The Nexus Between Electricity Consumption, Economic Growth, and CO2 Emission: An Asymmetric Analysis Using Nonlinear ARDL and Nonparametric Causality Approach
Bibliographic record
Abstract
This article examines the asymmetric relationship between electric consumption, economic growth, and carbon dioxide emission in 15 countries over the period 1971–2014. We employed a nonlinear auto-regressive distribution Lag (NARDL) model approach to investigate the asymmetric cointegration between variables. Additionally, we applied the asymmetric causality approach to determine the causal relationship between variables. Results confirm nonlinear cointegration between variables in Cameroon, Congo Republic, Zambia, Canada, and the UK. The Wald test results confirm a long-run asymmetric link between electricity consumption, economic growth, and carbon emission in Canada and Cameroon, while a short-run asymmetric effect in the Congo Republic and the UK. Findings from the granger causality test are volatile across variables. The result provides strong support for the symmetric relationship between electric consumption, economic growth, and carbon emission in the short and long run. This study provides new evidence for policymakers to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".