Pipeline Capacity Rationing and Crude Oil Price Differentials: The Case of Western Canada
Bibliographic record
Abstract
This paper examines the impact of pipeline capacity constraints on the discount of Canadian oil prices relative to U.S. benchmark oil prices. Using a panel of monthly data for Canadian oil exporting pipelines, we estimate that the price differentials between the U.S. markets and Western Canada would increase by 3.4% for a 1% increase in oil shipping nominations excluded from transportation service due to insufficient pipeline capacity. Pipeline capacity constraints in Canada have resulted in an average loss of $5.07 for every barrel of crude oil exported to the U.S. between 2009 and 2017. In 2015 and 2016, the losses due to insufficient pipeline capacity were equivalent to 3%--5% of the Canadian oil and gas industry's sales revenue and 67%--96% of its royalty payments to provincial governments. Western Canadian oil refiners benefit from the depressed crude oil prices and this translates into increasing profitability of $0.1 per gallon for refined products. However, the total gain captured by local refiners is much smaller than the losses of the upstream sector.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
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".