Green Subsidies in Agriculture: Estimating the Adoption Costs of Conservation Tillage from Observed Behavior.” Canadian
Bibliographic record
Abstract
Due to payoff uncertainties combined with risk aversion and/or real options, farmers may demand a premium in order to adopt conservation tillage practices, over and above the compensation for the expected profit losses (if any). We propose a method of directly estimating the financial incentives required for adopting conservation tillage and distinguishing between the expected payoff and premium of adoption based on the observed behavior. We find that the premium may play a significant role in farmers' adoption decisions. In an application to the state of Iowa, we find that if a uniform conservation tillage adoption subsidy program were offered in 1992, over 86% of the subsidy program payments would be an income transfer to existing and low‐cost adopters. En raison des incertitudes quant aux gains, combinées à l'aversion pour le risque et/ou aux options réelles, les agriculteurs pourraient réclamer une prime pour l'adoption de méthodes culturales de conservation du sol, une prime qui serait supérieure à l'indemnisation offerte en cas de perte de gains prévue (s'il y a lieu). Nous avons proposé une méthode fondée sur le comportement observé qui permet une estimation directe des incitatifs financiers exigés pour adopter les méthodes culturales de conservation du sol et qui fait une distinction entre les gains prévus et la prime d'adoption. Nous avons constaté qu'une prime pourrait influencer considérablement les décisions des agriculteurs quant à l'adoption de méthodes culturales de conservation du sol. En Iowa par exemple, nous avons trouvé que, si un programme de subventions uniforme pour l'adoption de méthodes de conservation du sol avait été offert en 1992, plus de 86 p. 100 des paiements du programme de subvention aurait constitué un transfert de revenus aux adopteurs existants et à faibles coûts.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".