Explaining Occupational Gender Inequality: Hours Regulation and Statistical Discrimination

28 Pages Posted: 1 Aug 2011 Last revised: 17 Aug 2013

See all articles by Torben Iversen

Torben Iversen

Harvard University

Frances McCall Rosenbluth

Yale University - Department of Political Science

Date Written: 2011

Abstract

Women shoulder a heavier burden of family work than men in modern society, preventing them from matching male success in the external labor market. At least hypothetically, limiting working hours is a plausible way to level the playing field by creating the possibility of less gendered roles for both sexes. We find, however, the opposite has occurred: the greater the restrictions on working hours, the fewer the women who make it to the top of their professions. We explain this result with reference to statistical discrimination: As long as women are more likely than men to interrupt their careers for family considerations, firms will avoid hiring and promoting women to leadership positions that require long hours and continuous commitment. Where the absence of hours restrictions allow some women to signal their willingness to relinquish family responsibilities by working extraordinarily long hours at the office, women have a significantly higher chance of rising to managerial positions. We also note, however, that the absence of hours restrictions and other labor protections correspond with larger gender wage gaps lower on the occupational ladder because of the absence of wage compression. Moreover, the women who rise to managerial positions in liberal market economies remain outliers. The ability of outlier women to signal commitment to a long term career will not eliminate statistical discrimination itself until employers can expect the average man and woman to take equal amounts of time for family work.

Suggested Citation

Iversen, Torben and Rosenbluth, Frances McCall, Explaining Occupational Gender Inequality: Hours Regulation and Statistical Discrimination (2011). APSA 2011 Annual Meeting Paper, Available at SSRN: https://ssrn.com/abstract=1900012

Torben Iversen

Harvard University ( email )

Institute for Quantitative Social Science
1737 Cambridge Street
Cambridge, MA 02138
United States
617-384-5847 (Phone)
617-496-5149 (Fax)

HOME PAGE: http://www.people.fas.harvard.edu/~iversen/index.htm

Frances McCall Rosenbluth (Contact Author)

Yale University - Department of Political Science ( email )

Box 208269
New Haven, DC 06520-8269
United States
203-432-5256 (Phone)

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
72
Abstract Views
621
rank
375,533
PlumX Metrics