While the environmental issues resulting from carbon emissions are widely recognized by the public, there is a lack of in-depth research on whether controlling carbon emissions will have an impact on social development at the national level. In this study, we used panel data from 166 countries worldwide from 2005 to 2020 to construct coupled coordination models, panel regression models, and spatial Durbin models to assess the impact of carbon emissions on the coupled coordinated development of sustainable development goals (SDGs) in different countries around the world. This study is the first to investigate the features, heterogeneity, and spatial effects of carbon emissions on the SDG coupling coordination degree. We found that: (1) Globally, the SDG coupling coordination degree was generally low from 2005 to 2020. Despite the slow improvement in the global SDG coupling coordination degree over the past 16 years, it has always been in a barely imbalanced transitional development state. At the same time, there was a phenomenon of “high-income > high–middle-income > low–middle-income > low-income” difference in the SDG coupling coordination development level among countries of different income types. (2) Carbon emissions have a significant promoting effect on the SDG coupling coordination degree for low-income and low–middle-income countries while having a significant inhibitory effect on the SDG coupling coordination degree for high–middle-income and high-income countries. In addition, the impact of carbon emissions on the SDG coupling coordination degree also exhibits regional heterogeneity. (3) Carbon emissions have a significant spatial spillover effect on the SDG coupling coordination degree, with a positive promoting effect on the SDG coupling coordination degree in one’s own country and a significant inhibitory effect on the SDG coupling coordination degrees of neighboring countries. Our research can help decision-makers develop targeted carbon reduction plans to avoid social development losses caused by controlling carbon emissions in a crude manner. Our research findings provide crucial evidence for the formulation of international policies aimed at reducing carbon emissions, in order to avoid the inequities that may result from the adoption of extreme carbon reduction policies.

This paper uses the entropy method to estimate China’s green financial development from four aspects, namely, green credit, green securities, green insurance, and green investment, based on the provincial-level panel data from 2008 to 2019. The spatial Durbin model (SDM) is adopted to estimate the spatial effect of green finance on carbon emissions. We then compare the heterogeneous effect in the South and North of China. The results show that China’s green financial development can significantly reduce carbon emissions, and regional heterogeneities are obvious. In the South of China, this effect from local and adjacent regions is not significant, while on the whole, green finance can significantly reduce carbon emissions; but for Northern China, this effect is not significant; nationally, the development of green finance and carbon emissions in adjacent areas showed an inverted U-shaped relationship. China’s green financial development and carbon emissions also showed an inverted U-shaped relationship. These results suggest that the effect of green finance development on carbon emissions exhibits substantial regional heterogeneity in China. Our paper provides some concrete empirical evidence for policymakers to formulate green financial policies to achieve the double carbon goal in China.