ESG is emerging as a new benchmark for measuring a company's sustainable development capabilities and social impact. As a measure of ESG performance, ESG ratings are increasingly receiving attention from companies, the general public, and government institutions, and are becoming an important reference factor influencing their decision-making. This paper investigates the impact of corporate ESG ratings on Total Factor Productivity (TFP) and its mechanisms of action. Focusing on listed companies in China, we find that higher ESG ratings contribute to improving a company's TFP, and this conclusion remains valid after robustness tests and addressing endogeneity issues. Further exploration into the reasons behind this result reveals that ESG ratings can be seen as a signal that a company sends to the outside world, representing its overall performance. Higher ESG ratings enhance a company's TFP by reducing market financing constraints and obtaining government subsidies. Heterogeneity analysis shows that the positive impact of ESG ratings on TFP is more pronounced for companies with higher levels of attention, reputation, and audit quality. Additionally, we explore whether ESG ratings can serve as a predictive indicator for measuring a company's TFP. This hypothesis was tested using machine learning algorithms, and the results indicate that models incorporating ESG rating indicators significantly improve the accuracy of predicting a company's TFP capabilities.

This paper examines the impact of ESG rating divergence on stock price delays in the context of the Chinese capital market. We find that ESG rating divergence significantly increases the stock price delays. Mechanism analysis results suggest that ESG rating divergence affects stock price delays by reducing information transparency and firm internal control quality. Heterogeneous analysis results indicate that the impact of ESG rating divergence on stock price delays is more pronounced in high-tech firms and when investor sentiment is high.

There is substantial evidence indicating that enterprises are negatively impacted by climate risk, with the most direct effects typically occurring in financial domains. This study examines A-share listed companies from 2007 to 2023, employing text analysis to develop the firm-level climate risk indicator and investigate the influence on corporate financial risk. The results show a significant positive correlation between climate risk and financial risk at the firm level. Mechanism analysis shows that the negative impact of climate risk on corporate financial condition is mainly achieved through three paths: increasing financial constraints, reducing inventory reserves, and increasing the degree of maturity mismatch. To address potential endogeneity, this study applies instrumental variable tests, propensity score matching, and a quasi-natural experiment based on the Paris Agreement. Additional tests indicate that reducing the degree of information asymmetry and improving corporate ESG performance can alleviate the negative impact of climate risk on corporate financial conditions. This relationship is more pronounced in high-carbon emission industries. In conclusion, this research deepens the understanding of the link between climate risk and corporate financial risk, providing a new micro perspective for risk management, proactive governance transformation, and the mitigation of financial challenges faced by enterprises.

We evaluate the impact of digital finance on the ESG performance of manufacturing enterprises and whether digital and traditional finance play a complementary or substitute role in promoting the ESG performance. First, we find that developing digital finance can alleviate financing constraints and promote technological innovation, thereby increasing enterprises' investment in environmental, social, and governance, providing sufficient technical support, and improving their ESG performance. Furthermore, digital finance and traditional finance have a direct impact on the ESG performance and further enhance their influence through complementary effects. Therefore, this paper may provide a valuable reference for finance to support manufacturing enterprises' development effectively.

The study indicates that under conditions of financial repression, a enterprise’s ESG performance significantly impacts the extent of its short-term debt used for long-term purposes. The mechanism test reveals that ESG performance mitigates the degree of short-term debt for long-term use through three pathways: enhancing information transparency, alleviating financing constraints, and curbing excessive investment. Further research suggests that the influence of ESG performance on the use of short-term debt for long-term purposes is more pronounced among private enterprises, high-pollution and high-energy-consuming enterprises, and enterprises in underdeveloped regions. This paper enriches the research on the relationship between ESG performance and corporate financing decisions.

This paper investigates whether Environmental, Social, and Governance (ESG) performance influences the stock idiosyncratic risk and extreme risk. We find that the ESG performance of listed companies significantly reduces the stock idiosyncratic risk and extreme risk. Furthermore, we identify that this mitigating effect is shaped by the nature of enterprise ownership and the firm life cycle. Through additional mechanistic analysis, we confirm that ESG performance affects the stock price volatility risk of listed companies by reducing levels of corporate earnings management and bolstering corporate reputation, thereby alleviating both idiosyncratic risk and extreme risk in stock prices.

This paper proposes the concepts of ESG information flows and a predictable framework of ESG flows based on AR process, and studies how ESG information flows are incorporated into and affect a dynamic portfolio with transaction costs. Two methods, called the ESG factor model and the ESG preference model, are considered to embed ESG information flows into a dynamic mean-variance model. The dynamic optimal portfolio can be expressed as a traditional optimal portfolio without ESG information and a dynamic ESG preference portfolio, and the impact of ESG information on optimal trading is explicitly analyzed. The rich numerical results show that ESG information can improve the out-of-sample performance, and ESG preference portfolio has the best out-of-sample performance including the net returns, Sharpe ratio and cumulative return of portfolios, and contribute to reducing risk and transaction costs. Our dynamic trading strategy provides valuable insights for sustainable investment both in theory and practice.

摘 要：本文基于利益相关者理论、信号传递理论和委托代理理论分析了企业 ESG 表现对绿色创新绩效可能的影响及其机制，并以 2009—2021 年中国 A 股上市公司为样本，实证分析了企业 ESG 表现的绿色创新效应。从机制分析发现，ESG 表现主要通过缓解融资约束、提高人力资本水平促进企业绿色创新绩效。从拓展性研究发现，ESG 表现的三个子维度都有助于提升绿色创新绩效，且公司治理表现的提升效应最强；ESG 表现不仅提高企业策略性绿色创新绩效、独立绿色创新绩效，还可提升实质性绿色创新绩效、合作绿色创新绩效。

立足于当前民营企业“反向混改”积极推进和 ESG 实践蓬勃发展的大背景,文章以2010—2020 年存在国有资本参股的 A 股民营上市公司为样本,检验国有股东委派董事对民营企业善待员工的影响、机制及边界条件。结果发现,国有股东委派董事显著提升了民营企业的员工责任分数,有利于民营企业善待员工。机制分析表明,国有股东委派董事通过提供资源支持和增加社会关注促进民营企业履行善待员工的社会责任。异质性分析表明,上述结果在管理层短视程度较高、行业集中度较高以及劳动密集度较低的样本中更加显著。进一步考虑国有股东的异质性特征发现,当国有股东为战略型投资者以及与民营企业位于同一注册地时,其委派董事对民营企业善待员工的促进作用更加显著。文章从董事会层面混合治理的视角厘清了国资参股促进民营企业善待员工的机制和作用条件,为民营企业通过制度设计实现“高质量”混合以及借助“反向混改”的契机改善ESG 实践提供了一定的启示。

This paper investigates the effect of exchange-traded funds (ETFs) on the ESG performance of their underlying firms. Using data from China, we find that ETFs enhance the ESG performance of their underlying firms. This finding remains consistent after several robustness and endogeneity tests. Further, we show that the effect is more pronounced for non-SOEs, firms in low-polluting industries, and firms at growth and maturity stages. Studying the mechanisms behind these results, we find that ETFs mitigate the corporate agency problems, enhance the willingness of managers to invest in ESG, and improve the ESG performance.