Do Structural Oil-Market Shocks Affect Stock Prices?
Bibliographic record
Abstract
This paper investigates how explicit structural shocks that characterize the endogenous character of oil price changes affect stock-market returns in a sample of eight countries --- Australia, Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States. For each country, the analysis proceeds in two steps. First, modifying the procedure of Kilian (2008a), we employ a vector error-correction or vector autoregressive model to decompose oil-price changes into three components: oil-supply shocks, global aggregate-demand shocks, and global oil-demand shocks. The last component relates to specific idiosyncratic features of the oil market, such as changes in the precautionary demand concerning the uncertainty about the availability of future oil supplies. Second, recovering the oil-supply shocks, global aggregate-demand shocks, and global oil-demand shocks from the first analysis, we then employ a vector autoregressive model to determine the effects of these structural shocks on the stock market returns in our sample of eight countries. We find that international stock market returns do not respond in a large way to oil market shocks. That is, the significant effects that exist prove small in magnitude.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".