State liberalism, female supervisors, and the gender wage gap

Soc Sci Res. 2015 Mar:50:126-38. doi: 10.1016/j.ssresearch.2014.11.005. Epub 2014 Nov 25.

Abstract

Whereas some are concerned that the gender revolution has stalled, others note the rapid increase in women's representation in the ranks of management, and the reduction of wage inequality in larger and more active welfare states. Although these latter trends portend an attenuation of gender inequality, their effects on the gender pay gap in the U.S. are understudied due to data limitations, or to the assumption that in the U.S. pay is determined by market forces. In this study we extend research on the determinants of the gender wage gap by examining sex-of-supervisor effects on subordinates' pay, and to what degree the state's commitment to equality conditions this relationship. We pooled the 1997 and 2002 National Study of the Changing Workforce surveys to estimate hierarchical models of reporting to a female supervisor and wages, with theoretically important predictors at the individual level, and at the state of residence (an index composed of women's share of legislators, a measure of the liberal leanings of the state, and the size of the public sector relative to the labor force). We found that state effects on pay were mixed, with pay generally rising with state liberalism on the one hand. On the other hand, working for a female boss significantly reduced wages. We discussed the theoretical implications of our results, as well as the need for further study of the career effects on subordinates as women increasingly enter the ranks of management.

Keywords: Female supervisors; Gender inequality; Sex gap in pay.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Female
  • Humans
  • Income / statistics & numerical data*
  • Male
  • Middle Aged
  • Organization and Administration / economics
  • Organization and Administration / statistics & numerical data*
  • Politics*
  • Sex Factors
  • Sexism / economics*
  • Sexism / statistics & numerical data
  • United States
  • Women
  • Young Adult