Regional‐Level Analysis of Oligopsony Power in the Ukrainian Dairy Industry
Bibliographic record
Abstract
Transition was characterized by massive structural changes in most economic sectors in Ukraine. This is especially true for the dairy sector. Several countervailing developments took place under transition that affected the dairy industry. Interregional trade became feasible, the importance of milk delivered by households increased significantly, and most dairies became investor‐owned companies. The latter point and the fact that the Antimonopoly Committee of Ukraine detected several price cartels in the industry lead us to offer that after transition, dairies were able to exercise oligopsony power toward dairy producers at the regional level. This paper estimates market structure models for raw milk in Ukraine using a translog production function for the processing sector at the national and regional level. The results suggest the existence of oligopsony power in three of 25 administrative regions in Ukraine, coupled with a potential deviation of procurement prices for raw milk from the value marginal product of raw milk ranging from 24.6% to 49.4%.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".