Asymmetric threshold effects of economic growth on renewable energy in response to energy price fluctuations
Bibliographic record
Abstract
Using a panel smooth threshold regression to analyze data from 17 Middle East and North Africa (MENA) countries, this study investigates how asymmetries in energy price (EP) fluctuations impact renewable energy (RE) development, considering varying economic growth rates. The findings reveal that EP fluctuations influence RE development differently across income levels. In high-income countries, higher EPs stimulate RE expansion, while in low-income nations, they hinder it. These results support the substitution hypothesis, indicating that higher EPs encourage a shift toward alternative RE sources, though only within the high-GDP per capita regime in the MENA region. This evidence challenges the notion of a one-size-fits-all energy policy for MENA, highlighting the need for tailored strategies based on individual countries' economic contexts. High-income nations should prioritize subsidy removal to incentivize RE investments, whereas low-income countries require phased approaches to maintain economic stability. The study's broader implications extend to global energy policy, advocating for differentiated strategies that balance sustainable energy transitions with economic growth. • Energy price fluctuations impact renewable energy differently across MENA income levels. • High-income countries experience increased renewable energy investment with rising energy prices. • In low-income countries, higher energy prices hinder renewable energy development. • Findings support differentiated energy policies rather than a one-size-fits-all approach. • Results align with SDGs 7 and 13, advocating tailored sustainability policies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.011 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".