U.S. softwood lumber demand and supply estimation using cointegration in dynamic equations
Why this work is in the frame
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Bibliographic record
Abstract
This research estimated dynamic supply and demand equations for the U.S. softwood lumber using two-stage least squares. Long-run and ECM equations were derived from the estimated coefficients. Empirical data included monthly observations from 1990 to late 2006. Stationarity of the residuals was explored using Augmented Dickey-Fuller statistics. Results suggest that demand and supply elasticities in both short and long-run are relatively small compared with past studies. The Canadian softwood lumber supply to the U.S. is more price elastic than the domestic softwood lumber supply. U.S. import tariffs have had limited impact on the amount of softwood lumber imported from Canada. Technological progress and end-of-year seasonal effects on softwood lumber demand and supply were significant over this period. © 2010 Department of Forest Economics, SLU Umeå, Sweden.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it