Canada-US Softwood Lumber Trade Revisited: Examining the Role of Substitution Bias in the Context of a Spatial Price Equilibrium Framework
Bibliographic record
Abstract
In the last two decades, softwood lumber trade between Canada and the United States has been characterized by numerous trade restrictions. Many studies have attempted to quantify the effects of such sanctions, and in doing so, softwood lumber was modeled as a single, homogenous commodity. However, recent research has suggested that this may be a misleading assumption, since not all softwood lumber products are equivalent substitutes. We refer to this problem as the substitution bias, and uniquely address this issue in estimating the effects of trade restricting policies. Using a spatial price equilibrium (spe) model, impacts of the post-sla import duties are estimated and compared to estimates of two alternative policy regimes – an export tax and quota. By controlling for substitution bias, our estimates indicate a larger share of the tariff burden is placed on us consumers, with Canadian producers suffering less injury compared to estimates using the traditional homogenous lumber assumption. In addition, by comparing the net impact associated with the alternative policy regimes, a policy equivalence result is found. Our results suggest that the short-run impact of a trade restriction is largely independent of the policy regime incorporated, with the collection of quota rents or tax revenues determining overall winners and losers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".