Russell Sage Foundation
Figure 12. Wage Differentials for Women Relative to Men, Hispanics Source: Authors’ calculations based on data from the National Science Foundation’s Scientists and Engineers Statistical Data System (SESTAT) 1995–2008. Notes: All men and women graduating with a STEM bachelor’s degree between 1970 and 2004, working at least thirty-five hours a week in a STEM occupation. Results from OLS regressions of logged hourly wages on indicator for female. Dark bar represents coefficient on female in OLS regression with no other controls (model 1 from ). Light shaded bar represents coefficient on female in OLS regression with full set of controls (model 5 from ). Each bar represents a different regression. Regressions run separately by race and STEM field. Wages are calculated by dividing annual salary by number of weeks worked per year and average number of hours worked per week. All wages reported in 2014 dollars. Regressions weighted by person weights. Italicized terms indicate significantly different from zero at the p < 0.05 level.
Figure 12.

Wage Differentials for Women Relative to Men, Hispanics

Source: Authors’ calculations based on data from the National Science Foundation’s Scientists and Engineers Statistical Data System (SESTAT) 1995–2008.

Notes: All men and women graduating with a STEM bachelor’s degree between 1970 and 2004, working at least thirty-five hours a week in a STEM occupation. Results from OLS regressions of logged hourly wages on indicator for female. Dark bar represents coefficient on female in OLS regression with no other controls (model 1 from table 1). Light shaded bar represents coefficient on female in OLS regression with full set of controls (model 5 from table 1). Each bar represents a different regression. Regressions run separately by race and STEM field. Wages are calculated by dividing annual salary by number of weeks worked per year and average number of hours worked per week. All wages reported in 2014 dollars. Regressions weighted by person weights. Italicized terms indicate significantly different from zero at the p < 0.05 level.

Direct correspondence to: Katherine Michelmore at kmichelm@umich.edu, 935 S. State St. Ann Arbor, MI 48109; and Sharon Sassler at sharon.sassler@cornell.edu, Department of Policy Analysis and Management, Cornell University, 297 Martha Van Rennselaer Hall, Ithaca, NY 14850.
Copyright © 2016 Russell Sage Foundation

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