The Sustainable Forestry Initiatives impact on stumpage markets in the US South
Bibliographic record
Abstract
Using survey data and an equilibrium displacement model, we estimate the market and economic impacts of the American Forest and Paper Association's Sustainable Forestry Initiative (SFI) on stumpage markets in the US South. We examine four timber product markets: softwood pulpwood, softwood sawtimber, hardwood pulpwood, and hardwood sawtimber. In each market we calculate changes in producer and consumer welfare using the equilibrium displacement model that accounts for reductions in timber inventories caused by SFI compliance. We find that SFI compliance costs the US South's economy about $36 million annually. SFI-compliant stumpage producers lose more than $33 million each year in producer surplus as a result of SFI compliance, and consumers lose about $12 million annually in consumer surplus due to higher product prices. These costs are offset partially by benefits to nonindustrial private forest producers, non-SFI-compliant industry producers, and public forest producers, who collectively gain about $10 million in producer surplus annually as a result of higher stumpage prices.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".