Faculty Publications

Bayesian Spatial Modeling Of Housing Prices Subject To A Localized Externality

Document Type

Article

Keywords

Geostatistics, Hedonic regression, Monte Carlo, Random field, Real estate data

Journal/Book/Conference Title

Communications in Statistics - Theory and Methods

Volume

37

Issue

13

First Page

2066

Last Page

2078

Abstract

This work proposes a non stationary random 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.

Department

Department of Mathematics

Original Publication Date

1-1-2008

DOI of published version

10.1080/03610920701858404

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