The Unemployment-Specialization Relationship under Collective Bargaining Constraints Evidence from EU Regions
Simonetta Longhi,
Peter Nijkamp and
Iulia Traistaru ()
Authors registered in the RePEc Author Service: Iulia Siedschlag ()
ERSA conference papers from European Regional Science Association
Abstract:
Standard labor market theories predict that workers employed in more specialized areas earn higher wages in comparison with similar workers employed in less specialized areas. Empirical studies for the US generally confirm the existence of a positive effect of sectoral specialization on wages and on unemployment. However, these relationships might not hold in labor markets that are characterized by substantially higher collective bargaining coverage and more centralized bargaining systems. In the EU, for example, collective wage agreements impose identical wages across regions belonging to the same country, thus leaving little room for regional wage flexibility. Using regional data for EU member states, we model regional unemployment as a function of regional specialization measures. The comparison between such countries, that are still characterized by separate and independent collective agreements on wages, can give us new insights on the effects that collective bargaining may have on the relationship between sectoral specialization of regions and regional unemployment rates.
Date: 2004-08
New Economics Papers: this item is included in nep-geo and nep-lab
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www-sre.wu.ac.at/ersa/ersaconfs/ersa04/PDF/447.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wiw:wiwrsa:ersa04p447
Access Statistics for this paper
More papers in ERSA conference papers from European Regional Science Association Welthandelsplatz 1, 1020 Vienna, Austria.
Bibliographic data for series maintained by Gunther Maier ().