Minimum price policy impact in the Tunisian dairy sector
Bibliographic record
Abstract
Purpose The purpose of this paper is to develop a partial equilibrium model for the Tunisian dairy sector according to “quantity formulation” and “price formulation” and to show their equivalence under the assumption of perfect competition. Design/methodology/approach This model incorporates domestic policies, that is, producers' price support and subsidies to milk collection centres and trade policies, that is, TRQ and ad valorem tariffs. The authors illustrate theoretically and numerically how to incorporate the minimum price policy at the farm level for the Tunisian dairy sector according to the price formulation approach. Findings Two scenarios for the removal of a minimum price policy are analysed and show that producers' surplus loss varies between 78.6 and 127.8 million dinars. The overall welfare implications of removing a minimum price policy are negative and range between 13.3 and 18.2 million dinars. Research limitations/implications This study could not include all of the detailed factors in the Tunisian dairy sector. Originality/value Based on the numerical results obtained in the study, the authors recommend that public authorities maintain the minimum price policy because it prevents a decrease in raw milk producers' surplus. Moreover, this policy is effective because it generates excess raw milk production, estimated at 28.23% in 2010, that can be used for various homemade dairy products. Under an effective minimum price policy, the formal processing sector absorbs all the excess raw milk only if the public authorities allocate grants to encourage investment in new milk collection centres and in milk drying equipment, especially in disadvantaged rural regions. The latter economic policy coupled with a minimum price policy not only guarantees a higher income for raw milk producers but also may represent a development factor for underprivileged rural areas.
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 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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".