Evidence map›Paper›PMID 37767489›Full record

ArticleHeliyon2023

Revisiting R&D intensity and CO2 emissions link in the USA using time varying granger causality test: 1870∼2020.

Hao-Wen Chang, Tsangyao Chang, Feiyun Xiang, Alexey Mikhaylov, Adriana Grigorescu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 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.

Hao-Wen ChangDepartment of Information Management and Finance, National Yang-Ming Chiao-Tung University, Hsinchu, Taiwan.
Tsangyao ChangDepartment of Finance, Feng Chia University, Taichung, Taiwan.
Feiyun XiangSchool of Mathematics and Information Science, Guangzhou University, Guangzhou Higher Education Mega Center No. 230, Guangzhou, PR China.
Alexey MikhaylovFinancial University Under the Government of the Russian Federation, Moscow, Russia.
Adriana GrigorescuNational University of Political Studies and Public Administration, Bucharest, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

R&D intensity, per capita GDP, and per capita CO2 emissions links in the USA over the period of 1870-2020 reflects the evolution of the economic development and technology for the environment benefit. Using Time varying Granger causality, the empirical results indicate both causal links between R&D intensity and per capita CO2 emissions and between per capita GDP and per capita CO2 emissions are time varying. In addition, R&D intensity significantly affects per capita CO2 emissions since 1975, and the per capita GDP significantly influences per capita CO2 emissions since 1978. That is, these findings not only in supportive of the EKC theory, but further disentangle the subtly linkages for the R&D intensity and CO2 emissions and the per capita GDP and CO2 emissions. Finally, the policy implication is that launch the new technical innovation and increase in R&D investment to maintain its sustainable economic growth are the best government strategy to reduce CO2 emissions in the USA.

Indexed as

Economic developmentEnvironment protectionGranger causality testInnovationPer capita CO2 emissionsPer capita GDPR&DTime-varying

Identifiers

PMID37767489
PMCPMC10520821

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.