Publication:
Efficiency in a matching model with heterogeneous agents: too many good or bad jobs?

dc.affiliation.dptoUC3M. Departamento de Economíaes
dc.contributor.authorBlázquez, Maite
dc.contributor.authorJansen, Marcel
dc.date.accessioned2006-11-09T11:26:46Z
dc.date.available2006-11-09T11:26:46Z
dc.date.issued2003-10
dc.description.abstractThis paper analyzes the efficiency of the equilibrium allocation in a matching model with two types of workers and jobs. The technology is such that high-skill workers can perform all jobs, while low-skill workers can only perform unskilled jobs. In this setup two types equilibria may occur. A cross-skill matching equilibrium in which high-skill workers accept all jobs and an ex-post segmentation equilibrium in which they accept only skilled jobs. Our first result shows that the equilibrium with ex-post bargaining is never efficient. Second, under Hosios'(1990) condition we show that low-skill workers are overvalued, while the opposite holds for high-skill workers. In equilibrium, firms therefore create too few unskilled jobs and too many skilled jobs. In addition, high-skill workers may decide to accept unskilled jobs while the efficient allocation features ex-post segmentation. Finally, in an extension we show that efficiency can be restored through taxation and we analyze how workers bargaining strength affects unemployment and the degree of skill-mismatch.
dc.format.extent634406 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.issn2340-5031
dc.identifier.repecwe035019
dc.identifier.urihttps://hdl.handle.net/10016/301
dc.language.isoeng
dc.language.isoeng
dc.relation.ispartofseriesUC3M Working Paper. Economics
dc.relation.ispartofseries2003-19
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaEconomía
dc.titleEfficiency in a matching model with heterogeneous agents: too many good or bad jobs?
dc.typeworking paper*
dspace.entity.typePublication
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