Farm Return and Land Price Effects from Environmental Standards and Stocking Density Restrictions. Agricultural and Resource Economics Review 33(2
Bibliographic record
Abstract
This study assesses the economic and environmental effects to hog finishing farms from residual taxes/standards and restrictions on manure application and stocking density. Economic effects are measured in terms of net farm income and land prices, while levels of ammonia and excess nitrogen and phosphorus proxy the environmental effects. Any environmental policy requiring the need for additional land comes at a small cost to farmers who have access to adequate neighboring land. If this is not the case, then manure application and stocking density restrictions are expensive since the producer is basically forced to either purchase land or reduce hog production levels. Key Words: land value, manure application restrictions, stocking density Public concerns over the environmental consequen-ces of livestock production and the concentration of that production in larger farm units has led to more numerous, and increasingly more stringent, regu-lations on farm practices. These regulations have evolved from simple ex ante restrictions, such as minimum separation distances of new barns from waterways, to ex post controls or incentives on man-agement practices. Although there is a geographical disparity in the extent of the legislation among countries and jurisdictions (Beghin and Metcalfe, 2000), nutrient management standards and/or stock-ing density restrictions are becoming part of the regulatory constraints facing livestock farmers. For example, confined animal feeding operations (CAFOs) in the United States will not be able to spread manure at a rate greater than the crop nutrient demands. Similarly, many Canadian livestock farmers will be required to have in place a nutrient management plan (NMP) that includes a verification
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".