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Record W7018817256

Energy Consumption, Carbon Dioxide Emissions and Economic Growth: Empirical Results for Selected Developed Countries

2020· dissertation· en· W7018817256 on OpenAlexaboutno aff

Bibliographic record

VenueEastern Mediterranean University Institutional Repository (Eastern Mediterranean University) · 2020
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodTSG101HyporeflexiaArticular cartilage damageLiquationDiafiltration
DOInot available

Abstract

fetched live from OpenAlex

This research investigates the association between energy consumption, CO2 emissions and economic growth for the United States, Japan, Russia, Canada and Australia. It also estimates the impact of other macroeconomic fundamentals including inflation rate, investment rate and trade openness on economic growth. Multiple regression analysis is employed for annual data covering the timespan from 1989 to 2014. The empirical findings indicate that energy consumption has a positive and significant impact on economic growth of the selected countries. This means that energy is a critical factor in economic development. CO2 emissions, which is a proxy for fuel based energy use, has a destructive influence on the environment. Therefore, in this study, various policies have been suggested to reduce carbon dioxide emissions. In addition, the results show that positive association exist between investment rate, trade openness and output growth. However, inflation rate in all of the selected countries has a negative but insignificant impact on economic growth. Keywords: economic growth, energy consumption, CO2 emissions, inflation rate, investment rate, trade openness

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.880
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.037
GPT teacher head0.218
Teacher spread0.181 · 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.

Study designNot applicable
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

Citations0
Published2020
Admission routes1
Has abstractyes

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