Paper prepared for presentation at the 2001 AAEA–CAES Annual Meeting American Agricultural Economics Association and Canadian Agricultural Economics Society
Bibliographic record
Abstract
Agricultural policy support to farmers is being reconsidered in most industrialized countries. The adverse incentive structure of price support is generally considered to be inadequate. Income support schemes may therefore be preferable in view of externalities of agricultural production such as the development and maintenance of nature. A plethora of studies comprises estimates of the impact of a sustained future benefit stream (among other things through continued price and income support) on land prices. The empirical results of these studies vary considerably. We apply meta-analytical methods to identify the factors explaining this variation in capitalization of future benefits in agricultural land prices. The resultant information is of crucial importance given the current change from price support to income support in agricultural policymaking. The results of the meta-analysis show that there is considerable variation due to the way in which income is taken into account, and the way in which expectations of future benefits are operationalized. There is also evidence that a change from a mixed price and income support scheme to a system of income support will result in substantially lower capitalization in land values.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.424 | 0.086 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".