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- Title
The Predictive Power of Anisotropic Spatial Correlation Modeling in Housing Prices.
- Authors
Zhu, Bing; Füss, Roland; Rottke, Nico
- 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.
- Subjects
LUCAS County (Ohio); OHIO; HOME prices; ECONOMIC models; AUTOCORRELATION (Statistics); REGRESSION analysis; HOUSING market; EMPIRICAL research; ECONOMETRICS
- Publication
Journal of Real Estate Finance & Economics, 2011, Vol 42, Issue 4, p542
- ISSN
0895-5638
- Publication type
Article
- DOI
10.1007/s11146-009-9209-8