生产力
业务
因子(编程语言)
全要素生产率
经济
计算机科学
程序设计语言
宏观经济学
作者
Qinyuan Xue,Y. J. Jin,Cheng Zhang
标识
DOI:10.1016/j.irfa.2024.103381
摘要
As a measure of corporate environmental, social, and governance (ESG) performance, ESG ratings have increasingly gained attention from corporations, the public, and government agencies, gradually becoming a key factor influencing their perceptions and decision-making regarding corporations. This study explores the impact of corporate ESG ratings on Total Factor Productivity (TFP) and its underlying mechanisms. Using listed companies in China as the research sample, it was found that higher ESG ratings significantly enhance corporate TFP, a conclusion that holds even after conducting robustness checks and addressing endogeneity issues. Further analysis indicates that high ESG ratings improve corporate TFP by reducing financing constraints and increasing government subsidies. Heterogeneity analysis shows that the effect of ESG ratings on enhancing TFP is more pronounced for corporations with high levels of attention, good reputations, and high audit quality. Additionally, the study also examines whether ESG ratings can serve as an effective predictor of corporate TFP. By applying machine learning algorithms for validation, the results show that incorporating ESG ratings significantly improves the accuracy of predictions for corporate TFP.
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