Do Petroleum Price Asymmetries and Price Deregulation Cause Business Cycles in Ghana?
Bibliographic record
Abstract
Abstract In the context of volatilities in the international situations in recent times, studies regarding the complexities of oil price fluctuations have focussed on analysing the special fluctuation characteristics of oil prices in different historical perspectives. This study examines the extent to which petroleum price fluctuations under the petroleum price deregulation regime impact on business cycles in Ghana. The study uses the autoregressive distributed lag (ARDL) model with a quarterly data spanning from the first quarter of 2005 to the fourth quarter of 2022. Our empirical results show that price stability impacts positively on economic growth, both in the short and the long run, while foreign direct investment also has a positive effect on economic growth in the short run. Our findings are consistent with theory and empirical studies and contributes immensely to the discussions about price asymmetry and business cycles. Again, offers a nuanced perspective on how policy makers can enact policies that ensures efficient and effective deregulation and price stability.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".