Three-Party Stochastic Evolutionary Game Analysis of Reward and Punishment Mechanism for Green Credit

• Published in: Discrete dynamics in nature and society Vol. 2021; pp. 1 - 12
• Main Authors: Zhu, Qingfeng, Zheng, Kaimin, Wei, Yilin
• Format: Journal Article
• Language: English
• Published: New York Hindawi 01.01.2021; John Wiley & Sons, Inc; Hindawi Limited
• Subjects: Analysis; Bank loans; Banks; Banks (Finance); Behavior; China; Commercial banks; Credit policy; Differential equations; Economic incentives; Financial institutions; Game theory; Hypotheses; Incentives; Interest income; Interest rates; Li Keqiang; Local government; Ordinary interest; Regulatory agencies; Simulation; Stability; Strategy; Subsidies; Supervision; Sustainable development; China
• ISSN: 1026-0226; 1607-887X
• DOI: 10.1155/2021/5596015

To get rid of the development dilemma of green credit, we constructed a stochastic evolutionary game model of local government, commercial banks, and loan enterprises. We gave sufficient conditions for the stability of strategy based on the stability discriminant theorem of Ito^'s stochastic differential equation (SDE). Then, we discussed the impacts of incentive and penalty parameters on green credit. Through the above analysis, we got the following conclusions: (1) rewards and punishments always benefit green production and green credit, but increasing incentives is not conducive to the governments’ performance of regulatory duties; (2) punishments can better improve the convergence rate of players’ strategy than rewards; and (3) both rewards and punishments can exert an obvious effect in improving the changing degree of players’ strategy. Finally, we put forward some suggestions to optimize the green credit mechanism.