Evidence map›Paper›PMID 37819906›Full record

ArticlePloS one2023

Dose institutional quality influences the relationship between urbanization and CO2 emissions?

Hayat Khan, Tengpeng Chen, Robeena Bibi, Itbar Khan

RetractedOpen access · goldAbstract readRetracted Publication
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
3.4field-weighted citation impact, top 6% of its field
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, 6 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Hayat KhanSchool of Economics and Management, Zhejiang University of Science and Technology, Hangzhou, China.ORCID 0000-0001-6826-2187
Tengpeng ChenChina Center for Special Economic Zone Research, Shenzhen University, Shenzhen, China.
Robeena BibiSchool of Public Administration, Hohai University, Nanjing, China.
Itbar KhanCollege of Economics, Shenzhen University, Shenzhen, China.ORCID 0000-0001-9741-2236
Shenzhen University · CNHohai University · CNZhejiang University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a result of rapid economic expansion, increased energy use, and urbanization, global warming and climate change have become serious challenges in recent decades. Institutional quality can be the remedy to impede the harmful effect of factors on environmental quality. This study investigates the impact that urbanization and institutional quality on environmental quality in in the Belt and Road Initiative (BRI) countries from 2002 to 2019. By using two step generalized method of moment, the findings shows that urbanization leads to an increase in carbon dioxide emissions and a decline in environmental quality. On the other hand, the square term of urbanization indicates that an increase in urbanization leads to a reduction in emissions at a later stage after reach a certain level. Education, on the other hand, has the reverse impact of increasing carbon emissions; economic growth, foreign direct investment, and government effectiveness all boost carbon emissions. In a similar vein, the interaction between urbanization and the effectiveness of the government is unfavorable, underscoring the transformative role that the effectiveness of the government plays in leading to environmental sustainability. Finally, the findings of this study have considerable policy implication for the sample countries.

Indexed as

Carbon DioxideUrbanizationEconomic DevelopmentGlobal WarmingInternationalityInvestmentsCarbon Dioxide

Identifiers

PMID37819906
PMCPMC10566697
OpenAlexW4387542027

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.