Table 1_Exploring spillover effects between climate policy uncertainty and carbon trading prices: evidence from China.docx

IntroductionAs China advances its dual carbon targets, the carbon market has become a key policy instrument. However, climate policy uncertainty (CPU) can disrupt expectations and amplify risks in carbon trading prices (CTP), creating challenges for market stability and policy effectiveness.
MethodsTo address this issue, this study constructs a weekly China-specific CPU (CCPU) index using text analysis of domestic newspapers and employs the Quantile Vector Autoregression–Diebold-Yilmaz (QVAR-DY) framework to assess its spillover effects on returns and volatility across six regional carbon markets. The quantile Granger-causality test is also applied to further validate the direction and significance of spillovers under different market conditions.
ResultsThe analysis shows that spillovers remain moderate under normal conditions but intensify considerably under extreme states, particularly at higher quantiles, as confirmed by the quantile Granger-causality tests. The most striking finding is that spillovers from CCPU to volatility are consistently stronger than to returns, indicating that systemic risk contagion is more pronounced through volatility channels.
DiscussionBy integrating a quantile perspective with dynamic spillover analysis, this study reveals the asymmetric transmission of policy uncertainty in China’s carbon markets and provides new insights for risk monitoring and policy design in the low-carbon transition.