Catchment area analysis

Transcription

1 Civil Aviation Authority Airport market power assessments Catchment area analysis Working Paper October 2011

2 Table of contents 1. Introduction Surface access travel times Passenger usage of airports by surface travel time Geographic distribution of actual airport usage Conclusions Annex A. Detailed surface travel time analysis... 48

3 1. Introduction Purpose of this paper 1.1 The CAA has committed to carrying out assessments of the market power held by Heathrow, Gatwick and Stansted. These assessments will form part of the evidence base informing the approach to the upcoming regulatory reviews ( Q6 ) for these three airports. They may also provide useful evidence on other issues such as disputes between airports and airlines (e.g. price discrimination investigations under section 41 of the Airports Act 1986), complaints about compliance with the EU Airport Charges Directive (ACD), and the development of economic licences for airports under the Government s proposed reforms of economic regulation. 1.2 The CAA s initial thinking on these competition assessments will be published by the end of 2011, in order to inform the discussions on the appropriate ways of regulating the three airports. More information on this process and how the competition assessments relate to the price controls can be found in the CAA s consultation document Setting the scene for Q6, which was published in July This working paper forms part of the CAA s work on the market power assessments. It pulls together evidence on the catchment areas of the four major London airports, which can be used to inform the analysis of the sources of competitive constraints between relevant near and neighbouring airports. This working paper provides a basis for further work on defining the relevant geographic market(s) and the competitive constraints on the three airports being assessed. The paper mainly makes use of airport statistics and survey data held by the CAA. 1.4 This paper does not attempt to draw any direct conclusions regarding the market power of Heathrow, Gatwick and Stansted, from the analysis presented in this paper. Instead, it provides evidence that will support this assessment. While this working paper focuses on the catchment areas of only the four major London airports, for which the most reliable data are available, the competitive constraints imposed by regional airports will be considered at greater length in the CAA s initial assessments that are expected to be published in December Distinguishing catchment area analysis and geographic market definition 1.5 Although catchment area analysis can provide useful evidence regarding an airport s passenger base, and the potential and strength of constraints from its competitors, it is important to note the distinction between catchment area analysis and geographic market definition. 1.6 Catchment area analysis is a way of estimating the geographic area from which a large proportion of an airport s outbound passengers originate, or 1 CAA, Q6 Setting the Scene: Review of Price and Service Quality Regulation at Heathrow, Gatwick and Stansted airports - consultation document, July 2011, available at Catchment area analysis 3

4 inbound passengers travel to, and their geographic distribution within this area. The size of catchment areas and overlaps between catchment areas of neighbouring airports could provide useful evidence of the potential for, and strength of, competition between these airports. 1.7 By contrast, geographic market definition analyses the area over which passengers would substitute to other airports in light of a small but significant non-transitory increase in price of 5 to 10% above the competitive price level at the original airport. Consequently, while catchment areas can provide useful evidence, they should not be taken as establishing which airports are within the same geographic market, for two main reasons: Catchment areas illustrate overlaps between all airports in the regions being considered. However, the services offered at these airports may be differentiated in such a way that limits competition between them. Consequently there could be fewer airports in the same relevant market than indicated by the catchment area analysis. Conversely, catchment areas might in some circumstances be smaller than the relevant geographic market, in particular where catchment areas are based on current airport usage patterns. Two neighbouring airports with similar services and prices might have relatively small catchment areas with little or no overlaps, but any increase in price or reduction in service quality might result in a significant shift of passengers from one airport to another, suggesting they might be in the same geographic market. 1.8 Catchment area analysis could therefore provide an initial indication of the patterns of substitution between the various neighbouring airports, but methodological differences between catchment area analysis and the definition of the relevant market framework mean that supplementary evidence would need to be considered when defining the relevant geographic market. Data and methodological issues 1.9 This paper makes use of catchment area analysis using surface access travel time and actual usage data. As with all empirical methods, these have a number of advantages and disadvantages, which will be discussed in the relevant sections. However, a number of general points can be made: No technique in isolation is likely to provide definitive evidence on the geographic market definition and the strength of competitive constraints between airports. All quantitative techniques require some judgment to be applied, either through the determination of required input assumptions, the appropriate structuring of the modelling, or in the interpretation of the results. By their nature, quantitative techniques all rely on the availability, quality and robustness of the data that are used for the analysis. This raises a number of issues. Catchment area analysis 4

5 In most areas, only historical data can be captured that cannot, therefore, capture the potential for airports, airlines or passengers to change their behaviour and preferences in the future (an issue that is particularly relevant to forward-looking analysis of airport competition). Where prevailing prices diverge from the competitive price level there is a risk that analysis based on historical data might lead to defining the relevant market too widely (if prevailing prices are above the competitive price) or too narrowly (if prevailing prices are below the competitive level), which might also affect the reliability of the methods used in this paper. The structure of this paper 1.10 The rest of this paper is structured as follows: Chapter 2 focuses on surface travel times to analyse the potential willingness and ability to travel of the population originating in relevant districts; Chapter 3 presents analysis of catchment areas for each of the London airports on the basis of both surface travel times and historical passenger surface access travel time distributions; Chapter 4 analyses catchment areas that consider the geographic distribution of passengers; and Chapter 5 summarises and set outs what the key implications could be inferred from the analysis in this paper. Views invited 1.11 This paper presents analysis of various types of catchment areas and their overlaps for the four major London airports. We would welcome stakeholders views on the information presented in this paper, in particular where there are important catchment area considerations that are not covered, or where stakeholders interpret the information differently At this stage, we have a preference for dialogue and discussion with stakeholders, rather than a detailed written response to this paper. There will be a number of opportunities to comment on the contents of this paper going forward, including by: attending the workshop scheduled for Tuesday 15 November at 10am, at the CAA s London offices, where the CAA will bring together the emerging evidence that is informing the competition assessments; responding to the CAA s initial assessments expected to be published in December 2011; and/or Catchment area analysis 5

6 responding to later consultations that form part of the Q6 price control process More generally, we encourage stakeholders to share their views with the project team. If you would like to discuss the contents of this working paper, in the first instance please contact Alexander Dünki on / alexander.dunki@caa.co.uk You can also contact: Isabell Kohten on / isabell.kohten@caa.co.uk Alina Jardine Goad on / alina.jardine@caa.co.uk Chris Hemsley on / chris.hemsley@caa.co.uk Catchment area analysis 6

7 2. Surface access travel times Introduction 2.1 This chapter focuses on surface travel times to analyse the potential willingness and ability to travel of the population originating in relevant districts, in order to derive an indication of the potential scope for competition between the London airports, and how the usage of these airports could potentially evolve. 2.2 Surface access travel time tends to be a major consideration in passengers choice of airport, and one that neither the passengers nor the airlines or airports can influence directly in the short to medium term. Analysing the surface access travel times can then provide an indication of the potential usage of an airport and the potential for passengers to make choices between different airports, while the catchment area analysis in chapters 3 and 4 takes account, to varying degrees, of the actual choices made by passengers and underlying market conditions. 2.3 The amount of time taken to travel to an airport has been commonly used to define its catchment area. Airlines and airports, along with industry analysts, have stated that they assess the population distribution and economic activity within a certain distance or travel time to the airport. 2 The European Commission also used this technique for geographic market definition. For example, in the context of its assessment of Berlin airports, it chose a 100km/1h travel distance/time for short haul and a 300km distance for international airports 3. Methodology 2.4 Surface access travel times (hereafter surface travel times) can be mapped to establish the proximity of surrounding districts to a particular airport, according to the time taken to travel by surface transport from the centroid of a district to a particular airport. The maps are a factual representation of travel times and do not take account of actual passenger activity or population density. 2.5 Several airlines and airports have also previously made use of isochrones to establish the potential passenger base when analysing the profitability of opening or expanding operations at an airport 4. Similarly, airports have illustrated their catchment area using isochrones and income distribution maps to market themselves to prospective airlines or to existing airlines looking to expand operations, by giving a sense of the size and attractiveness of their passenger base 5. 2 Examples of catchment areas are available on the anna.aero Route Shop 3 German Airport Performance The economic market power of Amsterdam Airport Schiphol para226 April Evidence submitted to the CAA. 5 Evidence submitted to and interviews with the CAA. Catchment area analysis 7

8 2.6 The CAA and the Office of Fair Trading (OFT) have also previously used travel time to define catchment areas in the form of isochrones. For indicative purposes, the CAA has previously used 120 minutes to construct the drive time isochrone for UK short haul leisure passengers and 60 minutes for UK international short haul business passengers in Supporting Paper II of its Initial price control proposals for Heathrow, Gatwick and Stansted airports published in December The OFT has also previously analysed catchment area overlaps between the London airports based on catchments areas of 60, 90 and 120 minutes in BAA The OFT s reference to the Competition Commission in April However, while the CAA s previous work made use of the Mappoint software to construct isochrones, the surface access travel time maps used in the current paper are constructed on the basis of a Department for Transport (DfT) airport surface access dataset 6. Although Mappoint provides estimates of drive times, with the possibility to vary assumptions regarding congestion and other factors, the data ignore some important means of public transport available to passengers travelling to the London airports, such as rail links. The principal advantage of the DfT dataset is that it contains both road and rail travel time estimates from the centre of each district in England and Wales, which allows the analysis to account for two ways for passengers to travel to an airport. The surface travel time estimate is given as the lowest value of the rail and road travel times. 2.8 However, unlike Mappoint, the DfT data measure the surface travel time from the centroid of planning districts, as opposed to providing flexibility as to the start point of an estimate. This might mean that the estimates could slightly misstate an airport s catchment area at the fringes, especially in geographically larger districts. However, using surface access travel times calculated on the basis of more than one mode of transport means that the analysis has taken into account the possibility of inter-modal substitution in surface access, and would be more likely to be representative of actual passenger surface travel times. 2.9 Surface travel time maps are useful in capturing the potential for airports to compete to attract the population originating in a given area. However, due to their construction, the surface travel time maps do not provide evidence regarding actual and historical competition for backward-looking analysis. In light of this, it would be necessary to compare this analysis of the potential for competition with catchment areas drawn on the basis of passenger behaviour, which will be undertaken in chapters 3 and 4. Surface travel time maps 2.10 The surface travel time maps in figure 1 below show which districts are within particular travel times of the four largest London airports 7. The red districts 6 The DfT dataset used in this paper was previously used for the traffic forecasts produced for the Air Transport White Paper of Due to its small size, narrow catchment area and focus on business passengers, London City airport has been omitted from the analysis in this paper. Catchment area analysis 8

9 are within 60 minutes, while the orange and yellow districts are within 90 and 120 minutes respectively. These three time thresholds have been chosen to provide an indication of the potential for competition on the basis of travel times alone. In order to take a view on the appropriate travel time thresholds, it is useful to consider how far passengers are willing to travel to reach an airport, as discussed in chapter 3. Figure 1 - Surface travel time maps for the four London airports Heathrow Gatwick Luton Stansted Source: CAA analysis of DfT surface access data Red: 60 minutes; Orange: 90 minutes: Yellow: 120 minutes 2.11 The districts within 90 minutes of each London airport (represented by the red and orange areas taken together) cover a considerable portion of the same geographical area. This suggests that there could be a significant degree of overlap between the catchment areas of the four London airports, which is considered in figure 2. It is also notable that there are a number of districts lying within 120 minutes of each airport, which are located a considerable distance from their respective airport. For example, the Bath district lies within 120 minutes of Heathrow. This pattern appears to reflect the proximity of these districts to rail interchanges with fast connections to London. Catchment area analysis 9

10 Surface travel time map overlaps 2.12 Analysing the extent to which surface travel time catchment areas overlap for the four London airports can provide a useful indication of the potential for competition between them to attract each district s population. On the basis of the analysis carried out in chapter 3, 90 minutes and 120 minutes appear to be reasonable benchmarks for passengers overall and for various segmentations. Figure 2 - Overlap of districts within 90 minutes Source: CAA analysis of DfT surface access data Blue: 1 airport; Light blue: 2 airports; Light red: 3 airports; Red: 4 airports 2.13 Figure 2 shows the overlaps of the four major London airports surface travel time catchment areas based on a 90 minutes threshold. A substantial number of districts (those coloured in red) including inner London and districts on its outskirts can be seen to be located where the catchment areas of all four London airports overlap. Several other districts are covered by the catchment areas of 2 or 3 airports, particularly to the north and south west London Figure 3 presents the scope for catchment area overlaps using airport catchment areas that include the population lying within a 120 minute surface travel time of the airport. Catchment area analysis 10

11 Figure 3 - Overlap of districts within 120 minutes Source: CAA analysis of DfT surface access data Blue: 1 airport; Light blue: 2 airports; Light red: 3 airports; Red: 4 airports 2.15 In figure 3, the overall area lying within the catchment area of at least one London airport is considerably larger than in figure 1 (which would be expected as the catchment area definition is broader). Further, the number of districts which are covered by three to four London airports is more significant, particularly to the west of London. Population densities 2.14 Surface travel times and overlap maps can provide a helpful indication of the districts from which the London airports may potentially attract passengers, while the overlaps suggest the areas over which there could be more competition for potential passengers. However, such maps do not take into account any variations population densities in the different districts, which could influence the importance of a district to an airport. For example, a populous district over which four airports catchment areas overlap would suggest that there could be a greater potential scope for competition than the same overlap over a sparsely populated district. Catchment area analysis 11

12 Figure 4 - Population density in the South East of England Source: Office for National Statistics Regional Trends Figure 6 shows that London is the most densely populated area with most districts containing 2,500 or more people per square kilometre. The population becomes gradually less dense moving away from the capital, although dense pockets of population are found in regional conurbations such as Birmingham, Oxford and Southampton. Perhaps unsurprisingly, Greater London is both the largest area of high population density and the area over which there are significant catchment area overlaps based on surface travel times. Chains of substitution 2.16 As well as scope for competition arising from overlaps of neighbouring airports catchment areas, competitive constraints may also arise indirectly through what is known as chains of substitution: other near (but not neighbouring) airports could impose competitive constraints by influencing the competitive behaviour of other neighbouring airports For example, airport B may have catchment area overlaps with airport A and C while these two do not have any catchment area overlaps with each other. Assuming they offer services that are considered to be substitutes by a number of each airport s passengers, it is possible that pricing by airport C, which would directly constrain the pricing behaviour of airport B, could indirectly exert competitive pressure on airport A because the latter reacts to Catchment area analysis 12

13 pricing behaviour of airport B. The overlaps between surface travel isochrones can inform the consideration of the potential magnitude of this effect Figures 5 and 6 below show, with 60 minutes and 120 minutes road travel isochrones, potential chains of substitution for illustrative purposes. This is also an example of the isochrones constructed using Mappoint, which were previously used in CAA work cited in paragraph 2.5. Figure 5 - Chains of substitution with 60 minutes isochrones Figure 6 - Chains of substitution with 120 minutes isochrones Airports included: Luton, Stansted, Birmingham, East Midlands, Bristol, Manchester 2.19 In figure 5, there appears to be an overlap chain between Stansted (dark blue), Luton (pink) and Birmingham (light blue). This might suggest that, were the pricing at Birmingham airport to constrain Luton airport, Birmingham s pricing would indirectly constrain Stansted airport through Luton s initial reaction. However, given the small size of the isochrones, the chains of substitution do not appear to be particularly important, at the 60 minute threshold In contrast, the isochrones shown in figure 6 suggest that the chains of substitution could have a considerable effect where the 120 minute travel time is the appropriate threshold. These isochrones overlap to a far greater degree, which could be indicative of a more important potential competitive constraint. It would follow that chains of substitution with 90 minutes isochrones would show a median effect. Catchment area analysis 13

14 Summary of surface travel time analysis 2.21 This chapter presents analysis of catchment areas based solely on surface travel time for the four largest London airports. This type of catchment area analysis can support forward-looking analysis by providing useful evidence of the potential for competition between the London airports for the population domiciled in their proximate districts. The abstract nature of this analysis means that it is not influenced by actual passenger choices and underlying market conditions such as economic regulation or ownership structure, and so can suggest the potential for competition under different market conditions The surface travel time maps suggest that, in some cases, the level of connectivity of a district may be more important than its distance from an airport in influencing potential passengers willingness to travel to the airport. Catchment areas constructed on the basis of 90 minute travel times overlap to a significant degree for the four major London airports. Using 120 minute catchment areas, this finding is even more pronounced. Overlap analysis of these catchment areas shows that these overlaps are particularly pronounced for the Greater London districts. Population density maps show that these districts are also the most densely populated districts, which supports the inference from the overlap analysis that the London districts appear to be particularly important in determining the potential scope for competition between the London airports. It also appears that potential chains of substitution may be a relevant consideration when assessing potential competition constraints faced by the London airports, for those passengers willing to travel up to 120 minutes to reach an airport Catchment areas defined solely according to surface travel time provide useful evidence as to the potential for competition between the London airports independently of market conditions, and so could be useful in forward-looking analysis. However, it is informative to combine this analysis of potential competition with analysis of actual passenger surface travel time distribution. This analysis is discussed in the following chapter. Implications There is a large area over which the catchment areas of all four London airports overlap, which covers primarily the Greater London districts. Population density maps of the South East of England show that the districts over which there are the greatest overlaps also tend to be most densely populated. Chains of substitution may also be a relevant consideration when defining the relevant geographic market(s), and may be relevant when understanding the nature of competition for passengers willing to travel up to 120 minutes (or more) to reach an airport. Catchment area analysis 14

15 3. Passenger usage of airports by surface travel time Introduction 3.1 The previous chapter focused on an airport s potential catchment area based solely on the surface travel time to each airport, thereby abstracting from actual, historical, passenger behaviour. This chapter presents analysis of catchment areas for each of the London airports on the basis of both surface travel times and historical passenger surface access travel time distribution. This form of catchment area analysis is a way of estimating the geographic area from which a large proportion of an airport s outbound passengers originate, or inbound passengers travel to. Methodology 3.2 By combining the data on surface travel time used in chapter 2 with data on actual usage of the London airports, it is possible to establish catchment areas that show the areas from which the closest passengers originate or travel to (i.e. a cumulative passenger density distribution map with the districts ranked according to surface travel time). 3.3 However, it should be also noted that catchment areas constructed on this basis are influenced in part by the market conditions that were contemporary to passengers decisions, for example the existence of economic regulation and/or of common airport ownership and the services offered by airlines. 3.4 To draw the catchment areas setting out the passenger usage of the London airports according to travel time, historical passenger surface access travel time distribution data from the CAA Passenger Survey has been combined with the DfT surface travel time estimates described in chapter 2. The stated district of origin of each surveyed passenger is matched to the corresponding DfT surface travel time estimate. As the estimate is from the centroid of each district, there will be inevitably some measurement error in the travel times for certain passengers. For each London airport, the districts from which its passengers originate were then ranked according to the travel time to the airport, and a cumulative passenger density distribution produced on this basis. 3.5 In order to graphically represent this kind of catchment area, it is necessary to determine the appropriate percentile of passengers that will be used as the outer boundary of the catchment area. A threshold of 80% of passengers, the first 80 percentiles, has been chosen as a reasonable threshold for comparisons between airports and different types of passengers. As this choice is somewhat arbitrary, sensitivity analysis is carried in paragraph 3.44 to identify whether there are any marked differences in overlaps when the threshold is varied. Catchment area analysis 15

16 Surface access travel time at the London airports 3.6 The services offered from each of the four London airports are differentiated in several ways. For example, Heathrow has hub operations and long haul flights, while Stansted and Luton have almost exclusively short haul and domestic flights, as figure 9 shows. Different kinds of passengers may also have different preferences with regard to their surface travel to their departing airport. As a result, passenger surface travel time may vary across each airport. Figure 7 - Overall surface travel time at the London airports 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Heathrow Gatwick Stansted Luton Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data 3.7 Figure 7 sets out the surface travel times for passengers overall at each of the major four London airports. 8 The 80 th percentile of passengers using Stansted and Luton has the shortest travel time, approximately 90 minutes, which may reflect the fact that principally short haul and domestic flights are operated from these airports. By contrast, at this benchmark level, those flying from Gatwick travel to their departing airport for between 90 and 105 minutes, possibly reflecting the greater number of long haul flights at the airport. Heathrow passengers have the longest surface travel time of the four London airports with 105 minutes, again possibly reflecting the greater proportion of passengers flying on long haul flights. 3.8 The surface travel times on aggregate at the four London airports suggest that there is some variation in their passengers willingness to travel to the airports. To develop a clearer understanding of these variations, it could be informative to consider the variations in passenger surface travel times according to differing passenger characteristics. 8 London City airport is not included in these figures, as explained in chapter 2. Catchment area analysis 16

17 The different passenger groups 3.9 Passengers can vary in their characteristics and preferences regarding which airports they consider to be substitutes, which may result in different surface travel times. In light of this, it can be informative to analyse separately the different groups of passengers There are various ways in which passengers can be differentiated, including according to: journey purpose; flight distance (short or long haul); and whether they are UK or foreign residents Figure 8 below presents the share of different passenger types at the London airports, categorised according to the criteria set out above. Figure 8 - Residency-Purpose segmentation of airport passengers, excluding connecting passengers 9 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 15% 13% 15% 20% 18% 18% 10% 8% 4% 19% 49% 19% 16% 14% 14% 7% 27% 24% 7% 11% 5% 10% 28% 22% 29% 29% 10% 10% 14% 14% Heathrow Gatwick Stansted Luton Total London Foreign VFR Foreign Leisure Foreign Business UK VFR UK Holiday UK Business Source: CAA Passenger Survey (several years weighted to 2010 levels) 3.12 The figure shows that passenger composition varies across the London airports. For example, while Heathrow appears to have a relatively even distribution of different passenger types 10, the three other London airports shown tend to have a notable majority of a particular group. Leisure passengers (shown as Holiday on the figure above) make up 57% of Gatwick s passengers, with 49% being UK leisure passengers. Further, nonbusiness passengers constitute 86% of Gatwick s passengers, with 68% being UK residents. 9 Some totals add up to more or less than 100% due to rounding. 10 It should be noted that 35% of Heathrow s passengers are connecting passengers and so do not form part of the airport s surface passenger base illustrated in figure 8. Catchment area analysis 17

18 3.13 Stansted and Luton have a similar overall proportion of leisure passengers to Gatwick, with 83% and 81% respectively, of which UK residents make up the majority. However, the split between leisure passengers and those visiting friends and relatives (VFR) is more even than at Gatwick. Figure 9 - Percentage shares of passengers at each London airport according to immediate flight destination 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 1% 2% 15% 1% 5% 30% 6% 22% 88% 84% 68% 40% 7% 11% 9% 11% Heathrow Gatwick Stansted Luton Rest of world North America Europe Domestic Source: CAA Airport Statistics 3.14 Figure 9 sets outs the different compositions of each London airport s passenger base according to immediate destination. To analyse the shares according to flight distance, European destinations can be considered to represent international short haul flights and the North America and Rest of world shares together can be interpreted as long haul flights. Approximately half (52%) of Heathrow s passengers fly to long haul destinations, while the remainder largely fly on international short haul flights and a small percentage (7%) fly on domestic routes. By contrast, the other London airports appear to have a majority of international short haul operations, with Gatwick having the second largest percentage (21%) of long haul flights. Airlines at Stansted and Luton operate predominantly domestic and international short haul routes, with the latter constituting the overwhelming majority On the basis of the above observations, it can be seen that the London airports each have a different composition of passenger types. This may translate to different patterns of usage (and surface access travel times) between the airports. As a result, it would be useful to analyse the airports catchment areas separately according to journey purpose and flight distance. Journey Purpose 3.16 Passenger preferences and their willingness to travel by surface transport to their departure airport can vary according to their journey purpose. The three Catchment area analysis 18

19 types of journey purpose considered here are leisure, visiting friends and relatives, and travelling on business. A fuller consideration and description of the various types of journey purpose can be found in the CAA s Competition Guidelines Issues 11 paper and Guidance on the assessment of airport market power Leisure passengers, for example going on holiday, are likely to be willing to choose between a wide range of destinations. Due in part to this flexibility, they tend to be more price sensitive and, as a result, may be willing to travel greater distances to a departure airport, from which a better priced substitutable service could be offered. Further, their travel decisions tend to be discretionary, which means that there could be most inclined not to travel when there are few or no suitable substitutes available Passengers visiting friends and relatives, in contrast to leisure passengers, could have less discretion regarding their travel and a relatively narrow choice of destinations. Their time sensitivity can also vary greatly, for example according to whether they are flying for pleasure or for a particular occasion or event In contrast to both leisure and VFR passengers, business passengers tend to have a fixed destination and be most time sensitive. Consequently, they would be more likely to travel to the most proximate airport to their point of origin, and could also be tied to an airport where their employer has a corporate contract with a particular airline. Figure 10 - Surface travel time according to journey purpose 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% BUS HOL VFR Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data 11 CAA Competition Guidelines Issues September CAA Guidance on the assessment of airport market power April Catchment area analysis 19

20 3.20 Figure 10 shows the estimates surface travel times according journey purpose, aggregated across the London airports. At the 80 th percentile, leisure passengers had the longest surface travel time, of 105 minutes, while business and VFR have approximately the same surface travel time of 90 minutes. Flight duration 3.21 The time for which a passenger would be willing to travel by surface transport to their departing airport is likely to be influenced by the duration of their flight; whether they are flying on a domestic short haul, international short haul or long haul flight. Depending on the flight duration, each additional minute of surface access travel can be less or more important with regard to the overall travel time. For example, a journey time to the airport of 30 minutes to take a 90 minute flight represents a greater proportion of the passenger s overall travel time compared to the same surface journey for a long haul service. It could then be expected that passengers taking a shorter flight may have a preference for a shorter surface travel time. Figure 11 - Surface travel time according to flight duration 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Domestic Short haul Long haul Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data 3.22 Figure 11 indeed shows that the surface travel times appear to vary according to the flight duration in the expected way. At the 80 th percentile, passengers on domestic flights tend to travel 75 minutes to one of the four major London airports, whilst international short haul passengers travel for 90 minutes to their departure airport. Perhaps unsurprisingly, long haul passengers travel for longest, between 120 and 150 minutes. Catchment area analysis 20

21 UK and foreign residents 3.23 Whether a passenger is a UK or foreign (non-uk) resident could suggest certain variations in their travel choices, including their willingness to travel to the airport. For example, a UK resident may begin their journey to their departing airport from a point of origin, such as their domicile or place of work, which may have been determined independently of an airport s location. By contrast, a foreign resident, who could be beginning their return journey to their country of residence, may travel a more limited distance from their point of origin to their departure airport as the latter could have been chosen with regard to airport proximity. Foreign residents may then have lower surface travel times to a UK airport than UK residents Figure 12 below shows the surface travel time for passengers at London airports as a whole, and for UK and foreign residents. Figure 12 - Surface travel time according to residence 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Total UK total Foreign total Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data 3.25 Indeed, the surface travel time for a foreign resident is 75 minutes, which is considerably shorter than the surface travel time of approximately 120 minutes for UK residents. Travel time estimates that aggregate UK and foreign residents, as in the previous figures, could then mask an important difference between these two groups of passengers. Further disaggregation of surface travel times 3.26 The previous sections have provided an overview at an aggregate level of the variations in surface travel time across the London airports. A more detailed, disaggregated, analysis is available in Annex A, from which a few notable points are discussed below. Catchment area analysis 21

22 3.27 Considering UK and foreign residents separately reveals that UK resident passengers travelling for leisure are the least time sensitive, while UK resident business and VFR passengers tend to have similar travel times. Regarding flight distance, the surface travel times for domestic flights are the shortest, suggesting that these passengers either do not need, or are generally unwilling, to travel long distances to reach an airport. By contrast, passengers taking international short haul flights at each airport have a surface travel time of between 105 and 120 minutes. In addition, business passengers at Stansted and Luton travel to their respective airports for 120 minutes, markedly longer than for Heathrow or Gatwick, which is perhaps unexpected given that business passengers are often assumed to be particularly sensitive to travel time 13. Lastly, passengers taking long haul flights have the longest surface travel time, which is likely to create more catchment area overlaps, particularly for leisure passengers Foreign residents generally have markedly shorter surface travel times, thereby reducing the size of any catchment area overlaps. The surface travel times for international short haul do not differ significantly according to journey purpose. However, foreign residents flying long haul from Gatwick tend to travel for 105 minutes, compared with 75 minutes at Heathrow, which may be due to Gatwick offering a number of unique point-to-point routes Although some preliminary observations have been drawn from the measurement of surface travel times, it is also useful to consider the geographical distribution of these catchment areas, by presenting the data graphically. The following sections set out the four major London airports catchment areas using overall surface travel times for the first 80% of their passengers in districts ranked by travel time. Heathrow 3.30 Figure 13 below shows the surface travel time catchment area for passengers overall at Heathrow. The dark and light green districts together show the catchment area that contains 80% of Heathrow passengers, and translates as a surface travel time of approximately 105 minutes based on figure However, it must be noted that the DfT surface travel time data pre-date the introduction of rail links such as the Stansted Express. 14 The darker area shows that closest 70% of passengers, whilst the green and white areas represent 90%. Catchment area analysis 22

23 3.31. Figure 13 - Heathrow overall surface travel time catchment area Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data Dark green 70%; Light green 80%: White 90% of passengers 3.32 Table 1 15 below presents the distribution of the passengers within Heathrow s surface travel time catchment area according to different areas of overlap with the other London airports. This provides an indication of how important these districts are to Heathrow and how many passengers from these districts use one of the other major London airports. In this table, a district is considered to be in an overlap if it is within the catchment area (at the 80% level) of more than one of the airports shown. Table 1 Heathrow aggregate surface travel time catchment area Overlaps #Districts 4 Airport Pax LHR Pax Proportion (4 APTS) Proportion (LHR) LHR Share LHR/ 10 2,736,364 1,515,170 3% 4% 55% LHR/LGW/ 21 6,387,930 1,758,202 7% 4% 28% LHR/STN/ 2 760, ,110 1% 0% 22% LHR/LTN/ 3 1,520, ,048 2% 1% 38% LHR/LGW/LTN/ 5 3,247,318 1,855,996 3% 4% 57% LHR/LGW/STN/ 6 1,909, ,833 2% 1% 22% LHR/STN/LTN/ 5 2,514, ,097 3% 1% 25% LHR/LGW/STN/LTN/ 73 56,919,885 25,821,956 60% 62% 45% Total LHR Catchment ,996,554 32,731,412 80% 79% 43% Out of Catchment 19,032,301 8,858,396 20% 21% 47% Total 95,028,855 41,589, % 100% 44% Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data 3.33 The fourth column in table 1 shows that, of its 41.6 million surface passengers, Heathrow s catchment area, as defined in this chapter, contains 15 The table includes only the catchment area overlaps that exist between the four major London airports. Due to rounding, the table may show the 78 th or 79 th percentile as the catchment threshold. Catchment area analysis 23

24 Gatwick 32.7 million of them across 125 districts. Ten districts in Heathrow s catchment area are served solely by Heathrow at the 80% benchmark level. Interestingly, Heathrow only has a 55% share of passengers in those districts, which means that 45% of 2.7million passengers fly to one of the three other London airports. There are 21 districts that lay in overlaps between (only) Gatwick and Heathrow, of which Heathrow has a 28% passenger share. The most notable finding is perhaps that 73 districts, representing 60% and 62% of London airport passengers and Heathrow s passengers respectively, are located in areas of overlap between Heathrow, Gatwick, Stansted and Luton. While Heathrow has a 45% share of all passengers in such districts, the concentration of 56.9 million passengers in areas of four-way catchment overlaps suggests that there is a significant prospect that a large proportion of passengers can choose (in principle, at least) between multiple London airports. However, these figures do not take into account the different mix of passengers at the London airports or other factors affecting passenger choices, such as route availability and affordability of surface access transport The surface travel time catchment area for Gatwick is shown in figure 14. The catchment area (at the 80% benchmark level) represents a surface travel time by surface transport of between 90 and 105 minutes, slightly shorter than for Heathrow. Table 2 16 sets out the analysis of the extent of catchment area overlaps. Figure 14 Gatwick overall surface travel time catchment area Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data Dark green 70%; Light green 80%: White 90% of passengers 16 The table includes only the catchment area overlaps that exist between the four major London airports. Due to rounding, the table may show the 78 th or 79 th percentile as the catchment threshold. Catchment area analysis 24

25 Table 2 - Gatwick aggregate surface travel time catchment area Overlaps #Districts 4 Airport Pax LGW Pax Proportion (4 APTS) Proportion (LGW) LGW Share LGW/ 3 416, ,073 0% 1% 63% LHR/LGW/ 21 6,387,930 4,186,783 7% 15% 66% LHR/LGW/STN/ 6 1,909,550 1,235,245 2% 4% 65% LHR/LGW/LTN/ 5 3,247, ,093 3% 4% 30% LHR/LGW/STN/LTN/ 73 56,919,885 15,305,212 60% 55% 27% Total LGW Catchment ,881,414 21,973,407 72% 79% 32% Out of Catchment 26,147,441 5,883,420 28% 21% 23% Total 95,028,855 27,856, % 100% 29% Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data 3.35 Fifty-five per cent of the 22 million passengers in Gatwick s surface travel time catchment area are located in the four-airport overlap area, where the airport has a 27% share of passengers. The area over which Heathrow and Gatwick s catchment areas overlap provides the second largest proportion of Gatwick passengers (15%), with Gatwick having a 66% share of passengers from those 21 districts The remainder of Gatwick s passengers come from the three-way overlap areas, with only a small proportion coming from its three unique districts. Gatwick s share of 32% across its catchment area compares to 43% for Heathrow. Stansted 3.37 The overall surface travel time catchment area for Stansted, shown in figure 15, shows a catchment area corresponding to a surface travel time of 90 minutes at the 80% benchmark level. Figure 15 - Stansted overall surface travel time catchment area Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data Dark green 70%; Light green 80%: White 90% of passengers Catchment area analysis 25

26 3.38 Table 3 17 shows that, in line with its lower annual passenger number than Heathrow and Gatwick, Stansted has a lower share (21%) of its catchment area. Stansted attracts a larger proportion of its passengers (64%) from the four-way overlap area than the other airports, despite only having a 19% share of the area itself. Other overlap areas individually provide each only up to 5% of Stansted s potential passenger base. Table 3 - Stansted aggregate surface travel time catchment area Overlaps #Districts 4 Airport Pax STN Pax Proportion (4 APTS) Proportion (STN) STN Share STN/ 7 1,628, ,476 2% 5% 50% LHR/STN/ 2 760, ,846 1% 2% 47% STN/LTN/ 4 730, ,469 1% 2% 43% LHR/LGW/STN/ 6 1,909, ,020 2% 1% 11% LHR/STN/LTN/ 5 2,514, ,836 3% 5% 36% LHR/LGW/STN/LTN/ 73 56,919,885 10,948,193 60% 64% 19% Total STN Catchment 97 64,463,130 13,537,842 68% 79% 21% Out of Catchment 30,565,726 3,651,545 32% 21% 12% Total 95,028,855 17,189, % 100% 18% Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data 3.39 However, the very small number of long haul flights from Stansted means that care is needed when making direct comparisons between Stansted and Gatwick or Heathrow for reasons discussed earlier in this chapter. Luton 3.40 Figure 16 shows Luton s catchment area, which represents a surface travel time of between 75 and 90 minutes. Figure 16 - Luton overall surface travel time catchment area Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data Dark green 70%; Light green 80%: White 90% of passengers 17 The table includes only the catchment area overlaps that exist between the four major London airports. Due to rounding, the table may show the 78 th or 79 th percentile as the catchment threshold. Catchment area analysis 26

27 Table 4 Luton aggregate surface travel time catchment area Overlaps #Districts 4 Airport Pax LTN Pax Proportion (4 APTS) Proportion (LTN) LTN Share LTN/ 6 711, ,523 1% 2% 23% LHR/LTN/ 3 1,520, ,079 2% 7% 37% STN/LTN/ 4 730, ,050 1% 2% 18% LHR/LGW/LTN/ 5 3,247, ,505 3% 2% 5% LHR/STN/LTN/ 5 2,514, ,285 3% 9% 29% LHR/LGW/STN/LTN/ 73 56,919,885 4,844,524 60% 58% 9% Total LTN Catchment 96 65,645,014 6,587,966 69% 78% 10% Out of Catchment 29,383,841 1,804,868 31% 22% 6% Total 95,028,855 8,392, % 100% 9% Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data 3.41 As can be seen in table 4 18, Luton attracts 4.8 million (or 73%) of the 6.6 million passengers in its catchment area from the four-way overlap of Heathrow, Gatwick, Stansted and Luton. In common with the other three major London airports, the four-way overlap is its principal source of passengers. The three-way overlap between Heathrow, Stansted and Luton is the source of 9% of Luton hypothetical passenger base. The third most important area of attraction is that where Heathrow and Luton overlap, from which 7% of Luton s surface passengers start their journey. Overlap maps 3.42 According to the estimates above, when a catchment area is defined as containing the first 80% of an airport s passengers in districts ranked according to surface travel time, each of the London airports has an aggregate surface travel time of approximately 90 minutes, with the exception of Heathrow with 105 minutes. Analysing the extent of overlaps between the four London airports on the basis of this definition of a catchment area could then provide an indication of the potential competitive constraints between the near and neighbouring London airports. 18 The table includes only the catchment area overlaps that exist between the four major London airports. Due to rounding, the table may show the 78 th or 79 th percentile as the catchment threshold. Catchment area analysis 27

28 Figure 17 Overlaps of catchment areas with 80% of passengers Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data Blue: 1 airport; Light blue: 2 airports; Light red: 3 airports; Red: 4 airports 3.43 Figure 17 suggests that passengers across Greater London have significant levels of choice between airports (i.e. in the area coloured in red). Further, passengers located in the districts to the north and south of London are located in areas of catchment are overlap of two or three airports, and so could still have the potential to choose between these airports. Perhaps unsurprisingly, the districts furthest from London are only served by one of the London airports. This is largely consistent with the construction used for the catchment areas in this chapter, as the ranking of districts by surface travel time results in a pattern resembling concentric rings around each airport There is an element of arbitrariness in the choice of the threshold of 80% of passengers to define a catchment area. Reflecting this, sensitivity analysis is undertaken below to establish whether there are any marked differences in overlaps when the catchment area is defined as covering either the first 70% or the first 90% of passengers in districts ranked according to surface travel time. Figure 18 shows the extent of catchment area overlaps when the first 70% of each airport s passengers are included in their respective catchment areas, which corresponds to a surface travel time of up to 75 minutes. As evidence suggests that business, VFR and some international short-haul passengers have a lower willingness to travel to reach an airport, figure 18 might be also appropriate for considering the extent of competition for these passengers. Catchment area analysis 28

29 Figure 18 - Overlaps when catchment areas are defined with 70% of passengers Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data Blue: 1 airport; Light blue: 2 airports; Light red: 3 airports; Red: 4 airports 3.45 Compared to catchment areas covering the first 80% of each airport s passengers, the degree of overlap when the catchment area is restricted to the first 70% of passengers is (predictably) smaller, as fewer passengers are included in the analysis. Most of the districts that were in four-way overlap areas in figure 17 are now only covered by the catchment areas of three London airports. The number of districts which are located in the catchment areas of two or one airport(s) is also significantly smaller Figure 19 sets out the catchment area overlaps when the catchment area is redefined as the districts, ranked by travel time, including the first 90% of an airport s passengers. Catchment area analysis 29

30 Figure 19 - Overlaps when catchment areas are defined with 90% of passengers Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data Blue: 1 airport; Light blue: 2 airports; Light red: 3 airports; Red: 4 airports 3.47 The clearest difference between figure 19 and figures 17 and 18 is that the area over which the catchment areas of the four London airports overlap is significantly greater. This would be expected since it the catchment areas now include the first 90% of each airport s passenger base, which covers a greater number of common districts. It also accounts for a greater surface travel time, which means that distant districts such as Newport are in the catchment area of one of the London airports. On basis of figure 19, to the extent that passengers have a greater willingness to travel to reach an airport, particularly if this willingness is significantly greater than 90 minutes, a much larger number of passengers would have choices between multiple London airports It is worth repeating that catchment area overlap analysis does not provide a complete indication of possible competition between the London airports. Such analysis takes no account of the airports relative size and capacity, nor does it consider differences in airport or airline business models. For example, an area of catchment area overlap between an airport with primarily low cost carriers and an airport with mostly full-service long haul operations would not necessarily result in a high degree of competition as passengers may not consider these two airports, and their overall product, to be substitutable. The types of passengers, and their corresponding preferences, in the relevant given districts could also be an important factor determining the level of potential competition between the London airports. Nevertheless, the catchment area analysis in this chapter provides useful evidence about the potential competition for passengers between airports, albeit that it needs Catchment area analysis 30

31 to be combined with other evidence before definitive conclusions can be drawn. Common routes 3.49 This chapter has so far covered surface travel time catchment area analysis, which ignores possible variations in the availability of routes from each London airport. The analysis below considers how route overlaps affect surface travel times. Where a route is available from more than one airport, passengers could incur a lower surface travel time as a result of choosing to fly from the more proximate airport offering the route Figure sets out the impact of average surface travel times at each London airports according to how commonly a route is served. A preliminary observation is that Gatwick has the longest average surface travel time of the four London airports, with 95 minutes. It is possible that the number of unique point-to-point routes and charter operations from Gatwick leads to passengers having to travel to the airport. Perhaps surprisingly, despite its long haul operations, Heathrow has a similar average surface travel time to Stansted and Luton with approximately 75 minutes At Heathrow and Gatwick, the surface travel time falls by 13 and 12 minutes respectively when a route is also served by another London airport, as shown by the difference between the blue and red bars. The impact of a common route at another airport is slightly smaller at Stansted and Luton, where surface travel times fall by 3 and 8 minutes respectively. There does not appear to be a trend in the rate at which surface travel time decreases with the addition of another airport from which a route is operated. Overall, the greater the number of London airports from which a common route is operated, the shorter the average surface travel time is for each London airport, as shown by the downward trend in the bars in figure Again, this analysis only includes the four major London airports: Heathrow, Gatwick, Stansted and Luton. Catchment area analysis 31

32 Figure 20- Impact of route commonality on overall surface travel times Airport 2 Airports 3 Airports 4 Airports LHR LGW STN LTN Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data 3.52 The analysis in figure 20 looks across all services for the four London airports. These overall surface travel times reflect each type of flight operated from the airports, which means the averages for Heathrow and Gatwick include the surface travel times for long haul flights (including long haul charter at Gatwick), that tend to be greater than those for international short haul and domestic flights. By contrast, the averages for Stansted and Luton are largely based on surface travel times for the large majority of domestic and international short haul flights that are operated from these airports, as figure 9 showed To explore the impact of differences in route networks, figure 21 compares the airports on the basis of surface travel times for international short haul flights only to enable analysis on more comparable basis. As a result, the average surface travel times in blue (representing unique routes in the context of the four major London airports) are shorter than those in figure 20 for Heathrow and Gatwick but longer for Stansted and Luton due to the exclusion of domestic operations. Again, there does not appear to be a trend in the specific effect of adding either the second, third or fourth airport. However, as with the overall averages, the international short haul average surface travel times fall as a route is operated at more of the London airports. Catchment area analysis 32

33 Figure 21 - Impact of route commonality on surface travel times for international short haul flights Airport 2 Airports 3 Airports 4 Airports LHR LGW STN LTN Source: CAA analysis of the CAA Passenger Survey 2010 and DfT surface access data 3.54 It is clear from the figures above that route commonality reduces the average surface travel time for each airport. Further, the average surface travel times fall further as a route becomes more common. This would suggest that passengers may select the most proximate airport offering their preferred route and, in doing so, reduce their average surface travel time. Route commonality can be therefore an important factor to consider when analysing catchment areas. Summary of analysis 3.55 The catchment area analysis in this chapter has provided analysis of data on districts, ranked according to surface travel time, from which passengers have originated For passengers overall across the four major London airports, a significant proportion of passengers using an airport accept a surface travel time of approximately 90 minutes. However, there are variations in this travel time according to journey purpose, flight duration and whether a passenger is a UK resident The catchment area overlap analysis suggests that the majority of each London airport s passengers originate from districts where there is a four-way overlap of catchment areas. By contrast, none of the airports attracts a considerable number of passengers from districts that are uniquely part of that airport s catchment. Unsurprisingly, the London districts are those with the most significant overlaps. Lastly, common routes appear to have an increasingly contractionary effect on surface travel times at each London airport as a route becomes more common. Catchment area analysis 33

34 3.58 Chapters 2 and 3 have considered catchment area analysis to inform the analysis of the potential scope for competition between the four London airports. It is also useful to consider the geographic distribution of passengers, to explore the areas from which high concentrations of passengers originate or travel to. This is analysed in chapter 4. Implications For passengers overall across the London airports, a significant proportion of passengers accept a surface travel time of approximately 90 minutes. However, there are variations according to journey purpose, flight duration and whether a passenger is a UK resident. The majority of each London airport s passengers appears to originate from districts over which the catchment areas of all four airports overlap. By contrast, none seem to draw a significant amount of passengers from districts unique to their catchment area. There is a significantly large area over which the catchment areas of all four London airports overlap, which covers primarily the Greater London districts. Common routes appear to have a contractionary effect on surface travel times at each London airport as a route becomes more common. Catchment area analysis 34

35 4. Geographic distribution of actual airport usage Introduction 4.1 The analysis in chapter 3 has considered catchment area analysis that focused on surface travel time but also incorporated actual usage data. This chapter analyses catchment areas that consider the actual geographic distribution of passengers. Methodology 4.2 The catchment areas in this chapter are constructed using historical CAA Passenger Survey data to show the choices of airport made by passengers, and establish the locations from which the highest proportion of passengers have originated. 4.3 The methodology of historical usage catchment areas used in this paper is similar to that employed to construct the catchment areas in chapter 3 that show passenger usage according to surface travel time. However, the current catchment areas are defined as districts ranked by passenger numbers from where an airport has drawn 80% of its surface access passengers. Contrary to the two previous types of catchment areas, the current catchment areas do not explicitly make use of surface travel times, although they are implicitly reflected in the actual passenger behaviour. 4.4 However, current usage patterns are not a complete indication of the area over which an airport might currently or prospectively compete for passengers. Indeed, two neighbouring airports with similar services and service quality might have relatively small overlaps in catchment areas, but any increase in price or reduction in service quality might result in a significant shift of passengers from one airport to another, and lead to a significant change in the catchment area. Additionally, actual passenger behaviour in the light of price rises, or changes in service quality, at airports with substantial market power or subject to regulation may not reflect switching patterns observed in a well-functioning market. Nevertheless, catchment area analysis based on actual airport usage data can provide evidence on passenger usage patterns and inform the analysis of passenger choices and competition. Previous use of catchment area analysis based on historical usage 4.5 The CAA has previously analysed catchment areas based on historical usage data, and their overlaps, in Supporting Paper II of the Initial price control proposals for Heathrow, Gatwick and Stansted published in December The catchment area overlap map in that paper showed the districts in the lower half of the UK where between one and three London airports had a market share above 25%. 4.6 The Competition Commission (CC) has also undertaken catchment area analysis, and overlap analysis, based on historical usage data for airports in the South East of England in appendix 3.5 of its BAA airports market investigation, published in March While the current analysis includes districts ranked according to passenger numbers, the CC analysis included Catchment area analysis 35

36 Heathrow districts within an airport s catchment area only if the airport had at least 2% of the passengers originating from that district 20, which could underestimate the size of the catchment area (particularly for smaller airports). The CC s previous analysis of catchment area overlaps, which took the form of similar tables to table 1, excluded districts from an airport s catchment area where the airport had a share of passengers lower than 20%. By contrast, the analysis in this paper includes all districts and defines a catchment based on the districts providing the most passengers to a given airport. 4.7 The catchment area containing 80% of Heathrow passengers, based on their districts of origin, is shown by the green districts in figure 22. It is immediately clear that the concentration of passengers does not follow an even distribution by travel time or distance from the airport. Instead, it appears that proximity to transport links and conurbations could be more important factors, as the analysis in chapter 2 suggested. For example, districts such as Birmingham, Bristol and Swindon, which are all significant centres both in terms of population and in terms of interchanges on the rail network, are some of the districts with the densest concentration of Heathrow passengers, despite being somewhat distant from the airport. By contrast, other districts such as Epping Forest and West Oxfordshire are the point of origin for considerably fewer Heathrow passengers, despite being more proximate 21. Figure 22 - Heathrow overall historical usage catchment area Source: CAA analysis of the CAA Passenger Survey (2010) 20 Competition Commission BAA Airports Market Investigation March 2009 Appendix 3.5, para21 21 Due to the nature of survey data, there remains the possibility that certain surveyed passengers may have reported their point of origin as the nearest conurbation rather than their actual domicile, though this effect is expected to be small. Catchment area analysis 36

37 4.8 The notable differences between catchment areas focusing on surface travel time and those showing passenger usage by travel time (in chapter 3) suggest that catchment area overlaps based on the concentration of usage will not be as large as those with surface travel time catchment areas. Table 5 22 sets out of these catchment area overlaps. Table 5 - Heathrow historical catchment area Overlaps #Districts 4 Airport Pax LHR Pax Proportion (4 APTS) Proportion (LHR) LHR Share LHR/ 17 3,977,797 2,534,452 4% 6% 64% LHR/LGW/ 21 9,900,148 4,303,976 10% 10% 43% LHR/STN/ 1 243,260 99,348 0% 0% 41% LHR/LTN/ 5 1,621, ,854 2% 2% 43% LHR/LGW/STN/ 7 3,528, ,286 4% 2% 24% LHR/LGW/LTN/ 8 5,539,693 2,764,902 6% 7% 50% LHR/STN/LTN/ 7 4,047,482 1,535,437 4% 4% 38% LHR/LGW/STN/LTN/ 28 40,577,229 19,951,335 43% 48% 49% Total LHR Catchment 94 69,435,453 32,731,590 73% 79% 47% Out of Catchment 25,593,402 8,858,218 27% 21% 35% Total 95,028,855 41,589, % 100% 44% Source: CAA analysis of the CAA Passenger Survey (2010) 4.9 The 80% of Heathrow s passengers originating from the most important districts to Heathrow cover 94 districts, compared to the 125 districts in catchment areas based on passenger usage by surface travel time 23. As can be seen from the sixth column (compared to its geographic equivalent of 62%) the proportion of passengers that Heathrow attracts from districts that are part of the four-way overlap zone is 14 percentage points lower at 48%. In contrast, 6% more of Heathrow s passengers originate from both the districts where its catchment overlaps with Gatwick alone and those where it overlaps with those of Gatwick and Luton. Nevertheless, it is noteworthy that the area over which four catchments overlap generate 48% of Heathrow s passengers, accounts for 49% of the journeys undertaken from these districts. Gatwick 4.10 Figure 23 illustrates the corresponding catchment area for Gatwick s passengers, which again varies considerably from its chapter 3 counterpart. 22 The table includes only the catchment area overlaps that exist between the four major London airports. Due to rounding, the table may show the 78 th or 79 th percentile as the catchment threshold. 23 This is due in large part to the construction of these catchment areas. Catchment area analysis 37

38 Figure 23 Gatwick overall historical usage catchment area Source: CAA analysis of the CAA Passenger Survey (2010) 4.11 As with Heathrow, more distant urban centres such as Bristol and Southampton are the source of more passengers than many more proximate districts, which may reflect the populations of these districts and their relatively fast transport links to the airport. Based on figure 23, it seems that very few passengers flying from Gatwick originate from East Anglia, or the north east of London. This suggests that passengers may be reluctant to travel to or from the other side London, or that Stansted or Luton may be suitable substitutes for Gatwick in many cases. Table 6 24 sets out how this translates into catchment area overlaps. Table 6 - Gatwick historical catchment area Overlaps #Districts 4 Airport Pax LGW Pax Proportion (4 APTS) Proportion (LGW) LGW Share LGW/ 23 5,487,159 3,639,880 6% 13% 66% LHR/LGW/ 21 9,900,148 4,897,288 10% 18% 49% LGW/STN/ 4 1,301, ,347 1% 2% 41% LHR/LGW/STN/ 7 3,528,403 1,606,456 4% 6% 46% LHR/LGW/LTN/ 8 5,539,693 1,683,276 6% 6% 30% LHR/LGW/STN/LTN/ 28 40,577,229 9,428,237 43% 34% 23% Total LGW Catchment 91 66,334,081 21,783,485 70% 78% 33% Out of Catchment 28,694,774 6,073,342 30% 22% 21% Total 95,028,855 27,856, % 100% 29% Source: CAA analysis of the CAA Passenger Survey (2010) 4.12 As with Heathrow, Gatwick s catchment areas calculated based on the density of passengers usage is more concentrated than its catchment areas based on surface travel times, as 80% of its passengers originate from 91 instead of 108 districts. In addition, there is a significant increase in the number of districts that are uniquely within Gatwick s catchment area, with The table includes only the catchment area overlaps that exist between the four major London airports. Due to rounding, the table may show the 78 th or 79 th percentile as the catchment threshold. Catchment area analysis 38

39 unique districts (with regard to the four major London airports), compared to 3 districts when passenger usage is ranked by surface travel time Compared to its figures in chapter 3, a notable difference is that Gatwick has drawn 13% of its passengers from districts where it does not have any overlaps, which is substantially more than the 1% for the catchment areas focusing on surface travel times. Additionally, the 34% of Gatwick s passengers originating in the four-way overlap zone is markedly lower than the corresponding 55% in chapter 3. Stansted 4.14 Stansted s corresponding catchment area, shown in figure 24, is again consistent with better connected, yet more distant, districts being the source of a considerable number of passengers. Except for a small number of districts to the south east of London, such as Ashford and Canterbury, it appears that the majority of Stansted s 80% of passengers originate from London and East Anglia. This is consistent with a similar observation made with regard to Gatwick that passengers appear perhaps reluctant to travel across London, which could be due to more proximate suitable substitutes being available. Figure 24 - Stansted overall historical usage catchment area Source: CAA analysis of the CAA Passenger Survey (2010) Catchment area analysis 39

40 Table 7 - Stansted historical catchment area Overlaps #Districts 4 Airport Pax STN Pax Proportion (4 APTS) Proportion (STN) STN Share STN/ 18 3,588,346 1,916,219 4% 11% 53% LHR/STN/ 1 243,260 72,598 0% 0% 30% LGW/STN/ 4 1,301, ,600 1% 3% 36% STN/LTN/ 6 2,227, ,012 2% 5% 40% LHR/LGW/STN/ 7 3,528, ,858 4% 6% 27% LHR/STN/LTN/ 7 4,047,482 1,194,776 4% 7% 30% LHR/LGW/STN/LTN/ 28 40,577,229 8,002,654 43% 47% 20% Total STN Catchment 71 55,513,569 13,509,717 58% 79% 24% Out of Catchment 39,515,286 3,679,669 42% 21% 9% Total 95,028,855 17,189, % 100% 18% Source: CAA analysis of the CAA Passenger Survey (2010) 4.15 In line with the figures for Heathrow and Gatwick, table 7 25 shows that Stansted also has a greater number of actual unique districts (18) than its corresponding figure of seven from chapter 3, and as a result draws 6% more of its passengers from these districts. Its catchment area is more concentrated than in the previous chapters with 71 districts, as opposed to 97. Further, although Stansted s share of the four-way overlap zone is approximately the same as with surface travel time catchment areas, the airport draws 47%, instead of 64%, of its total catchment from that zone. Luton 4.16 Compared to the other three London airports discussed above, Luton s catchment area appears to be considerably more concentrated around the most proximate districts, with a couple of exceptions such as Birmingham and Nottingham. The relatively small number of light green districts would suggest that the passenger base is more concentrated than for the other London airports. 25 The table includes only the catchment area overlaps that exist between the four major London airports. Due to rounding, the table may show the 78 th or 79 th percentile as the catchment threshold. Catchment area analysis 40

41 Figure 25 - Luton overall historical usage catchment area Source: CAA analysis of the CAA Passenger Survey (2010) Table 8 - Luton historical catchment area Overlaps #Districts 4 Airport Pax LTN Pax Proportion (4 APTS) Proportion (LTN) LTN Share LTN/ 14 2,448, ,713 3% 11% 36% LHR/LTN/ 5 1,621, ,195 2% 5% 28% STN/LTN/ 6 2,227, ,459 2% 6% 22% LHR/LGW/LTN/ 8 5,539, ,721 6% 9% 13% LHR/STN/LTN/ 7 4,047, ,226 4% 10% 21% LHR/LGW/STN/LTN/ 28 40,577,229 3,195,003 43% 38% 8% Total LTN Catchment 68 56,461,791 6,612,316 59% 79% 12% Out of Catchment 38,567,065 1,780,517 41% 21% 5% Total 95,028,855 8,392, % 100% 9% Source: CAA analysis of the CAA Passenger Survey (2010) 4.17 As with the other three airports analysed above, table 8 26 shows Luton has a significantly greater unique catchment area than established for catchment areas focusing on travel times, covering 14 instead of 6 districts and 11 per cent instead of 1 per cent of its passengers. Additionally, although it draws 20% fewer passengers from the four-way overlap zone, it still maintains its share based on surface travel time catchment areas. Its catchment area also covers 68 districts with historical data, instead of 96 with travel times. Overlap analysis for actual usage catchment areas 4.18 The analysis of each London airport s catchment area based on actual airport usage suggests that, while the catchment areas focusing on surface travel 26 The table includes only the catchment area overlaps that exist between the four major London airports. Due to rounding, the table may show the 78 th or 79 th percentile as the catchment threshold. Catchment area analysis 41

42 time show evenly distributed overlap maps, this is not the case for those catchment areas based on the concentration of usage. Figure 26 - Overlaps of actual using catchment areas using 80% passengers Source: CAA analysis of the CAA Passenger Survey (2010) Blue: 1 airport; Light blue: 2 airports; Light red: 3 airports; Red: 4 airports 4.19 Figure 26 shows the extent of catchment area overlaps for the London airports. It would appear that the area of overlap between all four airports is relatively small while the number of districts covered by only one airport s catchment area is large 27. Outside the London districts, only three more distant districts, Birmingham, Oxford and St. Albans, are located in the catchment areas of all four London airports. There are also several isolated districts which are in the area of a three-way overlap of London airports catchment areas, such as Norwich, Reading and Southampton. Nevertheless, the catchment area overlaps suggest the area where the largest number of passengers has the greatest choice includes the London districts and a small number of well connected conurbations outside of London In order to consider the impact of choosing 80% as the relevant threshold to determine catchment areas, sensitivity analysis is undertaken in figure 27 and 28 below to show the overlaps that result from various definitions of the catchment area Figure 27 sets outs the extent of catchment area overlaps when a catchment area includes 70% of an airport s passengers, which would result in a smaller 27 In figure 26, there are 73 districts that are unique to the catchment area of one London airport, relative to the other London airports considered in this paper, compared to 28 districts where the catchment areas of all four airports overlap. Catchment area analysis 42

43 number of districts lying within each airport s catchment area and could be expected to result in fewer overlaps. As the map shows, there are a smaller number of districts that lie in areas of four-way overlaps, though the ratio of unique to four-way overlaps remains similar. Figure 27 - Overlaps of actual catchment areas with 70% passengers Source: CAA analysis of the CAA Passenger Survey (2010) Blue: 1 airport; Light blue: 2 airports; Light red: 3 airports; Red: 4 airports 4.22 Figure 28 maps the catchment overlaps when the catchment area definition has been widened to include 90% of an airport s passengers. As would be expected, the number of districts over which the catchment areas all of the London airports overlap is markedly greater. Figure 28 - Overlaps of actual catchment areas with 90% passengers Source: CAA analysis of the CAA Passenger Survey (2010) Blue: 1 airport; Light blue: 2 airports; Light red: 3 airports; Red: 4 airports Catchment area analysis 43