Transborder Demand Leakage and the US-Canadian Air Passenger Market
Bibliographic record
Abstract
The US–Canadian air traffic market is one of the largest international markets in the world – estimated at 23million passengers in 2008. The market is currently regulated by an “Open Skies” agreement, which eliminated all restrictions on the frequency of flights, the aircraft flown, and the fares charged on transborder routes. Although there is evidence that consumers have benefited from the Open Skies agreement, there is also evidence that many passengers have chosen to avoid transborder services, and instead fly from airports in US border cities and cross the border by surface transportation. This paper uses a passenger demand model to determine the scope of this “leakage” from transborder routes. In addition, transborder airfares are compared to US domestic airfares to determine whether transborder fares are “excessive”, a potential cause of the leakage. Results show a substantial amount of leakage estimated at over 4.7million passengers for 2008. Furthermore, after controlling for the impact of route-specific variables, such as market concentration, average fares are 28.2% higher in the transborder market. Finally, policy implications and the future of the transborder air passenger market are discussed.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".