Abstract
The paper asks how the three countries have retained their low level of youth unemployment through the crisis. An institutional approach is taken, criticizing simplistic ideas on how collective skills systems manage the low level of youth unemployment. The analysis starts with Austria, and compares this experience to the other cases. Comparative statistics are used to describe the way of the three countries through the time period 2004 to 2012. In Austria a main component of managing the low level of youth unemployment is a very strong tradition of youth labour market policy (LMP); the apprenticeship system itself has also been supported quite strongly by LMP for decades. Thus, not the apprenticeship system itself, but rather the employment status of apprentices that has included them into social security and thus into LMP seems the main reason of retaining the low level of youth unemployment. The comparison takes three steps: First the features of the apprenticeship (or ‘dual’ or ‘trial’) systems are analysed, showing that Austrian Vocational education and training (VET) is much more diverse with apprenticeship homogenously situated at the lower end; second OECD LMP statistics show a higher intensity and more concentration on apprentices in Austria, pointing to different patterns for explanation; third labour market figures and policies indicate a more severe situation in Germany, which was quite successfully brought down after the crisis. Overall, apprenticeship appears quite diverse, as are the policy approaches, and it is certainly not an ‘easy fix’ for problems on the youth labour market.
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Notes
- 1.
This aspect seems unclear in an EU-study about the impact of apprenticeship, in which the authors do not consider this relationship. They show and interpret correlations between incidence of apprenticeship and employment, unemployment, and rates of young people neither in education nor employment (NEETs), and per country. The results are completely dominated by the three countries Austria, Germany and Denmark (it’s only about EU, so Switzerland is not included); and the NEETs indicator – which is less related to employment – shows the least robust results (ECORYS, IES, IRS 2013).
- 2.
The analysis of effects of the economic cycle would need rather longer data series to be independent from specific conditions; most available analyses use time spans since the mid-1980s which are somehow driven by the exceptional baby boomers from the 1960s, which came to apprenticeship at the same time with the economic turbulences of the early 1980s, so the analyses get stronger effects from demography than from the economic cycle, and some tend to downplay the latter (see estimations by Mühlemann et al. 2009; Müller and Schweri 2006 for Switzerland; Stöger and Winter-Ebmer 2001 for Austria; Baldi et al. 2014; Troltsch and Walden 2010 for Germany).
- 3.
A similar argument of scale was used in the analysis of British higher education, when the budget responsibility for universities was shifted from the Ministry of Finance where it was a relatively negligible proportion of the whole budget, to a specific Ministry, where the same sum had to compete with all the other Ministries, and has consequently been put under much more scrutiny.
- 4.
The specific names and constructions of these Ministries have varied over time, so we use here the basic functional expressions which hold over time.
- 5.
In 2014 the proportion of persons (incidence) unemployed longer than 180 days averaged at two percent below 20 years and at four percent in the 2024 years age group, as compared to 24 percent among all unemployed persons (see statistics of Public Employment Service, Sect. Long-term Unemployed. http://www.ams.at/_docs/001_jb2014.pdf). Some years ago the proportion was even reported at zero.
- 6.
This programme can be seen as a real alternative to the German ‘Übergangssystem’, as it provides a full apprenticeship status, with a slightly lower ‘wage’ paid from the unemployment insurance, and full inclusion into social security, and potentially can also been used during the full period of apprenticeship.
- 7.
The one percent-sample based data from the Labour Force Survey or the Micro-Census are based on quite small absolute sample sizes, and can be used only in a limited way for the analysis of youth because of high error margins for subgroups (this applies also for other small countries).
- 8.
It should be mentioned here, that the discourses at the different levels always take notice of a range of different ‘qualities’ at the apprentices and applicants side, however, also to assume a range of different qualities at the enterprises side is much less common, and this issue is also one seldom directly addressed by research, sometimes under terms as exploitation.
- 9.
Besides, the author has widely searched for information and data that would provide more comprehensive comparative information about how much emphasis is devoted to young people in LMP relative to adults. However, the available literature is mostly about the evaluation of punctual measures, and meta-analysis of this literature. Thus the analysis given in this section, and the data on which it is based cannot be easily compared or triangulated with more established knowledge.
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Lassnigg, L. (2017). Apprenticeship Policies Coping with the Crisis: A Comparison of Austria with Germany and Switzerland. In: Pilz, M. (eds) Vocational Education and Training in Times of Economic Crisis. Technical and Vocational Education and Training: Issues, Concerns and Prospects, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-319-47856-2_7
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