Evidence map›Paper›PMID 38394288›Full record

ArticlePloS one2024

Can the green credit guidelines effectively deter enterprise inefficient investment of innovation? -evidence from heavy polluting enterprises in China.

Chuanhua Song, Shengli Jiao, Zengjun Sun

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Chuanhua SongGraduate School, Namseoul University, Cheonan, South Korea.
Shengli JiaoGraduate School, Jeonju University, Jeonju, South Korea.
Zengjun SunGraduate School, Namseoul University, Cheonan, South Korea.ORCID 0009-0001-0765-5996

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The green credit policy serves as a crucial instrument for achieving the dual objectives of optimal resource allocation and green development. It plays a pivotal role in curbing inefficient investments in innovation by enterprises. This research employs the PSM-DID method to effectively explore the practical effects of the green credit policy on the innovation inefficiency investments of heavily polluting enterprises in China. Examining the impact from the perspectives of environmental regulation and financial constraints, the study utilizes panel data from listed companies on the Shanghai and Shenzhen A-shares markets spanning from 2010 to 2020. The following conclusions are drawn: (1) Green credit policy has proven effective in inhibiting the inefficient investment in innovation by heavily polluting enterprises when compared to non-heavily polluting enterprises. (2) Moreover, this effect is more pronounced in state-owned enterprises and regions with less financial development. (3) Mechanism testing reveals that the green credit policy can discourage corporate over-investment by influencing financing constraints and can alleviate under-investment through commercial credit.

Indexed as

InvestmentsPolicyChinaEnvironmental PolicyResource Allocation

Identifiers

PMID38394288
PMCPMC10890769

What OpenQuestion holds

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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.