Exploring the Relationship Between Crop Rotations, Crop Insurance, Market Prices, and Crop Yields: Evidence from Three Studies in Saskatchewan
Notice bibliographique
Résumé
Crop rotations are one of the most important management decisions in western Canadian agriculture. Traditionally, farmers have used crop rotations to mitigate the risk of crop pests and diseases. In recent years, shorter crop rotations have garnered significant attention from economists, agronomists, and farmer-led organizations. The absence of sufficient non-experimental field-level evidence creates uncertainty regarding which factors are influencing these rotations and how they are affecting productivity. This doctoral dissertation comprises three studies that consider multiple aspects related to crop rotations. Using field-level data, these studies focus on the effects of high prices on crop rotations, the influence of these rotations on yields, and the implications of and for agricultural insurance. The first study examines the nexus between canola’s rising prices and crop choice, acreage, and rotations. Rotating out of canola in the Canadian prairies becomes less common when prices are rising. Some fields likely turn to shorter rotations expecting prices to stay high, while others maintain the same rotations. This study does two tasks for each soil zone in Saskatchewan based on field-level data taken from satellite imagery. One, it estimates determinants of crop choice under a dynamic crop choice model, and two, it estimates price elasticities of crop acreage and rotations. The results suggest that higher expected prices increase the probability of growing canola. Crop choice also depends on crops grown in past years, reflecting the use of rotations. After an expected price increase, the results suggest acreage gains and a tendency towards shorter rotations pushing for more canola production in Saskatchewan. The second study establishes how crop rotations impact wheat yields. The purpose is to estimate fixed effects models to determine the effects of previous crops grown on wheat yields. This study completes several tasks, with three of them taking precedence. One, it quantifies the effects of various crops grown in the past on wheat yields. Two, it establishes how far back in time previous crops grown help explain wheat yields. Three, it examines if previous crops grown have different effects across soil zones. The results suggest that the planting decisions made in the past four years can explain wheat yields. The planting of canola, oilseeds, or pulses relative to grains in the previous year results in a 11.7%, 9.5%, or 16.1% increase in wheat yields. The effects of previous crops grown differ based on the soil region. For instance, the canola effect is strong in the gray soil zone, increasing wheat yields by 14.0% relative to grains. The results convey that crop diversification is important to sustain wheat yields. The third study examines the impact of crop insurance on crop rotations. The focus is on AgriStability and AgriInsurance, two key business risk management (BRM) programs in Canada’s agricultural sector. These programs are included in the policy frameworks of Growing Forward and Growing Forward 2, and the Canadian Agricultural Partnership agreement. The main objective is to measure the profitability and expected utility of profits from crop rotations on a per acre basis, both with and without insurance. The analysis is for a representative farmer in Saskatchewan’s dark brown soil zone. Under risk-aversion, the results suggest that enrolling in a BRM program leads to shifts in expected utility, making both diversified and continuous crop rotations more profitable. Canola-durum wheat-canola-durum wheat and canola-durum wheat-lentils-spring wheat form highly desirable crop rotations, surpassing others in terms of expected utility.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,008 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».