Bibliographic record
Abstract
This paper studies vertical R&D spillovers between upstream and downstream firms. The model incorporates two vertically related industries, with horizontal spillovers within each industry and vertical spillovers between the two industries. Four types of R&D cooperation are studied: no cooperation, horizontal cooperation, vertical cooperation, and simultaneous horizontal and vertical cooperation. Vertical spillovers always increase R&D and welfare, while horizontal spillovers may increase or decrease them. The comparison of cooperative settings in terms of R&D shows that no setting uniformly dominates the others. Which type of cooperation yields more R&D depends on horizontal and vertical spillovers, and market structure. The ranking of cooperative structures hinges on the signs and magnitudes of three competitive externalities (vertical, horizontal, and diagonal) which capture the effect of the R&D of a firm on the profits of other firms. One of the basic results of the strategic investment literature is that cooperation between competitors increases (decreases) R&D when horizontal spillovers are high (low); the model shows that this result does not necessarily hold when vertical spillovers and vertical cooperation are taken into account. The paper proposes a theory of innovation and market structure, showing that the relation between innovation and competition depends on horizontal spillovers, vertical spillovers, and cooperative settings. The private incentives for R&D cooperation are addressed. It is found that buyers and sellers have divergent interests regarding the choice of cooperative settings and that spillovers increase the likelihood of the emergence of cooperation in a decentralized equilibrium. Cet article étudie les externalités de recherche verticales entre des firmes en amont et des firmes en aval. Il y a deux industries verticalement reliées, avec des externalités horizontales au sein de chaque industrie et des externalités verticales entre les deux industries. Quatre structures de coopération en R&D sont considérées: pas de coopération, coopération horizontale, coopération verticale, et coopération horizontale et verticale simultanément. Les externalités verticales augmentent la R&D et le bien-être, alors que les externalités horizontales peuvent les augmenter ou les diminuer. La comparaison des structures de coopération en terme de R&D révèle qu'aucune structure ne domine uniformément les autres. Le classement des structures de coopération dépend des externalités horizontales et verticales, et de la concurrence. Le classement dépend des signes et magnitudes de trois externalités concurrentielles (verticale, horizontale et diagonale) qui captent l'effet de la R&D d'une firme sur les profits des autres firmes. Un des résultats de base de la littérature sur l'investissement stratégique est que la coopération entre concurrents augmente (diminue) la R&D lorsque les externalités horizontales sont élevées (faibles); le modèle montre que ce résultat n'est pas toujours vérifié en présence des externalités verticales et/ou de la coopération verticale. Le papier propose une théorie reliant le degré d'innovation à la structure du marché: la relation entre la concurrence et l'innovation dépend des externalités horizontales, des externalités verticales et de la structure de coopération. Les incitations privées à la coopération en R&D sont examinées; on montre que les vendeurs et les acheteurs ont des préférences différentes quant au choix de structure de coopération et que les externalités augmentent la vraisemblance de l'émergence décentralisée de la coopération.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".