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Record W4405173310 · doi:10.1111/caje.12750

Endogenous equity shares in duopoly markets with product differentiation

2024· article· en· W4405173310 on OpenAlexvenueno aff
Yi Li

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMerger and Competition Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDuopolyProduct differentiationEquity (law)BusinessEconomicsEndogenous growth theoryMicroeconomicsIndustrial organizationMarket economyHuman capital

Abstract

fetched live from OpenAlex

Abstract Firms can form partial passive ownership arrangements by acquiring equity shares in competitors' profits. We consider a duopoly model in which products are differentiated along both vertical and horizontal dimensions and one firm may acquire the other firm's equity shares before they engage in strategic competition. We identify equilibrium equity shares and characterize how the choice of equity shares depends on three previously unexplored factors: (i) the size of the market, (ii) the degree of horizontal product differentiation and (iii) the degree of vertical product differentiation. Whether an increase in the size of the market increases firm's incentive to hold a stake in the rival depends on whether the acquiring firm is a high‐quality firm or a low‐quality firm. The effect of vertical product differentiation also depends on the type of the acquiring firm, high‐quality vis‐à‐vis low‐quality. On the contrary, an increase in horizontal product differentiation can increase firm's incentive to hold a stake in the rival, irrespective of the type of the acquiring firm. We also find that the equilibrium levels of consumer welfare and social welfare may be lower compared to the case of no partial passive ownership.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.153
GPT teacher head0.190
Teacher spread0.037 · 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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes1
Has abstractyes

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