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Geographic matching analysis between green finance development and carbon emissions in China’s new era of environmental transition
Green finance plays a pivotal role in driving sustainable development. While its effectiveness in promoting green development is well-established, the impact of regional heterogeneity on its outcomes warrants further investigation. By introducing the Spatial Durbin Model (SDM) model, we analyze the...
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Published in: | Research in international business and finance 2025-01, Vol.73, p.102581, Article 102581 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Green finance plays a pivotal role in driving sustainable development. While its effectiveness in promoting green development is well-established, the impact of regional heterogeneity on its outcomes warrants further investigation. By introducing the Spatial Durbin Model (SDM) model, we analyze the causal relationship between provincial carbon emissions and green finance development in China, accounting for spatial spillovers across provinces. A geographic mismatch between regions of green finance development and carbon emission concentration is revealed. Central and Western areas exhibit higher carbon emissions, indicating a greater need for targeted green finance initiatives to promote sustainable development. However, green finance growth in these areas remains sluggish. Moreover, carbon emissions hinder local green finance development and negatively impact neighboring regions. We present new insights into the influence of carbon emissions on green finance, highlighting the importance of inter-regional collaboration and the potential applicability to other countries facing similar challenges.
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•An obvious spatial correlation between green finance and carbon emissions is observed.•There is a mismatch in green finance development and emission concentration regions.•High emissions in an area will restrict its green finance as well as the surroundings.•We introduce network analysis to illustrate the provincial economic-geographical relations. |
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ISSN: | 0275-5319 |
DOI: | 10.1016/j.ribaf.2024.102581 |