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Cited by 289

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

Women directors, firm performance, and firm risk: A causal perspective

Open access
Yang, Philip, Riepe, Jan, Moser, Katharina, Pull, Kerstin, Terjesen, Siri·2019·The Leadership Quarterly

Abstract

Norway was the first of ten countries to legislate gender quotas for boards of publicly traded firms. There is considerable debate and mixed evidence concerning the implications of female board representation. In this paper, we explain the main sources of biases in the existing literature on the effects of women directors on firm performance and review methods to account for these biases. We address the endogeneity problem by using a difference-in-differences approach to study the effects of women directors on firm performance with specific consideration of the common trend assumption, and we explicitly distinguish between accounting-based (i.e., operating income divided by assets, return on assets) and market-based (i.e., market-to-book ratio and Tobin's Q) performance measures in the Norwegian setting. The control group are firms from Finland, Sweden, and Denmark. We further extend the analysis of causal effects of women directors to firm risk. Our results imply a negative effect of mandated female representation on firm performance and on firm risk.

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Metadata

Authors
Yang, P., Riepe, J., Moser, K., Pull, K., & Terjesen, S.
Venue
The Leadership Quarterly
Publisher
Elsevier BV
Published
2019-10
Volume
30
Issue
5
Pages
101297
ISSN
1048-9843 (ISSN-L)
OpenAlex
W2951046369
Cited by
289
References
14
FWCI
46.77
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Women directors, firm performance, and firm risk: A causal perspective. https://app.cochat.ai/papers/10.1016/j.leaqua.2019.05.004
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Yang, P., Riepe, J., Moser, K., Pull, K., & Terjesen, S. (2019). Women directors, firm performance, and firm risk: A causal perspective. The Leadership Quarterly. https://doi.org/10.1016/j.leaqua.2019.05.004

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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.