Rule-Based Resource Revenue Stabilization Funds: A Welfare Comparison
Why this work is in the frame
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Bibliographic record
Abstract
Resource prices, and petroleum prices in particular, are volatile and difficult to predict, so government revenue in resource-producing regions is also uncertain and volatile. Adjusting government expenditure in response to these revenue movements involves economic, social and political costs. Many jurisdictions have established rule-based revenue stabilization funds to address revenue volatility, but there is little evidence on whether these funds improve welfare or if some fund designs increase welfare more than others. Using Monte Carlo techniques, we provide a quantitative welfare comparison of several types of rule-based stabilization funds for a petroleum-producing jurisdiction. We find large potential gains from the use of a fund to stabilize revenue, but some fund types reduce welfare, particularly those that accumulate large stocks of assets or debt. A fund that performs well, and is generally robust to changes in the simulation parameters, has a fixed deposit rate out of resource revenue and a fixed withdrawal rate out of assets.
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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) | 0.001 | 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