1. Does Science Promote Women? Evidence from Academia: 1973-2001 for presentation at: Science and Engineering Workforce Project at NBER October 20, 2005 Donna K. Ginther University of Kansas Shulamit Kahn Boston University

2. Introduction Federal agencies and others monitor the status of women in science and find they are under- represented without evaluating likely causes. Federal agencies and others monitor the status of women in science and find they are under- represented without evaluating likely causes. CAWMSET (2000) CAWMSET (2000) GAO (2004) GAO (2004) Nelson and Rogers (2005) Nelson and Rogers (2005)

3. Introduction January 16, 2004 Chronicle of Higher Education reports: Women are Underrepresented in Sciences at Top Research Universities January 16, 2004 Chronicle of Higher Education reports: Women are Underrepresented in Sciences at Top Research Universities Is under-representation caused by the promotion process? Is under-representation caused by the promotion process?

4. Research Question Does Science Promote Women? Does Science Promote Women? We examine gender differences in: We examine gender differences in: Tenure Track jobs Tenure Track jobs Promotion to Tenure Promotion to Tenure Promotion to Tenured, Full Professor Promotion to Tenured, Full Professor We find negligible gender differences in promotion. We find negligible gender differences in promotion.

5. Literature Review From Scarcity to Visibility, Long et. al. (2001) From Scarcity to Visibility, Long et. al. (2001) Shows that women in science, broadly defined, have made progress Shows that women in science, broadly defined, have made progress Representation, Salary, Promotion Representation, Salary, Promotion Aggregates data such that its difficult to observe problems Aggregates data such that its difficult to observe problems

6. Literature Review Women in Science, Xie and Shauman (2003) Women in Science, Xie and Shauman (2003) Life course approach to science careers Life course approach to science careers Sex differences in research productivity have declined, explained by observable characteristics Sex differences in research productivity have declined, explained by observable characteristics Find small pay differences, some promotion differences for nonacademics Find small pay differences, some promotion differences for nonacademics

7. Literature Review Promotion in Science Promotion in Science NSF (2004) NSF (2004) Finds significant gender gap in promotion in science Finds significant gender gap in promotion in science Gap is reduced after controlling for family characteristics Gap is reduced after controlling for family characteristics Combine science and social science in the analysis Combine science and social science in the analysis

8. Literature Review Academic Labor Markets Academic Labor Markets Promotion differentials: Long, Allison and McGinnis (1993) Kahn (1993, 1995) Ginther and Kahn (2004) Promotion differentials: Long, Allison and McGinnis (1993) Kahn (1993, 1995) Ginther and Kahn (2004) Ginther and Hayes 1999, 2003; Ginther 2004, 2003, 2001 Ginther and Hayes 1999, 2003; Ginther 2004, 2003, 2001 There is no, single academic labor market. There is no, single academic labor market.

9. Data Use 1973 - 2001 Survey of Doctorate Recipients (SDR) Use 1973 - 2001 Survey of Doctorate Recipients (SDR) Biennial, Longitudinal Survey of U.S. Doctorates Biennial, Longitudinal Survey of U.S. Doctorates Used by NSF to analyze scientific labor force Used by NSF to analyze scientific labor force

10. Data Longitudinal Sample: Individuals who received their Ph.D. between 1972 and 1991 observed between 1973 and 2001. Longitudinal Sample: Individuals who received their Ph.D. between 1972 and 1991 observed between 1973 and 2001. Tenure-track sub-sample: Those who report ever having a tenure- track job. Tenure-track sub-sample: Those who report ever having a tenure- track job.

11. Data Academics in the Sciences: Academics in the Sciences: Life Sciences Life Sciences Agriculture and Food Science Agriculture and Food Science Biology and Life Sciences Biology and Life Sciences Physical Sciences Physical Sciences Chemistry Chemistry Earth Science Earth Science Physics Physics Computer Science / Mathematics Computer Science / Mathematics Engineering Engineering

12. Data Dependent variables: Dependent variables: Probability of Tenure Track job Probability of Tenure Track job Probability of Promotion to tenure and full professor Probability of Promotion to tenure and full professor Duration between Ph.D. and promotion to tenure and full professor Duration between Ph.D. and promotion to tenure and full professor

13. Data Independent variables: Independent variables: Gender Gender Age Ph.D. Age Ph.D. Year Ph.D. Year Ph.D. Race Race Academic field Academic field Degree institution characteristics Degree institution characteristics

14. Data Time-varying Independent variables: Time-varying Independent variables: University/College employer characteristics University/College employer characteristics Rank and Tenure status Rank and Tenure status Primary / Secondary work activities Primary / Secondary work activities Government Support of Research Government Support of Research Publications**** Publications****

15. Data Difficulties Biennial Survey Biennial Survey Changes in the sampling frame Changes in the sampling frame Numerous missing observations, required a lot of imputation Numerous missing observations, required a lot of imputation Imputed productivity from three years of observed publications Imputed productivity from three years of observed publications

16. Empirical Methods Probit models (dependent variable): Probit models (dependent variable): Tenure track within 5 years of Ph.D. Tenure track within 5 years of Ph.D. Tenured at 11 years after Ph.D. Tenured at 11 years after Ph.D. Tenured, Full Professor at 15 years after Ph.D. Tenured, Full Professor at 15 years after Ph.D.

17. Empirical Methods Hazard of Promotion Hazard of Promotion Proportional Hazards Model with time-varying covariates Proportional Hazards Model with time-varying covariates Hazard model is preferred specification Hazard model is preferred specification

18. Stylized Facts Womens representation in science depends upon the field Womens representation in science depends upon the field Life ScienceProgress Life ScienceProgress Physical Science, Engineering,Anemic representation Physical Science, Engineering,Anemic representation

20. Probability of Tenure Track Job Model 1Model 2Model 3Model 4 Science-0.038-0.044-0.031-0.033 (0.009) (0.010) Life Science-0.041-0.059-0.075-0.077 (0.012)(0.013) Physical Science-0.0020.003-0.010-0.015 (0.016) (0.017) Engineering0.0000.0140.0090.013 (0.033)(0.034)(0.035) DemographicsNoYes Degree CharacteristicsNo Yes FieldsNo Yes

21. Probability of Tenure Track JobIncluding family variables ScienceLifePhys.Eng. Female0.1560.1080.2060.072 (0.018)(0.025)(0.029)(0.064) Female*Married-0.171-0.149-0.2360.009 (0.024)(0.033)(0.041)(0.092) Female*Total Children-0.029-0.022-0.055-0.053 (0.013)(0.017)(0.022)(0.045) Female*Young Children-0.059-0.068-0.0210.000 (0.028)(0.038)(0.050)(0.100)

24. Gender Promotion Gap Previous Research (Ginther and Kahn 2004; Ginther and Hayes 1999, 2003) has shown a significant gender promotion gap in Previous Research (Ginther and Kahn 2004; Ginther and Hayes 1999, 2003) has shown a significant gender promotion gap in Economics Economics Humanities Humanities What about science? What about science?

25. Promotion to Tenure Full Sample Life Science Physical Science Engineer Ing Female Probit Coefficient 0.00-0.030.010.02 Promoted 11 Yrs Ph.D. (0.88)(0.19)(0.73)(0.75) Survival Curve 1.260.350.000.49 Homogeneity (0.26)(0.55)(0.95)(0.49) Female Risk Ratio 0.971.021.001.06 (No Covariates) (0.33)(0.60)(0.96)(0.56) Model 1 Female Risk Ratio 0.950.890.931.00 (Covariates ex. Productivity) (0.14)(0.02)(0.22)(0.97) Model 2 Female Risk Ratio 0.970.920.94 1.03 (Including Productivity) (0.29)(0.07)(0.28)(0.82)

27. Promotion to Full Professor Full Sample Life Science Physical Science Engineer- ing Female Probit Coefficient -0.05-0.09-0.020.09 Promoted 15 Yrs Past Ph.D. (0.02)(0.00)(0.51)(0.37) Survival Curve 7.570.6111.590.14 Homogeneity (0.01)(0.44)(0.00)(0.71) Female Risk Ratio 0.900.960.790.95 (No Covariates) (0.01)(0.48)(0.00)(0.74) Model 1 Female Risk Ratio 0.950.930.871.09 (Covariates ex. Productivity) (0.34)(0.37)(0.11)(0.89) Model 2 Female Risk Ratio 0.970.960.89 1.04 (Including Productivity Covariates) (0.54)(0.61)(0.19)(0.82)

29. Tenure at Research I Full Sample Life Science Physical Science Engineer Ing Female Probit Coefficient 0.01-0.03-0.010.00 Promoted 15 Yrs Past Ph.D. (0.84)(0.40)(0.88)(0.97) Survival Curve 3.481.110.272.97 Homogeneity (0.06)(0.29)(0.61)(0.08) Female Risk Ratio 0.920.940.961.24 (No Covariates) (0.10)(0.35)(0.65)(0.14) Model 1 Female Risk Ratio 1.000.910.971.17 (Covariates ex. Productivity) (0.99)(0.22)(0.72)(0.33) Model 2 Female Risk Ratio 1.020.930.98 1.23 (Including Productivity Covariates) (0.75)(0.31)(0.86)(0.20)

30. Full Professor at Research I Full Sample Life Science Physical Science Engineer- ing Female Probit Coefficient -0.04-0.06-0.040.27 Promoted 15 Yrs Past Ph.D. (0.24)(0.11)(0.56)(0.09) Survival Curve 15.696.799.520.00 Homogeneity (0.00)(0.01)(0.00)(0.95) Female Risk Ratio 0.770.800.680.99 (No Covariates) (0.00)(0.02)(0.01)(0.95) Model 1 Female Risk Ratio 0.891.020.681.02 (Covariates ex. Productivity) (0.18)(0.87)(0.01)(0.95) Model 2 Female Risk Ratio 0.911.010.71 1.07 (Including Productivity Covariates) (0.23)(0.90)(0.03)(0.78)

31. Conclusions Does Science Promote Women? Does Science Promote Women? YES YES Gender differences in tenure track Gender differences in tenure track Explained by marriage and family. Explained by marriage and family. Little evidence of gender promotion gap to tenure, full professor. Little evidence of gender promotion gap to tenure, full professor.

32. Conclusions One exception: One exception: Full Professors in Physical Science at Research I Universities Full Professors in Physical Science at Research I Universities Each academic field presents different hurdles for women in terms of pay and promotion. Each academic field presents different hurdles for women in terms of pay and promotion. Science: 12% gender gap in salaries at Full Professor (Ginther 2004) Science: 12% gender gap in salaries at Full Professor (Ginther 2004)