Renewable Energy Consumption, Income, CO2 Emissions and Oil Prices in G7 Countries: The Importance of Asymmetries
Bibliographic record
Abstract
This paper investigates the asymmetric transmission of income, carbon emissions and oil prices to renewable energy consumption for the long-run and short-run in G7 countries using quarterly data over the period from 1955Q1 to 2014Q4. We employ the nonlinear ARDL (NARDL) model to test for the long-run and short-run sensitivity of renewable energy consumption to its determinants. We find that income significantly influences renewable energy consumption in a symmetric manner in the long-run for the US, UK, France and Germany and in an asymmetric manner in Japan. However, renewable energy consumption is found to be insensitive to income in the long-run for Italy. Renewable energy consumption is positively and symmetrically affected by carbon emissions in the long-run for USA, France, Germany, Japan and Italy. Carbon emissions impact renewable energy consumption in an asymmetric manner for Canada but insignificant for the UK in the long-run. In the long-run, oil prices influence renewable energy consumption in an asymmetric manner in USA, symmetrically in the UK and France but insignificantly in Canada, Germany, Japan and Italy. Given the need to establish a global green energy environment our findings have important implications for energy policy makers in the world.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".