Comparing Residential Segregation of Migrant Populations in Selected European Urban and Metropolitan Areas

2020 
Residential segregation is a well studied subject especially after the publication of the pioneering and seminal contribution of Duncan and Duncan (Am Sociol Rev 41:210–217, 1955). Considering the theoretical and methodological advances made since then, the contribution endeavours in describing and understanding the differences in residential segregation in an international perspective using 2011 population census data. The contribution analyses the residential segregation of migrants (here foreign citizens or foreign born) usually resident in the 493 Functional Urban Areas (FUAs) of selected European Union countries. The analysis is conducted using 2011 census data on regular grid (100 mt × 100 mt) provided by the Data Challenge on ‘Integration of Migrants in Cities’ (D4I) and refers to all migrants and to two sub groups (EU 28 and non EU 28). In a first step the levels and spatial patterns of residential segregation across all FUAs of France, Germany, Ireland, Italy, Portugal, Spain, The Netherlands and the United Kingdom are analysed. Particular attention is paid to identifying differences and similarities between the FUAs, among and within the single countries. In a further analysis the relationship between the level of residential segregation in the metropolitan FUAs of the selected EU countries and contextual demographic and socio-economic factors are investigated. Results indicate that, even if, the larger metropolitan areas attract more migrants, the highest levels of residential segregation are observed in smaller urban areas. Moreover important national peculiarities emerge clearly with countries of northwestern Europe recording lower levels of residential segregation compared to the Southern European countries. Finally, residential segregation shows clear relationships with some contextual factors, especially the ones related to economic well-being and the labour market in a positive manner.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    49
    References
    5
    Citations
    NaN
    KQI
    []