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Record W3207236172 · doi:10.1257/aer.20211337

Hub-and-Spoke Cartels: Theory and Evidence from the Grocery Industry

2024· article· en· W3207236172 on OpenAlexaffabout
Robert Clark, Ig Horstmann, Jean‐François Houde

Bibliographic record

VenueAmerican Economic Review · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Market Behavior and Pricing
Canadian institutionsQueen's University
Fundersnot available
KeywordsIndustrial organizationBusinessCompetition (biology)CommerceEconomics

Abstract

fetched live from OpenAlex

Numerous recently uncovered cartels operated along the supply chain, with firms at one end facilitating collusion at the other—hub-and-spoke arrangements. These cartels are hard to rationalize because they induce double marginalization and higher costs. We examine Canada’s alleged bread cartel and provide the first comprehensive analysis of hub-and-spoke collusion. Using court documents and pricing data, we make three contributions: (i) we show that collusion was effective, increasing inflation by about 50 percent; (ii) we provide evidence that collusion existed at both ends of the supply chain; and (iii) we develop a model explaining why this form of collusion arose. (JEL E31, K21, L12, L14, L22, L42, L81)

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 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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.932
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.282
Teacher spread0.249 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations10
Published2024
Admission routes2
Has abstractyes

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