Generally, with reference to the geographical variability of real estate values, the observed variables may have non-linear relationships with the response variable. For this reason it’s possible to combine kriging techniques with additive models to obtain the geoadditive models. In this paper a geoadditive model based on penalized spline functions has been applied, in order to obtain improvements respect to usual Kriging techniques and to provide a spatial distribution of real estate unitary values for a central area of the city of Reggio Calabria (Italy). This is the first preliminary phase for the verification of the robustness of the real estate sample, or for the subsequent individuation of progressive real estate sub-samples, for to detect and to identify possible potential market premium in real estate exchange and rent markets for green buildings.

Isovalore Maps for the Spatial Analysis of Real Estate Market: A Case Study for a Central Urban Area of Reggio Calabria, Italy

MASSIMO Domenico Enrico
;
MUSOLINO Mariangela;
2019-01-01

Abstract

Generally, with reference to the geographical variability of real estate values, the observed variables may have non-linear relationships with the response variable. For this reason it’s possible to combine kriging techniques with additive models to obtain the geoadditive models. In this paper a geoadditive model based on penalized spline functions has been applied, in order to obtain improvements respect to usual Kriging techniques and to provide a spatial distribution of real estate unitary values for a central area of the city of Reggio Calabria (Italy). This is the first preliminary phase for the verification of the robustness of the real estate sample, or for the subsequent individuation of progressive real estate sub-samples, for to detect and to identify possible potential market premium in real estate exchange and rent markets for green buildings.
2019
978-3-319-92098-6
Post carbon city, Green buildings, Geoadditive models, Semiparametric regression, Real estate market analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/13222
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