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Record W4388564011 · doi:10.32479/ijeep.14505

Renewable Energy Consumption Convergence in G-7 Countries

2023· article· en· W4388564011 on OpenAlexaboutno aff
Mohamad Husam Helmi, Abdurrahman Nazif Çatık, Nuran COŞKUN, Esra Ballı, Çiler SİGEZE

Bibliographic record

VenueInternational Journal of Energy Economics and Policy · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyUnit rootEnergy consumptionConvergence (economics)Consumption (sociology)Unit (ring theory)EconomicsSustainable developmentNatural resource economicsEnvironmental economicsEconometricsEconomic growthEngineering

Abstract

fetched live from OpenAlex

This study examines the convergence of renewable energy consumption in G-7 countries. We employ LM unit root and RALS version of LM unit root tests with endogenously determined with structural one or two breaks. Despite the increase in renewable energy consumption in G-7 countries, it is important to identify whether renewable energy consumption converges across these countries to formulate appropriate policies to support sustainable energy consumption and reduce CO2 emissions. Our analysis indicated that Germany, Italy, and Canada exhibit evidence of convergence. However, after employing both the LM and RALS versions of the LM unit root tests, which consider level shifts with one or two breaks or trend shifts with one or two breaks, we found that there is no evidence of convergence for France, Japan, and the United Kingdom. Overall, our results highlight the importance of formulating country-specific policies to support renewable energy consumption and reduce CO2 emissions. Policymakers need to identify the drivers of renewable energy consumption and adopt appropriate measures to ensure that the countries can meet their climate goals while also ensuring energy security.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.239
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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