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

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  • Kenneth Brown
  • Bulent Uyar

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.

Suggested Citation

  • Kenneth Brown & Bulent Uyar, 2004. "A Hierarchical Linear Model Approach for Assessing the Effects of House and Neighborhood Characteristics on Housing Prices," Journal of Real Estate Practice and Education, Taylor & Francis Journals, vol. 7(1), pages 15-24, January.
    • Handle: RePEc:taf:rjrpxx:v:7:y:2004:i:1:p:15-24
    DOI: 10.1080/10835547.2004.12091603
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