Classifying and modeling nonlinearity in commodity prices using Incoterms
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes a novel approach of classifying and modeling the nonlinear behavior of commodity prices using regime-switching models with exogenous transition variables. The approach rests on using the International Commercial Terms (Incoterms), also known as border prices, to classify commodities in groups that tend to display similar dynamics. The suggested border price classification is useful in identifying the key exogenous driving variables in each group. In particular, the classification suggests that inflation and oil price are the best transition candidates that are capable of capturing the nonlinear dynamics of free on board (FOB) and cost insurance and freight (CIF) prices respectively. Our statistical linearity tests and estimation results confirm this prediction and highlight the importance of the suggested border price classification in improving our understanding of the behavior of commodity prices.
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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