Additive Hedonic Regression Models with Spatial Scaling Factors: An Application for Rents in Vienna

Wolfgang Brunauer (), Stefan Lang (), Peter Wechselberger () and Sven Bienert ()

Working Papers from Faculty of Economics and Statistics, University of Innsbruck

Abstract: We apply additive mixed regression models (AMM) to estimate hedonic price equations. Non-linear effects of continuous covariates as well as a smooth time trend are modeled non-parametrically through P-splines. Unobserved district-specific heterogeneity is modeled in two ways: First, by location specific intercepts with the postal code serving as a location variable. Second, in order to permit spatial variation in the nonlinear price gradients, we introduce multiplicative scaling factors for nonlinear covariates. This allows highly nonlinear implicit price functions to vary within a regularized framework, accounting for district-specific spatial heterogeneity. Using this model extension, we find substantial spatial variation in house price gradients, leading to a considerable improvement of model quality and predictive power.

Keywords: Hedonic regression; submarkets; multiplicative spatial scaling factors; semiparametric models; P-splines (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-geo, nep-mkt and nep-ure
Date: 2008-08
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Persistent link: http://EconPapers.repec.org/RePEc:inn:wpaper:2008-17

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