Are Shocks to Air Passenger Traffic Permanent or Transitory? Implications for Long-Term Air Passenger Forecasts for the UK
Bibliographic record
Abstract
An important question facing air transport forecasters and developers of airport capacity in the UK is how robust is air passenger traffic to exogenous shocks such as, for example, September 11 and the second Gulf war. To address this question, this paper analyses statistical properties of air passenger traffic data for the UK and four other major developed aviation markets (Australia, Canada, Germany and the US), using time series methods. The evidence for the UK, Germany and Australia indicates that shocks to air passenger traffic are largely transitory and do not, in general, merit revision of forecasts over a long horizon. The exception is the shock associated with 1970s oil price rises, and the concurrent worldwide economic recession, which is found to have had a long-term impact on air passenger traffic growth in these countries. The US and Canada have also experienced a marked slowdown in traffic growth since the 1970s, but the evidence for these two countries is not consistent with a characterisation of shocks as being transitory fluctuations around a stable growth path.
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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 | 0.002 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".