Evidence map›Paper›PMID 36010706›Full record

ArticleEntropy (Basel, Switzerland)2022

The Spatial Heterogeneity Effect of Green Finance Development on Carbon Emissions.

Langang Feng, Shu Shang, Sufang An, Wenli Yang

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Langang FengGuizhou Key Laboratory of Big Data Statistics and Analysis, Guizhou University of Finance and Economics, Guiyang 550025, China.
Shu ShangSchool of Big Data Application and Economics, Guizhou University of Finance and Economics, Guiyang 550025, China.
Sufang AnCollege of Information and Engineering, Hebei GEO University, Shijiazhuang 050031, China.
Wenli YangSchool of Big Data Application and Economics, Guizhou University of Finance and Economics, Guiyang 550025, China.

Funding

the National Social Science Fund 17BJY076the Student Research Funding project of Guizhou University of Finance and Economics 2020ZXSY10
6 · The paper itself

Abstract

This paper uses the entropy method to estimate China's green financial development from four aspects, namely, green credit, green securities, green insurance, and green investment, based on the provincial-level panel data from 2008 to 2019. The spatial Durbin model (SDM) is adopted to estimate the spatial effect of green finance on carbon emissions. We then compare the heterogeneous effect in the South and North of China. The results show that China's green financial development can significantly reduce carbon emissions, and regional heterogeneities are obvious. In the South of China, this effect from local and adjacent regions is not significant, while on the whole, green finance can significantly reduce carbon emissions; but for Northern China, this effect is not significant; nationally, the development of green finance and carbon emissions in adjacent areas showed an inverted U-shaped relationship. China's green financial development and carbon emissions also showed an inverted U-shaped relationship. These results suggest that the effect of green finance development on carbon emissions exhibits substantial regional heterogeneity in China. Our paper provides some concrete empirical evidence for policymakers to formulate green financial policies to achieve the double carbon goal in China.

Indexed as

carbon emissionsentropy methodgreen financeheterogeneityspatial Durbin model

Identifiers

PMID36010706
PMCPMC9407523

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.