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This study investigates the impact of UAE’s Green Credit Policy on the non-performing loan. One of the main pillars in the UAE green agenda 2015–2030 is the green finance that has been growing in high acceleration in the Gulf Cooperation Council (GCC) countries and the whole world. Consequently, the main objective of this study is to investigate in the financial risks that associated with green lending and whether an increasing in green lending will decrease the non-performing loans ratio (NPLR) of UAE banks, based on the period 2015–2020 dataset of 23 UAE’s banks. To achieve this objective, we have used a regression technique that includes a two-stage least square regression analysis and random-effect regression analysis to test if the increase in green credit ratio can reduce the NPL ratio in a sample of UAE’s banks. The current study can be considered the first empirical attempt that conducted on the banking sector in UAE, to discover the variables that might have a direct impact on the NPL ratio. The results reveal that the ratio of green loans has a negative impact on the NPL ratio, as much as the return of equity, while the quality of credit, inefficiency, and the bank size have a positive impact on NPL ratio. But as was not as expected, we found that the impact of solvency ratio has a negative significant on the NPL ratio. Finally, the current study introduces a new value to the current literature about the impact of green lending policies and provides a new perspective which supports the financial sustainability in UAE.

Green finance is one of the most important ways to help companies achieve green transformation and development. We construct a quasi-natural experiment with the “ Green Credit Guidelines ” and establish a difference-in-differences model to empirically test the implementation effect of the green credit policy in China. The results show that after the implementation of China’s green credit policy, the debt financing scale of listed companies in heavily polluting industries has decreased significantly, the debt financing cost has increased significantly, and the debt financing maturity has been shortened significantly, indicating that the green credit policy has inhibited the debt financing of heavily polluting enterprises. We further find that this inhibition has also been affected by the nature of controlling shareholders, environmental information disclosure levels, regional environmental regulations and regional financial development levels. China’s green credit policy has played a role in guiding listed companies to go green through the redistribution of debt financing.

Treating the green credit policy issued in 2012 as a quasi-natural experiment, this study has investigated the impact of green credit policy on total factor productivity of the manufacturing firms in China by using the panel data of the A-share firms listed on the Shanghai and Shenzhen stock exchanges during 2008 and 2020, with the consideration of the mediating role of debt financing and the moderating role of environmental regulation simultaneously. The results show that green credit policy has a negative effect on total factor productivity of the manufacturing firms in China. Empirical evidence also shows that debt financing could oppositely mediate the nexus between green credit policy and total factor productivity of the manufacturing firms in China by both inhibiting long-term loans and promoting short-term loans. In addition, the moderating role of environmental regulation is partially and conditionally established. Furthermore, the regional heterogeneity and the property rights heterogeneity are proved. Finally, conclusions and policy implications are provided to improve the quality of green credit policy in the future.

Taking the green credit policy in 2012 as a quasi-natural experiment, this paper has investigated the impact of green credit policy on Chinese firms’ green strategy choices by using the panel data of A-share listed firms from 2008 to 2019. The results reveal that green credit improves firms’ green innovation overall. In terms of time, the green-washing behavior of listed firms will increase significantly in the early stage of the implementation of green credit policy, but as time goes by, such green behavior of firms will be detected, which in turn will motivate firms to improve green innovation. Furthermore, the green credit policy has a more significant effect on green innovation of firms in localities under high environmental regulation, economically developed regions, and without other alternative financing channels. Firms located in regions with economically underdeveloped and low environmental regulation are more inclined to adopt the behavior of green-washing environmental information. Besides, after the implementation of the green credit policy, green innovation can improve corporate financial, environmental, and social performance, while green-washing behavior will damage corporate financial, environmental, and social performance. Our findings contribute to the literature on green credit policy, corporate green innovation, and environmental information disclosure, and also provide policy implications for improving the quality of green credit policy in the future.

This study explores China’s green credit policy from a credit risk perspective. Green finance has been growing rapidly in China since the government issued its Green Credit Policy. The objective of this study is to explore whether green loans are less risky than non-green loans. Based on a five-year dataset of 24 Chinese banks, we used panel regression techniques, including two-stage least square regression analysis and random-effect panel regression to examine whether a higher green credit ratio reduces a bank’s non-performing loan ratio (NPL ratio). The results suggest that allocating more green loans to the total loan portfolio does reduce a bank’s NPL ratio. We conclude that institutional pressure by the Chinese Green Credit Policy has a positive effect on both the environmental and the financial performance of banks. The study contributes to the literature on the correlation between green lending and credit risks, as well as to the literature on the impact of institutional pressure on environmental and financial risks.

Promoting new energy vehicles (NEVs) is considered to be one of the most effective ways to solve the increasingly serious problems of energy security and environmental pollution. Under the background of a gradual decline in the use of subsidy policy, the dual-credit policy (DCP), as a market-incentive environmental regulation, has been introduced to the process of policy development. This is of great significance in promoting NEVs and upgrading of the automobile industry. Based on data for 56 listed companies related to NEVs from 2012 to 2019, this study investigated the impact of the DCP on total factor productivity (TFP) under the framework of the propensity score matching difference-in-differences (PSM-DID) and further analyzed the mechanisms by how the DCP impacted on TFP. In addition, the heterogenous impacts of different firms were investigated. The results reveal three key findings. (1) After using instrumental variable to overcome endogenous problems and carrying out a series of robustness tests, the DCP can significantly improve firms’ TFP, and this effect is increasing annually. (2) The results of the mechanism analysis show that technological innovation, reputation enhancements, and the reduction of manager motivation have promotional effects on firms’ TFP. Besides, environmental tax can reduce the contribution of research and development (R&D) innovation to TFP. (3) In terms of regional and market structural levels, the promotional effect of the DCP on firms’ TFP in the eastern region is greater than that in the midwestern region. Furthermore, it has no significant effect on competitive firms, but plays a significant role in the improvement of oligopolistic firms’ TFP. This study supported the Porter Hypothesis that flexible market-incentive environmental regulation is likely to trigger positive productivity effects, and provided an empirical basis and latest information for promoting the accuracy and effectiveness of the DCP implementation.

Supply chain management aims to integrate environmental thinking with efficient energy consumption into supply chain management. It includes a flexible manufacturing process, more product delivery to customers, optimum energy consumption, and reduced waste. The manufacturing process can be made more flexible through volume agility. In this scenario, production cannot be constant, and with the concept of volume agility, production is taken as a decision variable under the effect of optimum energy consumption. Considering a two-echelon supply chain, we consider a producer and supplier with two-level-trade-credit policies (TLTCP) with the optimum consumption. To reduce the integrated total inventory cost, we believe that demand is a function of the credit period and selling price. The cost function is analyzed, either with the credit period dependent demand rate or with the selling price dependent demand rate through the numerical examples under energy costs. Energy and carbon emission costs are introduced in setup/ordering cost, holding cost, and item cost for producer and supplier. The effect of inflation on the total cost cannot be ignored; this model is being developed for deteriorating items with the simultaneous impact of volume agility, energy, carbon emission cost, and two-level-trade-credit policies with inflation. This supply chain model was solved analytically and obtained the optimum decision variables in a quasi-closed form solution. An illustrative theorem is being utilized to analyze the optimum result for all the decision parameters. The convexity of the objective function is being obtained analytically as well as graphically. Finally, numerical examples and sensitivity analysis are employed to illustrate the present study and with managerial insights.

The green credit policy (GCP) is an institutional framework aimed at guiding enterprises towards green transformation and promoting high-quality development, which serves as a crucial tool for supporting the establishment of a green technology innovation system. In this study, utilizing the green credit guidelines as a quasi-natural experiment and constructed a continuous difference-in-difference (DID) model, examines the impact of GCP impact on enterprise green innovation and its internal mechanisms by analyzing data from Chinese A-share listed companies between 2006 and 2021. Our findings indicate that the GCP had a significant impact on enterprise green innovation, inhibiting companies from in-dependently developing green innovation while promoting joint green innovation with other institutions; These results were robust and consistent, even after conducting several sensitiv-ity analyses; This mechanism indicate that the commercial credit plays an important regulatory role in the process of GCP affecting green innovation of enterprises and the financing constraints act as an intermediary factor in the process of GCP affecting green innovation. Based on our research, we offer policy recommendations aimed at improving the GCP and fostering a market-oriented green technology innovation system. First published online 14 March 2024

Green credit policy is an important practice to guide green development through the rational allocation of credit funds. Using the promulgation of the “Green Credit Guidelines” policy in China as a quasi-natural experiment, this paper examines the impact of green credit policy on heavily polluting enterprises’ substantive and strategic green innovations within a difference-in-differences framework. We find that green credit policy improves the overall and strategic green innovations but has no significant effect on substantive green innovation of heavily polluting enterprises. Moreover, this effect is more prominent for state-owned enterprises and enterprises in regions with lower levels of financial development. Further analysis demonstrates that the green innovation induced by green credit policy increases heavily polluting enterprises’ loan availability but does not improve heavily polluting enterprises’ value. This paper sheds new light on the relationship between green credit policy and corporate green innovation in China as a transition economy.

Green credit is regarded as an important means to promote sustainable growth. Based on the provincial panel dataset of China from 2007 to 2017, this paper investigates the dual impacts of green credit on the economy and environment, and it establishes mediating effect models to analyze the Porter hypothesis. The results show that the green credit policy significantly improves economic performance and reduces pollutant emissions. The above results are robust to employing methods with alternative variables and instrumental variables. Second, the green credit policy contributes to innovation; that is, the green credit increases the innovation scale and improves innovation efficiency. The results of mediating effect models suggest that the Porter effect of green credit can be achieved by improving innovation efficiency. The findings of the current study indicate that the green credit policy helps achieve the win–win situation for economic goals and environmental targets.