Volatility Spillover Between China’s Carbon Market and Traditional Manufacturing - Jining Wang; Dian Sheng; Lei Wang (Mathematics)
This study constructed a DGC-t-MSV model by integrating dynamic correlation and Granger causality into the MSV framework. Using daily closing price data from 4 January 2022 to 21 November 2024, it empirically analyzed volatility spillover effects between China’s carbon market and traditional manufacturing from an industrial heterogeneity perspective. The findings are as follows: (1) The carbon market exhibits significant unidirectional volatility spillover effects on carbon-intensive industries, such as steel, chemicals, shipbuilding, and automobile manufacturing, with the carbon market acting as the spillover source. (2) Bidirectional volatility spillover effects exist between the carbon market and industries such as forest products, textiles, construction engineering, and machinery manufacturing, with the carbon market predominantly acting as a recipient. (3) The carbon market exhibits general dynamic correlations with traditional manufacturing industries, where the correlation strength is positively associated with industry-level carbon emissions. Notably, the correlations with the steel, chemicals, machinery manufacturing, construction engineering, and automobile manufacturing industries are significant, whereas those with the textile industry and the forest products industry are relatively weaker. Furthermore, the carbon market demonstrates substantially higher volatility than traditional manufacturing industries. This study innovatively explored volatility spillover effects between China’s carbon market and traditional manufacturing from an industrial heterogeneity perspective, providing policy implications for their coordinated development.