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are typically States, but Spain and Portugal are split into two, and Belgium &
Luxembourg and Serbia & Montenegro are combined. Larger aggregate regions,
such as the 27 EU States, are also included. For each traffic zone, forecasts are
given separately for the main region-to-region flows (Annex C defines these traffic
regions) in the supplementary volume 2 of this report. Traffic flows are also
categorised as internals (within the traffic zone), arrival in or departure from the traffic
zone, and overflights (neither departing from nor landing in the traffic zone, but
passing through its airspace).
The forecast is published annually, at the beginning of the year and refreshed
mid-year to support the capacity planning process. Key features of the method are:
· Development of a core, airport-pair forecast which, at each update of the
medium-term forecast, is shared by medium- and short-term forecasts;
· A supply-side model is used to forecast growth directly on airport pairs, if this
gives better results than the traditional demand-side model;
· The demand-side model focuses on economic growth and its influence on
demand from travellers and shippers;
· Specific models for some market segments, such as business aviation and a
low-cost effect;
· The forecast is constrained by annual airport capacity.
· The overflights are calculated using the airport-to-airport routing in the baseline
year, plus more recent trends captured by the short-term forecast method.
The forecast method is continuously being refined to improve the quality of the
outputs. The main changes this year are:
· Completion of the integration of the short- and medium-term forecasts, which are
now identical for the February and September updates of the medium-term
forecast;
· The business aviation growth model uses both trends observed at national level
and any observed relationship with economic growth.
· The forecast process is summarised in Figure 17.
· The review body for STATFOR is the STATFOR User Group. This has members
from civil aviation authorities and air navigation service providers, and from other
industry organisations. Participants are typically actively involved in statistics or
forecasting. The STATFOR User Group meets once or twice per year. It reviews
the inputs to the medium-term forecast and the resulting draft forecast. The aim of
the review process is to produce a forecast which is consistent on a European
EUROCONTROL Medium-Term Forecast: IFR Flight Movements 2010-2016
Page 18 Released Issue Edition Number: v1.0
level and acceptable to member States. This does not necessarily mean the
forecast is the same as that produced nationally.
Figure 17. Preparation process of the Medium-Term Forecast.
History (10+ years)
Calibration data from STATFOR
Archives, CFMU, PRISME-Fleet,
National Sources, OAG...
Supply-Side Demand-Side
Scenario Inputs
- Economic Growth
- High-Speed Train
- Airport capacity
- Events & Trends
- Low-cost growth
- Load factor change
- Demographic change
Passenger All-Cargo
Historical Flight Routings
Calibration data from CFMU & National
Sources (including overflights)
Airport Capacity
• Short- and Medium-Term Reports, Tables
and Maps
• Dashboard
• Additional views (eg emissions)
Review by STATFOR User Group
Forecast
Routings
Airport-Pair History
Historical growth
Economic Growth
High-Speed Train
Network change
Low-Cost Growth
Airport-Pair
Forecast
Small Military
Constant Trend
BizAv
Trend
& Economy
Initial MTF Forecast
STF alignment Short-Term Forecast
Forecast Flights
per Airspace
The forecast is built from three main datasets.
· A historical database of the STATFOR monthly statistics (derived from CRCO,
CFMU and National sources) for the last ten or more years at airport-pair level;
· A baseline from CFMU and National sources that includes routing information;
· The set of scenario inputs.
The Medium-Term Forecast uses three scenarios which differ in terms of the
assumptions. The low-growth and high-growth scenarios between them capture the
most-likely range of future growth in flight movements; the baseline scenario indicates
a likely position within this range. The main parts of the scenario data are:
· Economic growth, summarised as GDP growth forecasts in real prices in local
currency; (Annex D.1)
· Low-cost growth, which adds additional flight movements, on top of economic
　
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