Female Leadership and Financial Performance: A Meta-Analysis
Female Leadership and Financial Performance: A Meta-Analysis
Author: |
Katarina Gomoryova |
---|---|
Published in: | IES Working Papers 6/2024 |
Keywords: | meta-analysis, publication bias, Bayesian Model Averaging, female leadership, gender diversity, financial performance |
JEL codes: |
J23, J24, J31 |
Suggested citation: |
Gomoryova K. (2024): " Female Leadership and Financial Performance: A Meta-Analysis" IES Working Papers 6/2024. IES FSV. Charles University. |
Abstract: |
Is female leadership the secret ingredient to financial prosperity? This question has been the subject of extensive research, yet the findings remain inconclusive. We aim to provide a comprehensive understanding of this relationship employing contemporary techniques on the up-to-date dataset comprising 1,131 estimates gathered from 96 distinct studies. We address the pervasive issue of publication bias resulting in the mild preference for positive outcomes. After filtering out this bias, the study finds a negligible mean effect estimate, suggesting that the impact of women in leadership on financial performance is minimal. We further explore the potential factors that could account for variations in the estimated effects across different studies. Utilising Bayesian Model Averaging, weighted by the inverse number of estimates, we identify thirteen significant moderators that influence the relationship under study. Among these, the proportion of female authors, the impact factor of the journal, the duality of the CEO role, and the tenure of leaders are found to exert the most positive influence on the effect. Conversely, the age of leaders pushes effect the most in the opposite direction. Other influential factors include the publication status of the article, the number of variables used in the study, publication bias, the use of random estimation and matching approaches, the use of accounting-based financial measures, focus on the emerging market, and the representation of the leadership variable as a proportion. |
Download: | wp_2024_06_gomoryova |