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Exploring the dilemma of overcapacity governance in China's coal industry: A tripartite evolutionary game model

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  • Wang, Yadong
  • Wang, Delu
  • Shi, Xunpeng

Abstract

Coal overcapacity reduction is an essential part of China's energy transition. An effective governance model is a key to realizing the smooth exit of excess coal capacity. We construct a tripartite evolutionary game model involving the central government (CG), local governments (LGs) and coal enterprises (CEs), and then use it to examine the dilemma of overcapacity governance and alternative policies. Our results demonstrate that: First, the evolutionary convergence of strategy among the tripartite game agents exhibits a reliable degree of interdependence. The market-oriented central regulation mechanism of the CG may incentivize LGs to take a strict implementation. Also, when the LGs strictly perform the de-capacity policy, CEs are more active in responding to the de-capacity task. Second, the stable and ideal evolutionary state of (0,1,1) can be achieved when the corresponding conditions are met, which indicates that the coal de-capacity should coordinate the interests of multiple stakeholders. Third, inspired by the parameters sensitivity simulation, reducing the de-capacity costs, a balanced performance appraisal system, an appropriate supervision and punishment mechanism for de-capacity implementation, and increasing the investment in technological innovation and upgrading can promote the effective management of the coal overcapacity issue. This study can more genuinely reflect the complicated dynamic game process of China's coal de-capacity than the previous studies, and thus provides insights and decision-making references for the design of an effective coal overcapacity governance mode.

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  • Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2021. "Exploring the dilemma of overcapacity governance in China's coal industry: A tripartite evolutionary game model," Resources Policy, Elsevier, vol. 71(C).
    • Handle: RePEc:eee:jrpoli:v:71:y:2021:i:c:s0301420721000179
    DOI: 10.1016/j.resourpol.2021.102000
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