Match me up before I go-go! : Matching functions for spatially connected VET labor markets

bibb.id785052de
bibb.participationBIBB-Mitarbeiterde
bibb.voevzlinkhttps://res.bibb.de/vet-repository_785052
dc.contributor.authorKubitza, Dennis [Verfasser]de
dc.date.accessioned2026-07-01T08:20:13Z
dc.date.available2026-07-01T08:20:13Z
dc.date.issued2026
dc.description.abstract"Local labor markets in Germany are interconnected through mobile workers who commute or migrate across borders. Therefore, the aggregated number of new matches between employers and employees in one region is influenced by spillovers from neighboring markets, but might also be disproportionately higher due to easier access to suitable jobs in agglomerated areas. Vocational education and training (VET) students in company training, so called apprentices, are younger and therefore less mobile than the general workforce, suggesting that regional spillovers may be less pronounced when looking at VET labor markets. In addition, occupational heterogeneities in the spatial distribution of employers might further amplify or decrease these spillovers. This paper provides the first estimates of spatial matching functions for VET students in general and for multiple profession groups. Using a matching function model with spatially lagged stocks of applicants and vacancies, it analyses efficiency, elasticities, regional influences, and spatial spillovers. To do so, it develops a novel set of spatial weights and ways to measure agglomeration. The findings show that matching efficiency for VET is higher in more agglomerated regions and that measurable spillovers do exist, even for the group of less long-distance mobile adolescents. This underscores the importance of accurate spatial modeling: only indices based on realistic travel times or commuting data show these influences. Finally, this paper finds significantly lower elasticities in the stock of unemployed applicants for regions that are well connected to their surroundings, leading to a more balanced matching process."de
dc.description.statementofresponsibilityDennis Oliver Kubitzade
dc.description.versionreferiertde
dc.format.extent1 Online-Ressource (1-36)de
dc.format.illustrationIllustrationende
dc.format.illustrationDiagrammede
dc.format.mediumElektronische Ressourcede
dc.format.mediumZeitschriftenaufsatzde
dc.identifier.uriDOI:10.1007/s11067-026-09742-1
dc.identifier.urihttps://bibb-dspace.bibb.de/jspui/handle/BIBB/785052
dc.language.isoende
dc.rdacarrier.codecrde
dc.rdacarrier.sourcerdacontentde
dc.rdacarrier.termOnline-Ressourcede
dc.rdacontent.codetxtde
dc.rdacontent.sourcerdacontentde
dc.rdacontent.termTextde
dc.rdamedia.codecde
dc.rdamedia.sourcerdacontentde
dc.rdamedia.termComputermediende
dc.relation.ispartofNetworks and spatial economics : a journal of infrastructure modeling and computation
dc.relation.ispartofvolumepublished online
dc.rightsNamensnennung 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.classificationG 1.3.3.3 Mobilitätde
dc.subject.classificationG 1.2.1 Grund- & Strukturdaten des Arbeitsmarktesde
dc.subject.ddc370de
dc.subject.ddc300de
dc.subject.otherAusbildungsmobilitätde
dc.subject.otherRegionale Mobilitätde
dc.subject.otherArbeitsmarktde
dc.subject.otherArbeitsmarktanalysede
dc.subject.otherÖffentlicher Personennahverkehrde
dc.subject.otherRegressionsanalysede
dc.titleMatch me up before I go-go! : Matching functions for spatially connected VET labor marketsde

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