Impact of climate policy uncertainty on traditional energy and green markets: Evidence from time-varying granger tests

Abstract

Extreme weather anomalies act as threat multipliers, warning us to focus on low-carbon transition and sustainable development. This study analyses the dynamic bidirectional causality between climate policy uncertainty (CPU) and traditional energy, represented by oil, coal, and natural gas, as well as green markets, represented by clean energy, green bonds, and carbon trading. This research provides the first comprehensive assessment of CPUs across multiple dimensions of different energy properties, causal spillover directions, and temporal heterogeneity using the time-varying Granger test. The results indicate that significant dynamic causality exists within each series rather than the entire period, and that causality manifests differently between pairs of series. In addition, CPU is more inclined to act as a risk recipient than a sender in the market volatility spillover. Whenever extreme climate events or major climate policy changes are encountered, the causal relationship between CPU and the relevant markets will rise significantly. Overall, governments should pay attention to the role of climate policy implementation in energy transition as well as attempt to reduce uncertainty.

Keywords: Extreme weather Clean energy Green bonds CPU Energy transition