Background: Green economic development refers to reducing pollution emissions and increasing production efficiency while promoting economic growth. Although the renewable energy consumption is “green,” it may not promote green economic development due to the constraints of existing technical conditions. Therefore, the technological advancement approach that can help coordinate the relationship between renewable energy consumption and green economic development should be identified. That is, determining whether to develop new technologies or improve existing technologies should be paid more attention in the context of continuous increase in renewable energy consumption. Results: (1) The inverted N-shaped relationship between renewable energy consumption and green economic development under the existing technical conditions. The degree of renewable energy consumption can merely promote green economic development in the interval of 0.67–10.87. That is, the renewable energy consumption (% of total energy consumption) is less than 0.67% or greater than 10.87%, which is not conducive to green economic development. (2) Developing new technologies can stimulate the positive effect of renewable energy consumption on green economic development. However, the improvement of existing technologies fails to exhibit an effective impact on the relationship between renewable energy consumption and green economic development. (3) Coordinating the relationship between renewable energy consumption and green economic development can also be achieved by reducing the dependence of Gross Domestic Product (GDP) on fossil fuels. (4) The stage of economic development might impact the effect of renewable energy on green economic development. Conclusions: It is particularly important to improve technological innovation capabilities, especially in countries with a high proportion of renewable energy consumption. In addition, the government should guide the funds and resources to the renewable energy industry through the credit rationing system to promote the transition of the industrial structure to an environmentally friendly direction. For countries with relatively low levels of economic development, this does not mean that these countries should reduce their demand for renewable energy. Instead, these countries need to take more proactive measures, such as increasing technological innovation capabilities and optimizing industrial structure to coordinate the relationship between renewable energy consumption and green economic development.

On the basis of the original camel rating system, this study added the green indicator and formed the G-CAMELS evaluation system (An improved rating system based on the CAMELS rating system to evaluate the business operation of financial institutions more comprehensively.) to comprehensively evaluate the competitiveness of commercial banks. It followed China’s current requirements for the sustainable development of commercial banks. In this paper, factor analysis, entropy methods, and dynamic evaluation models are used to obtain the ranking of competitiveness. In addition, according to the same steps as above, the comprehensive ranking based on the CAMELS evaluation system (A comprehensive rating system which is standardized, institutionalized and indexed for business operations of commercial banks and other financial institutions.) was obtained. The two ranking systems were compared. It is found that with the entropy weight method, in the G-CAMELS system, the weight of the green index is quite large, so it magnifies the impact of the financial industry on the environment. Compared with the original CAMELS system, the newly formed system will increase the ranking of state-owned banks and there is no significant change in the ranking of joint-stock banks. In order to improve the competitiveness of banks, state-owned banks should innovate their banking business and continue to implement the green credit policy; joint-stock banks should continue to seize the opportunity of green credit and expand profitability while paying attention to safety. In addition, the government could consider relaxing green credit standards for city commercial banks to ease pressure on banks.

This study uses data from seven countries with high energy consumption levels in 1997–2016 (i.e., the US, China, Japan, Canada, South Korea, Germany, and France) to establish a panel threshold model and analyze the multiple threshold effects of new energy consumption transformation on economic growth. Research results show the non-linear impact of new energy consumption transformation on economic growth. On the one hand, the transformation of new energy consumption will occasionally bring economic costs, thereby resulting in a negative impact on economic growth. On the other hand, economic cost occasionally disappears, thereby resulting in the positive impact of the transformation of new energy consumption on economic growth. This study proposes that economic cost is affected by the levels of research and development (R&D), economic development, and traditional energy dependence, therefore, we use these three variables as threshold variables. Threshold variable is essential in a panel threshold model. The behavioral varies of model can be predicted when threshold variable is at different ranges of levels. In other words, the behavior of panel threshold model may change as the level of threshold variable changes. In particular, when the R&D level is used as a threshold variable, the impact of new energy consumption transformation on economic growth will change from negative to positive as the level of R&D increases. We present a similar conclusion when the level of economic development is used as a threshold variable. However, when the level of traditional energy dependence is used as the threshold variable, the impact of new energy consumption transformation on economic growth will change from positive to negative as the level of traditional energy dependence increases.

Commercial banks follow sustainable development strategies to provide green credit for companies. As the main target for banks to issue green credit, environmental protection companies carry out research and development (R&D) activities for the purposes of protecting the environment and sustainable development. Therefore, the R&D level of environmental protection companies is a measure of whether the green credit policy meets its purpose. Therefore, it is particularly important to study green credit from a company perspective. This paper used panel data from 24 environmental protection companies listed on the Shanghai and Shenzhen Stock Exchange from 2012 to 2017 and adopted a threshold model to examine the relationship between green credit and company R&D level. The results indicate that there is a positive but nonlinear relationship between green credit and company R&D levels. The empirical analysis through the threshold model shows that a threshold effect remains on the relationship and this threshold effect is caused by the levels of firm size, bank lending, and government subsidies.

For reliving the pressure of air pollution and corresponding the sustainability development policy in China, the companies are urging the creation of a highly productive low-carbon supply chain. This work uses price regulation, the cap-and-trade model, and a green financial policy background to establish a strategy for the coal–electric power supply chain with two-level carbon reduction and operation with financial constraints. A Stackelberg model was built to help investigate the rate of thermal order realization, the carbon reduction strategy in the coal enterprise, and the amount of thermal energy ordered in the electric enterprise. Results show that under a green financial background, a high bank loan discount rate for investing in carbon reduction technology equates to large carbon reduction in coal enterprises, large quantities of thermal energy ordered in electric enterprises, and high profit for coal and electric enterprises. However, the realization rate of thermal power ordered decreased when the price regulation become strict, thereby reducing the profit and carbon emission in electric enterprise. Therefore, the thermal price regulation level increased, the profit on both company and the production did not respond with sensitivity, and the government could encourage a low carbon model by controlling the bank loan rate.