Biased Prediction of Housing Values

John Knight, Carter Hill and C. F. Sirmans

Real Estate Economics, 1992, vol. 20, issue 3, 427-456

Abstract: This paper introduces the use of non‐sample, prior information to the problem of predicting prices of heterogeneous products. Using data from the 1983 American Housing Survey, the predictive performance of three Stein‐like empirical Bayes estimation rules are compared to the least squares estimator and the traditional biased estimation technique, ridge regression. The biased estimators improve upon the least squares mean square error of prediction risk under certain design‐related conditions. We provide evidence of this for the housing market in this paper.

Date: 1992
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://doi.org/10.1111/1540-6229.00590

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:reesec:v:20:y:1992:i:3:p:427-456

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=1080-8620

Access Statistics for this article

Real Estate Economics is currently edited by Crocker Liu, N. Edward Coulson and Walter Torous

More articles in Real Estate Economics from American Real Estate and Urban Economics Association Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().