Is Training More Frequent When Wage Compression is Higher? Evidence from the European Community Household Panel

Andrea Bassanini and Giorgio Brunello

No 839, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: When labor markets are imperfectly competitive, firms may be willing to finance general training if the wage structure is compressed, that is, if the increase of productivity after training is greater than the increase in pay. We propose a novel way of testing this proposition, which exploits the variation in training incidence and in the training wage premium within the European Union. Our results unambiguously show that (general) training incidence is higher in clusters – defined by country, sector, occupation and educational attainment – with a lower training wage premium, measured as the differential between the median wage growth of trained and untrained employees.

Keywords: ECHP; wage compression; training (search for similar items in EconPapers)
JEL-codes: J24 J31 J41 (search for similar items in EconPapers)
Pages: 41 pages
Date: 2003-08
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

Published - revised version published as 'Is training more frequent when the wage premium is smaller? Evidence from the European Community Household Panel' in: Labour Economics, 2008, 15(2), 272-290

Downloads: (external link)
https://docs.iza.org/dp839.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:iza:izadps:dp839

Ordering information: This working paper can be ordered from
IZA, Margard Ody, P.O. Box 7240, D-53072 Bonn, Germany

Access Statistics for this paper

More papers in IZA Discussion Papers from Institute of Labor Economics (IZA) IZA, P.O. Box 7240, D-53072 Bonn, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Holger Hinte ().