碳排放税
补贴
税率
经济
偏爱
碳纤维
公共经济学
微观经济学
货币经济学
温室气体
市场经济
生态学
生物
复合数
复合材料
材料科学
作者
Dongsheng Liao,Binbin Tan
出处
期刊:Energy
[Elsevier]
日期:2023-02-01
卷期号:264: 126156-126156
被引量:21
标识
DOI:10.1016/j.energy.2022.126156
摘要
This paper uses evolutionary game theory to explore an effective carbon taxation mechanism in post-subsidy era based on hoteling demand. First, an evolutionary game model is constructed to explore interplays between local governments and auto-manufacturers. Then, optimal carbon tax mechanism and parameters sensitivity are analyzed and compared in different scenarios using empirical analysis. We conclude that: (1)In subsidy phase-out scenario, static carbon tax policy is better than phasing in carbon tax policy; in subsidy withdrawn scenario, phasing in carbon tax policy can popularize NEVs in a more stable way. (2)Under the mechanism of withdrawal subsidy and carbon tax phase-in, there exist marginal diminishing effects in phase-in rate r and carbon tax rate Tc; under the mechanism of subsidy phase-out and static carbon tax, both marginal increasing effect and marginal decreasing effect are existed in carbon tax rate Tc. (3)Under the mechanism of withdrawal subsidy and carbon tax phase-in, a threshold effect is found in carbon emission trading revenue Rc, license priority for NEVs consumers η, charging pile coverage rate β, corporate income tax concession Rd, consumers' low carbon preference θ and vehicle purchase tax Tb, while there is a marginal incremental effect in them under the mechanism of withdrawal subsidy and carbon tax phase-in, and the parameters in former mechanism are more sensitive. Further, those parameters are divided into three levels according to their influential degree, in which consumers’ low carbon preference θ is at first level. Accordingly, it is suggested that governments implement appropriate carbon tax policies at different industrial developmental phase, supplemented by support policies paying most attention on vigorously promoting low-carbon consumption or subsidizing low-carbon behaviors.
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