New Aggregate and Source-Specific Pork Import Demand Elasticity for Japan: Implications to U.S. Exports
Bibliographic record
Abstract
The common treatment of a separate import demand specification in the literature is usually motivated by product differentiation. Most studies, however, proceed further with a separability assumption between domestic and imported product for data consideration and ease in estimation. In this study, a two-stage model is used to estimate aggregate and source-specific import demand elasticities for pork in Japan. This approach allows substitution between domestic and imported product on the one hand and avoids econometric problems in generating source-specific parameters, on the other. Pork imports into Japan are constrained by both the high protection and the strong preference of Japanese consumers for domestic pork over imported pork. Domestic pork commands a price premium of 13 to 29 percent in the retail market. Also, imported pork has a relatively low income elasticity reflecting consumer survey results of lower quality rating for imported pork compared with domestic pork. U.S. pork exports to Japan in particular have lower income elasticity than their closest competitor--Canadian pork. Japanese consumers perceive U.S. pork as inexpensive, but with food safety and quality being the main drivers of pork import demand in Japan, an "inexpensive" attribute may not be the right signal that will provide a true market advantage. However, U.S. pork exports to Japan have performed very well in the last three years. This means either that the United States was just strategically positioned when other foreign suppliers such as Taiwan and the European Union (EU) were challenged by diseases (e.g., foot-and-mouth disease [FMD] and Classical Swine Fever [CSF]), or that U.S. exporters are getting better at understanding Japanese consumer preferences, and are delivering the products that meet them.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".