In order to reduce carbon emissions for sustainable development, we analyzed the impact of China’s digital economy development on carbon emissions. Based on the panel data of 30 Chinese provinces from 2009 to 2019, we measured the level of development of China’s digital economy using the entropy method. The relationship between the digital economy and carbon emissions was analyzed from multiple perspectives with the help of the fixed-effects model, the mediated-effects model and the spatial econometric model. The results indicate that the digital economy plays a significant inhibitory role in carbon emissions. In addition, the digital economy inhibits carbon emissions through the innovation effect and the industrial structure upgrading effect. Moreover, the digital economy exhibits a significant spatial spillover effect in dampening carbon emissions. Finally, there is regional heterogeneity in the direct and spatial spillover effect. The findings provide a basis for the digital economy to contribute to carbon emissions reduction and provide relevant policy references for achieving carbon neutrality and sustainable development.

China’s economy has developed rapidly since the reform and opening up, but under the long-term traditional extensive development model, energy consumption is excessive and carbon emissions rank first in the world. Therefore, how to reduce carbon emissions is a current hot issue in China. Although many scholars have found that green finance is the basic driving force to promote carbon emission reduction, its role path is diverse, and it still needs to be explored in width and depth. Especially in the green transformation stage of the economy, the potential unemployment risk is also a matter of concern. This study selects 30 provincial panel data from the Chinese mainland for the 2004–2019 years to investigate the impact of green finance on carbon emissions from the perspective of unemployment using ordinary least square (OLS), generalized method of moments (GMM), and mediating effect models. In addition, in order to avoid the bias of regression results caused by the cross-section dependence of the data, the feasible generalized least squares (FGLS) and the panel-corrected standard errors (PCSE) models are used for the robust test after correction. The findings show that 1) green finance has a significant inhibitory impact on carbon emissions; 2) green finance has significantly reduced the unemployment rate; 3) carbon emissions increase significantly with increasing the unemployment rate; and 4) there is regional heterogeneity in the effect of green finance on carbon emissions in eastern, central, and western China. Green finance in the eastern and central regions significantly inhibits carbon emissions, especially in the central region, while insignificantly in the western region. 5) According to the OLS and mediating effect regression results, economic growth and environmental regulation play a significant positive role in promoting carbon emissions. This study has theoretical reference significance for accelerating the realization of the dual carbon goal and alleviating phased unemployment.