Deep trade agreements and vertical FDI: The devil is in the details
Bibliographic record
Abstract
Abstract Although pre‐1990s preferential trade agreements focused mostly on tariff liberalization, recent agreements increasingly contain deep provisions in diverse areas, such as intellectual property rights, investment and standards. At the same time, there has been a remarkable increase in the internationalization of production through foreign direct investment and outsourcing. This paper studies how deep trade agreements affect the international organization of production. Using new measures of the depth and content of preferential trade agreements and of vertical foreign direct investment, the analysis finds evidence that the depth of trade agreements is correlated with vertical foreign direct investment. Furthermore, this relationship is driven by the provisions that improve the contractibility of inputs provided by suppliers, such as standards, while provisions that increase the contractibility of headquarter services, such as intellectual property rights and investment protection, are generally negatively correlated with foreign investment. This finding is consistent with the so‐called “property rights” theory of the multinational firm according to which improving the contractibility of an input reduces the importance of giving incentives through ownership.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 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 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".