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Regional Science Policy & Practice

Urban Preferences, Amenities and Age: Exploring the Spatial Distribution of Age in Stockholm from 1991 to 2011

Journal Article
Reference
Andersson, Martin, Johan P. Larsson and Joakim Wernberg (2018). “Urban Preferences, Amenities and Age: Exploring the Spatial Distribution of Age in Stockholm from 1991 to 2011”. Regional Science Policy & Practice 10(4), 367–381. doi.org/10.1111/rsp3.12150

Authors
Martin Andersson, Johan P. Larsson, Joakim Wernberg

Cities exhibit a rich and complex heterogeneity in people and activities. This poses a sizable challenge for planners when planning new neighbourhoods or the reconstruction of old ones as well as when considering the allocation of supply of and demand for amenities, e.g. kindergartens or health facilities. However, individual preferences may also exhibit common denominators that may provide structure to this heterogeneity. One such denominator is age. In this paper we introduce the concept of neighbourhood age, defined as the mean age of people living in exogenously defined squares of 1km2 in a city. We use highly disaggregated geocoded data to map how the spatial distribution of neighbourhood age changes over a 20‐year period from 1991 to 2011 in the city of Stockholm, Sweden. We then test the correlation between neighbourhood age and two categories of urban amenities: supply of local consumption amenities and distance to the city's central business district (CBD). The paper presents three main findings: First, neighbourhood age changes and polarizes significantly over the observed period, suggesting that different age groups are concentrating in different parts of the city. Second, there is a rejuvenation in the central parts of the city but also in more distant clusters of amenities. Third, over a long‐term perspective, the results suggest that local clusters of consumption amenities outside the inner city may become increasingly attractive to younger people. Our conclusion is that neighbourhood age and age‐related patterns over time provides a tool for planners to better understand the spatial distribution of age‐related demand.