The impact of COVID‐19 on price transmission and price volatility in the Canadian beef supply chain
Bibliographic record
Abstract
Abstract The COVID‐19 pandemic resulted in disruptions to the Canadian meat and livestock markets. While prices initially decreased, the shutdowns of beef packing plants led to a large reduction in the supply of beef and a corresponding increase in the wholesale price with ramifications along the entire supply chain. This study examines the effect of COVID‐19 on price transmission and price volatility in the Canadian beef supply chain using monthly farmgate, wholesale, and retail price data covering the period from July 2005 to February 2022. We find evidence indicating that COVID‐19 affected long‐run price transmission from farmgate and wholesale markets to the retail market. Specifically, we find that the pandemic resulted in a 94.42 and 81.48% decrease in price transmission from the farmgate and wholesale market, respectively, to the retail market, indicating that higher prices at the wholesale level were not being passed on to consumers to the same extent. In the short run, we find asymmetric price adjustments and both direct and indirect volatility spillovers among the three levels of markets, implying strong market interactions across the beef supply chain. Overall, our results suggest the resiliency of the Canadian beef sector to COVID‐19 shocks.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".