Evidence map›Paper›PMID 36507092›Full record

ArticleResources policy2023

The role of foreign trade and technology innovation on economic recovery in China: The mediating role of natural resources development.

Mohammad Maruf Hasan, Fang Du

Open access · greenAbstract read
In one paragraph

Article in Resources policy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
11.5field-weighted citation impact, top 2% 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

2 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
  2. Article
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.

Mohammad Maruf HasanSchool of International Studies, Sichuan University, Chengdu, Sichuan, 610065, PR China.
Fang DuSchool of International Studies, Sichuan University, Chengdu, Sichuan, 610065, PR China.
Sichuan International Studies University · CNSichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease (COVID-19) has caused the most recent global economic collapse, which severely impacted worldwide economic operations. Natural resource volatility significantly affects global economic recovery. Therefore, the study aims to determine the significance of natural resource volatility, foreign trade, technological innovation, urbanisation, and investment in energy resources on the economic recovery of Chinese provinces. A total of 30 provinces in China were examined between 1995 and 2020. The generalised method of movement (GMM) technique was used to demonstrate that investments in energy sector resources, international commerce, and technological innovation are inconsistent than gross domestic product (GDP) and natural resources. The results demonstrated how trade blocs limit the effect of natural resources on regional economic development in the central provinces. Specifically, 33.4% of energy was saved while 35.2% of emissions were reduced. Although abundant natural resources significantly influence economic growth, studies discovered a negative impact on urbanisation. Nonetheless, the positive effects of trade openness outweighed those of economic recovery. The study proposed stabilising the fluctuating costs of natural resources, encouraging green financing, and increasing investment in energy resources. The findings also provided a novel strategy for achieving high economic growth and recovery.

Indexed as

Ecological footprintEconomic recoveryForeign tradeNatural resources volatilityTechnology innovation

Identifiers

PMID36507092
PMCPMC9718377
OpenAlexW4310665149

What OpenQuestion holds

Textmetadata
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.