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A spatial price equilibrium model in the oligopolistic market for oil derivatives: an application to the brazilian scenario

2007· article· en· W2004875293 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

VenuePesquisa Operacional · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversité de Montréal
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsOligopolyEconomicsMonopolyCompetition (biology)Market structureIndustrial organizationWork (physics)Microeconomics

Abstract

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This paper presents a spatial price equilibrium model in an oligopoly market for refined oil products. Till 1997 the Brazilian oil market was characterized by the state monopoly of Petrobras, which up to 2001 remained the only firm authorized to import oil derivatives. With several agents operating in the primary oil supply market, the government stopped fixing the prices for Petrobras, which started to determine the prices based on competition with other players. In this new scenario some questions arise regarding the price levels at which refined products will be supplied in different regions across Brazil as well as the capacity of national refineries to compete with imported products. To answer those and other questions, a new oligopoly spatial equilibrium model is herein proposed, taking into account the special characteristics of production of refined oil products. An iterative Gauss-Seidel-like algorithm with sequential adjustments was developed and applied to Brazilian market data. The model, the algorithm and its application are described in this work. Such a model may be used both by regulatory authorities and by companies in the sector.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.061
GPT teacher head0.267
Teacher spread0.207 · 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