Market Power in the Log and Lumber Import Market in Japan
Bibliographic record
Abstract
Japan imports rather than exports forestry products even though it has ample forestry resources. Moreover, the leading exporters of forest products often have strong market power in the trade market of forestry products. The possibility of incomplete competition in the Japanese wood import market can also be suspected from the fact that the structure of imports of logs and lumber has remained unchanged over the past 10 years. However, there has been limited empirical economic analysis of the timber trade market to support this assertion. In this study, we examine the market power of the primary exporting countries in the Japanese log and lumber market based on the residual demand model. We analysed the import data of forestry products from 1988 to 2010 with respect to every main item exported to Japan. The analysis shows that Canada has market power over several items of logs in the Japanese import market, while the United States and Canada have market power over several items of lumber. The study also clarifies that imperfect competition exists in the Japanese timber import market and that the timber price in Japan is partially determined by the exporting countries. JEL Classification: Q17, Q23, Q27
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".