Improved Estimators of Hedonic Housing Price Models

Helen X. H. Bao () and Alan T. K. Wan ()
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Helen X. H. Bao: University of Cambridge 19 Silver Street Cambridge CB3 9EP, U.K
Alan T. K. Wan: Department of Management Sciences, City University of Hong Kong Kowloon, Hong Kong

Journal of Real Estate Research, 2007, vol. 29, issue 3, pages 267-302

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.

JEL-codes: L85 (search for similar items in EconPapers)
Date: 2007

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