Evidence map›Paper›PMID 34374013›Full record

ArticleEnvironmental science and pollution research international2022

Fiscal policy and environment: a long-run multivariate empirical analysis of ecological footprint in Pakistan.

Samia Zahra, Dilawar Khan, Muhammad Nouman

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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. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
6.8field-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

3 citing papers in PubMed, 31 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Samia ZahraHigher Education Archives and Libraries Department., Kohat, KP, Pakistan. samiazahra022@gmail.com.ORCID http://orcid.org/0000-0002-8832-053X
Dilawar KhanKohat University of Science and Technology, Kohat, Pakistan.
Muhammad NoumanKohat University of Science and Technology, Kohat, Pakistan.
Kohat University of Science and Technology · PKGovernment of Khyber Pakhtunkhwa · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ecological footprint attempts to quantify human impact on nature and its resources necessary to satisfy human needs. This research study explores the long-run implications of fiscal policy on the ecological footprint in Pakistan empirically, keeping different socio-economic factors into consideration. Per annum, time series data have been collected between 1976 and 2018, and the ARDL model is applied to investigate this long-run and short-run association. The conclusion of ARDL model shows that a 1% increase in public development expenditures, total population, GDP, and energy consumption increase 0.19, 2.17, 1.16, and 2.17% ecological footprint, respectively, in Pakistan between 1976 and 2018 vice versa. However, it is also derived that a 1% increase in public tax and non-tax revenue and current public expenditures (in health, education, and other social sectors) shrink 0.36 and 0.013% ecological footprint in the long run in Pakistan. For policy implications, these results focus on practical fiscal policy significance to achieve environmental targets in Pakistan, suggesting an increase in public current expenditures in public and social sectors and increasing public revenue by expanding the tax base, which will ultimately reduce ecological footprint in the long run in Pakistan.

Indexed as

Economic DevelopmentFiscal PolicyAnthropogenic EffectsCarbon DioxideHumansPakistanCarbon DioxideARDL modelEcological footprintFiscal policySocio-economic determinantsVariance decomposition analysis

Identifiers

PMID34374013
OpenAlexW3145400711

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.