Evidence map›Paper›PMID 34414540›Full record

ArticleEnvironmental science and pollution research international2022

How FDI and technology innovation mitigate CO

Zhaocheng Wang, Lijuan Gao, Zixiang Wei, Abdul Majeed, Iqbal Alam

Erratum issuedAbstract read
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In one paragraph

Article in Environmental science and pollution research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Zhaocheng WangSchool of Software, Zhengzhou University, Zhengzhou, China.
Lijuan GaoYunNan Nuclear Industry Mining Group, Kunming, Yunnan, China.
Zixiang WeiIntellectual Property and Achievement Center, China Institute of Marine Technology and Economy, Beijing, China.
Abdul MajeedBusiness School, Huanggang Normal University, Huanggang, 438000, Hubei, China. abdulmajeed192@hotmail.com.ORCID http://orcid.org/0000-0001-5231-8756
Iqbal AlamNanyang Academy of Sciences (NASS), Nanyang, China. iqbalalam@nassg.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The high technology (high-tech) industry of China has gained a key strategic position in the Chinese economic goals. In this positioning, foreign direct investment (FDI) and technological innovation have emerged as strong pillars of the high-tech industry. However, there are growing concerns of carbon emission from this industry which is still debatable. In this context, this study measures the effect of FDI and technology innovation on carbon emissions in the high-tech industry from 28 provinces of China. The study uses the provincial data for China over the period 2000-2018. In addition to examining unit root properties, structural breaks, and cointegration, this study uses quantile regression for estimating long-run relationships among study variables. The findings reveal the negative impact of FDI on carbon emissions. Technology innovation positively impacts in the initial three quantiles, whereas negatively impacts in the next six quantiles. These results indicate that FDI and technology innovation have shaped the energy intensity in the high-tech industry, which causes fluctuation in carbon emissions over time. After controlling the effects of urbanization, energy intensity, and economic growth, this study recommends that policymakers should emphasize on the heterogeneous effects of FDI and technology-lead emissions at different quantiles during the process of CO

Indexed as

Carbon DioxideInventionsChinaEconomic DevelopmentInvestmentsTechnologyCarbon DioxideChinaForeign direct investmentHigh-tech industryTechnology innovation

Identifiers

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.