Abstract: Third-party institutions' ESG evaluations furnish stakeholders with vital insights into a company's sustainable development. However, the economic implications and mechanisms of divergent evaluations remain a subject of ongoing debate. Employing an information utilization framework, this study examines two opposing mechanisms based on uncertain and heterogeneous information from an analyst's perspective. The study analyzes the ratings data of seven different ESG rating agencies for Chinese A-share listed companies from 2017 to 2021, empirically testing these two mechanisms. The results show that ESG evaluation divergence actually reduces analysts' forecast errors, confirming the effectiveness of the heterogeneous information mechanism. This finding indicates that while ESG evaluation divergence may increase market uncertainty, the heterogeneous information it contains positively impacts analysts' predictions of company's future performance. Furthermore, the study delves into how ESG evaluation divergence reduces analysts' forecast errors. It reveals that the divergence effectively captures key information closely related to a company's earnings per share, significantly enhancing analysts' accuracy in forecasting a company's financial status and future performance. Additionally, the research finds that in companies with higher information asymmetry, particularly where information disclosure is insufficient or lacks transparency, ESG evaluation divergence provides analysts with more comprehensive and in-depth insights. The study also explores the relationship between ESG evaluation divergence and financial indicators (such as ROA and ROE), as well as stock returns, controlling for the average ESG score. It finds a positive correlation between ESG evaluation divergence and these financial indicators, confirming its informational effect. This suggests that ESG evaluation divergence not only provides multidimensional information but may also serve as a market indicator for predicting a company's financial and stock performance. In summary, this paper supplements existing ESG literature from the new perspective of evaluation divergence and elucidates the informational effects and intrinsic mechanisms of ESG evaluation divergence. These findings offer a fresh perspective on the role of analysts in ESG evaluations and provide theoretical and empirical support for improving the quality of ESG assessments. Practically, these insights are significant in assisting analysts and investors in more accurately and comprehensively assessing corporate ESG performance. Moreover, the results suggest that policymakers and rating agencies should focus on unifying and refining ESG evaluation standards to promote effective market operation and sustainable corporate development.

Key words: ESG, ESG Discrepancies, Informational Impact, Analysts

摘要： 第三方机构的ESG评价结果为使用者提供企业的可持续发展信息,然而评价分歧的经济后果及其机制尚未形成共识。本文研究ESG评价分歧的信息效应,基于信息使用框架,从分析师角度出发,提出基于不确定性信息和异质性信息的两种对立机制,利用2017—2021年7家不同ESG评价机构的得分数据对上述机制进行验证。结果表明,ESG评价分歧会降低分析师预测误差,从而支持异质性信息的观点。研究还发现,ESG评价分歧通过反映企业每股收益和提高市场分析师整体预测质量来降低分析师预测误差。此外,ESG评价分歧能够为分析师提供信息不对称程度高企业的更多信息。在控制ESG得分均值的情况下,ESG评价分歧与ROA、ROE和个股回报率呈现正相关关系,进一步验证了信息效应。本文不仅以评价分歧的新视角补充了ESG相关文献,还阐明了ESG评价分歧的信息效应及其机制,为后续的高质量ESG评价提供了理论和实证支持。

关键词: ESG, ESG分歧, 信息效应, 分析师