This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Meen, D. Articles by Meen, G. Search for Related Content Social Bookmarking                   What's this?

Social Behaviour as a Basis for Modelling the Urban Housing Market: A Review

Centre for Spatial and Real Estate Economics, Department of Economics, School of Business, The University of Reading, PO Box 219, Whiteknights, Reading RG6 6AW, UK,

Geoffrey Meen

Centre for Spatial and Real Estate Economics, Department of Economics, School of Business, The University of Reading, PO Box 219, Whiteknights, Reading RG6 6AW, UK, g.p.meen{at}reading.ac.uk

This paper considers how empirical models of urban housing markets might be constructed as a basis for policy analysis. It is suggested that this is fundamentally more difficult than national or regional models, because of particular characteristics of urban markets-notably, the importance of social interactions, non-linearity and segregation. However, recent advances in the modelling of social interactions point to a possible way forward. The paper begins by reviewing some aspects of this literature and shows how the models generate non-linearities consistent with recent work on thresholds in local housing markets. Simple cellular automata are also used to demonstrate this point and how segregation may arise. A review follows of work on discrete choice models, which include social interactions within their structure. Bringing all the tools together, it is suggested that there is now the potential to construct urban housing models, although a great deal of theoretical and empirical work remains to be done.

CiteULike    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?