How are artificial intelligence, carbon market, and energy sector connected? A systematic analysis of time-frequency spillovers

Xu, Yingying; Shao, Xuefeng; Tanasescu, Cristina

doi:10.1016/j.eneco.2024.107477

Cited by 2 publications

(1 citation statement)

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“…This means that a lack of financial support or monitoring systems could lead to increased carbon emissions. Carbon market institutions in carbon pilot regions may be more mature and perfect, including monitoring, reporting and verification (MRV) systems, as well as carbon trading and regulatory frameworks [45]. This helps them participate more effectively in the national carbon market.…”

Section: Discussionmentioning

confidence: 99%

Emission Reduction Effects of China’s National Carbon Market: Evidence Based on the Power Sector

Xu,

Zhao,

Chu

et al. 2024

Energies

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The power sector is one of the major CO2-emitting industries in China. It is also the first key emissions control industry included in China’s national carbon trading market established in 2021. Therefore, based on the data of 30 provinces and cities in China from 2015 to 2022, this study analyzes the impact of the national carbon market policy on the carbon emissions of the power industry based on the generalized Difference-in-Difference (DID) model. Based on the method of text analysis, this paper constructs the carbon market policy intensity index of each region and incorporates it into the DID model. Empirical analysis finds that the national carbon market policy can significantly inhibit the carbon emissions of the power industry. However, the heterogeneity analysis of 30 provinces and cities shows that the national carbon market policy has a significant impact on the regions that already have a carbon pilot, but not on the non-pilot regions. Therefore, this paper demonstrates the effectiveness of the national carbon market policy in the power industry emissions control, and also exposes the heterogeneity between regions, providing an important empirical basis for the inclusion of other energy-intensive industries.

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Section: Discussionmentioning

confidence: 99%