Improved estimators of hedonic housing price models

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

13 Scopus Citations
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Original languageEnglish
Pages (from-to)267-301
Journal / PublicationJournal of Real Estate Research
Volume29
Issue number3
Publication statusPublished - Jul 2007

Abstract

In hedonic housing price modeling, real estate researchers and practitioners are often not completely ignorant about the parameters to be estimated. Experience and expertise usually provide them with tacit understanding of the likely values of the true parameters. Under this scenario, the subjective knowledge about the parameter value can be incorporated as non-sample information in the hedonic price model. This paper considers a class of Generalized Stein Variance Double k-class (GSVKK) estimators, which allows real estate practitioners to introduce potentially useful information about the parameter values into the estimation of hedonic pricing models. Data from the Hong Kong real estate market are used to investigate the estimators' performance empirically. Compared with the traditional Ordinary Lease Squares approach, the GSVKK estimators have smaller predictive mean squared errors and lead to more precise parameter estimates. Some results on the theoretical properties of the GSVKK estimators are also presented.

Citation Format(s)

Improved estimators of hedonic housing price models. / Bao, Helen X.H.; Wan, Alan T.K.

In: Journal of Real Estate Research, Vol. 29, No. 3, 07.2007, p. 267-301.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal