An Asymmetric Nash Bargaining Model for Carbon Emission Quota Allocation among Industries: Evidence from Guangdong Province, China
Fei Ye,
Lixu Li,
Zhiqiang Wang and
Yina Li
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Fei Ye: School of Business Administration, South China University of Technology, Guangzhou 510640, China
Lixu Li: School of Business Administration, South China University of Technology, Guangzhou 510640, China
Zhiqiang Wang: School of Business Administration, South China University of Technology, Guangzhou 510640, China
Yina Li: School of Business Administration, South China University of Technology, Guangzhou 510640, China
Sustainability, 2018, vol. 10, issue 11, 1-18
Abstract:
As the most cost-effective mechanism, an emissions trading scheme (ETS) plays an important role in mitigating global warming, whilst any such scheme requires the initial allocation of quotas. Current allocation methods, however, pay little attention to the interests of abatement entities, which will hinder the long-term sustainable goals. To mobilize the enthusiasm of different abatement entities, this study proposes a multiplayer asymmetric Nash bargaining model, ensuring that all entities can obtain more quotas after negotiation. To demonstrate the advantages of the proposed method, this study selects Guangdong where the principal allocation method is the grandfathering approach as an illustrative case and develops three preference cases including balanced weighting, economic-oriented weighting, and emission-oriented weighting. The empirical results show that the proposed method not only reflects the “polluter pays principle”, but also helps to save emission reduction costs. In further analysis, this study considers both free allocation ratio and ETS coverage, providing inspirations for policy makers to develop new ETS regulations. In general, the proposed method not only assists policy makers of Guangdong in improving the current ETS deficiencies but also can be generalized into other regions.
Keywords: emissions trading scheme; asymmetric Nash bargaining model; grandfathering approach; carbon reduction labelling; Guangdong (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:10:y:2018:i:11:p:4210-:d:182988
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