Trade implications of price discrimination in a domestic market
Bibliographic record
Abstract
Abstract This study examines how domestic price discrimination between fluid and manufacturing milk influences dairy trade. Two types of dairy models are used for the study. The first one is a stylized mathematical model which is used to explore the relative trade effects of domestic price discrimination accompanied with revenue pooling mechanism versus border measures in dairy product markets. The second one is a partial equilibrium, multiple‐region model of dairy policy and trade, which is used to see the empirical implication of domestic price discrimination for six major dairy producers. The analytical results identify the trading status as the key to determine the relative trade effects. While domestic price discrimination is always less trade distorting than border measures in a net‐importer case, the relative trade distortiveness depends on the export volume in a net exporter case. The theoretical possibility that domestic price discrimination is more trade distorting than border measures is found when the ratio of dairy export to domestic manufacturing milk consumption is very high. The results also indicate that while the both support measures increase dairy export, domestic price discrimination may place greater economic burden on fluid milk consumers and less economic burden on tax payers than border measures. In addition, the results imply that domestic price discrimination schemes can be effective trade protective measures for Canada, Japan and the United States, where the schemes are currently being implemented. © 2010 Wiley Periodicals, Inc.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".