The masculinity of money: Automatic stereotypes predict gender differences in estimated salaries

Melissa J. Williams, Elizabeth Levy Paluck, Julie Spencer-Rodgers

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

We present the first empirical investigation of why men are assumed to earn higher salaries than women (the salary estimation effect). Although this phenomenon is typically attributed to conscious consideration of the national wage gap (i.e., real inequities in salary), we hypothesize instead that it reflects differential, automatic economic valuing of men and women. In the four studies described here, we demonstrate that the salary estimation effect is present in both student and community samples, is not explained by participants' awareness of real gender inequities in pay, and appears in descriptive tasks (i.e., estimating what men and women do earn; Studies 1 and 2) as well as in a prescriptive task (i.e., determining what men and women should earn; Study 3). Further, the salary estimation effect is best predicted by the degree to which participants hold an automatic stereotype that links men, more than women, with wealth (Study 4). These results suggest that differential estimates of men's and women's salaries, rather than deliberately reflecting reality, instead indicate a male-wealth stereotype that operates largely outside of awareness. We discuss the implications of these results for salary decision making and the unintentional perpetuation of the gender gap in wages.

Original languageEnglish (US)
Pages (from-to)7-20
Number of pages14
JournalPsychology of Women Quarterly
Volume34
Issue number1
DOIs
StatePublished - Mar 1 2010

All Science Journal Classification (ASJC) codes

  • Gender Studies
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Psychology(all)

Fingerprint Dive into the research topics of 'The masculinity of money: Automatic stereotypes predict gender differences in estimated salaries'. Together they form a unique fingerprint.

Cite this