Parametric vs. Semi-parametric Estimation of the Male-Female Wage Gap: An Application to France
Robert Breunig and
Sandrine Rospabe
No 548, CEPR Discussion Papers from Centre for Economic Policy Research, Research School of Economics, Australian National University
Abstract:
We use a semi-parametric method to decompose the difference in male and female wage densities into two parts-one explained by characteristics and one which is attributable to differences in returns to characteristics. We demonstrate that one learns substantially more about the gender wage gap in France through this analysis than through standard parametric techniques. In particular, we find that there are no unexplained differences in male and female earning distributions in the bottom fifth of the data. Occupation and part-time status are the most important determinants of the wage gap for all workers. In the semi-parametric estimates we find that education plays no role in the wage gap once we account for occupation and part-time status.
Keywords: Gender pay gap; sticky floors; glass ceilings; semi-parametric estimation (search for similar items in EconPapers)
JEL-codes: J16 J31 J7 (search for similar items in EconPapers)
Date: 2007-03
New Economics Papers: this item is included in nep-lab
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.cbe.anu.edu.au/researchpapers/CEPR/DP548.pdf (application/pdf)
Related works:
Working Paper: Parametric vs. semi-parametric estimation of the male-female wage gap: An application to France (2005) 
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:auu:dpaper:548
Access Statistics for this paper
More papers in CEPR Discussion Papers from Centre for Economic Policy Research, Research School of Economics, Australian National University Contact information at EDIRC.
Bibliographic data for series maintained by ().