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Record W3212651679 · doi:10.32479/ijefi.11544

R&D INVESTMENTS IN PLANT BREEDING UNDER CHANGING INTELLECTUAL PROPERTY RIGHTS

2021· article· en· W3212651679 on OpenAlexaff
Mehdi Arzandeh, Derek G. Brewin

Bibliographic record

VenueInternational Journal of Economics and Financial Issues · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMerger and Competition Analysis
Canadian institutionsUniversity of ManitobaLakehead University
Fundersnot available
KeywordsEndowmentIntellectual propertyInvestment (military)Cournot competitionEconomicsVariety (cybernetics)DuopolyMicroeconomicsIndustrial organizationBusinessComputer scienceLawPolitical science

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.246
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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