Home Bias in Primary Agricultural and Processed Food Trade: Assessing the Effects of National Degree of Uncertainty Aversion
Bibliographic record
Abstract
Abstract This study investigates the effects of national degrees of uncertainty aversion (unfamiliarity avoidance) on the magnitude of bias towards domestic products rather than imports. The empirical analysis is implemented for primary agricultural and processed food products, using a panel dataset covering trade between and within OECD countries. Primary agricultural products are often blended and associated with reference prices. Conversely, processed food products exhibit higher levels of product differentiation. The empirical results confirm expectations by emphasizing the magnifying effects of uncertainty aversion on home bias in the case of processed food products but not in the case of primary agricultural products. These magnifying effects are primarily associated with processed food products destined for final household consumption. Other results reveal significant variations between different countries (based on geo‐economic and national income categories). Our results also indicate that home bias and uncertainty aversion effects on home bias have not decreased over time. The empirical results remain robust under different estimation methods.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".