The Link between Economic Growth and Sustainable Energy in G7-Countries and E7-Countries: Evidence from a Dynamic Panel Threshold Model
Bibliographic record
Abstract
The available literature on sustainable energy use and economic growth nexus yields conflicting conclusions, as the effect can be positive, negative, or insignificant. This research explores the causal link between sustainable energy use and economic growth in G7-countries (Japan, Canada, Germany, Italy, France, United Kingdom, and United States) and E7-countries (Russia, Brazil, Indonesia, China, Mexico, India, and Turkey) countries from 1990 to 2019. We discover that sustainable energy use and economic growth are proportional. Our results show that sustainable energy use positively affects economic growth if E7-countries exceed a specific threshold. It is detrimental to economic growth for the E7 countries' sustainable energy use to fall below a certain threshold. The use of sustainable energy has no significant impact on economic growth, although it does have a positive and noticeable impact in the G7 countries. In order for the countries of the G7 to see positive economic growth as a result of their investment in renewable energy, it is necessary for those nations to surpass a certain threshold in terms of their use of sustainable energy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".