Production Risk, Acreage Decisions and Implications for Revenue Insurance Programs
Bibliographic record
Abstract
Revenue insurance programs are an increasingly popular alternative to direct price supports or federal farm income support programs. Such insurance programs are likely to have effects on cropping patterns, particularly if coverage is not universal. These effects on cropping patterns in turn may have unintended environmental consequences. This paper explores the relationship between production risk, cropping patterns and revenue insurance programs. These relationships are first examined using mathematical and statistical models of acreage response. An empirical analysis of these relationships is then performed using economic and environmental data from 421 counties in the Corn Belt, which in turn is used in a simulation analysis to predict changes in crop acreage under two revenue insurance programs. The results confirm that revenue insurance will alter cropping patterns. The effects of these acreage changes are likely to involve environmental consequences, as the counties most prone to acreage shifts are also those with higher potential for environmental damage. Les programmes d'assurance du revenu gagnent de plus en plus en popularité en tant que solution de rechange aux mesures directes de soutien des prix ou aux programmes fédéraux de soutien du revenu agricole. Les programmes d'assurance de ce genre auront sans doute des répercussions sur les systémes de culture, surtout en l'absence d'une couverture universelle. Ces répercussions pourront avoir des conséquences inattendues sur l'environnement. Les auteurs examinent les liens qui existent entre les risques de production, les systémes de culture et les programmes d'assurance du revenu. Pour cela, ils recourent d'abord à des modéles mathématiques et statistiques afin d'étudier la variation de la superficie des cultures. Ils procèdent ensuite à une analyse empirique des mêmes liens à partir des données économiques et environnementales recueillies dans 421 comtés de la ceinture de culture du maïs, avant de s'en servir dans une simulation qui prévoit la variation de la superficie cultivée consécutivement à l'introduction de deux programmes d'assurance du revenu. Les résultats confirment que les programmes de ce genre modifieront les systémes de culture. La variation de la superficie cultivée devrait avoir des répercussions sur l'environnement, car les comtés où la superficie cultivée changera le plus probablement sont aussi ceux où les risques de pollution sont les plus grands.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".