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This study investigates the impact of geopolitical risk on firm-level environmental, social, and governance (ESG) performance. Using a news-based indicator of geopolitical risk across 41 countries and a comprehensive dataset spanning from 2002 to 2021 with 65,354 firm-year observations, we uncover that geopolitical risk is negatively associated with ESG performance. Our findings remain robust even when considering alternative measures of geopolitical risk, ESG components, and sub-samples. Moreover, we address potential endogeneity concerns through two-stage least squares, propensity score matching and entropy balancing approaches. Interestingly, we find that the effect of geopolitical risk is positive for countries with lower geopolitical risk and high peace, indicating that relatively stable environments can incentivize firms to enhance their sustainability practices. We also examine the potential channel effects of cash holding, corporate investment, and cost of capital, and found significant effects. Overall, this paper underscores the significance of geopolitical risk as a macro-level shock that significantly influences ESG performance.

In the context of China\'s efforts to combat climate change and promote sustainable development, the solid waste treatment industry\'s environmental, social, and corporate governance (ESG) performance is receiving significant attention. To comprehensively assess the ESG performance of the solid waste treatment industry and identify company types, this study constructs a targeted ESG evaluation index system based on existing literature, SASB industry standards, and company reports and utilizes a random forest approach combined with K-means clustering to determine indicator weights. Based on this index system, the paper evaluates the ESG performance of 71 solid waste disposal companies (SWDCs) from 2013 to 2021 and identifies their ESG types from static and dynamic perspectives. In the static view, company types are determined based on annual ESG performance, while the dynamic view considers time-series changes to observe the evolution of company ESG types. The results show that the overall ESG performance of SWDCs falls within the 2-8-point range, indicating a noticeable high-low imbalance. Key initiatives to improve ESG performance in this industry include enhancing waste management measures, developing emergency plans, and reinforcing ESG disclosure. From a static perspective, this paper can identify companies into three categories: delayed development, single-wheel-driven, and coordinated development. Finally, from a dynamic perspective considering the time factor, companies are further subdivided into five types: continual leading, growth catch-up, slow progress, fluctuating change, and retrogressive inertia. This study not only provides targeted recommendations for different types of ESG companies but also helps various sectors of society better understand the ESG conditions of this high environmental risk industry, thereby enhancing the regulation and support for its sustainable development.

This study investigates the practical effects of adopting the environmental protection tax (EPT) policy on corporate performance in China. The analysis uses the Difference in Differences (DID) approach based on a quasi-natural experiment scenario. The findings indicate there is a negative impact of implementing the EPT policy on the financial performance of corporations, and the conclusion remains unchanged despite exhaustive robustness testing. The negative impact can be partly attributed to corporate technology innovation inputs. Meanwhile, enterprise property rights, pollution, and technical levels also substantially influence the implementation effect of the legislation. However, implementing this policy has improved corporations\' environmental performance and established its efficacy in enhancing their sustainable capabilities. This study comprehensively explores the impact of environmental control legislation on business performance, spanning financial, environmental, and social dimensions. Corresponding findings offer valuable insights into how firms react to environmental legislation and adjust to the external environment. Meanwhile, it also provides an objective reference for the comprehensive green transformation.

As sustainability emerges as a crucial factor in the development of modern enterprises, integrating environmental, social, and governance (ESG) information into financial assessments has become essential. ESG indicators serve as important metrics in evaluating a company\'s sustainable practices and governance effectiveness, influencing investor trust and future growth potential, ultimately affecting stock prices. This study proposes an innovative approach that combines ESG sentiment index extracted from news with technical indicators to predict the S&P 500 index. By utilizing a deep learning model and exploring optimal window sizes, the study explores the best model through mean absolute percentage error (MAPE) as an evaluation metric. Additionally, an ablation test clarifies the influence of ESG and its causality with the S&P 500 index. The experimental results demonstrate improved predictive accuracy when considering ESG sentiment compared to relying solely on technical indicators or historical data. This comprehensive methodology enhances the advantage of stock price prediction by integrating technical indicators, which consider short-term fluctuations, with ESG information, providing long-term effects. Furthermore, it offers valuable insights for investors and financial market experts, validating the necessity to consider ESG for financial assets and introducing a new perspective to develop investment strategies and decision-making processes.

The deep integration of digital technology and the real economy not only affects the production and operation mode of enterprises, but also becomes the promoter of service-oriented transformation and the driving force of sustainable development. Based on the text analysis method, this paper uses the data of Chinese listed manufacturing enterprises from 2011 to 2020 to study the impact of digital technology application on the service-oriented transformation and sustainable development of enterprises. It is found that digital technology application significantly improves the environmental performance and economic performance of enterprises by driving their service-oriented transformation and technological innovation, and then enhances their sustainable development. The improvement effect of digital technology application on the sustainable development of resource-based enterprises and capital-intensive enterprises is more significant. The conclusion in this paper provides micro-evidence for understanding the role of digital technology in addressing environmental issues and sustainable development.

As climate change and geopolitical conflicts intensify, understanding how geopolitical risks affect companies prioritizing Environmental, Social, and Governance (ESG) practices is crucial. This study investigates the dynamic relationship between global geopolitical risks and the performance of Environmental, Social, and Governance (ESG) and non-ESG companies, particularly their influence on green markets. Utilizing a robust methodological framework, including the dynamic time-varying parameters vector autoregression (TVP-VAR) model, and causal impact modeling, we analyze daily financial data from 2021 to 2024. The results reveal a substantial negative impact of geopolitical risks on non-ESG companies, contrasting with the resilience of ESG-committed counterparts. This suggests that ESG-committed companies demonstrate better resilience against geopolitical risks, emphasizing the protective role of ESG practices amid uncertainties. Additionally, the inclusion of ESG companies in green markets diminishes the severity of the negative impact of geopolitical risks, underlining the transformative role of ESG commitment in shaping investor behavior towards sustainable investments. Our findings offer insights for policymakers and investors navigating geopolitical risks and ESG performance, with a focus on environmental management, and provide guidance for effective risk mitigation and investment policies to enhance environmental sustainability.

The enhancement of corporate environmental, social, and governance (ESG) performance represents a crucial aspect of the broader green transformation agenda. Using a DID design, this paper examines the impact of China\'s low-carbon city pilot (LCCP) policy on the corporate ESG performance. Our findings demonstrate that the construction of LCCP exerts a positive influence on corporate ESG performance in pilot regions, particularly in industries and areas with high carbon emission intensity. Channel analyses reveal that LCCP policy heightens the environmental concerns of local governments and the public. Furthermore, LCCP policy has a crowding out effect with firms located in the surrounding cities. This paper responds to the calls for the determinants of ESG and enriches the understanding of policy impacts on corporate sustainability practices.

Sustainable development is a practical path to optimize industrial structures and enhance investment efficiency. Investigating risk contagion within ESG industries is a crucial step towards reducing systemic risks and fostering the green evolution of the economy. This research constructs ESG industry indices, taking into account the possibility of extreme tail risks, and employs VaR and CoVaR as measures of tail risk. The TENET network approach is integrated to to capture the structural evolution and direction of information flow among ESG industries, employing information entropy to quantify the topological characteristics of the network model, exploring the risk transmission paths and evolution patterns of ESG industries in an extreme tail risk event. Finally, Mantel tests are conducted to examine the existence of significant risk spillover effects between ESG and traditional industries. The research finds strong correlations among ESG industry indices during stock market crash, Sino-US trade frictions, and the COVID-19 pandemic, with industries such as the COAL, CMP, COM, RT, and RE playing key roles in risk transmission within the network, transmitting risks to other industries. Affected by systemic risk, the information entropy of the TENET network significantly decreases, reducing market information uncertainty and leading market participants to adopt more uniform investment strategies, thus diminishing the diversity of market behaviors. ESG industries show resilience in the face of extreme risks, demonstrating a lack of significant risk contagion with traditional industries.

OBJECTIVE: The mainstay of treatment for metabolic dysfunction-associated steatotic liver disease (MASLD) is weight loss. Endoscopic gastric remodeling (EGR) and glucagon-like peptide-1 receptor agonist (GLP-1RA) are effective weight loss therapies. This study aims to assess the effect of combining EGR with GLP-1RA on liver-related outcomes and weight profile.
METHODS: This is a retrospective study of a prospectively collected registry of patients with MASLD and compensated advanced chronic liver disease (cACLD) who underwent EGR. Patients were categorized as (1) monotherapy: EGR alone and (2) combination therapy: GLP-1RA prescribed within 6 months prior to or after EGR. Outcomes included changes in noninvasive tests of hepatic fibrosis, weight profile, and insulin resistance status at 12 months.
RESULTS: Thirty patients (body mass index 40.7 ± 9.3 kg/m2) were included. Of these, 12 patients (40%) underwent EGR monotherapy, and 18 patients (60%) underwent EGR + GLP-1RA combination therapy. Combination therapy group experienced greater improvements in fibrosis compared to monotherapy group (alanine aminotransferase: reduction by 55 ± 23% vs 29 ± 22% (p = 0.008), NAFLD fibrosis score: reduction by 181 ± 182% vs 30 ± 83% (p = 0.04), liver stiffness measurement on transient elastography: reduction by 54 ± 12% vs 14 ± 45% (p = 0.05)). There were greater reductions in hemoglobin A1c and homeostatic model assessment for insulin resistance in combination therapy compared to monotherapy (p < 0.05). At 12 months, the combination therapy group experienced 18.2 ± 6.6% TWL, while monotherapy group experienced 9.6 ± 3.3% TWL (p = 0.004).
CONCLUSIONS: In patients with MASLD and cACLD, combination of EGR with GLP-1RA is associated with greater improvements in hepatic fibrosis, weight profile, and insulin resistance compared to EGR alone.