Crude Oil Price and Aggregate Economic Activity: Asymmetric or Symmetric Relationship: Evidence from Canada’s Economy
Bibliographic record
Abstract
We represent an alternative time series technique to examine alternative asymmetry hypothesis based on the reliable vector Error Correction Model (ECM). We add up negative and/or positive and negative changes of crude oil prices in bivariate and multivariate ECM techniques among GDP, crude oil price, short-term interest rate, and aggregate implicit price deflator. This paper unlike the literature considers unit root and structural break tests for deciding whether co-integration and ECM techniques or VARs technique and innovation accounting tools would be used to explain the interaction of economic activities, oil price shocks, and other key economic variables. We apply this alternative method to Canada’s economy using quarterly data over the period (1984-2002). Our results suggest the long-term equilibrium relationship among GDP, the crude oil price, and other key economic variables. In contrast with the most literature, the results show that there is a significant portion of the symmetric and reversible response of Canada’s economy to the crude oil price changes in both bivariate and multivariate context over the study period. We find that this symmetric response is due to the symmetric relationship of the crude oil price with the short-term interest rate and the
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".