Green Credit and Regional Carbon Emissions:Taking into Account the Regulatory Role of Urbanization and Informatization
To realize the new type of urbanization and informatization has been included in the overall goal of China's development in 2035.Clarifying the mechanism of green credit's impact on carbon emissions and the role of urbanization and informatization in this mechanism is of great significance for realizing the"double carbon goal".Based on the panel data of 31 provincial levels in China from 2003 to 2021,the fixed-effect model is used to study the impact of green credit on carbon emissions,and the mediation effect model and regulatory effect model are combined to explore the channels and regulatory effects.The results show that:First,the issuance of green credit can significantly curb carbon emissions,and this conclusion can still pass a series of robust verification after alleviating endogenous problems.Second,the establishment of green finance reform and innovation pilot zone can enhance the inhibition effect of green credit on carbon emissions;Compared with large energy provinces,green credit in non-energy provinces has a more significant effect on curbing carbon emissions.Third,green credit can inhibit carbon emissions by reducing energy intensity,but it cannot temporarily inhibit carbon emissions by optimizing energy structure.Fourth,urbanization level plays a negative regulating role in the mechanism of green credit to curb carbon emissions,while informatization level plays a positive regulating role in the mechanism of green credit to curb carbon emissions.According to the above research conclusions,the author puts forward the suggestions of continuously increasing the support for green credit,insisting on the first trial in key regions,vigorously developing clean coal technology,promoting the new urbanization strategy,improving the quality of urbanization and developing information and communication technology.
green creditregional carbon emissionenergy intensityurbanizationinformatization
NETL
NSTL
万方数据
