Gender stereotypes in job advertisements: What do they imply for the gender salary gap?
Eva Arceo-Gomez (),
Raquel Y. Badillo and
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Raquel Y. Badillo: Banco de México
Sergio Lopez-Araiza: Instituto Tecnológico Autónomo de México
Journal of Labor Research, 2022, vol. 43, issue 1, No 3, 65-102
Abstract Gender stereotypes, the assumptions concerning appropriate social roles for men and women, permeate the labor market. Analyzing information from over 2.5 million job advertisements on three different employment search websites in Mexico, exploiting approximately 235,00 that are explicitly gender-targeted, we find evidence that advertisements seeking “communal” characteristics, stereotypically associated with women, specify lower salaries than those seeking “agentic” characteristics, stereotypically associated with men. Given the use of gender-targeted advertisements in Mexico, we use a random forest algorithm to predict whether non-targeted ads are in fact directed toward men or women, based on the language they use. We find that the non-targeted ads for which we predict gender show larger salary gaps (8–35 percent) than explicitly gender-targeted ads (0–13 percent). If women are segregated into occupations deemed appropriate for their gender, this pay gap between jobs requiring communal versus agentic characteristics translates into a gender pay gap in the labor market.
Keywords: Gender stereotypes; Salary gap; Discrimination; Big data; Machine learning; Mexico (search for similar items in EconPapers)
JEL-codes: C52 C53 E24 J64 O54 (search for similar items in EconPapers)
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