The effects of ESG controversies and women on boards on ESG-washing behavior: Global evidence from the banking industry
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DOIhttp://dx.doi.org/10.21511/bbs.20(2).2025.01
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Article InfoVolume 20 2025, Issue #2, pp. 1-14
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This study analyzes the effects of environmental, social, and governance (ESG) controversies and the presence of women on boards on ESG-washing practices in the global banking sector. ESG washing is a manipulative practice in ESG disclosure where companies highlight positive information to conceal poor sustainability performance. This study employs a panel dataset from 279 public banks in 67 countries, covering five major regions – Asia, Europe, Africa, America, and Oceania – over the period 2011 to 2023. Data were obtained from Refinitiv Eikon and Bloomberg for bank-level information, as well as the World Bank for macroeconomic data. The results show that ESG controversies significantly drive ESG washing. Banks involved in controversies tend to use manipulative ESG disclosures to protect their reputation and mitigate the impact of scandals. Conversely, the presence of women on the board has a significant mitigating effect on ESG washing. This study also identifies a critical mass effect, where the positive influence of women on boards in reducing ESG washing becomes optimal when their representation reaches a certain level. These findings have important implications for policymakers and regulators to promote inclusive governance and sustainability transparency, particularly through increasing gender diversity on boards of directors. Furthermore, these results indicate that good governance, supported by adequate representation of women, can help combat unethical practices such as ESG washing in the global banking sector.
- Keywords
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JEL Classification (Paper profile tab)G30, J16, G21, M14
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References51
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Tables8
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Figures0
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- Table 1. Baseline results
- Table 2. Quadratic regression
- Table 3. Robustness check by decomposing ESG washing pillars
- Table 4. Robustness test using the instrumental variable (IV)
- Table 5. Robustness test using subsample analysis
- Table A1. Variables and definitions
- Table B1. Descriptive statistics
- Table C1. Pairwise correlations
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