Evidence map›Paper›PMID 40246967›Full record

ArticleScientific reports2025

Green credit and enterprises' carbon emission intensity: empirical data from Chinese microenterprises.

Xiaoyun Zhang, Xiaorong Xie, Jin Xiao, Yuanyuan Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Xiaoyun ZhangDepartment of Economics and Finance, Xi'an International Studies University, Xi'an, Shaanxi, People's Republic of China.
Xiaorong XieDepartment of Economics and Finance, Xi'an International Studies University, Xi'an, Shaanxi, People's Republic of China.
Jin XiaoSchool of Economics, Jinan University, Guangzhou, Guangdong, People's Republic of China.
Yuanyuan WangDepartment of Economics and Finance, Xi'an International Studies University, Xi'an, Shaanxi, People's Republic of China. 1395288898@qq.com.

Funding

Ministry of Education 22YJC790008Science and Technology Department of Shaanxi Province 2024ZC-YBXM-192Xi'an International Studies University 23XWC01
6 · The paper itself

Abstract

This study empirically examined whether China's green credit policies could significantly reduce enterprises' carbon emission intensity. Constructing a difference-in-differences model, we utilized data from 1742 listed enterprises from 2003 to 2019 and the green credit guidelines issued in 2012 to perform a quasi-natural experiment. We found that (1) green credit can significantly reduce enterprise carbon emission intensity. (2) Green credit can significantly reduce the carbon emission intensity of enterprises at the macro level, through mechanisms such as industrial structure upgrading and energy efficiency improvement, and at the micro level, through mechanisms such as changing corporate business performance and reducing inefficient investment. (3) Enterprises with high social responsibility, low financing constraints, and low financial distress, as well as regions with high environmental regulatory intensity and high financial development, are prone to the inhibitory effect of green credit on corporate carbon emissions. Thus, implementing green credit policies in these areas would be effective. Based on these findings, specific recommendations are provided to promote a reduction in corporate carbon emissions.

Indexed as

Corporate carbon emission intensityEnergy efficiencyEnterprise business performanceGreen creditIndustrial structure upgradingNon-efficient investment

Identifiers

PMID40246967
PMCPMC12006435

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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.