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Gender Bias among Professionals: An Identity-Based Interpretation

Alice H. Wu
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Alice H. Wu: Harvard University

The Review of Economics and Statistics, 2020, vol. 102, issue 5, 867-880

Abstract: This paper measures gender bias in discussions about women versus men in an online professional forum. I study the content of posts that refer to each gender and the transitions in the topics between consecutive posts once attention turns to one gender or the other. Discussions about women tend to emphasize their personal characteristics instead of professional accomplishments. Posts about women are also more likely to lead to deviations from professional topics than are posts about men. I interpret these findings through a model that highlights posters' incentives to boost their own identities relative to the underrepresented out-group in a profession.

Date: 2020
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The Review of Economics and Statistics is currently edited by Pierre Azoulay, Olivier Coibion, Will Dobbie, Raymond Fisman, Benjamin R. Handel, Brian A. Jacob, Kareen Rozen, Xiaoxia Shi, Tavneet Suri and Yi Xu

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