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Record W3125013023 · doi:10.1111/joie.12159

Sufficient Decisions in Multi‐Sided and Multiproduct Markets

2017· article· en· W3125013023 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Industrial Economics · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMerger and Competition Analysis
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsProfit maximizationOligopolyMonopolyMicroeconomicsMaximizationProfit (economics)EconomicsTransformation (genetics)Industrial organizationComputer scienceOperations researchMathematical economicsBusinessCournot competitionMathematics

Abstract

fetched live from OpenAlex

Abstract We show that in many models where firms make multiple decisions, analysis can be made more tractable by re‐formulating the model into one in which each firm makes a single choice, which we call a sufficient decision. The transformation allows application of standard techniques in these settings, including pass‐through for tax incidence and upward pricing pressure for merger analysis. The transformation works because the assumption of profit maximization links the firms’ decisions together. Examples include models of monopoly and oligopoly in two‐sided markets, where a natural sufficient decision may be the number of transactions that the firm facilitates, and multiproduct markets.

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.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.140
GPT teacher head0.278
Teacher spread0.138 · 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