Research on the risk spillover effect of carbon emission trading market and various industry markets in China and the European Union

Widely concerns over the carbon emission problems have been aroused. Prior studies have documented the correlation between the carbon emission market and industries separately. This study compared the tail risks and risk spillover effect of the carbon emission and 11 industries markets in China and the European Union (EU) by using the multivariate multi-quartile conditional autoregressive at-risk model. Moreover, to evaluate the risk spillover of each market under extreme risk conditions in time domain and frequency domain, DY spillover index and BK spillover index were constructed via generalized forecast error variance decomposition and generalized causation spectrum, respectively. Findings are as follows: (1) The tail risks and fluctuation of the trend of Chinese industry markets reflects more higher and larger than those in the EU; (2) The EU suffers from smaller external shocks, while China has the opposite result and can recover relatively faster; (3) In China, energy, industrial, information technology, financial, real estate, consumer goods, carbon emissions, and discretionary consumption industries are risk spillover industries, while healthcare, materials, telecommunication services, and utilities industries are risk receiving industries. In contrast, the risk spillover industries in the EU remain consistent with those of the Chinese markets except for the materials, discretionary consumption, consumer goods, information technology and real estate industries. (4) On the short-term, medium-term and long-term scales, the risk spillover of China's carbon emission trading market and various industries is basically consistent with that of the EU. These findings contribute to reducing greenhouse gas emissions and achieving the goal of carbon peak and carbon neutrality. The study visualizes how various industries in China and the European Union (EU) interact with the carbon emission trading markets, with a particular focus on tail risks and spillover effects across time and frequency domains. Notably, the analysis reveals stronger and more volatile spillovers in Chinese markets, with rapid recovery from shocks, while EU markets show more stable and smaller fluctuations. image