Elasticity of demand for Canadian logs and lumber in China and Japan
Bibliographic record
Abstract
Over the past decade, Chinese demand for forest products has increased substantially. While domestic production has risen, this increased demand has been met mostly by imports. The boom has been a welcome benefit to large forest products exporting countries such as Canada, especially in light of the weakened demand that occurred in the United States (US) following the financial crisis. While estimates of demand parameters for the US are vast, little is known about Canada’s other two leading markets: China and Japan. Furthermore, many existing trade models assume that logs and lumber are homogenous, perfectly substitutable regardless of their origin. In this note, we apply a source-differentiated Almost Ideal Demand System (AIDS) model to Chinese and Japanese log and lumber imports, with an emphasis on imports originating from Canada. Results indicate that the price elasticity of demand for Canadian lumber and logs in China is elastic. In contrast, in Japan, the price elasticity of demand for Canadian lumber is inelastic, but like China, demand for Canadian log imports is elastic. Expenditure elasticities suggest that Canadian wood products are expected to be favoured relative to other countries as demand in China grows; this finding may be attributed to marketing programs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".