How do natural and man-made disasters affect international trade? A country-level and industry-level analysis
Why this work is in the frame
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Bibliographic record
Abstract
This study examines the influence of disasters on international trade with a gravity equation model. Four types of disasters will be introduced: natural disasters, technological disasters, political risks, and financial crises. Existing literature implies that any type of disasters can either positively or negatively associated with international trade. The effects of disasters are different across the socioeconomic status of trade pairs and across industries as well as across different types of disasters. Results from country-level and industry-level show that natural disasters reduce international trade flows by raising trading and security costs and hardening borders. In contrast to previous findings, these results show that terrorism activities and technological disasters increase the international trade particularly between developed countries. The econometric specification controls unobserved characteristics of trade pairs and endogeneity problems. Managerial implications and future research are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it