Modeling Spatial and Temporal House Price Patterns: A Comparison of Four Models

Modeling Spatial and Temporal House Price Patterns: A Comparison of Four Models This research reports results from a competition on modeling spatial and temporal components of house prices. A large, well-documented database was prepared and made available to anyone wishing to join the competition. To prevent data snooping, out-of-sample observations were withheld; they were deposited with one individual who did not enter the competition, but had the responsibility of calculating out-of-sample statistics for results submitted by the others. The competition turned into a cooperative effort, resulting in enhancements to previous methods including: a localized version of Dubin’s kriging model, a kriging version of Clapp’s local regression model, and a local application of Case’s earlier work on dividing a geographic housing market into districts. The results indicate the importance of nearest neighbor transactions for out-of-sample predictions: spatial trend analysis and census tract variables do not perform nearly as well as neighboring residuals. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journal of Real Estate Finance and Economics Springer Journals

Modeling Spatial and Temporal House Price Patterns: A Comparison of Four Models

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2004 by Kluwer Academic Publishers
Subject
Economics; Regional/Spatial Science; Financial Services
ISSN
0895-5638
eISSN
1573-045X
D.O.I.
10.1023/B:REAL.0000035309.60607.53
Publisher site
See Article on Publisher Site

Abstract

This research reports results from a competition on modeling spatial and temporal components of house prices. A large, well-documented database was prepared and made available to anyone wishing to join the competition. To prevent data snooping, out-of-sample observations were withheld; they were deposited with one individual who did not enter the competition, but had the responsibility of calculating out-of-sample statistics for results submitted by the others. The competition turned into a cooperative effort, resulting in enhancements to previous methods including: a localized version of Dubin’s kriging model, a kriging version of Clapp’s local regression model, and a local application of Case’s earlier work on dividing a geographic housing market into districts. The results indicate the importance of nearest neighbor transactions for out-of-sample predictions: spatial trend analysis and census tract variables do not perform nearly as well as neighboring residuals.

Journal

The Journal of Real Estate Finance and EconomicsSpringer Journals

Published: Oct 13, 2004

References

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