Natural Resources Volatility and Economic Growth: Evidence from the Resource-Rich Region
Why this work is in the frame
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Bibliographic record
Abstract
This research paper investigates the impact of natural resources volatility on economic growth. The paper focused on three resource-rich economies, namely, UAE, Saudi Arabia, and Oman. Using data from 1970 to 2016 and employing the autoregressive distributed lag (ARDL) cointegration approach, we found that both natural resources and their volatility matter from the perspective of growth. The study found strong evidence in favor of a positive and statistically significant relationship between natural resources and economic growth for the economies of UAE and Saudi Arabia. Similarly, for the economy of Oman, a positive but insignificant relationship is observed between natural resources and economic growth. However, we found that the volatility of natural resources has a statistically significant negative impact on the economic growth of all three economies. This study contradicts the traditional concept of the resources curse and provides evidence of the resources curse in the form of a negative impact of volatility on economic growth.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it