Earnings Functions and the Measurement of the Determinants of Wage Dispersion: Extending Oaxaca's Approach
Jacques Silber and
Joseph Deutsch
No 2007-19, Working Papers from FEDEA
Abstract:
This paper extends the famous Blinder (1973) and Oaxaca (1973) discrimination analysis in several directions. First the wage difference breakdown is not limited to two groups. Second a decomposition technique is proposed that allows analyzing the determinants of the overall wage dispersion. The approach presented combines two techniques. The first one is popular in the field of income inequality measurement and concerns the breakdown of inequality by population subgroups. The second one, very common in the labor economics literature, uses Mincerian earnings functions to derive a decomposition of wage differences into components measuring respectively group differences in the average values of the explanatory variables, in the coefficients of these variables in the earnings functions and in the unobservable characteristics. This methodological novelty allows one to determine the exact impact of each of these three elements on the overall wage dispersion, on the dispersion within and between groups and on the degree of overlap between the wage distributions of the various groups.
Date: 2007-06
New Economics Papers: this item is included in nep-lab and nep-ltv
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://documentos.fedea.net/pubs/dt/2007/dt-2007-19.pdf (application/pdf)
Related works:
Working Paper: Earnings Functions and the Measurement of the Determinants of Wage Dispersion: Extending Oaxaca’s Approach (2007) 
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:fda:fdaddt:2007-19
Access Statistics for this paper
More papers in Working Papers from FEDEA
Bibliographic data for series maintained by Carmen Arias ().