Acreage Response to Weather, Yield, and Price
Bibliographic record
Abstract
This paper examines the effect of weather on the distribution of yield and its subsequent impact on the acreage allocation decisions of crop farmers in Ontario. The mean and variance of yield are estimated for corn, soybeans, and winter wheat for eight counties in Ontario over a 26‐year period. The predicted parameters of the yield distribution are then used along with expectations on the distribution of crop price to estimate area response functions. A principal contribution of the paper is the decomposition of the revenue impact on crop area allocation into separate average and variance contributions for both price and yield. This decomposition illustrates the importance of expected yield in the area allocation decisions. Crop yield is especially influenced by the length of the growing season and this has a significant impact on acreage allocations. This implies that crop area will be altered in response to expected changes in climate, even without shifts in crop prices. Le présent article examine l'incidence des facteurs météorologiques sur la distribution des rendements et leurs conséquences sur les décisions des producteurs agricoles de l'Ontario concernant l'allocation des superficies cultivées. Nous avons estimé la moyenne et la variance des rendements pour le maïs, le soja et le blé d'automne cultivés dans huit comtés ontariens au cours d'une période de 26 ans. Les paramètres prédits de la distribution des rendements et l'espérance de la distribution du prix des cultures ont été utilisés pour estimer les fonctions de réponse par région. La décomposition de l'impact du revenu sur l'allocation des superficies cultivées en terme d'effets sur les moyennes et les variances des prix et des rendements constitue une importante contribution de l'article. Cette décomposition montre l'importance des rendements prévus dans les décisions d'allocation des superficies. Le rendement de culture est particulièrement influencé par la longueur de la saison de croissance qui a une incidence considérable sur l'allocation des superficies cultivées. Par conséquent, les superficies cultivées seront influencées par les changements climatiques prévus, et ce, même en l'absence de fluctuation du prix des cultures.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".