Regional Inequality and Influencing Factors of Province-Level Energy-Related Carbon Emissions in China - Weichen, Sun (Transformations In Business & Economics, 2025)
This paper estimates carbon emissions from energy consumption in 30 Chinese provinces using the IPCC methodology based on eight types of energy consumption data spanning from 2005 to 2018. Spatial autocorrelation analysis is applied to investigate changes in spatial patterns, while the Geographically Weighted Regression (GWR) model is employed to assess the factors influencing carbon emissions in each province. Three principal findings emerge from the analysis: first, a significant spatial dependency among carbon emissions is observed across the provinces. Provinces with high emissions tend to be geographically clustered with others exhibiting similar levels, forming distinct high-high and low-low agglomeration patterns. However, this spatial dependency has been weakening over time. Second, carbon emissions display significant local spatial clustering, with each province exhibiting unique spatial heterogeneity. Finally, the economic conditions, technological progress, and energy structures vary considerably among provinces leading to differentiated impacts on carbon emissions. Factors such as economic growth, population size and energy structure generally contribute to the rise in carbon emissions.
Keywords: carbon emissions; province-level; spatial pattern; influencing factors