Predicting House Prices Using Multiple Listings Data

Predicting House Prices Using Multiple Listings Data It is often necessary to accurately predict the price of a house between sales. One method of predicting house values is to use data on the characteristics of the area's housing stock to estimate a hedonic regression, using ordinary least squares (OLS) as the statistical technique. The coefficients of this regression are then used to produce the predicted house prices. However, this procedure ignores a potentially large source of information regarding house prices—the correlations existing between the prices of neighboring houses. The purpose of this article is to show how these correlations can be incorporated when estimating regression coefficients and when predicting house prices. The practical difficulties inherent in using a technique called kriging to predict house prices are discussed. The article concludes with an example of the procedure using multiple listings data from Baltimore. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journal of Real Estate Finance and Economics Springer Journals

Predicting House Prices Using Multiple Listings Data

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 1998 by Kluwer Academic Publishers
Subject
Economics; Regional/Spatial Science; Financial Services
ISSN
0895-5638
eISSN
1573-045X
D.O.I.
10.1023/A:1007751112669
Publisher site
See Article on Publisher Site

Abstract

It is often necessary to accurately predict the price of a house between sales. One method of predicting house values is to use data on the characteristics of the area's housing stock to estimate a hedonic regression, using ordinary least squares (OLS) as the statistical technique. The coefficients of this regression are then used to produce the predicted house prices. However, this procedure ignores a potentially large source of information regarding house prices—the correlations existing between the prices of neighboring houses. The purpose of this article is to show how these correlations can be incorporated when estimating regression coefficients and when predicting house prices. The practical difficulties inherent in using a technique called kriging to predict house prices are discussed. The article concludes with an example of the procedure using multiple listings data from Baltimore.

Journal

The Journal of Real Estate Finance and EconomicsSpringer Journals

Published: Oct 6, 2004

References

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