Investment returns of US commercial timberland: insights into index construction methods and results
Bibliographic record
Abstract
This study compares different index construction methods of timberland investment returns and evaluates the resulting indices by various asset pricing models. In addition to various NCRIEF indices, I include a de-smoothed index that attempts to restore property market values, a transaction-based index that tracks ex post transaction prices, and a pure-play index that is based on unleveraged returns of public timber firms and only has exposures to the timber segment. The findings are that the appraisal-based timberland index has higher mean and lower volatility compared with the transaction-based timberland index, separate accounts outperform comingled funds in the private timberland market, the pure-play timberland index exhibits higher return and lower risk than the corresponding portfolio of public timber firms, and abnormal performance of timberland asset becomes less significant after controlling for the appraisal smoothing or by using real transaction data. These results can help timberland investors better benchmark their financial performance.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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 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".