Are ESG performance-based incentives a panacea or a smokescreen for excess compensation?

激励 公司治理 高管薪酬 企业社会责任 业务 灵丹妙药 股东 会计 公共经济学 经济 公共关系 微观经济学 财务 政治学 医学 替代医学 病理
作者
S. Leanne Keddie,Michel Magnan
出处
期刊:Sustainability Accounting, Management and Policy Journal [Emerald Publishing Limited]
卷期号:14 (3): 591-634 被引量:12
标识
DOI:10.1108/sampj-11-2022-0605
摘要

Purpose This paper aims to examine how the use of environmental, social and governance (ESG) incentives intersects with top management power and various corporate governance mechanisms to affect excess annual cash bonus compensation. Design/methodology/approach The authors use a novel artificial intelligence (AI) technique to obtain data about ESG incentives use by firms in the S&P 500. The authors test the hypotheses with an endogenous treatment-regression and a contrast test. Findings When the top management team has power and uses ESG incentives, there is a 32% reduction in excess annual cash bonuses implying ESG incentives are an effective corporate governance tool. However, nuanced analyses reveal that when powerful management teams with ESG incentives are from environmentally sensitive industries, have a corporate social responsibility (CSR) committee or have long-term view institutional shareholders, they derive excess bonuses. Practical implications Stakeholders will better understand management’s motivations for the inclusion of ESG incentives in executive compensation contracts and be able to identify situations which require closer scrutiny. Social implications Given the increased popularity of ESG incentives, society, regulators, boards of directors and management teams will be interested in better understanding when these incentives might be effective and when they might be abused. Originality/value To the best of the authors’ knowledge, this study is the first to examine the use of ESG incentives in relation to excess pay. The authors contribute to both the CSR and executive compensation literatures. The work also uses a new methodological technique using AI to gather difficult-to-obtain data, opening new avenues for research.
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