Article Gold Open Access 2015

Spatial structure counts: The relevance of regional labour-market conditions for educational transitions to vocational training

Empirical Research in Vocational Education and Training
Journal · Vol. 7 · Issue 1 · Art. 12
Abstract

Regional context conditions can have a crucial impact on school-to-work transitions and subsequently individual life chances. This paper aims to develop an approach to analyse the spatial references of regional socio-economic contextual settings young adults are embedded in. We apply this approach to assess the impact of regional unemployment on the transition from lower or intermediate compulsory schooling to vocational education and training (VET) in Germany. We use data from the German Socio-Economic Panel Study (GSOEP) and merge these with administrative time series data on NUTS 3-regions level. We attach geocodes to the administrative districts to allow for a flexible operationalisation of the spatial reference of regional socioeconomic contextual settings. Our results indicate, first, a negative relation between regional unemployment and the chances of entering vocational training in the dual system. Second, the effects of unemployment on adolescents' transition chances have a specific spatial structure: The labour-market situation in the respondent's district of residence moderates the relation between the labour-market situation in surrounding districts and the school graduates' chances of entering dual training. © 2015 Weßling et al.

Keywords

Author Keywords

vocational education and training (VET) school-to-work transitions Dual system GSOEP Linking micro- and macro-level data Regional labour-market conditions Spatial patterns

Index Keywords

Author Affiliations
Department of Sociology, Eberhard Karls Universität Tübingen, Tubingen, Baden-Wurttemberg, Germany
Funding & Acknowledgements
Deutsche Forschungsgemeinschaft, DFG
Grant: 767/6-1
We would like to thank the German Research Foundation (DFG) (Award No. 767/6-1) for project funding.
Deutsche Forschungsgemeinschaft, DFG
We would like to thank the German Research Foundation (DFG) (Award No. 767/6-1) for project funding.
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