Evidence map›Paper›PMID 31965503›Full record

ArticleEnvironmental science and pollution research international2020

Testing environmental Kuznets curve hypothesis in the presence of green revolution: a cointegration analysis for Pakistan.

Arif Ullah, Dilawar Khan

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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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
7.9field-weighted citation impact, top 3% of its field
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

6 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
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  5. Management of green economy in China and India: dynamics of poverty and policy drivers.Environmental 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

2 authors at 2 institutions in 1 country.

Arif UllahDepartment of Economics, Preston University Kohat Campus, Kohat, 26000, Pakistan.
Dilawar KhanDepartment of Economics, Kohat University of Science & Technology, Kohat, 26000, Pakistan. dilawarmkd@yahoo.com.
Kohat University of Science and Technology · PKPreston University · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, it has been observed that ecological and environmental condition of Pakistan is going worse due to greenhouse gases emissions. Therefore, an immediate response is necessary to mitigate the high impact of these gases. We employed modern time series econometric models to examine the association between green revolution and carbon dioxide emission in Pakistan spanning the time period of 1972-2014. These modern econometrics techniques encompassing of Johansen cointegration, ARDL bounds testing approach and its diagnostics statistics. Evidence of the Johansen model shows significant long-run cointegration between the green revolution and carbon dioxide emission in Pakistan. Results of the ARDL model show that a 1% increase in area irrigated, agricultural tractors and fertilizer used will increase carbon dioxide emissions by 0.35, 0.33 and 0.32%, respectively. Moreover, an inverted U-shaped relation was found between crops production and carbon dioxide emission both in the short and long-run. This relationship indicates that environmental Kuznets curve hypothesis validation prevailed in the presence of green revolution. The ARDL model credibility, stability and reliability were found correct based on the diagnostic statistics. The findings of variance decomposition analysis revealed that the green revolution in Pakistan significantly causes carbon dioxide emissions.

Indexed as

Economic DevelopmentGreenhouse GasesCarbon DioxidePakistanReproducibility of ResultsCarbon DioxideGreenhouse GasesARDLEnvironmental Kuznets curveGreen revolutionPakistan

Identifiers

PMID31965503
OpenAlexW3001628056

What OpenQuestion holds

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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.