An Experimental Analysis of Modifications to the Centralized Milk Quota Exchange System in Quebec
Bibliographic record
Abstract
Using experimental economics, this paper tests the potential impacts of modifying the centralized quota exchange system in Quebec with the intent of decreasing the quota price while minimizing negative impacts on auction effectiveness. Two separate treatments are applied to a uniform price auction similar to that employed in Quebec. The first treatment is an exclusion (5% or 15%) of the highest buyer bids and seller offers. The second is a tax (2% or 10%) on all units offered for sale that remain unsold. Various combinations of the two treatments are also tested. The results suggest that exclusion of the highest bids and offers can decrease the price of the quota and that a 15% exclusion rate is more effective than a 5% rate. The tax alone has little impact on quota price. The combination of the two treatments generates a more marked reduction in both the number of exchanges and the price of the quota than when the tax or the exclusion is applied individually. However, the combination of treatments results in a greater loss of economic efficiency. In all cases, relatively small market price reductions are realized at the expense of substantial losses in economic efficiency. La présente étude teste de manière expérimentale la capacité d'une modification au système centralisé de vente du quota à faire diminuer le prix du quota laitier au Québec tout en minimisant les impacts négatifs des changements sur l'efficacité de l'enchère. Cette modification consiste à appliquer deux traitements sur l'enchère de prix uniforme où s'échange le quota. Le premier traitement consiste en une exclusion (5% ou 15%) des mises les plus élevées des acheteurs et des vendeurs. Le second traitement est une taxe (2% ou 10%) appliquée aux unités que les vendeurs mettent en marché et ne réussissent pas à vendre. Différentes combinaisons de ces deux traitements sont également testées. Les données générées permettent de conclure que le mécanisme d'exclusion des mises les plus élevées permet de faire diminuer le prix du quota, l'exclusion de 15%étant plus efficace que celle de 5%. Pour sa part, la taxe seule a peu d'impact sur le prix du quota tandis que la combinaison des deux traitements entraîne une diminution du nombre de transactions et du prix du quota plus marquée que lorsque les traitements de taxe et d'exclusion sont appliqués individuellement. Cela a comme corollaire d'entraîner une perte d'efficacitééconomique plus importante. Dans tous les cas, des baisses de prix de marché relativement modestes sont réalisées au coût d'importantes pertes d'efficacitééconomique.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".