Bibliographic record
Abstract
Abstract While we would expect that cross‐border patents are used to protect a technology that is made available in another country, that technology could either be produced locally or imported. International patent filings could therefore be either complements or substitutes to international trade. This study combines data on patenting and trade for 149 countries and 249 industries between 1974 and 2006 with a “three‐way” panel data model that addresses several biases emphasized in the trade literature in order to provide a systematic analysis of how bilateral trade responds to cross‐border patent filings. We find that cross‐border patents have a positive (complementary) overall effect on the patent‐filing country's exports to the patent‐granting country and no effect overall on imports flowing in the opposite direction. These effects vary substantially across industry groups, with patents promoting significantly more export growth in industries with a high demand elasticity and in industries that are relatively more downstream in supply chains. We also find that patents, once obtained, are associated with increased trade even in jurisdictions with weak intellectual property regimes.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".