Evidence map›Paper›PMID 39480855›Full record

ArticlePloS one2024

The government's environmental attention and corporate green innovation: A threshold analysis and quantile regression approach.

Guoyan Huang, Xiao Li, Zhen Chu

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.

Guoyan HuangSchool of Finance and Business, Shanghai Normal University, Shanghai, China.ORCID 0000-0003-2056-050X
Xiao LiSchool of Finance and Business, Shanghai Normal University, Shanghai, China.ORCID 0000-0001-8999-7748
Zhen ChuSchool of Finance and Business, Shanghai Normal University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on an analysis of 643 listed firms in clean technology sectors, this study explores the nonlinear impact of the government's environmental attention (GEA) on firms' green innovation by exploiting threshold and quantile regression techniques on Stata 17. We show that a double threshold exists when the level of the GEA is 51 or 104, above which the positive impact of the GEA on green innovation in cleantech firms significantly diminishes. The results from the quantile regression further indicate that cleantech firms receive almost no benefits from the GEA at lower levels of green innovation. Thus, policy-makers designing environmental policies should consider that the marginal benefit of environmental attention on green innovation wanes beyond certain levels, especially for firms that lack sufficient enthusiasm for innovation.

Indexed as

GovernmentEnvironmentEnvironmental PolicyHumansInventionsRegression Analysis

Identifiers

PMID39480855
PMCPMC11527151

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.