Evidence map›Paper›PMID 36768098›Full record

ArticleInternational journal of environmental research and public health2023

Can Digital Economy Development Contribute to the Low-Carbon Transition? Evidence from the City Level in China.

Bei Liu, Yukun Li, Xiaoya Tian, Lipeng Sun, Pishi Xiu

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2023. 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

5 authors.

Bei LiuSchool of Management, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.ORCID 0000-0001-9256-3182
Yukun LiBusiness School, Shandong Normal University, Jinan 250358, China.
Xiaoya TianSchool of Management, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.
Lipeng SunSchool of Management, Wenzhou Business College, Wenzhou 325035, China.
Pishi XiuSchool of Management, Wenzhou Business College, Wenzhou 325035, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a new engine to promote high-quality development and a sustainable economy, the digital economy (DE) plays a key role in achieving carbon reduction targets. In this paper, we use the "broadband China (BC)" policy as a proxy variable for the DE and employ the panel data of Chinese prefecture-level cities from 2006 to 2019 to investigate the effect of DE development on carbon emission intensity and its mechanism of action. It is found that (1) DE development significantly reduces the carbon emissions of cities and presents dynamic and sustainable characteristics; (2) the results of mechanism tests indicate that DE development is more inclined to reduce carbon emission intensity by improving regional innovation quality than by improving regional innovation quantity; (3) the impact of DE development on carbon emission intensity differs among cities with different characteristic attributes and different environmental regulation intensity, and the emission reduction effect is more obvious in non-resource-based cities, cities with lower environmental regulation intensity, and cities with weaker environmental target constraints; (4) the impact of DE development and innovation-driven development strategies on reducing carbon emission intensity has a policy linkage effect.

Indexed as

Air PollutionCarbonChinaCitiesEconomic DevelopmentCarbon“broadband China” strategycarbon emission intensitydigital economyinnovation qualitypolicy linkage

Identifiers

PMID36768098
PMCPMC9916021

What OpenQuestion holds

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Registered trials

None linked

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.