On Optimal British Columbia Log Export Policy: An Application of Trade Theory
Bibliographic record
Abstract
The log export policy suggestion by Dumont and Wright (2006) is critically assessed in an effort to determine if it is based on economic efficiency. The optimal log export policy for British Columbia is derived using two different models. The first model assumes that B.C. is a small open economy, and the second is a two country model that provides B.C. the opportunity to improve its terms of trade. In both cases it is shown that an optimal log export tax when a fixed lumber export tax exists can be characterized as a problem of second best. In that scenario the optimal log export policy is a positive export tax in both models. In the second model a positive export tax is also optimal when there is no lumber export tax, but it is smaller than when the lumber export tax is levied. In comparison to the log export tax recommended by Dumont and Wright (2006), the optimal tax for a small economy is always lower, while it is lower only in certain circumstances for an economy with market power. These results suggest that the Dumont and Wright policy is not efficient.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".