- Title
- How are artificial intelligence, carbon market, and energy sector connected? A systematic analysis of time-frequency spillovers
- Creator
- Xu, Yingying; Shao, Xuefeng; Tanasescu, Cristina
- Relation
- Energy Economics Vol. 132, Issue April 2024, no. 107477
- Publisher Link
- http://dx.doi.org/10.1016/j.eneco.2024.107477
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2024
- Description
- The dual role of artificial intelligence (AI) in carbon emissions has come under scrutiny. The feedback mechanism in the “AI-Carbon-Energy” system contains the enlightenment of coordinated development of environment and economy. Based on the dynamic connectedness index and network diagrams, we quantify how the AI industry is connected to the carbon market and the energy sector in the short-term and long-term. Our empirical findings suggest that the information spillover within the system changes over time and across frequency bands. The long-term component drives the overall information spillover. Both the carbon market and the energy sector are closely connected with the AI industry. Specifically, AI industry trading volume is a main information transmitter. Since the release of GPT-4, however, investor attention to the AI industry becomes more important. The carbon market receives a lot of information from the AI industry trading volume and investor attention to the AI industry, particularly since 2023. Nevertheless, the energy sector is only weakly connected to the other two markets. These findings have important implications for policy makers, investors, and producers.
- Subject
- artificial intelligence; carbon market; energy industry; investor attention; information spillover
- Identifier
- http://hdl.handle.net/1959.13/1501447
- Identifier
- uon:55143
- Identifier
- ISSN:0140-9883
- Language
- eng
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