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Record W1580264864

Selling to a cartel of retailers: a model of hub-and-spoke collusion

2013· article· en· W1580264864 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

VenueRePEc: Research Papers in Economics · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMerger and Competition Analysis
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsCollusionCartelBargaining powerWelfareSpoke-hub distribution paradigmBusinessMicroeconomicsConsumer welfareIndustrial organizationMarket powerEconomicsMarket economyMonopolyEngineeringTransport engineering
DOInot available

Abstract

fetched live from OpenAlex

This model describes the working of hub-and-spoke collusion that has been discussed recently by competition policy authorities. We develop a model of tacit collusion between a manufacturer and two retailers, competing a la Rotemberg and Saloner (1986). The best collusive equilibrium between retailers is inefficient and it is in the interest of the supplier to help retailers reach a more efficient collusive equilibrium. The hub and spoke conspiracy reduces double marginalization, but raises the ability of retailers to collude. The impact of a hub-and-spoke cartel on consumer's welfare depends on the bargaining power in the relationship. If the supplier has the bargaining power, the agreement, comparable to a vertical restraint, can be welfare improving in reducing double marginalization. When retailers have the bargaining power, the agreement is closer to an horizontal agreement in which retailers use the supplier to improve their collusive scheme, which leads to a loss of welfare. The result has important implications for competition policy and antitrust enforcement which are further developed in our companion paper Sahuguet and Walckiers (2013).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.048
GPT teacher head0.267
Teacher spread0.219 · 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