The Distributional Consequences of Preferential Trade Liberalization: Firm-Level Evidence
Why this work is in the frame
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Bibliographic record
Abstract
Abstract While increasing trade and foreign direct investment, international trade agreements create winners and losers. Our paper examines the distributional consequences of preferential trade agreements (PTAs) at the firm level. We contend that PTAs expand trade among the largest and most productive multinationals by lowering preferential tariffs. We examine data covering the near universe of US foreign direct investment and disaggregated tariff data from PTAs signed by the United States. Our results indicate that US preferential tariffs increase sales to the United States from the most competitive subsidiaries of multinational corporations operating in partner countries. We also find increases in market concentration in partner countries following preferential liberalization with the United States. By demonstrating that the gains from preferential liberalization are unevenly distributed across firms, we shed new light on the firm-level, economic sources of political mobilization over international trade and investment policies.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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