The impact of green bond issuance on carbon emission intensity and path analysis
Introduction and literature review The issue of green bonds has garnered increasing attention worldwide as a result of the pressing need to reduce carbon emissions and mitigate the negative impacts of greenhouse gases. The majority of studies on the subject have focused on the pricing of green bond issuance, return risk, and financing costs. However, the impact of green bond issuance on carbon emission intensity has received comparatively little attention. This subject has gained significance as reducing carbon emission intensity is essential for achieving sustainable development. This paper uses the spatial Durbin model to conduct an empirical analysis using data from 26 provinces in China between 2016 and 2021. The results show that an increase in the issuance of green bonds is associated with a reduction in carbon emission intensity. This effect is stronger in less economically developed regions than in economically developed regions. The analysis of mediated transmission suggests that green bonds can reduce carbon emission intensity by changing the energy consumption structure or improving the efficiency of green technology innovation.
Introduction The urgent need to reduce carbon emissions and address the detrimental effects of greenhouse gases has made the issue of green bonds a topic of increasing attention worldwide. Previous studies on the topic have primarily focused on the pricing of green bond issuances, return risk, and financing costs. However, the effect of green bond issuance on carbon emission intensity has received less attention. This topic is crucial given the importance of reducing carbon emission intensity for achieving sustainable development. This paper uses the spatial Durbin model to analyze data from 26 provinces in China between 2016 and 2021 and draws empirical conclusions. The results show that an increase in green bond issuance is associated with a reduction in carbon emission intensity. This effect is more pronounced in less economically developed regions compared to economically developed regions. The analysis of mediated transmission suggests that green bonds can reduce carbon emission intensity by changing the energy consumption structure or improving the efficiency of green technology innovation.
Method This study used a spatial Durbin model to analyze the data, which considers the spatial autocorrelation between regions and allows for the identification of the direct and indirect effects of green bond issuance on carbon emission intensity. A total of 26 provinces in China were selected for this study, and the data covered the period from 2016 to 2021. The dependent variable was carbon emission intensity, while the independent variable was green bond issuance.
Results and discussion The results of this study show that an increase in green bond issuance is associated with a reduction in carbon emission intensity. This effect is stronger in less economically developed regions than in economically developed regions. The analysis of mediated transmission suggests that green bonds can reduce carbon emission intensity through changes in the energy consumption structure or improvements in the efficiency of green technology innovation.
Conclusion This study used a spatial Durbin model to analyze the impact of green bond issuance on carbon emission intensity in 26 provinces in China. The results showed a positive relationship between green bond issuance and a reduction in carbon emission intensity. This effect was found to be stronger in less economically developed regions compared to economically developed regions. The analysis of mediated transmission suggests that green bonds can reduce carbon emission intensity through changes in the energy consumption structure or improvements in the efficiency of green technology innovation. Additionally, this study has important implications for promoting green and low-carbon development and providing financing support for related projects in less economically developed regions.