Gender Discrimination in Job Ads: Evidence from China*

By Peter Kuhn, Kailing Shen. 2013

263 citations recorded by the source corpus.

We study explicit gender discrimination in a population of ads on a Chinese Internet job board. Gender-targeted job ads are common, favor women as often as men, and are much less common in jobs requiring higher levels of skill. Employers' relative preferences for female versus male workers, on the other hand, are more strongly related to the preferred age, height, and beauty of the worker than to job skill levels. Almost two thirds of the variation in advertised gender preferences occurs within firms, and one third occurs within firmoccupation cells. Overall, these patterns are not well explained by a firm-level animus model, by a glass-ceiling model, or by models in which broad occupational categories are consistently gendered across firms. Instead, the patterns suggest a model in which firms have idiosyncratic preferences for particular job-gender matches, which are overridden in skilled positions by factors such as thinner labor markets or a greater incentive to search broadly for the most qualified candidate. JEL Codes: J16, J63, J71. Copyright 2013, Oxford University Press.

Subfields: Economics and Econometrics, Gender Studies, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/6a9bce10ce70e2919a16ceb42a17304543d8cfa1

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Citations in the corpus

Fairness Under Composition (2018, background): “Although the formal statement of Theorem 11 only implies that individually fair classifiers exist that exhibit unfairness under task-competitive composition, our intuition suggests that this happens often in practice and that small relaxations will not be sufficient to alleviate this problem, as the”
Opening the Black Box of the Matching Function: The Power of Words (2020, background): “…search literature analyzing firms’ strategies for finding the right match (Barron et al., 1985, 1987) as well as the emerging empirical literature on online job search (see e.g. Kuhn & Shen, 2012; Brenc̆ic̆ & Norris, 2012; Pallais, 2012; Faberman & Kudlyak, 2014; Marinescu, 2014; Gee, 2014).”
The Forgotten Margins of AI Ethics (2022, background): “allocations [60, 63, 80], to discriminatory targeted ads [4, 46, 71], algorithmic systems present real harm to the most marginalized groups of society and furthermore pose a threat to human welfare, freedom, and privacy.”
Who Wears the Pants? Gender Identity Norms and Intrahousehold Financial Decision‐Making (2017, unknown): “Even if women decide to participate in the labor force, gender norms play a major role in recruiting processes (Kuhn and Shen, 2013).”