The carbon emission reduction effect of digital finance: a spatio-temporal heterogeneity perspective

This study constructs a geographically and temporally weighted regression model to investigate the spatio-temporal heterogeneity effect of digital finance on carbon emissions and carbon emission intensity, using panel data of 30 Chinese provinces from 2011 to 2019 as a sample. The results demonstrate that digital finance can significantly reduce carbon emissions and carbon emission intensity. And there is a significant positive spatial autocorrelation between the carbon emissions of each province in each year, that is, neighboring cities have spillover effects on local carbon emissions. In addition, there is spatial and temporal heterogeneity in the effects of various factors on carbon emissions. Specifically, the carbon reduction capacity of digital finance becomes weaker between 2011 and 2019, and the carbon reduction effect of digital finance is stronger in northern China than in southern China. Digital finance reduces carbon emissions and carbon emission intensity with the law of diminishing marginal utility, that is, it has a more significant impact on carbon emission reduction in the first few years, with greatest impact on various subjects and fields at the beginning of its launch. And due to the difference in energy structure and economic and social development level between the north and south of China, the influence of digital finance on carbon emission level presents spatial heterogeneity. In view of the impact path of digital finance to reduce carbon emissions, this paper analyzes and verifies it from both theoretical and empirical aspects. Overall, these findings are helpful to guide and promote the development of digital finance, so that it can play a better role to achieve more social benefits, especially its contribution to environmental protection.