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Article

The Impact of Carbon Emissions Trading Pilots on the Low-Carbon Competitiveness of High-Carbon Industry-Listed Companies: An Empirical Analysis Based on Double Machine Learning

1
College of Digital Economy, Fujian Agriculture and Forestry University, Quanzhou 362406, China
2
College of Rural Revitalization, Fujian Agriculture and Forestry University, Fuzhou 350002, China
3
College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350002, China
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(24), 10886; https://doi.org/10.3390/su162410886
Submission received: 21 November 2024 / Revised: 6 December 2024 / Accepted: 10 December 2024 / Published: 12 December 2024

Abstract

Carbon emissions trading pilots are an essential environmental regulation tool for incentivizing companies to reduce carbon emissions and a critical initiative for achieving “dual carbon” targets. This study, based on 2366 observations of 169 high-carbon listed companies on the Shanghai and Shenzhen stock exchanges from 2009 to 2022, uses double machine learning analysis to examine the impact and mechanisms of pilot policy on the low-carbon competitiveness of high-carbon industry-listed companies. The empirical results show that, first, pilot policy significantly enhances the low-carbon competitiveness of high-carbon industry-listed companies, and this conclusion holds after considering a series of robustness checks. Second, mechanism analysis indicates that alleviating green financing constraints and enhancing total factor productivity are pathways through which pilot policy influences low-carbon competitiveness. Heterogeneity analysis shows that the policy effects are stronger for state-owned enterprises, small- and medium-sized enterprises, and companies in eastern regions. Further analysis reveals that pilot policy enhances low-carbon competitiveness and increase enterprise value. Based on the study’s conclusions, the government should ensure the incentivizing effect of pilot policy, promote expansion of the carbon emissions trading market, assist enterprises in overcoming green financing constraints, improve total factor productivity, and formulate tailored policies according to the development levels and resource endowments of regions and companies.
Keywords: carbon emissions trading pilots; low-carbon competitiveness; double machine learning; high-carbon industry-listed companies carbon emissions trading pilots; low-carbon competitiveness; double machine learning; high-carbon industry-listed companies

Share and Cite

MDPI and ACS Style

Yi, X.; Liu, W.; Weng, D.; Ma, Z.; Wei, J.; Dai, Y. The Impact of Carbon Emissions Trading Pilots on the Low-Carbon Competitiveness of High-Carbon Industry-Listed Companies: An Empirical Analysis Based on Double Machine Learning. Sustainability 2024, 16, 10886. https://doi.org/10.3390/su162410886

AMA Style

Yi X, Liu W, Weng D, Ma Z, Wei J, Dai Y. The Impact of Carbon Emissions Trading Pilots on the Low-Carbon Competitiveness of High-Carbon Industry-Listed Companies: An Empirical Analysis Based on Double Machine Learning. Sustainability. 2024; 16(24):10886. https://doi.org/10.3390/su162410886

Chicago/Turabian Style

Yi, Xiangfa, Wanyi Liu, Diyao Weng, Ziyuan Ma, Jian Wei, and Yongwu Dai. 2024. "The Impact of Carbon Emissions Trading Pilots on the Low-Carbon Competitiveness of High-Carbon Industry-Listed Companies: An Empirical Analysis Based on Double Machine Learning" Sustainability 16, no. 24: 10886. https://doi.org/10.3390/su162410886

APA Style

Yi, X., Liu, W., Weng, D., Ma, Z., Wei, J., & Dai, Y. (2024). The Impact of Carbon Emissions Trading Pilots on the Low-Carbon Competitiveness of High-Carbon Industry-Listed Companies: An Empirical Analysis Based on Double Machine Learning. Sustainability, 16(24), 10886. https://doi.org/10.3390/su162410886

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