Gasoline and crude oil prices: why asymmetry? Federal Reserve Bank of Dallas Economic and Financial Review, Third Quarter
Bibliographic record
Abstract
The available evidence suggests that asymmetry is unlikely to be the result of monopoly power exercised by large, integrated oil companies. The United States consumes 8.5 million barrels of gasoline daily—nearly half its daily consumption of all petroleum products. The average automobile tank is filled weekly, and gasoline prices are posted at every street corner where there is a gasoline station. Consequently, most U.S. consumers are very aware of movements in gasoline prices and closely observe the asymmetry when crude oil and gasoline prices fluctuate. Many consumers complain that gasoline prices rise more quickly when crude oil prices are rising than they fall when crude oil prices are falling, exhibiting an asymmetric relationship. 1 To the naked eye, movements in spot crude oil and retail gasoline prices may lend some credence to consumers ’ complaints (Figure 1). Furthermore, in some instances when gasoline prices have risen sharply and swiftly following a rise in crude oil prices—such as occurred in 1999 and 2000 and during the Gulf War in 1990—consumers and politicians have called for policies to put a stop to what is seen as unfair pricing practices for petroleum products. 2 Such reactions seem to stem from a popular suspicion that large, integrated companies have monopolized the oil industry. The public seems to take the asymmetric relationship between gasoline and crude oil prices as evidence that the petroleum industry is monopolistic. Most of the previous research on the subject confirms at least part of what consumers suspect: it provides econometric evidence of an asymmetric relationship between gasoline and crude oil prices. This article extends inquiry into the issue by considering competing explanations for the asymmetry. The available evidence
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".