Hedonic House Price Modeling Based on Multilevel Structured Additive Regression View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2015

AUTHORS

Alexander Razen , Wolfgang Brunauer , Nadja Klein , Stefan Lang , Nikolaus Umlauf

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. More... »

PAGES

97-122

References to SciGraph publications

Book

TITLE

Computational Approaches for Urban Environments

ISBN

978-3-319-11468-2
978-3-319-11469-9

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-11469-9_5

DOI

http://dx.doi.org/10.1007/978-3-319-11469-9_5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1026721456


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