The Predictive Power of Anisotropic Spatial Correlation Modeling in Housing Prices
Journal
Journal of Real Estate Finance and Economics
ISSN
0895-5638
ISSN-Digital
1573-045X
Type
journal article
Date Issued
2011-05-01
Author(s)
Abstract
This paper develops a method to capture anisotropic spatial autocorrelation in the context of the simultaneous autoregressive model. Standard isotropic models assume that spatial correlation is a homogeneous function of distance. This assumption, however, is oversimplified if spatial dependence changes with direction. We thus propose a local anisotropic approach based on non-linear scale-space image processing. We illustrate the methodology by using data on single-family house transactions in Lucas County, Ohio. The empirical results suggest that the anisotropic modeling technique can reduce both in-sample and out-of-sample forecast errors. Moreover, it can easily be applied to other spatial econometric functional and kernel forms.
Language
English
Keywords
Spatial regression - Hedonic price model - Anisotropic spatial correlation - Simultaneous autoregressive model - Housing market
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Springer Science
Publisher place
New York
Volume
42
Number
4
Start page
542
End page
565
Pages
24
Subject(s)
Eprints ID
216299
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Name
Zhu_PredictivePower.pdf
Size
735.61 KB
Format
Adobe PDF
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