Granger Causality Analysis on Ghana’s Macro-Economic Performance and Oil Price Fluctuations
Bibliographic record
Abstract
Oil has had an exclusive position in the world’s economic system. It is an essential source of energy, an irreplaceable transport fuel, and a vital raw material in many manufacturing processes. Despite the incredible role oil plays in socio-economic development and most industrial activity, studies on oil price-economy relationship seems to have received little attention from the perspective of developing economies. Although a colossal volume of literature exist on oil prices effects on economic performance, majority of these studies are concentrated on rather developed markets. As Ghana continues her quest to grow into a middle-class economy, it is imperative to secure a reliable supply of energy largely from imports, which is vital for fueling economic growth and development. Consequently, guaranteeing the supply of this all-important resource brings verification of the interconnection between oil price fluctuations in the global market and Ghana macroeconomic performance. Considering the fact that most developing economies are oil dependent for economic growth and industrial productivity, a formal studies on oil price fluctuations and Ghana economy will better position policy makers in taking energy policy issues to address impacts of oil price fluctuations. Against this backdrop, we employ an empirical modelling technique using Granger Causality test to investigate the direction of causation between oil price fluctuations and the Ghanaian economy. The empirical findings of this study suggest that oil price variations have adverse impact on Ghana’s macroeconomic performance. We also observe that a uni-directional causality runs from oil price fluctuations to output and economic growth in Ghana. Thus, we recommend that policy action be formulated to expand and refurbish the nation’s refinery hub, thereby allowing for home production of finished crude oil products which drains the nation’s budget during periods of oil price spikes. Keywords : Oil price, Ghana, Granger Causality, Macroeconomy.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".