Threat or shield: Environmental administrative penalties and corporate greenwashing

Kuo Zhou, Zhi Qu, Jiayang Liang, Yunqing Tao and Mengting Zhu

Finance Research Letters, 2024, vol. 61, issue C

Abstract: We develop a method that identifies corporate greenwashing adopting a deep learning algorithm and find a robust positive association between environmental administrative penalties and corporate greenwashing. We also find that opportunistic management tendencies and heightened external pressures motivate firms to greenwash after such penalties. Additionally, firms with weak internal control quality, operating within fiercely competitive industries, or located in regions of severe environmental pollution are more inclined to greenwash to mitigate losses stemming from administrative penalties. Our work provides theoretical insights into the effectiveness of environmental penalties and contributes to the ongoing regulation and disclosure debate.

Keywords: Corporate greenwashing; Environmental administrative penalties; Deep learning; Textual analysis; Impression management (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:61:y:2024:i:c:s1544612324000618

DOI: 10.1016/j.frl.2024.105031

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