Invisible chains of conflict: economy-wide spillovers from an agricultural shock in Ukraine – mixed input–output evidence
Why this work is in the frame
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Bibliographic record
Abstract
This article quantifies how a conflict-related agricultural supply shock propagates through Ukraine’s economy. Instead of the conventional demand-driven Leontief model, we use a mixed input – output model that introduces the shock directly as a capacity constraint in agriculture. In our central scenario, a 25% reduction in the agricultural workforce leads to a 4.6% decline in GDP, and impacts spread rapidly beyond farming. Sectors highly dependent on agricultural inputs are hit hardest, with chemicals (−30%) and motor vehicles (−28.8%) showing the largest losses, while public services remain comparatively stable. Sensitivity and robustness checks indicate near proportional effects, consistent with fixed-coefficient technologies and short-run rigidities. The results reveal a hierarchy of vulnerabilities and provide policy-relevant benchmarks to help secure critical supply chains and strengthen economic resilience against cascading shocks.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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