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Record W2147625786 · doi:10.5547/01956574.35.3.3

Daily Price Cycles and Constant Margins: Recent Events in Canadian Gasoline Retailing

2013· article· en· W2147625786 on OpenAlexaffabout
Benjamin Atkinson, Andrew Eckert, Douglas S. West

Bibliographic record

VenueThe Energy Journal · 2013
Typearticle
Languageen
FieldEnergy
TopicEnergy, Environment, and Transportation Policies
Canadian institutionsUniversity of AlbertaMount Royal University
Fundersnot available
KeywordsVolatility (finance)EconomicsGasolineEconometricsRefineryMonetary economicsMicroeconomicsEnvironmental science

Abstract

fetched live from OpenAlex

Retail gasoline pricing in Canada has typically followed certain distinct patterns, ranging from long durations of price rigidity relative to wholesale prices to daily price cycles. This paper examines recent changes to pricing patterns in Canadian cities resulting in new equilibrium behavior, and discusses possible reasons for these changes. Using high frequency retail price data obtained from GasBuddy.com, it is demonstrated that volatility changes exhibited in Toronto appear to correspond to an increased frequency of the price cycle, and replacement of the cycle with fixed retail margins. While multiple factors may have contributed to the first pricing change, the second change corresponds closely to a refinery fire in southern Ontario; this temporary event (in conjunction with a rail strike and refinery maintenance) could have triggered a permanent change in equilibrium behavior. This paper also illustrates problems for academic researchers and policymakers when using low frequency price data to analyze pricing in a market characterized by a price cycle.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.077
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.213
Teacher spread0.202 · 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 designObservational
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

Citations17
Published2013
Admission routes2
Has abstractyes

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