Trends in the earnings gender gap among dentists, physicians, and lawyers

J Am Dent Assoc. 2017 Apr;148(4):257-262.e2. doi: 10.1016/j.adaj.2017.01.005. Epub 2017 Feb 24.


Background: The authors examined the factors associated with sex differences in earnings for 3 professional occupations.

Methods: The authors used a multivariate Blinder-Oaxaca method to decompose the differences in mean earnings across sex.

Results: Although mean differences in earnings between men and women narrowed over time, there remained large, unaccountable earnings differences between men and women among all professions after multivariate adjustments. For dentists, the unexplained difference in earnings for women was approximately constant at 62% to 66%. For physicians, the unexplained difference in earnings for women ranged from 52% to 57%. For lawyers, the unexplained difference in earnings for women was the smallest of the 3 professions but also exhibited the most growth, increasing from 34% in 1990 to 45% in 2010.

Conclusions: The reduction in the earnings gap is driven largely by a general convergence between men and women in some, but not all, observable characteristics over time. Nevertheless, large unexplained gender gaps in earnings remain for all 3 professions.

Practical implications: Policy makers must use care in efforts to alleviate earnings differences for men and women because measures could make matters worse without a clear understanding of the nature of the factors driving the differences.

Keywords: Blinder-Oaxaca decomposition; Salary; earnings disparities; professionals.

MeSH terms

  • Dentists / economics*
  • Dentists / statistics & numerical data
  • Dentists, Women / economics
  • Dentists, Women / statistics & numerical data
  • Female
  • Humans
  • Income / statistics & numerical data*
  • Lawyers / statistics & numerical data*
  • Male
  • Physicians / economics*
  • Physicians / statistics & numerical data
  • Physicians, Women / economics
  • Physicians, Women / statistics & numerical data
  • Sexism / economics*
  • Sexism / statistics & numerical data
  • United States