Green credit is one of the most important financial instruments to promote sustainable development. Taking the provincial panel dataset of China as the research sample, this paper investigates the spatial impacts of green credit on the green economy. The super slack-based measure (Sup-SBM) model with undesirable outputs is employed to calculate the level of green economy within China. On this basis, we establish spatial Durbin models to study the impact of green credit on green economy and its transmission mechanisms. The results show that green credit exhibits a local-neighborhood effect on green economy; that is, the green credit can not only improve the local green economy but also generate spatial spillover effect to promote the development of green economy in surrounding areas. The above conclusion still holds after the robustness test by replacing spatial weight matrices and alternative measurement for the explained variable. Furthermore, enhancing innovation efficiency and optimizing energy structure are important ways for green credit to promote green economy. The findings of this study not only provide a new perspective for understanding the economic consequences of green credit policy but also provide empirical evidence for the important role of green finance in achieving the win-win goals of economic growth and environmental protection. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-021-15419-8.
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.
In 2005 China announced that together with further economic development, resource efficiency and protection of the natural environment are becoming policy objectives. This is referred to as a dual-goal society and the study examines China's progress in achieving these objectives. It puts forward a model to assess China's performance from the point of view of resource efficiency and environmental friendliness. This model is then applied to analyse data from 30 provinces over the 2003-2009 period. The analysis shows that China's fast developing dual-goal society has created a serious regional imbalance. These disparities need to be adjusted for the dual goal to be achieved at a country level. Further challenges associated with the factors influencing the development of a dual-goal society and how they impact on China's national policies and strategies are also discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.