Projected effects of US tariffs on Canadian softwood lumber and newsprint imports: a cobweb model
Bibliographic record
Abstract
Starting from the cobweb theorem, a model of demand, supply, multilateral trade, and prices was formulated for the softwood lumber and newsprint markets in Canada, the United States (US), and the rest of the world. Parameters were estimated with panel data from multiple years and countries. The model was used to project the effects of US tariffs on softwood lumber and newsprint imports from Canada. To assess the uncertainty of the projections, multiple replications were performed by repeated sampling from the parameters’ statistical distributions. The results suggested that the initial shock of the tariffs dampened out and took 3 to 4 years to stabilize. In the long run, other things being equal, a 20.83% US tariff on softwood lumber imports from Canada decreased US imports from Canada by 4.7% to 8.0% and raised the US price by 0.3% to 2.3% and the US production by 0.9% to 1.7%, with 95% probability, while it lowered the Canadian price by 0.7% to 3.0% and Canadian production by 1.1% to 2.4%. A 28.69% US tariff on newsprint imports from Canada decreased US imports from Canada by 3.2% to 7.0% and raised the US price by 1.4% to 3.3% and the US production by 2.9 to 6.3%, while it lowered the Canadian price by 0.8% to 1.9% and the Canadian production by 1.6% to 3.5%.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".