Evaluating the cumulative impact of the US–China trade war along global value chains
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The US–China trade war has been a key aspect of empirical review in recent times. Using the OECD Inter‐Country Input–Output Model, this study proposes an improved incomplete tariff pass‐through measurement method of cumulative tariff costs incurred across GVCs. Such an approach provides a more accurate picture of the impact of the US–China trade war on not only themselves but also third‐party countries. Our study found that five rounds of tit‐for‐tat tariff escalation has resulted in an indirect tariff burden of around 23 billion US dollars (USD) in total, of which 67% was caused by the US’s tariffs on Chinese imports. Moreover, perhaps unsurprisingly, the United States and China have suffered most economically, and in addition to direct tariff costs, they have to bear the indirect tariff burden of approximately 10 and 6.5 billion USD, respectively. This was followed by the EU, Canada and Mexico, which incurred indirect tariff costs of around 700 million to 1.7 billion USD. In addition, the burden on third‐party countries is expected to rise by 30%–70%, if we consider the hypothesis of complete tariff pass‐through.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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