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Women on boards and bank earnings management: From zero to hero

Fan, Yaoyao, Jiang, Yuxiang, Zhang, Xuezhi, Zhou, Yue·2019·Journal of Banking & Finance

Abstract

We examine how women on boards influence bank earnings management. Using the likelihood of a board appointing women directors based on a Blau index of gender diversity in each director's total employment connections outside our sample banks for identification, we find an inverted U-shaped relation between women on boards and bank earnings management. Specifically, when there exists only a marginal number of women directors, banks are more likely to manipulate earnings. But, when the number of women directors reaches three or more, bank earnings management declines. This inverted U-shaped impact is intensified if women sit on audit or nomination committees, is moderated if women directors have higher education levels and more board experience, and is unchanged during the 2007–2009 financial crisis. Our results hold when we use alternative measures of bank earnings management, employ GMM estimations and test for alternative hypotheses for the inverted U-shaped relation.

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Metadata

Authors
Fan, Y., Jiang, Y., Zhang, X., & Zhou, Y.
Venue
Journal of Banking & Finance
Publisher
Elsevier BV
Published
2019-10
Volume
107
Pages
105607
ISSN
0378-4266 (ISSN-L)
OpenAlex
W2964755164
Cited by
239
References
2
FWCI
36.81
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Women on boards and bank earnings management: From zero to hero. https://app.cochat.ai/papers/10.1016/j.jbankfin.2019.105607
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Fan, Y., Jiang, Y., Zhang, X., & Zhou, Y. (2019). Women on boards and bank earnings management: From zero to hero. Journal of Banking & Finance. https://doi.org/10.1016/j.jbankfin.2019.105607

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.