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

Author

Listed:
  • Qingfeng Zhu
  • Kaimin Zheng
  • Yilin Wei
  • Ruguo Fan

Abstract

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.

Suggested Citation

  • Qingfeng Zhu & Kaimin Zheng & Yilin Wei & Ruguo Fan, 2021. "Three-Party Stochastic Evolutionary Game Analysis of Reward and Punishment Mechanism for Green Credit," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-12, June.
    • Handle: RePEc:hin:jnddns:5596015
    DOI: 10.1155/2021/5596015
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