Bibliographic record
Abstract
This paper employed a structural vector autoregression model in a quantitative assessment of the effect of exogenous shocks related to oil price determination on countriesʼ exchange rates and outputs. Because we were interested in the effect of oil price changes on energyexporters and importers, we chose Australia, Canada, Japan, Norway, and the UK as sample countries. This model comprised of four structural shocks :（i）oil supplyshocks,（ii）global demand shocks,（iii）oil price fluctuations that are not related to supplyand demand, and（iv）pure exchange rate fluctuations that are not related to other structural shocks. Various responses to structural shocks explain the correlation structure of the currencies. Moreover, pure exchange rate shocks are the main sources of exchange rate volatility.We also examined the role of structural shocks in explaining macro variables, taking Australia and Japan as examples. We thus discovered that global demand shocks and non-fundamental oil price fluctuations have a strong impact on GDP and export growth for both countries, while pure exchange rate shocks were relativelyunimportant in explaining Japanʼs macroeconomic variables.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".