Testing the relationships between energy consumption and income in G7 countries with nonlinear causality tests
Bibliographic record
Abstract
Knowing the real causal links between energy consumption and national income is crucial for policy decision making. In this article, we address this issue for the G7 countries by using two nonlinear causality tests in the sense of Hiemstra and Jones (1994), and Kyrtsou and Labys (2006). Our results reveal some new, but mixed results. Hiemstra–Jones test indicates unidirectional causality running from energy consumption to GDP for the United Kingdom, while a bidirectional causality between energy consumption and GDP is found for Canada, France, Japan and United States. On the other hand, Kyrtsou–Labys test shows that a unidirectional causality runs from energy consumption to GDP for France and the United States, and from GDP to energy consumption for Germany. Overall, our findings suggest that policy implications of the energy-GDP links should be interpreted with caution, given the test-dependent and country-specific results.
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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 | 0.009 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".