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Record W2020464577 · doi:10.1257/mic.5.3.97

Collusion with Asymmetric Retailers: Evidence from a Gasoline Price-Fixing Case

2013· article· en· W2020464577 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAmerican Economic Journal Microeconomics · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMerger and Competition Analysis
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsCollusionPrice fixingMechanism (biology)Point (geometry)MicroeconomicsTransfer (computing)EconomicsIndustrial organizationBusinessEconometricsComputer science

Abstract

fetched live from OpenAlex

We point out a fundamental difficulty of successfully colluding in retail markets with heterogeneous firms, and characterize the mechanism recent gasoline cartels in Canada used to sustain collusion. Heterogeneity in cost and network size necessitates arrangements whereby participants split the market unequally to favor stronger players. We characterize empirically the strategy and transfer mechanism using court documents containing summaries and extracts of conversations between participants. The mechanism implements transfers based on adjustment delays during price changes. We estimate that these delays can translate into substantial transfers and provide examples in which they can substantially reduce deviation frequency. (JEL K21, L12, L71, 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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.679
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.007

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 head0.018
GPT teacher head0.215
Teacher spread0.196 · 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