Evidence map›Paper›PMID 33963996›Full record

ArticleEnvironmental science and pollution research international2021

Estimating the connection of information technology, foreign direct investment, trade, renewable energy and economic progress in Pakistan: evidence from ARDL approach and cointegrating regression analysis.

Abdul Rehman, Hengyun Ma, Munir Ahmad, Ilhan Ozturk, Cem Işık

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Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Historical trend and drivers of China's COEnvironment, development and sustainability · 2022
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  11. How COEnvironmental science and pollution research international · 2022
    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.

Abdul RehmanCollege of Economics and Management, Henan Agricultural University, Zhengzhou, 450002, China. abdrehman@henau.edu.cn.
Hengyun MaCollege of Economics and Management, Henan Agricultural University, Zhengzhou, 450002, China.
Munir AhmadSchool of Economics, Zhejiang University, Hangzhou, 310027, China.
Ilhan OzturkFaculty of Economics and Administrative Sciences, Cag University, 33800, Mersin, Turkey.
Cem IşıkFaculty of Tourism, Anadolu University, Eskişehir, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study aims to investigate the effects of information and communication technology, foreign direct investment, trade and renewable energy use with GDP growth in Pakistan using time series data ranging from 1985 to 2017. Stationarity of data was verified by using unit root tests including ADF and P-P, while an autoregressive distributed lag (ARDL) model was used to check the dynamic association amid prescribed variables with long- and short-run analysis. Furthermore, cointegrating regression analysis with FMOLS, DOLS and CCR was applied to validate the variables causality. The outcomes during long-run analysis show that ICTE, trade and renewable energy have constructive linkage to GDP growth, while foreign direct investment has adverse influence to GDP growth in Pakistan. Similarly, the outcomes from cointegrating regression technique exposed that all variables including foreign direct investment, ICTE and trade have positive and constructive association with GDP growth except renewable energy that causes the adverse association to GDP growth in Pakistan. On the basis of outcomes, we will discuss the policy recommendations.

Indexed as

Economic DevelopmentInformation TechnologyCarbon DioxidePakistanRegression AnalysisRenewable EnergyCarbon DioxideARDLEconomic growthEnergyForeign investmentInformation technologyTrade

Identifiers

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Textmetadata
Read underepoch 390

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.