Bibliographic record
Abstract
In an international Cournot oligopoly model, we compare two different merger policies when firms are merging endogenously and engage in research and development (R&D). In the benchmark model, countries set optimal tariff levels but do not have merger policy. If ex-ante identical firms merge internationally, they have an ex-post cost advantage over the outsiders due to tariff savings. This gives the merger an incentive to increase its R&D investment, which increases the cost dispersion further; therefore, the merger paradox, where each firm wants to be an outsider, disappears when R&D is efficient. As a result, we find different equilibrium market structures depending on the efficiency of R&D. In the second part, we compare two different merger policies, one that puts emphasis on welfare (roughly the Canadian merger policy) and another one that puts emphasis on consumer surplus (roughly the European Union’s merger policy). We show that under the “welfare-increasing” merger policy, monopoly is the equilibrium market structure when R&D is very efficient. This explains why a merger, which created a monopoly, was approved in Canada. As R&D becomes less efficient, the equilibrium market structures become less concentrated under the two different merger policies. Each merger policy can be global welfare maximizing depending on the efficiency of R&D; however, the “consumer-surplus-increasing” merger policy is optimal for a wider range of parameters.
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 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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".