AgriStability with Catastrophic Price Risk for Cow‐Calf Producers
Bibliographic record
Abstract
AgriStability is the primary Canadian agricultural risk management program. Recent experience with bovine spongiform encephalopathy (BSE) in the cattle sector demonstrated that output prices are susceptible to both “normal” risk and sudden, “catastrophic” declines. This paper evaluates the AgriStability program for cow‐calf producers when there is potential for catastrophic price risk. A simulation model is developed. Under a base case scenario, when there is no catastrophic price risk, AgriStability behaves more like an income support program than a risk management tool. Risk‐neutral producers see a 12.1% increase in certainty equivalent wealth compared to 12.5% for moderately risk‐averse producers. Introducing catastrophic price risk increases risk‐averse producers’ expected benefits to 21.8%. Actuarially fair program premiums and implied subsidies are also estimated. These results demonstrate that AgriStability is highly subsidized. Finally, benefits from supplementary catastrophic revenue insurance are calculated and discussed, along with several additional structural features of the program . Agri‐stabilité constitue le principal programme canadien de gestion des risques en agriculture. L'encéphalopathie spongiforme bovine qui a frappé le secteur de l’élevage bovin a démontré que les prix des extrants sont exposés à des risques « normaux » et à des chutes soudaines et « catastrophiques ». Le présent article évalue le programme Agri‐stabilité dans le cas des producteurs vache‐veau (veaux d’embouche) lorsqu’un potentiel de risque de prix catastrophique existe. Nous avons élaboré un modèle de simulation. Dans le cadre d’un scénario de référence, lorsqu’il n’existe pas de risque de prix catastrophique, le programme Agri‐stabilité ressemble davantage à un programme de soutien du revenu qu’à un outil de gestion des risques. Dans le cas des producteurs indifférents aux risques, l’équivalent certain de la richesse aléatoire est supérieur de 12,1 % comparativement à 12,5 % dans le cas des producteurs modérément risquophobes. L'introduction de risque de prix catastrophique augmente les bénéfices espérés des producteurs risquophobes de 21,8 %. Nous avons également estimé ce que représentent les indemnités actuariellement justes ainsi que les subventions implicites. Les résultats ont montré que le programme Agri‐stabilité est très subventionné. Finalement, nous avons examiné et calculé les indemnités tirées d’une assurance‐revenu supplémentaire en cas de risque catastrophique et nous avons aussi analysé plusieurs autres caractéristiques structurelles du programme .
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 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".