Evidence map›Paper›PMID 39215117›Full record

ArticleScientific reports2024

Exploring impact of green finance and natural resources on eco-efficiency: case of China.

Xu Fang, Osamah Ibrahim Khalaf, Wu Guanglei, Juan Felipe Espinosa Cristia, Salwa Almasabi

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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
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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

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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

5 authors.

Xu FangSchool of Accounting, Hunan University of Finance and Economics, Changsha, China.
Osamah Ibrahim KhalafDepartment of Solar, Al-Nahrain Research Center for Renewable Energy, Al-Nahrain University, Jadriya, Baghdad, Iraq.
Wu GuangleiSchool of Accounting, Hunan University of Finance and Economics, Changsha, China. wuguanglei@hufe.edu.cn.
Juan Felipe Espinosa CristiaDepartamento de Ingeniería Comercial, Universidad Técnica Federico Santa María, 2390123, Valparaiso, Chile.
Salwa AlmasabiDepartment of Accounting, College of Business Administration, Princess Nourah Bint Abdulrahman University, P.O.Box 84428, 11671, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China ranks 160 out of 180 countries in terms of ecological efficiency, with an EPI score of 28.40 and a 10-year average change in score of 11.40. This article examines the impact of green finance and China's natural resources on regional ecological efficiency using the Tobit regression model. The study uses the average yearly exchange rate to normalize dollar-related values and GDP to 2012 RMB using the price deflator. Variables used as explanatory tools include green financing, the availability of natural resources, and regional eco-efficiency. The results of the study imply that natural resources in eastern region of China are better managed as and have avoided the resource curse as compared to central and western regions. Resources temporarily support area economic and social growth. However, resource agglomeration locks many elements in the resource industry and degrades regional industrial development, generating environmental and social difficulties that may hinder regional economic progress. Given that Foreign Direct Investment (FDI) increases regional eco-efficiency after accounting for adjustment. The FDI positively correlated with ecological efficiency in the east zone, while central and western zones have negative correlations. The industrial development of the nation negatively impacts ecological efficiency in the East, Midwest, and West regions. Western results are distinctive, with ecological efficiency and regional economic growth frequently going hand in hand.

Indexed as

Ecological efficiencyEconomic & social developmentFDIGreen finance

Identifiers

PMID39215117
PMCPMC11364548

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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.