Discrete Choice Modelling of Urban Housing Markets: A Critical Review and an Application
Judith Yates and
Daniel F. Mackay
Additional contact information
Daniel F. Mackay: Department of General Practice, University of Glasgow, 1 Horselethill Road, Glasgow, G12 9LX, UK. Daniel.Mackay@clinmed.gla.ac.uk
Urban Studies, 2006, vol. 43, issue 3, 559-581
Abstract:
The housing choice literature is a vast area of housing research which has resulted in giant leaps forward in recent years in terms of its econometric modelling. This is due in large part to the significant increases now available in computing power allowing researchers to combine the latest advances in theory with empirical application. This paper brings together and critically reviews the housing choice literature and techniques that have been used to model the household's housing choice decision. The basic multinomial logit model is reviewed alongside the more recent advances in discrete choice modelling-the nested multinomial logit model and the heteroscedastic extreme value model. The various techniques are illustrated using data from the Australian census of 1986 and 1996 to model housing choice in Sydney. The results show that careful consideration must be given to the assumptions underlying any chosen modelling technique if one is not to draw misleading conclusions from the analysis.
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)
Downloads: (external link)
https://journals.sagepub.com/doi/10.1080/00420980500533695 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:sae:urbstu:v:43:y:2006:i:3:p:559-581
DOI: 10.1080/00420980500533695
Access Statistics for this article
More articles in Urban Studies from Urban Studies Journal Limited
Bibliographic data for series maintained by SAGE Publications ().