Modeling Spatial Dimensions of Housing Prices in Milwaukee, WI

Author:

Yu Danlin1,Wei Yehua Dennis2,Wu Changshan3

Affiliation:

1. Department of Earth and Environmental Studies, Montclair State University, Montclair, NJ 07043, USA

2. Department of Geography and Urban Studies Program, University of Wisconsin—Milwaukee, Milwaukee, WI 53201, USA

3. Department of Geography, University of Wisconsin—Milwaukee, Milwaukee, WI 53201, USA

Abstract

In this study we investigate spatial dimensions of housing-market dynamics in the City of Milwaukee by modeling the determinants of housing prices. From the 2003 Master Property data file of the city, two sets of owner-occupied single-family houses were randomly selected (one to construct the models, and the other to rest the models). Besides conventional housing attributes, remote-sensing information, in particular the fractions of soil and impervious surface representing degraded neighborhood environment conditions, is added to improve the model. Spatial regression and geographically weighted regression approaches are employed to examine spatial dependence and heterogeneity. Results reveal that these spatial models tend to perform better, especially in terms of model performance and predictive accuracy, than the ordinary least squares estimates.

Publisher

SAGE Publications

Subject

General Environmental Science,Geography, Planning and Development

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