The study of the impact of Carbon finance effect on carbon emissions in Beijing-Tianjin-Hebei region-based on logarithmic mean divisia index decomposition analysis

26Citations
Citations of this article
70Readers
Mendeley users who have this article in their library.

Abstract

The negative effects of global warming are becoming more and more serious. The fundamental way to prevent global warming is by reducing carbon dioxide emissions. Achieving this has become a key concern for all countries. The logarithmic mean divisia index model was constructed to decompose the total carbon emission increment. Carbon finance effect was divided into green credit effect and carbon trading effect to analyze the impact of carbon finance on carbon emissions. The results showed that the total carbon emission reduction value caused by green credit effect from 2010 to 2016 in the Beijing-Tianjin-Hebei region was 66193.96 million tons, and the added value of carbon emission caused by carbon trading effect was 80266.68 million tons. There are regional differences in the effects of carbon finance on carbon emissions in these regions. It can be concluded that to a certain extent, green credit can reduce carbon emissions, and carbon trading can increase carbon emissions. Using the gradual expansion of carbon finance trading and market mechanism of carbon finance to solve the problem of carbon emission can improve the efficiency of carbon emission reduction.

Cite

CITATION STYLE

APA

Li, L., Di Liu, Hou, J., Xu, D., & Chao, W. (2019). The study of the impact of Carbon finance effect on carbon emissions in Beijing-Tianjin-Hebei region-based on logarithmic mean divisia index decomposition analysis. Sustainability (Switzerland), 11(5). https://doi.org/10.3390/su11051465

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free