Investigating the Determinants of Carbon Emissions Using the Granger Causality Test: Evidence from China’s Main Sectors

This study attempts to investigate the key determinants of carbon emissions across China’s major sectors, including transportation, real estate, and industrial sector, throughout the period between 2004 and 2023. Then examine their causal relationship to develop a carbon emission reduction framework. The Auto-Regressive Distributed Lag (ARDL) model and Granger causality test were utilized for analysis. In the long-term, EC and FDI negatively affect CE, while IT positively affects that. In the short-term, CE are positively influenced by FDI and PG, while negatively impacted by EG and EC. Besides, the impacts of these determinants on carbon emissions vary across sectors. Moreover, the analysis reveals bidirectional causality between CE and EG, CE and FDI, and CE and IT, while unidirectional causal relationship is observed with EC driving CE. The finding also reveals that the policies should prioritize low-carbon transitions by integrating sustainability into economic planning and infrastructure development in the “the Five-Year Plans”. This study provides critical policy-relevant insights to guide policymakers in designing effective strategies for carbon emission mitigation. It introduces an innovative sector-specific analysis that identifies key opportunities across different sectors. Additionally, the study proposes a structured policy framework to systematically support China’s carbon goals. By bridging research and practical implementation, this work contributes both theoretically and empirically to the advancement of sustainable development.