The impact of carbon emissions on green total factor productivity: an empirical analysis based on Chinese provincial panel data

Jiaqiu Wang; Xiaocheng Sun

doi:10.1117/12.2671807

28 March 2023 The impact of carbon emissions on green total factor productivity: an empirical analysis based on Chinese provincial panel data

Jiaqiu Wang, Xiaocheng Sun

Author Affiliations +

Proceedings Volume 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022); 1259715 (2023) https://doi.org/10.1117/12.2671807
Event: Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 2022, Nanjing, China

Abstract

By investigating the impact of carbon emissions on green total factor productivity, this paper calculated the green total factor productivity of 30 provinces and municipalities in China from 2005 to 2017 using SBM-ML index, and empirically tested the impact of carbon emissions on green total factor productivity based on linear regression model. It is found that carbon emission intensity has a negative impact on green total factor productivity, and R&D intensity has a positive effect on green total factor productivity. In view of this, on the one hand, carbon dioxide emissions can be reduced through certain environmental regulation policies, and on the other hand, enterprises can be encouraged to research and innovation through certain tax support, so as to improve the level of green total factor productivity, in order to achieve China's dual carbon goal as soon as possible.

Citation Download Citation

Jiaqiu Wang and Xiaocheng Sun "The impact of carbon emissions on green total factor productivity: an empirical analysis based on Chinese provincial panel data", Proc. SPIE 12597, Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), 1259715 (28 March 2023); https://doi.org/10.1117/12.2671807

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