Document Type
Article
Abstract
This article examines the significant roles of sustainable finance and Artificial Intelligence (AI) in advancing China’s energy sustainability by employing the TVP-VAR-SV model to track dynamic interactions among the Green Bond Index (GBI), New Economy Index (NEI), and Energy-related Uncertainty Index (EUI). Findings indicate that both GBI and NEI reduce EUI, with GBI exerting a stronger influence due to its direct link to sustainable finance, underscoring its role in mitigating energy market uncertainties. EUI, however, negatively affects GBI, revealing that high energy uncertainty may impede sustainable finance progress. Interestingly, EUI has a mixed effect on NEI, suggesting that energy uncertainties can either drive or hinder AI development. GBI and NEI show a positive relationship, moving in tandem, emphasizing how sustainable finance and AI could collectively address energy challenges amid climate concerns and technological advancement.
Recommended Citation
Su, Chi Wei and Qin, Meng
(2024)
"Unravelling Dynamics and Connectedness: Distinguishing The Influence of Sustainable Finance and Artificial Intelligence on Energy Sustainability in China,"
Bulletin of Monetary Economics and Banking: Vol. 27:
No.
4, Article 8.
DOI: https://doi.org/10.59091/2460-9196.2418
Available at:
https://bulletin.bmeb-bi.org/bmeb/vol27/iss4/8
First Page
741
Last Page
766
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Country
China
Affiliation
Wuchang University of Technology
