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Youth unemployment has been on the rise since the beginning of the crisis in 2008. Even more troublesome is the dramatic rise in the number of youth not in employment, education or training, which has led to widespread concerns about the impact on social cohesion and fears of a “lost generation”. Given the extreme differences in youth unemployment levels among member states, it is clear that no single labour market policy will be appropriate throughout the EU. There may, however, be opportunities for mutual learning on how to combat youth unemployment. This Forum explores youth unemployment in the EU via case studies of England, Belgium, Spain, Poland and Ireland. It also examines Germany’s dual vocational training system as one potential solution.

What Measures Can Be Taken to Address the Specific Problem of Young People Who Are NEET?

The need to address the “problem” of young people who are disengaged from mainstream learning and employment-related activity is recognised internationally. Drawing on evidence from policies implemented across a range of countries, this paper, which has been developed from a memo produced for the Policy Network,1 will consider what can be done to reduce the numbers of those young people who are classified as not in education, employment or training (NEET). It will look broadly at key issues underpinning the NEET phenomenon, factors which need to be taken into account when devising policy interventions and elements of those interventions which have been shown to be successful. It will then focus on the example of England before drawing some overall conclusions.

While governments worldwide grappled with youth unemployment in previous recessions, the term NEET is now commonly used to capture disengagement and social exclusion, as well as high levels of unemployment among young people. At times of economic recession, young people suffer disproportionately due to their often precarious position in the labour market, which is attributed to their lack of skills and experience. The scarring effects of long-term youth unemployment and social disengagement continue to challenge policy makers to develop successful and sustainable interventions.2 Moreover, the costs to the public purse of managing the economic and social consequences of inactivity among young people cannot be ignored.

For example, in the UK, the short- and long-term consequences of high youth unemployment and low participation in employment and training have been found to be far-reaching. The Commission on Youth Unemployment showed that young people aged 16-24 years who were unemployed were more likely to spend longer out of work throughout their lives, be paid less when in work,3 have poorer mental and physical well-being and be involved in criminal activity.4 It was estimated that in 2012 alone the costs of youth unemployment were £4.8 billion, plus £10.7 billion in lost output, and in subsequent years this will cost £2.9 billion and £6.3 billion per year respectively.5

Defining NEET

Before discussing approaches to policy interventions aimed at addressing the NEET problem, it is important to understand that the definitions and measures of youth unemployment and NEET differ significantly across nations. The term “NEET” emerged in the UK in the late 1980s following changes to unemployment benefit entitlement regulations which essentially removed young people under the age of 18 from the unemployment statistics.6 It is also now widely applied across EU states and OECD countries and covers a broader age spectrum, typically 15- to 24-year-olds. In contrast, the youth unemployment rate is a narrower definition, being a percentage of all young people (aged 15 to 24) who are unemployed compared to the total labour force in that age group.7 It does not take into account those who are studying or who are in training, who may or may not be seeking employment, or those who are not registered in the unemployment statistics.

The literature is rife with labels such as “early school leaving” (ESL), being “disengaged” and being “at risk” of becoming NEET. For example, while in the UK the NEET group is the focus of policy initiatives and interventions, much of the attention in the international literature is on those who are in the education system but are perceived to be in danger of dropping out before they complete the statutory period, with damaging personal consequences. It could be construed that concentrating on this latter group is an attempt to reduce the likelihood of their becoming “disengaged” by intervening earlier. In contrast, the focus on those who are already NEET seeks to introduce measures to re-engage those individuals.

In the United States, the focus has been on those who drop out of the education system before completing their high school diploma. At the same time, a recent wide-ranging study, which encompassed data from all 27 member states of the European Union as well as in-depth analysis of nine countries, focused on “early school leaving”.8 However, while this title may give the impression of a concentration on a narrower range of individuals than the broader approach cited above, the definition of “early school leavers” in the EU is “those aged 18-24 with at most lower secondary level education who have not progressed to any further education or training”.

At the outset, it is important to quantify and contextualise the emergence of youth unemployment and disengagement as priorities for the agendas of governments across Europe. The International Labour Organization (ILO) recently stated that “[s]ince 2009, little progress has been made in reducing youth unemployment in the advanced economies”,9 with both the level and duration of unemployment increasing significantly. It was estimated that the youth unemployment rate was 18.1 per cent, which represented a rise of 25 per cent from 2008. Eurostat statistics show that in March 2013 more than half of young people in Greece (59.1 per cent) and Spain (55.9 per cent) were unemployed.10 Only Germany and Austria (both 7.6 per cent) had levels below ten per cent.

As far as the NEET figures were concerned, the ILO report, citing OECD figures, estimates that one in six young people are “without a job and not in education or training”, with Estonia, Iceland, Ireland and Spain having particularly high rates. This has subsequent damaging impact on young people’s employment and earnings prospects, as well as health and job satisfaction, up to two decades later.11


In the UK, while there is an abundance of research evidence about the composition and characteristics of the under-18 NEET group, there is less definitive data available on the characteristics and composition of the post-18 NEET population. Given that this population spans a wider age cohort, its segmentation is likely to be more complex, since it will include young people who left school at 16, post-16 education and training completers and dropouts, and young workers, as well as those who have spent periods of time churning between EET activities and NEET status.

The delineation of the NEET group in the UK, in terms of its size, characteristics and propensity to re-engage in education, employment and training has been the subject of innumerable political, research and media reports.12 In addition, the “triggers” of NEET status are well recorded. These include low socio-economic status, bullying at school, exclusion and absenteeism, low attainment, special educational needs, parental education, and low level or lack of parental support.13 There are also regional variations and differences between localities, dependent on levels of social deprivation and adult unemployment.14 Thus, locality, place attachment and social networks clearly shape the structure of opportunities available to young people.15 At the same time, research findings and evidence from programme evaluations have enabled the factors which contribute to successful outcomes for young people who are NEET to be identified.16

Underpinning factors

Three key factors need to be taken into account when devising policies targeted at NEET young people. The first is the need to distinguish between “preventive” and “reintegration” strategies. In assessing the appropriate response to the problems of ESL, a recent appraisal of approaches adopted in a wide range of European countries17 distinguishes between three tactics:

  • Strategic level responses – Under this approach, policies are coordinated within an overall framework.
  • Preventive strategies – These are early interventions designed to reduce the likelihood of drop-out at a later stage. At-risk young people are identified on the basis of their neighbourhood, school, family background, etc.
  • Reintegration strategies – These are targeted at those who have already dropped out of the education and training system.

The distinction between “preventive” and “reintegration” strategies is of crucial importance in deciding when and where mechanisms for establishing risk factors are introduced. Prevention points to the need for predominantly school-based data to be collected and analysed at an early stage in a young person’s experience in the education system, whereas reintegration is likely to require the input of a range of agencies and takes place once an individual has fallen out of the system.18 At present, responses to recession which emphasise austerity measures and cuts to services, the escalating costs of welfare, concerns about civil unrest, and the breakdown of social cohesion challenge governments’ ability to tackle NEET prevention and re-integration simultaneously.

The second factor that needs to be recognised is that not all young people who are NEET are “vulnerable” or “marginalised”. It is misleading to assume that the most vulnerable or marginalised groups, such as the homeless, young offenders or young people leaving care, comprise the majority of the at-risk NEET or NEET groups. While certain characteristics – notably poor educational performance, disaffection with education and low socio-economic status – are more prevalent, many young people who are NEET have average levels of attainment, live at home supported by their family and, as such, can become “invisible”. Policy interventions tend to be focused on the most marginalised and vulnerable groups, while mainstream groups often operate under the radar of policy intervention until their status triggers entitlement to social security and associated benefits.

The third factor which must be taken into consideration is the rising number of young people whose destinations are “unknown”, rather than NEET. This is a worrying trend which may be a sign of an emerging underclass. It may be the result of an absence of, or the dismantling of, tracking and support services. Irrespective of the cause, the spectre of an emerging underclass which is distinct from the NEET group and does not attract interventions due to its lack of any policy identity cannot be discounted. Therefore, effective tracking systems are essential for the targeting of policy interventions.

In some countries, the focus has been on NEET prevention, i.e. early intervention, to prevent young people from dropping out, while in others policy attention has concentrated on NEET reduction. The considerable and often prohibitive cost of pursing both types of intervention draws attention to the question “what works best, where and for whom?”

Measures to address the NEET problem

Early intervention measures

Research evidence from longitudinal studies shows that early intervention measures can reduce the likelihood of young people dropping out of education at a later stage, often by identifying those who might be at risk of dropping out on the basis of characteristics such as their family background, neighbourhood and school performance.19

Recent years have seen a proliferation of “early warning systems” being introduced in countries across the world in an attempt to provide early identification of young people who may be at risk of becoming NEET or dropping out of education. Such systems have been particularly prevalent in the United States.20 It is important to remember that the target group in these systems is early school leavers, which differ from the NEET group in that they include those who leave school but enter employment or job-related training. These early warning systems tend to be school-based, with data routinely collected in order to flag the existence of risk factors which point to a heightened possibility of dropout or disengagement. Levels of attendance and fluctuations in academic performance are prominent as indicators of young people at risk. There is also often a recognition of the importance of external agencies for their ability to address specific problems being encountered.

The thrust of these early warning systems is geared to the implementation of prevention strategies, rather than reintegration strategies. Whatever risk factors are employed, the key contribution of the system is to alert school staff and other relevant agencies that certain pupils may be in need of additional support.

Types of interventions which have been shown to be successful include:

  • Investing in good quality Early Childhood Education and Care to reduce the propensity of ESL/NEET status, even though this requires long-term investment to achieve and substantiate the benefits;21
  • Identifying, targeting and supporting at-risk students, especially through the use of assessment tools and one-to-one intensive mentoring support;
  • Offering financial support to those from lower income households and other vulnerable groups, thereby encouraging and sustaining their participation in learning;22
  • Within schools, introducing alternative curricula, providing more vocational and technical education, and working in partnership with other organisations, such as specialist technical colleges, the charity/voluntary sector and employer organisations, to combat the propensity for early leaving;
  • Identifying the triggers of disengagement from school – in the Netherlands, for example, local programmes have been developed to prevent drop-out, including long-term performance agreements between schools, municipalities and the national government, in partnership with business and youth care workers, and a funding policy linked to the reduction of the number of early school leavers;23
  • Raising the participation age at which young people can leave education or training. This is currently being enacted in the UK. However, such a policy runs the risk of simply “warehousing” young people, unless it is accompanied with meaningful learning and the attainment of credible qualifications and learning that has real currency in the labour market.24

Re-integration measures

Re-integration strategy at the level of the individual requires systems which have the capacity and capability to identify young people who become NEET and support them to achieve positive outcomes in terms of re-engagement. Moreover, it should be remembered that the NEET population is not homogeneous, and therefore it is essential to cover the breadth of the population.

As far as specific measures are concerned, outreach services have been shown to be successful, but they are resource intensive. At the same time, young people who are NEET need financial support mechanisms, intensive support (from trained advisers) and tailored education, employment and training solutions to achieve long-term, sustainable outcomes. A programme called Activity Agreements, which combined all three types of intervention, was piloted in England between 2006 and 2010.25 Again, such an approach requires substantial investment of both time and money.

Tracking systems

Clearly, it is important to have accurate and up-to-date information about the numbers and characteristics of those who are NEET or are at risk of becoming NEET. Therefore, a key element of initiatives seeking to address the NEET issue is the implementation of systems for mapping and tracking groups of young people who have been identified as being in one of these categories. These approaches are typically employed by organisations in monitoring the status of target groups of young people at regular intervals and ensuring that appropriate provision is being offered.

Approaches to mapping and tracking can also be used to generate information to develop or refine predictive models. When seeking to derive data from which robust indicators can be generated, great emphasis is placed on the importance of collecting adequate data on all young people, as this enables trends to be understood and addressed. It also underpins NEET prevention initiatives through early identification of those deemed at risk of becoming NEET.

Effective tracking systems can bring together data held by different organisations in order to monitor the activity of the target group. At a strategic level, tracking systems can help governments monitor aggregate data on the status of whole cohorts of the population or on specific groups within that population, while at an operational level, they can identify and monitor the status of individuals within a particular target group.

Active labour market measures

Another mechanism for tackling youth unemployment is to introduce active labour market measures to stimulate the demand for young people in the labour market.26 A common feature of such approaches is to offer wage and training subsidies or tax and national insurance breaks/credits to employers. This has been the case in the UK, as will be demonstrated below. Programme interventions which offer a bridge between education and work are also prevalent. Examples of such policies include the creation of programmes which offer young people training and work experience, the broadening of apprenticeship programmes, the provision of training in entrepreneurship and interpersonal skills, and the availability of work preparation courses for young people who lack the immediate skills to enter the workplace.

In some countries, youth guarantees are in place. These guarantees ensure that unemployed young people are offered a job or an educational or training opportunity within a specified timeframe following their unemployment registration. Overall, however, active labour market policies are unlikely to work for the most disadvantaged groups unless accompanied by re-engagement strategies.

Quality of jobs

While stimulating the demand for young workers is important, the quality of the jobs they occupy must be safeguarded. In addition to enabling young people to access the labour market, priority should be given to improving the quality and security of jobs they are able to enter and ensuring that young workers receive a living wage. For example, stricter limits on temporary working have been found to reduce the incidences of “churn” between employment and unemployment among low qualified young people and early school leavers. Short-term or temporary working patterns do not facilitate access to permanent jobs for young people. They are much more likely to trap young workers in precarious “in-and-out-of-work” trajectories. Another approach to reducing the likelihood of unemployment and NEET group status that has been applied in some EU countries is to reduce the costs of employing lower skilled youth through sub-minimum wages and/or lowering social security contributions.

Young people NEET in England

In the UK, the numbers of young people who are NEET and/or disengaged have been a major focus of research and policy interest for over a decade and continue to be so. Despite an increase in the proportion of 16- to 18-year-olds participating in full-time education, a persistent minority remains NEET. However, it is the swelling number of young people in the post-18 NEET group that currently gives greatest cause for concern. In the first quarter of 2013, 8.2 per cent of 16- to 18-year-olds were NEET in England. The rate for 18-year-olds was 13.8 per cent. The NEET rate for 19- to 24-year-olds was 18.2 per cent.27 In the three months to April 2013, 20.5 per cent of 16- to 24-year-olds were unemployed, equivalent to 950,000 young people.28

There have been many measures introduced to reduce youth unemployment among 18- to 24-year-olds in England and to increase their participation in education, employment and training. These include the launch of the National Careers Service, the reform of the Apprenticeship programme, the full funding of 18- to 24-year-olds to gain their first Level 2 or 3 qualification, and the development of progressive ways to jobs and apprenticeships, aiming particularly to promote the effective use of flexibilities in the skills system and the Work Programme to best meet the needs of young people.

In addition, elements targeted at young people have been introduced to the Work Programme, which provides support for those unemployed and receiving Job Seeker’s Allowance (JSA) for more than 12 months and for those at risk of long-term unemployment. Those aged 18 to 24 can be referred to the programme after receiving JSA for nine months. Meanwhile, 18-year-olds who have been NEET for six months can be referred after claiming JSA for three months. Official estimates are that a fifth of referrals to the Work Programme will be young people aged 18 to 24.

For short-term unemployed young people, support continues to be available from Jobcentre Plus through placing greater emphasis on flexibility and a menu of support options for young people. This approach allows advisers and young people to decide on the most suitable support and aims to get young people into work and exploring self-employment opportunities before they become eligible for long-term support.

The Youth Contract, which was launched in April 2012, brings together key initiatives with three main aims:

  • increasing support available to young people trying to enter the labour market;
  • helping unemployed young people gain work-relevant skills; and
  • helping young people enter work.

There is also a programme of support within the Youth Contract targeted at disengaged 16- to 17-year-olds in England. Under this strand, organisations are appointed on a regional or sub-regional basis to help young people move into full-time education, to start an apprenticeship or to take a job with training.

Both the Work Programme and the Youth Contract involve a study of the payment by results model and black box approaches to policy design and implementation, which delegates responsibility from government to the prime providers, who are contracted to manage and deliver the programme(s).


The terms NEET, youth unemployment and early school leaving are often used interchangeably to attempt to capture and to quantify a crisis that is facing many EU and OECD countries, namely the lack of opportunities for young people as they make their transitions into adulthood and the long-term consequences of successive generations unable to achieve their potential. While many governments grapple with the effects of the economic crisis, it remains an imperative that the lack of good and sustainable jobs which harness the skills and talents of young people is prioritised and underpinned by substantial and sustained investment to support youth transitions.

Measures designed to reduce the NEET population should include policies which tackle NEET prevention, re-engagement strategies for the hardest to reach groups, and active labour market policies for the young unemployed. This should be supported by well-resourced tracking systems. A piecemeal approach, simply focusing on quick fixes, will not facilitate and sustain meaningful transitions into adulthood. Furthermore, interventions can be inhibited by competition among agencies which offer similar programmes to achieve often short-term goals as well as by a lack of strategy to address the underlying issues that NEET young people face. Therefore, overall strategy should be led by government.

While the NEET issue is stated as a key priority in many national policy agendas, intervention programmes are often limited in duration and funding, with an over-emphasis on immediate impact in order to prove that the programme itself has worked, for political expediency, rather than tackling the underlying obstacles to reducing the NEET population. Moreover, there has been a concentration on quantifying the “problems” with this population, specifically with regard to its social and educational characteristics, rather than tackling the underlying reasons for young people’s disengagement or developing and investing in long-term solutions. As a starting point, governments across the EU should commit to sharing the wealth of innovatory and good practices which can be found in many member states and which could form the building blocks of an effective EU-wide assault on the scourge of youth unemployment.

This paper has received the financial support of the EU (DG Employment, Social Affairs and Inclusion of the European Commission).
The opinions expressed are those of the author only and do not represent the European Commission’s official position.

  • 1 S. Maguire: Responding to the NEET demographic, in: The Politics of Growth, Stability and Reform, Policy Network & Global Progress, London 2013, pp. 117-120, http://www.policy-network.net/.
  • 2 D.N.F. Bell, D.G. Blanchflower: Young people and the great recession, IZA Discussion Paper No. 5674, 2011.
  • 3 L. Macmillan: The cost of youth unemployment, in: Youth unemployment: the crisis we cannot afford, The ACEVO Commission on Youth Unemployment, 2012, pp. 78-93.
  • 4 D.N.F. Bell, D.G. Blanchflower, op. cit.
  • 5 L. Macmillan, op. cit.
  • 6 Eurofound: NEETs – Young people not in employment, education or training: Characteristics, costs and policy responses in Europe, Publications Office of the European Union, Luxembourg 2012, p. 19.
  • 7 http://www.ilo.org/public/english/employment/yen/whatwedo/projects/indicators/2.htm.
  • 8 European Union: Reducing Early School Leaving in the EU, European Parliament’s Committee on Education and Culture, June 2011, p. 31.
  • 9 International Labour Organization: Global Employment Trends for Youth 2013: A generation at risk, Geneva 2013, p. 3.
  • 10 The Guardian, 29 May 2013.
  • 11 D.N.F. Bell, D.G. Blanchflower, op. cit.
  • 12 See Audit Commission: Against the odds: re-engaging young people in education, employment and training, 2010, available at http://www.audit-commission.gov.uk/SiteCollectionDocuments/Downloads/20100707-characteristicsofyoungpeopleneetforagainsttheodds.pdf; and T. Spielhofer, T. Benton, K. Evans, G. Featherstone, S. Golden, J. Nelson, P. Smith: Increasing Participation: Understanding young people who do not participate in education or training at 16 or 17, DCSF Research Report 072, Department for Children, Schools and Families, London 2009.
  • 13 S. Gracey, S. Kelly: Changing the NEET mindset: Achieving more effective transitions between education and work, London 2010, LSN.
  • 14 D. Sachdev, B. Harries, T. Roberts: Regional and sub-regional variation in NEETs – reasons, remedies and impact, Learning and Skills Development Agency, 2006.
  • 15 A. Green, R. White: Attachment to place: Social networks, mobility and prospects of young people, Joseph Rowntree Foundation, York 2007.
  • 16 S. Maguire, B. Newton: Activity Agreement Pilots – trialling different approaches to re-engaging young people not in education, employment or training (NEET): Evaluation of the 2009-10 Extension, Department for Education: RR065, 2011, available at https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/182308/DFE-RR086.pdf.
  • 17 European Union, op. cit.
  • 18 R. Dale: Early School Leaving Lessons from Research to Policy Makers, NESSE, 2010.
  • 19 Ibid.
  • 20 See e.g. L. Pinkus: Using Early-warning Data to Improve Graduation Rates: Closing Cracks in the Education System, Alliance for Excellent Education Policy Brief, 2008; J. Heppen, S.B. Therriault: Developing Early Warning Systems to Identify High School Dropouts, Issue Brief, National High School Center, American Institutes for Research, 2008, available at http://www.betterhighschools.org/pubs/ews_guide.asp.
  • 21 A.J. Reynolds, S.R. Ou, J.W. Topitzes: Paths of Effects of Early Childhood Intervention on Educational Attainment and Delinquency: A Confirmatory Analysis of the Chicago Child-Parent Centers, in: Child Development, Vol. 75, No. 5, 2004, pp. 1299-1328.
  • 22 S. Maguire, J. Rennison: Two Years On: The Destinations of Young People who were NEET at 16, in: Journal of Youth Studies, Vol. 8, No. 3, 2005, pp. 187-202.
  • 23 K. De Witte, S. Cabus: Does School Time Matter? On the impact of compulsory education age on school drop-out, in: S. De Groof, M. Elchardus (eds.): Early School Leaving and Youth Unemployment, Tielt and Amsterdam 2013, LannooCampus and Amsterdam University Press.
  • 24 S. Maguire: Will the Raising of the Participation Age (RPA) in England solve the NEET problem?, in: Research in Post-Compulsory Education, Vol. 18, Nos. 1-2, 2013, pp. 61-76.
  • 25 Department for Education: What works re-engaging young people who are not in education, employment or training (NEET)? Summary of evidence from the activity agreement pilots and the entry to learning pilots, Department for Education Research Report DFE-RR065, 2011.
  • 26 International Labour Organization, op. cit., pp. 61-69.
  • 27 Department for Education: Statistical First Release: NEET Statistics - Quarterly Brief – Quarter 1, 2013.
  • 28 House of Commons Library: Youth unemployment statistics, 12 June 2013, available at www.parliament.uk/briefing-papers/sn05871.pdf.When young people in full-time education are excluded, the unemployment rate is 18.9 per cent, or 659,000 young people. See Office for National Statistics: Statistical Bulletin: Labour Market Statistics, June 2013, available at http://www.ons.gov.uk/ons/dcp171778_312067.pdf.

Youth Unemployment in Belgium: Diagnosis and Key Remedies

In late 2012, the European Commission raised the alarm about the evolution of the youth (under 25 years old) unemployment rate since the start of the Great Recession in 2008. The youth unemployment rate in the European Union (EU27) had attained an unprecedented height of 22.8 per cent, which is 7.2 percentage points higher than four years earlier and more than twice as high as the prime-aged adult (25 to 54 years old) rate.1 The Commission therefore launched the Youth Guarantee in February of this year, an action worth €6 billion for the period 2014-2020 to help EU countries get young people into employment, further education or (re)training within four months of leaving school. Is the call for urgency justified and is this action an adequate response?

It should be no surprise that the youth unemployment rate is higher and fluctuates more with the business cycle than the adult unemployment rate. First, it is higher because youths are at the start of their careers, a period in which they are typically searching for an adequate job match. This search process induces high job turnover, possibly with intervening spells of unemployment. Second, in a downturn, employers will be reluctant to lose more experienced workers, since these have more firm-specific skills and greater redundancy costs. So, the burden of adjustment typically falls on low-wage workers, such as the young.

The dramatic rise in the youth unemployment rate since 2008 is therefore primarily a consequence of the profound economic crisis in the EU. If the Commission aims at bringing the youth unemployment rate back down to the 2008 level, it should follow a less restrictive fiscal policy rather than investing in a Youth Guarantee. However, in view of the high public debts of many EU member states, a looser fiscal policy may be counterproductive, because it may result in lower private sector growth through the mechanism of expectations regarding the reimbursement of this debt and higher interest rates. Finding a way to counter the current crisis is therefore difficult.

Nevertheless, the fact that youth unemployment is currently high on the political agenda generates a window of opportunity for addressing structural problems in a number of countries. Table 1 reports the average youth and prime-aged adult unemployment rate over the last ten years (2003-2012) in the EU27 and some selected member states. The average youth unemployment rate varies dramatically among member states, ranging from 7.3 per cent in the Netherlands to 30.7 per cent in Greece. However, this variation may partly reflect different general economic conditions among member states. We therefore also report the youth unemployment rate relative to the prime-aged adult rate, both in proportional terms and in absolute percentage differences (see columns 3 and 4). This, however, does not change the global picture. Some countries (Belgium, France, Greece and Spain) always display higher structural youth unemployment than others.

Table 1
Youth and prime-aged adult unemployment rates in selected EU countries, 10-year average (2003-2012)
Country/region (1)
(< 25 years) unemployment rate
Prime-aged adult
(25-54 years) unemployment rate
Absolute difference, in percentage points:
Greece 30.7% 11.1% 2.8 19.6
Spain 30.4% 13.2% 2.3 17.2
France 20.9% 7.7% 2.7 13.2
Belgium 19.8% 6.8% 2.9 13.0
Brussels 35.0% 15.8% 2.2 19.1
Wallonia 29.6% 9.6% 3.1 20.1
Flanders 13.5% 4.0% 3.3 9.4
EU27 18.9% 7.9% 2.4 11.0
Germany 11.4% 7.9% 1.4 6.5
Denmark 10.4% 4.8% 2.2 5.6
Austria 9.0% 4.0% 2.2 5.0
Netherlands 7.3% 3.4% 2.1 3.9

Source: Eurostat.

Some features characterising the countries reported in Table 1 suggest possible mechanisms explaining this divide. France, Greece and Spain are countries where employment protection is very high, while Denmark, the Netherlands and Austria are countries in which active labour market policies (ALMP) are known to be very effective. Furthermore, Germany, Denmark and Austria have a well-developed dual apprenticeship system. In this paper, we will explore the extent to which these elements play a role in explaining the high structural youth unemployment in Belgium.

In Belgium it is commonly believed that youth unemployment is essentially a problem in Wallonia and Brussels, but not so much in Flanders, the third Belgian region. We do not agree with this view.2 The youth unemployment rates in Brussels and Wallonia are indeed extremely high, reaching 35 per cent and 30 per cent respectively, against only 13 per cent in Flanders. However, no country or region in Table 1 displays a higher relative youth unemployment rate than Flanders. In terms of absolute differences, Flanders performs better but still considerably worse than the aforementioned high-performing countries.

The high relative youth unemployment rate in Belgium reflects predominantly a problem among low-skilled youth. Below the age of 25, the low educated are over-represented in the active population, since the highly educated are still studying at young ages, whereas the low educated have already entered the labour market. Between 2003 and 2012, the average unemployment rate of highly educated youth in Belgium was 12.7 per cent, lower than the EU27 average of 14.2 per cent. By contrast, the corresponding rate for youth without a secondary school diploma was 30.4 per cent in Belgium against 23.8 per cent in the EU27.

Figure 1 provides further evidence that the school-to-work transition is especially problematic for the low educated in Belgium. In the first five years after graduating, Belgian youth are on average employed for only three years. This is well below the OECD average of about 3.5 years. However, the low educated are only expected to spend slightly more than one year in employment during their first five years after leaving school. No other country displayed in Figure 1 performs as poorly as Belgium.

Figure 1
Expected number of years spent in employment during the five years after school, 2008

1 Less than upper secondary education. 2 Data refer to 2006 for Australia.

Source: J. Høj: Enhancing the Inclusiveness of the Labour Market in Belgium, in: OECD Economics Department Working Papers, No. 1009, 2013, OECD Publishing, p. 16.

In Belgium migrant youths are also much more affected than in other European countries. Baert and Cockx and Baert et al. analyse this problem in detail and show that discrimination is an important explanatory factor.3 However, for lack of space, we do not discuss the specific problems of migrant youth in this contribution.

In this contribution, we aim at getting a better understanding of the drivers of structural youth unemployment in Belgium and propose key remedies based on recent academic research. Furthermore, we discuss the importance of the three aforementioned factors: employment protection, education, and the design of passive and active labour market policies.

Employment protection

In Belgium employees are protected by a minimum wage and by extensive employment protection legislation (EPL). We argue that strict EPL decreases the speed of the school-to-work transition for the high skilled, but not so much for the low skilled. The employment of the latter group is more affected by the very high minimum wage in Belgium.

EPL for regular employment

Scientific studies consistently conclude that the overall impact of EPL on aggregate unemployment rates is weak with an ambiguous sign and that the effect on employment is negative but modest.4 The main explanation for this is that strict EPL has two opposite effects. On the one hand, it tends to reduce the job separation rate, i.e. the rate at which workers transit from employment to unemployment. On the other hand, strict EPL decreases the exit rate from unemployment into work, since firms, anticipating future costs on labour force adjustment, become more cautious about hiring. These effects may, in principle, offset each other. However, there is ample evidence that stringent EPL tends to worsen the employment prospects of those groups that are most subject to problems of (re-)entry into the labour market, such as young people, women and the long-term unemployed.

EPL for regular employment contracts is less strict in Belgium than on average in the OECD and only slightly stricter than in Denmark, which is known for its relatively flexible system.5 However, the OECD indicator of employment protection conceals considerable heterogeneity in strictness in Belgium, especially according to the type of labour contract. In Belgium EPL for open-ended contracts differs between blue- and white-collar workers. For the latter group, it differs between those earning more than €32,254 a year and those earning less. The notice period for a blue-collar worker is generally less than one month for each five years of seniority, while for low-wage and high-wage white-collar workers it is three and five months respectively. This means that in Belgium EPL for high-wage white-collar workers is probably among the strictest in the OECD, while the reverse holds for blue-collar workers.

To the extent that white-collar workers are more educated than blue-collar workers, we conclude that in Belgium the strictness of EPL in regular open-ended contracts is especially a barrier for the highly educated youth. For low-educated youth, EPL strictness is less of an issue and, as discussed below, other factors are more important.

EPL for temporary employment

The stricter the EPL is for open-ended contracts, the more employers tend to use temporary contracts as a selection device before making open-ended contracts available and as a way to manage fluctuations in product demand. This risks segmenting the labour market into a primary segment of long-term employment and a secondary segment in which workers transit from one short-term dead-end job to another, possibly with some intervening spells of unemployment.

In Belgium temporary contracts seem to be used less commonly than in other European countries (see Figure 2). Only about 30 per cent of the employed youth are employed in temporary contracts. This is considerably lower than the 40 per cent European average. Moreover, in Belgium this share is nearly five times that of prime-aged workers (among the highest in the OECD), meaning that in Belgium temporary employment is even less widespread among prime-aged workers than among youth.

Figure 2
Incidence of temporary employment (fixed-term contract, temporary help) in youth employment, 2011

Source: P. Cahuc, S. Carcillo, K.F. Zimmermann: L’emploi des jeunes peu qualifié en France, in: Les notes du conseil d’analyse économique, No. 4, 2013, pp. 1-12, here p. 10.

The aforementioned relatively weak protection for blue-collar workers in open-ended contracts – together with the very strict EPL in fixed-term contracts for all types of workers – explains the relatively limited use of temporary contracts in Belgium. In addition, employers of blue-collar workers can make use of the very flexible system of temporary unemployment to manage fluctuations in product demand.6 Nevertheless, these arguments are less applicable to high-skilled, white-collar workers. The risk of getting trapped in temporary jobs is therefore still present for this group.

The findings of Cockx and Picchio further reinforce this view.7 Based on a sample of more than 15,000 long-term unemployed school-leavers in Belgium, these researchers find that the majority of short-lived jobs are not dead ends but stepping stones to long-lasting jobs. By accepting a job that lasts at most one quarter instead of continuing job search for a longer-lasting job, the probability of entering a long-lasting job within two years increases by 13.4 percentage points for men and by 9.5 percentage points for women. Nevertheless, this conclusion should be regarded with caution, since this effect displays substantial heterogeneity. Among those entering short-lived jobs, 40 per cent actually have less chance of entering a long-lasting job. Moreover, in line with expectations, the stepping-stone effect is weaker among the highly educated.

Minimum wage and wage cost

As mentioned above, the transition from school to work for low-educated youth in Belgium is extremely troublesome, but strict EPL is not the main driver of this. High minimum wages are more to blame. There is increasing agreement among researchers that minimum wages have a very harmful impact on the employment of low-skilled youth.8

Figure 3 shows that among OECD countries in which a minimum wage is in force, the cost of employing a 20-year-old in Belgium is among the highest. More­over, this figure underestimates the genuine level of wage costs, since it is based on the legal minimum wage. In Belgium a higher minimum wage is negotiated in most sectors. Kampelmann and Rycx report that in 2007 the employment-weighted average of the minimum wages was 17 per cent higher than the legal minimum wage.9

Figure 3
Hourly wage cost of a 20-year-old employee working at the minimum wage in OECD countries in which a minimum wage is in force, 2010

Source: P. Cahuc, S. Carcillo, K.F. Zimmermann: L’emploi des jeunes peu qualifié en France, in: Les notes du conseil d’analyse économique, No. 4, 2013, pp. 1-12, here p. 9.

Policy implications

Since EPL in Belgium is only strict for white-collar workers, it may mainly hamper the school-to-work transitions of highly educated youth. This discrimination in EPL against blue-collar workers is currently the subject of much controversy and debate. It is clear that the discrimination must eventually disappear and that the level of strictness will converge. This may facilitate the school-to-work transition for the highly educated but risks impeding that of the low educated. We argue that in order to avoid this negative side effect, the harmonisation of EPL should be paired with a more structural reform of EPL that uses available funds more efficiently, stimulating re-employment rather than inactivity. In a nutshell, we propose pooling the bulk of insurance payments in an insurance fund and using it partially to finance the activation of redundant workers.10

For the labour market integration of low-skilled youth, the high minimum wage is a major problem in Belgium, since it raises the wage costs above productivity, making it unprofitable for employers to hire this group. Moreover, this problem has been exacerbated by the recent agreement by the social partners to abolish by 1 January 2015 the phasing in of the minimum wage by age.11 This means that the full minimum wage will apply to young employees under 21, dramatically increasing their wage costs. We strongly plead for reconsidering this measure. Moreover, in view of the internationally high minimum wage level in Belgium, this will not be sufficient. Either the minimum wage should be further reduced or, if this is not socially acceptable, low wages should be structurally reduced. Numerous studies have shown that reducing labour costs creates more employment, even more so when the reduction is targeted at low wages close to the minimum wage.12 Following Dejemeppe and Van der Linden,13 these targeted wage cost reductions can be financed by abolishing the majority of the targeted recruitment subsidies. In addition, rather than reinforcing across-the-board reductions in labour costs – as is often proposed in the public debate as a remedy for the low employment rates in Belgium – these should rather be targeted at low wages. This is because across-the-board wage reductions are largely absorbed by higher (bargained) net wages,14 therefore inducing hardly any employment growth.

The educational system

In Belgium the educational system is organised according to the different language Communities, i.e. the Flemish and the French.15 Nevertheless, the educational systems in these Communities share a number of common features. Compulsory schooling starts at age six and ends at 18,16 later than in most OECD countries.17 Streaming occurs at the beginning of secondary school, generally at the age of 12. This is relatively early from an international perspective. The median age at which pupils in OECD countries are streamed is 15 years.18

Pupils are divided into four major streams: general, technical, vocational and arts. The general stream prepares explicitly for higher education, the vocational stream prepares directly for a profession and the two other streams have mixed objectives. The streaming system has a very (implicit) hierarchical ordering and contains a large number of sub-streams. The hierarchical ordering has been labelled the “cascade-system”, since many pupils starting off in the “higher” streams are gradually forced down the cascade by a system of reorientation at the end of each school year. A consequence is that pupils do not end up in technical and vocational streams as a deliberate choice, but rather as an outcome of a forced reorientation after failure in a “higher” stream. Technical and vocational streams therefore attract more low-ability and discouraged pupils, which is detrimental to their image.

Another important common feature is the use of retention as a policy of remediation. This policy is used much more often than in other countries. In the OECD, 13 per cent of 15-year-olds have repeated at least one year, while this figure was 30 per cent for Belgium.19

Finally, combining work with studies is very uncommon in Belgium. Students in the vocational stream can switch to part-time education from 16 years onwards, but in 2008 only three per cent of youth aged 15-29 combined studies with working, while this share was 12 per cent in the EU15. Moreover, part-time students have many difficulties in finding employment, since firms are reluctant to offer employment to these students due to the aforementioned negative image.

Policy recommendations

Most scientific evidence indicates that grade repetition significantly worsens performance on various measures of academic achievement.20 Similarly, even if scientific research is inconclusive regarding the average level of achievement, there is firm evidence that early streaming has negative effects on the performance of pupils with disadvantaged family backgrounds.21 Numerous studies have shown that the transition from school to work is greatly facilitated by an apprenticeship system that guarantees high quality work-based learning.22 However, international experiences show that schemes can only be implemented successfully if there is significant institutional support and acceptance by major actors. Employers should be fully integrated in the design and implementation of such schemes to guarantee that training curricula are up to date and in line with future needs. Moreover, a system of certification of competences has to be elaborated to ensure that young workers’ competences are also valued in firms other than the one in which these competences were acquired.

Since grade repetition, early streaming and deficiencies in work-based learning are characteristic features of the educational systems in both the Flemish and French Communities, educational reform should have similar characteristics in both of them. We summarise the main ingredients of such schooling reform briefly:

  1. Address grade repetition by continuous remediation during the school year and by supporting teachers to teach classes with more diverse attainment levels;
  2. Postpone streaming in secondary schools;
  3. Stimulate work-based learning by explicitly integrating the social partners as actors in the labour market in the design of the schooling reform. Elaborate a system of certification of work-placed learning so that skills learnt in one firm can be valued in another.

This list of key remedies is in line with the recent policy advice of the OECD.23 In Flanders the aforementioned policy recommendations were the basis of a school reform proposed recently endorsed by the Flemish government, with official implementation planned for 2016. However, the persistent opposition by Flanders’ major political party has made it uncertain whether and in which form this plan will be eventually enacted. Moreover, the current version of the plan allows schools to opt out. On the other hand, major actors in the field favour the reform. In addition, schools will be financially rewarded if they follow the guidelines of the reform. Proponents therefore claim that it will be difficult to block this reform. Despite the less favourable performance of the educational system, reforms undertaken in the French Community are more piecemeal than in Flanders. The most notable is the system of certification and employer integration in the design of vocational education.24 It is urgent to undertake a more global structural reform.

Unemployment benefits and active labour market policy

Unemployment benefits and job search requirements

In contrast to many other countries, in Belgium school-leavers are entitled to unemployment benefits (UB) even if they have no work experience. However, the entitlement starts only after an “integration period” of one year (as of 2012; it was previously nine months). During this period, needy youth are entitled to a means-tested welfare allowance paid out at the municipal level conditional on signing an “integration contract”. The UB level depends on the age and the household situation of the youth. For youth older than 18, the UB monthly level currently varies between €417 and €1,084 for cohabitants without and with dependents respectively. Since young people often continue to live with their parents, the lower level applies in most cases. Before 2012 individuals were entitled to these UB for an indefinite period. Since January 2012, cohabitants are only entitled to UB for a maximum period of three years. For other school-leavers, this time limit of three years begins to apply at the age of 30.

Since 2004 the job search of UB recipients is monitored, and sanctions apply in case of non-compliance. Benefit sanctions are much harsher than elsewhere, but the frequency of the monitoring is very low compared to international standards. For those under (over) 25, job search effort is not evaluated before the 15th (21st) month of unemployment, and if the requirements are satisfied, the next evaluation takes place 12 or 14 months later. This contrasts starkly with the median monitoring frequency of one month in OECD countries.25 The Belgian programme has been rigorously evaluated and shown to significantly stimulate the transition to work and to be cost effective.26

Since August 2012, the government has intensified its monitoring of the job search activity of school-leavers. Beginning with the start of the entitlement, job search effort is monitored every six months. In April 2013, the minister of employment also announced that the job search effort of school-leavers starting unemployment spells in the academic year 2012-2013 will be monitored already in the seventh and 11th months of the integration period. In case of a negative evaluation, school-leavers will be entitled to UB only six month later if at that moment they satisfy the job search requirements.

Active labour market policies

In Belgium UB and the associated job search monitoring scheme are organised at the national level, while ALMP are the competence of regional authorities. Part of the ALMP (e.g. the recruitment subsidies) is, however, still in the process of being transferred from the national level.

Following the recommendations of the EU, in all three regions (Brussels, Flanders and Wallonia), the regional Public Employment Service (PES) currently contacts the young unemployed very early in the unemployment spell: youths aged below 25 are contacted beginning one month after registration, and by the fourth month all unemployed youths should have been invited to a meeting with a counsellor. If they lack the empowerment to find a job by themselves, an action plan is drawn up and training, counselling or job search assistance is tailored to their needs.

In January 2013, a nationally coordinated action plan reinforced at the regional level was launched. This plan targets school drop-outs and graduates with at most a secondary education diploma, groups facing acute difficulties in the school-to-work transition (see Figure 1). It aims at offering more workplace-based learning opportunities. Specifically, these school-leavers are offered full-time apprenticeships of three to six months. Participants are entitled to a daily allowance (€27) paid out by the federal unemployment agency. The employer pays a monthly compensation of €200.

Finally, the federal government activates the unemployed via targeted recruitment subsidies to employers27 and a wage bonus28 to low-wage workers. The current agreement stipulates that the budget of the targeted recruitment subsidies be transferred to the regions. This is a window of opportunity for reform.

Policy recommendations

As mentioned above, youth unemployment in Belgium is essentially a problem of the labour market integration of low-educated school-leavers. We therefore mainly propose reforms that target this group.

More intensive guidance for school drop-outs

First, the recently launched action plan providing apprenticeships for low-educated youth is a step in the right direction, but it should be reinforced with more intensive guidance. Academic research has shown that only early, enduring and intensive remedial education and guided work experience helps this target group.29 In addition, the counselling by the regional PES should be more targeted at this group instead of aiming at reaching all youth early in the unemployment spell.

Early UB entitlement, more frequent monitoring, lower sanctions

We propose to pay to school-leavers relatively low (of the order of €400) flat-rate UB early after the start of their unemployment spell. For those in need, this flat-rate UB could be topped up by a means-tested welfare allowance. Job search effort would be monitored on the basis of written reports to be handed in on a monthly basis. A random sample of these monthly reports would be thoroughly checked. In case of non-compliance, an invitation should follow to draw up an action plan with clearly defined goals. This action plan should be tailored to the profile and needs of the job seeker. For high-skilled job seekers, it would typically consist of clearly defined job search requirements evaluated in an interview after one month. For other job seekers, it would consist of participation in some action such as training, counselling and job-search assistance. Compliance with this action plan should be closely monitored. In case of non-compliance, sanctions should be more moderate than the current sanctions, but progressive in case of recidivism. To the extent that job search effort and active participation in actions are closely monitored, benefits need not run out. However, entitlement to a higher level of UB requires a minimal employment record.

Entitling UB close to the start of the unemployment spell goes against current policy of lengthening the “integration period”. We justify this as follows. First, paying a non-means-tested allowance early in the unemployment spell provides incentives for disadvantaged youth to register as job seekers. This makes early intervention possible, a crucial condition for success.30 Second, up-front benefits and a time limit increase the job-search incentives with unemployment duration, countering the discouragement of long-term unemployment. By contrast, during the current “integration period”, this discouragement is reinforced, since search incentives decrease as one approaches the moment at which UB entitlement starts.

Youth must be made aware that the payment of this non-means-tested UB imposes costs on society and therefore requires effort aimed at minimising these costs. For that reason, we propose to sharply intensify job search monitoring. This can be realised with relatively limited means if the first screening is based on written proofs. However, correctly measuring search intensity is difficult. To compensate for measurement error, the sanction level should be modest and other more easily measurable actions should be involved in the evaluation of the effort exerted.

Replacement of recruitment subsidies by a low-wage subsidy, except for the long-term unemployed

Currently, recruitment subsidies targeted at low-skilled and long-term unemployed youth are granted for a limited time period after recruitment. This time limit is justified by the gradual productivity growth with tenure. This productivity growth is, however, very heterogeneous, and it may be very low among the low-skilled.31 It is therefore unlikely that it exactly matches the decreasing profile of the subsidy and thus risks inducing a waste of resources. The wage evolution should, however, more or less match that of productivity. In a subsidy scheme targeted at low wages, the subsidy tapers off with the wage. The decline will therefore be much more in line with productivity growth than any recruitment subsidy scheme. We therefore propose to replace the recruitment subsidies targeted to low-educated youth by a permanent low-wage subsidy. Such a scheme also avoids the turnover induced by temporary subsidies and the possible substitution with older workers if the recruitment subsidy is targeted at youth.

For the recruitment of the long-term unemployed, the temporary nature of the recruitment subsidy may have another justification.32 Cockx and Picchio find evidence that the lower employability of the long-term unemployed is not so much a consequence of human capital depreciation, but more a consequence of the negative signal this duration conveys to recruiters.33 In this case, the subsidy aims at compensating for the additional selection costs borne during the probation period when hiring long-term unemployed workers.


In Belgium structural youth unemployment is higher than in many other European countries. The problem is particularly severe for low-educated youth. A high minimum wage, a strict separation between school and work and a vertically segmented schooling system with high retention rates and too early streaming have been identified as key causal factors. Strict employment protection legislation focuses only on high-skilled youth. A reduction of the labour costs of low-wage workers and a fundamental schooling reform that aims at dismantling the strict barrier between school and work are proposed as key remedies. In addition, rather than aiming at reaching all youth early in the unemployment spell, ALMP should assign more resources to very intensive remedial education and guided work experience supporting very low-educated youth. Finally, entitling youth to low UB based on the principle of “mutual obligation”, coupled with very intensive and durable guidance targeted at disadvantaged youth, is to be preferred over a strategy in which youth are not (or only late in the unemployment spell) entitled to UB.

I thank Stijn Baert, Yves Saks and Bruno Van der Linden for comments on a first draft of this paper.

  • 1 See http://epp.eurostat.ec.europa.eu/portal/page/portal/employment_unemployment_lfs/introduction.
  • 2 See also B. Van der Linden: Un regard sur le rapport de l’OCDE: Des emplois pour les jeunes, in: Regards économiques, No. 56, 2007.
  • 3 S. Baert, B. Cockx: Pure Ethnic Gaps in Educational Attainment and School to Work Transitions. When Do They Arise?, Ghent University Working Paper, No. 2013/832, 2013; and S. Baert, B. Cockx, N. Gheyle, C. Vandamme: Do Employers Discriminate Less if Vacancies are Difficult to Fill? Evidence from a Field Experiment, Ghent University Working Paper, No. 2013/830, 2013.
  • 4 For a review, see e.g. European Commission: Flexibility and security in the EU labour markets, Employment in Europe 2006, 2006, pp. 75-118.
  • 5 Measured in 2008, see http://stats.oecd.org/Index.aspx?QueryId=10179.
  • 6 J.J. Høj: Enhancing the Inclusiveness of the Labour Market in Belgium, in: OECD Economics Department Working Papers, No. 1009, 2013, OECD Publishing. Between 2009 and 2011, a comparable system for white-collar workers was temporarily introduced.
  • 7 B. Cockx, M. Picchio: Are Short-Lived Jobs Stepping Stones to Long-Lasting Jobs?, in: Oxford Bulletin of Economics and Statistics, Vol. 74, No. 5, 2012, pp. 646-675.
  • 8 See e.g. F. Kramarz, T. Philippon: The Impact of Differential Payroll Tax Subsidies on Minimum Wage Employment, in: Journal of Public Economics, Vol. 82, No. 1, 2001, pp. 115-146; and D. Neumark, W. Wascher: Minimum Wages, Massachusetts 2008, MIT Press.
  • 9 S. Kampelmann, F. Rycx: Who Earns Minimum Wages in Europe? New Evidence Based on Household Surveys, DULBEA Working Paper, No. 13-01.RS, Brussels 2013, Université Libre de Bruxelles, Table 3.
  • 10 For more details, see B. Cockx, B. Van der Linden: Flexicurity in Belgium. A reform proposal based on economic principles, in: International Labour Review, Vol. 149, No. 3, 2010, pp. 361-372; and B. Cockx, Van der Linden: Quelle protection de l’emploi en Belgique?, Regards économiques, Focus, 19 April 2013.
  • 11 Currently, the reduced rate is 70 per cent for those under 17, gradually increasing to 100 per cent by the age of 21.
  • 12 B. Cockx, H. Sneessens, B. Van der Linden: Evaluation micro et macroéconomique des allégements de la (para)fiscalité en Belgique, Gent 2005, Academia Press. P. Cahuc, S. Carcillo, K.F. Zimmermann: L’emploi des jeunes peu qualifié en France, in: Les notes du conseil d’analyse économique, No. 4, 2013, pp. 1-12.
  • 13 M. Dejemeppe, B. Van der Linden: Les soutiens financiers à la création d’emploi, Etude pour la Maison des Entreprises wallonnes ASBL, IRES, Université catholique de Louvain, Louvain-la-Neuve 2013.
  • 14 Ibid.
  • 15 We ignore the small German Community.
  • 16 From 15 years onwards, only part-time education (alternating with work) is compulsory, but this concerns very few pupils.
  • 17 In most OECD countries compulsory education ends at age 16; see OECD: Equity and Quality in Education. Supporting Disadvantaged Pupils and Schools, Paris 2012, OECD Publishing, p. 83.
  • 18 Ibid, p. 56.
  • 19 Ibid, p. 49.
  • 20 G. Schwerdt, M.R. West: The Effects of Test-based Retention on Student Outcomes over Time: Regression Discontinuity Evidence from Florida, IZA Discussion Paper Series, No. 7314, 2013.
  • 21 M. Piopiunik: The Effects of Early Tracking on Student Performance: Evidence from a School Reform in Bavaria, Ifo Working Paper, No. 153, 2013.
  • 22 C. Biavaschi, W. Eichhorst, C. Guilietti, M.J. Kendzia, A. Muravyev, J. Pieters, N. Rodríguez-Planas, R. Schmidl, K.F. Zimmermann: Youth Unemployment and Vocational Training, IZA Discussion Paper Series, No. 6890, 2012.
  • 23 See OECD, op. cit.; and OECD: Action Plan for Youth, Paris 2013, OECD Publishing.
  • 24 See http://www.cpu.cfwb.be/.
  • 25 OECD: Activating the Unemployed: What Do Countries Do, in: Employment Outlook, 2007, pp. 207-242.
  • 26 B. Cockx, M. Dejemeppe, B. Van der Linden: Evaluation de l’activation du comportement de recherche d’emploi, Gent 2011, Academia Press; and B. Cockx, M. Dejemeppe: Monitoring job search effort: an evaluation based on a regression discontinuity design, in: Labour Economics, Vol. 19, No. 5, 2012, pp. 729-737.
  • 27 These subsidies are the sum of the “targeted” reductions in the employer’s social security contributions and a subsidy from the federal unemployment agency (ACTIVA).
  • 28 This takes the form of a reduction of the employee’s social security contributions.
  • 29 P.Z. Schochet, J. Burghardt, S. McConnell: Does Job Corps Work? Impact Findings from the National Job Corps Study, in: American Economic Review, Vol. 98, No. 5, 2008, pp. 1864-1886.
  • 30 Recently, P. Cahuc et al., op. cit.; and OECD, 2013, op. cit. pleaded for similar schemes.
  • 31 B. Cockx, C. Goebel, B. Van der Linden: Politiques d’activation pour des jeunes chômeurs de longue durée sans expérience de travail, Gent 2004, Academia Press.
  • 32 Ibid.
  • 33 B. Cockx, M. Picchio: Scarring effects of remaining unemployed for long-term unemployed school-leavers, in: The Journal of the Royal Statistical Society: Series A (Statistics in Society), forthcoming.

Spanish Youth Unemployment: Déjà Vu

Up to 2007, youth employment rates in Spain rose steadily for more than a decade, and the Spanish economy appeared to be on its way to bridge a persistent gap with the leading economies of Europe. However, since the onset of the Great Recession, this favourable trend has reversed. The employment rate for the age group 16-24 has dropped by more than 27 percentage points, from a peak of 45.2 per cent in 2007 to a trough of 17.6 per cent in 2013, thereby eliminating all of the gains achieved during the preceding long expansion.

Over the same period, the youth unemployment rate has almost tripled. While this rate bottomed out at about 20 per cent in 2007, it now stands at a record level of 57.2 per cent. This unmatched increase in youth unemployment has turned Spain into the EU country with the second-highest youth unemployment rate, just behind Greece, despite that country’s much more dramtic GDP decline.

It should be made clear from the outset that the problems in the Spanish youth labour market are far from new. Spain has suffered from youth unemployment rates above 40 per cent on three separate occasions during the last thirty years – in the mid-1980s, the mid-1990s and today – as illustrated in Figure 4. Furthermore, this graph also shows that the ratio between the unemployment rates of the youth and the adult populations has stabilised at a value of 2.3 since the early 1990s. It is noteworthy that this value is almost identical to the European average and substantially lower than the corresponding ratio for countries such as Italy, Sweden or the UK.

Figure 4
Youth unemployment rates and ratio of youth-to-adult unemployment rates

Source: Spanish LFS (EPA).

What makes Spain an outlier, though, is the high cyclical volatility of total unemployment. During the 2009 trough, the reduction in GDP was moderate in international comparison. Yet the Spanish economy destroyed more jobs per percentage point reduction in GDP than any other OECD country, explaining in this fashion the steep rise in unemployment.1 In fact, the left panel of Figure 5 shows that the fall in employment has been much larger than the drop in real GDP, a feature that is not observed in other countries, including those suffering the burst of a housing bubble. Moreover, the employment losses are concentrated in temporary jobs (as indicated in the right panel of Figure 5). Labour costs, on the contrary, failed to adjust until quite recently. Indeed, average real wages set in collective bargaining agreements kept rising until 2012 despite the steep rise in unemployment.2

Figure 5
The cyclical dynamics of the Spanish labour market

Sources: EPA and Spanish National Accounts (INE).

These pieces of evidence suggest that the high levels of youth unemployment in Spain are a reflection of structural problems in the labour market that affect workers of all ages, and not just the young. Strategies to fight youth unemployment should therefore prioritise policy changes that improve the overall performance of the Spanish labour market, achieving not only a reduction in the unemployment level but also in its cyclical volatility. In our view, this requires much stricter limits on the widespread use of fixed-term contracts.

However, implementing this type of policy may not suffice. Further reforms should also be designed to address severe problems in the school-to-work transition of Spanish youth and to reduce the mismatch between skills supply and demand. The absolute priority in this respect is to adopt policy measures that achieve a substantial reduction in the still unsustainably high school dropout rates.

During the preceding expansion, the boom in the construction sector, induced by the strong decline in real interest rates when Spain accessed into the euro area, generated a strong demand for low-educated workers. As a result, Spain ranked among the European countries with the highest employment rates for youth with at most lower-secondary education.3 Given these excellent employment opportunities and the concomitant relatively high wages in that sector, many young males dropped out of school when they were 16, the age at which compulsory education ends. Unfortunately, when the real estate bubble burst, they lost their jobs and today most of them remain jobless without clear employment prospects for the future.

A small share of the jobless dropouts has returned to education, but the vast majority remains unemployed. The result is an alarmingly high number of low-educated workers under 30 (1.1 million, almost 24 per cent) who are neither in employment nor in education or training (NEET). Almost half of them have completed no more than primary education, while the rest dropped out of education after completion of compulsory lower-secondary education. Moreover, it is important to make a distinction between the age groups 16-24 and 25-30. In effect, while the number of NEET in the first group has been falling since 2009, the size of the second group continues to rise, especially among those young people with no more than primary education attainment. For these workers, a return to education is often not an option, as many have family duties and mortgages to pay. Solutions should therefore come primarily from fostering dual vocational training as the most important channel, which would allow these individuals to get new skills for future alternative occupations while providing them and their families with a means of living.

During a future recovery, firms may be willing to satisfy some of the training needs through the creation of subsidised training jobs, but they may be reluctant to hire those NEET youth who have remained jobless for several years. Currently, there are over 300,000 young workers below 30 with no more than lower-secondary education who have been unemployed for more than two years. Prior to the crisis, these disadvantaged workers still managed to exit unemployment at a quarterly rate of 15 per cent.4 However, since the outbreak of the Great Recession, job-finding rates have plummeted without any signs of recovery in the near future. At present, the exit rate out of unemployment for low-educated workers (of all ages) lies around 10 per cent after the first month, and it falls well below 5 per cent after two years of unemployment. These figures clearly indicate that there is a substantial risk that many young NEET youth will be excluded from the labour market for years to come.

Dual labour markets and excess volatility

In a recent study for the OECD, we analysed data for various European countries in order to provide a cross-country perspective of the main determinants of the dismal performance of the youth labour market in Spain, both before and during the crisis.5 This study complements earlier work by some of us analysing the underlying reasons behind the resistance to implementing more efficient reforms in the Spanish labour market6 and the factors that contribute to its excessive volatility.7 All of this available research points at the importance of the dual structure of employment protection in Spain as a key element in explaining its dysfunctional labour market.

Before the crisis, Spain was one of the OECD countries with the most stringent employment protection for permanent contracts. By contrast, fixed-term contracts could be terminated at virtually no cost, with hardly any control on their fraudulent use by many firms. Due to these features, Spanish employers not only have traditionally created a large number of temporary contracts (about 92 per cent of the overall number of contracts signed each year) but also have been very reluctant to convert them into permanent jobs once the legal limit on renewals is reached (the temporary-to-permanent conversion rates never exceeded 12 per cent during the expansion, and they have fallen to five per cent during the current slump).

Bentolila et al. and several other related studies use state-of-the-art dynamic matching models in segmented labour markets to demonstrate that the dual structure of employment protection amplifies the cyclical fluctuations in unemployment.8 The rationale behind this effect is simple. The ease to create and destroy fixed-term positions leads to strong job creation during expansions, but a considerable share of these jobs are of low quality. Hence, when recessions arrive, most of them are destroyed. It is also clear that youth bear most of the burden of this excessive volatility, as they are clearly over-represented among workers holding temporary contracts. Conversely, the system grants older workers with permanent contracts a high level of job stability, as firms prefer to use temporary contracts as a buffer stock against demand fluctuations.

In our 2010 study, we corroborate this last finding with the help of international survey data on workers’ perceived employment stability.9 In this survey, Spanish teenagers and young adults report a substantially lower average level of perceived job stability than their counterparts in other developed countries, while the opposite is true for older workers. Moreover, both the rules for the election of union representatives and the rigid system of collective bargaining exacerbate dualism. This is because unions have an incentive to represent the interests of their median voters, i.e. insiders (workers with permanent contracts) at the expense of the outsiders (the unemployed and workers with temporary contracts). As documented in Bentolila and Dolado, this last feature also helps explain why bargained wages in Spain failed to adjust in the last two major recessions despite the strong increase in unemployment: unions asked for unjustified high wages for their members, anticipating that firms would adjust employment via cuts in temporary employment.10

Finally, as mentioned earlier, in Dolado et al. we use micro data from various sources to compare the performance of the youth labour market of Spain to that of four reference countries (France, Germany, the Netherlands and the UK).11 First, we document that the high incidence of temporary contracts with very short durations poses severe difficulties for the school-to-work transition of Spanish youth. Second, we identify those shortcomings in the Spanish educational system which are mainly responsible for the skill bottlenecks in the labour market. By contrast, alternative explanations, such as cross-country differences in the sectoral composition of employment (e.g. in the weight of seasonal activities in services industries like tourism), are shown to explain a relatively small share of the differences in employment rates. Below we briefly review some of this evidence before drawing useful policy implications.

Table 2
Time needed to find a first regular job after leaving education, 15-34-year-olds
Months since leaving education Percentage who have not found a regular job Average time needed to find a job, in months
Spain France Netherlands UK Spain France Netherlands UK
13-24 40.4 25.5 6.1 10.7 4.1 3.7 2.1 3.1
25-36 28.1 17.3 5.4 8.3 6.3 6.2 3.6 4.2
37-48 18.5 12.9 5.8 8.1 9.3 5.7 5.2 4.3
49-60 19.7 15.4 5.0 4.3 12.8 6.7 6.3 4.4

Source: J.J. Dolado, F. Felgueroso, M. Jansen, A. Fuentes, A. Wölfl: Youth Labour Market Performance in Spain and its Determinants: A Micro-Level Perspective, OECD Economics Department Working Papers, No. 1039, 2013, based on 2009 EU Labour Force Survey, ad hoc module.

Temporary contracts fail to act as stepping stones towards stable jobs

In the late nineties, young workers in Spain were much more likely to hold a temporary contract than their counterparts in the reference countries. Yet in recent years, the temporary employment rates for youth in Spain have dropped to about 60 per cent, in line with those observed in the reference countries (with the exception of the UK).12

What makes Spain unique is the persistence of fixed-term employment throughout the working lives of employees. While almost 40 per cent of workers without a university degree and 20 per cent of the university graduates in Spain still hold temporary contracts at the age of 39, the corresponding fractions in the reference countries are at most 15 per cent and ten per cent respectively. In other words, while fixed-term contracts often act as stepping stones towards more stable employment in most EU countries, they often become dead-end jobs in Spain.

The same picture arises when the self-reported reasons for the use of temporary contracts are analysed. In France or Germany, the vast majority of these contracts cover a training period (as apprentices or trainees), while 46 per cent of the teenagers in the Netherlands and 63 per cent in the UK declare their preference for such contracts over permanent contracts. In stark contrast to these figures, around 60 per cent of teenagers and 77 per cent of youth aged 20-24 across all sectors in Spain declare that they accepted a temporary contract because they failed to find a permanent job.

Time to find a first regular job

Not surprisingly, the high turnover on temporary contracts leads to considerable problems in the school-to-work transition of youth in Spain. The time required before a school leaver finds a first regular job (defined as a job that lasts for more than three months) is significantly longer than in the reference countries, and this difference already existed before the crisis.

Our estimates, based on a survey carried out in 2009, indicate that almost 20 per cent of the 15-34-year-olds who left education for good three to five years before being interviewed still had not found their first regular job, as compared to five to six per cent in the Netherlands or the UK. Additionally, those who had not managed to find their first regular job after five years in the labour market had to wait on average longer than 12 months, compared to six months in the Netherlands and only four months in the UK.13 Similarly, 57 per cent of the school leavers in the Netherlands found a regular job within their first month in the labour market, while the corresponding figure for Spain is 23 per cent.14

One factor that helps account for these differences is the amount of work experience acquired by young people while studying. While this sort of work experience significantly reduces the required time to find a regular job in the reference countries, no significant effects are found in Spain. Furthermore, the work experience acquired during interruptions of studies also contributes to a quicker transition from school to regular employment, but very few students use this option in Spain.

Finally, it is worth mentioning that, relative to natives, having an immigrant status exerts a much stronger negative effect on the length of the school-to-work transition in Spain than in the reference countries.15

Poor match between the demand and supply of skills

Although our OECD study considers a wide range of determinants of the delays in the school-to-work transition of Spanish youth – including demographic factors and the lack of a well-developed rental market for housing – for brevity we focus below exclusively on one of the main determinants, namely the shortcomings of the Spanish educational system.

High dropout rates

The biggest challenge for Spain is to achieve a substantial reduction in the share of early school leavers.16 While this rate has fallen from 32 per cent to 25 per cent during the ongoing crisis, it remains more than twice as high as in many other European countries. Unless Spain manages to keep more students in education until they have at least completed upper-secondary education, structural problems in the labour market will remain persistent because the relative demand for this type of worker will not return to its pre-crisis level.

Few students choose vocational education or training

Next, among the students who do complete upper-secondary education, the vast majority opt for general education, while very few students follow vocational training tracks. Broadly speaking, while this ratio is about 50:50 in Central European countries, in Spain it is 67:33. The result is a supply distribution of skills which looks like an hourglass: while most workers are either placed at the top (those with tertiary education) or at the bottom (school dropouts) of the skills distribution, relatively few people in Spain have intermediate (vocational) degrees. To document this feature, Table 3 reports the orientation of the highest degree obtained by individuals in the age group 15-34 with at least lower-secondary education who left education between 2002 and 2009.

Table 3
Orientation of the highest degree obtained in formal education
in %
Orientation Spain France Germany UK Netherlands
General education 80.2 39.0 21.9 57.1 23.1
Vocational education 19.8 61.0 78.1 42.9 76.9
Mainly school-based 17.6 37.8 1.7 6.7
Dual training 1.9 0 75.2 0
Mainly work- place-based 0.2 21.6 1.2 31.7
No distinction possible 0.1 1.6 0 4.5 76.9

Source: Calculations based on the 2009 ad-hoc module of the EU LFS.

As can be observed, the percentage of individuals in Spain who obtained their last degree in general education is much larger (80.2 per cent) than in the reference countries, while only a small fraction of those who finished vocational training were enrolled in a programme that offered training at a workplace. This sharply contrasts with the figures from Germany, where 78.1 per cent opted for vocational education and 75.2 per cent for dual or apprenticeship training. Interestingly, additional evidence shows that only seven per cent of Spanish teenagers work outside their educational programmes. Overall, a clear implication of this evidence is that the relevant work experience of youth joining the labour market in Spain is definitely insufficient.

Skill and qualification mismatch

The poor match between the skills supplied by school leavers and the skills demanded by employers leads to bottlenecks (i.e. mismatches) in the labour market. The degree of mismatch in Spain, both in terms of skills and qualifications, is high by international standards and, moreover, this unfavourable gap holds across all educational levels.

A simple index of the degree of over-qualification that is easily comparable across countries is the share of individuals with tertiary education who work as managers or professionals (ISCO classification 1 and 2). The lower this share, the higher the level of over-qualification. Using data from the yearly subsamples of the EU LFS corresponding to 2002-2010, we find that this fraction is only around 40 per cent, compared to rates of over 60 per cent in the Netherlands. Moreover, the Spanish share has been following a marked downward trend since 2002.

Many of the over-qualified individuals with tertiary education end up in jobs that are more suitable for workers with upper-secondary education, forcing the latter to seek even less demanding jobs.17 Indeed, in the age group 30-34, the share of individuals with upper-secondary education who work in elementary occupations (ISCO classification 8 and 9) rose by almost ten percentage points between 2002 and 2008. This share reached a high of 23 per cent, which is more than twice the rate of around ten per cent found in Germany and the Netherlands. From 2008 to the present, the rate has fallen sharply but still remains around 20 per cent.

Survey evidence based on questions about a worker’s suitability for her/his current job leads to similar results. In the age group 16-29, 40 per cent of Spanish workers with a general education degree at the upper-secondary or tertiary level consider themselves over-qualified for their jobs, relative to 28 per cent and 32 per cent for those with equivalent vocational degrees.18 Interestingly, however, the data from the European Survey of Working Conditions suggest that the international differences in the degree of skill mismatch are smaller than the differences in qualification mismatch. This observation may confirm earlier findings by the OECD showing that the Spanish share of over-qualified workers is only slightly higher than the European average.19 The smaller differences in skill mismatch suggest that the correlation between degrees and skill levels is less favourable in Spain than elsewhere in the EU.

Policy lessons

Since 2010, the Spanish labour market has undergone three reforms and, on top of those, the government announced a new plan earlier this year to foster youth employment. All of these initiatives are based on a correct diagnosis of the problems but, with the exception of the changes in the system of collective bargaining implemented in the 2012 reform, this has unfortunately not led to the adoption of adequate corrective measures.

In particular, the authorities are still hesitant to implement far-reaching measures to eradicate the dual structure of the labour market. The above-mentioned reforms have reduced the gap in employment protection between permanent and fixed-term positions, but none of them tackled the root of the problem. The firing costs in case of unfair dismissals are still high by international standards and, rather than restricting the use of fixed-term jobs, the Spanish authorities have (temporarily) removed the restrictions on the renewal of fixed-term positions. In addition, they have introduced new precarious contracts like the Contrato de Apoyo a los Emprendedores for firms with less than 50 employees. On paper, this heavily subsidised contract for SMEs creates an open-ended position. However, workers hired on these contracts may be laid off at no cost during a probation period of 12 months. The incentives to rotate workers on these contracts are therefore even stronger than in the case of most temporary contracts. This diagnosis seems to be clearly supported by the fact that only eight per cent of all permanent contracts and 30 per cent of those in SMEs have been signed under this new format during its first 18 months in operation.

The stimulus plan for youth employment, the Estrategia de Emprendimiento y Empleo Joven, contains similar flaws. The plan includes some novel measures to help young entrepreneurs start their own businesses, but the rest of the plan simply consists of extending hiring subsidies for a whole range of precarious positions, including temporary part-time jobs with no clear training content. Hiring subsidies for temporary or part-time jobs may be a useful instrument to provide initial work experience to labour market entrants. However, the widespread use of hiring incentives is clearly inefficient, as previous experience with these policies has shown that they generate substantial deadweight losses and undesirable substitution effects between subsidised and non-subsidised workers.20

Given the tight budget constraints and the large number of low-educated NEET youth, it would have been better to restrict subsidies to contracts with a clear training content, such as the Contrato para la Formación y el Aprendizaje. The 2012 reform temporarily extended the age limit from 25 to 30 for this type of contract, meant to offer workplace training to workers without upper-level secondary education. Currently, there are almost 250,000 low-educated NEETs in this age group who would qualify for such a contract. However, workplace-based training will only be a success if it is financially attractive to firms. The social partners should therefore refrain from setting training wages above the level of the statutory minimum wage (about €750 per month). Even so, firms still remain reluctant to hire older NEETs who have been unemployed for several years. Under the current rules, this group only has access to training as part of an active labour market programme if they are entitled to the welfare subsidy for unemployed workers.21 It is crucial to expand the scope of these programmes to all workers at risk of social exclusion.

For the youngest NEETs, the authorities should opt for measures that stimulate their return to the educational system. In this respect, the region of Extremadura recently launched an initiative that allows high school dropouts to complete their mandatory secondary education (ESO) in a special programme of six months. If successful, the programme should be introduced nationwide, as this educational degree provides access to further training or education.

To conclude, the Spanish government will need to step up its efforts to improve youth employment prospects and to offer solutions to those who entered the labour market with insufficient skills. Otherwise, it will be difficult to prevent the mistakes that were made during the boom preceding the crisis from leaving permanent scars on an entire generation of youth. The introduction of a youth guarantee, as recently proposed by the European Commission, sounds attractive, but this measure is only feasible if the government first introduces effective measures to reduce the excessive rate of worker turnover. In this respect, our viewpoint is that it is indispensable that the government introduces what is known as a single open-ended contract with gradually increasing severance pay that converges to a reasonable upper bound which is lower than the current severance pay for unfair dismissals. This new contract should replace most of the existing (temporary) contracts.22

Finally, the current slump illustrates that it is of utmost importance to deter young people from entering the labour market without the minimal credentials to guarantee access to stable employment. In the future, Spain should envisage the option of increasing the mandatory schooling age to 18 for those who have not yet completed upper-level secondary education or equivalent vocational education. However, before this becomes a real option, the country would need to strengthen its system of vocational training. This can be done through an extension of the apprenticeship system that is currently being tested in many regions, as well as by offering students the option to start with vocational education before completion of the ESO. The education reform that is currently under discussion contains several proposals along these lines. Insofar as it guarantees unrestricted access to further education or training to those who opt for basic vocational training at an earlier age, the reform could help in converting youth employment experiences into a real stepping stone to a stable career. However, the current across-the-board budgetary cuts in education may endanger this goal.

This paper has received the financial support of the EU (DG Employment, Social Affairs and Inclusion of the European Commission).
The opinions expressed are those of the authors only and do not represent the European Commission’s official position.

  • 1 See e.g. T. Boeri: Institutional Reforms and Dualism in European Labor Markets, in: Handbook of Labor Economics, Vol. 4, Part B, pp. 1173-1236.
  • 2 Average growth in nominal wages in newly signed collective agreements deflated by the consumer price index.
  • 3 J. Dolado, F. Felgueroso, M. Jansen, A. Fuentes, A. Wölfl: Youth Labour Market Performance in Spain and its Determinants: A Micro-Level Perspective, OECD Economics Department Working Papers, No. 1039, 2013, Table 40.
  • 4 Bank of Spain: Boletín Económico, May 2012.
  • 5 J. Dolado et al., op. cit.
  • 6 J. Dolado, F. Felgueroso, M. Jansen: El Conflicto entre la Demanda de Flexibilidad Laboral y la Resistencia a la Reforma del Mercado de Trabajo en España, in: Papeles de la Economía Española, No. 124, 2010, pp. 84-97.
  • 7 See e.g. S. Bentolila, J. Dolado, J.F. Jimeno: Reforming an Insider-Outsider Labor Market: The Spanish Experience, in: IZA Journal of European Labor Studies, Vol. 1, No. 4, 2012.
  • 8 S. Bentolila, P. Cahuc, J. Dolado, T. Le Barbanchon: Two-Tier Labour Markets in the Great Recession: France vs. Spain, in: The Economic Journal, Vol. 122, pp. 155-187, 2012.
  • 9 J. Dolado et al.: El Conflicto entre …, op. cit.
  • 10 S. Bentolila, J. Dolado: Labour Flexibility and Wages: Lessons from Spain, in: Economic Policy, Vol. 18, 1994, pp. 55-99.
  • 11 J. Dolado et al.: Youth Labour Market …, op. cit.
  • 12 For comparison, the overall share of temporary contracts before the Great Recession hovered around 32 per cent, whereas since the crisis, it has dropped to less than 25 per cent, due to the intense destruction of temporary jobs (85 per cent of all destroyed jobs).
  • 13 See J. I. García Pérez: ¿Qué Efectos Tendría un Contrato Único sobre la Protección del Empleo?, in: J.J. Dolado, F. Felgueroso (eds.): Propuesta para la Reactivación Laboral en España, Fedea, 2010 for comparable evidence on the time elapsed before a Spanish school leaver obtains a permanent job.
  • 14 We lack comparable data for Germany, but it is well documented that over 80 per cent of the apprentices there remain with their training firm upon completion of education.
  • 15 These are defined as nationals from countries outside the EU15, regardless of whether they were born in Spain.
  • 16 Individuals aged 18-24 with at most lower-secondary education who are neither in formal education nor in training.
  • 17 J. Dolado, M. Jansen, J.F. Jimeno: On-the-Job Search in a Matching Model with Heterogeneous Jobs and Workers, in: The Economic Journal, Vol. 119, 2009, pp. 200-228.
  • 18 These calculations are based on four waves of the Encuesta de Condiciones de Vida en el Trabajo (ECVT) for the time period 2006-2010. The reported numbers refer to averages over this time period.
  • 19 G. Quintini: Right for the Job: Over-Qualified or Under-Skilled, OECD Social, Employment and Immigration Working Papers, No. 120, 2011.
  • 20 J.I. García Pérez, Y. Rebollo: The Use of Permanent Contracts across Spanish Regions: Do Regional Wage Subsidies Work?, in: Investigaciones Económicas, Vo. 33, No. 1, 2009, pp. 97-130.
  • 21 This means-tested welfare subsidy of €426 per month is provided during a period of at most six months to those unemployed workers who have exhausted their entitlement to unemployment benefits. Participation in active labour market programmes is mandatory for all participants.
  • 22 For a detailed proposal, see S. Bentolila, J. Dolado, J.F. Jimeno: Reforming an Insider-Outsider Labor Market: The Spanish Experience, in: IZA Journal of European Labor Studies, Vol. 1, No. 4, 2012.

Enhancing Youth Opportunities in Employment: Determinants and Policy Implications

It is a commonly known fact that young people face several challenges when entering the labour market. More­over, a number of institutions have argued that young people were additionally affected by the recession beginning in 2008.1 The weakening of the global recovery in 2012 and 2013 has further aggravated the youth job crisis. In the majority of OECD countries, at least a third of young jobseekers were unemployed for at least six months, and the global youth unemployment rate is projected to rise to 12.8 per cent by 2018, up from 11.5 per cent prior to the crisis.2

Since 2009, little progress has been made in reducing youth unemployment in developed economies and in the European Union in particular. The need to focus more on youth is now central to the European policy debate, and the term is explicitly mentioned in the Europe 2020 agenda as well as in the 2012 European Commission employment package, “Towards a job-rich recovery”.3 The Europe 2020 flagship initiative “Youth on the Move” aims at “unleashing all young people’s potential” and clearly emphasises the importance of focusing on youth in general and on young people who are not in employment, education or training (NEETs) in particular.4

Consequently, the need for additional indicators to identify these NEETs has emerged. However, the heterogeneity of NEETs has proven to be problematic for policy makers. This has important implications for policy responses. The NEET concept includes different groups that are characterised by common vulnerabilities but that may have different needs. Thus, while governments are correct to set targets to reduce the overall levels of NEET youth, it has been emphasised that they should also plan their interventions by disaggregating the NEET category.5 This has been a neglected part of the research into this topic thus far.

Consequently, the aim of this paper is to identify the characteristics and needs of the various subgroups of the youth population that require distinct forms of policy interventions. More specifically, using Poland as a case study, I develop a categorisation of young people based on their labour status, their ability to seek a job and their educational activity. Next, I analyse the changes in this distribution over time. Using this categorisation, I then explore in greater depth how the labour status of young people is to be interpreted within the context of their family and intergenerational background, their values, and the economic barriers they must overcome in order to gain employment. Finally, I make an attempt to identify the extent to which educational programmes offered by public and private institutions enhance chances to reach economic independence in each group of young workers. The differences among young people may imply that programmes should be focused on selected groups of young people in order to be more effective in improving youth employability.

For the current study, based on the 2000-2011 period, the Social Diagnosis Survey database is used. It examines the conditions and quality of life of Polish families. It investigates all the significant aspects of individual households and their members, including economic (income, wealth, etc.), social (education, personal values, well-being, etc.) and additional factors.

Polish youth labour market in comparison with the EU25

Some convergence in the distribution of the youth unemployment rates of Poland and the EU25 was observed until 2008 (see Figure 6). While the youth unemployment rate in Poland was almost twice as high as the EU average in 2002, it continuously declined through the end of 2008, when it reached a level comparable to the EU25 rate (17 per cent compared to the EU25 average of 15 per cent). Throughout this period, the EU youth unemployment rate had been rather stable. From 2008 on, however, the unemployment rate began to increase in both areas.

Figure 6
Labour market status of young people in Poland and the EU25

Source: Own calculations based on Eurostat data.

The gap between the EU and Polish youth employment rates slightly decreased in the period 2000-2012, as the EU rate shrank marginally while the Polish rate grew a bit. Nonetheless, the Polish rate remained nine percentage points below the EU average in 2012. The shrinking gap might be the result of the “educational boom” that has taken place during the past 15 years. The small increase in the Polish youth employment rate through 2008, however, was primarily related to non-standard jobs, including temporary employment and part-time work. Indeed, since the mid-1980s, all EU countries have moved in the direction of labour market deregulation and contract flexibility, with the principal aim of enhancing job opportunities for the young.6

We observe some divergence in the distribution of the inactivity rate between Poland and the EU25. While in Poland the inactivity rate slowly worsened from 60 per cent in 2001 to 66.4 per cent in 2011/12, it followed a downward path in the EU25, improving from 46 per cent in 2001 to 43.6 per cent in 2011. The increase in Polish inactivity might be the consequence of the entry of Polish “baby boomers” from the 1980s into the labour market.

Between 2001 and the onset of the crisis, the NEET rate had sharply decreased in Poland. As participation in education expanded (leading to a higher inactivity rate) and as the economy improved in the first part of the last decade, the number of young people who were NEET began falling, from nearly 18 per cent in 2001 to a low of nine per cent in 2008. At that point, it was lower than the EU average by two percentage points. Thereafter, the NEET rate started to increase sharply, but it still remained below the average EU25 rate (see Figure 7).

Figure 7
NEET rates in Poland and the EU25

Source: Own calculations based on Eurostat data.

According to the 2011 EU Labour Force Survey (LFS), the NEET population was split into two almost equally sized groups: just over half (51.2 per cent) were registered as unemployed, and just under half were registered as inactive (48.8 per cent). In countries in which the majority of NEET youth are classified as inactive, a structural problem might exist in engaging young people with the labour market or the education system. Analysis of the temporal trends in the labour market status of NEETs shows that the “inactive” proportion has remained stable over the years and seems to be less sensitive to business cycles. Conversely, the unemployment NEET subgroup is much more responsive to business cycles.

Finally, according to an analysis of micro-data from the 2009 EU LFS, 63 per cent of inactive NEETs in Europe stated that they were available to start working within two weeks but that they are not looking for a job. Among those who were available to work, only 20 per cent were not looking for a job because of personal unavailability due to family responsibilities. Meanwhile, almost 39 per cent of inactive NEETs were not seeking a job because they believed that there was no work available.

Data and methodology

Dependent variable

In order to take into account the heterogeneity of the youth population, I follow the extended Eurofound report on NEETs.7 The report analyses the impact of personal characteristics on NEET youth. I expand their work by disaggregating labour market statuses into eight categories and translating them into the dependent variable. The resulting subgroups within the youth population are identified in Figure 8.

Figure 8
Youth labour market statuses

Source: Own illustration.

The reason for using this disaggregation is twofold. First, the NEET category contains a variety of subgroups which have very different personal experiences, characteristics, education levels and attitudes toward job seeking. As stated in the Eurofound report, when designing policies to re-engage NEET youth with the labour market or with education, a one-size-fits-all approach should be avoided.8 The categorisation presented here might serve as a guide to assist with policy decisions. Second, employment-seeking activity appears to be a characteristic which varies significantly among various NEET youth subgroups.9 Differentiating by this category enables us to identify the most vulnerable youth groups.

Independent variables

The literature suggests that there are two principal risk factors relating to vulnerable NEET status: disadvantage and disaffection.10 While educational disadvantage is associated with social factors such as family, school and the personal characteristics of the young person, disaffection is concerned with the attitudes young people have towards life in general and schooling in particular, as expressed by truancy or behaviour that leads to school exclusion. Both educational disadvantage and disaffection are linked to a number of background factors. These include family background, having one or both parents unemployed, economic deprivation,11 living in a high unemployment area, large family size12 and poor housing.13 At the individual level, they include academic attainment,14 membership of an ethnic minority group, religiousness, and having a chronic illness or disability.15

This information serves as the background for the creation of a list of independent variables, grouped into five categories:

  • Individual characteristics, including gender, marital status, disability, level of education, foreign language knowledge and whether an individual has studied abroad;
  • Intergenerational household and family features, approximated by the number of household members, father’s educational level and source of main household income (a proxy for workless households);
  • Economic barriers, approximated by the regional unemployment rate in the place of residence at the NUTS 2 level;
  • Civic engagement and personal values, represented by religiousness, political activity, being a member of an association, and whether an individual agrees with the statements that everyone has their fate in their own hands, that it is important to have material goods, that it is important to be good-looking, and that it is important to treat everybody equally;
  • Educational training programmes, defined as participation within the last two years in a training programme financed by national, EU or private sources.

The current analysis uses the fifth wave of the 2011 Social Diagnosis Survey with a total sample of over 10,000 observations of young people aged 16-24. The characteristics of labour market status are investigated through the multinomial logit model.

Figure 9
Changes in Polish youth labour market statuses

Source: Own calculations based on Social Diagnosis Survey.


Labour market status of individuals

Figure 9 presents the changes in the structure of the labour force participation of Polish youth between 2000 and 2011. Usually the unemployment rate and the NEET rate are not comparable measures due to different assumptions about the denominator. While the former refers only to the economically active members of the population who are unable to find a job, the latter measures the share of the total population of young people who are currently not engaged in employment, education or training. In this paper, the number of youth in different labour market statuses is based on the total population of young people.

As shown in Figure 9, the share of employed youth increased from 17 per cent in 2000 to 28 per cent in 2009 before slightly decreasing in 2011. Meanwhile, the unemployment rate declined between 2000-2007 and then slightly increased in the following years.

Some interesting findings can be detected by analysing the four unemployed subgroups. For example, in 2000 the share of unemployed youth seeking a job, regardless of educational activity, was relatively high, constituting 75 per cent of all unemployed youth. This share decreased significantly through 2007 – when it dropped to 61 per cent – before beginning to rise again. The proportion of the population in the inactive subgroups seeking a job remained stable over the years and seems to be less sensitive to business cycles.

The proportion of economically inactive Polish youths slightly increased over time, mainly due to the decrease in the share of young people in education. The proportion of economically inactive NEETs that were looking for employment declined during times of prosperity and began to increase in 2009. At the same time, the share of economically inactive NEETs that were not seeking a job remained at a rather steady level until 2005 and then began to increase. This investigation of the Polish NEET population structure shows that it is split into two similarly sized groups, i.e. just around half is registered as unemployed (almost 57 per cent in 2000 and 47 per cent in 2011).

Summing up, important changes in the labour market structure are observed mainly in the groups of youths seeking jobs. During more prosperous times, the proportion of unemployed or inactive youths who are seeking employment decreases. Contemporarily, the share of unemployed or inactive young people who are not seeking employment does not seem to be sensitive to business cycles. Because they appear less affected to business cycles, this group of NEETs deserves deeper analysis.

Figure 10 presents the explanations given by NEET youth for not looking for a job and the changes in this distribution over time. Due to data limitations, we are only able to provide the descriptive analysis from 2007 on. The percentage of NEETs not seeking work due to household or family duties increased from around 35 per cent in 2007 to 53 per cent in 2011. Additionally, the personal perception that one would not find a job increased by more than six percentage points. In 2011, this sense of discouragement applied to one in ten NEETs not seeking employment.

Figure 10
Barriers to Polish NEETs pursuing employment

Source: Own calculations based on Social Diagnosis Survey.

The results highlight the fact that over half of Polish NEETs do not enter the labour market due to family and household duties. In fact, the acquisition of household services is still not so popular in Poland, and the majority of household work is provided solely by household members.16 Second, the duty of taking care of the elderly still falls upon family members, as institutional long-term care is very limited among the Polish elderly.17 Finally, the number of public kindergartens and nurseries is still insufficient, which imposes additional responsibilities on family members. The lack of social instruments undermines young people’s ability to reconcile work, family and childcare responsibilities.

Impact of personal characteristics on labour market status

For policy makers and social partners, it is crucial to understand why some young people might end up as NEET. Thus, we now focus on the individual characteristics and the household and personal factors which may increase the risks of being unemployed. The results present a high level of consistency with the general literature. Table 4 presents the estimation results of two multinomial logit models. The first model estimates the impact of personal, household and economic factors on the probability of being in one of eight subgroups of young people (called the “main model”). The second model estimates the impact of the same characteristics on the probability of being employed, unemployed or inactive (called the “standard model”). The aim of this comparison is to see whether missing information hidden behind the heterogeneity of the NEET label leads to mistaken assumptions when creating policy responses for young people.

Table 4
Descriptive statistics
in %
Variable Employed Unemployed Inactive
In education Not in education Not in education In education
Seeking employment Not seeking employment Seeking employment Not seeking employment Seeking employment Not seeking employment
Female 41.69 68.91 66.67 49.02 69.17 40.94 74.24 54.17
Married 42.93 11.76 24.44 21.63 52.08 25.73 54.78 1.87
Disabled 2.61 1.72 2.22 4.61 6.69 5.29 18.83 4.23
Higher 35.53 18.97 20 24.09 12.92 20.47 20.63 5.69
Medium 37.15 65.52 51.11 34.09 33.33 34.50 34.95 26.80
Vocational 23.92 15.52 28.89 33.48 39.58 36.26 29.98 49.35
Compulsory 35.53 18.97 20 24.09 12.92 20.47 20.63 5.69
Foreign language knowledge 78.28 89.08 95.56 70.50 54.17 63.74 61.31 92.73
Studies abroad 0.62 1.69 4.44 0.46 0 0 0.37 0.83
Intergenerational household and family characteristics
Number of household members 62.15 51.69 53.33 53.48 49.17 64.33 52.25 53.37
Father’s educational level:
Higher 8.71 3.88 9.09 5.57 2.82 7.75 5.75 11.62
Medium 21.58 21.36 9.09 17.59 10.80 13.95 17.40 24.73
Vocational 49.54 63.11 45.45 51.89 57.28 54.26 47.20 48.96
Compulsory 20.17 11.65 36.36 24.96 29.11 24.03 29.65 14.69
Source of main household income 0.99 15.13 31.11 19.21 27.50 7.60 32.77 13.01
Economic barriers
Regional unemployment 12.67 12.57 13.55 13.16 13.76 12.49 12.96 13.09
Civic engagement and personal values
Religiousness 61.15 73.33 56.82 61.11 61.32 55.91 63.65 71.70
Political activity 65.92 70.87 58.14 55.64 53.17 50.39 57.87 38.98
Member of association 11.43 8.57 13.64 5.79 2.87 6.25 8.04 15.40
Each has fate in their own hands 85.35 81.90 79.55 81.72 82.55 79.84 79.38 84.75
Important to have material goods 38.60 34.29 36.36 46.87 41.51 44.19 39.03 41.99
Important to be good-looking 92.11 93.33 95.45 90.32 92.92 92.25 92.05 92.54
Important to treat everybody equally 80.55 80.95 84.09 79.75 86.32 82.95 80.33 81.40
Training programmes 9.26 7.56 4.44 5.90 3.33 4.68 3.51 0.50

Source: Own calculations based on Social Diagnosis Survey.

Being a woman increases the chances of being unemployed regardless of educational involvement or job-hunting activity. Married people are more motivated to work, as they have to maintain their own households. The same is true for disabled people. The results of the main model reveal that these characteristics are significant only for those subgroups in which people actually seek employment, regardless of educational activity. They are statistically insignificant for those not seeking a job.

Higher levels of education decrease the chances of being unemployed. While educational level is statistically insignificant for those that remain in education, it has a relevant impact on those no longer pursuing education, regardless of their job search activity. Additional educational attainment, such as foreign language ability or studies abroad, does not have a significant impact on employment status.

Intergenerational household features also have a significant impact on labour market opportunities for youth. For example, the chances of escaping from unemployment increase in households with no more than four members. Again, this fact is only valid for those looking for a job, regardless of educational activity.

Table 5
Probability of being in one of eight subcategories of labour market statuses
Variable Unemployed Inactive
In education Not in education Not in education In education
Seeking employment Not seeking employment Seeking employment Not seeking employment Seeking employment Not seeking employment
Female 1.192*** (0.255)
0.552 (0.357)
0.788*** (0.108)
1.588*** (0.194)
0.076 (0.211)
1.886*** (0.125)
1.191*** (0.084)
Married -1.748*** (0.328)
-0.468 (0.359)
-1.084*** (0.118)
0.072 (0.177)
-0.509** (0.209)
0.797*** (0.114)
-3.555*** (0.174)
Disabled -1.662* (0.949)
-1.347 (1.137)
-0.801*** (0.278)
-0.575 (0.402)
-0.187 (0.493)
1.158*** (0.207)
-0.839*** (0.208)
Higher 13.281 (115.335)
12.407 (907.119)
-0.952*** (0.262)
-2.587*** (0.39)
-1.357*** (0.435)
-1.961*** (0.239)
-4.058*** (0.216)
Medium 15.083 (115.335)
13.505 (907.119)
-0.591** (0.245)
-1.191*** (0.303)
-0.849** (0.383)
-1.281*** (0.217)
-1.990*** (0.189)
Vocational 14.485 (115.335)
13.899 (907.119)
-0.049 (0.231)
-0.789*** (0.284)
-0.559 (0.356)
-0.821*** (0.208)
-0.229 (0.179)
Foreign language knowledge 0.444 (0.404)
3.419** (1.419)
0.125 (0.362)
-0.688*** (0.194)
-0.236 (0.241)
-0.146 (0.131)
2.304*** (0.141)
Studies abroad 1.971** (0.816)
-0.198 (1.765)
-1.438 (1.366)
-14.434 (2693.12)
-15.556 (2976.08)
-1.671 (1.773)
0.531 (0.453)
Intergenerational household and family characteristics
Number of household members -0.844*** (0.252)
0.036 (0.398)
-0.413*** (0.107)
-0.098 (0.172)
0.263 (0.217)
-0.248** (0.109)
-0.255*** (0.084)
Father’s educational level:
Higher 0.033 (0.663)
-0.124 (0.553)
-0.337 (0.259)
-0.471 (0.576)
0.292 (0.409)
0.382* (0.223)
1.718*** (0.165)
Medium 0.707 (0.453)
-1.317** (0.544)
-0.02 (0.17)
-0.546 (0.337)
-0.05 (0.332)
0.26 (0.164)
1.284*** (0.136)
Vocational 0.592 (0.41)
-1.201*** (0.407)
0.107 (0.134)
0.253 (0.199)
0.12 (0.253)
-0.069 (0.132)
0.382*** (0.118)
Source of main household income 2.997*** (0.356)
4.126*** (0.378)
3.075*** (0.195)
3.236*** (0.246)
1.663*** (0.419)
3.195*** (0.188)
3.074*** (0.186)
Economic barriers
Regional unemployment -0.007 (0.042)
0.02 (0.057)
0.066*** (0.017)
0.088*** (0.027)
-0.008 (0.034)
0.006 (0.018)
0.027** (0.013)
Civic engagement and personal values
Religiousness 0.435 (0.267)
0.02 (0.057)
0.115 (0.107)
0.16 (0.181)
-0.116 (0.199)
0.076 (0.11)
0.643*** (0.083)
Political activity 0.219 (0.265)
-0.024 (0.361)
-0.041 (0.107)
-0.129 (0.173)
-0.514** (0.199)
-0.095 (0.108)
-0.661*** (0.082)
Member of association -0.554 (0.456)
0.434 (0.461)
-0.805*** (0.224)
-0.726* (0.409)
-0.238 (0.355)
-0.098 (0.179)
0.484*** (0.121)
Each has fate in their own hands -0.407 (0.296)
-0.468 (0.249)
-0.327** (0.129)
-0.292 (0.176)
-0.233 (0.246)
-0.428*** (0.129)
0.021 (0.109)
Important to have material goods -0.162 (0.258)
-0.278 (0.386)
0.354*** (0.106)
-0.092 (0.175)
0.081 (0.202)
0.197* (0.109)
-0.145* (0.082)
Important to be good-looking 0.293 (0.464)
-0.444 (0.528)
-0.384** (0.167)
0.521 (0.407)
-0.236 (0.305)
-0.247 (0.192)
0.059 (0.144)
Important to treat everybody equally -0.693*** (0.263)
0.472 (0.479)
-0.059 (0.128)
0.201 (0.233)
0.051 (0.241)
-0.065 (0.129)
-0.068 (0.1)
Training programmes 0.288 (0.404)
-1.456* (0.879)
-0.119 (0.199)
-0.479 (0.422)
-0.593 (0.413)
-0.709*** (0.217)
-2.276*** (0.282)

Note: *, ** and *** indicate significance at the 10%, 5% and 1% level. Standard errors are in parentheses.

Source: Own calculations based on Social Diagnosis Survey.

The educational level attained by one’s father is mainly statistically insignificant. However, in jobless households, i.e. households in which the primary income comes from social benefits, young individuals are more prone to be unemployed. In general, economic barriers, approximated here by a higher regional unemployment rate (at the NUTS 2 level), are significant and increase the chances of unemployment among those not in education, regardless of their employment-seeking activity. Civic engagement and personal values have a mixed effect on the probability of being unemployed, while political or religious activity is statistically insignificant.

Personal characteristics significantly influencing the economic inactivity of young people include gender, marital status, level of disability as well as educational level. Women are more likely to be inactive and to either stay in education or fall into the NEET category if they are not seeking employment.

Having no more than four household members decreases the chances of being inactive. However, this is only valid for those that do not seek employment. Higher paternal levels of education increase the chances of being inactive, although this result refers mainly to economically inactive youth in education.

High levels of regional unemployment increase the chances of being economically inactive and engaged in education, suggesting that when regional economic barriers to finding employment are high, people prefer to pursue education instead of being unemployed.

Table 6
Probability of being unemployed or inactive
Variable (reference: Employed) Unemployed Inactive
Female 0.989*** (0.092)
1.289*** (0.069)
Married -0.894*** (0.096)
-1.206*** (0.075)
Disabled -0.854*** (0.244)
-0.098 (0.173)
Higher -1.352*** (0.219)
-3.265*** (0.17)
Medium -0.600*** (0.201)
-1.756*** (0.154)
Vocational -0.226 (0.193)
-0.390*** (0.146)
Foreign language knowledge -0.062 (0.113)
1.179*** (0.097)
Studies abroad -0.163 (0.644)
0.025 (0.402)
Intergenerational household and family characteristics
Number of household members -0.338*** (0.09)
-0.234*** (0.069)
Father’s educational level:
Higher -0.265 (0.212)
1.222*** (0.134)
Medium -0.087 (0.145)
0.883*** (0.108)
Vocational 0.127 (0.26)
0.199** (0.092)
Source of main household income 3.182*** (0.179)
3.049*** (0.169)
Economic barriers
Regional unemployment 0.060*** (0.014)
0.014 (0.011)
Civic engagement and personal values
Religiousness 0.138 (0.09)
0.438*** (0.068)
Political activity -0.021 (0.089)
-0.523*** (0.067)
Member of association -0.649*** (0.174)
0.283*** (0.101)
Each has fate in their own hands -0.321*** (0.11)
-0.097 (0.275)
Important to have material goods 0.171* (0.089)
-0.026** (0.702)
Important to be good-looking -0.184 (0.22)
-0.002 (0.118)
Important to treat everybody equally -0.053 (0.108)
-0.074 (0.082)
Training programmes -0.166 (0.171)
-1.431*** (0.172)

Note: *, ** and *** indicate significance at the 10%, 5% and 1% level. Standard errors are in parentheses.

Source: Own calculations based on Social Diagnosis Survey.

Impact of educational programmes on the labour market status of young people

Labour market reforms targeting individuals are better known under the term “activation”, which refers to the bundle of training measures implemented by labour market officers or within enterprises for improving the skills of workers and thus their employability. Activation is central to the National Action Plans on Employment implemented within the framework of the European Employment Strategy and mainly targets older workers, women, the unemployed and low-skilled young people.

An interesting result emerges when analysing the impact of training programmes on the labour market participation of young people. While the standard model indicates that training programmes are significant and increase inactive young people’s chances of finding employment, an analysis of subgroups indicates that training programmes are mainly significant for those that do not seek employment, regardless of whether they are unemployed or inactive. Participation in these programmes also decreases the chances of being in education.


The main results of this paper indicate that important changes in the Polish labour market structure over time can be observed mainly in the groups of people that seek employment. During prosperous times, the proportion of unemployed or inactive people that seek employment decreases. Contemporarily, the proportion of unemployed or inactive young people not seeking employment does not seem to be sensitive to business cycles.

Second, the analysis of the reasons young people do not seek employment reveals that the over half of NEET youth in Poland do not seek employment due to family and household duties. This fraction has increased over time, suggesting that the ongoing lack of instruments undermines young people’s ability to reconcile work, family and childcare responsibilities. The discouragement effect also increases over time, though it is still relatively low when compared to the EU average.

Third, personal factors influencing youth employability can be divided into two groups. Factors in the first group, which consists of so-called motivators, increase the chances of being employed, but only for those seeking work. It includes marital status, disability level and household structure. The second group of characteristics influence the labour market status of all categories of young people in this study and is mainly related to the disadvantageous position of youth. It consists of educational level, economic deprivation (jobless household) and regional barriers.

Finally, while the standard model indicates that training programmes are significant and increase the chances of finding employment for inactive young people, the analysis of subgroups indicates that training programmes are mainly significant for those that do not seek employment, regardless of their labour market status. This suggests that training programmes and policy responses should be addressed mainly to the most discouraged groups of young people, i.e. those that cannot seek employment due to external limitations or those with a lack of belief that they will be able to find a job. Additionally, we argue that policies which facilitate the common functioning of young individuals’ private and professional lives would help them to be more active in the labour market.

  • 1 International Labour Organization: Global Employment Trends for Youth 2013, Geneva; N. O’Higgins: This Time It’s Different? Youth Labour Markets During “The Great Recession”, IZA Discussion Papers, No. 6434, 2012.
  • 2 International Labour Organization, op. cit.
  • 3 European Commission: Towards a job-rich recovery, COM(2011) 933 final, Brussels 2012.
  • 4 European Commission: Youth on the move, Publication Office of the European Union, Luxembourg 2010.
  • 5 Eurofound: NEETs – Young people not in employment, education or training: Characteristics, costs and policy responses in Europe, Publications Office of the European Union, Luxembourg 2012.
  • 6 B. Contini: Youth Employment in Europe: Institutions and Social Capital Explain Better than Mainstream Economics, IZA Discussion Papers, No. 4718, 2010.
  • 7 Eurofound, op. cit.
  • 8 Ibid.
  • 9 Ibid.
  • 10 Ibid.
  • 11 L. Cusworth, J. Bradshaw, B. Coles, A. Keung, Y. Chzhen: Understanding the risks of social exclusion across the life course: Youth and young adulthood, Social Exclusion Task Force, Cabinet Office, London 2009.
  • 12 P. Meadows: Young men on the margins of work: An overview report, Joseph Rowntree Foundation, York 2001.
  • 13 J. Strelitz: Tackling disadvantage: Place, in: D. Darton, J. Strelitz (eds.): Tackling UK poverty and disadvantage in the twenty-first century: An exploration of the issues, Joseph Rowntree Foundation, York 2003, pp. 91-103.
  • 14 B. Coles, S. Hutton, J. Bradshaw, G. Craig, C. Godfrey, J. Johnson: Literature review of the costs of being “not in education, employment or training”, research conducted for the Audit Commission by University of York, York 2002.
  • 15 Ibid.; P. Stoneman, D. Thiel: NEET in Essex: A review of the evidence, University of Essex, Colchester 2010.
  • 16 I. Styczynska: Determinants of Household Demand for Services – Formal versus Informal Sector, Eastern European Economics, forthcoming.
  • 17 S. Golinowska: The system of long-term care in Poland, CASE Network Studies and Analyses, No. 416, 2010.

The Impact of the Recession on the Structure and Labour Market Success of NEET Youth in Ireland

The recent global recession has had a major impact on young people’s labour market status, particularly in those economies that have been worst affected by the downturn. One such country is Ireland, where real GDP fell by ten per cent between 2008 and 2010 before returning to modest growth in 2011.1 The labour market consequences from this severe fall in economic activity were stark, with the country’s overall unemployment rate increasing from 4.4 per cent in 2006 to 14.7 per cent in 2012.2 The youth unemployment rate grew from 8.7 per cent in 2006 to 30.6 per cent in 2012,3 while the youth unemployment ratio4 doubled over the course of the recession, increasing from 5.4 per cent in the third quarter (Q3) of 2007 to 12.8 per cent in Q3 2011; it currently stands at 9.8 per cent.5 The youth unemployment ratio is widely viewed as a better indicator of unemployment among young people, given that many choose to remain in education during an economic downturn.

In relation to young unemployed people, there are two worrying trends. First, the numbers of young unemployed people with relatively low levels of schooling6 increased from 17.4 per cent in 2007 to 48.9 per cent in 2011.7 Second, the share of long-term unemployed grew from 20.3 per cent in 2007 to 45.8 per cent in 2011.8 Another disquieting development has been the rise in the number of young people not in employment, education or training (NEET), which increased from 11.8 per cent in 2006 to 24 per cent in 2011.9

While the unemployment rate of young people has been well documented in Ireland, very little is known about NEET individuals, particularly in terms of their profile and whether it has changed since the recent recession.10 Another important information gap is in relation to their labour market transitions – i.e. the extent to which youth NEETs have transitioned into employment, both before and after the recession. Given this gap in the literature, and specifically its importance in the design of effective activation measures to assist NEET youth, this paper aims to address the following questions:

  1. What are the determinants of being a NEET youth, and have these factors changed since the recession?
  2. What are the labour market transition patterns of NEET youths before and after the boom?
  3. To what extent do changes in the composition of the NEET youth stock explain changes in their labour market transition rates over time?
  4. To what degree do adjustments in the labour market value of various attributes account for changes in labour market transition rates for NEET youth before and after the recession?

Newly available longitudinal data from the Quarterly National Household Survey (QNHS), Ireland’s Labour Force Survey, has been used to address these questions. For comparative purposes, the same questions have been examined for unemployed prime-aged individuals.

Data and methodology

The data used in this paper come from the QNHS longitudinal data file, which is a relatively new dataset compiled by the Central Statistics Office. The main objective of the QNHS is to provide quarterly data on employment, unemployment, etc. The survey is continuous and targets all private households. The total sample for each quarter is approximately 39,000, which is achieved by interviewing about 3,000 households per week. Households are asked to take part in the survey for five consecutive quarters. In each quarter, one-fifth of the households surveyed are replaced, and thus the QNHS sample involves an overlap of 80 per cent between consecutive quarters and 20 per cent between the same quarters in consecutive years. Participation in the QNHS is voluntary; however, the response rate is quite high (approximately 85 per cent in recent years).11 One of the main benefits of using the QNHS longitudinal data is that it enables researchers to track individuals for up to five consecutive quarters.

In this study, we focused on comparing the situation of NEET youths and unemployed prime-aged individuals both before the recession and at the latter stages of the economic downturn. We chose Q2 2006 as the starting point for our analysis, which was during the height of Ireland’s boom, and Q2 2011 as our recessionary time point. We selected two balanced panels for each sub-group analysed. Specifically, we focused on NEET youths (defined as aged 15 to 24) and unemployed prime-aged individuals (defined as aged 25 to 54) who were in each of their respective labour market states on entering the panel and who remained in the panel for the next two consecutive quarters. We were not able to use the five quarters of data, as the number of young people who were initially NEET and remained present in the data for five continuous quarters during the earlier period (e.g. 2006) was too small. For comparative purposes, we then restricted the unemployed prime-aged analysis to two waves as well. Thus, the paper focuses on the labour market transition patterns of NEET youths and unemployed prime-aged individuals between Q2 2006-Q4 2006 and Q2 2011-Q4 2011, concentrating particularly on their transitions from NEET/unemployment into employment. In order to accommodate our empirical strategy, we transformed our balanced panel into a cross-sectional dataset based on the characteristics of individuals observed in Q2 2006 and Q2 2011 and incorporated their transition behaviours in Q3 and Q4 for each of the observed years. The analysis is based on individuals who remained in Ireland over the observation periods; therefore, the impacts of migration are not considered.

In terms of our approach to defining the samples, the QNHS contains two economic status variables: an International Labour Office (ILO) measure and a self-defined Principal Economic Status (PES) measure. The PES variable allows for the separate identification of students, those on home duties and those that have retired, in addition to those in employment and unemployed. For the purposes of this paper, we used the official ILO measure to create our prime-aged unemployment variable. In terms of our NEET measure, we initially selected the ILO “unemployed” and “not economically active” categories. We then cross-referenced this NEET measure with the PES variable to omit individuals that defined themselves as being either a student or in employment. Finally, we excluded individuals from this latter NEET measure who indicated in the QNHS that they had received formal education in the past four weeks. Based on these unemployed and NEET definitions and the restriction of our data to those who were in the 2006 and 2011 panels for three consecutive quarters (i.e. Q2 to Q4), our samples for each sub-group analysed are set out in Table 7.12

Table 7
Sample information
2006 2011
NEET youths 15,430 23,389
Unemployed prime-aged individuals 11,053 65,385

Note: These figures relate to population figures, which have been obtained by expanding the QNHS data by the population sample.

In terms of methodology, we began by estimating separate binary probit models to identify the characteristics associated with being i) a NEET youth or ii) an unemployed prime-aged individual in both 2006 and 2011. For both of these models, the dependent variable equalled one for the subgroup being examined (e.g. NEET youths) and zero otherwise. The characteristics investigated are gender, age, nationality, educational attainment and geographic location. We also ran a series of probit models where we included year interaction terms to test for significant differences in the coefficients between the boom (2006) and recessionary (2011) time points.

We then assessed the impact of various socio-economic and demographic factors on the likelihood of transitioning to employment for NEET youth and unemployed prime-aged individuals. These analyses were undertaken by estimating separate binary probit models for 2006 and 2011, where the dependent variable equalled one if an individual transitioned to employment during the observation period and zero otherwise.13

Finally, we used decomposition analysis to determine the extent to which variations in the rate of transitions to employment between 2006 and 2011 were related to changes in the population structures of the two groups analysed (an endowment effect) as opposed to changes in the return to labour market characteristics (a coefficient effect). The decomposition models are estimated by pooling the data for each grouping for 2006 and 2011 and then decomposing differences in the employment transition rate for the group over the period. Given that our dependent variable is a dichotomous (0/1) variable, we estimated a non-linear Oaxaca decomposition.

Table 8
Determinants of being a NEET or unemployed prime-aged individual
Marginal effects
2006 2011 Change
NEET youths
Reference: Female
Male -0.116*** 0.018*** Yes
Reference: Age 15-19
Age 20-24 0.029*** 0.056*** No
Reference: Junior Certificate or less
Leaving Certificate -0.145*** -0.291*** Yes
Post Leaving Certificate -0.132*** -0.165*** Yes
Third-level non-degree -0.133*** -0.299*** Yes
Third-level degree -0.152*** -0.351*** Yes
Reference: Dublin
Border -0.007* 0.109*** Yes
Mid-East -0.059*** -0.077*** Yes
Midlands -0.034*** 0.131*** Yes
Mid-West 0.020*** 0.096*** Yes
South-East -0.023*** -0.044*** No
South-West -0.029*** -0.007 Yes
West 0.022*** 0.027*** No
Reference: Non-Irish
Irish -0.021*** -0.078*** Yes
Unemployed prime-aged
Reference categories as above
Male -0.008** 0.042*** Yes
Age 35-44 -0.012*** -0.046*** No
Age 45-54 -0.010** -0.084*** Yes
Leaving Certificate -0.027*** -0.074*** No
Post Leaving Certificate -0.021*** -0.046*** No
Third-level non-degree -0.027*** -0.107*** Yes
Third-level degree -0.039*** -0.150*** Yes
Border -0.004 -0.012 No
Mid-East -0.014** -0.012 No
Midlands -0.018** -0.007 Yes
Mid-West -0.007 0.034** Yes
South-East -0.002 0.028** No
South-West -0.007 -0.011 No
West -0.004 0.013 No
Irish -0.034*** -0.039*** Yes

Note: *, ** and *** significant at the 10%, 5% and 1% level respectively.


Table 8 presents the results from our probit model on the determinants of being a NEET youth relative to an employed youth in both 2006 and 2011. The same model is also shown for unemployed prime-aged individuals. The “change” column indicates whether the movement in the coefficients between 2006 and 2011 is statistically significant.

In 2006, the characteristics that raised the probability of being a NEET youth relative to an employed youth were being female, aged 20 to 24 (relative to those aged 15 to 19) and being educated to a compulsory lower secondary school qualification – known as the Junior Certificate – or less. Living in the Mid-West and West, relative to Dublin, also increased a youth’s likelihood of being NEET during the boom. In the aftermath of the downturn (2011), the negative impact of having compulsory lower secondary educational attainment or less became much stronger, with graduates 35 per cent less likely to be NEET relative to youths with lower secondary compulsory levels of schooling or less (compared to a 15 per cent impact in 2006). The impact of geographical location also became more pronounced; in particular, the degree of disadvantage to living outside of Dublin rose substantially for many regions. Interestingly, male youths were much more likely to be NEET in 2011, which can probably be linked to their concentration in the construction sector during the boom period and the subsequent collapse of the property market. Finally, immigrant youths were statistically more likely to be NEET during both the boom and recession.

Prime-aged unemployed individuals and NEETs shared similar traits during both the boom and recession, specifically in terms of gender, nationality and educational attainment. However, the negative impact of having a compulsory lower secondary or less qualification was much lower for prime-aged individuals. Given the insignificance of many of the regional effects, location does not appear to be as strong a factor in determining older individuals’ economic status as it is for youths.

Moving on to our labour market transitions analysis, Table 9 shows the two-quarter transition rates for NEET youths and unemployed prime-aged individuals in both 2006 and 2011.

Table 9
Labour market transition rates for NEET youths and prime-aged unemployed individuals
Continuously NEET Into employment
NEET youths
2006 78.6 21.4
2011 86.4 13.6
Continuously unemployed Into employment Into inactivity
2006 38.5 28.3 33.2
2011 62.9 16.6 20.6

Source: Constructed with data from the 2006 (Q2) and 2011 (Q2) Quarterly National Household Survey longitudinal data files.

Among NEET youths, 79 per cent remained continuously NEET during the boom, while 21 per cent transitioned into employment. By 2011, the proportion of NEET youths that remained continuously NEET increased to 86 per cent, with only 14 per cent transitioning into employment.

With regards to unemployed prime-aged individuals, 39 per cent remained continuously unemployed during three quarters in 2006, 28 per cent transitioned into employment and a slightly higher proportion became inactive (33 per cent). By 2011, the share of prime-aged unemployed that remained continuously unemployed increased quite considerably to 63 per cent, while only 17 per cent transitioned into employment and 21 per cent into inactivity.

Our probit model results on the determinants of transitioning from NEET to employment in two subsequent quarters, or from unemployment to employment for prime-aged individuals, in 2006 and 2011 are presented in Table 10. During both the boom and post-recessionary periods in Ireland, prime-aged unemployed males were significantly less likely than unemployed females to transition to employment. In contrast, NEET males were more likely to transition to employment during the boom period, but by 2011 their transition pattern was consistent with prime-aged unemployed males. Similarly, NEET youths aged 20 to 24 were more likely to find a job compared to those aged 15 to 19 during 2006; however, the opposite was the case during 2011. During both 2006 and 2011, prime-aged unemployed people aged 25 to 34 were more likely to transition to employment compared to their older counterparts.

Table 10
Probit models of the determinants of transitioning from unemployment/NEET to employment
2006 2011
NEET youths Unemployed prime-aged NEET youths Unemployed prime-aged
Gender (Reference = Female)
Male 0.077*** (0.007)
-0.210*** (0.013)
-0.010** (0.004)
-0.026*** (0.004)
Age (Reference = Age 15-19)
Age 20-24 0.028*** (0.007)
- -
-0.104*** (0.007)
- -
Age (Reference = Age 25-34)
Age 35-44 - -
-0.185*** (0.012)
- -
-0.040*** (0.003)
Age 45-54 - -
-0.078*** (0.012)
- -
-0.079*** (0.004)
Educational attainment (Reference = Junior Certificate or less)
Leaving Certificate 0.116*** (0.008)
0.315*** (0.015)
0.016*** (0.005)
0.037*** (0.005)
Post Leaving Certificate 0.353*** (0.021)
0.215*** (0.022)
0.051*** (0.008)
0.160*** (0.006)
Third-level non-degree -0.040*** (0.014)
0.001 (0.018)
0.075*** (0.014)
0.163*** (0.008)
Third-level degree 0.070*** (0.020)
0.081*** (0.020)
0.402*** (0.018)
0.253*** (0.008)
Geographic location (Reference = Dublin)
Border -0.023** (0.010)
0.068*** (0.017)
-0.050*** (0.005)
0.010 (0.007)
Mid-East -0.136*** (0.005)
0.071*** (0.026)
-0.015* (0.008)
0.052*** (0.007)
Midlands -0.109*** (0.008)
-0.215*** (0.023)
0.030*** (0.009)
0.035*** (0.008)
Mid-West -0.128*** (0.006)
0.013 (0.020)
0.136*** (0.011)
0.101*** (0.007)
South-East -0.012 (0.010)
-0.137*** (0.015)
-0.003 (0.007)
0.058*** (0.006)
South-West -0.121*** (0.006)
0.212*** (0.018)
0.062*** (0.008)
0.086*** (0.006)
West -0.080*** (0.007)
0.001 (0.022)
-0.024*** (0.006)
0.098*** (0.007)
Previous unemployment duration (Reference = 1-3 months)
4-6 months -0.021* (0.012)
-0.353*** (0.008)
0.084*** (0.011)
-0.066*** (0.004)
7-12 months -0.106*** (0.006)
-0.308*** (0.009)
-0.110*** (0.003)
-0.076*** (0.004)
13 months and above -0.125*** (0.006)
-0.524*** (0.008)
-0.001 (0.007)
-0.170*** (0.004)
Never had a job -0.328*** (0.009)
- -
-0.095*** (0.006)
- -
Nationality (Reference = Non-Irish)
Irish -0.207*** (0.015)
-0.045** (0.018)
0.087*** (0.004)
0.020*** (0.004)
Observations 15,430 11,053 23,389 65,385
Pseudo R2 0.244 0.321 0.174 0.0967

Note: *, ** and *** significant at the 10%, 5% and 1% level respectively.

In relation to nationality, Irish NEETs and prime-aged unemployed individuals were less likely to transition to employment during the boom period compared to immigrants, but by 2011 we see a reversal in the employment fortunes of Irish nationals for both groups.

From a policy perspective, probably the most important pattern that we observe is with respect to education. During 2006, an unusual non-linear relationship existed between employment transitions for both NEET and unemployed prime-aged individuals. Specifically, both compulsory higher secondary school (i.e. the Leaving Certificate) and the Post Leaving Certificate (PLC) qualification, which tends to be vocational in nature, had a stronger marginal impact than third-level education on transitioning to employment for both NEET and unemployed prime-aged individuals. In fact, NEET individuals with a third-level non-degree qualification were less likely to transition to employment compared to those with compulsory lower secondary school or less education, while there was no difference between prime-aged individuals with both of these types of education. The strength of the PLC qualification in 2006 likely at least partially reflected the importance of the construction industry during that time period. By 2011, the impact of education generally followed a more standard linear pattern, with higher levels of educational attainment having a bigger marginal impact than lower qualifications on both NEET and prime-aged unemployed individuals’ likelihood of transitioning to employment. Perhaps not surprisingly, the marginal impact of a PLC qualification fell off dramatically by 2011 due, presumably, to a substantial fall in the demand for vocationally qualified labour.

Previous unemployment duration emerged as another important factor in determining transitions to employment for both NEET and unemployed prime-aged individuals during both the boom and recession, with the probability of an employment transition being lower for both groups the higher the duration. However, in terms of the order of magnitude, this factor had the largest negative impact on prime-aged individuals, particularly for durations in excess of 12 months. By 2011, the marginal impact of a previous unemployment spell fell dramatically for both NEET and prime-aged unemployed individuals. In particular for NEET youths, the movement was most marked at both extremes of the duration spectrum, with little change observed with respect to the 7 to 12 months duration variable. Thus, for NEET individuals there has been a rapid fall in the scarring impact of both short- and long-term previous unemployment durations. The fall in the scarring effect of previous long-term unemployment is likely to be driven by the higher incidence of long-term unemployment among NEET individuals. The implication of this result is that the policy emphasis should be on improving the human capital of young NEET individuals as opposed to focussing on the cessation of the drift into long-term unemployment. For prime-aged unemployed individuals, a substantial fall occurred in the marginal impact of all three unemployment duration variables between 2006 and 2011. As with NEET youths, the fall in the marginal impact of the 13 month and above unemployment duration variable is most likely explained by the rapid increase in the incidence of long-term unemployment among prime-aged individuals by 2011.

Table 11
Overall decomposition results
NEET youths
Overall difference -7.8
Endowment effect 1.4
Coefficient effect -13.6
Interaction 4.4
Unemployed prime-aged
Overall difference -17.4
Endowment effect -0.3
Coefficient effect -8.8
Interaction -8.4

Next, we undertook our decomposition analysis, the results from which are presented in Tables 11 and 12. The overall decomposition result from the Oaxaca non-linear decomposition is presented in Table 11, and a breakdown of the individual coefficient results is shown in Table 12.

Focussing first on the results in Table 11, the “overall difference” result for each sub-group analysed tells us by how much the transition rate to employment fell between 2006 and 2011. For NEET youths, the rate for transitioning into employment fell by just under eight percentage points, while for unemployed prime-aged individuals, the rate fell by just over 17 percentage points. For NEET youths, changes in the composition of the population, the endowment effect, accounted for less than two percentage points of the overall fall. The vast majority of the fall in the transition rate relates to coefficient effects, which incorporate a change in the return to observable and unobservable characteristics. A similar pattern emerges for prime-aged unemployed individuals: composition effects explain virtually none of the fall in employment transitions, with the bulk of the change related to coefficient effects.

Table 12
Oaxaca individual coefficient effects on change in labour market transition rates between 2006 and 2011
NEET youths Unemployed prime-aged
Observable coefficient effects
Male -0.055*** 0.157***
Aged 20-24 -0.130*** -
Aged 35-44 - 0.059***
Aged 45-54 - -0.010***
Leaving Certificate -0.041*** -0.086***
Post Leaving Certificate -0.030*** -0.002
Third-level non-degree 0.007*** 0.022***
Third-level degree 0.016*** 0.027***
Border -0.010*** -0.006***
Mid-East 0.015*** -0.000
Midlands 0.018*** 0.026***
Mid-West 0.032*** 0.016***
South-East 0.001 0.044***
South-West 0.034*** -0.015***
West 0.006*** 0.017***
4-6 months 0.010*** 0.059***
7-12 months -0.017*** 0.053***
13 months and above 0.060*** 0.312***
Never had a job 0.067*** -
Irish 0.350*** 0.080***
Total 0.333 0.755
Constant -0.470*** -0.842***
Overall coefficient effect -0.136 -0.088

Note: *, ** and *** significant at the 10%, 5% and 1% level respectively.

The individual coefficient results presented in Table 12 tell us what the main determinants are in explaining the change in the employment transition rate for NEET youths and unemployed prime-aged individuals between 2006 and 2011. We separate these results into the impacts on observables, which measure the change in the returns to labour market characteristics over time, and unobservables, which are proxied by the value of the constant term.

For NEET individuals, we found that being male, aged 20 to 24 (relative to those aged 15 to 19) and possessing a compulsory higher secondary school or a vocational type qualification, i.e. the Leaving Certificate or a PLC qualification (relative to a Junior Certificate or less qualification), had a depreciating effect on NEET youths’ employment transition rate between 2006 and 2011, suggesting declines in the returns to such characteristics. In line with the earlier probit models, having a previous unemployment duration of 7 to 12 months (relative to 1 to 3 months) also had a depreciating effect on NEET individuals’ employment transition rate between 2006 and 2011. Possessing a third-level qualification and being Irish, on the other hand, had appreciating effects on the employment transition rate for NEET youths between 2006 and 2011, as did having a previous unemployment duration of either 4 to 6 months or 13 months and above. The positive coefficient effect for both short-term and long-term unemployment may seem unusual; however, as indicated earlier, it is clear that the result reflects a fall in the negative impact of short- and long-term previous unemployment durations. Similar determinants emerged for unemployed prime-aged individuals, particularly in relation to the impact of educational attainment and being Irish. However, being male had an appreciating effect on the unemployment-to-employment transition rate for prime-aged individuals, as did all previous unemployment durations. This latter result suggests that the fall in unemployment scarring effects was more consistent for prime-aged individuals. For both NEET and prime-aged unemployed individuals, the change in the return to observables increased the likelihood of labour market transitions. However, these positive impacts were more than offset by a decline in the return to unobservables, which, presumably, relate to factors and characteristics not controlled for in the model, such as the external macroeconomic environment, social class, previous employment tenure, etc.

Overall, the results from this analysis suggest that the relative fall in the NEET/unemployment-to-employment transition rates for NEET youths and unemployed prime-aged individuals between 2006 and 2011 is not due to changes in the underlying sub-group population structures but to changes in external factors that have had an impact on the importance of possessing certain characteristics as the recession has persisted. Thus, even though there have been huge changes in the macroeconomic environment between 2006 and 2011 which resulted in a rapid growth of the unemployed and NEET populations, these changes in the underlying populations have not substantially impacted the extent of transitions to employment. Nevertheless, the period has seen a substantial change in the labour market value of some characteristics. In particular, there has been a decline in the value of lower level credentials, a rise in the value of more advanced levels of educational attainment and a decline in the scarring impacts of previous unemployment.


This paper uses a unique longitudinal dataset to examine the extent to which transitions to employment among NEET youths and the prime-aged unemployed changed over the course of the economic cycle in Ireland and attempts to explain the nature of such change. We find that for both groupings, the rate of transition to employment has, not surprisingly, fallen dramatically. Overall, the results from this analysis show for NEET youths and prime-aged unemployed individuals that the drop in their transition rates is not due to changes in the underlying sub-group population structures but to changes in external factors that have had an impact on the importance of possessing certain characteristics over the recession. For instance, we found that the labour market value of certain characteristics in achieving a successful transition has altered, including a rise in the marginal value of education and Irish nationality and a fall in the scarring impact of unemployment durations among both groups.

From a policy perspective, the results would seem to support a greater emphasis towards higher levels of human capital (i.e. third-level qualifications) for young NEET individuals. Given the rapid fall-off in the returns to vocational-type qualifications (i.e. PLCs), the results suggest that vocational training should be redesigned to focus on those areas of the labour market where jobs are emerging. Finally, the evidence suggests that the level of disadvantage had become much more acute for unqualified individuals by 2011, suggesting the need for a greater emphasis on policies designed to tackle early school leaving.

This paper has received the financial support of the EU (DG Employment, Social Affairs and Inclusion of the European Commission). The opinions expressed are those of the authors only and do not represent the European Commission’s official position.

  • 1 A. Barrett, S. McGuinness: The Irish Labour Market and the Great Recession, in: CESifo DICE Report 2/2012, pp. 27-33.
  • 2 Central Statistics Office: Live Register: December 2011, Cork 2012; Central Statistics Office: Live Register: February 2013, Cork 2013.
  • 3 Eurostat, March 2013, available at http://epp.eurostat.ec.europa.eu/tgm/table.do?tab=table&plugin=1&language=en&pcode=tsdec460.
  • 4 Youth unemployed expressed as a ratio of the total youth population.
  • 5 E. Kelly, S. McGuinness, P.J. O’Connell, D. Haugh, A. González Pandiella: Transitions in and out of Unemployment among Young People in the Irish Recession, Draft OECD Technical Working Paper, 2013.
  • 6 These proportions relate to individuals holding a Junior Certificate or lower qualification. The Junior Certificate is typically taken by 16-year-old students.
  • 7 Eurostat, October 2012, available at http://appsso.eurostat.ec.europa.eu/nui/show.do.
  • 8 OECD, March 2013, available at http://stats.oecd.org/Index.aspx?DatasetCode=DUR_I#.
  • 9 Eurostat, March 2013, available at http://appsso.eurostat.ec.europa.eu/nui/setupModifyTableLayout.do.
  • 10 FÁS – Training and Employment Authority: Irish Labour Market Review 2008, Dublin 2008, presented a profile of NEETs in Ireland in 2008 using Irish labour force survey data, the Quarterly National Household Survey and cross-country comparative NEET statistics using 2008 OECD data. The most recent research on NEETs in Ireland, which was part of a cross-country comparative study that used the 2008 wave of the European Values Survey and 2012 Eurostat data, was conducted by Eurofound: NEETs – Young people not in employment, education or training: Characteristics, costs and policy responses in Europe, Luxembourg 2012, Publications Office of the European Union.
  • 11 Information provided by the Central Statistics Office.
  • 12 We omitted individuals that did not provide education data, and those who transitioned into economic inactivity are excluded from the unemployed prime-aged models.
  • 13 The same covariates that were used in the individual sub-group determinant models were used in this analysis as well, with the inclusion of a previous unemployment duration variable.

Youth Unemployment in Europe: What to Do About It?

Strikingly high youth unemployment in some member states of the EU is not only challenging national labour market policies, but courts danger to the EU as a whole. In the long run, an entire generation is at risk of having no access to employment in their own country, and policy makers are, not without reason, blamed for that. This is why, in addition to massive economic losses, the EU faces a serious lack of acceptance among young people who ought to be shaping its future. The long-term consequences – from a “brain drain” to the danger of political radicalisation – would be immeasurable. Although demographic change will bring relief to European labour markets in a few years, offering highly qualified people better prospects than they have now, that is little comfort for today’s unemployed youth.

Alarming statistical evidence

The dimension of the problem can be illustrated by some statistics: currently in Spain there are about one million people aged 15-24 out of employment; in Italy this number is more than 600,000. In Greece and Portugal, as well as in Spain and Italy, the number of young people out of employment has significantly increased during the past five years. The number of unemployed people aged 25 or younger has increased by nearly 800,000 to reach 2 million in these four countries alone. However, the employment situation of the young generation is problematic in other countries such as the United Kingdom and France, too.

The same alarming trend becomes obvious when looking at people aged 15-24 years that are NEET (not in employment, education or training). Since 2008, the share of NEETs has risen significantly in 20 of 27 EU countries. The situation is particularly serious, with NEET levels on the order of 20 per cent, in the crisis countries Greece, Cyprus, Spain and Italy, as well as in Bulgaria and Croatia. In other words, up to a fifth of all young people in these countries are in effect not participating in the labour market or training. The NEET risks are especially high for low-skilled individuals and migrants.

The risk of a “lost generation” – what can be done to avoid it

Persistently high youth unemployment causes considerable economic costs. In 2011 alone, Eurofound estimates costs on the order of €150 billion for NEETs in the EU27 aged 15-29. This corresponds to approximately 1.2 per cent of the European GDP.1 Moreover, this estimate does not take into account social “costs” in terms of a loss of trust and exclusion. Even though this rough estimate assumes in a quite simplistic manner that every individual in this group could be successfully integrated into the labour market, the economic losses remain severe in any case. In purely mathematical terms, a reintegration of only 20 per cent of all NEET young people could lead to public budget relief of €30 billion per year and to considerable economic gains due to additional employment.2 Furthermore, it needs to be pointed out that young people who are not able to enter employment or training are marked by the psychological and emotional scars of this experience for their whole working life. According to a recent study, each additional day of unemployment can lead to up to six additional days of unemployment in the young person’s further working life.3

In addition to statistical facts, it must be stated that during an economic crisis, young persons – whether in work or job seekers – are generally the weakest group in the labour market and need special attention in terms of forward-looking labour market policies. Limited work experience, low social capital, less distinctive company-specific knowledge, fewer years of service and the resulting low redundancy payments make them the first to be dismissed when companies respond to recession-induced overcapacities of staff. At the same time, when it comes to new hiring, risk assessment is weighted relatively strongly, and experienced candidates are privileged. Furthermore, institutional conditions like high starting salaries or distinct dismissal protection could encourage firms to be reluctant to employ young applicants.

This gives rise to the question of how national and European labour market policy makers can tackle the problem of youth unemployment effectively. Measures to reduce the large number of dropouts from education and training and increase the skills of low-skilled youth in Europe are by far not sufficient, considering that even highly skilled young people face unemployment risks in many EU countries. Economic policies that support medium-sized businesses ensure the creation of new jobs which cannot be filled by young people alone. In addition to incentives for education and labour mobility in Europe, the reform of training schemes based on the highly successful German dual apprenticeship system, reforms leading to a better social partnership as well as new regulations for permanent and temporary employment need to be mentioned.

These reforms cannot be expected to have a large structural impact in the short run. That is why innovative migration strategies, which can function as an escape valve, are of special importance. After generally bad experiences with job creation measures, it would be wrong to count on these costly and inefficient instruments when looking for immediate success.4 Also, a return to the unsuccessful policy of early retirement in the hope of creating new space for youth employment would not be favourable. As a recent study shows, there is no relevant competition between young and older workers in the labour market. They rather complement each other in the production process. Therefore, the aim must be to improve the employment prospects of young people and at the same time keep older people in work, instead of playing them off against each other.5 Not least, it is a moral imperative to finance social security schemes, which are on track to develop into an unbearable burden for young workers, without extending working lives.

Supporting temporary migration for education and training

From the policy instruments aimed at tackling youth unemployment, improved training and labour mobility policies are supposed to bring about positive effects immediately. Beyond issues of stimulating regional mobility by setting certain incentives, cross-border migration in particular offers enormous potential to solve problems. The latest inter-governmental agreement between Germany and Spain (May 2013) on training and employment opportunities for around 5,000 young Spaniards in Germany through 2017 is a step in the right direction. However, though symbolically important, it makes no relevant difference in quantitative terms. In spite of severe economic imbalances, the development of labour mobility within the “old” EU is still too weak to balance regional fluctuations in the labour markets and to avoid unnecessary unemployment.

Every country would benefit if young people regularly migrated for training and employment purposes within the EU – for example, within the context of EU-supported initiatives like “Youth on the Move”. Regarding the European labour market, it is definitely not about poaching the “brightest and youngest brains” of certain member states, but rather about preventing scarce human capital from being unexploited, becoming devalued during youth or, in the case of trainees without prospects, going undeveloped in the first place.

That is why the latest initiative for hosting young Spaniards in Germany should be soon followed by intergovernmental agreements between other countries. At the same time, the European Portal for Job Mobility, EURES, should be established as the central information portal for workers and potential trainees interested in moving. Furthermore, every country has to create more transparency for foreign job seekers. National online portals should not only be run by governmental institutions but also by employer associations and companies. Apart from language barriers, there are a number of information deficits adversely affecting migration decisions which can be easily resolved. The willingness to migrate among young people can be specifically supported by more transparency during the search process for suitable training or employment opportunities.6

Meanwhile, the bureaucratic hurdles concerning the recognition of educational qualifications obtained abroad have been significantly reduced, and the comparability of degrees has been made easier by standardisations in the context of the European Qualifications Framework. A continued legislative alignment in this field and a further expansion of the European ERASMUS programme could have an additional impact on increasing cross-border educational mobility.7

Young education and labour migrants from the crisis countries can contribute to welfare gains in other member states and thus support the EU as a whole. Losses of human capital would be prevented, and additional qualification and working experience abroad would be gathered. After a few years, at which point the crisis will hopefully have been defeated, the majority of these young labour migrants will likely return to their native countries.

Developing dual vocational training and social partnership

Focusing on youth unemployment in Western Europe, it is most striking that those countries with dual vocational training systems and certified, transferable occupational skills have the lowest unemployment rates. In addition to Germany, Austria, the Netherlands, Denmark and Switzerland also practice various forms of vocational training with a strong focus on firm needs and the involvement of employers. Its advantages are obvious. As opposed to either pure general or vocational schooling, such a system connects trainees with the changing needs of the economy and allows them to gain specific knowledge and initial job experience via a close link to the training company. Firms make a significant contribution to the costs and the co-management of the overall system.

Despite some problems that dual systems have in coping with quick changes in qualification requirements, this concept has proven itself and has secured a high level of acceptance among employers, unions, young people and their parents. But dual training systems require a cooperative partnership between all parties involved – government, companies as well as social partners. When effective cooperation is part of tradition, as in Germany for example, dual vocational training systems are easier to establish or already exist. However, if social partners regard each other with suspicion, chances for the successful establishment of dual vocational training are much worse.

Current economic developments have strengthened Germany’s dual training system. It can serve as a role model for other countries, although its specific historical and culturally developed arrangement is only somewhat applicable to other economies. In recent years, several EU countries, including Spain, have taken steps to institute dual training systems, but it is too soon to evaluate their success. It is quite obvious that this is only manageable in well-considered individual steps. Therefore, it seems appropriate to first try a dual system on a sectoral or regional level in close cooperation with a group of involved companies with similar interests. This makes it easier to design dual vocational training modules and to evaluate their feasibility in practical terms. Therefore, the social partners – in particular employers – should organise sectorally or regionally and establish uniform standards and certifications. It would be unrealistic to expect a broad and extensively regulated German-style training system to be built up within a short time, but this is not necessary to carry out dual vocational training. It could start with vocational schooling or academic education combined with some firm-based phases, such as internships. Measures to strengthen the practical orientation of training will only have an effect on the labour market after a considerable delay, of course. Short-term effects to relieve the current crisis are not achievable with training reforms. However, the crisis offers the opportunity to depart from old paths.

Employment protection, temporary employment and active labour market policies

Temporary employment contracts have been liberalised in many European countries since the 1980s to create new employment opportunities without questioning the often extensive individual dismissal protection. Experiences in Spain, France, Italy, Portugal and Greece have shown that young people in particular were offered temporary contracts and that transitions into permanent employment have been quite difficult. During the economic crisis, the number of temporary jobs dropped massively – forcing young people to bear a particularly large part of the economic costs.

Strict employment protection is generally seen as a serious impediment for labour market entrants. First, these regulations stabilise the jobs of employees with many years of tenure in times of crisis more than those of young employees who do not qualify for redundancy payments. Second, firms are more reluctant when it comes to hiring young and inexperienced applicants during a crisis due to strict employment protection regulations. Weak employment protection tends to strengthen the demand for (young) workers, albeit only on a temporary basis, as well as to cause higher unemployment during a recession.8

Companies in heavily regulated labour markets increasingly use temporary employment as a flexibility reserve, and in markets with particularly strict employment protection legislation, it can even substitute for permanent employment. Unlike past generations, fewer and fewer labour market entrants today can assume that they will be able to secure permanent employment in the short or even the medium term. Although the demographic change will lead to more “employee power” and therefore to more permanent employment, for the generations threatened by the current financial and economic crisis, this turnaround will come too late.

During the current crisis, the importance of establishing new regulation of temporary and permanent employment contracts, as has already begun in some countries with segmented labour markets, should be obvious. These new regulations should be pushed because the current situation offers an opportunity for structural reforms, even though these reforms will only have an effect in the medium term, once the private sector’s demand for labour in the affected countries increases again. A solution discussed in Italy, France and Spain tries to create uniform labour legislation that does not distinguish between temporary and permanent employment (the so-called “single contract”),9 but rather assumes every contract to be generally permanent and increases entitlement to redundancy payments according to employment duration. At the same time, requirements for a justified dismissal need to be simplified. Such a system would significantly improve employment prospects for young people and remove the need to eventually make a decision regarding permanent employment.

The German “Agenda 2010” has proven that an outdated labour market environment can be modernised in a relatively short time if the process does not end with the implementation of partial reforms. In this regard, a “promote and require” strategy for young people is absolutely crucial. In the case of Germany, a scientific evaluation of active labour market policies has led to significant modifications within a short time. Inefficient programmes were corrected or ended, and resources were generally used more purposefully. The timing of certain measures was also improved – for example, immediate programme participation after reporting to the unemployment office is not always appropriate, because advance notice of imminent programme participation often already results in intensified job-search efforts.

In addition to a reform of the transfer system with more incentives to work and a professionalisation of employment services, support for vocational training was strengthened. Moreover, under certain circumstances temporary wage cost subsidies are paid to employers if they employ difficult to place (young) applicants and keep them for a minimum duration. Furthermore, start-ups out of unemployment were temporarily but intensively supported.

According to evaluations, all three of these instruments have proven successful in the German context and have brought more young people into employment.10 Conversely, direct wage subsidies to employees, e.g. within combined-wage models, are too expensive and set uncontrollable disincentives in terms of a reduced labour supply to attain benefit eligibility. Programmes for the provision of public employment beyond regular labour markets are also inefficient. They not only intervene between market forces, they also promote a stigmatisation of programme participants and therefore make their return to private employment potentially more difficult.11

German experiences with active labour market policies are not perfectly applicable to other European countries. The same approach may lead to contrary results due to different labour market constellations. However, according to studies for France, the UK, Belgium and Sweden, temporary wage cost subsidies for employers hiring young people seem to be a reasonable instrument in general. Spain is one of several countries that have activating instruments to subsidise wages and training at its disposal. This approach emphasises a crucial element from which the success of a dual training system stems: true professional experience in the labour market. In this way, young people achieve knowledge and qualifications that can hardly be learned otherwise. However, temporary subsidised employment in countries with strongly segmented labour markets offers little chance for acceptance into permanent employment, especially if serious training elements are missing or neglected in practice.12

Support for young start-ups can also be found in Spain, Greece, Portugal, the UK and Ireland.13 Furthermore, today many countries have established or are developing programmes to promote regional mobility and to assess and accept non-formal qualifications that were gathered during the working process. The range of policy measures is already quite broad. The more these measures are linked to activating programmes and further labour market reforms, and the more thoroughly they are regularly evaluated, the better their medium-term success.

“Youth on the Move”? Answers at the European level

The European Commission is working to reduce youth unemployment through targeted stimulus and by supporting reforms in the member states. First and foremost, the programme “Youth on the Move” needs to be mentioned. This programme, which was begun in 2010 as part of the Commission’s “Europe 2020” strategy, aims to improve the mobility and the general, vocational and higher education of young trainees and job seekers, as well as to support start-ups and the labour market entrance of young people in EU countries with above average youth unemployment rates.14

Quite rightly, the Commission criticises the high rates of early school-leaving and advocates preventive measures. At the same time, the programme recommends strengthening the recognition of informally acquired qualifications, modernising dual training systems and specifically supplying practical internships to push the early acquisition of vocational experience. Against the backdrop of increasing qualification requirements, the Commission also calls for stronger efforts to modernise higher education to significantly increase the number of university graduates across Europe.

At the same time the programme “Youth on the Move” intends to implement a European “Youth Guarantee” that enables every EU inhabitant aged 15 to 24 to claim the right to employment, training or participation within a qualification programme. This proposal stems from similar approaches in several EU countries (e.g. Austria, the Netherlands, Sweden and Finland). After the European Parliament joined this proposal and called for its legal implementation in May 2012, the Youth Guarantee was approved by the EU Ministry Council for Employment and Social Policy (EPSCO) in February 2013.15 As soon as the concept is converted into national law, labour market policy in the EU faces the huge challenge of providing qualified employment, training or internships within four months to every young person that graduates from school or reports unemployment. That will urge governmental authorities in many countries to intensify the interaction among public and private employment services, schools, universities, vocational training providers and wage settlement partners.

However, there is a great threat of rising disappointment (for which the EU will be blamed) as well as massive economic mismanagement. In view of approximately 7 million unemployed young people across the EU, it would call for huge national programmes to maintain the Youth Guarantee, whose design and coordination would be accompanied by considerable difficulties, although around €8 billion is being provided from EU funds. Instead of spending organisational power and scarce financial means for this Youth Guarantee, the numerous important aspects of the Youth on the Move strategy should be followed, and current crisis states should be “promoted and required” to reform their labour markets by reducing the structural discrimination of young people and supporting the creation of new employment.

In the end, only extensive reform policies in the respective countries can ensure the improvement of young people’s prospects. The EU should maintain the pressure to reform, but it should refrain from offering guarantees and thereby raising expectations that cannot be kept.


Against the backdrop of the financial, economic and euro crisis, youth unemployment in many European countries has developed into a dangerous threat. There is little evidence that high unemployment rates will decrease quickly or easily. On the contrary, rigid labour market structures combined with the effects of recession and fiscal restraints on the national budgets of the crisis states make a solidification of youth unemployment likely. For Europe the risks are serious. A large number of youth run the danger of becoming labour market outsiders. Besides the high costs of unemployment and the enduring economic discrimination against the persons affected, the effects for society are even more costly. Continuous systemic discouragement may lead to eroding political participation or even to a distancing from democratic values. A European Union that is already facing a legitimacy crisis cannot respond to this ineffectually – it must focus on ensuring many more young people can enter employment. But with a Youth Guarantee, the EU raises more expectations than it can fulfil – guaranteeing employment, training or qualification to every young person will tie up power and financial funds in questionable ways and will inevitably lead to mismanagement, distracting from the original tasks.

At this point, the individual states must do their part. The capability at the European level is limited when member states fail to enact essential labour market reforms. Employment services must be made more professional and more customer-oriented. Elements of “flexicurity” and the concept of “promoting and requiring” can provide stronger incentives for increased job-seeking efforts. An extension of temporary employment is not an option in several crisis states, because it already dominates the labour markets there and has actually contributed to the current crisis in youth employment. New transitions from temporary to permanent contracts, for example through increased employment security as one’s tenure with a company grows, can contribute to more stable youth employment but cannot work immediately. Modernisations of training systems similar to the successful German model of dual vocational training are also particularly promising in the medium and long term.

To rely on short-term job-creating measures or even early retirement schemes is economically absurd. Temporary wage subsidies to employers that hire young people is a common practice and should be extended, because such policies are most likely to create positive effects at short notice. They are even more valuable if combined with effective training requirements that can eventually constitute a nucleus for more systematic employer involvement in vocational training. This is also true for the promotion of start-ups among young qualified individuals. In this context, additional European programmes for low-interest or even interest-free loans for education or to finance mobility need to be considered.

The key to coping with the European youth unemployment crisis lies in structural reform of the respective labour markets. However, the effects of such reforms will be reaped too late for the currently affected young people. Although this should not lessen the importance of such reforms, suitable measures must also be developed for them. Even though these measures entail significant costs, these costs have to be compared with the long-term costs of a lost generation. The overall balance will be positive for measures that create employment in the private sector and increase mobility across Europe.

  • 1 Eurofound: NEETs – Young People not in employment, education or training: Characteristics, Costs and Policy Responses in Europe, Luxembourg 2012, Publications Office of the European Union.
  • 2 Ibid.
  • 3 A. Schmillen, M. Umkehrer: The Scars of Youth: Effects of Early-Career Unemployment on Future Unemployment Experiences, IAB Discussion Paper, No. 6/2013, 2013.
  • 4 For international evidence, see D. Card, J. Kluve, A. Weber: Active Labour Market Policy Evaluations: A Meta-Analysis, in: The Economic Journal, Vol. 120, No. 548, 2010, pp. F452-F477. For an evaluation of job-creating measures in Germany, see M. Caliendo, R. Hujer, S.L. Thomsen: The Employment Effects of Job-Creation Schemes in Germany – A Microeconometric Evaluation, in: T. Fomby, R.C. Hill, D.L. Millimet, J.A. Smith, E.J. Vytlacil (eds.): Advances in Econometrics, Volume 21 – Modelling and Evaluating Treatment Effects in Econometrics, 2008, pp. 381-428. Using such measures for young people is also seen as very critical, see M. Caliendo, S. Künn, R. Schmidl: Fighting Youth Unemployment: The Effects of Active Labor Market Policies, IZA Discussion Paper, No. 6222, 2011.
  • 5 W. Eichhorst, T. Boeri, M. Braga, A.D. Coen, V. Galasso, M. Gerard, M.J. Kendzia, C. Mayrhuber, J.L. Pedersen, R. Schmidl, N. Steiber: Combining the Entry of Young People in the Labour Market with the Retention of Older Workers (based on a study conducted for the European Parliament), IZA Research Report, No. 53, 2013.
  • 6 For an analysis of information deficits from the German perspective, see A. Constant, U. Rinne: Labour Market Information for Migrants and Employers: The Case of Germany, IZA Research Report, No. 50, 2013.
  • 7 For mobility supporting effects of the ERASMUS programme, see M. Parey, F. Waldinger: Studying Abroad and the Effect on International Labor Market Mobility: Evidence from the Introduction of ERASMUS, in: The Economic Journal, Vol. 121, No. 551, 2011, pp. 194-222.
  • 8 T. Boeri: Institutional Reforms and Dualism in European Labor Markets, in: Handbook of Labor Economics, Vol. 4, Part B, 2011, pp. 1173-1236.
  • 9 For France see e.g. P. Cahuc, F. Kramarz: De la précarité à la mobilité: vers une Sécurité sociale professionnelle, La documentation Française 2005; for Spain J.J. Dolado, F. Felgueroso: Propuesta para la reactivación laboral en España, 2010; for Italy T. Boeri, P. Garibaldi:Un nuovo contratto per tutti, Turin 2008.
  • 10 For a general overview see M. Caliendo, S. Künn, R. Schmidl, op. cit. See M. Caliendo, S. Künn: Start-Up Subsidies for the Unemployed: Long-Term Evidence and Effect Heterogeneity, IZA Discussion Paper, No. 4790, 2011, for an evaluation of German start-up subsidies.
  • 11 See for international evidence, see D. Card, J. Kluve, A. Weber, op. cit.; for evidence from Germany, see M. Caliendo, S. Künn, R. Schmidl, op. cit.
  • 12 J.J. Dolado, M. Jansen, F. Felgueroso, A. Fuentes, A. Wölfl: Youth Labour Market Performance in Spain and its Determinants: A Micro-Level Perspective, OECD Economics Department Working Papers, No. 1039, 2013.
  • 13 For detailed descriptions, see W. Eichhorst et al., op. cit., p. 35-39.
  • 14 European Commission: ‘Youth on the Move’ – An initiative to unleash the potential of young people to achieve smart, sustainable and inclusive growth in the European Union, Luxembourg/Brussels, 2010.
  • 15 W. Eichhorst et al., op. cit.

DOI: 10.1007/s10272-013-0464-9

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