Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/71939 
Year of Publication: 
2008
Series/Report no.: 
Working Papers in Economics and Statistics No. 2008-17
Publisher: 
University of Innsbruck, Department of Public Finance, 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.
Subjects: 
hedonic regression
submarkets
multiplicative spatial scaling factors
semiparametric models
P-splines
Document Type: 
Working Paper

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