Pricing to Market Behavior by Canadian and U.S. Agri‐food Exporters: Evidence from Wheat, Pulse and Apples
Bibliographic record
Abstract
A fixed‐effects model to control for time variation in marginal costs is employed to pinpoint evidence of price discriminatory behavior of Canadian and U.S. exporters of agri‐food products. We test for evidence of pricing to market behavior and whether price discrimination or commodity/country characteristics may provide a plausible explanation. A distinguishing feature of our approach is to examine the time‐series properties of the data by the conventional augmented Dickey‐Fuller and recently developed panel unit root test. The panel data set employed in this paper consists of annual exchange rates and export prices for three agri‐food products (wheat, pulse and apples) exported by Canada and the U.S. in foreign markets during 1980–98. Our fixed‐effects model suggests that U.S. exporters are sensitive to exchange rate changes, while Canadian exporters in most cases raised price markups in response to a depreciated currency in overseas markets. The results highlight the differences in pricing policy that both countries employ to merchandise agri‐food products in export markets.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".