Bibliographic record
Abstract
We study the role of international trade risk for food security, the patterns of production and trade across sectors, and its implications for policy.We document that food import dependence across countries is associated with higher food insecurity, particularly in low-income countries.We provide causal evidence on the role of trade risk for food security by exploiting the exogeneity of the Ukraine-Russia war as a major trade disruption limiting access to imports of critical food products.Using micro-level data from Ethiopia, we empirically show that districts relatively more exposed to food imports from the conflict countries experienced a significant increase in food insecurity by consuming fewer varieties of foods.Motivated by this evidence, we develop a multi-country multisector model of trade and structural change with stochastic trade costs to study the impact and policy implications of trade risk.In the model, importers operate subject to limited liability and trade off the production cost advantage against the risk of higher trade costs when sourcing goods internationally.We find that trade risk can threaten food security, with substantial quantitative effects on trade flows and the sectoral composition of economic activity.We study the desirability of trade policy and production subsidies in partially mitigating exposure to trade risk and diversifying domestic economic activity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".