Low-wage mobility in the Portuguese labour market

José Vieira

Portuguese Economic Journal, 2005, vol. 4, issue 1, 14 pages

Abstract: Low-wage employment has become a matter of concern in many countries, Portugal being among them. In particular, the extent to which low-wage employment is a permanent or transitory situation is an important issue. This paper examines low-wage mobility in the Portuguese labour market using the bivariate probit model proposed by van de Ven and van Praag (1981), in order to account for the potential endogeneity of the initial state. For this purpose, we use a matched employer-employee panel data for 1996 and 2000. Raw figures show that a significant number of workers are trapped into low-wage employment. We also find that males and the better-educated are more likely to escape from such a situation. Furthermore, initial firm characteristics, such as firm size, age and industry influence mobility. In particular, low-wage workers in larger or in newer firms have better mobility prospects. Copyright Springer-Verlag Berlin/Heidelberg 2005

Keywords: Wage mobility; low-wage; firm age; Portugal (search for similar items in EconPapers)
Date: 2005
References: Add references at CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://hdl.handle.net/10.1007/s10258-005-0038-2 (text/html)
Access to full text is restricted to subscribers.

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:spr:portec:v:4:y:2005:i:1:p:1-14

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10258/PS2

DOI: 10.1007/s10258-005-0038-2

Access Statistics for this article

Portuguese Economic Journal is currently edited by Luís F. Costa

More articles in Portuguese Economic Journal from Springer, Instituto Superior de Economia e Gestao
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().