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How Representative Are Social Partners in Europe? The Role of Dissimilarity

Marta Martínez Matute (marta.martinezm@uam.es) and Pedro Martins
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Marta Martínez Matute: Universidad Autónoma de Madrid

Authors registered in the RePEc Author Service: Marta Martínez-Matute (mm_matute@hotmail.com)

No 15370, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Social partners (trade unions and employers' associations) and their representativeness can shape labour institutions and economic and social outcomes in many countries. In this paper, we argue that, when examining social partners' representativeness, it is important to consider both affiliation rates and dissimilarity measures. The latter concerns the extent to which affiliated and non-affiliated firms or workers are distributed similarly across relevant dimensions, including firm size. In our analysis of the European Company Survey, we find that affiliation density and dissimilarity measures correlate positively across countries, particularly in the case of employers' associations in which we focus. This result also holds across employers' associations when we use more detailed, firm population data for Portugal. We conclude that higher affiliation densities do not necessarily correspond to more representative social partners as they can involve greater dissimilarity between affiliated and non-affiliated firms.

Keywords: social dialogue; employers' associations; collective bargaining (search for similar items in EconPapers)
JEL-codes: J23 J50 L22 (search for similar items in EconPapers)
Pages: 47 pages
Date: 2022-06
New Economics Papers: this item is included in nep-bec and nep-lma
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Published - published in: Labour, 2022, 36, 424 - 444

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Journal Article: How representative are social partners in Europe? The role of dissimilarity (2022) Downloads
Working Paper: How representative are social partners in Europe? The role of dissimilarity (2020) Downloads
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