Propagation of International Supply-Chain Disruptions between Firms in a Country
Bibliographic record
Abstract
This study shows how import and export shocks propagate through domestic supply chains using actual Japanese supply-chain data and a world input-output table (WIOT) based on firm-level agent-based simulations. We propose three different models with which to connect the domestic firms to a WIOT. Then, we estimate the value-added losses of Japanese firms caused by shocks of different magnitudes and durations originating in China, in the EU and the US, and globally. The volume and rates at which losses increase are very different across the connection models, which indicates that the assignment of international connections to firms matters greatly. The losses increase sublinearly as the duration expands, which indicates that the shock propagation ultimately saturates the economy. Rates of saturation differ substantially depending on the assignment of international connections. The losses increase superlinearly as the initial reduction rate increases. This occurs because there is a greater probability of one supplier being replaced by other suppliers if the reduction is smaller.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".