Evidence map›Paper›PMID 37876485›Full record

ArticleHeliyon2023

Industrialization, globalization, ICT, and environmental degradation in Malaysia: A frequency domain analysis.

Kizito Uyi Ehigiamusoe, Hooi Hooi Lean, Marina Mustapha, Suresh Ramakrishnan

Abstract read
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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Kizito Uyi EhigiamusoeTIFIES Research Group and Southampton Malaysia Business School, University of Southampton, Malaysia.
Hooi Hooi LeanEconomics Program, School of Social Sciences, Universiti Sains Malaysia, 11800, Gelugor, Penang, Malaysia.
Marina MustaphaSchool of Accounting and Finance, Taylor's University, Malaysia.
Suresh RamakrishnanFaculty of Management, Universiti Teknologi, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper examines the causal relationship between industrialization, globalization, information communication technology (ICT) and environmental degradation in Malaysia during 1970-2019. It uses two indicators of environmental degradation (carbon emissions and ecological footprint), three dimensions of globalization (political, social, and economic) and three indicators of ICT (users of internet, mobile cellular, and fixed telephone subscriptions). It utilizes Granger causality technique in frequency domain which differentiates between permanent and temporary causality, Vector Error Correction approach as well as Variance Decompositions. The bound test shows that the variables have cointegration relationship. It reveals joint long-run and short-run causality from industrialization, globalization, and ICT to carbon emissions, albeit the causality to ecological footprint is tenuous. It indicates that industrialization, globalization, and ICT significantly predict carbon emissions at high frequency than at low frequency. A substantial percentage of the forecast error variance in environmental degradation are explained by industrialization, globalization, and ICT. The robustness of the empirical outcomes is confirmed by the alternative proxies of the variables. Our study implies that industrialization, globalization, and ICT are determinants of environmental degradation. Therefore, policies to mitigate environmental problem should prioritize these variables to attain green economy.

Indexed as

Environmental degradationGlobalizationGreen economyICTIndustrialization

Identifiers

PMID37876485
PMCPMC10590859

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.