Analysis of the optimal policy for managing strategic petroleum reserves under long-term uncertainty: The ASEAN case
Bibliographic record
Abstract
We examine the issue of petroleum stockpiling in the Association of Southeast Asian Nations (ASEAN), computing the optimal build-up and draw-down policies under different conditions. We study, in detail, the properties of petroleum prices, oil imports and production, and GDP, analyzing the impact of the planning horizon, discount rate and price elasticity of demand on the optimal policy. We use a finite horizon stochastic program (with varying branching) in which the policymaker minimizes the negative impacts of oil price increases on the GDP and the cost of holding the strategic petroleum reserve. We propose an inter-generational equity rule to compute the level of inventory in the final states of the decision tree. We find that ASEAN countries would benefit significantly from developing a strategic petroleum reserve, with net benefits ranging from US$25–125 billion. Our suggested target stockpile is consistent with the International Energy Agency’s recommendation of holding stocks equal to 90 days of net imports.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".