A Hierarchical Linear Model Approach for Assessing the Effects of House and Neighborhood Characteristics on Housing Prices

Kenneth Brown and Bulent Uyar

Journal of Real Estate Practice and Education, 2004, vol. 7, issue 1, 15-24

Abstract: This pedagogical paper illustrates how a hierarchical linear model (Raudenbush and Bryk, 2002) can be used by researchers and practitioners to estimate housing prices as a function of both house and neighborhood characteristics. While traditional hedonic regression models allow researchers to include both house and neighborhood characteristics in the study of housing prices, hedonic regression does not account for the inherent hierarchy in the housing purchase decision, namely that houses reside in neighborhoods, which in turn exist within cities and states. On the other hand, multinomial logit models incorporate such hierarchy but focus primarily on the housing purchase decision and not the housing price. Thus, the hierarchical linear model gives researchers a more flexible tool to model housing prices.

Date: 2004
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10835547.2004.12091603 (text/html)
Access to full text is restricted to subscribers.

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:taf:rjrpxx:v:7:y:2004:i:1:p:15-24

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/rjrp20

DOI: 10.1080/10835547.2004.12091603

Access Statistics for this article

Journal of Real Estate Practice and Education is currently edited by Reid Cummings

More articles in Journal of Real Estate Practice and Education from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().