Examining CEO Characteristics and Carbon Emissions: A Quantile Approach to UK-Listed Firms
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| Publicado en: | Sustainability vol. 17, no. 13 (2025), p. 5732-5750 |
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| Autor principal: | |
| Otros Autores: | , , , |
| Publicado: |
MDPI AG
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| Resumen: | This study aims to empirically examine the effects of CEO characteristics (gender, nationality, multiple directorships) on the carbon emissions of UK-listed firms. We focus on understanding how these factors influence carbon emissions across the overall sample and within specific industry sectors grounded on the upper echelons and stakeholder theories. We employed a quantitative research design using quantile regression analysis. Our dataset comprises 295 UK-listed firms from the STOXX 600 Index of European-listed companies, covering the period from 1999 to 2023. Data were sourced from BoardEx, Refinitiv DataStream, annual reports, and sustainability reports. Our results indicate that foreign CEOs are associated with higher carbon emissions across the overall sample of UK-listed firms, across the three levels of carbon emitters within the sensitive industries, and within low- and high-level emitters within the non-sensitive industries. CEOs with multiple directorships were found to have a significant association with higher carbon emissions, likely due to divided attention and obligations. As for the CEO gender, it is noteworthy that it has an insignificant effect on reducing carbon emissions in low emission companies within sensitive industries. In contrast, female CEOs were associated with lower carbon emissions in medium-emitting firms within non-sensitive industries. This study contributes to existing literature by employing sensitivity analysis (sensitive sectors and non-sensitive). The study also employs a novel econometric technique, quantile regression, which provides a comprehensive understanding of the relationship between independent and dependent variables across different points of the distribution. |
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| ISSN: | 2071-1050 |
| DOI: | 10.3390/su17135732 |
| Fuente: | Publicly Available Content Database |