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Record W2116276235 · doi:10.5547/01956574.35.1.2

The Incidence of an Oil Glut: Who Benefits from Cheap Crude Oil in the Midwest?

2013· article· en· W2116276235 on OpenAlexaboutno aff
Severin Borenstein, Ryan Kellogg

Bibliographic record

VenueThe Energy Journal · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsGallon (US)GasolineCrude oilDiesel fuelPipeline transportCrack spreadAgricultural economicsOil priceEconomicsEnvironmental scienceEngineeringPetroleum engineeringWaste managementEnvironmental engineeringMonetary economics

Abstract

fetched live from OpenAlex

Beginning in early 2011, crude oil production in the U.S. Midwest and Canada surpassed the pipeline capacity to transport it to the Gulf Coast where it could access the world oil market. As a result, the U.S. “benchmark” crude oil price in Cushing, Oklahoma, declined substantially relative to internationally traded oil. In this paper, we study how this development affected prices for refined products, focusing on the markets for motor gasoline and diesel. We find that the relative decrease in Midwest crude oil prices did not pass through to wholesale gasoline and diesel prices. This result is consistent with evidence that the marginal gallon of fuel in the Midwest is still imported from coastal locations. Our findings imply that investments in new pipeline infrastructure between the Midwest and the Gulf Coast, such as the southern segment of the controversial Keystone XL pipeline, will not raise gasoline prices in the Midwest.

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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.205
Teacher spread0.188 · 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

Citations89
Published2013
Admission routes1
Has abstractyes

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