The Impact of Cooperative R&D and Advertising on Innovation and Welfare
Bibliographic record
Abstract
This paper studies the impact of cooperative R&D and advertising on innovation and welfare in a duopolistic industry. The model incorporates two symmetric firms producing differentiated products. Firms invest in R&D and advertising in the presence of R&D spillovers and advertising spillovers. Advertising spillovers may be positive or negative. Four cooperative structures are studied: no cooperation, R&D cooperation, advertising cooperation, R&D and advertising cooperation. R&D spillovers and advertising spillovers always increase innovation and welfare if products are highly differentiated and/or spillovers are sufficiently high. The ranking of cooperation settings in terms of R&D, profits and welfare depends on product differentiation, R&D spillovers and advertising externalities. Firms always prefer cooperation on both dimensions, which is socially beneficial only when advertising and R&D spillovers are sufficiently high.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".