How does green credit affect carbon emissions in China? A theoretical analysis framework and empirical study

• Published in: Environmental science and pollution research international Vol. 29; no. 39; pp. 59712 - 59726
• Main Authors: Hu, Yi, Zheng, Jiayu
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2022; Springer Nature B.V
• Subjects: Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Carbon; China; credit; Earth and Environmental Science; Ecotoxicology; Emission analysis; Emissions; Empirical analysis; empirical research; Energy; Environment; Environmental Chemistry; Environmental Health; Environmental science; Research Article; Theoretical analysis; threshold models; Waste Water Technology; Water Management; Water Pollution Control; China; Theoretical analysis framework; Green credit; Mediating effect model; Dynamic panel threshold model; Carbon emissions
• ISSN: 0944-1344; 1614-7499; 1614-7499
• DOI: 10.1007/s11356-022-20043-1

As an important part of China’s green finance, green credit is regarded as an important tool to promote China’s transformation to a low-carbon economy. In order to clarify the mechanism of green credit on carbon emissions, this paper puts forward a theoretical analysis framework including “functional attributes – micro subject response – key influencing factors” from the macro and micro perspectives. We select the panel data of 30 provinces in China from 2005 to 2019 for an empirical test and identify the action paths of green credit on carbon emission based on the mediating effect model. Further, we consider the special mechanism of “signal formation” and test it based on the dynamic panel threshold model. The results show that: (1) China’s green credit mainly inhibits carbon emissions through three paths: industrial structure, energy structure and energy intensity. (2) There is a signal formation mechanism for the impact of green credit on carbon emissions, which mainly acts on the two action paths of industrial structure and energy intensity. (3) The signal formation mechanism is heterogeneous in each province. According to the empirical results, we divide the provinces into three echelons and propose corresponding suggestions.