How strong is the causal relationship between globalization and energy consumption in developed economies? A country-specific time-series and panel analysis
Bibliographic record
Abstract
We examine the causal relationship between globalization, economic growth and energy consumption for 25 developed economies using both time series and panel data techniques for the period 1970–2014. Due to the presence of cross-sectional dependence in the panel (countries from Asia, North America, Western Europe and Oceania), we employ the cross-sectional augmented IPS test to ascertain unit root properties. The cointegration test results indicate the presence of a long-run association between globalization, economic growth and energy consumption. Long-run heterogeneous panel elasticities are estimated through the common correlated effects mean group estimator and the augmented mean group estimator. The empirical results reveal that, for most countries, globalization increases energy consumption. In the USA and UK, globalization is negatively correlated with energy consumption. The causality analysis indicates the presence of the globalization-driven energy consumption hypothesis. This empirical analysis suggests insightful policy guidelines for policy makers using globalization as an economic tool to utilize energy efficiently for sustainable economic development in the long run.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".