What are the spatio-temporal differentiation characteristics and driving factors of the coupling coordination degree between green finance and ecological efficiency? Evidence from 84 cities in western China
Dalai Ma, Bitan An, Zuman Guo, Jiawei Zhang, Fengtai Zhang, Ruonan Chang, Yin Yan, Xiaoyong Zhou, Xiaoyong Zhou, Xiaoyong Zhou

TL;DR
This paper studies how green finance and ecological efficiency interact in 84 cities in western China from 2007 to 2021, identifying regional patterns and factors influencing their coordination.
Contribution
The study provides empirical evidence on the spatio-temporal differentiation and driving factors of green finance and ecological efficiency coordination in western China.
Findings
Green finance levels are rising but show significant regional disparities, with high-level areas shifting from northwest to southwest.
The coupling coordination degree between green finance and ecological efficiency is higher in the northwest than in the southwest.
Factors like industrial structure and technological progress positively influence coordination, while population size and government intervention have negative effects.
Abstract
Facilitating the coordinated and effective progress of green finance (GF) and ecological efficiency (EE) stands as a potent approach to support our nation in attaining sustainable development goals. This paper Utilized panel data encompassing 84 cities in Western China spanning from 2007 to 2021, this paper empirically analyzes the spatio-temporal characteristics and driving factors of the coupling coordination degree between green finance and ecological efficiency (CCD-GFEE) in western cities. The findings indicate that: (1) The level of GF demonstrates a rising trajectory, with significant regional disparities. Besides, the high level area progressively moves from the northwest to the southwest. (2) On the whole, urban EE demonstrates a relatively elevated level, but it still fails to reach DEA effectiveness. Compared to the northwest region, the southwest region has poorer…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Figure 18
Figure 19
Figure 20
Figure 21
Figure 22
Figure 23
Figure 24
Figure 25
Figure 26
Figure 27
Figure 28
Figure 29
Figure 30
Figure 31
Figure 32
Figure 33
Figure 34
Figure 35
Figure 36
Figure 37
Figure 38
Figure 39
Figure 40
Figure 41
Figure 42
Figure 43
Figure 44
Figure 45
Figure 46
Figure 47
Figure 48
Figure 49
Figure 50Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsEnergy, Environment, Economic Growth · Efficiency Analysis Using DEA · Sustainable Finance and Green Bonds
