Climate Policy Uncertainty And Carbon Price: Evidence From Frequency And Quantile Perspective

Changes in climate policy are posing enormous challenges to carbon markets. However, the intricate link and time-frequency features between climate policy uncertainty (CPU) and carbon emission price (CEP) have not been extensively explored in the current literature. This paper aims to reveal the dynamic relationship between the two under different time frequencies and quantiles by using a wavelet-based quantile-on-quantile regression (QQR) method. Nine sets of variable pairs with various temporal frequencies are constructed, such as short-term CPU and long-term CEP. The results demonstrate that their coefficients would change from positive to negative or irrelevant, or conversely, under different quantiles and frequencies. China has been a global focus and an interesting case since its relentless efforts towards addressing climate change and constructing a carbon market, which makes one of the contributions of this paper. Additionally, time frequencies combined with different quantiles are employed to explore the connection between CPU and CEP, revealing nonlinear and asymmetric features between variables, and enriching the theoretical influencing mechanisms. Therefore, the government should avoid drastic policy changes, and make full use of policy guidance effect. Besides, top-design and market-oriented reforms for the carbon market are needed.