Examining the Impact of Tax Competition on Industrial Carbon Emissions—Evidence from Provincial Panel Data in China

Against the backdrop of China’s “dual carbon” goals and mounting fiscal pressures at the local level, local governments face a dilemma between offering tax incentives and reducing industrial carbon emissions. This study uses data from 30 Chinese provinces between 2000 and 2022. It employs the Dagum Gini coefficient to characterize regional disparities and spatial heterogeneity in industrial carbon emissions, utilizes the Super-Slack-Based Measure (SBM) model and kernel density estimation to estimate the spatiotemporal evolution of tax competition, constructs a Spatial Durbin Model (SDM) to examine its direct effects and spatial spillover effects, and conducts robustness tests using four different methods. The study finds that: (1) tax competition has a significant positive direct effect on local industrial carbon emissions and generates positive spatial spillovers; bottom-up tax competition exacerbates overall regional carbon emissions; (2) control variables such as economic development level and energy intensity all exhibit significant spatial spillover characteristics; and (3) the carbon emission effects of tax competition exhibit regional heterogeneity, with positive spatial spillovers in the eastern region and predominantly negative spillovers in the central and western regions. From a spatial competition perspective, this paper reveals the underlying mechanisms and regional differences between these two factors. The findings provide empirical insights and policy references to optimize the competitive landscape among local governments, improve the regional collaborative green tax system, promote low-carbon industrial transformation, and achieve the “dual carbon” goals.