Table of Contents

  • Cities are places of opportunity. In cities people can benefit from work and training opportunities, proximity to other people and physical access to many high-level services that are important for well-being. When cities are well-organised and inclusive, they allow people to access opportunities, regardless of their location within the city.

  • Cities bring together people of different backgrounds. Within this diversity, people sharing common characteristics are often found in close proximity to each other, and at the same time, separated from other social groups. Such a separation is also known as spatial segregation. There is no unique answer to the question of why segregation exists, as it is the outcome of a process that can involve preferences, as well as the availability of affordable housing in certain areas. At the same time, segregation does not necessarily represent a problem to be solved, as people that seek proximity to their own may do so precisely because there are benefits for them. In some instances, however, these positive effects can be outweighed by negative effects related to uneven access to opportunities and lack of diversity. Sustained exposure to concentrations of disadvantage at work, school and other domains have been found to affect individual outcomes, leading to vicious circles of disadvantage.

  • Cities are spaces of diversity where people of different backgrounds come together to share the benefits of proximity. In these diverse spaces, the daily experience of a given individual in terms of her contact with other socio-economic groups and her access to city services widely differs across people of different backgrounds. For some, their usual dayto- day social contact in their neighbourhood, workplace and leisure spaces can be confined to people that share roughly the same socio-economic characteristics, although the city they inhabit may be extremely diverse. Such separation is also known as spatial segregation.

  • This chapter provides an assessment of income segregation levels within cities in 12 countries. It also provides an analysis of the characteristics of cities associated with income segregation. Within-city variation in income segregation is measured using a fine‑grained method for obtaining spatial entropy indexes based on gridded income data. This measurement approach, applied to the EC-OECD functional urban areas, minimises the biases due to different administrative boundaries and allows robust international comparability. The results may inform public policy in domains connected to urban development, including housing and transport.

  • This chapter investigates the role of vertical neighbourhoods in explaining income segregation at the bottom and top of the income distribution for 100 urban agglomerations in Brazil in 2000 and 2010. Income segregation is measured using rank-order income segregation measures for different neighbourhood definitions and income percentiles. An econometric model of income segregation is fitted for income segregation measures at the bottom and top of the income distribution against a new measure that aims to capture the isolation of apartment dwellers to other type of dwellers. The results show that this measure is significant in explaining the segregation of those at the top of the income distribution but not of those at the bottom.

  • This chapter provides a broad comparison of residential distribution and segregation of immigrants in Europe, covering around 45 000 local administrative units in 8 EU member states (France, Germany, Ireland, Italy, the Netherlands, Portugal, Spain, and the United Kingdom). The analysis is based on a map of immigrant population with an unprecedented spatial resolution (i.e. cells) of 100 m by 100 m. Having discussed the importance of the local dimension for migrants’ integration, the chapter then describes the method developed to create maps and presents empirical results on, respectively, the concentration, diversity and segregation indexes across cities of destination and countries of origin. The penultimate section presents the results on possible drivers of the observed segregation indexes. The last section concludes summing up the main results and outlining possible future avenues of research.

  • This chapter studies patterns in job accessibility via transit, that is the number of jobs that are accessible with a 30-minute commute from a given census tract, across and within 46 US Core Based Statistical Areas (CBSAs). The Gini Index is used to measure inequality in job accessibility. Census and administrative data are used to construct several indices of racial segregation, concentration, and centralisation. The chapter examines the correlation between the observed inequality in job accessibility via transit and the spatial distribution of CBSAs’ residents and jobs, as measured by these indices, as well as economic outcomes such as economic inequality and unemployment. Finally, the chapter characterises tracts enjoying different levels of job accessibility, both in terms of residents’ characteristics and of geographic location within CBSAs.

  • This chapter develops a multi-level conceptual model of segregation, by using three conceptual levels – individuals and households, generations, and urban regions. Different socio-economic groups sort into different types of neighbourhoods and other domains, leading to patterns of segregation at the urban regional level. At the same time exposure to different socio-economic contexts also affects individual outcomes, and this subsequently leads to sorting processes into neighbourhoods and other domains. This vicious circle of sorting and contextual effects continuously crosses the three levels, and leads to higher levels of segregation. The chapter concludes with a discussion of several intervention strategies that focus on breaking the vicious circles to improve cities as places of opportunities by investing in people, in places and in transport.