Time-Frequency and Quantile Connectedness Among Geopolitical Risks, Conventional and Clean Energy, Electricity, and Carbon Markets

Climate change, energy crisis, and geopolitical conflicts have become the triple dilemma of the world, which seriously hinders global sustainable development. Against this context, achieving net-zero emissions and promoting energy transition have been put on the urgent agenda. Therefore, it is necessary to have a deep understanding of the linkage among geopolitical risks, conventional/clean energy, electricity, and carbon markets, so as to stabilize energy and carbon markets and ensure the orderly progress of energy transition and carbon emission reduction. This study explores the dynamic and directional connectedness among these variables under multiple time frequencies and conditions by using two volatility spillover approaches and the quantile vector autoregression model. We find that the interconnectedness between variables is greatly strengthened during extreme conditions and dominated by the spillover effects in the short run. Electricity market is always the critical risk spillover contributor in situations of various scales of shocks. Fossil and clean energy are both net recipients of spillover effects from electricity and carbon markets. And notably, the geopolitical risks act as the net short-term spillover receiver and medium- and long-term spillover transmitter in the connectedness network. Additionally, we show that carbon market becomes a significant risk transmitter under extreme circumstances. Our findings have implications for preventing adverse effects of cross-risk spillovers and promoting global sustainability. Received: 25 July 2024 | Revised: 9 October 2024 | Accepted: 20 January 2025 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, Writing - review & editing, Supervision. Jingang Jiang: Software, Data curation, Writing - original draft, Visualization. Jinyan Hu: Funding acquisition.