Long-run urban dynamics

Understanding local housing market change in London

Bibliographic Data

ID11485237
AuthorsKenneth Gibb (0000-0002-1148-9249, University of Glasgow), Geoffrey Meen (0000-0001-8502-9694, University of Reading, corresponding author), Christian A Nygaard (0000-0002-6286-6163, Swinburne University of Technology), Christian Nygaard (Swinburne University of Technology)
Year2019
Volume34
Issue2
Pages338-359
Publication date2019-02-07
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueHousing Studies (JOURNAL)
Journal identifiersISSN: 0267-3037 • E-ISSN: 1466-1810
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/02673037.2018.1491533
OpenAlexW2877120869
LanguageEN
Citations received7
References cited29

Recently, a literature has emerged using empirical techniques to study the evolution of international cities over many centuries; however, few studies examine long-run change within cities. Conventional models and concepts are not always appropriate and data issues make long-run neighbourhood analysis particularly problematic. This paper addresses some of these points. First, it discusses why the analysis of long-run urban change is important for modern urban policy and considers the most important concepts. Second, it constructs a novel data set at the micro level, which allows consistent comparisons of London neighbourhoods in 1881 and 2001. Third, the paper models some of the key factors that affected long-run change, including the role of housing. There is evidence that the relative social positions of local urban areas persist over time but, nevertheless, at fine spatial scales, local areas still exhibit change, arising from aggregate population dynamics, from advances in technology, and also from the effects of shocks, such as wars. In general, where small areas are considered, long-run changes are likely to be greater, because individuals are more mobile over short than long distances. Finally, the paper considers the implications for policy

Demographic change · Economic geography · Economics · Empirical evidence · Geography · Macroeconomics · Neighbourhood (mathematics · Population · Regional science · Set (abstract data type · Short run · Sociology · Computer Science · Housing Market and Economics · Regional Economics and Spatial Analysis · Urban, Neighborhood, and Segregation Studies

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