Abstract
At the United Nations General Assembly, the Chinese government promised to reach the peak of carbon dioxide emissions by 2030 and achieve a relative balance between carbon dioxide production and offsetting by 2060. The research aims to explore the relationship between carbon trading prices and stock prices in various high emission industries in China and analyze the attitudes and behaviors of enterprises towards carbon trading. From a market perspective, this topic has important theoretical significance and practical value for promoting energy transformation, encouraging enterprises to reduce emissions, and controlling greenhouse gas emissions. In addition, understanding the behavior and attitude of enterprises in the carbon market is also of great significance for formulating policies and measures to develop the carbon trading market. The study used the VAR model to empirically analyze the relationship between carbon trading prices and stock prices. Granger causality test, impulse response analysis, and variance decomposition analysis are used for analysis. The research results indicate that the contribution rate of carbon trading prices in the first phase is 100%, which gradually decreases to the lowest value of 98.27% in the eighth phase. The stock price contribution rates of the water, electricity, and gas supply industries reach a peak of 0.74% in the second period and gradually decrease to 5.2% in the eighth period. The contribution rate of stock prices in other industries has gradually increased. At present, the carbon trading market in China is still in the development stage, and it is necessary for the government to adopt various policies to regulate it, including encouraging enterprises in high emission industries to increase investment in emission reduction, strengthening the supervision of the carbon trading market, providing technical support and green innovation incentives, strengthening enterprise emission reduction awareness and information disclosure.
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Abbreviations
- VAR:
-
Vector autoregression
- AIC:
-
Akaike Information Criterion
- BIC:
-
Bayesian Information Criterion
- CSI:
-
Crime scene investigation
- ADF:
-
Augmented Dickey-Fuller test
- CNY:
-
Chinese Yuan
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Yukun Song: conceptualization, data curation, methodology, and writing — original draft; Yang Liu: data curation, visualization, supervision, editing, writing — review and editing, and software.
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Song, Y., Liu, Y. Empirical analysis of the relationship between carbon trading price and stock price of high carbon emitting firms based on VAR model — evidence from Chinese listed companies. Environ Sci Pollut Res 31, 1146–1157 (2024). https://doi.org/10.1007/s11356-023-30906-w
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DOI: https://doi.org/10.1007/s11356-023-30906-w