Quantile Time-Frequency Connectedness Between Carbon Emissions, Traditional and New Energy: Evidence from COVID-19 and the Russia-Ukraine Conflict

This study investigates the spillover effects associated with diverse market conditions in energy and carbon markets, encompassing both new and traditional energy sectors. Using a quantile vector autoregression approach, this research explores the dynamic interactions among carbon emissions, traditional energy, and new energy from January 1, 2019, to July 28, 2023. Firstly, the research findings presented in this article reveal a significant spillover effect under extreme conditions, whether the change is highly positive or negative, with increases observed from 26.67% to 76.15% and 74.19%, respectively. Secondly, during the Russia-Ukraine conflict and COVID-19 pandemic, the interaction among carbon emissions, traditional energy, and new energy intensified, transforming their roles in the context of spillover effects. The negative spillover effects in the new energy and carbon markets position them as effective hedging tools. Finally, the pandemic and conflicts have underscored the increasing importance of new energy, particularly in the long run, as evidenced by the significant expansion of spillover effects in the new energy market. These findings inform policymakers and ecological investors in developing effective policies and tailored investment strategies across various frequency ranges. Received: 27 August 2024 | Revised: 15 October 2024 | Accepted: 22 November 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data available on request from the corresponding author upon reasonable request. Author Contribution Statement Wei Jiang: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Writing - review & editing, Funding acquisition. XiaoLiang Guo: Conceptualization, Software, Validation, Formal analysis, Investigation, Data curation, Writing - original draft, Writing - review & editing, Visualization, Project administration. Sifeng Bi: Data curation, Writing - review & editing, Supervision.