An Evolutionary Game Analysis of Environmental Governance Strategies of Central and Local Governments under High-Pressure Environmental Inspections
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Abstract
High-pressure environmental inspections have reshaped the interaction between central and local governments and created new challenges for understanding the dynamic formation of environmental governance behavior. To address this issue, this study develops an evolutionary game model under bounded rationality to examine the strategic interaction between central supervision and local governance decisions. A payoff matrix incorporating governance costs, supervision costs, accountability penalties, and environmental performance benefits is constructed to capture the incentive structure of both actors. Replicator dynamics and Jacobian stability analysis are employed to identify equilibrium states and evaluate their stability conditions. Furthermore, parameter sensitivity analysis and scenario simulations are conducted to explore how institutional variables influence strategic evolution. The results indicate that stronger supervisory pressure promotes proactive environmental governance and accelerates convergence toward a collaborative equilibrium. When supervision intensity reaches 0.6, the probability of local governments adopting proactive governance rises to 0.87, the real part of the equilibrium eigenvalue remains at - 0.23, and the system converges within 16 periods. In addition, accountability penalties strengthen the stability of cooperative behavior, whereas higher governance costs weaken governance incentives and slow convergence. The findings demonstrate that high-pressure environmental inspections can effectively reshape the payoff structure of environmental governance and foster a stable collaborative governance pattern between central and local governments. This study provides a dynamic analytical framework for understanding governmental behavior and offers policy insights for optimizing environmental governance mechanisms.
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