad – in these countries relative duration of time spent in employment was half less than those with secondary education. At the same time, tertiary educated were more advantaged in Bulgaria and Hungary compared to other countries indicating extremely high variability of labour market outcomes across educational levels in these countries.

The second most widespread youth LM status between 2012 and 2014 was unemployment. From EU benchmark countries, on average youth situation in the UK, Finland and Austria seems favourable as during 3 years youth look for job only for 2–3 months. The situation is much less favourable in Italy, where youth spent almost 10 months in unemployment yet educational differences are small there. At the same time, the low educated are especially disadvantaged at Finnish and Austrian labour market.

A considerable variation in unemployment spells can be observed also among CEE countries where on the one extreme are Bulgarian youth with an average of 9.8 months (similar to Italy) and on the other extreme the Czech Republic with 2.5 months (similar to Austria). On average, youth spent in unemployment considerable more time in the CEE countries than in benchmark countries (except Italy): around 5–6 months during the early career years. While the lowest average duration of unemployment in the UK is attributed generally to the high flexibility of labour market, the same does not seem to hold for the CEE countries with less regulated labour market.

When looking at the educational level, the higher educated are the best off in the Czech Republic and Hungary (0.2–0.3 times the ISCED-3 average). The difference in unemployment spells between highly educated and medium-educated youth is the lowest in Slovenia resembling in this respect the situation in Italy. Thus, between 2012 and 2014 the youth in CEE countries tend to spend on average more months in unemployment compared to their counterparts in benchmark countries except Italy, whereas differences between educational levels are smaller especially for low educated. It might be that low educated opt rather for inactivity if work chances are low or migrate to other countries where low-skilled jobs are better paid than in home countries.

For youth, who already entered LM, the returning to training and education is rather rare in the CEE region. While in Finland as an example of universalistic regime with extended welfare support, youth spent during the observed period on average 3.5 months in education or training (more than in unemployment or inactivity); this share was much lower in the CEE countries – on average 0.6 months, with the longest period observed in Slovenia (1.5). Also in other benchmark countries – Austria, Italy and the UK – the return to full-time training and education was much more common than in the CEE region. One of the explanations for this difference could be the average lower level of ‘investment’ into active labour market policy measures, which include education and training for unemployed or inactive, in the CEE countries compared to ‘old’ EU member states’ (see Table 5.1) and also http://stats.oecd.org/. When looking at educational differences, not very clear pattern can be observed. On the one hand, in countries such as Poland and Bulgaria , but also Hungary, where the share of months spent in education among low educated is higher (1.2–4.1 times) compared to medium educated, and in other countries such as Slovenia, Latvia and Lithuania, the likelihood for low educated to return to education or training is lower (0.6–0.7 times the ISCED-3 average). Higher educated tend to return more likely to education (compared to ISCED-3 level) in the Czech Republic and Bulgaria. One could argue that continuing education is one of the strategies how to avoid unemployment or inactivity status, but here no very clear educational pattern can be observed.

Another status to be observed in the sequence analysis was inactivity due to home and care reasons. Also here, a considerable variation can be observed between CEE countries – on the one extreme are Estonia (on average 5 months out of 36) and the Czech Republic (on average 4.3 months out of 36) and on the other extreme Slovenia (0.3 months out of 36). In the benchmark countries, home- and care-related status was around 3 months in average (in Italy somewhat less and UK slightly more). In this category, different from other statuses, there can be observed significant gender difference in terms of duration – women spent significantly more time in inactivity status caused by care responsibilities and fulfilling domestic tasks compared to men. Long average duration of care status could be related to the existing fertility behaviour and welfare benefits related to that. Although the fertility rates in the CEE region are low, the average age at birth of the first child tends to be lower compared to Western Europe,Footnote 7 and therefore it is plausible that many respondents in the observed age group entered parenthood during the observation window. Still, another argument could be that home and care responsibilities are a sign of ‘hidden unemployment’. For example, in Bulgaria, Slovenia and Hungary, but also Poland, Latvia and Lithuania, home and care activities during the early career phase relate very much to youth with the lowest level of education (ISCED 0–2).

Another way of looking at the LM entry process is the general mobility and/or labour market flexibility level during the transition period, here characterised by a volatility measure. Higher values of volatility indicator are showing that positive transitions to employment or education and training are outnumbering the transitions to unemployment and inactivity. The Czech Republic, Slovenia and Poland stand out as the best and Bulgaria and Hungary as the worst. While compared against the EU benchmark , this indicator for all countries but the Czech Republic is again close to the value for Austria. Compared to Southern European counterparts, youth in CEE countries tend to be better off in terms of volatility. When looking at educational differences, in the CEE countries, the lowest volatility level characterises the ISCED 0–2 group (0.5–0.9 times the ISCED-3 average) and highest among higher educated (2.2–3.2 times the ISCED-3 average).

Thus, the largest disadvantage regarding labour market exclusion exists for those with the lowest levels of education. However, as could be also observed in Fig. 5.2, their chances differ depending on country. The unemployed youth with the lowest educational attainment in Latvia (ISCED 0–2) experienced more transitions to employment since 2012 than the youth with the same educational attainment in Hungary. In Bulgaria low-educated youth who were inactive due to domestic task and care responsibility in January 2012 remained largely inactive also in December 2014. At the same time, in Slovenia a lot of unemployed youth with lower level of education switched into employment, especially at the beginning of 2014.

Fig. 5.2
figure 2

Labour market trajectories by level of education in selected CEE (Sources: EU-SILC longitudinal data, own calculations. Graph CZ: ISCED 0–2 should be treated with caution due to low number of cases)

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Interestingly, the labour market situation of youth from majority of the CEE countries became more stable, once they have entered the labour market. For example, youth from Bulgaria and Poland who were employed in 2012 have more than 92% probability to remain employed also in 2014 regardless of their educational attainment. These figures are much higher than in the benchmark countries, especially in the case of low-educated people. This result can indicate that due to the relatively high unemployment rates youth with lower education are more likely to accept and try to keep the job. It could also be a sign of the hiring based on previous work experience; thus, once low educated manage to enter, their employability is not lower than of those with secondary education. The urge to accept any job and thus being continuously employed might also be enforced by the low coverage and low benefits of social welfare in the CEE countries.

Unfortunately, these two countries, Bulgaria and Poland, share another common pattern: low transition rate from unemployment into employment for low-educated youth – in which they differ from some Baltic states like Latvia and Lithuania but remain similar to Slovenia and Estonia. Only 18% of initially unemployed young people with lower education in Bulgaria and 19% in Poland were able to find a job in 2 years’ time. This indicates the strong insider-outsider division reflected in low chances to enter employment. On the other hand, young unemployed from Hungary and Latvia have the highest chance of transition into employment (respectively, 40% and 35%).

5.6 Summary and Discussion

While summarising the empirical part of the individual labour market trajectories, several findings are worth mentioning. First and foremost, we want to underline that it is not possible to treat the CEE countries as one homogenous LM entry regime. The CEE countries differ between each other not less than the benchmark countries Austria, Italy, the UK and Finland. Thus, it would be oversimplification to assume that the youth transitions would be similar inside the CEE countries as different countries have very different institutional setups. Also the results confirm that youth chances vary on great extent across the CEE countries.

The youth transitions in the Czech Republic, Slovenia and Poland resemble Austria where educational system has high vocational specificity and regular workers are well protected which seems to contribute to continuous employment in early career. For other countries, the differences in the employment protection legislation do not have clear-cut implications for youth labour market outcomes. The low employment protection in Hungary or Bulgaria is not reflected in the volatility of its labour market. In majority of the CEE countries, even in systems with vocational orientation, labour entry is crucial for youth as employed youth regardless of their educational resources is much more likely to be employed also in the future, indicating the role of work experience in the job matching process in the CEE countries. However, Bulgaria stands out from the rest of the CEE countries with a very low labour market participation of unskilled and low-educated youth and the lowest LM volatility.

Still, there are also some specific features of the CEE countries which are worth pointing out. First of all, the labour market inequality related to educational attainment is much more pronounced in the CEE countries that in the rest of Europe. The common distinctive feature of the CEE countries is the relatively low number of young people with the lowest level of education – the proportion of youth with no more than lower secondary education is below the EU-28 average (respectively, 10% versus 17%). However, the experience of unemployment is much harder for them as they have much lower chances to leave unemployment and find a job than their better educated counterparts. At the same time, youth with lower secondary education have rather high employment stability once they found a job. This suggests that there is a need for better tailored labour market policies addressing barriers to labour market entry and exclusion of low-educated and unskilled youth in the CEE. Understanding what is behind these barriers is crucial for developing effective policy interventions.

Secondly, in the majority of the CEE countries (except for Slovenia and Estonia), the episodes of education and training among youth who finished formal education are rare; thus, there are few opportunities to overcome the initial shortage of educational resources. This result fits into a broader context of low participation in lifelong learning activities in the CEE. According to the EurostatFootnote 8 in the EU-28 on average, 50% of youth aged 25–34 participated in formal and non-formal education and training, while in the CEE region, this proportion was much lower and varied from 13% in Romania up to 64% in Estonia, which was exceptional in this regard. The analysis in this chapter reveals low transition rates from inactivity and unemployment into education in the CEE, which can be related to the size and direction of the expenditure on active labour market policies. While on average in the EU-28 0.46% of the countries’ GDP was spent on active measures – training, employment incentives, etc. – in the CEE it was only around 0.24%.Footnote 9 Policies aimed at promotion of lifelong learning initiatives and providing training opportunities for the most disadvantaged, low-skilled and low-educated youth can boost not only their future labour market prospects but also prepare them to the challenges of rapidly changing economies.

While analysing the most recent labour market situation of young people from the CEE region, we cannot ignore the migration outflow, which occurred after the EU accession in 2004. Before 2004 the youth unemployment rates in the CEE countries were much higher than after it; the decline was mostly observed in Poland (from 40% in 2004 to 17% in 2008), in Slovakia (from 33% to 19%) or in Estonia (from 24% to 12%) (OECD 2016b). However, the EU accession was in parallel with economic upward trend in most countries that makes it hard to disentangle the different effects. This gradual improvement of the situation in the labour market was hindered by the recent economic crisis starting in September 2008, which was especially severe in the Baltic states and in Hungary. However, since then the macroeconomic situation in the majority of the CEE countries has improved, leading to a certain stabilisation of labour market situation of youth by 2014.

Finally, it is worth noting that employment per se in the CEE region does not always translate into favourable financial and economic situation. In Bulgaria, Romania and Hungary, more than 20% of working youth still live in severely materially deprived households, and more than 40% of working youth report difficulty in making ends meet (Rokicka and Kłobuszewska 2016). Given that the unemployment rate is already high in these countries, the overall group of economically disadvantaged youth is quite remarkable. Although policies promoting the youth labour market participation would undoubtedly be very valuable, some evidence show that active labour market interventions work better for prime age workers than youth (Martin and Grubb 2001). What seems to be essential for combating the youth labour market disadvantages are early educational interventions, which address the inequality at the very early stage, reducing school dropout rate, and ensuring that the young people leave education with skills and competences highly valued on the labour market. We should also remember that the youth labour market does not exist in isolation from the rest of the economy, so good macroeconomic conditions, and good business climate, are essential for youth employment prospects.