The growing emphasis on Environmental, Social, and Governance (ESG) principles, particularly in corporate sectors, shapes investment trends and operational strategies, whose shift is supported by the increasing role of media in monitoring and influencing corporate ESG performance, thereby driving the energy innovation. Therefore, based on reported events from Baidu News and patent text information of Chinese A-share listed companies from 2012 to 2022, this study innovatively applied machine learning and text analysis to measure ESG news sentiment and corporate energy innovation indicators. Combing with reputation, stakeholder, and agency theories, we find that a good reputation conveyed by positive ESG textual sentiments in the media significantly promotes corporate energy innovation, and the effect is mainly realized through alleviating financing constraints and agency problems and promoting green investment. Further analysis shows that ESG news sentiment promotes corporate energy innovation mainly among private firms, non-growth-stage firms, high-energy-consuming firms, and regions with better green finance development and higher ESG governance intensity. From the perspective of ESG news content and information content, greater ESG news attention can also exert an energy innovation incentive effect, in which the incentive effect exerted by positive media sentiment in the environmental (E) and social (S) dimensions, as well as excellent attention, is more robust. This study provides new insights for promoting green and low-carbon development and understanding the external governance role of media in corporate ESG development.

Green bonds, pivotal to green finance, draw growing attention from scholars and investors. Social media’s proliferation has amplified the influence of investor sentiment, necessitating robust analysis of its market impact. However, general sentiment lexicons often fail to capture domain-specific slang and nuanced expressions unique to China’s bond market, leading to inaccuracies in sentiment analysis. Thus, this study constructs a specialized sentiment lexicon for the green bond market, namely the COBC (Chinese online bond comments sentiment lexicon), to dissect bond market slang and investor remarks. Compared to three general lexicons (Textbook, SnowNLP, and VADER), it improves the average prediction accuracy by approximately 87.2% in sentiment analysis of Chinese online language within the green bond domain. Sentiment scores derived from COBC-based dictionary analysis are systematically integrated as predictive features into a two-stage hybrid predictive model is proposed integrating Support Vector Machine (SVM), Auto-Regressive Moving Average (ARMA), Bidirectional Long Short-Term Memory Networks (BiLSTM), and Attention Mechanisms to forecast China's green bond market, represented by the China Bond 45 Green Bond Index. First, ARMA-SVR is employed to extract residuals and statistical features from the green bond index. Then, the BiLSTM-Attention model is applied to assess the impact of investor sentiment on the index. Empirical results show that incorporating investor sentiment significantly enhances the predictive accuracy of the green bond index, achieving an average of 67.5% reduction in Mean Squared Error (MSE), and providing valuable insights for market participants and policymakers.

This study identifies an incentive-compatible mechanism to foster individual environmental engagement. Utilizing a dataset comprising 100,000 randomly selected users of Ant Forest—a prominent personal carbon accounting platform embedded within Alipay, China's leading BigTech super-app—we provide causal evidence that individuals strategically engage in eco-friendly behaviors to enhance their credit limits, particularly when approaching borrowing constraints. These behaviors not only illustrate the green nudging effect of BigTech but also generate value for the platform by leveraging individual green actions as soft information, thereby improving the efficiency of credit allocation. Using a structural model, we estimate an annual green value of 427.52 million US dollars generated by linking personal carbon accounting with BigTech credit. We also show that the incentive-based mechanism surpasses green mandates and subsidies in improving consumer welfare and overall societal welfare. Our findings highlight the role of an incentive-aligned approach, such as integrating personal carbon accounts into credit reporting frameworks, in addressing environmental challenges.

Financial technology, also known as Fintech, is transforming our daily life and revolutionizing the financial industry. Yet at present, consensus regarding the effect of Fintech on green bonds market is lacking. With novel data from China, this study documents robust evidence showing that Fintech development can significantly boost green bonds issuance. Further analysis suggests that this promotion effect occurs by empowering intermediary institutions and increasing social environmental awareness. Additionally, we investigate the heterogeneous effect and find that the positive relation is more pronounced for bonds without high ratings and in cities connected with High-Speed Railways network. The results call for the attention from policymakers and security managers to take further notice of Fintech utilization in green finance products.

This article examines the impact of the Green Financial Regulatory Policy on corporate strategic ESG behavior against the backdrop of the 2017 policy integration of “green finance” into the Macro-Prudential Assessment by the central bank. The research identifies that GFRP may shift corporate focus towards the disclosure of ESG performance while neglecting the actual practices of ESG engagement, potentially inducing firms to engage in ESG greenwashing. It is further posited that corporate green perception and executives’ environmental backgrounds serve as primary mechanisms in this dynamic. Additionally, the policy efficacy of GFRP on strategic ESG behavior exhibits heterogeneity

The use of green finance to slow down global warming in support of sustainable development remains widely discussed. This study examines whether investment structure moderates the impact of green finance on the environment in China, one of the top carbon-emitting nations and the second-largest economy in the world. We primarily used the moments-quantile regression approach with fixed-effect models on panel data from 1992Q1 to 2020Q4. First, the results confirmed that green finance and public and private investments worked synergistically to lower CO2 emissions, especially in Central and Western China. However, there was no proof that green finance and foreign direct investment were complementary in reducing CO2 emissions in China, unlike the Central region. Second, green finance marginally lowered CO2 emissions in all provinces, mainly in Eastern and Western China; this reduction was largely dependent on private investment in the Western region’s most polluting areas and foreign direct investment in Eastern and Western China’s least polluting provinces. Third, the beneficial effect of green finance occurred at varying optimal thresholds and investment-related conditions across Chinese regions at different quantiles. Lastly, we showed that in contrast to the variable impacts of urbanization, oil prices, and economic growth across Chinese regions at different quantiles, renewable energy, and trade openness reduced CO2 emissions. In conclusion, the study makes some policy recommendations for China’s sustainable economic development, an important model from which other countries can tailor their investment strategies and environmentally friendly policies.

Green finance has drawn increased worldwide attention from policymakers as a financial mechanism that could potentially encourage corporations to actively engage in sustainable activities. However, despite a growing body of studies investigating the economic outcomes of green financial policies, there is still a lack of research that systematically quantifies the social welfare implications of green finance. Hence, this study aims to fill this research gap by establishing the causal effect of green finance on corporate environmental responsibility. Exploiting the "bottom-up" enforcement of the green finance pilots in 2017 in China as a quasi-natural experiment and the difference-in-difference-in-difference identification strategy, we find that green finance significantly enhances corporate environmental responsibility performance in high-polluting industries relative to their counterparts, and this evidence continues to survive a battery of robustness checks. Moreover, we explore three underlying mechanisms that possibly explain this beneficial effect: risk-taking, external governance and financing channels. Furthermore, we uncover that corporate environmental responsibility serves as a plausible non-economic channel that combines green finance with economic benefits by stimulating green innovation, promoting total factor productivity and expanding market share. Overall, our study offers new insights on both the economic and non-economic consequences of green finance on business performance.

Fighting global warming has become a vital requirement for environmental sustainability. Green finance has gained popularity as a promising mechanism for transitioning to a lowcarbon economy. Thus, this paper investigates whether excess green financing increases renewable energy capacities and enhances environmental quality from 1992Q1 to 2020Q4 in China, one of the major CO2 emitters. We primarily used the method of moments-quantile regression with fixed-effect models. First, we found nonlinear U-shaped impacts of green finance on wind power capacities in all Chinese regions, thermal power capacities in the Western and Central areas, and hydropower capacities in Eastern China, respectively. Second, we confirmed an inverted U-shaped impact of green finance on CO2 emissions in the Eastern region but U-shaped effects in the Western and Central regions. The impacts of green finance were asymmetrical due to the heterogeneous distributions of renewable energy sources and environmental quality within and between regions. Green finance mostly improved environmental quality when certain conditions and thresholds were met. Third, green finance had substantial marginal effects on environmental quality in the least polluted provinces (Q.20) in Western China and the most polluted provinces (Q.80) in Eastern China. Finally, there were heterogeneous effects of oil prices, urbanization, foreign direct investments, and trade openness on renewable energy consumption and environmental quality across Chinese provinces. Accordingly, this study provides some policy recommendations for China’s sustainable development, a key example from which the international community can adjust its green policies.

In the process of green transformation of China's economy, it is of great practical significance to study the impact of green finance in supporting the development of the real economy, especially the impact of green credit on enterprise innovation, in order to promote the green transformation of enterprises, industrial structure upgrading and sustainable economic development. This paper takes green credit as a perspective and introduces it into the analytical framework of the impact of environmental regulation on corporate green innovation, through theoretical mechanism analysis and empirical testing, in order to reveal the impact and mechanism of green credit on corporate green innovation. It is found that green credit can effectively promote green innovation in heavy polluting enterprises, and it is mainly reflected in the increase of green utility model patent applications with a low degree of inventiveness. The promotion effect of green credit on green innovation is more obvious in regions with lower levels of economic development. Further mechanism analysis shows that green credit policy promotes green innovation of heavy polluting enterprises mainly through the incentive effect brought by changing financing environment and the pressure effect brought by increasing market competition. The findings of this paper can provide references for policy-making departments, banks and enterprises.

As the problem of global climate change becomes more severe, countries have proposed the goals of carbon capping and carbon neutrality. Green finance is an essential capacity support for achieving carbon peaking and carbon neutrality, and it can guide and stimulate social capital to invest in low-carbon industries and initiatives via marketbased mechanisms. Based on the panel data of Chinese prefecture-level cities from 2006 to 2020, this paper empirically examines the impact of green finance on carbon emission efficiency using a two-way fixed-effects model, conducts a regional heterogeneity analysis, and examines the threshold effect of economic development level and the mediating role of regional innovation. The results indicate that, first, green finance contributes significantly to the improvement of carbon emission efficiency, and second, the level of regional economic development has a double threshold effect on the contribution of green finance to the improvement of carbon emission efficiency. Third, regional innovation is an important green finance channel for influencing carbon emission efficacy. The sensitivity of carbon emission efficiency to the green finance index demonstrates an inverted U-shaped trend. Fifth, the importance of green finance sub-dimensions in relation to carbon emission efficacy is as follows: green support, green credit, green insurance, green investment, green equity, green bond, and green fund. These findings provide theoretical support for green finance's role in promoting co-carbon efficiency and are valuable for policy formulation.