Exploring the dynamic linkages between carbon trading market and smart technology indices: A multi-dimensional analysis of China's case

Abstract

This paper examines the dynamic correlation and spillover effects between China's carbon emissions trading market and smart technology indices (including intelligent transportation, smart cities, robotics, cloud computing, and smart manufacturing) through a multi-dimensional empirical framework. By employing the DCC-GARCH connectedness model, wavelet coherence analysis, and quantile wavelet correlation methods, we document several important findings: (1) The carbon emissions market demonstrates strong independence with a systemic connectedness index of 24.91%, acting as a primary source of volatility transmission in the system; (2) The dynamic connectedness between markets shows significant temporal variation, reaching its peak of 70% in mid-2022 and maintaining around 50% throughout 2023; (3) The wavelet coherence analysis identifies substantial co-movement patterns between carbon market and smart technology indices across different frequencies, with the strongest correlation observed in the medium-frequency band (16-32 days); (4) The quantile wavelet correlation results suggest a significant positive relationship between carbon market and smart technology indices during medium to long-term frequencies (64-256 days) and at medium to high quantile levels (0.5-0.8), highlighting the constructive role of smart technologies in carbon reduction efforts. Our findings reveal that technological innovation in smart sectors contributes positively to carbon market efficiency, particularly during periods of market stability. This research provides critical insights for policymakers seeking to enhance the synergy between technological development and carbon reduction objectives. These findings offer valuable insights into understanding the intricate relationship between carbon trading and technological advancement in China's context.