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Hedonic House Price Modeling Based on Multilevel Structured Additive Regression

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Computational Approaches for Urban Environments

Part of the book series: Geotechnologies and the Environment ((GEOTECH,volume 13))

Abstract

This chapter reviews recent developments in hedonic modeling of house prices based on structured additive regression (STAR) models. In STAR models, continuous covariates are modeled as P(enalized)-splines. Furthermore, random effects for spatial indexes, smooth functions of two-dimensional surfaces, and (spatially) varying coefficient terms may also be estimated using this methodology. Based on hierarchical STAR models, we discuss a number of useful extensions. With respect to value-at-risk concepts, financial institutions are often not only interested in the expected value but also in different quantiles of the distribution of real estate prices. To meet these requirements, we apply multilevel STAR models for location scale and shape (GAMLSS type regression) and a Bayesian version of quantile regression. As another extension, we sketch multiplicative region-specific scaling factors for nonlinear covariates in order to permit spatial variation in the nonlinear price gradients.

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Acknowledgements

This work was supported by funds of the Oesterreichische Nationalbank (Oesterreichische Nationalbank, Anniversary Fund, project number: 15309).

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Authors and Affiliations

  1. University of Innsbruck, Universitätsstraße 15, A-6020, Innsbruck, Austria

    Alexander Razen, Stefan Lang & Nikolaus Umlauf

  2. UniCredit Bank Austria AG, Julius Tandler-Platz 3, A-1090, Wien, Austria

    Wolfgang Brunauer

  3. University of Göttingen, Platz der Göttinger Sieben 5, D-37073, Göttingen, Germany

    Nadja Klein

Authors
  1. Alexander Razen
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  2. Wolfgang Brunauer
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  3. Nadja Klein
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  4. Stefan Lang
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  5. Nikolaus Umlauf
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Corresponding author

Correspondence to Alexander Razen .

Editor information

Editors and Affiliations

  1. Department of Human Geography and Spatial Planning, Utrecht University, Utrecht, The Netherlands

    Marco Helbich

  2. Institute of Geography, Heidelberg University, Heidelberg, Germany

    Jamal Jokar Arsanjani

  3. Dept. of Geography and Anthropology, Louisiana State University, Baton Rouge, Louisiana, USA

    Michael Leitner

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Razen, A., Brunauer, W., Klein, N., Lang, S., Umlauf, N. (2015). Hedonic House Price Modeling Based on Multilevel Structured Additive Regression. In: Helbich, M., Jokar Arsanjani, J., Leitner, M. (eds) Computational Approaches for Urban Environments. Geotechnologies and the Environment, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-11469-9_5

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