Global Supply Chains and the Political Economy of Preferential Tariff Liberalization 1
Bibliographic record
Abstract
How does the increasing reliance on global supply c hains change the political economy of trade? We argue that firms that offshore parts of the prod uction to either subsidiaries or other companies located outside national boundaries become increasingly dependent on imports of intermediates. As a result, we expect that with ris ing imports of intermediates the support for the liberalization of intermediates increases; however, for finished goods, greater imports should have the opposite effect. We also expect that most support for liberalization should come from companies that engage in vertical foreign investmen ts rather than arm’s length trade, as the former have a much larger stake in the lowering of specific trade barriers. Relying on a newly compiled dataset with highly disaggregated tariff d ata collected for a sample of 90 tariff schedules drawn up by Australia, Canada, Japan, South Korea and the United States in preferential trade agreements (PTAs) signed between 1996 and 2010, we find support for these expectations. The paper has implications for the li teratures on trade politics and PTAs.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".