The Impact of Worker and Establishment-level Characteristics on Male-Female Wage Differentials: Evidence from Danish Matched Employee-Employer Data
Nabanita Datta Gubta () and
Donna S. Rothstein ()
Additional contact information
Nabanita Datta Gubta: Centre for Labour Market and Social Research, Aarhus School of Business, Postal: The Aarhus School of Business, Prismet, Silkeborgvej 2, DK 8000 Aarhus C, Denmark
Donna S. Rothstein: Bureau of Labor Statistics, US, Postal: 2 Massachusetts Ave., NE, Suite 4945, Washington, DC 20212-0001, USA
Authors registered in the RePEc Author Service: Nabanita Datta Gupta
No 01-9, CLS Working Papers from University of Aarhus, Aarhus School of Business, Centre for Labour Market and Social Research
Abstract:
This paper examines how the segregation of women into certain occupations, industries, establishments, and job cells impacts the gender wage differential of full-time, private sector workers in Denmark. We use matched employer and employee data that contain labor market information for the Danish population. This enables us to document, for the first time, the wage impacts of gender segregation at the level of establishment and job cell in Denmark. We estimate the wage effects of gender segregation at the above four levels through fixed effects or through controls for the proportion of females within the four structures. We find that occupation has a much larger role than industri or establishment in accounting for the gender gap in full-time private sector wages in Denmark. In addition, men and women earn different wages within job cells.
Keywords: Women and employment; Wages; Denmark (search for similar items in EconPapers)
JEL-codes: J31 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2001-08-01
New Economics Papers: this item is included in nep-lab
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Citations: View citations in EconPapers (10)
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Related works:
Journal Article: The Impact of Worker and Establishment‐level Characteristics on Male–Female Wage Differentials: Evidence from Danish Matched Employee–Employer Data (2005)
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