Carbon Dioxide Emissions, Energy Consumption and Economic Growth: A Comparative Empirical Study of Selected Developed and Developing Countries. “The Role of Exergy”
Bibliographic record
Abstract
Diverse factors may have an impact in carbon dioxide (CO2) emissions; thus, three main contributors, energy consumption, gross domestic product (GDP) and an exergy indicator are examined in this work. This study explores the relationship between economic growth and energy consumption by means of the hypothesis postulated for the Environmental Kuznets Curve (EKC). Panel data for ten countries, from 1971 to 2014 have been studied. Despite a wide gamma of research on the EKC, the role of an exergy variable has not been tested to find the EKC; for this reason, exergy analysis is proposed. Exergy analyses were performed to propose an exergetic indicator as a control variable and a comparative empirical study is developed to study a multivariable framework with the aim to detect correlations between them. High correlation between CO2, GDP, energy consumption, energy intensity and trade openness are observed, on the other hand not statistically significant values for trade openness and energy intensity. The results do not support the EKC hypothesis, however exergy intensity opens the door for future research once it proves to be a useful control variable. Exergy provides opportunities to analyze and implement energy and environmental policies in these countries, with the possibility to link exergy efficiencies and the use of renewables.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".