The dynamic connectedness in the “carbon-energy-green finance” system: The role of climate policy uncertainty and artificial intelligence

Shaozhou Qi, Lidong Pang, Xinqiang Li and Lin Huang

Energy Economics, 2025, vol. 143, issue C

Abstract: The shared vision of mitigating carbon emissions in response to climate change has fostered the interconnection among the EU ETS, traditional energy and green finance sectors. This paper employs the time-frequency spillover methods to explore the connectedness within the Carbon-Energy-Green Finance system, from a time-frequency domain perspective. The empirical results indicate limited connectedness in this system, and are predominantly visible in the high-frequency (short-term) range. Although there are co-movement patterns across different frequencies, the roles of some specific markets tend to shift over time. Notably, the natural gas market primarily serves as the net receiver of spillover effects, demonstrating heightened sensitivity to information from other nodes within the system. In addition, there is heterogeneity in the impact of climate policy uncertainty and artificial intelligence development on the network in time-domain and high-frequency scenarios. However, the dominant positive effects of both can be captured in the long run, albeit with a lesser magnitude. Therefore, investors should be adaptable to adjust their portfolios under different investment horizons. And in the pursuit of sustainable ambitions, the strategy of policymakers to cushion potential external risks also cannot be shelved.

Keywords: Carbon trading market; Green finance; Time-frequency spillover; Climate policy uncertainty; Artificial intelligence (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:143:y:2025:i:c:s0140988325000647

DOI: 10.1016/j.eneco.2025.108241

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