Bayesian Spatial Modeling of Housing Prices Subject to a Localized Externality

Mark Ecker and Victor Oliveira
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Mark Ecker: University of Northern Iowa
Victor Oliveira: University of Texas at San Antonio

No 30, Working Papers from College of Business, University of Texas at San Antonio

Abstract: This work proposes a non-stationary ramdom field model to describe the spatial variability of housing prices that are affected by a localized externality. The model allows for the effect of the localized externality on house prices to be represented in the mean function and/or the covariance function of the random field. The correlation function of the proposed model is a mixture of an isotropic correlation function and a correlation function that depends on the distances between home sales and the localized externality. The model is fit using a Bayesian approach via a Markov chain Monte Carlo Algorithm. A dataset of 437 single family home sales during 2001 in the city of Cedar Falls, Iowa, is used to illustrate the model.

Keywords: Geostatistics, Hedonic regression; Monte Carlo; Random field; Real estate data. (search for similar items in EconPapers)
JEL-codes: C11 C16 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2007-12-10
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