Bibliographic record
Abstract
The system of supply management in the Canadian dairy sector requires that farmers acquire quota to produce milk. In Canada's largest dairy producing province, Quebec, a ceiling on the price of quotas has been in effect since 2007. Previous research established that the use of quota price ceilings create a new source of inefficiency in the Canadian dairy sector. An alternative method for lowering quota prices is to lower the rent from quotas through lowering the farm price of milk. I determine the magnitude of the decrease in the farm price of milk that would be required to reduce the valuation of Quebec dairy quotas to the current price ceiling of $25,000 per unit. Accomplishing this task requires modeling the implicit valuation of quotas during the price ceiling era. Starting from a dynamic model of the demand for quotas, I develop an econometric model to estimate producers' discount factor. Using my econometric results and the modeled equilibrium price, I estimate the price of dairy quotas over the period 1993-2010. In 2010, I estimate that dairy quotas in Quebec would have traded at a price of $31,955 in the absence of the price ceiling. My results indicate that lowering the valuation of quotas to $25,000 per unit would have required an 11.83% reduction in the farm price of milk.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".