Natural Resources, Financialization and Economic Growth: Empirical Evidence in a Global Sample
Why this work is in the frame
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Bibliographic record
Abstract
The nexus between natural resources and economic growth remains one of the great controversies in economic literature. The objective of this study is to examine this relationship by considering the role of financial development. We use data from 162 countries, covering the period from 1996 to 2017. The methodology is based on a long-run analysis and a nonlinear panel model exploring the non-linearity impact of natural resources and financialisation on economic growth, and threshold effects. The results of the estimates show a differentiated effect based on the level of development of countries: natural resource income negatively affects long-term growth in low-income countries, while it has no significant effect for high-income countries. Moreover, while the degree of financial development can mitigate the adverse effects of natural resources on growth, the phenomenon is non-linear in the sense that there are thresholds of financial development necessary to reverse the natural resource curse.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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