A varying coefficient approach to estimating hedonic housing price functions and their quantiles

Alan T. K. Wan (), Shangyu Xie and Yong Zhou
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Alan T. K. Wan: City University of Hong Kong
Shangyu Xie: University of International Business and Economics
Yong Zhou: Shanghai University of Finance and Economics

No GRU_2016_003, GRU Working Paper Series from City University of Hong Kong, Department of Economics and Finance, Global Research Unit

Abstract: The varying coefficient (VC) model introduced by Hastie and Tibshirani (1993) is arguably one of the most remarkable recent developments in nonparametric regression theory. The VC model is an extension of the ordinary regression model where the coef- ficients are allowed to vary as smooth functions of an effect modifier possibly different than the regressors. The VC model reduces the modeling bias with its unique structure while also avoiding the “curse of dimensionality” problem. While the VC model has been applied widely in a variety of disciplines, its application in economics has been minimal. The central goal of this paper is to apply VC modeling to the estimation of a hedonic house price function using data from Hong Kong, one of the world’s most buoyant real estate markets. We demonstrate the advantages of the VC approach over traditional parametric and semi-parametric regressions in the face of a large number of regressors. We further combine VC modeling with quantile regression to examine the heterogeneity of the marginal effects of attributes across the distribution of housing prices.

Keywords: hedonic price function; heterogeneity; housing; kernel estimation; quantile regression; varying-coefficient (search for similar items in EconPapers)
JEL-codes: C14 C21 R21 (search for similar items in EconPapers)
Pages: 24 pages
New Economics Papers: this item is included in nep-ure
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Published in Journal of Applied Statistics, Volume 44-11, Pages 1979-1999

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