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Biased Prediction of Housing Values
Author(s) -
Knight J. R.,
Hill R. Carter,
Sirmans C. F.
Publication year - 1992
Publication title -
real estate economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.064
H-Index - 61
eISSN - 1540-6229
pISSN - 1080-8620
DOI - 10.1111/1540-6229.00590
Subject(s) - estimator , econometrics , ordinary least squares , economics , estimation , mean squared error , bayes' theorem , statistics , regression , sample (material) , least squares function approximation , mathematics , actuarial science , bayesian probability , chemistry , management , chromatography
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.