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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Alan T. K. Wan & Shangyu Xie & Yong Zhou, "undated". "A varying coefficient approach to estimating hedonic housing price functions and their quantiles," GRU Working Paper Series GRU_2016_003, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    • Handle: RePEc:cth:wpaper:gru_2016_003
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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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