Implementation of a multi-agent environmental regulation strategy under Chinese fiscal decentralization: An evolutionary game theoretical approach

• Main Authors: JIANG, Ke, YOU, Daming, MERRILL, Ryan Knowles, LI, Zhendong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Fiscal decentralization; Environmental regulation strategy; Evolutionary game theory; Evolutionary stable strategy; Multi-agent; Numerical simulation; Asian Studies; Environmental Policy; Environmental Sciences; Strategic Management Policy
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/6582; https://ink.library.smu.edu.sg/context/lkcsb_research/article/7581/viewcontent/Implementation_multi_agent_environ_av.pdf
• Institution: Singapore Management University

Evolutionary game theory (EGT) provides a powerful tool with which to unpack the interactive strategies of polluting enterprises (PEs), local government regulators (LG), and central government planners (CG) in China. Here, the prevailing institutional system of fiscal decentralization sees regulatory mandates set by the CG and enforced at the LG level. This delegation shapes managers' incentives when deciding the degree to which firms will incur costs to reduce pollution and comply with state directives. Manager's choice sets draw shape from decisions at the LG level, where regulators balance the pursuit of environmental quality with the economic payoffs of tacit collusion with industry. LG and PEs incentives reciprocally shape and draw shape from outcomes at the CG level, where policymakers decide the degree to which they will support and supervise the behavior of LGs. By exploring the evolution of different participants' behavior and their evolutionary stable strategy (ESS) in line with the duplication of dynamic equations, EGT enables a robust, quantitative analysis of this iterative, interactive, three-player game, A numerical example serves to verify the theoretical results and support four key insights. First, the selection of environmental strategies manifest in a dynamic process of constant adjustment and optimization. Second, LGs outperform by integrating decisions from both CG and PEs in weighing alternative environmental strategies. Third, reducing regulatory costs at the CG level cascades to strengthen penalties for local violations and improve mitigation incentives in ways that aid an evolutionary game to converge on an ideal decision state. Fourth, a stable equilibrium cannot persist to allow LGs to sustain behaviors towards a "race to the bottom", even in the total absence of central regulation or high levels of dominance of polluting firms of LG regulators. EGT thus not only outcomes shed light on the full variation set of game outcomes, it also reveals the consequences of variable levels of collusion between LGs and PEs and options for the redesign of incentive mechanisms to reform the regulatory regime and improve market outcomes in China. (C) 2018 Elsevier Ltd. All rights reserved.