R&D INVESTMENTS IN PLANT BREEDING UNDER CHANGING INTELLECTUAL PROPERTY RIGHTS
Bibliographic record
Abstract
In a Cournot duopoly model, we examine three policy regimes relevant to current international plant breeding: patents alone, patents with a farmer exemption to use saved seed, and patents with research collaboration. In the symmetric version of the model where firms are identical, we show that the social planner prefers patents with research collaboration over patents alone and prefers the patents alone to patents with a farmer exemption. We examine two variations of the model where firms are asymmetric i. due to cost differences and ii. due to the different endowments of germplasm. Situations develop where the research collaboration resolves the common pool problem and increases R&D investment and where it creates free riding problem and decreases R&D investment. We show that the lower cost (more endowed) breeder invests more in R&D under the research collaboration than patents if variety differentiation is high and cost (knowledge endowment) dispersion is low. On the other hand, the higher cost (less endowed) breeder, generally, invests less in R&D under a research collaboration if variety differentiation or cost (knowledge endowment) dispersion is low. These findings suggest new gains are likely from the adoption of international conventions of plant breeders' rights. Keywords: Plant breeding, farmer exemption, research collaboration, Intellectual Property Rights, product differentiation, Cournot oligopoly.JEL Classifications: D21, D43, D60, D82, L13, L24, O34, O38, Q16, Q18DOI: https://doi.org/10.32479/ijefi.11544
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".