A Note on the Empirical Relation between Oil Prices and the Value of the Dollar
Bibliographic record
Abstract
This paper offers an empirical characterization of the relation between the international price of oil and exchange rates that is both useful and reliable. Our characterization is useful because it rests on information of asset prices that are determined in functioning asset markets. Our characterization is reliable because its maintained assumptions are not rejected by the data. Four features differentiate our work from previous analyses. First, our reliance on bilateral rates opens previously ignored financial arbitrage opportunities between oil prices and exchange rates. Second, our emphasis on statistical testing makes our characterization empirically reliable. Specifically, we use a vector-error correction modeling strategy in which both oil prices and exchange rates are endogenous. This framework allows testing for the existence of an arbitrage relation, for the direction of causality, for parameter constancy, for white noise residuals, and for forecast accuracy. Third our reliance on data through 2020 makes our analysis timely. Fourth, to emphasize the advantages of our approach, we compare our results to those derived for formulations relying on effective exchange-rate indexes.
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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 | 0.003 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".