A Study of the Influencing Factors on the Carbon Emission Trading Price in China Based on the Improved Gray Relational Analysis Model

Xiaohua Song, Wen Zhang, Zeqi Ge, Siqi Huang, Yamin Huang and Sijia Xiong
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Xiaohua Song: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Wen Zhang: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Zeqi Ge: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Siqi Huang: School of Accounting, Capital University of Economics and Business, Beijing 100070, China
Yamin Huang: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Sijia Xiong: School of Economics and Management, North China Electric Power University, Beijing 102206, China

Sustainability, 2022, vol. 14, issue 13, 1-27

Abstract: Carbon emission trading market construction is an important policy tool to promote the realization of China’s “double carbon” goal. However, problems still exist, such as the lack of market trading vitality, the large difference in carbon trading prices between the eight pilot markets and the instability of the prices. In order to explore the key influencing factors on carbon trading prices, 15 factors were selected to study in detail according to the policy, green industry, economy and environment. Taking China’s eight pilot carbon trading markets as research subjects, we explored the correlation degree of each factor by using the improved gray relational analysis model (GRAM) from the two dimensions of space and time. The research results show that from the space dimension, the industrial development level, development degree of low-carbon industries, air pollution degree and green technology maturity are the main factors that affect the carbon trading price in the eight pilot areas. Meanwhile, from the time dimension, the correlation degree between various factors and carbon trading price both showed a downward trend as a whole, and the fluctuation of the correlation degree of individual factors was different from the overall trend. In conclusion, we can put forward recommendations on the pricing mechanism of the carbon trading market after this comprehensive study.

Keywords: carbon emissions trading; carbon trading price; influencing factors; improved gray relational analysis model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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