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dc.contributor.authorLeknes, Stefan
dc.contributor.authorRattsø, Jørn
dc.contributor.authorStokke, Hildegunn Ekroll
dc.date.accessioned2022-10-19T16:56:35Z
dc.date.available2022-10-19T16:56:35Z
dc.date.created2022-06-15T19:53:41Z
dc.date.issued2022
dc.identifier.citationRegional Science and Urban Economics. 2022, 22 .en_US
dc.identifier.issn0166-0462
dc.identifier.urihttps://hdl.handle.net/11250/3027163
dc.description.abstractWe investigate the heterogeneity of assortative labor matching with respect to geography, skills, and tasks. Our contribution is to separate plant quality by education level and occupation tasks using the AKM-model. We introduce a geology-related instrument to analyze the city effect and address limited mobility bias. Using rich administrative worker-plant dataset for Norway, we show that matching of the college educated have a strong city effect. The IV estimates indicate that a doubling of city size increases the correlation between worker and plant quality by 9 percentage points. A wage decomposition shows that matching accounts for 22% of the urban wage premium adjusted for sorting. In terms of occupations, better matching in cities is observed only for non-routine abstract tasks.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse-Ikkekommersiell-DelPåSammeVilkår 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/deed.no*
dc.titleAssortative labor matching, city size, and the education level of workersen_US
dc.title.alternativeAssortative labor matching, city size, and the education level of workersen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY liceneen_US
dc.subject.nsiVDP::Samfunnsvitenskap: 200::Økonomi: 210en_US
dc.source.pagenumber18en_US
dc.source.volume22en_US
dc.source.journalRegional Science and Urban Economicsen_US
dc.identifier.doihttps://doi.org/10.1016/j.regsciurbeco.2022.103806
dc.identifier.cristin2032228
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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