The Great Recession and scarring effects

The Great Recession of the late 2000s and the ensuing rather anaemic economic recovery − or rather stabilisation in most member states − has hit young people all over the EU disproportionately hard, though with clear variations between countries (and, in some cases, regions). Against a backdrop of very high youth unemployment and, in some cases, dramatically and persistently high NEET rates (and their well-documented long-term ‘scarring’ effects), as well as precariousness in employment, the EU has made the need to improve the labour market prospects and employment chances of young people one of its key priorities.

Policies to combat a ‘lost generation’: The Youth Guarantee

In the face of a dramatic rise in youth unemployment, especially during and after the Great Recession, and the risk of a ‘lost generation’ of young Europeans, EU institutions such as the European Commission, together with national governments, have put the promotion of youth employment at the top of the political agenda. Often following European Commission recommendations, many member states have embarked upon ambitious reform programmes—such as the introduction of the Youth Guarantee (YG), structural reforms of vocational education and training (VET) and activation policies—which have the potential to significantly alter the way in which STW transitions are structured.

Our research goals

We set out to:

  • provide quantitative estimates of the impact of specific active labour market policies (ALMPs) and associated programmes on youth unemployment;
  • conduct a causal analysis on the impact of specific youth-related labour market and education and training policies on youth labour market outcomes; and
  • carry out a cost−benefit analysis on the welfare implications of the different policy options available in order to improve the situation of young people in the labour market.

In order to assess the performance of youth labour markets and the effectiveness of implemented policies, our analysis covered the EU27 and Turkey. Macroeconomic as well as microeconomic indicators were analysed in order to explain structural, cyclical and individual factors affecting STW transitions. Furthermore, a single index measure of youth labour market performance was developed to simplify the evaluation of the multi-dimensional nature of factors influencing STW transitions. At the same time, we conducted a comprehensive literature review of the existing evidence on the effectiveness of ALMPs, both in general and in relation to young people, as well as in terms of their impact at macroeconomic level (e.g., aggregate employment/unemployment, functioning of the labour market/Beveridge curve).

Research questions

Our review highlighted the fact that there is little or no evidence concerning (i) the quantitative impact of improved policy interventions in the form of ALMPs in relation to young people and (ii) the long-term/future social benefits of increased public spending at present.

Our research aims to contribute to the debate, first, by estimating the quantitative impact of ALMP and other institutional features on youth unemployment and, second, by discussing costs and benefits of different policy options that would, ideally, lead to better informed and more evidence-based policy-making in relation to young people’s labour market entry.

Our research methods

Our analysis provides quantitative estimates of the impact of ALMPs on youth unemployment in Europe based on a macroeconomic panel data set of youth unemployment, ALMP and education policy variables, and further country-specific characteristics of labour market institutions and the broader demographic and macroeconomic environment for all EU member states.

Using Blundell, Bond and Windmeijer’s (2000) GMM estimator for dynamic panel data models, we estimated the impact of different ALMP options on youth unemployment ratios. This is a more reliable indicator than the youth unemployment rate because it reflects the proportion of unemployed youth in relation to the total youth population (employed, unemployed and inactive, including those in full-time education).

Active Labour Market Programmes

In terms of the different ALMP options examined, we adopted the typical classification used by both the EU and the OECD. This includes

  1. provision of public employment services (PES), such as jobsearch assistance;
  2. training programmes for unemployed people, including those that offer subsidies for trainees who attend courses, including VET or apprenticeships, and for companies that take on people who combine work with relevant training;
  3. subsidies for regular employment in the private sector in the form of wage subsidies or tax reductions; and
  4. direct job creation such as public works programmes and support to agencies or local authorities for hiring unemployed (young) people. Because of methodological and data limitations, for our quantitative estimates on the impact of ALMPs on youth unemployment we restricted our analysis to using participation in ALMP as the relevant policy variable.

Vocational Education and Training: Apprenticeships

In addition to ALMPs, VET, including apprenticeships, is considered key to lowering youth unemployment and facilitating youth STW transitions. Policy-makers across Europe have been attempting to improve VET in order to provide an attractive alternative to general upper-secondary and tertiary education and in order to better meet the skill requirements of the labour market. Since VET plays an increasingly crucial role in the policy response to youth unemployment, in particular in the longer term, we have also used participation in VET as a percentage of the total population of the age range 15-24 to analyse the impact of vocational education policy on the youth unemployment ratio.

Our results

Overall, our results show that participation in vocational education at ISCED-3 level and in some ALMPs and associated programmes has significant effects on aggregate youth unemployment, while ALMP-related training programmes do not show a significant impact.

Based on models without a lagged policy variable, our estimates show that significant reductions of youth unemployment ratios could be achieved by increasing VET. Specifically, the youth unemployment ratio (15-24 year-olds) would decrease by 0.25 percentage points if participation stocks in vocational education (as a percentage of all 15-24 year-olds) increased by one percentage point. Introducing a lag does not change this finding by much.

The picture is different for the variables estimating the impact of ALMP on young peoples’ unemployment ratios. For example, the increase in participation in employment incentive programmes (relative to youth unemployment) by one percentage point reduces youth unemployment by 0.7 percentage points.

Likewise, youth unemployment ratios would decrease by about 0.4 percentage points if participation in job-creation schemes (stocks as a percentage of youth unemployment) increased by one percentage point. On the other hand, increasing the participation in ALMP-related labour market training was found to increase youth unemployment. Table 1 summarises the findings of our analysis.

Table 1: Impact of participation in ALMPs as % of unemployment (15-24 average annual stocks) on unemployment ratios
Coef. Robust SE z P>|z|
ALMP part. as % of UE (under 25)
a) Employment incentive programmes -0.0075 0.0036 -2.0600 0.0400
b) Job creation schemes -0.0399 0.0199 -2.0100 0.0440
c) Labour market service -0.0002 0.0042 -0.0600 0.9560
d) Labour maket training 0.0012 0.0051 0.2300 0.8150
e) Business start ups -0.1154 0.1160 -0.9900 0.3200
L3 vocational education (all)
% of 15-24 year olds -0.0249 0.0079 -3.1600 0.0020

Source: Speckesser, S, (2015). D3.1 – Key Indicators and Drivers of Youth Unemployment, presentation at the STYLE Grenoble meeting, 5/3/2015

Note: Marginal effect percentage point change in observed unemployment ratio (UE as a percentage of the 15-24 year-old population); significant estimates are in bold


We have also contextualised our analysis with an evidence base on the impact of ALMPs on youth unemployment. We have related our findings to available estimates of individual and social benefits of reducing youth unemployment and the number of NEETs.

This literature found that being NEET at a young age is likely to result in lower earnings over the life course, poorer health and higher probability of committing crime, for which various studies – mainly from the UK – have provided estimations of these costs in monetary terms.

Cost-Benefit Analysis

A full Cost-Benefit Analysis relating to the increase in VET and ALMP as a value measure of social benefits could not be undertaken as part of our research because the evidence base on the benefits of reducing youth unemployment (and the cost of NEETs) is limited to only very few countries.

However, we have produced estimates that can be used for some policy reform modelling by parameterising a model of the incremental costs of policy reform; for example, extending employment incentive programmes to temporarily improve young people’s position in the job matching process. The resulting value parameters are shown in Table 2 below. This allows us to gain an understanding of the costs associated with increasing the use of policy interventions relating to ALMPs and VET in order to reduce youth unemployment.

Table 2 Impact of spending (in €1,000 per UE) and VET participation on unemployment ratios
Impact on 15-19 youth unemployment ratio Impact on 20-24 youth unemployment ratio
COEF. Std. Err z P>|z| COEF. Std. Err z P>|z|
Employment incentive programmes -0.017 0.096 -0.18 0.856 0.034 0.208 0.16 0.869
Job creation schemes -0.164 0.072 -2.28 0.023 -0.201 0.105 -1.91 0.056
Labour market service 0.196 0.072 2.14 0.032 0.281 0.091 3.09 0.002
Labour market training -0.077 0.105 -0.74 0.46 -0.062 0.155 -0.4 0.69
Business start ups 0.63 0.758 0.83 0.406 -0.777 1.657 -0.47 0.639
People in L3 vocational programmes -0.031 0.007 -4.81 0 -0.024 0.011 -2.27 0.023

Source: Speckesser, S, (2015). D3.1 – Key Indicators and Drivers of Youth Unemployment, presentation at the STYLE Grenoble meeting, 5/3/2015


On the basis of our estimates presented in both Table 1  (impact of ALMPs and VET on youth unemployment ratios) and Table 2 (cost of policy reform), we can draw the following tentative conclusions:

  • Increasing VET by one percentage point significantly reduces youth unemployment, but it would have to be a large-scale intervention for such an effect to take place since there are already many young people in vocational education. Moreover, such education and training has comparatively high costs per participant.
  • Employment incentives are a more costly ALMP-related programme but, on average, fewer people are engaged. Extending this element, as part of the youth-related policy mix, would potentially be more costly per participant (in most countries); however, the overall spending to achieve a significant reduction in youth unemployment could be potentially lower.
  • Job creation schemes are the most costly option, but there is also some evidence of higher impacts than other interventions. However, it should also be stressed here that, as our literature review highlighted, the evidence regarding the impact of such schemes in terms of sustainable employment and cost effectiveness is not very robust. As a result, this finding of our analysis should be interpreted with extreme caution.
  • Overall, it seems that work experience (acquired as part of either job-creation schemes and/or employment incentives) reduces youth unemployment most and is most cost effective. On the other hand, training programmes as part of ALMPs do not reduce youth unemployment. As far as extending vocational education is concerned, its impact on reducing youth unemployment is positive; however, the magnitude of this impact is rather small.

The above discussion notwithstanding, we firmly believe that in order to understand the welfare implications of policy change, such estimates as those presented above would have to be further refined, for example considering differential impacts across countries; the choice of countries is also dependent on which suitable data would have to be made available.

We are fully aware that the findings of this aggregate analysis of the impact of ALMPs on youth unemployment should be interpreted with caution since we were severely constrained by the limited availability of relevant, consistent and comparative data across the EU. In that regard, we were indeed constrained by having to rely for our analysis on very rough measures of ALMP spending and participation. Following this analysis, we believe that there is an urgent need to set up a proper data collection and monitoring system across the EU which should, inter alia, include micro- and macro-economic data with coherent concepts of policy interventions (and indicators for policy effectiveness) for young people. Improved estimates of the long-term cost of youth unemployment (and the long-term economic benefit of reducing NEETs) to the European economy also need to be produced in order to allow for consistent research on the impact of policy and programmes (e.g., ALMPs). This will also contribute to better policy-making based on improved understanding of the social return on investment of policy aimed at reducing youth unemployment.


Gonzalez Carreras, Francisco, Laura Kirchner Sala and Stefan Speckesser. 2015. The Effectiveness of Policies to Combat Youth Unemployment’ STYLE Working Paper WP3.2 Policies to combat Youth Unemployment

Blundell, Richard, Stephen Bond and Frank Windmeijer. 2000. Estimation in Dynamic Panel Data Models: Improving on the Performance of the Standard GMM Estimator. IFS Working Paper 12. London: Institute for Fiscal Studies.