Synchronized movement between US lumber futures and southern pine sawtimber prices and COVID-19 impacts
Bibliographic record
Abstract
We analyzed the synchronized movements of lumber futures and southern pine sawtimber stumpage prices in the United States since 2011 and their response to COVID-19 events using wavelet analysis and event study. We found that the sawtimber and lumber prices have followed complex comovement patterns in the time–frequency domain and both reacted to COVID-19 events with a higher response intensity of the lumber price. Although they reacted differently to the early COVID-19 episodes and vaccine news, the sawtimber and lumber prices responded similarly to the COVID-19 pandemic declarations by the World Health Organization and US president, the US Food and Drug Administration panel’s recommendation of the first COVID-19 vaccine, and economic stimulus legislation. The patterns of synchronized movements between the sawtimber and lumber prices varied with time and frequency, but their comovement at low frequencies (>64 weeks) has strengthened since 2014 and been led by the lumber futures price; COVID-19 episodes have not changed this trend. The different magnitude of response of the two prices to the COVID-19-related events, as well as the long-term dominance of the lumber price in the comovement, reveals asymmetric price negotiation power and benefit distributions among the agents of the lumber value chain.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".