Evidence map›Paper›PMID 32666445›Full record

ArticleEnvironmental science and pollution research international2020

Dynamic connection between inward foreign direct investment, renewable energy, economic growth and carbon emission in China: evidence from partial and multiple wavelet coherence.

Hira Arain, Arshian Sharif, Bilal Akbar, Md Yamin Younis

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Article in Environmental science and pollution research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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  7. Modeling COEnvironmental science and pollution research international · 2021
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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

4 authors.

Hira ArainDepartment of Finance, School of Economics & Management, Beihang University (BUAA), Beijing, China. arainhira400@gmail.com.
Arshian SharifOthman Yeop Abdullah graduate school of business, Universiti Utara Malaysia, Kedah, Malaysia.
Bilal AkbarDepartment of Mechanical Engineering, Mirpur University of Science and Technology (MUST), Mirpur-10250, (AJK), Pakistan.
Md Yamin YounisDepartment of Mechanical Engineering, Mirpur University of Science and Technology (MUST), Mirpur-10250, (AJK), Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents a fresh understanding of the vigorous connection between inward FDI, renewable energy consumption, economic growth and carbon emission in the Chinese economy employing novel Morlet wavelet analysis. Wavelet correlation, continuous wavelet transform and partial and the multiple wavelet coherence analyses are applied on variables under study for data acquired during the period 1979 to 2017. The outcome of these analyses reveals that the connections among the variables progress over frequency and time. From the frequency domain point of view, the current study discovers noteworthy wavelet coherence and robust lead and lag linkages, although time domain reveals inconsistent associations among the considered variables. The wavelet analysis according to economic point of view supports that inward foreign direct investment (FDI) and renewable energy consumption help to enhance economic condition in Chinese economy. The results also suggested that inward FDI enhances the environmental degradation in medium and long run in China. The results emphasize the significance of having organized strategies by the policymakers to cope with huge environmental degradation occurred for a couple of decades in China.

Indexed as

CarbonEconomic DevelopmentCarbon DioxideChinaInvestmentsRenewable EnergyCarbonCarbon DioxideCarbon emissionChinaInward foreign direct investmentPartial and multiple wavelet coherenceRenewable energy

Identifiers

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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.