Evidence map›Paper›PMID 34036495›Full record

ArticleEnvironmental science and pollution research international2021

Economic policy uncertainty and energy production in China.

Wei Wei, Haiqing Hu, Chun-Ping Chang

Abstract read
In one paragraph

Article in Environmental science and pollution research international, 2021. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Does policy uncertainty threaten renewable energy? Evidence from G7 countries.Environmental science and pollution research international · 2022
    Article
  3. 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

3 authors.

Wei WeiSchool of Economic and Management, Xi'an University of Technology, Xi'an, Shaanxi, China.
Haiqing HuSchool of Economic and Management, Xi'an University of Technology, Xi'an, Shaanxi, China.
Chun-Ping ChangShih Chien University, Kaohsiung Campus, Kaohsiung, Taiwan. cpchang@g2.usc.edu.tw.ORCID http://orcid.org/0000-0003-1782-4551

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Owing to economics are usually linked with energy production, economic policy may have an instantaneous adjustment according to the current monetary, financial, cultural circumstances. This research thus investigates the dynamic co-movement as well as cointegration relationships between economic policy uncertainty (EPU) and disparate energy productions, i.e., Chinese coal, natural gas, crude oil, electricity as well as renewable energy, during the period from January 1995 to October 2019 in China. We compare the two EPU indices and make empirical and robust analysis to get more evidence for the time-varying co-movement between energy production and EPU. The empirical results show that there are stationary properties and cointegration relationships between energy production and EPU. By utilizing wavelet co-movement analysis in the time-frequency domain, our results show a significant positive co-movement among disparate energy productions and EPU at high frequencies, i.e., in the short term, but weaker co-movement at low frequencies, i.e., in the long term. Hence, the phase-difference series are mostly around the zero line, implying the variables behave to the dynamics of the co-movement with positive causality. Policy recommendations are offered in accordance with our finding.

Indexed as

Economic DevelopmentRenewable EnergyCarbon DioxideChinaNatural GasUncertaintyCarbon DioxideNatural GasEconomic policy uncertainty;Energy production;Phase-difference;Time-frequency domainWavelet co-movement;

Identifiers

PMID34036495
PMCPMC8147580

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.