The Impact of Local Ethanol Production on the Corn Basis in Ontario
Bibliographic record
Abstract
This paper investigates the factors affecting the corn basis in Ontario with particular emphasis on the effect of ethanol production given the projected detrimental effect its expansion could have on the red meat sector. We estimate a location‐specific and panel vector error correction models (VECM) for seven elevators in Ontario from 2006 to 2013. We find a long‐run equilibrium relationship exists between the basis and factors affecting local supply and demand including ethanol capacity and that the direction of causality is from these factors to changes in corn price. A one‐time increase in ethanol capacity of 100 million liters is projected to increase the basis by approximately 30 cents per bushel within two years. However, the impact is insignificant for elevators located in the livestock‐intensive regions of the province. The demand for corn as livestock feed is a determinant of the local corn price for all elevators. The decline in the number of hogs and beef cattle along with the 50% increase in corn supply have resulted in the observed decline in the local corn price despite the significant increase in demand from ethanol. L'impact de la production locale d′éthanol sur le prix de base du maïs en Ontario Cet article cherche à comprendre les facteurs ayant un effet sur le prix de base du maïs en Ontario, en particulier sur les effets de la production d′éthanol étant donné les effets négatifs attendus sur le secteur de la viande rouge causés par son expansion. Nous estimons des modèles vectoriels à correction d'erreurs (MVCE) à emplacements précis et panel entre 2006 et 2013, pour 7 silos‐élévateurs en Ontario. Nous constatons une relation d′équilibre à long terme entre le prix de base et les facteurs ayant un effet sur l'offre et la demande locale incluant la capacité pour l′éthanol. Nous constatons aussi que le sens de la causalité passe de ces facteurs aux changements du prix du maïs. L'on s'attend à voir une augmentation d'environ 30 cents du prix de base du boisseau suivant l'augmentation unique de 100 millions de litres de la capacité d′éthanol. Par contre, l'impact est négligeable pour les silos‐élévateurs situés dans les régions d′élevage intensif de la province. La demande pour le maïs comme aliment pour le bétail est un facteur déterminant du prix local du maïs pour tous les silos‐élévateurs. Le déclin du porc et des bovins ainsi que l'augmentation de 50 % de l'offre de maïs ont mené à la diminution notée du prix du maïs local malgré l'augmentation significative de la demande pour l′éthanol.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".