This chapter discusses the role of transport for quality of life in cities and provides an analysis of how well local transport systems do in terms of connecting citizens with surrounding opportunities in different cities and for different socio-economic groups. It starts with a presentation of different channels through which transport policy matters for life in cities, most notably its role at fostering the transition towards a climate-neutral economy. Next, it moves to the description of how accessibility, i.e. the number of opportunities reachable from a given place in a given time by a given transport mode, and other transport quality indicators vary across cities of different countries and different sizes. It analyses the sizeable and positive accessibility gap between high- and low-income groups within cities and between cities in the same country. It concludes with potential explanations and suggested ways forward to improve accessibility inclusiveness in countries.
Transport Bridging Divides
2. Transport for access to opportunities in cities
Abstract
Transport investment contributes to quality of life in cities
The transport system provides access to economic opportunities and thereby enhances quality of life in cities. As established in Chapter 1, faster connections allow reaching a broader set of opportunities, e.g. jobs and services in a given time. In many cities, opportunities, such as jobs, are often concentrated in few places (typically the city centre). Faster connections from and to the city centre make higher job density in city centres more sustainable, thereby allowing cities to better reap the positive externalities associated with density.1
The transport system plays a critical role in making parts of the city viable places to build homes and create jobs. For example, investments in transport infrastructure in the metropolitan area of Vancouver have been credited as the force behind the reputation as one of the best places to live in Canada and the world. The problem is that as the built area and population grow, the number of challenges for the city also increases. For Vancouver, the boom in house prices and rents in central areas are pushing people to move to the suburbs where they do not always have the same level of access to opportunities.
Transport investment needs to keep up with growth in cities. Valle de México, the metropolitan area around Mexico’s capital Mexico City experienced rapid population growth from the 1950s onwards. From the 1980s onwards, growth started to slow down. At the same time, the share of the population living in the poorly connected commuting zone has continued growing, thus causing rising congestion. To maintain growth, the transport system must catch up with the rapid development the metropolitan area has undergone in the last decades, crucially by connecting and densifying the commuting zone to turn it into a more attractive residential choice (OECD, 2015[1]). The planned expansion of the metropolitan area, in particular along transport corridors, i.e. transit-oriented development, is also crucial to alleviate the investment burden. As cities sprawl over increasingly larger areas, the cost of connecting the entire metropolitan area to (public) transport grows with significantly higher costs for infrastructure provision. In the United States, for example, the road network in low-density cities has is about three time as long (in terms of kilometres per capita) than in higher-density cities (Litman, 2015[2]).
By reducing car usage, investments in public transport also create the opportunity to convert parking into green and walkable space, another important driver of quality of life in cities (Leinberger and Alfonzo, 2012[3]). Investments in public transport give the opportunity for residents to be less car-dependent. If they succeed in making travellers switch from car to public transport, thereby reducing the demand for parking space, policymakers can next consider whether to convert the space previously occupied by parking into green, walkable and recreational areas, with positive implications for the well-being of residents. Alternatively, in less densely populated neighbourhoods, the new space can be used to expand the housing supply, therefore releasing potential upwards pressure on housing costs.
The most important factors that link transport and quality of life of residents differ across metropolitan areas. The transport vision for metropolitan areas like London, New York and Vancouver is to meet all transport needs in a way that enhances the health of residents, communities, the economy and the environment to maintain or even improve living standards. For New York City, United States, to sustain the city’s growth and expand capacity, it is essential to allocate more street space to walking, biking and buses trying to move the greatest number of people while using the least amount of street capacity (NYC DOT, 2016[4]). London adopted the “Healthy Streets Approach” as part of its transport strategy. The basic premise is that the quality of the experience of using the city streets helps to define the quality of the journey. All metro and rail journeys rely on good street access to stations and streets, and are therefore important to providing attractive public transport options for each mode (Box 2.1).
Box 2.1. London’s Healthy Streets Approach
In the United Kingdom, London’s transport strategy has adopted a Healthy Streets Approach that provides the framework for putting human health and experience at the heart of city planning. It uses ten evidence-based indicators to assess the experience of being in the streets. Good performance on each indicator means that individual streets are appealing places to walk, cycle and spend time. Improvements against all indicators across the city’s streets are expected to transform the day-to-day experience of living and working in London. The ten indicators are:
Clear air – improving air quality.
Pedestrians from all walks of life – streets should be welcoming places for everyone to walk and spend time.
Easy to cross – to encourage walking and connect communities.
Shade and shelter – to enable everybody to use the streets whatever the weather.
Places to stop and rest – to foster mobility for all groups of people.
Not too noisy – to improve the ambience of the street environments encouraging travel and human interaction.
People choose to walk, cycle and use public transport – walking and cycling are the healthiest and most sustainable ways of travel. A successful transport system encourages and enables more people to walk and cycle more often and this is achieved by reducing motor traffic and improving the experience of being in the street.
People feel safe – people should not feel worried about road danger or experience threats to their personal safety.
Things to see and so – people are more likely to use the streets when their journey is interesting and stimulating with attractive views, buildings, plantings and where other people are using the street.
People feel relaxed – streets are not dominated by motorised traffic, and pavements and cycle paths are not overcrowded, dirty, cluttered or in disrepair.
Source: Greater London Authority (2018[5]), Mayor’s Transport Strategy, http://www.london.gov.uk (accessed on 15 July 2019).
The New York City Strategic Plan intends to improve street safety as part of its transport strategy. The plan considers the streets as conduits for people and goods as well as public spaces essential to the life and vibrancy of the city. Its basic premise is that the more attractive the streets and sidewalks, the more pedestrians will choose to use them (NYC DOT, 2016[4]). Streets make up 27% of New York City’s land area and, for many residents, the local street is also their backyard. Therefore, the transport strategy aims to: “make streets and sidewalks attractive safe public spaces for walking, resting and gathering; expand public open space by creating pedestrian plazas across the five boroughs, especially in underserved neighbourhoods; [and] reconnect communities and create new open spaces by enhancing and activating underutilised areas under bridges, elevated roads and train lines” (NYC DOT, 2016, p. 59[4]). Improving the open space and reconnecting communities is a way to encourage more social cohesion and urban redevelopment around transport.
Through improving access to green spaces, cities and communities can contribute to the United Nations (UN) Sustainable Development Goals (SDGs) (OECD, 2020[6]). In SDG 11.7, the global agenda to sustainably improve living standards and the quality of life across the developed and developing world includes an explicit target for access to green space. Green areas are an important amenity for local residents, especially if reachable within a short walk or ride. The likelihood of being able to reach within a short walk a green area in cities is however inversely proportional to average urban density. For instance, the metropolitan area of Paris is on average more densely developed than the metropolitan area of Rome, thus making it easier for its residents to get to work in relatively little time (see the upcoming section on this). However, people living in Rome’s densest areas have access on average to 15% more square metres than people living in Paris’ densest areas, which is approximately a third of the variation in going from an area in central Paris with low-to-intermediate access to green areas to one with intermediate-to-high access (Figure 2.1). A third urban development model, alternative to the one of Paris and Rome, exists and it consists of reconciling efficient development and sustainability within the same urban space.
Box 2.2. New York City’s Plaza Equity Program
The New York City (NYC) Department of Transportation (DOT) focuses on improving sidewalks and streets but also on creating signature open spaces across the five boroughs, particularly in areas with few open space resources. Through the NYC Plaza Program, DOT partners with local communities to convert underused streets into public plazas. According to the strategic plan, a well-designed plaza provides residents with a place to gather, promotes local business, reconnects neighbourhoods and creates a venue for recreational and cultural events. Thus, the DOT provides financial assistance to plaza partners in low- and moderate-income areas. The DOT is also exploring ways to activate and beautify areas under elevated highways and train lines. The aim is to ensure that residents live within a 10-minute walk of a quality open space.
To date, the DOT has developed or is planning 73 plazas across the 5 boroughs. The problem is that not every community has a partner organisation that can afford the required upkeep a public plaza demands. That is why the Plaza Equity Program provides USD 1.4 million in technical assistance for designated medium- and high-need plazas citywide. The programme provides funding to under-resourced communities to support their plazas, providing needed funds for maintenance services, including daily cleaning, trash removal, furniture management and horticultural care. Partner organisations also receive technical assistance with navigating city permitting processes, maintenance and event planning. Of the 73 plazas throughout the city, 30 receive support, enabling these diverse communities to have a high-quality public space.
Source: NYC DOT (2016[4]), New York City Strategic Plan 2016, https://www.nycdotplan.nyc/PDF/Strategic-plan-2016.pdf (accessed on 6 August 2019).
From mobility to accessibility
Quality of life in cities depends on accessibility not mobility. For decades transport investment aimed to increase the number of travellers and speed up their trips. This allowed cities to grow as people could commute longer distances in a shorter time. In Korea, for example, the average commute was less than 10 kilometres one way and took 42 minutes in 1990. Twenty years later it was 13 kilometres in only 32 minutes (OECD, 2016[7]). A focus on passenger number and speeds meant that transport became an end in itself rather than a means to access jobs, friends, family, amenities, etc. The concept of “accessibility” acknowledges that it is the access to opportunities that transport provides that matters for people’s well-being and the functioning of cities. “Accessibility” denotes the opportunities that a resident of a city can reach using different modes of transport within a given time, where opportunities can include access to people, jobs, shops, services, green spaces, restaurants, etc. In practice, measures of accessibility tend to be limited by the need for very granular data on opportunities (see below on measurement).
The benefits of pursuing accessibility in cities
Accessibility contributes to broader government objectives of well-being and sustainability (ITF, 2019[9]). The provision of “access to safe, affordable, accessible and sustainable transport systems for all” features among the UN SDGs as a necessary step towards building sustainable cities and communities (OECD, 2020[6]). However, cities need to improve their understanding of the links between accessibility and well-being. Transport can contribute more effectively to wider well-being objectives. It enables access to jobs, education, healthcare, services, markets and other services and goods. It helps to improve quality of life and assists in lifting people out of poverty. Nevertheless, this can only be achieved if the potential synergies between improving the access to goods, services and information, and goals such as environmental protection, limiting social exclusion and improving health are considered (ITF, 2019[9]).
A focus on mobility rather than accessibility may lead to long commutes, mobility divides, air pollution and loss of public space. The success of transport infrastructure investment is often judged by the volume of use of the infrastructures. Such a focus on mobility rather than on the access to opportunities that transport provides can come at the cost of significant negative externalities. They incentivise more traffic and longer trips, thereby creating pollution that could have been avoided. The space used for infrastructures is “lost” for alternative uses. Therefore, to promote sustainable accessibility, cities are increasingly adopting policies that endorse nearness, densification, mixed land uses, integration and slow transport modes to redefine planning. In countries like Sweden, accessibility and sustainability are the principal policy goals of urban development at the national and subnational levels of government (Gil Solá, Vilhelmson and Larsson, 2018[10]). Gothenburg is pursuing a traffic strategy that promotes slower transport modes and local living (Hellberg et al., 2014[11]); Stockholm is planning for future urban development in terms of a compact city (City of Stockholm, n.d.[12]); and Malmö aims to be a city of short distances (City of Malmö, 2016[13]).
Accessibility may also be a channel for cities to address global challenges such as climate change. Approximately 10 billion trips are made every day in urban areas around the world and a significant share of these trips are high-carbon and energy-intensive private motorised vehicles (Rode et al., 2014[14]). According to the Intergovernmental Panel on Climate Change (IPCC) (2014[15]), about 80% of the increase in global transport emissions since 1970 has been due to road vehicles. Around 10% of the global population account for 80% of total motorised passenger-kilometres, which means that most of the world population hardly contributes to emissions at all. OECD countries dominate transport emissions of greenhouse gases (GHG) but emissions in Asian countries are rapidly increasing (IPCC, 2014[15]). Nowadays, planners and researchers focus on compact, transit-accessible, pedestrian-oriented, mixed-use development patterns and land reuse issues to foster smart growth and urban sustainable development. In Sweden, for instance, work on a total transport system is expected to increase by 29% between 2010 and 2030. In the metropolitan area of Gothenburg, the use of private car will stand at around 25% by 2030; therefore, to achieve climate objectives, total passenger volumes need to be reduced by 20% (from 2010 levels) by 2030 (Hellberg et al., 2014[11]).
Transport authorities and city planners acknowledge the relevance of transport in socio-economic development and environmental protection. Investment in rail, buses, cycling and walking links to goods and services intend to use traffic to boost cities’ growth potential. For that, cities require providing high-quality public transport services that connect seamlessly to other forms of travel to provide alternatives to car use. The experience of cities like London, Malmö, Prague and Vancouver suggests that getting the planning process right is key to making transport a key contributor to sustainable and inclusive growth. In the aftermath of the current COVID-19 crisis, there will be opportunities to reallocate road space and encourage active transport to support the transition towards carbon neutrality and boost healthy lifestyles. At least 150 cities around the world have taken action during 2020 to create temporary cycle lanes and other spaces for active transport that allow travellers to maintain a social distance judged safe with respect to the transmission of the virus (ITF, 2020[16]).
Accessibility is also a factor that may contribute to the city’s competitiveness. Cities and regions compete for students and skilled workers to join the labour force. Accessibility to surrounding areas and attractive urban environments are important factors for maintaining and attracting a skilled workforce.
Measuring access to opportunities
Access to opportunities – henceforth “accessibility” – builds on two elements: the presence of a transport system and the opportunities the transport system gives access to. The simple existence of a public transport stop, for instance, does not translate into good access to opportunities if few jobs or services can be reached via a given public transport connection. Accessibility-based indicators therefore represent an improvement with respect to the existing metrics that were used to gauge the magnitude of benefits from transport infrastructure and that tended to be based uniquely on the first element, i.e. the possibility of accessing the transport network from a given place. Despite growing recognition of the necessity to adopt accessibility-based measures as a guiding element of local policymaking, the paucity of accessibility-based decision-making frameworks hinders their use in urban and regional planning. The Urban Access Framework developed by the OECD in co‑operation with the European Commission (EC) and the International Transport Forum (ITF) represents a first important step towards filling this gap (ITF, 2019[8]).
The Urban Access Framework jointly developed by the EC, the ITF and the OECD describes the access to opportunities provided by the urban transport network (ITF, 2019[8]). The framework provides three easy to interpret measures for accessibility and its links with the performance of the transport network at the city level. The measures are calculated based on the existing transport network and all potential travel from any point in a city to any other point. The Urban Access Framework has allowed the creation of harmonised indicators across a large set of European metropolitan areas. These indicators are flexible with respect to the choice of geography (i.e. what is “urban”) and can be easily combined with external sources of data. For different transport modes, such as driving, cycling, walking or public transport, the framework includes three indicators: accessibility, proximity and transport performance.
Accessibility refers to the total number of destinations that can be reached from a given location by driving, cycling, walking or taking public transport within a given amount of time. It is shaped by both the availability of opportunities in the surroundings of the given location and the characteristics of the transport network connecting that location to other parts of the city.
Proximity is defined as the total number of destinations available within a given distance from a given location regardless of the travel time required to access them.
Performance of the transport network captures how well the network connects residents of a given area to the opportunities existing in the proximity of such an area. It compares the total number of destinations reachable from a given location by a given transport mode within a given amount of time with the total number of destinations available within a given distance.
How many shops can residents access within 30 minutes?
Accessibility indicators implementing the EC-ITF-OECD Urban Access Framework are available for 121 European metropolitan areas for 2018 (Box 2.3). For four countries (France, England [UK], Italy and Spain), accessibility indicators are matched with data on income (or a proxy thereof) at the neighbourhood level (Annex Table 2.A.3). This combination of data sources gives the opportunity to zoom into each city and assess who benefits from better access to opportunities. The focus of this chapter is on accessibility by car and public transport within a 30-minute ride time. Car and public transport accounted jointly for 96% of urban passenger transport in OECD countries in 2015 and 30 minutes is the length of the average daily commute in OECD countries, except for Japan and Korea (OECD, 2017[17]). The analysis focuses on consumption opportunities as captured by the number of shops people can reach from their place of residence. Shop accessibility was chosen because, among the opportunities included in the dataset, it is the one that is more likely to have a strong correlation with jobs accessibility. Unlike other opportunities, the location of shops and jobs alike is mostly market-driven. Policymakers have indeed fewer tools to influence the distribution of shops than they have, for example, with schools. In the case of public services, e.g. schools or hospitals, they can, for instance, improve accessibility, not only by intervening on the transport network but also through investments in either the creation of new facilities or the expansion of existing ones.
Box 2.3. The EC-ITF-OECD Urban Access Framework
The EC, the ITF and the OECD jointly developed the Urban Access Framework, which provides a flexible framework to capture accessibility and transport performance in cities.
According to the Urban Access Framework, accessibility is measured on a 500-by-500-metre grid and refers to the number of opportunities reachable within a fixed amount of time from a given grid cell through the available transport network. The measure has been calculated with respect to a large set of opportunities, i.e. other people, schools, hospitals, food shops, restaurants, recreational activities and green spaces. These indicators have been computed for 121 metropolitan areas in 30 European countries based on data for 2018 (although not all transport modes are available in all cities). In terms of data sources, opportunities have been identified based on either OpenStreetMap or proprietary data sources (e.g. TomTom).
Accessibility is itself shaped by two further characteristics of the urban space. The first is proximity, i.e. how many opportunities there exist within a fixed physical distance from a given location. The second is the performance of the transport network, defined as the ratio between the number of opportunities reachable within a given time and the number of opportunities existing in the proximity of a given location. The higher this ratio, the more efficient the transport network, in the sense that it allows people to reach a larger share of the opportunities that exist nearby.
Figure 2.2 shows the distribution of accessibility, proximity and performance by car across the wider metropolitan area of Hamburg. Proximity (top left-hand figure) in Hamburg as well as in most cities in the sample is higher in the city centre compared to the commuting zone, due to the higher density typical of city centres. Conversely, performance (bottom figure) of the car transport network is higher in the commuting zone, due to the more intense traffic and lower speed limits in the city centre. Since accessibility increases in both proximity and performance, these two patterns represent two opposing forces. Ultimately, the differences in proximity between the centre and the commuting zone outweigh the differences in performance in the case of the city of Hamburg, so that accessibility is on average higher in the city centre compared to other parts of the cities (top right-hand figure).
Across European metropolitan areas, average accessibility by car is higher than average accessibility by public transport. The average number of shops reachable within a 30-minute car ride is 1 402, more than twice the average number of shops reachable by public transport (Figure 2.3). Car accessibility is higher than public transport accessibility for access to public services as well. Across the 118 cities considered, the average number of schools accessible within a 30-minute car ride is 354 (Annex Figure 2.A.1). This number drops to 112 when considering public transport rides. A similar ranking between car and public transport accessibility is found for hospitals as well (Annex Figure 2.A.2). Residents of the cities considered can access, on average, 5 hospitals within a 30-minute public transport ride and as many as 17 within 30 minutes by car.
Larger metropolitan areas provide better access to opportunities. Figure 2.3 reports the number of shops accessible within a 30-minute ride by car or public transport across European metropolitan areas. The largest metropolitan areas have significantly better access. In the sample, the 20 largest metropolitan areas provide access to more than 3 times the number of shops than the 20 smallest metropolitan areas for trips by car and nearly 3 times the number of shops for access by public transport.2 A similar gradient along the city size hierarchy is present for public services as well.3 Beyond the general tendency for better access in larger metropolitan areas, there is sizeable variation in the performance of metropolitan areas. Some smaller metropolitan areas provide access equal to that of mid-sized ones and the transport network in some of the largest metropolitan areas performs so badly that it provides access to the same number of opportunities offered to a resident in a much smaller metropolitan area.
Accessibility in the commuting zone is much lower than in city centres. Across 32 metropolitan areas in England, France, Italy and Spain, the number of shops reachable by car from the city centre is on average almost six times higher than for the commuting zone (Table 2.1). The ratio is as high as 23 for public transport. For access to jobs in the United Kingdom, accessibility in the commuting zone is much lower than in city centres (Swinney and Bidgood, 2014[18]).4 The rising concentration of jobs observed in the city centre of many cities is likely to accentuate such a gap. Cities are therefore coming increasingly under pressure to build a more effective integration between the city centre and commuting zone by means of their local public transport system.
Table 2.1. Differences in accessibility between the commuting zone and the city centre, 2018
|
Commuting zone |
City centre |
City centre/commuting zone ratio |
---|---|---|---|
Public transport |
28 |
651 |
23.25 |
Car |
281 |
1 617 |
5.95 |
Note: Each cell in the table reports the population‑weighted number of shops accessible within a 30-minute ride by either public transport or car, across the city, in the city centre and commuting zone. The cities included are the 32 metropolitan areas located in England, France, Italy and Spain.
Source: Data on transport accessibility are from ITF (2019[8]), Benchmarking Accessibility in Cities, International Transport Forum, Paris.
What drives access to opportunities: Proximity or performance?
Accessibility depends on the proximity of opportunities as well as the performance of the transport system. “Proximity” captures that opportunities in cities are provided close to where people live (in other words, whether housing is developed close to jobs, shopping and other opportunities). The more opportunities in the vicinity of people, the more accessible the city – independent of how well the transport network functions. “Performance” relates to the efficiency of the transport network. It captures the share of opportunities in proximity of where people live and which can be reached by car, public transport, walking or cycling. For example, London offers excellent access to opportunities by public transport compared to other cities but ranks low in terms of car accessibility. This result is driven by the subpar performance of the road network – due to congestion – compared to the public transport system.
The performance of the road network tends to be better in small metropolitan areas compared to larger ones (Figure 2.4). For example, in metropolitan areas with more than 1 million inhabitants, residents can access, on average, the total number of opportunities available in an 8 km radius plus an additional 23% within a 30-minute car ride. In metropolitan areas with less than 1 million inhabitants, the additional number of opportunities is, on average, 42%. Congestion is partly responsible for the subpar performance of the road network in large cities compared to smaller ones (ITF, 2019[8]); a more extensive commuting zone is another reason.
Better accessibility in larger metropolitan areas is driven by greater proximity to opportunities for the average resident rather than the performance of the transport network. Overall, the greater proximity to opportunities in large cities outweighs the lower performance of their transport system, thus resulting in better accessibility. Larger cities tend to provide more opportunities in the proximity of the place where people live. Their greater density reduces travel time leading to overall more attractive cities where accessibility is higher not just in certain areas but overall. This is in contrast to metropolitan areas below 750 000 inhabitants. For them, the performance of the transport network is the key distinguishing feature. Large metropolitan areas have worse transport performance compared to other metropolitan areas when it comes to car transport relative to public transport networks. Congestion matters more for car use than for public transport. There are, however, exceptions. Milan, for example, is a rather sparsely populated metropolitan area, which attenuates the issue of road congestion and improves the performance of the road network. However, the city lacks an effective public transport network connecting its commuting zone to the city centre. As a result, Milan ranks lower in its public transport performance among the metropolitan areas than in its road network performance.
Who benefits from better accessibility?
Even cities with the highest accessibility have pockets of better and worse access. The difference in accessibility for trips by car between the best-connected neighbourhoods – defined as the 500 m² grid cells with the highest accessibility in a metropolitan area that account for 25% of its population – and the worst-connected neighbourhoods (25% of the population with worst accessibility) ranges from just 1% (Saragossa, Spain) to nearly 7 times (670% in Gothenburg, Sweden).5 On average across the 118 European metropolitan areas, the number of opportunities that can be reached by residents of best-connected neighbourhoods by car is more than 2.5 times higher than the one that can be reached by residents of worst-connected neighbourhoods.
Access to opportunities by car is more unequal in larger metropolitan areas. In small metropolitan areas with less than 565 000 inhabitants, the number of shops reachable within 30 minutes of driving by residents of best-connected neighbourhoods is on average 85% higher than the number of shops reachable by residents of worst-connected neighbourhoods. In large metropolitan areas with more than 3 million inhabitants, this number is as high as 380% (Figure 2.5).6 Greater dispersion in car accessibility in larger metropolitan areas is driven by a few areas being characterised by extremely high as opposed to extremely low accessibility compared to the rest of the metropolitan area. In small metropolitan areas, the number of shops reachable within 30 minutes of driving by residents of best-connected neighbourhoods is on average 11% higher than the number of shops reachable from a neighbourhood with average accessibility. In large metropolitan areas, this number is almost 5 times larger and equal to 60%.
Greater dispersion in car accessibility for larger metropolitan areas is a by-product of a higher concentration of population in the city centre. Across the 118 metropolitan areas considered, a doubling in the number of residents is, on average, associated with a 5 percentage point increase in the share of people living in the city centre. Many of the 118 metropolitan areas have a gradient in accessibility with high accessibility in the city centre and a more or less smooth decline in accessibility as the distance from the city centre increases. If a large share of the population lives in the city centre, more people have access to a large number of shops within a short ride, thus giving rise to a larger gap between people residing in the city centre and people residing in the commuting zone.
Differences in accessibility by public transport are larger than for accessibility by car, but the difference depends less on city size (Figure 2.5). Twenty-one of the 82 European metropolitan areas with public transport data provide no access to shops within 30 minutes to at least 25% of the population in the metropolitan area. This is due to low public transport coverage of the population in the commuting zone. On average, the best-connected neighbourhoods provide access to 168% more shops via public transport than the worst-connected neighbourhoods. There is only a weak association with city size. Two factors compensating each other are behind this result. On the one hand, the number of opportunities reachable by public transport by residents of best-connected neighbourhoods is much higher in larger than in smaller cities; on the other, in small cities, a large share of the population lives in the commuting zone where public transport is often absent. These two factors tend to compensate each other, with the result that the dispersion of public transport accessibility across neighbourhoods is just as high in larger cities than in smaller ones.
Public transport uptake for the daily commute is positively associated with the effectiveness of the public transport system. An analysis based on a sample of 11 French metropolitan areas shows that workers living in neighbourhoods with better public transport performance, i.e. a larger number of local opportunities accessible by public transport, are more likely to choose public transport for their commute (Box 2.4). The probability of taking public transport to go to work in Paris is, on average, 5 percentage points higher in a neighbourhood within the top 25% of neighbourhoods in terms of public transport performance than it is in the best performing neighbourhood among the bottom 25%.7 For the metropolitan area of Marseille, the share of commuters between the same neighbourhoods differs but better performance only increases commute by 2 percentage points. Differences across cities in the extent to which transport uptake to commute to work is associated with the effectiveness of the public transport system depend on many factors, some of which are related to the public transport system, such as its cost, while some others depend on the characteristics of commuters (e.g. age, married status, number of kids, income, etc.).
Box 2.4. Does better public transport performance attract commuters in French metropolitan areas?
The probability that an individual living in a given area uses public transport to go to work as opposed to taking the car should be higher in areas where public transport offers better accessibility to local opportunities, i.e. where the public transport performance is high. Combining data on the share of workers who use public transport for their commute with performance indicators for different neighbourhoods of a sample of 11 French cities shows that this is generally the case, with better performing public transport drawing more travellers in large rather than small cities. “Performance” is defined as the percentage of opportunities (shops) within an 8 km radius that can be reached within a 30-minute ride by public transport from a given neighbourhood (500 m²-grid cell) within the metropolitan area.
Substantial differences emerge across French cities with respect to the capability of a better public transport system to attract a larger share of commuters. In Paris, for instance, a difference of 1 standard deviation in public transport performance (roughly comparing a neighbourhood at the 25th percentile with one at the 75th percentile in terms of public transport performance) is associated with a 5 percentage point higher share of commuters taking public transport. Given that the average commuter share across neighbourhoods in metropolitan Paris is about 31%, a 5 percentage point increase is a sizeable step up. In Marseille, only about 8% of workers take public transport in neighbourhoods with average public transport performance but the estimated benefit of going from the 25th to the 75th percentile of the public transport performance distribution in Marseille is only an increase of 2 percentage points. The probability of using public transport should also depend negatively on car performance. In Bordeaux, for instance, 3 percentage points more workers will choose public transport to go to work if public transport performance increases by 1 standard deviation but as many as 8 percentage points fewer workers will do so if car performance improves by 1 standard deviation.
Richer neighbourhoods are characterised by better accessibility in three out of the four countries. In France, Italy and Spain, average accessibility in high-income neighbourhoods is much higher than in low-income neighbourhoods (Figure 2.7); in England, the opposite is the case for most metropolitan areas. Average accessibility in high-income neighbourhoods is on average 3 times higher than in low-income neighbourhoods in Italy for what concerns public transport. In France and Spain, the numbers are not very different respectively, 2.9 and 2.6. The city where inequality is the highest is Milan, the one where it is the lowest is Marseille, where public transport accessibility is nearly identical in high- and low-income neighbourhoods.
High-income residents in French, Italian and Spanish cities choose to live in neighbourhoods with better public transport accessibility. Time might be more valuable for high-income households that earn a higher hourly wage, thus increasing their willingness to pay higher housing costs in more accessible areas, in particular the city centre. Additionally, high-income residents tend to value more the proximity to amenities, such as restaurants, cinemas, cafés, which may disproportionately be located in the city centre (Diamond, 2016[20]).8 There is also a tendency towards segregation of neighbourhoods by income levels that is stronger in more affluent, larger and more productive cities. The extent to which households concentrate in specific neighbourhoods tends to increase with their income levels (Patacchini et al., 2009[21]; OECD, 2018[22]).
Conversely, in England, high-income residents tend to have on average lower public transport accessibility than low-income ones. London and Sheffield are the only cities where high-income residents benefit from better accessibility than low-income ones but the differences are much smaller than for the other European cities in the sample. For instance, in London, accessibility in high-income neighbourhoods is just 27% higher than in low-income ones, which is a rather small number compared to the 500% in Milan. In all remaining English cities considered, public transport accessibility in high-income neighbourhoods is lower than in low-income ones. In Birmingham, for example, accessibility in high-income neighbourhoods is 16% of accessibility in low-income ones.
England’s metropolitan areas are an exception because low-income residents disproportionately live in the centre of cities compared to metropolitan areas in France, Italy and Spain. English metropolitan areas share this characteristic with those in the United States (Glaeser, Kahn and Rappaport, 2008[23]). There are several potential explanations behind this empirical pattern. It can be, for instance, that richer households prefer to live in larger houses, thus purchasing a house in the suburbs where land is less scarce and housing costs per square metre are therefore lower. Alternatively, it can be that a private car is an expensive means of transport, while public transport is a cheap option, albeit more time-consuming, that is especially amenable to low-income residents. For this reason, low-income residents will sort into neighbourhoods characterised by better public transport accessibility, and hence the city centre.
Differences in housing policy can be responsible for the different residential patterns observed in European cities. Local and national governments efforts to keep housing affordable can substantially lift the opportunity for low-income households to enjoy higher levels of accessibility. Public instruments supporting housing affordability can be broadly classified into two groups: direct provision of social rental housing and housing costs subsidies, typically targeted towards low-income households and generally known as housing allowances. Countries differ widely in their policy mix: for instance, in Anglophone countries, social housing rental generally represents a rather low share of total dwellings, especially when compared against Northern European countries (Salvi Del Pero et al., 2015[24]). Among these countries, however, there are some, such as the United Kingdom, that spend a high share of their gross domestic product (GDP) in housing allowances.9 It could be that housing costs subsidies by reducing the housing cost for low-income households in high-accessibility neighbourhoods favour a smaller accessibility gap between high- and low-income residents.
A snapshot of income and accessibility within (selected) metropolitan areas
In two-thirds of the 32 metropolitan areas considered, residents living in low-income neighbourhoods must rely on cars to get access to opportunities due to insufficient access via public transport. Furthermore, in half of the metropolitan areas, residents of low-income neighbourhoods have worse access to opportunities compared to residents in high-income neighbourhoods even when they rely on their car instead of public transport for getting around the city. In order to rank metropolitan areas in terms of inclusiveness in accessibility, average accessibility in high- and low-income neighbourhoods was computed. High- and low-income neighbourhoods in each metropolitan area are defined as those neighbourhoods where the average income is higher or lower than the median income in each city. Each metropolitan area for each transport mode falls into one of four categories:
1. Average accessibility in high-income neighbourhoods is 25% or more of that in low-income ones for both car and public transport trips.
2. Average accessibility in high-income neighbourhoods is 25% or more of that in low-income ones for public transport trips but high-income and low-income neighbourhoods have similar (up to 25% difference) levels of accessibility by car.
3. Average accessibility in high-income neighbourhoods is about the same as in low-income ones (up to 25% difference) for both car and public transport trips.
4. Average accessibility in low-income neighbourhoods is 25% or more of that in high-income ones for both car and public transport trips.
Categories |
Examples |
---|---|
1. High-income neighbourhoods have better car and public transport accessibility |
Bologna, Bordeaux, Firenze, Genova, Grenoble, Lille, Lyon, Madrid, Milano, Montpellier, Nantes, Paris, Rennes, Rome, Strasbourg, Toulouse |
2. High-income neighbourhoods have better accessibility by public transport but not by car |
Malaga, Napoli, Palermo, Torino, Valencia, Venezia |
3. High- and low-income neighbourhoods have similar levels of accessibility |
Bilbao, London, Marseille, Sheffield |
4. Low-income neighbourhoods have better car and public transport access |
Birmingham, Leeds, Leicester, Manchester, Newcastle, Nottingham |
Table 2.2. Cui bono? Accessibility for richer relative to poorer neighbourhoods in metropolitan areas
Richer neighbourhoods have better car and public transport accessibility |
Richer neighbourhoods have better accessibility by public transport but not by car |
Richer and poorer neighbourhoods have similar levels of accessibility |
Poorer neighbourhoods have better car and public transport access |
---|---|---|---|
Bologna |
Malaga |
Bilbao |
Birmingham |
Bordeaux |
Naples |
London |
Leeds |
Florence |
Palermo |
Marseille |
Leicester |
Genoa |
Turin |
Sheffield |
Manchester |
Grenoble |
Valencia |
Newcastle |
|
Lille |
Venice |
Nottingham |
|
Lyon |
|||
Madrid |
|||
Milan |
|||
Montpellier |
|||
Nantes |
|||
Paris |
|||
Rennes |
|||
Rome |
|||
Strasbourg |
|||
Toulouse |
Note: The threshold for “better” accessibility is at least 25% higher accessibility in one type of neighbourhood relative to the other, i.e. a large difference. Transport data refers to 2018 and income data to the closest year available. See Annex Table 2.A.3 for a description of income data.
Source: Data on transport accessibility are from ITF (2019[8]), Benchmarking Accessibility in Cities, International Transport Forum, Paris.
One can identify two distinct degrees for the lack of inclusive access in metropolitan areas based on whether they feature a lack of inclusive access to just one or both. The first – and most severe – is one where a given metropolitan area lacks inclusive access with respect to both public transport and car. The second is milder than the first and identifies metropolitan areas that lack inclusive access only with respect to public transport. Despite public transport being a cheaper transport mode and therefore better suited for low-income households, in these cities, low-income residents could at least access the same number of opportunities as high-income ones if they relied on private cars. Equally importantly, no cities in the sample considered as a feature inclusive access to opportunities by public transport and not by car. This result can be a consequence of public transport accessibility being more heterogeneously distributed than car accessibility (Figure 2.5), thus implying that large differences between socio-economic groups are more likely to be detected for the first transport mode than the second one.
In one‑third of the metropolitan areas, access to opportunities is inclusive, in the sense of low-income households enjoying at least as high accessibility as high-income ones. In 4 out of the 32 analysed metropolitan areas, access to opportunities is comparable between neighbourhoods above and below the median income. In six metropolitan areas, there is even a “reverse lack of inclusive access”, in the sense of low-income households enjoying much higher levels of accessibility than high-income ones.
There is no systematic relationship between metropolitan areas providing good overall accessibility and whether accessibility is better for richer or poorer neighbourhoods. For example, London and Marseille provide equally good accessibility to both low- and high-income neighbourhoods. Nevertheless, average public transport accessibility (for both high- and low-income residents at this point) in London exceeds the one of Marseille by a factor of five.
A tale of four (types of) cities
High-income households have the best access in Rome
The centre of the metropolitan area of Rome in Italy is predominantly inhabited by high-income residents (Figure 2.8). Since public transport in the commuting zone is nearly absent or it has rather low performance, the public transport system in Rome clearly does not provide equal access to opportunities to all of Rome’s residents. In particular, it is especially low-income households, disproportionately concentrated in the outskirts of the centre and the commuting zone, who must rely on private transport to access opportunities such as jobs or services.
The picture looks similar when focusing on car accessibility. There are some exceptions. One exception is, for instance, the southeast part of the commuting zone where the highway towards Naples and the Pontina – another important “fast road” connecting Rome with the industrial district on the way towards Latina – cuts across. Nevertheless, there remain large swathes of the commuting zone that suffer from low car accessibility, the result of which is the overall lack of inclusive access in the Italian capital with respect to private transport too.
Inclusive accessibility in Birmingham
Most metropolitan areas in England provide better accessibility to low-income neighbourhoods than high-income neighbourhoods. The location of households rather than the effectiveness of the transport system makes the difference compared to other metropolitan areas. In Birmingham, below-median income neighbourhoods are concentrated in and around the city centre. Households in these neighbourhoods, therefore, have access to a larger number of opportunities reachable either by public or private transport than high-income households (Figure 2.9). The high level of spending in housing allowances in the United Kingdom (1.06% over GDP in 2018 (OECD, 2020[25]) far above the OECD average of 0.26%) might be a contributor to the higher representation of low-income households in the centre of English cities, including Birmingham, compared to other countries.
However, Birmingham has also one of the highest levels of income segregation among European metropolitan areas (OECD, 2018[22]). Low-income households are indeed very poorly mixed with people of a different socio-economic status. Housing allowances help low-income households afford to live in areas also inhabited by families with higher socio-economic status who might, however, choose to relocate elsewhere as low-income households’ concentration increases. In the end, despite achieving greater housing affordability, high spending on housing allowances can run into the problem of fostering the transformation of certain areas of the city into enclaves inhabited predominantly by low-income households.
Housing policies aimed at expanding the access to social housing must be complemented by policies aimed at promoting “mixed communities” (Salvi Del Pero et al., 2015[24]). Mixed communities are characterised some degree by social diversity as opposed to social segregation. Housing segregation is associated with reduced upward mobility (Chetty and Hendren, 2018[26]) so that it is rarely an amenable outcome. While the principle of mixed communities for new housing development has represented an important tenet of English housing and planning policy since 2005 (Lupton and Fuller, 2009[27]), the higher degree of segregation in cities such as Birmingham or Manchester, as opposed to London for instance, shows that English cities have implemented it with a varying degree of success.
London is one of the few metropolitan areas with equal accessibility for different income groups
London differs from most other metropolitan areas in England as both low- and high-income residents enjoy a high degree of accessibility (Figure 2.10). As opposed to Birmingham, social segregation is lower, a sign that housing policies geared towards the preservation of “mixed communities” have been more successful in the British capital than in other metropolitan areas in England.
The commuting zone also benefits from high accessibility thanks to a dense public transport network that stretches well out into the commuting zone. Public transport stops are identifiable on the map by means of the dark dots aligned along the radii departing from the city centre. High density (and proximity of opportunities) at the train stations located in the commuting zone is achieved thanks to tight co‑ordination with regulators in charge of disciplining land-use and developers. For instance, the fact that the London transport authority (Transport for London or TfL) also owns much of the land surrounding the train stations favours property development around them thus raising the range of opportunities accessible in the commuting zone given the transport network.10
Public transport in Paris favours the urban centre
Nine out of ten French metropolitan areas feature a severe lack of inclusive access to opportunities. Paris, the French capital, is one such example. The comparison between Paris (Figure 2.11) and London offers an example of how land-use patterns can affect accessibility. The Parisian commuting zone – where 22% of the total population of the metropolitan area live – is characterised by a low degree of accessibility around public transport stops compared to London. It is easy to pinpoint on the map where stations of the commuter trains (e.g. RER, Transilien) are located: both cities feature sequences of high-accessibility hotspots in the commuting zone located along with a set of radii departing from the city centre. However, higher accessibility in Paris is limited to a much more geographically limited neighbourhood around public transport stops compared to London.
Hence, the articulated public transport network that stretches well into the commuting zone in both cities provides access to fewer opportunities for Parisians than it does for Londoners. A likely explanation for the different pattern is the limited availability of opportunities in the proximity of public transport stops in Paris, which stands in great contrast with the traditional service-rich high streets in many London boroughs, including peripheral ones (Carmona, 2015[28]). The disproportionate concentration of services and economic activity at large in the city centre is a long-standing feature of the French capital. The villes nouvelles strategy elaborated in the 1960s aimed at addressing what was then perceived as a barrier to growth and decentralising economic activity in a few large French cities, including Paris. Besides the creation of new towns around delocalised production centres in the commuting zone of the city, the new strategy included the construction of the RER public transport network, with the objective of integrating the new different local labour markets. Ensuring mixed development and therefore homogenous access to services besides jobs along these newly formed public transport axes was not a declared priority at that time. It is, however, an objective of the Grand Paris Express, an important project – currently under construction – that aims at better integrating via public transport the Parisian commuting zone, also known as the couronne Parisienne (Beaucire and Drevelle, 2013[29]).
Low-income households in Valencia need to rely on cars for accessibility, high-income households benefit from public transport
Residents in low-income neighbourhoods in about 20% of metropolitan areas have at least as good accessibility as high-income neighbourhoods, but only by car. Low-income neighbourhoods in Valencia (Figure 2.12) are clustered in the immediate periphery around the city centre and the southern commuting zone at large. In contrast, high-income neighbourhoods tend to be concentrated either in the city centre or in the northern commuting zone. Despite the coastal highway running all around the commuting zone, car accessibility in the northern part is less than in the south owing to the mountainous terrain and lower residential development intensity. For this reason, low-income households can access a similar number of opportunities by car to one of high-income residents, in spite of having reduced access to the services-rich city centre. Conversely, the concentration of high-income residents in the city centre is responsible for a rather low degree of inclusiveness in public transport accessibility.
A snapshot of income and accessibility across (selected) metropolitan areas
Differences in accessibility between high- and low-income neighbourhoods depend on where people live within a metropolitan area but also in what metropolitan area they choose to live. Differences in the sorting pattern of high- compared to low-income residents across cities are just as marked as differences in the sorting pattern within cities. Residents in larger cities tend to be, on average, better educated and have higher income levels than residents of smaller cities (OECD, 2015[30]). As larger cities offer better accessibility on average across their neighbourhoods (Figure 2.3), differences in the way high- and low-income households sort across cities constitutes an additional factor driving overall differences in accessibility between income groups. As a result, high-income residents benefit from better accessibility not only because they live in parts of the metropolitan area where access to opportunities is on average better (Figure 2.7) but also because many of them live in richer metropolitan areas that enjoy overall better access to opportunities, regardless of the location within the city.
In France, for example, Parisians account for 85% of people who live in the richest top 10% of neighbourhoods across the 11 metropolitan areas considered. This share rises to 100% in the top-income percentiles. In contrast, (as good as) none of the top-income neighbourhoods can be found in Lille, the capital of France’s northernmost region Hauts-de-France. Lille and Paris are also the two metropolitan areas where the number of shops accessible within 30 minutes of public transport is respectively the lowest and the highest (Figure 2.3).
Metropolitan areas in England tend to provide inclusive access but, across metropolitan areas, there are dramatic differences in where the richest and the poorest part of the population live. All neighbourhoods in the top 10% of the income distribution are in London, the metropolitan area with highest public transport accessibility, on average. In contrast, none of the top 25% of neighbourhoods in terms of household income can be found in Birmingham (Figure 2.3), the metropolitan area with the lowest level of public transport accessibility, about 1/20th of London’s.11
References
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Annex 2.A. Data sources and additional figures
Accessibility data
The EC-ITF-OECD Urban Access Framework has been implemented for 121 functional urban areas (FUAs). The car accessibility indicators discussed in this chapter refer to 118 FUAs from 25 European OECD countries and 2 European Union, non-OECD member countries. Public transport accessibility indicators are available for a subset of cities, 82 in total.
Annex Table 2.A.1. FUAs with available car accessibility estimates
Name |
FUA code |
Name |
FUA code |
Name |
FUA code |
---|---|---|---|---|---|
Vienna |
AT001 |
Thessaloniki |
EL002 |
Riga |
LV001 |
Graz |
AT002 |
Madrid |
ES001 |
The Hague |
NL001 |
Linz |
AT003 |
Barcelona |
ES002 |
Amsterdam |
NL002 |
Brussels |
BE001 |
Valencia |
ES003 |
Rotterdam |
NL003 |
Antwerp |
BE002 |
Seville |
ES004 |
Utrecht |
NL004 |
Gent |
BE003 |
Saragossa |
ES005 |
Eindhoven |
NL005 |
Liege |
BE005 |
Malaga |
ES006 |
Oslo |
NO001 |
Sofia |
BG001 |
Las Palmas |
ES008 |
Warsaw |
PL001 |
Plovdiv |
BG002 |
Bilbao |
ES019 |
Lodz |
PL002 |
Varna |
BG003 |
Helsinki |
FI001 |
Cracow |
PL003 |
Zurich |
CH001 |
Paris |
FR001 |
Wroclaw |
PL004 |
Geneva |
CH002 |
Lyon |
FR003 |
Poznan |
PL005 |
Basel |
CH003 |
Toulouse |
FR004 |
Gdansk |
PL006 |
Prague |
CZ001 |
Strasbourg |
FR006 |
Lublin |
PL009 |
Brno |
CZ002 |
Bordeaux |
FR007 |
Katowice |
PL010 |
Ostrava |
CZ003 |
Nantes |
FR008 |
Lisbon |
PT001 |
Berlin |
DE001 |
Lille |
FR009 |
Porto |
PT002 |
Hamburg |
DE002 |
Montpellier |
FR010 |
Bucaresti |
RO001 |
Munich |
DE003 |
Saint-Etienne |
FR011 |
Stockholm |
SE001 |
Cologne |
DE004 |
Rennes |
FR013 |
Gothenburg |
SE002 |
Frankfurt am Main |
DE005 |
Grenoble |
FR026 |
Malmö |
SE003 |
Stuttgart |
DE007 |
Toulon |
FR032 |
Ljubljana |
SI001 |
Leipzig |
DE008 |
Marseille |
FR203 |
Bratislava |
SK001 |
Dresden |
DE009 |
Nice |
FR205 |
London |
UK001 |
Dusseldorf |
DE011 |
Rouen |
FR215 |
West Midlands urban area |
UK002 |
Bremen |
DE012 |
Budapest |
HU001 |
Leeds |
UK003 |
Hanover |
DE013 |
Dublin |
IE001 |
Glasgow |
UK004 |
Nuremberg |
DE014 |
Rome |
IT001 |
Liverpool |
UK006 |
Freiburg im Breisgau |
DE027 |
Milan |
IT002 |
Edinburgh |
UK007 |
Augsburg |
DE033 |
Naples |
IT003 |
Manchester |
UK008 |
Bonn |
DE034 |
Turin |
IT004 |
Cardiff |
UK009 |
Karlsruhe |
DE035 |
Palermo |
IT005 |
Sheffield |
UK010 |
Ruhr |
DE038 |
Genoa |
IT006 |
Bristol |
UK011 |
Saarbrucken |
DE040 |
Florence |
IT007 |
Belfast |
UK012 |
Mannheim-Ludwigshafen |
DE084 |
Bari |
IT008 |
Newcastle upon Tyne |
UK013 |
Muenster |
DE504 |
Bologna |
IT009 |
Leicester |
UK014 |
Aachen |
DE507 |
Catania |
IT010 |
Portsmouth |
UK023 |
Copenhagen |
DK001 |
Venice |
IT011 |
Nottingham |
UK029 |
Tallinn |
EE001 |
Vilnius |
LT001 |
|
|
Athens |
EL001 |
Luxembourg |
LU001 |
|
Source: Data on transport accessibility are from ITF (2019[8]), Benchmarking Accessibility in Cities, International Transport Forum, Paris.
Annex Table 2.A.2. FUAs with available public transport accessibility estimates
Name |
FUA code |
Name |
FUA code |
Name |
FUA code |
---|---|---|---|---|---|
Vienna |
AT001 |
Lyon |
FR003 |
Utrecht |
NL004 |
Brussels |
BE001 |
Toulouse |
FR004 |
Eindhoven |
NL005 |
Antwerp |
BE002 |
Strasbourg |
FR006 |
Oslo |
NO001 |
Gent |
BE003 |
Bordeaux |
FR007 |
Warsaw |
PL001 |
Liege |
BE005 |
Nantes |
FR008 |
Wroclaw |
PL004 |
Zurich |
CH001 |
Lille |
FR009 |
Gdansk |
PL006 |
Geneva |
CH002 |
Montpellier |
FR010 |
Lisbon |
PT001 |
Basel |
CH003 |
Rennes |
FR013 |
Stockholm |
SE001 |
Prague |
CZ001 |
Grenoble |
FR026 |
Gothenburg |
SE002 |
Berlin |
DE001 |
Marseille |
FR203 |
Malmö |
SE003 |
Hamburg |
DE002 |
Nice |
FR205 |
Ljubljana |
SI001 |
Cologne |
DE004 |
Budapest |
HU001 |
London |
UK001 |
Leipzig |
DE008 |
Dublin |
IE001 |
West Midlands urban area |
UK002 |
Nuremberg |
DE014 |
Rome |
IT001 |
Leeds |
UK003 |
Bonn |
DE034 |
Milan |
IT002 |
Glasgow |
UK004 |
Karlsruhe |
DE035 |
Naples |
IT003 |
Liverpool |
UK006 |
Mannheim-Ludwigshafen |
DE084 |
Turin |
IT004 |
Edinburgh |
UK007 |
Aachen |
DE507 |
Palermo |
IT005 |
Manchester |
UK008 |
Copenhagen |
DK001 |
Genoa |
IT006 |
Cardiff |
UK009 |
Tallinn |
EE001 |
Florence |
IT007 |
Sheffield |
UK010 |
Athens |
EL001 |
Bologna |
IT009 |
Bristol |
UK011 |
Madrid |
ES001 |
Venice |
IT011 |
Belfast |
UK012 |
Valencia |
ES003 |
Vilnius |
LT001 |
Newcastle upon Tyne |
UK013 |
Malaga |
ES006 |
Luxembourg |
LU001 |
Leicester |
UK014 |
Las Palmas |
ES008 |
Riga |
LV001 |
Portsmouth |
UK023 |
Bilbao |
ES019 |
The Hague |
NL001 |
Nottingham |
UK029 |
Helsinki |
FI001 |
Amsterdam |
NL002 |
|
|
Paris |
FR001 |
Rotterdam |
NL003 |
|
Source: Data on transport accessibility are from ITF (2019[8]), Benchmarking Accessibility in Cities, International Transport Forum, Paris.
Income data
Not all countries provide data on income (or proxies thereof) at a highly disaggregated level, such as the neighbourhood level. The analysis on the distribution of accessibility across neighbourhoods according to their socio-economic status has been carried out on a sample of four large European countries that do, i.e. England (UK), France, Italy and Spain. The variables used to measure or proxy for income and the corresponding data sources are provided in Annex Table 2.A.3.
To link accessibility data with income levels, a 500-by-500-metre grid is overlapped with census tracts boundaries containing sociodemographic information. Sociodemographic information is then assigned at the grid cell level by taking a weighted average of the income variable (or its proxy) across overlapping census tracts. Only grids with no missing information for both income and accessibility and strictly positive population are retained.
Annex Table 2.A.3. Disaggregated data sources on income or proxies thereof
Variable |
Geography level |
Source |
Link |
---|---|---|---|
Disposable income |
Middle Layer Super Output Areas |
ONS |
|
Share of employment professional/ managerial occupations |
IRIS |
INSEE |
https://www.insee.fr/fr/statistiques?taille=100&debut=0&idprec=2386703&categorie=3&geo=ICQ-1 |
Share with tertiary education |
Sezioni di censimento |
ISTAT |
|
Share with tertiary education |
Secciones censales |
INE |
http://www.ine.es/censos2011_datos/cen11_datos_resultados_seccen.htm |
Accessibility of schools and hospitals
Notes
← 1. See Chapter 1 for a review of the positive externalities associated with density.
← 2. The average number of shops accessible within 30 minutes in the 20 largest metropolitan areas in the sample is 3.2 times the number in the smallest 20 cities for access by car and 2.8 times for public transport. The largest metropolitan areas have at least 2 million inhabitants for public transport and 2.6 million for access by car. The smallest 20 range from 420 000 inhabitants to 750 000 (public transport) or 625 000 (car).
← 3. See Annex Figure 2.A.1 and Annex Figure 2.A.2 for access to schools and hospitals.
← 4. Access to shops proxies for access to jobs that are more concentrated than population. Calculating the difference in access to people rather than shops shows a smaller (albeit still sizeable) disadvantage of living in the commuting zone (ITF, 2019[9]). The difference reflects the concentration of jobs (and shops) in city centres.
← 5. The difference is calculated as , which allows to retain metropolitan areas for which the 25th percentile of the accessibility distribution is equal to 0. The calculated difference ranges from 0 to 200 with small values coinciding with the percent difference between the percentiles. For large values the stated numbers are rescaled to percent differences. Concretely 150 corresponds to about 670% and 85% to 250%.
← 6. The smallest metropolitan areas correspond to the 12 (10% of the sample) smallest ones in the sample with 414 000 to 565 000 inhabitants and the largest 12 metropolitan areas are those with 3 million to 12 million inhabitants. A difference of 60 corresponds to about 185% difference in accessibility and a difference of 116% to 380%. See also the preceding endnote.
← 7. Neighbourhoods are grid cells (500 m²) and the comparison refers to the 75th percentile neighbourhood compared to the 25th percentile.
← 8. There is evidence that one of the reasons behind the divergence in residential choices of high-skilled and low-skilled people that led to the increasing concentration of the first group in a small set of US cities between 1980 and 2000 has been the capability of these cities to develop an attractive offer of amenities geared towards them (Diamond, 2016[20]).
← 9. In the United Kingdom, total spending on housing allowances amounted to 1.06% over GDP in 2018, far above the OECD average of 0.26% (OECD, 2020[25]).
← 10. TfL owned 5 700 acres of land in 2015 in the Greater London area. However, this number includes also land that cannot be used for building on because occupied by railways or roads. See https://www.theguardian.com/uk-news/davehillblog/2015/oct/20/transport-for-london-picks-first-300-acres-for-property-development-drive.
← 11. These percentiles refer to the distribution obtained pooling together the metropolitan areas considered in this report. Such distribution abstracts therefore from earnings of individuals living outside of these metropolitan areas. The units considered to calculate this distribution are Lower Super Output Areas, which contain an average of 1 500 individuals.