Gender influences on earnings of obstetrician-gynecologists.
OBJECTIVE
To test the hypothesis that the observed difference in earnings between male and female obstetrician-gynecologists could be explained by variations in productivity and human capital.


METHODS
Data from a 1991 national survey of ACOG Fellows were used to provide a descriptive analysis of male and female obstetrician-gynecologists' demographic characteristics, net income, experience, practice characteristics, workload, and practice activities. Variables found to have a significant impact on net income or to vary significantly by sex were included in a multiple regression analysis.


RESULTS
Twenty-one percent of the 1286 survey respondents were female obstetrician-gynecologists. Women were almost twice as likely as men to be in salaried positions (P < .001) and more than twice as likely to have less than 10 years of experience (P < .001). Women reported fewer annual patient-contact hours (P < .05) and performed fewer than half as many hysterectomies (P < .001). Average annual earnings for women were 71% of men's annual net income (P < .001). The multivariate regression analysis found that male-female differences in the factors included in the analysis (ie, workload, experience, practice type) resulted in an 18.7% male-female income gap. The analysis also revealed an income gap of 14.2% that was not accounted for by differences in the objective factors included in the model.


CONCLUSIONS
More than half of the overall male-female income gap was explained by differences in personal and practice characteristics. However, female obstetrician-gynecologists earned 14.2% less than men, after controlling for variations in productivity and human capital.
Kelly
R W
RW
American College of Obstetricians and Gynecologists, Washington, DC, USA.
Pereles
S A
SA
D000328:Adult; D005260:Female; D006176:Gynecology / Q000191:economics* / Q000706:statistics & numerical data; D006801:Humans; D007182:Income / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009774:Obstetrics / Q000191:economics* / Q000706:statistics & numerical data; D012044:Regression Analysis; D017678:Sex Distribution; D012737:Sex Factors