Trade liberalization and inter-provincial dumping in a spatial equilibrium model: the case of the Canadian dairy industry
Bibliographic record
Abstract
The paper introduces imperfect competition in a spatial equilibrium model of provincial dairy markets to analyze the welfare impacts of trade liberalization. Our model accounts for output restrictions at the farm level and the potential presence of market power at the processing level. Our model builds on the reciprocal dumping model of Brander and Krugman (1983) because processing firms from different provinces compete with one another in several provinces. Simulations reveal that welfare in the Canadian dairy sector could increase by as much as $1 billion per year if aggressive tariff cuts were made while moderate liberalization plans would yield annual gains of $234.5 million. Even large producing provinces like Quebec and Ontario gain from trade liberalization. In comparison, a perfect competition model yields more modest welfare gains in the range of $15.6 million and $34.5 million. Finally, we show that the switch in the sign of the transport cost-welfare relation identified by Brander and Krugman (1983) occurs at transport costs that are too high to be policy-relevant.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".