The Long Run Effects of Oil Prices on Economic Growth: The Case of Saudi Arabia
Bibliographic record
Abstract
This paper studies the long run effects of oil price growth rates (OS) on the economic growth of the Kingdom of Saudi Arabia (KSA). The empirical results of an ARDL model find a strong positive direct impact of OS on the GDP growth rates of KSA during the period 1995Q4-2015Q4. Despite the fact that China is the most important trading partner of KSA, OS doesn’t affect indirectly Saudi GDP growth rates. OS weakens the positive long run effect exercised on the GDP growth rates of KSA via trading with Japan. Although trading with South Korea and UK have negative significant effects on the Saudi GDP growth rates, OS has no possible indirect effect via trading with UK. But, it has a positive effect on the weighted GDP growth rates of S. Korea via trading with KSA. Trading with USA, India, Canada, France and Germany have no significant impacts on Saudi economy. Keywords: Saudi Arabia, Economic growth, Oil price effect, Autoregressive distributed lags model. JEL Classifications: O53, O40, C23
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".