Asymmetric role of energy sources on economic growth of Nigeria: Evidence from nonlinear approaches
Bibliographic record
Abstract
Abstract Nigeria has plentiful sources of renewable energies that are yet to be efficiently utilised, despite the country committing to net‐zero emissions by 2060, declared at the 26th United Nations Climate Change Conference in 2021, which necessitates lower consumption of fossil fuels. However, this commitment may divert the country from ending poverty as the main goal of sustainable development. This study seeks to identify the asymmetric effects of renewable and non‐renewable sources of energy used in electricity generation, along with CO2 emissions on the economic growth of Nigeria through asymmetric approaches. The findings indicate that Nigeria should mainly pursue policies concentrating on increased consumption of non‐renewable energies in the short run and more renewable energy in the long run to achieve higher economic growth. Furthermore, the long run causality results approving the only feedback relationship existing between renewable energy and economic growth, paves the way for Nigeria so that over the time the country will be able to significantly increase the share of renewable energy through which it can achieve a higher level of economic growth and approach its target of net‐zero emissions by 2060, both of which are the main goals of sustainable development.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.004 | 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".