关键词: 绿色信贷, 政府规制, 绿色技术创新, 企业寻租, 演化博弈

Abstract: Green finance represents a novel growth point and serves as a fresh impetus for the advancement of the green economy. It plays an important role in enhancing the ecological environment and promoting high-quality economic development. Currently, the focal point of green finance development in China centers on green credit. Both theoretical and empirical evidence indicates that green credit can effectively facilitate the transition to a green economy and achieve green growth by promoting cleaner production methods, enhancing the efficiency of green technology innovation, and optimizing energy consumption patterns. Nevertheless, as the green credit policy gains traction, challenges such as difficulties in verifying the authenticity of information pertaining to enterprise green innovation, concealment of environmental risks, and the absence of external oversight and guidance mechanisms are becoming increasingly salient. These issues significantly impact the willingness of banking and financial institutions to engage in green credit, thereby impeding the progress of the green financial system. To address these concerns, this paper formulates an evolutionary game model aimed at elucidating the dynamic interplay among enterprises, banking financial institutions, and the government within the context of green credit policy implementation. It further scrutinizes the dynamic influences of the initial participation intentions of decision-makers, government regulations, and the rent-seeking costs incurred by enterprises on the evolutionary system. This examination seeks to provide a certain degree of theoretical foundation and strategic recommendations for advancing the development of green credit.
From the perspective of bounded rationality, this paper analyzes the strategy selections of local governments, heavily polluting enterprises, and banking financial institutions. It proposes relevant basic assumptions grounded in evolutionary game theory. Subsequently, using Wolfram Mathematica 13.0, the revenue payoff matrix and evolutionary stable points are derived. The evolutionary stable strategy of the three-party game system is further delved into across four scenarios. Ultimately, based on the actual situation and initial parameter constraints, and in alignment with model parameter settings related to government regulation, banking financial institution investment, and enterprise green technology innovation, Matlab 2018a is utilized to simulate the dynamic evolution process of strategy choices among heavily polluting enterprises, banking financial institutions, and local governments under varying initial conditions. The influence of each subject’s initial willingness, local government incentives, punishments, subsidies, heavily polluting enterprises’ innovation feedback coefficients, and rent-seeking costs on the three-party game system is analyzed based on the simulation results.
The results show that: A)An enhancement in the local government’s initial regulatory willingness can motivate heavily polluting enterprises to embrace green technology innovation and encourage banking financial institutions to implement green credit practices. Notably, the rate of strategic evolution among heavily polluting enterprises is swifter than that of banking financial institutions. As the initial willingness of both heavily polluting enterprises and banking financial institutions rises, the evolutionary pace of local government strategies decelerates. B)Government incentives and penalties serve as substantial drivers for heavy pollution enterprises to adopt green technology innovation. However, subsidies play a comparatively minor role in nudging banking financial institutions towards green credit strategies. C)The innovation feedback coefficient of heavy pollution enterprises does not alter the regulatory strategies of local governments. Conversely, an escalation in rent-seeking costs favors enterprises in choosing green technology innovation strategies.

Key words: green credit, government regulation, green technology innovation, enterprise rent-seeking, evolutionary game