Evidence map›Paper›PMID 42402089›Full record

ArticleCarbon balance and management2026

Can better institutions drive cleaner energy in the United States? insights from wavelet quantile regression.

Qingzi Gu, Babatunde Sunday Eweade, Cathrine Banga, Mohamed Djafar Henni

Abstract read
In one paragraph

Article in Carbon balance and management, 2026. 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
–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

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

4 authors.

Qingzi GuSchool of Public Administration (MPA Education Center), University of Water Resources and Electric Power, Zhengzhou, 450000, China.
Babatunde Sunday EweadeIrfan Suat Günsel Operational Research Institute, Near East University, Northern Cyprus, via Mersin 10, Nicosia, Turkey.
Cathrine BangaTourism and Hotel Management Department, Bahçeşehir Cyprus University, Northern Cyprus, via Mersin 10, Nicosia, 99200, Turkey. cathrine.banga@baucyprus.edu.tr.ORCID http://orcid.org/0000-0003-1153-8431
Mohamed Djafar HenniDepartment of Economics, College of Business, Islamic University of Madinah, Madinah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The transition to clean energy in the United States remains insufficient despite rising environmental concerns and increasing renewable energy adoption. This study investigates whether better institutional quality can effectively drive cleaner energy outcomes by examining the impact of governance alongside key macroeconomic factors. Using quarterly data from 1990 to 2024, the study employs a wavelet quantile regression approach to capture nonlinear and time-varying dynamics across short-, medium-, and long-run horizons. The findings reveal that economic growth, foreign direct investment, and trade openness positively influence renewable energy consumption, particularly over longer time horizons. In contrast, carbon emissions exhibit a negative relationship with renewable energy adoption. Surprisingly, institutional quality shows a predominantly negative effect, suggesting that stronger institutions may reinforce existing fossil fuel-based energy structures rather than accelerate transition. These results highlight the complexity of institutional roles in energy transformation and emphasize the need for targeted regulatory reforms to support renewable energy expansion in the United States.

Indexed as

Economic growthForeign direct investmentInstitutional qualityRenewable energyTrade opennessWavelet quantile regression

Identifiers

PMID42402089
PMCPMC13637300

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.