Price Volatility Spillovers in the Western Canadian Feed Barley, U.S. Corn, and Alberta Cattle Markets
Bibliographic record
Abstract
Abstract Price volatility complicates price discovery and creates risks for cattle producers. This paper analyzes volatility spillovers in the western Canadian beef cattle supply chain. A modified bivariate VAR‐BEKK‐GARCH model is used to examine spillovers and account for asymmetries associated with rising versus falling markets. The spillovers that are found are unidirectional from input to output markets. Spillovers tended to be stronger when cattle prices are depressed and feed costs are rising. Volatility transmission is also flows from feed barley to feeder cattle markets, but volatility does not flow in the opposite direction nor does it advance by more than one level in the supply chain. La volatilité des prix complique la découverte des prix et crée des risques pour les éleveurs de bétail. Cet article analyse les répercussions de la volatilité au sein de la chaîne d'approvisionnement des bovins d'élevage. Un modèle VAR‐BEKK‐GARCH modifié à deux variables sert à l'examen des répercussions et tient compte des asymétries associées aux marchés à la hausse et à la baisse. Les répercussions décelées sont unidirectionnelles du marché des intrants aux produits. Les répercussions semblent plus fortes lorsque les prix des bovins sont bas, et les coûts de fourrage à la hausse. Le transfert de la volatilité se fait aussi sentir de l'orge de fourrage aux marchés de bovins d'engraissement, mais l'inverse ne survient pas et elle ne progresse pas de plus d'un niveau dans la chaîne d'approvisionnement.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".