Eurocontrol - Medium Term Forecast - Flights 2012-2018

8/2/2019 Eurocontrol - Medium Term Forecast - Flights 2012-2018

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EUROCONTROL

EUROCONTROL

Medium-Term ForecastFebruary 2012

Flight Movements

2012 - 2018


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EUROCONTROL Medium-Term Forecast: IFR Flight Movements 2012-2018

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EXECUTIVE SUMMARY

This report presents the February 2012 update of the EUROCONTROL Medium-Term flightforecast. The forecast considers the development of air traffic in Europe over the next7 years.

In recent months, Europe has seen a 5 percentage point drop in flight growth and a cut in theeconomic growth forecast for 2012 from 1.7% to 0%. This drop in flight growth is sooner anddeeper than the economic indicator would suggest. These two factors have stronglyinfluenced the short-term outlook for flights leading to a downward revision on the forecastissued in October 2011.

Over the full 7 years of the forecast Europe1 is expected to grow to 11.3 million IFR flights in2018, 16% more than in 2011. However, traffic in 2012 will decline (below -1% on 2011) andan anaemic recovery in traffic growth (+1.5%) is expected for 2013. The average growth rateover the 7 years remains weak at around 2% per year.

This forecast predicts that European traffic will reach the 10 million-per-year mark firstpassed in 2007 by 2014, two years later than last years prediction of 2012.

Figure 1. Summary of the forecast for the ESRA082.

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

AAGR2018/2011

H . . . . . . 9,759 9,999 10,414 10,805 11,229 11,693 12,057 3.0%

B 9,561 10,043 10,083 9,413 9,493 9,784 9,658 9,803 10,078 10,372 10,686 11,002 11,305 2.1%IFR Movements

(thousands)

L . . . . . . 9,565 9,626 9,778 9,968 10,182 10,365 10,560 1.1%

H . . . . . . -0.3% 2.5% 4.1% 3.8% 3.9% 4.1% 3.1% 3.0%

B 3.7% 5.0% 0.4% -6.6% 0.8% 3.1% -1.3% 1.5% 2.8% 2.9% 3.0% 3.0% 2.8% 2.1%Annual Growth(compared toprevious year)

L . . . . . . -2.2% 0.6% 1.6% 1.9% 2.2% 1.8% 1.9% 1.1%

Short-Term (2012-2013)

European flights in 2012 are expected to declineby 1.3% (+/-1%). This decline is widespreadamongst the busiest states in Western Europe and spreads out to Mediterranean countries(except Malta). The traffic forecast is largely influenced by the poor economic outlook and thedeclines in traffic growth since the beginning of the Winter timetable.

On top of these factors, the 2012 European flight forecast also reflects

a slow recovery of traffic following the end of the Arab Spring,

the flat to negative prospects for Summer flight growth (based on the schedules).

To the East, traffic growth remains positive in nearly all emerging markets though at slowerrates than the past two years.

1Europe is represented by the EUROCONTROL Statistical Reference Area (ESRA), see Annex B.

2

EUROCONTROL Statistical Reference Area in the extended 2008 definition (see Annex B).


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Current growth trends are strongly influenced at the regional and local levels by a number offactors and events. These imply specific risks to the forecast. In several cases whererecovery could be faster than anticipated, these are upside risks and traffic growth might bestronger. Risk areas include: recovery of flights to Egypt, which affects much of South-EastEurope but particularly Cyprus and Turkey; reactions to the failures of Spanair and Malev

(which cut 1% from total flights); airlines continuing revisions to their plans for the Summer;the restoration of Libyan overflights; growth to and from Russia and the recent climb in fuelprices.

At European level, 2013 sees a weak flight growth: +1.5% (+/-1%) with same level of trafficas in 2011 expected overall. Economic forecasts for 2013 have also seen recent downwardrevisions. Figure 2 shows disparities observed at State level in average growth rates over thefirst 2 years of the forecast. Some States (eg. UK, Spain, Italy) will struggle to come back topositive growth (compared to 2011) while others, on the east, will show strong growth levelsof around 5%.

Figure 2. Average annual growth 2011-2013 for each State.

Medium-Term (to 2018)

For the 2014-2018 period, traffic growth is expected to remain stable at around 3%.This is aslightly faster rate of flight growth than previously expected, but still below the pre-2009 long-term trend. This means a 6-7 year hiatus in flight growth; longer than the 4-year gapsfollowing the escalation of oil prices in 1980 or the over expansion of the late 1990s (seeFigure 18 in the report).

Again, some differences are observed at State level: growth is clearly stronger in theEast (Figure 3).

Over the whole period, a number of effects will reduce growth:

Lack of airport capacity means a reduction of around 134,000 IFR departures(1.2% off total growth over 7 years);

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Continuing improvements to the high-speed train network reduce growth by around47,000 IFR departures (0.4% off total growth to 2018) in Europe;

Aviation has now joined the EU Emissions Trading Scheme (ETS), reducing growthby a further 0.2% in Europe over the 7 years.

Figure 3. Average annual growth 2011-2018 for each State.

Any user of the forecast is strongly advised to use the forecast range (low-growth to high-growth) as an indicator of risk as part of the risk management process, notably duringplanning activities. This forecast includes upside and downside risks discussed in the report(section 4.1) and, by 2018, the high-growth scenario has around 750,000 more flightscompared to the base-scenario (+6.6%); the low-growth scenario has around the samenumber of flights fewer (-6.6%).

The EUROCONTROL 7-year flight forecast will next be refreshed in September 2012. The

first two years will also be updated in May 2012.

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EUROPEAN ORGANISATIONFOR THE SAFETY OF AIR NAVIGATION

EUROCONTROL

EUROPEAN AIR TRAFFIC MANAGEMENT PROGRAMME

EUROCONTROL Medium-Term Forecast: IFR Flight

Movements 2012-2018

Edition Number : v1.0Edition Date : 28/2/2012Status : Released IssueIntended for : General Public


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DOCUMENT CHARACTERISTICS

TITLE

EUROCONTROL Medium-Term Forecast: IFR FlightMovements 2012-2018

12/02/27-44Publications Reference:

Edition Number:Document Identifier v1.0

STATFOR Doc455 Edition Date: 28/02/2012

AbstractThis report presents the 2012 update of the EUROCONTROL 7-year forecast of instrument flightrules (IFR) flights in Europe in 2012-2018. It has been prepared by the EUROCONTROL Statistics

and Forecast Service (STATFOR) in November-February 2012 and it replaces the Medium-Termflight forecast of October 2011 and the Short-Term flight forecast of December 2011.

This document contains a description and discussion of the main results. The details of theforecasts for individual States are available on STATFOR website (www.eurocontrol.int/statfor).

KeywordsSTATFOR Forecast Medium-Term Traffic FlowMovements Flight Movements Trends

Contact Person(s) Tel Unit

Claire Leleu X3346

DNM/STATFOR

STATUS, AUDIENCE AND ACCESSIBILITY

Status Intended for Accessible via

Working Draft General Public Intranet Draft EATMP Stakeholders Extranet Proposed Issue Restricted Audience Internet (www.eurocontrol.int/statfor) Released Issue Printed copies of the document can be obtained from

the EUROCONTROL Publication and Documentation service (see

Page iii).

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Host System Software Size

Windows_NT Microsoft Word 10.0 8440 Kb

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PublicationsEUROCONTROL Headquarters96 Rue de la FuseB-1130 BRUSSELS

Tel: +32 (0)2 729 4715Fax: +32 (0)2 729 5149

E-mail: [email protected]

DOCUMENT APPROVAL

The following table identifies all management authorities who have successively approvedthe present issue of this document.

2012 The European Organisation for the Safety of Air Navigation (EUROCONTROL).This document is published by EUROCONTROL for information purposes. It may be copied in wholeor in part, provided that EUROCONTROL is mentioned as the source and to the extent justified by thenon-commercial use (not for sale). The information in this document may not be modified without priorwritten permission from EUROCONTROL.

The use of the document is at the users sole risk and responsibility. EUROCONTROL expresslydisclaims any and all warranties with respect to any content within the document, express or implied.

The Statistics and Forecasts Service (STATFOR) is ISO 9001:2008 certified.

Edition Number: v1.0 Released Issue Page iii
mailto:[email protected]:[email protected]:[email protected]


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DOCUMENT CHANGE RECORD

The following table records the complete history of the successive editions of the presentdocument.

EDITION

NUMBER

EDITION

DATE

INFOCENTRE

REFERENCEREASON FOR CHANGE

PAGES

AFFECTED

v0.1 20/01/12 Draft version All

v1.0 28/02/12 Final version All


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Edition Number: v1.0 Released Issue Page v

CONTENTS

1. INTRODUCTION...................................................................................................8 1.1

General......................................................................................................................................8

1.2 Summary of Forecast Method...................................................................................................8

2. TRAFFIC IN 2011 .................................................................................................93. FORECAST INPUTS AND ASSUMPTIONS ......................................................144. GROWTH IN IFR Flight MOVEMENTS TO 2018...............................................17

4.1 Summary of growth .................................................................................................................174.2 Other risks to the Forecast......................................................................................................224.3 Airport constraints ...................................................................................................................234.4 High-Speed Train ....................................................................................................................244.5 Emissions Trading Scheme (ETS)..........................................................................................254.6 Comparison with earlier forecasts...........................................................................................26

5. GLOSSARY........................................................................................................27Annex A. FORECAST METHOD...................................................................28

Annex B.

TRAFFIC REGION DEFINITIONS.................................................32

B.1 ESRA08...................................................................................................................................32B.2 Traffic regions .........................................................................................................................32B.3 Functional Airspace Blocks.....................................................................................................33

Annex C. SUMMARY OF FORECAST ASSUMPTIONS...............................34C.1 Economic Growth....................................................................................................................34C.2 Low-Cost Carrier Growth ........................................................................................................37C.3 High-Speed Train Network Development ...............................................................................39C.4 Airport Capacity.......................................................................................................................41 C.5 Load Factors ...........................................................................................................................41C.6 Events and Trends ..................................................................................................................43C.7 Airport Traffic Switch ...............................................................................................................45C.8 Emissions Trading Scheme ....................................................................................................46

Annex D. SUMMARY OF THE FORECAST FOR THE ESRA ......................48Annex E. FUTURE TRAFFIC AND GROWTH.......................................................51

E.1 Summary of the Forecast. Annual IFR Movements 2006-2018..............................................51E.2 Summary of the Forecast. Growth Rates 2006-2018 .............................................................56


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Annex F. REFERENCES .......................................................................................61

List of Figures.

Figure 1. Summary of the forecast for the ESRA08. ................................................................. iFigure 2. Average annual growth 2011-2013 for each State.................................................... iiFigure 3. Average annual growth 2011-2018 for each State................................................... iiiFigure 4. Actual traffic compared with the forecast of December 2010....................................9Figure 5. Growth in 2011 was particularly strong around the Baltic, in Turkey, the

Netherlands and Ukraine. ...............................................................................................10Figure 6. European neighbours: Strong Russian growth balances North African downturn. .11Figure 7. Load factors in Europe remained near record levels. (intra-Europe traffic) ............11Figure 8. Oil prices remained mostly above $100/bl in 2011. ................................................11Figure 9. Traditional scheduled carriers took over as the fastest-growing market segment ..12Figure 10. Market shares of the main segments hardly changed in 2011..............................12Figure 11. GDP forecast have seen strong downward revisions. ..........................................14Figure 12. Underlying growth for busiest States shows further falls in 2012..........................15Figure 13. Summary of the forecast for Europe (ESRA08). ...................................................17Figure 14. Forecast for 2012 in Europe is for a widespread decline. (Uncertainty is typically

1.0% percentage points)................................................................................................18Figure 15. Forecast for 2013 in Europe is for a weak growth. (Uncertainty is typically 0.9

percentage points) .......................................................................................................... 19Figure 16. Number of additional movements per day for each State (2013 vs 2011). ...........19Figure 17. Number of additional movements per day for each State (2018 v 2011). .............21Figure 18. IFR flight growth in Europe is now persistently below the pre-2009 long-term

trend................................................................................................................................21 Figure 19. Impact of airport constraints..................................................................................23Figure 20. Impact of high-speed train: reduction in IFR departures for ESRA08 (top) and

most affected States (bottom).........................................................................................24Figure 21. Impact of ETS: reduction in IFR departures for ESRA08 due to aviations

participation in the scheme. ............................................................................................25Figure 22. Forecast for the ESRA08 has been revised downwards (MTF11b dashed lines,

MTF12 solid lines)...........................................................................................................26Figure 23. Summary of short-term forecast method...............................................................28Figure 24. Preparation process of the Medium-Term Forecast..............................................30Figure 25. The EUROCONTROL Statistical Reference Area. ...............................................32Figure 26. Regions used in flow statistics. .............................................................................33Figure 27. FAB initiatives as of January 2011. (Source: EUROCONTROL PRU) .................33Figure 28. Changes per State in economic forecast for 2012 for this flight forecast. .............34Figure 29. Since the previous forecast, the economic outlook for EU27 has significantly

worsened.........................................................................................................................35 Figure 30. Summary of changes in GDP forecasts for 2012-2018: nearly all States see

reduction in 2012 and 2013.............................................................................................35Figure 31. GDP Growth by Traffic Zone.................................................................................36Figure 32. GDP Growth by Origin-Destination Zone..............................................................37Figure 33. GDP Growth by Traffic Region..............................................................................37


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Figure 34. Low-Cost effects by Traffic Zone ..........................................................................38Figure 35. High-Speed Train Times .......................................................................................39Figure 36. Example load factor forecast, for Europe.............................................................42Figure 37. Load factors by Traffic Region ..............................................................................42Figure 38. Events and Trends assumptions by Traffic Zone..................................................44Figure 39. Airport traffic switch...............................................................................................46Figure 40. ETS assumptions..................................................................................................46Figure 41. Prices ....................................................................................................................47Figure 42. Price Elasticities per (bidirectional) Traffic Region Pair and period ......................47Figure 43. Growth in Europe ..................................................................................................48Figure 44. Traffic on the main flow categories for the ESRA .................................................49Figure 45. Traffic and growth on the biggest region-to-region flows through the ESRA. .......50Figure 46. Annual traffic per traffic zone and 2012-2018 average annual growth..................51Figure 47. Annual growth rates per traffic zone and 2012-2018 average annual growth.......56


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Edition Number: v1.0 Released Issue Page 8

1. INTRODUCTION

1.1 General

This report presents the forecast of annual numbers of instrument flight rules (IFR)flight movements for 2012 to 2018, prepared by the EUROCONTROL Statistics andForecast Service (STATFOR) in December 2011-February 2012. This replaces theforecast issued in September 2011 (Ref. 1).

This report contains a summary and discussion of the forecast, starting with adiscussion of traffic in 2011 (section 2), the assumptions made in the forecastscenarios (section 3) and some highlights from the forecast results (section 4). Moredetails are provided in the annexes: forecast method ( Annex A), geographicaldefinitions (Annex B), forecast assumptions (Annex C), forecast details for Europe asa whole (Annex D) and annual total forecasts per State (Annex E). The detail for each

traffic zone (usually the same as State) is provided on STATFOR website (Ref. 2).STATFOR also prepares a long-term forecast (20 years) available in summary on theSTATFOR web pages (Ref. 3).

1.2 Summary of Forecast Method

The EUROCONTROL 7-year flight forecast grows airport-pair traffic usingmodels of recent trends, and of future economic and industry developments.

The 7-year forecast is a blend of two forecasting methods: time-series modelling ofrecent traffic trends; and a model of future flight demand based on economic growthand other developments. The trend-based modelling provides better accuracy in the

first years, so is more influential in the blend in the first two years. The economic andindustry modelling has more influence on the results for the later years.

The time-series modelling looks at recent and longer-term patterns of growth andseasonality, taking into account information about one-off events, about economicgrowth and available data on the airline schedules for the coming months.

The economic model is developed by growing baseline traffic (all IFR flightmovements for the last calendar year) taking into account factors such as economicgrowth, past patterns ofsupply, the growth of low-cost carriers, and the influenceofhigh-speed trains.

The results of these processes are then constrained by annual airport capacities

and converted from airport-to-airport counts into flights through airspace volumesusing the flight patterns in the last 12 months and recent trends in how these patternsare changing. No account of future route network changes is made (see section 4.2).More detail of the method is given inAnnex A.

Three scenarios are used to capture the likely range of growth of flight movements.They comprise: the low-growth and high-growth scenario which vary economicgrowth, load factors and other variables in order to capture the most-likely range; andthe baseline forecast which is a guidance figure within this range. The scenarios arediscussed in section 3 and detailed in annex B.1.

Experience in recent years has shown the need to take the whole forecast range(from low-growth to high-growth) into account. For this new forecast, the main areas

ofrisk are discussed in section 4.1.


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2. TRAFFIC IN 2011

2011 followed a trend of weak traffic growth, becoming weaker still with the newWinter 11/12 timetable. Overall, growth appeared stronger than it really was dueto cancellations in 2010. There were some hotspots, notably in the East andScandinavia.

Any discussion of 2011 traffic trends must start in 2010, which was a weak year forEuropean air traffic, but the particular legacy of interest for 2011 was the 170,000flights that were cancelled due to the ash-cloud, snow and strikes. Since 2011 sawfewer than 25,000 cancellations3, we saw bounce-back events throughout 2011 butparticularly in April 2011 and December 2011. Indeed April saw growth jumping to anunlikely-sounding 16%. Overall, that difference of around 150,000 cancellationsinflated the flight growth of 2011 by some 1.5% for Europe4.

This bounce-back is a substantial part of the overall growth in flights of 3.1% in 2011.

It means that the underlying trend during the year was only for between 1.5% and 2%growth, as aviation in Europe remained under the pressure of an unfavourableeconomic situation. Looking back, we can identify three phases of the year (Figure 4):

For the first few months, the weak underlying growth was masked bycancellations at the start of 2010, and by a hesitant optimism in the industry thatwas due to high load factors and an apparent improvement particular at thepremium end of the market. Reductions in flights to Tunisia and particularly Egyptprevented any recovery from lifting the growth trend.

Over the Summer, the underlying trend changed little, though it was slightly abovethe expectation of the May forecast. However, the mood of optimism began todisappear as economic forecasts and industry-sentiment indicators declined, and

in our own industry the signs also turned downwards, with cargo load factorsleading the way.

The Winter 11/12 timetable saw a sharp deceleration, as several carriers cut backto below the flight numbers of the previous Winter and warned of weak forwardbookings.

Figure 4. Actual traffic compared with the forecast of December 2010.

3This preliminary estimate undercounts the effects of events in Tunisia, Egypt and Libya (see below).

4

Here Europe is used to mean ESRA08. See Annex B for definition.


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This annual average masks a geographically varied situation (Figure 5). Stronggrowth was seen around the Baltic (extending also to Norway and the Netherlands)and in Turkey and the Ukraine. Figure 5 just covers the period May to November toavoid the confusion of the ash-cloud and snow bounce-back, but this still exaggeratesFrench growth due to the strike cancellations in the period in 2010. Notably Germany,

which as a large State would be expected to be to the left-hand side, does not appearat all in Figure 5 due to static traffic in part as a result of airlines response to a newdeparture tax.

In spite of its open skies agreement with the EU, Morocco saw a downturn inarrivals/departures in parallel with that elsewhere in North Africa, if not as large. Thestrength of the Canary Islands, which appears to be growing internally and as areplacement Winter sun destination, however, boosted Moroccos overflights.

Further afield, the effects of the Arab Spring are also evident in Figure 6: declines of80-90 departures/day to Egypt and Tunisia together over the Summer months. This is160-180 flights/day in both directions (the units ofFigure 5), meaning that this nearlycancelled out the Turkish growth. Indeed, taken over the whole year, this suggests

perhaps 50,000 flights fewer than expected5. By the same arithmetic, the growthto/from Russia of perhaps 140 flights/day places the Russian flow as the second-largest contributor to growth overall in Europe, after Turkey.

Figure 5. Growth in 2011 was particularly strong around the Baltic, in Turkey,the Netherlands and Ukraine.

5These are not necessarily cancellations in the same sense as those caused by snow or strike, so dont get captured by the

cancellation calculations.


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Figure 6. European neighbours: Strong Russian growth balances North Africandownturn.

Figure 7. Load factors in Europe remained near record levels.(intra-Europe traffic)

Figure 8. Oil prices remained mostly above $100/bl in 2011.



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Figure 9. Traditional scheduled carriers took over as the fastest-growing marketsegment

Figure 10. Market shares of the main segments hardly changed in 2011.

For commercial carriers, load factors remained near record levels (Figure 7), althoughthey began to weaken in the Autumn, especially on the high-yield Asian flow. Oilprices have now spent 12 months near 80/barrel (Figure 8) and the weakening euroof recent months suggests that fuel prices will become more difficult yet.

2011 saw a marked change in the relationships between the main market segments,as their growth patterns (Figure 9) became more synchronised than recently seen:

The traditional scheduled carriers grew the fastest, at 4.1%. This is the first timethey have out-grown the low-cost carriers in percentage terms since the early1990s.

The low-cost carriers had a year of much more moderate growth plans than in thepast, managing 3.9% flight growth. Some did better out of the strength around theBaltic, but the Winter saw a sharp scaling back.

The (tourist) charter segment had a particularly difficult year (non-scheduled inFigure 9), being the most affected by the drop in traffic to the winter leisuremarkets ofTunisia and Egypt; although some were insulated a little from this bytheir past diversification into scheduled operations. It declined by 5.8%.



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All-cargo saw warning signs in tonnage and load factors over the Summer; andthe flights finally went into decline in the Autumn. Over the year as a whole itachieved 2.9% flight growth.

Business aviation (2.3% increase) saw a similar evolution, but a slightly lowerannual figure as there was less bounce in April, since it was least affected by ashin April 2010.

The result of all of this was that their respective market shares hardly changed(Figure 10); charter lost 0.5% points, which the traditional segment gained whencompared to 2011 figures.



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3. FORECAST INPUTS AND ASSUMPTIONS

The forecast is driven by past traffic trends and by scenario assumptions forthe future. The downward revision in the new forecast starts from adeceleration in flight growth of around 5 percentage points since the end of theSummer timetable. While this is partly explained by a cut in forecast economicgrowth (equivalent to a 2.5%-3% drop in flights) it is an earlier and deeperdecline than economics alone would suggest.

The forecast is derived from historical traffic data and a set of scenario assumptions(listed in Annex C). The downward revision in the forecast can be understood fromthese data. In particular, since the 7-year forecast was last published in October theinputs have changed in two important respects: GDP and flight growth. Thesechanges are behind a strong downward revision, even if our judgement is that thisrevision may now have left us with up-side risks.

Firstly GDP forecasts, especially for 2012, have seen strong downward revisionduring 2011, and particularly since the Summer (Figure 11). The last GDP forecastthat we used was for 1.7% growth in 2012 at the EU level, but this is now cut to 0%for this update. This 1.7% revision alone would be expected to cut the flight growthforecast by between 2.5% and 3%. The weaker economic situation continues into2013 (more detail on this in Annex C.1.)

Figure 11. GDP forecast have seen strong downward revisions.

There was a sharp deceleration in flight growth from the end of October (Figure 4),which had been flagged in advance by some carriers, but the extent of the downturn

was beyond expectations. This downturn had some limited influence on theDecember forecast, whose input data included one month of the declining traffic. Ifanything, this deceleration is even stronger since the beginning of 2012, with someoperators making further cuts, in addition to the collapse of Malev and Spanair (whichhad 1% of European flights between them in 2011). Figure 12 uses the mediandailygrowth in the month, to give an approximate idea of the underlying trend largelyinsulated from spikes due to weather and strikes. For the busiest five States, thedownward shift is perhaps 5% points since October, which is more than would beexpected from economic reasons alone. Now with three months of this downturnfeeding into the short-term forecast, the effect on the forecast is much more marked.



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Figure 12. Underlying growth for busiest States shows further falls in 2012.

Amongst the explanations for a decline in flights that is sooner and deeper than theeconomic factors would imply are two factors which are not fully represented in the

forecast, but clearly weigh on the outlook for 2012. They are: the fuel price, whichhas been quoted by many airlines as causing difficulties, and now seems to beclimbing further due to tensions between Europe and Iran, with the Brent crude priceat record levels in euro terms; and the weakness of national airlines, with a largenumber of States looking to reduce or dispose of their stakes, leaving limited scopefor further re-capitalisation. We estimate that airlines with more than 6% of 2011European flights are up for sale, in bankruptcy protection or else struggling to financetheir operations.

Some of the growth areas seen last Summer (Figure 5) have lost all or most of theirstrength over the Winter: notably Canaries, Finland and Sweden. This weakness hasbeen picked up in the forecast. However, here there is an upside risk, with limitedvisibility in the schedule data for the Summer of whether Canaries will return to being

a destination of choice as an alternative to North Africa.

The traffic disruption that followed the Arab Spring is represented in the forecastsboth as historical data and as assumptions for the continuing recovery. Twelvemonths on from the sharpest downturn to Egypt, we are seeing some recovery in theoverflights for States such as Cyprus and Turkey. The timing and extent of thisrecovery is uncertain; our assessment is that this probably represents an upsiderather than a downside risk.

Other inputs include:

Low-cost. For this forecast we have reviewed the assumptions about low-costmarket share growth to take account of the fact that this market share is now

growing more slowly, if at all in recent years. These are discussed in detail inAnnex C.2. The effect is most marked for larger States, where the market sharegrows more slowly than in previous forecasts, or indeed in the low-growthscenario might see a small contraction.

High-Speed Rail: In spite of the economic downturn, high-speed raildevelopments continue to complete and deliver travel time savings. Over the next7 years, there are an increasing number of cross-border connections orimprovements, such as Lisbon-Madrid, Amsterdam-London, Madrid-Bordeaux,Paris-Barcelona, Zurich-Paris. (Annex C.3)

-5%

Airport capacity: These numbers have been refreshed, following data providedby STATFOR User Group members, or by airports directly to EUROCONTROL.



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The main change has been the addition of capacity for the third airport in Istanbul,which leads to faster growth from 2017. (Annex C.4)

Load factors: Our forecasts generally project these to increase further, althoughonly by a couple of percentage points in the case of intra-Europe traffic. Aftergrowth in load factors levelled off last year, the question must be asked whetherthey have now reached a practical maximum. If so, we may be underestimatingflight growth. (Annex C.5)

Events and trends: As well as Euro12, Olympics, Croatia & Icelandic accessionto the EU and relaxation of visa requirements in the Balkans, we have included ascenario for the continuing recovery of traffic to/from Egypt, Tunisia and Libya.Twelve months on, the sharp decline is dropping out of the tables. Other possiblescenarios certainly exist, and the knock-on effects of this for Malta and othersrequire further validation. (Annex C.6)

Emissions trading: This began in 2012, and is modelled as in previous forecasts.(Annex C.8)



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4. GROWTH IN IFR FLIGHT MOVEMENTS TO 2018

4.1 Summary of growth

As a result of the current poor economic outlook, which is for stagnation orweak growth, and the current traffic situation, which saw cutbacks in flightsthis Winter, we now forecast a decline in 2012, followed by a weak recovery in2013. Over the remaining years of the forecast, flight growth is stronger ataround 3% per year. This, however, reflects a long-term growth trend that isforecast to be lower than in the past. Total traffic reaches 11.3 Million flights in2018.

Figure 13. Summary of the forecast for Europe (ESRA08).

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018AAGR2018/20112006

. . . . . . 9,759 9,999 10,414 10,805 11,229 11,693 12,057 3.0%H

9,561B 10,043 10,083 9,413 9,493 9,784 9,658 9,803 10,078 10,372 10,686 11,002 11,305 2.1%IFR Movements

(thousands)

. . . . . . 9,565 9,626 9,778 9,968 10,182 10,365 10,560 1.1%L

. . . . . . -0.3% 2.5% 4.1% 3.8% 3.9% 4.1% 3.1% 3.0%H

3.7%B 5.0% 0.4% -6.6% 0.8% 3.1% -1.3% 1.5% 2.8% 2.9% 3.0% 3.0% 2.8% 2.1%Annual Growth(compared toprevious year)

.L . . . . . -2.2% 0.6% 1.6% 1.9% 2.2% 1.8% 1.9% 1.1%

Short-Term outlook (2012-2013)

As a result of the poor economic outlook, which is for stagnation or weakgrowth, and the current traffic situation, which saw cutbacks in flights thisWinter, we now forecast a decline in 2012, followed by a weak recovery in 2013(Figure 13).

The previous section has described how this update of the forecast is particularlyinfluenced by the drop in flights of 5 percentage points this Winter and a cut in theeconomic growth forecast for 2012 from 1.7% to 0%. This drop in flight growth issooner and deeper than the economic forecast would suggest. These two factorshave strongly influenced the short-term outlook for flights which is that Europeanflights in 2012 are expected to decline by -1.3% (+/-1%) (Figure 14). This decline iswidespread amongst the busiest states in Western Europe and spreads out toMediterranean countries (except Malta).

On top of these factors, the 2012 European flight forecast also reflects

a slow recovery of traffic following the end of the Arab Spring,

the flat to negative prospects for Summer capacities.

On the Eastern side, traffic growth remains positive in nearly all emerging marketsthough at slower rates than the past two years.

Growth forecasts for all States are provided in Annex E, and in more detail on theSTATFOR interactive dashboard (Ref. 2).



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Current growth trends are strongly influenced at the regional and local levels by anumber of factors and events. These imply specific risks to the forecast:

The forecast includes a scenario for recovery of Egypt traffic. However, variationsin this would change the recovery in overflights, in particular for Cyprus andTurkey, but indeed for much of South-East Europe. We believe this to be onbalance an upside risk, with recovery faster than currently forecast.

The recent failures of Spanair and Malev have cut 1% off total flights, with muchlarger effects locally. On the one hand, we have assumed some limitedsubstitution by other carriers, on the other there is an upside risk of moreextensive replacement which would improve traffic growth in Spain, Canaries andHungary.

Information on capacity for the Summer remains incomplete, and airlines continueto review their plans. We assess this on balance to be an upside risk, of strongergrowth than currently in the forecast.

The restoration of Libyan overflights has significant implications for Malta and, to a

lesser extent, Italy. This we also assess to be on balance a downside risk for theshort-term, with a less complete restoration of flights.

Growth in flights to/from Russia has been an important contributor to growth,especially for States in central and North-East Europe (section 2), if this growthcontinues, and particularly if the Russia-Egypt flow recovers more strongly, thenthere is a risk of faster growth overall.

Figure 14. Forecast for 2012 in Europe is for a widespread decline. (Uncertainty istypically 1.0% percentage points)



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The economic downward revisions extend into 2013, which is now expected to see a1.5% traffic growth (1%) across Europe (Figure 15).

Figure 15. Forecast for 2013 in Europe is for a weak growth. (Uncertainty is typically0.9 percentage points)

Figure 16. Number of additional movements per day for each State (2013 vs2011).



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Medium-Term outlook (to 2018)

Over the remaining years of the forecast, flight growth is stronger at around 3%per year. This reflects a long-term growth trend that is forecast to be lower thanin the past, reaching 11.3 Million flights in 2018.

After 2013, growth is expected to follow a trend of about 3% growth per year (Figure13). The previous peak annual traffic (10.1 Million flights in 2008) will be reachedagain in 2014. This means a 6-7 yearhiatus in flight growth, longer than the 4-yearhiatus after the 2000 and 1980 peaks6. Due to the weak start in 2012 and into 2013,the average growth between 2011 and 2018 is just 2.1%. The high- and low-growthscenarios are each around 1 percentage point from this.

As in recent years, the traffic development is not uniform across the region as Figure3 in the executive summary illustrates. Growth (in percentage terms) is clearlystronger in the East (see Annex E.2). In contrast, in terms of the number of additionalmovements per day, the traffic will increase the most in the busy States WesternEurope (eg. Germany) but also in Turkey and Ukraine, which are forecast to see

some of the strongest traffic growth in Europe (see Figure 17).Figure 18 illustrates that flight growth is now well below the pre-2009 long-term trendline, and is forecast to remain below that trend. There are some upside risks, butthere are also good reasons for the future long-term trends to be lower than thatobserved in the past. In particular, we can identify two major factors that havecontributed to strong growth in the last 20 years, but which now appear to be runningout of steam:

Deregulation of air transport in Europe around 1990 allowed supply to matchdemand more accurately, as well as contributing to the growth of the low-costmarket segment. However, for several North-West European states, there isincreasing evidence through long-term stagnation or decline of shorter-haul

markets that the number of under-served markets is limited. Nevertheless,deregulation of medium- or longer-haul remains a possible source of growth.

The expansion of the EU in 2004 and 2007 extended the area of air transportderegulation, but more importantly introduced free trade and free movement ofpeople and businesses. This provided a one-off boost to demand which has nowrun its course, though there are still some States that could be included.

6

The over-expansion in the late 1990s and the escalation of oil prices in 1980.


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Figure 17. Number of additional movements per day for each State (2018 v2011).

Figure 18. IFR flight growth in Europe is now persistently below the pre-2009long-term trend.

-5

0

5

10

15

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015-10%

-5%

0%

5%

10%

15%

20%

25%

30%

Annua l

G r o w t h

Long-TermAverage

Gr o w t h

Actua l

Traf f i c

Long-Term Trend

Before 200 9

Forecast

Traf f i c

FlightsinEurope(Million)

AnnualGrowth

IFR traffic in Europe1960-2011 historical figures

2012-2018 forecast

EUROCONTROL 2012. ww w .eurocontrol.int/s tatfor


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4.2 Other risks to the Forecast

Users of the forecast are strongly advised to use the forecast range (low-growth tohigh-growth) as an indicator of risk. A number of specific risks, particularly for the

short-term, have just been discussed (section 4.1). More generally, we identify: This forecast is prepared as the economic forecasts in Europe have again been

revised downwards. Nevertheless, there has been some relatively good news andit is possible that we are reaching the end of the downward revisions. Theuncertainty in economic growth has a direct impact on flight growth for Europe asa whole. Traffic growth is riding on the outcome of the crisis as well as the speedof the recovery.

In some States, the economic situation remains severe, with the potential forsignificant falls in GDP. These risks are highly uneven across Europe.

Network changes and the route choice of airlines have a large influence on thenumber of overflights. The recent events in North Africa have an important impacton overflight figures for Malta and Cyprus mainly, but also in Italy and theBalkans. We have included only one of a number of different recovery patterns.

More generally, recent refinements in the forecast method will better capture therecent trends in overflights, but future network changes (eg. routings) are notmodelled by the forecast.

Tourism trends are quite variable and sensitive to the political climate in thedestination country. Although the growth at destinations that can substitute forNorth Africa, such as Canaries, was strong last year, it is now much less so. Afurther burst of growth, as a substitute, would be possible but is not included in theforecast.

Oil prices have been relatively stable, but at a very high level, for the last 12months. With fuel accounting for 30-40% or even more of costs of the airlines, thishas a significant effect on fares and cost of travel for customer. The jump in recentweeks of the price of crude oil in euro terms to record levels has not beenexplicitly factored into this forecast.

Participation of aviation in the Emissions Trading Scheme is integrated into theforecast. However, recent experience has shown that national taxes in particularcan rapidly change the local outlook for flight growth.

Terrorist attacks, wars and natural disasters, socio-economic changes andepidemics. The last seven years have not been quiet ones for aviation. There isno reason to believe the next seven years will be uneventful. The impact on air

traffic could be a temporary one, or more significant.



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4.3 Airport constraints

Constraints at airports mean that demand for some 134,000 flights cannot beaccommodated by 2018, which means a 1.2% reduction in growth over 2011-

2018. This is a similar total to last years forecast, even though the new forecastis lower. The location of the constrained airports also differs, with the newairport for Istanbul making a significant difference in Turkey.

This forecast uses a refreshed set of airport capacity figures covering some 159airports, building on:

The work done for the Long-Term Forecast 2010 (Ref. 9) and Challenges ofGrowth 2008 (Ref. 4),

The data submitted directly by STATFOR User Group members,

Data compiled by the EUROCONTROL Airport unit from submissions from around30 airports.

In the baseline scenario in 2018, demand for around 134,000 departures will not beaccommodated due to airport congestion (Figure 19, mainly in UK, Netherlands,France and Germany). This will reduce the growth in departures by 1.2% acrossEurope as a whole between 2011 and 2018. The reduction in growth will, of course,be more marked in the States with congested airports, and is more significant in thehigh-growth scenario.

There has been a geographical shift in the location of the most constrained airportsas some capacity figures have been revised downwards (the Netherlands, Germany,UK, Hungary, Switzerland and Austria) while others have been revised upwards (Italy,Belgium and Sweden). In particular, capacity in Turkey has been boosted to simulatethe presence of a third airport in the capital from 2017 (see Annex C.4). Overall, and

despite a lower traffic forecast, the number of unaccommodated flights is similar tothe one in the previous Medium-Term Forecast (excess demand of around 100,000departures in 2017 in MTF11, see Ref. 5 compared to 98,000 in this forecast).

Figure 19. Impact of airport constraints.

Unit: Reduction in IFR Departures when airport constraints are taken into account

Change in IFR Departures (000s) Percentage Change

20132012 2014 2015 2016 2017 2018 2012 2013 2014 2015 2016 2017 2018

High 24.3 27.5 80.6 140.0 210.8 197.7 342.7 0.2% 0.3% 0.8% 1.3% 1.8% 1.6% 2.8%

Base 16.2 17.9 42.9 73.3 120.2 97.9 134.0 0.2% 0.2% 0.4% 0.7% 1.1% 0.9% 1.2%

Low 10.3 11.5 21.6 43.5 70.5 56.3 69.3 0.1% 0.1% 0.2% 0.4% 0.7% 0.5% 0.6%



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4.4 High-Speed Train

Expansion of the high-speed train network reduces flight growth by just 0.4%over 7 years, though the local effects are more significant. This is a slightly

weaker impact than in the previous forecast.In the forecast model, an improvement in travel times for rail leads to a reduction indemand for air travel. Figure 20 summarises the number of IFR departures that arelost to rail because of improvements in the high speed train (HST) network. The effectis around 0.4% in total over the 7 years of the forecast; which is small on the scale ofthe network as a whole. However, on specific city-pairs, the effect can be quite large,especially at the end of the horizon. Because some HST projects have been delayed(not only due to the economic crisis but for some of them, because of environmentaland political issues), and owing to the lower levels of traffic, the current reduction intraffic is below the MTF11 results (see Ref. 1) in which around 47,000 IFR departureswere assessed to be removed in 2017 from the network. It is now expected that areduction of the same order would only happen 2018. The HST network is assumedto grow more slowly in the high flight-growth scenario, hence lower values for theHigh in the Figure 18.

Figure 20. Impact of high-speed train: reduction in IFR departures for ESRA08(top) and most affected States (bottom).

Unit: Reduction in IFR Departures when airport High-Speed train network development in Europe istaken into account


20132012 2014 2015 2016 2017 2018 2012 2013 2014 2015 2016 2017 2018

High . 4.7 16.1 25.7 29.2 34.2 44.4 0.0% 0.0% 0.2% 0.2% 0.3% 0.3% 0.4%

Base . 11.9 19.0 23.8 28.1 38.9 47.4 0.0% 0.1% 0.2% 0.2% 0.3% 0.3% 0.4%

Low . 11.6 20.4 25.8 29.5 42.3 49.2 0.0% 0.1% 0.2% 0.3% 0.3% 0.4% 0.5%


2013 2014 2015 2016 2017 2018 2012 2013 2014 2015 2016 2017 20182012

. 2.2 4.4 4.5 4.5 5.3 7.8 . 0.2% 0.4% 0.4% 0.4% 0.5% 0.7%France

. 0.3 0.6 0.9 0.9 3.1 5.3 . 0.0% 0.1% 0.1% 0.1% 0.2% 0.4%Germany

. . 1.7 3.4 3.6 3.5 3.6 . . 1.3% 2.5% 2.5% 2.5% 2.5%Lisbon FIR

. . 0.8 . . . . . . 0.3% . . . .Netherlands

. 4.0 8.1 12.2 15.7 16.8 16.9 0.6% 1.1% 1.7% 2.1% 2.2% 2.2%Spain

. 0.3 0.4 0.3 0.2 . . . 0.1% 0.1% 0.1% 0.1% . .Switzerland

0.1Turkey 5.2 3.8 4.4 5.0 11.8 16.2 0.0% 1.0% 0.7% 0.7% 0.8% 1.6% 2.1%

Base

.UK . 0.5 0.8 0.8 0.7 0.2 . . 0.0% 0.1% 0.1% 0.1% 0.0%

As far as States are concerned, Spain and Turkey will see the largest impacts:reduction of 17,000 and 16,000 IFR departures respectively in 2018 whichcorrespond to around 2% of traffic in each state. The effects are mainly due to theMadrid-Bilbao and Madrid-Alicante lines in Spain and Istanbul-Ankara and Istanbul-Konya for Turkey. France and Germany are less affected with around 8,000 and5,000 (respectively) fewer IFR departures.



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4.5 Emissions Trading Scheme (ETS)

The forecast models the impact of compliance with the EU Emissions TradingScheme. This is expected to reduce flights by around 25,000 by 2018, which is a

0.2% reduction in growth over the whole period.This air traffic forecast includes an Emissions Trading Scheme (ETS) component toaccount for the integration of aviation7 within the EU cap-and-trade scheme since thebeginning of 2012. The scheme affects all aircraft operators regardless of where theyare based provided that they operate flights departing from or arriving at anaerodrome located in the EU. Aircraft operators have now to surrender one allowancefor every tonne of CO2 emitted on a flight

8 to/from Europe. Under current rules, EUgives the aircraft operators permits to cover 85% of the allowances (for free); the restneeds to be bought from auctions or on the free market. The component implementedin this forecast estimates the induced increase in fares (conversion of the excessallowances into monetary terms) and the resulting reduction in demand.

Figure 21 summarises the estimated number of IFR departures that are lost becauseof the entry into force of the ETS. In 2018, the forecast number of flights is expectedto be reduced by 25,000 IFR departures, corresponding to a 0.2% reduction inpercentage terms for Europe

Figure 21. Impact of ETS: reduction in IFR departures for ESRA08 due toaviations participation in the scheme.

Unit: Reduction in IFR Departures when EU-ETS is taken into account


2012 2013 2014 2015 2016 2017 2018 2012 2013 2014 2015 2016 2017 2018

High 2.6 7.0 10.6 14.6 26.3 38.5 41.3 0.0% 0.1% 0.1% 0.1% 0.2% 0.3% 0.3%

Base 1.4 4.6 7.5 11.4 16.2 24.6 24.7 0.0% 0.0% 0.1% 0.1% 0.1% 0.2% 0.2%

Low 0.9 3.4 5.8 9.1 12.9 18.2 19.2 0.0% 0.0% 0.1% 0.1% 0.1% 0.2% 0.2%

7

Directive 2008/101/EC of the European Parliament and of the Council of 19 November 2008.8

The modelling has been performed on passenger flights only.


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4.6 Comparison with earlier forecasts

A combination of lower-than-expected flight growth in 2011, downward revisionfor economic growth in 2012 from 1.7% to 0%, lingering into weak growth in

2013, and fewer airport constraints pushes the forecast back by about twoyears.

Figure 22 compares this new forecast (MTF12) with the previous MTF (MTF11b), themid-year update of the MTF published in October 2011 (Ref. 1).

The actual traffic in 2011, which is used as the baseline for the MTF12, is lowerthan what was forecast even in late 2011. In particular, the previous MTF under-estimated the downturn in flights at the start of the Winter 2011-2012 timetable, sothe new medium-term forecast starts lower than the previous forecast expected tobe.

The MTF11b was based on an expectation of economic growth in 2012 of 1.7% inEurope. For the MTF12, this has been revised sharply downwards to 0%. Coupledwith the weak Winter traffic, we now forecast decline in 2012, which thereforeshifts traffic volumes at least one year to the right. Recovery to the 2008 peak isprobably delayed until 2014.

The growth rates for 2013 are weaker than previously forecast, with the weakItalian and Spanish economies, for example, weighing on flight growth.

From 2014-2018 growth rates are higher in MTF12 compared to MTF11b. Slowergrowth in the early years reduces the effects of airport capacity constraints, andindeed the new forecast includes additional capacity in Istanbul, representing theplanned new airport.

The combination of these factors leaves the current forecast some two years behind

the previous. In the high-growth scenario, the number of flights could match theprevious baseline forecast around 2015.

Figure 22. Forecast for the ESRA08 has been revised downwards (MTF11b dashedlines, MTF12 solid lines).



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5. GLOSSARY

AAGR Average annual growth ACC Area Control Centre AEA Association of European AirlinesB (in tables) Baseline ScenarioCFMU Eurocontrol Central Flow Management UnitCRCO Eurocontrol Central Route Charges OfficeESRA Eurocontrol Statistical Reference Area (see Annex B)EU27 European Union (27 States)EU European Union (abbreviation for EU27)FIR Flight Information RegionGDP Gross Domestic ProductH (in tables) High-Growth ScenarioHST High-Speed Train

IFR Instrument Flight RulesL (in tables) Low-Growth ScenarioMTF Medium-Term ForecastNM Network ManagerSES Single European SkySTATFOR EUROCONTROL Statistics and Forecast ServiceSTF Short-Term ForecastTR Traffic Region (a grouping of TZs)TZ Traffic Zone (State, except for Spain, Portugal, Belgium and

Luxembourg, Serbia and Montenegro)UIR Upper Flight Information Region

Detailed explanations of the above terms are available in EUROCONTROL Glossaryfor Flight Statistics & Forecasts (Ref. 6) and on the STATFOR web pages (Ref. 3).



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ANNEX A. FORECAST METHOD

The forecast reported here combines the EUROCONTROL Short- and Medium-

Term Forecast methods. The short-term forecast is largely driven by analysis ofrecent trends. The medium-term forecast takes into account a broader range ofeconomic and industry developments.

Short-Term Forecast Method

The short-term forecast focuses on time-series modeling of traffic trends month-by-month. The final result is in terms of numbers of flights per month per pair of zones orregions: within Europe origin-destination zones are used (groups of airports oftensmaller than States); outside of Europe, large regions are used (groups of States).Four separate forecasts (with differing horizons and time and geographical resolution)contribute to the forecast as a whole (see Figure 23):

The State-flow forecast method is the method developed in the legacy code. Ithas been used for several years for published short-term forecasts. It forecastseach State separately, and within the State, separate forecasts for a few mainflows: internals, overflights etc.

The zone or region-pair forecast is largely based on time-series methods forsome 8000 series.

The schedule method uses data from published schedules for future months, andcomparisons of previous schedules with actual flights.

The first years of the medium-term forecast (see below) also contribute a view offuture traffic.

The combined forecast is then capped by airport capacities, using the same method

as used in the medium- and long-term forecasts. Overflights are calculated using boththe trends identified in the short-term forecast, and the base-year flight patterns usedpreviously in the medium-term forecast. The result is a single forecast from whichshort- and medium-term views can be reported.

Figure 23. Summary of short-term forecast method.

Historical Archive:Monthly Airport-Pair Data

Short-term Forecast Medium-Term Forecast(Parts of method only)

Zone/Region-Pair

Forecast Method

Schedule

Forecast Method

Historical Archive:Published Schedule

Combine

Supporting Data:-Events-Calendars

State-Flow

Forecast Method

Apply annual

capacities

Initial Airport-PairForecast

Aligned Airport-PairForecast

Final Airport-Pair

Forecast

FinalForecast

Forecast

Overflights


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Medium-Term Forecast Method

STATFOR produces medium-term (seven years ahead) forecasts of annual numbersof IFR flight movements for volumes of airspace called traffic zones. Traffic zonesare 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 arepublished for the main region-to-region flows (Annex B.2 defines these traffic regions)on the STATFOR Interactive Dashboard (Ref. 2). Traffic flows are also categorised asinternals (within the traffic zone), arrival in or departure from the traffic zone, andoverflights (neither departing from nor landing in the traffic zone, but passing throughits airspace).

The forecast is published annually, at the beginning of the year and refreshedmid-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;

The demand-side model focuses on economic growth and its influence ondemand from travellers and shippers;

A supply-side model is used to forecast growth directly on airport pairs, andreplaces the traditional demand-side model when appropriate;

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 baselineyear, plus more recent trends captured by the short-term forecast method.

The forecast method is continuously being refined to improve the quality of theoutputs. For this forecast, the emissions trading scheme is integrated into theforecasting process, and the supply-side modeling has been adapted to handle betterthe recent cases of decline over several years for some flows. The forecast process issummarised in Figure 24.

The review body for STATFOR is the STATFOR User Group. This has members fromcivil aviation authorities and air navigation service providers, and from other industryorganisations. Participants are typically actively involved in statistics or forecasting.The STATFOR User Group meets once or twice per year. It reviews the inputs to themedium-term forecast and the resulting draft forecast. The aim of the review processis to produce a forecast which is consistent on a European level and acceptable to

member States. This does not necessarily mean the forecast is the same as thatproduced nationally.

The forecast is built from three main datasets.

A historical database of the STATFOR monthly statistics (derived from CRCO,Network Manager9 and National sources) for the last ten or more years at airport-pair level;

9Network Manager as the new name of the former CFMU


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A baseline from Network Manager and National sources that includes routinginformation;

The set of scenario inputs.

Figure 24. Preparation process of the Medium-Term Forecast.

The Medium-Term Forecast uses three scenarios which differ in terms of theassumptions. The low-growth and high-growth scenarios between them capture themost-likely range of future growth in flight movements; the baseline scenario indicatesa likely position within this range. The main parts of the scenario data are:

Economic growth, summarised as GDP growth forecasts in real prices in localcurrency; (Annex C.1)

Low-cost growth, which adds additional flight movements, on top of economicgrowth to reflect new flight movements generated by low-cost airlines; (Annex

C.2)

High-speed train network, summarised as changes in rail travel time on city pairsserved by high-speed links, compared to the baseline year; (Annex C.3)

Airport capacity, in movements per year for major airports; (Annex C.4)

Load factors, which are assumed to change linearly from a current level to afuture level that can vary with region and scenario; (Annex C.5)

Network change, a percentage adjustment to arrival and departure movementsper traffic zone, which can be used - given supporting data - to represent in themodel the effects of consolidation, irregularities in the baseline, or local one-offeffects; (Annex C.6)



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Demographic change, which has a very small impact in the demand-side model.These data are derived from UN population forecasts.

Emission Trading Scheme characteristics, prices of CO2 allowances, cap onhistorical CO2 emissions and the level of auctioning in the ETS determine the

additional costs of airlines from aviation participation in the ETS. The MTF modelexpects that these are passed onto passengers and therefore reduces thepassengers' demand accordingly. (Annex C.8)

The medium-term forecast is prepared in two stages: first the airport-pair forecast;then the traffic per volume of airspace, calculated from this using estimates of routingfrom airport to airport. Published tables, reports, graphs and maps are derived fromthe second of these, for short- and medium-term forecast alike.

Each airport pair is grown as follows:

All-cargo flights are grown based on GDP growth.

Small airport pairs (< 25 flights per year) are kept constant.

Growth of military flight movements in the first year of the forecast follows theaverage of the last three years for the traffic zone as a whole, with a maximumchange of 5%, and is kept constant afterwards.

Business aviation flights are grown based on observed trend at a State leveltogether with economic growth if this is a useful explanatory variable for this State.

For other traffic, the use of supply-side or demand-side approach is considered.Supply-side is used if traffic matches one of the standard histories (circular flights,long-term stable or declining traffic, direct relationship to GDP) and if demandexceeds the supply. Otherwise, it is demand that drives and limits the growth.

In the demand-side, passenger numbers are estimated from flight counts, aircraft

type and load factors, then grown according to GDP growth and the elasticity forthis region-pair, then converted back to a number of flights using a number ofseats-to-flights relationships calibrated on historical data.

The first years of the forecast are aligned with the short-term forecast.

The growth of movements on an airport-pair may then be reduced if there hasbeen a reduction in journey times by HST since the baseline year, adjusted forlow-cost growth in the traffic zone and for any network change assumptions (bytraffic zone, airport, or airport pair) and capped by airport capacity.

The resulting growth per airport pair is the airport-pair forecast. The final step is tocalculate how many flights are generated in each airspace by these airport-to-airport

flights. This is done using a combination of the routings through airspace observed inthe baseline year and trends in overflight growth per traffic zone.

At each stage, the results are validated using any available data, such as from theSTATFOR User Group or from the Industry Monitor. For example: base-year airportmovements are compared with statistics published by airports; first-year growth iscompared with known airline plans; long-term growth is compared with otherforecasts in terms of flights or passengers. Such comparisons are typically a matter ofjudgement, rather than a precise numerical correlation.



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ANNEX B. TRAFFIC REGION DEFINITIONS

B.1 ESRA08

The EUROCONTROL Statistical Reference Area (ESRA) is designed to include asmuch as possible of the European Civil Aviation Conference (ECAC) area for whichdata are available from a range of sources within the Agency. It is used for high-levelreports from the Agency, when referring to 'total Europe'. The ESRA changes onlyslowly with time; a region is added to the ESRA only when there is a full year's datafrom all sources, so that growth calculations are possible. ESRA08 was introduced inthe Medium-Term Forecast report issued in february 2009. It is now used as a basisfor comparison at European level in the forecasts. Note that the EUROCONTROLforecast includes also regions outside of the ESRA (eg. Armenia and Latvia) thoughstill within ECAC.

Figure 25. The EUROCONTROL Statistical Reference Area.

Traffic zones are represented by an aggregate of FIRs & UIR of States. These do nottake delegation of airspace into account. For individual States, the differencesbetween charging areas and ACCs can have a big impact on overflight counts (andthus on total counts where the total is dominated by overflights). For the ESRA as awhole, there is only a small proportion of overflights, so that the difference betweenan FIR and an ACC definition is small.

B.2 Traffic regions

For this forecast, traffic flows are described as being to or from one of a number oftraffic regions listed in Figure 26 (for example inAnnex D). Each region is made up ofa number of traffic zones. Traffic zones are indicated in the table for brevity by thefirst letters of the ICAO location codes. The traffic regions are defined for statisticalconvenience and do not reflect an official position of the EUROCONTROL Agency.

The ESRA was defined in the previous section. For flow purposes, this is split into aNorth-West region mostly of mature air traffic markets, a Mediterranean regionstretching from the Canaries to Turkey and with a significant tourist element, and an



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Eastern region. The Other region includes the Baltic States and Oceanic. TheFormer CIS Region includes Armenia and Azerbaijan (members of ECAC). In timethese will join the ESRA. More details are available in STATFOR GeographicalHierarchy document (Ref. 7).

Figure 26. Regions used in flow statistics.

ICAO region/country

ESRA

ESRA1 ESRA North-West EB, ED, EF, EG, EH, EI, EK, EL, EN, ES, ET, LF, LN, LO, LS

ESRA2 ESRA Mediterranean GC, LC, LE, LG, LI, LM, LP, LT

ESRA3 ESRA East BK, EP, LA, LB, LD, LH, LJ, LK, LQ, LR, LU, LW, LY, LZ,UK

World 1 North Atlantic BG, BI, C, EK, K, P (except KG)

World 2 Middle-East O, L

World 3 North-Africa DA, DT, GM, HE, HL, HS

World 4 Southern Africa D, F, G, H, MR (except DA, DT, HE, HL, HS, GM, GE, and ESRA)

World 5 Far-East R, V, Z (except ZZZZ)

World 6 Oceania KG, N, P, Y (except NO)

World 7 Mid-Atlantic M, T (except MR)

World 8 South-Atlantic S

World 9 Former CIS Region U (except areas in ESRA)

Other Other EE, EN, EV, EY, GE, GM, LP, LX, Swanwick Oc., Bodo Oc., Santa Maria FIR

B.3 Functional Airspace Blocks

On top of the traffic zones, this report also presents the forecast of IFR movements from2012 to 2018 for Functional Airspace Blocks (FAB). A FAB is a block of airspace basedon operational requirements regardless of the State boundaries (Figure 27). FABinitiatives (definitions) are constantly evolving according to the targets defined to improvethe performance of the European air traffic management network. The FAB used in this

reports refers to the January 2011 definition.

Figure 27. FAB initiatives as of January 2011. (Source: EUROCONTROL PRU)



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Figure 29. Since the previous forecast, the economic outlook for EU27 hassignificantly worsened.

Figure 30. Summary of changes in GDP forecasts for 2012-2018: nearly allStates see reduction in 2012 and 2013.



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Figure 31. GDP Growth by Traffic Zone

Source: 2010-2018 from Oxford Economics Ltd, Jan2012

Comments: Real GDP Growth in local currency.Units: Growth per year. Data last updated: 06/02/2012

Actual Base20102009 2011 2012 2013 2014 2015 2016 2017 2018

Albania 2.8% 3.8% 3.0% 4.2% 4.2% 4.5% 4.5% 4.5% 4.5% 4.5%

Armenia -14% 2.1% 4.0% 4.3% 4.3% 4.6% 5.0% 5.0% 5.0% 5.0%

Austria -3.4% 2.3% 3.0% 1.0% 2.1% 2.2% 2.1% 2.1% 1.9% 1.9%

Azerbaijan 9.3% 5.0% 0.4% 4.0% 5.0% 5.5% 5.5% 5.5% 5.5% 5.5%

Belarus 0.2% 7.6% 5.0% 1.5% 4.3% 3.7% 3.3% 3.3% 3.3% 3.3%

Belgium/Luxembourg -2.7% 2.3% 2.0% 0.9% 2.9% 2.5% 2.1% 2.1% 1.9% 1.9%

Bosnia-Herzegovina -3.0% 0.5% 2.2% 2.1% 5.0% 5.5% 5.5% 5.5% 5.3% 5.3%

Bulgaria -5.6% 0.3% 2.2% 2.4% 5.3% 5.8% 5.9% 5.9% 5.7% 5.7%

Canary Islands -3.7% -0.1% 0.7% 0.2% 1.6% 1.7% 1.8% 1.8% 1.7% 1.7%

Croatia -6.0% -1.2% 0.4% 1.2% 2.0% 3.2% 3.6% 3.6% 3.2% 3.2%

Cyprus -1.7% 1.0% 1.1% 0.6% 1.5% 2.2% 3.5% 3.5% 3.5% 3.5%

Czech Republic -4.0% 2.2% 2.0% 1.4% 2.8% 3.1% 3.1% 3.1% 2.9% 2.9%Denmark -5.2% 1.7% 1.1% 1.2% 2.2% 2.3% 2.3% 2.3% 2.3% 2.3%

Estonia -14% 3.1% 7.2% 2.5% 4.2% 4.8% 4.7% 4.7% 4.5% 4.5%

FYROM -1.0% 1.7% 4.2% 2.8% 3.0% 4.5% 4.0% 4.0% 3.7% 3.7%

Finland -8.3% 3.6% 3.0% 1.3% 2.8% 3.1% 2.7% 2.7% 2.6% 2.6%

France -2.6% 1.4% 1.6% 0.3% 1.6% 2.0% 2.0% 2.0% 1.9% 1.9%

Georgia -3.8% 6.4% 5.6% 4.9% 5.5% 5.5% 5.2% 5.2% 4.9% 4.9%

Germany -4.7% 3.6% 2.9% 0.9% 2.0% 2.1% 2.0% 2.0% 1.9% 1.9%

Greece -2.3% -4.4% -6.2% -6.1% -2.0% -0.0% 1.8% 1.8% 2.1% 2.1%

Hungary -6.5% 1.1% 1.0% 0.7% 2.7% 3.4% 3.4% 3.4% 3.2% 3.2%

Iceland -6.9% -4.0% 2.1% 1.8% 2.9% 3.0% 2.8% 2.8% 2.7% 2.7%

Ireland -7.0% -0.4% 1.2% 0.5% 3.1% 3.4% 3.7% 3.7% 3.9% 3.9%

Italy -5.2% 1.2% 0.6% -0.7% 0.2% 0.9% 1.3% 1.3% 1.4% 1.4%

Latvia -18% -0.3% 4.3% 3.5% 5.8% 6.2% 5.7% 5.7% 5.3% 5.3%

Lisbon FIR -2.5% 1.3% -1.3% -2.9% 0.9% 1.7% 1.6% 1.6% 1.7% 1.7%

Lithuania -15% 1.3% 5.8% 3.7% 6.2% 6.3% 6.2% 6.2% 5.6% 5.6%

Malta -3.3% 2.7% 2.0% 1.5% 2.6% 3.0% 3.0% 3.0% 3.0% 3.0%

Moldova -7.3% 6.9% 6.5% 4.0% 5.5% 5.5% 5.5% 5.5% 5.5% 5.5%

Netherlands -3.5% 1.6% 1.8% 0.7% 2.0% 2.2% 1.9% 1.9% 1.8% 1.8%

Norway -1.6% 0.3% 1.2% 1.8% 2.2% 2.4% 2.3% 2.3% 2.2% 2.2%

Poland 1.6% 3.8% 4.2% 2.8% 4.1% 4.1% 3.8% 3.8% 3.5% 3.5%

Romania -6.9% -1.5% 1.2% 2.8% 5.2% 5.8% 5.7% 5.7% 5.6% 5.6%

Russian Federation -7.8% 4.0% 3.8% 4.4% 4.3% 3.6% 3.5% 3.5% 3.5% 3.5%

Santa Maria FIR -2.5% 1.3% -1.3% -2.9% 0.9% 1.7% 1.6% 1.6% 1.7% 1.7%

Serbia&Montenegro -3.1% 1.7% 2.7% 2.8% 5.0% 5.5% 5.5% 5.5% 5.3% 5.3%

Slovakia -4.8% 4.0% 2.9% 1.1% 3.5% 4.3% 4.7% 4.7% 4.0% 4.0%

Slovenia -8.4% 1.3% 1.1% 1.0% 2.2% 3.1% 3.5% 3.5% 3.4% 3.4%

Spain -3.7% -0.1% 0.7% 0.2% 1.6% 1.7% 1.8% 1.8% 1.7% 1.7%

Sweden -5.3% 5.4% 4.2% 1.5% 2.5% 2.1% 1.9% 1.9% 1.9% 1.9%

Switzerland -1.9% 2.7% 1.9% 0.6% 1.9% 2.0% 2.0% 2.0% 1.9% 1.9%

Turkey -4.8% 9.0% 7.7% 2.2% 5.6% 6.0% 5.5% 5.5% 5.4% 5.4%

UK -4.9% 1.8% 0.9% 1.0% 2.6% 2.8% 2.7% 2.7% 2.5% 2.5%

Ukraine -15% 4.2% 4.8% 4.4% 5.9% 6.5% 6.3% 6.3% 5.8% 5.8%



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Figure 32. GDP Growth by Origin-Destination Zone

Source: 1993-2004 from STATFOR records. 2005 onwards from Oxford Economics Ltd, Jan 12.

Comments: Real GDP Growth in local currency.

Units: Growth per year. Data last updated: 07/02/2012

Actual Base

20102009 2011 2012 2013 2014 2015 2016 2017 2018

China 9.2% 10% 9.1% 8.5% 8.8% 8.8% 8.3% 7.9% 7.5% 7.5%

India 7.0% 8.7% 7.1% 6.5% 8.7% 9.2% 8.6% 7.9% 7.6% 7.6%

Figure 33. GDP Growth by Traffic Region

Source: 2005 onwards updated from Oxford Economics Jan12

Comments: Real GDP Growth.

Units: Growth per year. Data last updated: 07/02/2012

Actual Base

20102009 2011 2012 2013 2014 2015 2016 2017 2018

ESRA East -3.6% 2.5% 3.1% 1.3% 2.7% 4.1% 4.4% 4.1% 4.6% 4.6%ESRA Mediterranean -4.4% 1.7% 1.2% -0.8% 0.8% 1.8% 2.4% 2.7% 2.8% 2.8%

ESRA North-West -4.1% 2.4% 2.0% 0.3% 1.8% 2.3% 2.3% 2.2% 2.4% 2.4%

Far-East -3.7% 5.6% 0.9% 2.3% 4.0% 3.3% 2.7% 2.4% 2.9% 2.9%

Former CIS Region -5.4% 4.8% 4.6% 4.1% 4.4% 4.8% 4.3% 4.1% 5.0% 5.0%

Mid-Atlantic -4.7% 4.3% 3.6% 3.5% 4.6% 4.6% 4.0% 3.5% 4.3% 4.3%

Middle-East 1.2% 4.2% 4.9% 3.5% 4.6% 4.6% 4.6% 4.5% 5.3% 5.3%

North Atlantic -3.4% 3.0% 1.8% 2.5% 2.7% 3.0% 3.0% 2.8% 3.5% 3.5%

North-Africa 1.6% 4.1% -12% 9.2% 6.7% 5.8% 4.9% 4.7% 5.2% 5.2%

Oceania 1.2% 2.5% 1.9% 3.0% 3.8% 3.3% 2.6% 2.2% 2.6% 2.6%

Other -16% 1.1% 6.2% 2.4% 4.9% 5.9% 5.7% 5.3% 5.9% 5.9%

South-Atlantic 0.0% 6.0% 6.6% 3.9% 4.0% 4.3% 3.7% 3.4% 4.0% 4.0%

Southern Africa 3.7% 6.1% 5.6% 5.9% 6.1% 6.0% 5.4% 5.2% 6.2% 6.2%

C.2 Low-Cost Carrier Growth

The starting point is the market share of low-cost carriers in each traffic zone inSeptember 2011. The low-cost carriers are defined by means of a list (Ref. 8), moredetailed data on this segment are available in STATFOR web page (Ref. 3). For thepurposes of this analysis only, the market share is defined as the share ofpassengerflights (i.e. excluding the military, cargo and business aviation since these areforecasted separately, seeAnnex A).

The observed market share in 2011 is assumed to continue to change according tolow-, base- and high- scenarios. These scenarios are based on observed averageannual growth across all States in the ESRA over 2005-2011, which is 0.9 percentagepoints per year, with a high rate of 2.9 points and low of -0.1.

These rates are rather different to previously used, as it is apparent that growth in thelow-cost market has for the most part slowed down considerably. The low valueindicates that in 25% of historical observations we saw an annual decrease in marketshare: as a projection this becomes a State seeing a 1% share decline for low-costover 7 years. The high value was seen for 25% of observations (TZ and year), but thedata suggest that it is only really applicable in States with less traffic, so we used halfthis rate for States with more than 25,000 departures in the month.



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The evidence is that low-cost carrier market share growth is partly new, generatedtraffic (for example attracted by the price), and partly replacement or re-badging ofexisting traffic. In the forecast, approximately half of the difference between thebaseline and future values shown in Figure 34 is converted to extra growth in flights.

Figure 34. Low-Cost effects by Traffic Zone

Source: STATFOR Analysis and modelling

Comments: Represents additional growth for Low-Cost, but only the baseline year is a true statistic for low-co

Units: Percentage Additional Growth Due to Low-Cost Growth. Data last updated: 06/02/2012

Actual Low Base High

2011 20182018 2018

Albania 41% 38% 42% 46%

Armenia 0% 0% 2% 6%

Austria 21% 21% 24% 27%

Azerbaijan 0% 0% 2% 6%

Belarus 0% 0% 2% 6%

Belgium/Luxembourg 15% 15% 19% 21%

Bosnia-Herzegovina 7% 11%7% 19%

Bulgaria 15% 14% 21% 36%

Canary Islands 34% 34% 38% 44%

Croatia 20% 20% 23% 31%

Cyprus 23% 22% 29% 44%

Czech Republic 26% 25% 32% 47%

Denmark 13% 13% 17% 19%

Estonia 11% 11% 14% 21%

FYROM 6% 6% 7% 8%

Finland 21% 21% 23% 27%

France 18% 18% 21% 24%

Georgia 0% 0% 2% 6%Germany 29% 32%29% 34%

Greece 23% 23% 26% 28%

Hungary 15% 15% 18% 25%

Iceland 2% 2% 5% 12%

Ireland 47% 46% 53% 68%

Italy 37% 36% 40% 42%

Latvia 11% 10% 17% 32%

Lisbon FIR 32% 32% 35% 42%

Lithuania 26% 25% 32% 47%

Malta 31% 30% 37% 52%

Moldova 3% 3% 7% 15%

Netherlands 22% 22% 25% 28%

Norway 22% 22% 25% 28%

Poland 25% 24% 31% 46%

Romania 26% 25% 32% 47%

Santa Maria FIR 0% 0% 2% 6%

Serbia&Montenegro 9% 9% 13% 21%

Slovakia 24% 23% 30% 45%

Slovenia 3% 2% 9% 24%

Spain 46% 41% 46% 50%

Sweden 20% 20% 23% 26%

Switzerland 16% 16% 20% 22%



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Actual Low Base High

2011 20182018 2018

Turkey 19% 19% 22% 25%

UK 46% 46% 48% 50%

Ukraine 0% 0% 4% 12%

C.3 High-Speed Train Network Development

The information on improvements in the high-speed train (HST) network between2011 and 2018 on is based on information provided by the Union Internationale desChemins de Fer and many websites of a number of specific HST projects. The modelconverts improved rail travel times into increased market share for rail, and thus fewerpassengers travelling by air.

Figure 35 indicates the changes in rail travel time in the baseline scenario. In the low-and high-growth scenarios, the times remain the same, but they happen earlier and

later, respectively. The distance indicated is based on an average location of airportsassociated with the city, not on city-centre locations. It is also a direct distance, sounderestimates the distance in particular where the sea intervenes, such as London-Amsterdam or Istanbul-Bursa.

For the 2012 medium-term forecast, the travel times have been updated, and theyears when the projects come into operation have been reviewed. In practice, therehave been few changes, since, in the medium-term the HST projects are largelyalready in progress and appear to have been relatively little affected by the economicslowdown.

Figure 35. High-Speed Train Times

Source: Actuals from on-line timetables. Plans from UIC, TEN-T and elsewhere.Comments: HST projects to be finalised 2012-2018.

Units: Travel time (minutes). Data last updated: 03/02/2012 Distances estimated from airport locations.

Distance Rail Time (mins) Speed (km/h)

2011 2012 2013 2014 2015 2016 2017 2011 2012 2013 2014 2015 2016 2017Km

B 355 720 . . . . . 120 30 . . . . . 177Sivas

BBURSA (MIL 317 240 . . . . . 130 79 . . . . . 146

Ankara

B 519 900 . . . . . 200 35 . . . . . 156IZMIR-ADNA

B 282 225 . 145 . . . . 75 . 117 . . . .Lyon

B 486 340 . 240 . . . . 86 . 121 . . . .Marseille

BNimes 484 350 . 250 . . . . 83 . 116 . . . .

Bale Mulho

BParis 398 210 . . 180 . . . 114 . . 133 . . .

Barcelona Lyon B 530 460 . . . . . 180 69 . . . . . 177

Bilbao B 91 130 . . . . 40 . 42 . . . . 136 .SAN SEBAST

B 195 180 . . 80 . . . 65 . . 146 . . .Bale Mulho

BFrankfurt 386 390 . 290 . . . . 59 . 80 . . . .

DIJON/DARO

BStrasbourg 242 220 . 130 . . . . 66 . 112 . . . .

Erfurt Leipzig B 102 70 . . . . 39 . 87 . . . . 156 .



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Eurocontrol - Medium Term Forecast - Flights 2012-2018

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