Evidence map›Paper›PMID 39102413›Full record

ArticlePloS one2024

The hidden costs of inflation: A critical analysis of industrial development and environmental consequences.

Dan Zheng, Abdullah Addas, Liaqat Ali Waseem, Syed Ali Asad Naqvi, Muneeb Ahmad, Kashif Sharif

Expression of concernErratum issuedAbstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It carries an expression of concern. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Dan ZhengSchool of Law, Southwestern University of Finance and Economics, Chengdu, China.
Abdullah AddasDepartment of Civil Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
Liaqat Ali WaseemDepartment of Geography, Government College University Faisalabad, Faisalabad, Punjab, Pakistan.
Syed Ali Asad NaqviDepartment of Geography, Government College University Faisalabad, Faisalabad, Punjab, Pakistan.
Muneeb AhmadDepartment of Finance, Riphah International University, Islamabad, Pakistan.ORCID 0000-0002-0606-0982
Kashif SharifDepartment of Statistics, University of Agriculture, Faisalabad, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study draws attention to the associations between monetary and economic elements and their potential environmental impacts. The study uses time series data from 1960 to 2022 to examine the connection between CO2 emissions, industrial growth, GNE, and inflation in China. The researchers utilized the well-known econometric technique of nonlinear autoregressive distributed lag (NARDL) to examine nonlinear correlations between these variables. The results reveal that GDP, inflation, and economic development influence long-term CO2 emissions. The strong positive correlation between gross national expenditures and economic activity increases CO2 emissions. In the short run, CO2 emissions are positively and statistically significantly affected by inflation. While inflation temporarily affects CO2 emissions, this effect dissipates with time. Industrial activity increases CO2 emissions, and China's fast industrialization has damaged the environment. The energy-intensive fertiliser manufacturing process and fossil fuels increase CO2 emissions. The research shows how government officials and academics may collaborate to create tailored measures to alleviate the environmental impacts of economic activity.

Indexed as

Carbon DioxideEnvironmentIndustrial DevelopmentChinaEconomic DevelopmentGross Domestic ProductInflation, EconomicCarbon Dioxide

Identifiers

PMID39102413
PMCPMC11299821

What OpenQuestion holds

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LicenceCC BY
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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.