Financial valuation and the optimal rotation of a fully regulated forest
Bibliographic record
Abstract
This paper demonstrates a new approach to identifying and characterizing the optimal number of age classes in a fully regulated (i.e., normal) forest. We introduce an equilibrium condition for the normal forest requiring that it is financially justified to maintain the steady income forest configuration. We apply two valuation approaches to derive the main conclusion that the Faustmann rotation is the optimal harvest age of a normal forest. Both approaches utilize the standard Fisherian method of asset valuation. The first valuation approach imposes a steady income stream requirement, whereas the second approach is free of such a requirement. The second approach can be interpreted as enforcing market discipline on the normal forest configurations in a competitive equilibrium and picking the only normal forest that can be sustained in competitive equilibrium, namely, the forest with the number of age classes corresponding to the Faustmann rotation age. Our results also highlight an alternative way of deriving and interpreting the so-called zero-profit condition that can be applied to determining the optimal number of age classes in a regulated forest.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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 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".