Bibliographic record
Abstract
The softwood lumber trade dispute between Canada and the United States has centered on the debate over the existence of a stumpage subsidy in Canada and recently on dumping by the Canadian softwood lumber producers in the U.S. markets. This thesis contains three essays that investigate the subsidy and dumping issues in this dispute. The results of these analyses indicate the economic performance of Ontario’s stumpage system. The first essay investigates the market performance of Ontario’s stumpage system by examining the long-run equilibrium and Granger-causality relationships between the stumpage prices and the market prices of various end products (lumber, pulp and wood composites) from June 1995 to February 2005 using Johansen’s multivariate co-integration approach and the Granger-causality test. Test results indicate that in terms of SPF (spruce, pine, fir) for lumber and pulp, Ontario’s stumpage system can establish stumpage prices that have the potential to reflect the market values of timber. However, there is a need to modify the system for the other products. In the second essay, an Enhanced Parity Bounds Model (EPBM) is developed and used to examine the discrepancy between the stumpage price of SPF timber for producing lumber and its market value from June 1995 to January 2007. The results show that in the short run, the stumpage prices were below or above the market values. However, in the long run, the underpayment and overpayment will even each other out. The results, therefore, imply that Ontario’s stumpage system has the ability to capture the full economic rents in the long run and thus does not confer a subsidy to Ontario’s softwood lumber producers. The third paper examines the issue of whether Ontario’s softwood lumber industry had dumped softwood lumber into a major US market from April 1996 to September 2006 using the EPBM. This is a critical issue for Ontario’s stumpage system because dumping could lead to lower stumpage prices under the current stumpage system. This analysis indicates that the industry gained considerably more profit from the U.S market than from the home market and did not dump lumber in the US market during this period.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".