Estimation of Housing Price Variations Using Spatio-Temporal Data
Metadatos
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Materia
Hedonic regression model Cokriging Spatio-temporal Housing price variation
Fecha
2019-03-14Referencia bibliográfica
Chica Olmo, J.; Cano-Guervos, R.; Chica Rivas, M.. Estimation of Housing Price Variations Using Spatio-Temporal Data. Sustainability 2019, 11, 1551; doi:10.3390/su11061551.
Patrocinador
This work was conducted within the framework of a research project granted by CEMIX-6/16 and financed by Banco Santander.Resumen
This paper proposes a hedonic regression model to estimate housing prices and the spatial
variability of prices overmultiple years. Using themodel, maps are obtained that represent areas of the
city where there have been positive or negative changes in housing prices. The regression-cokriging
(RCK)method is used to predict housing prices. The results are compared to the cokrigingwith external
drift (CKED) model, also known as universal cokriging (UCK). To apply the model, heterotopic data
of homes for sale at different moments in time are used. The procedure is applied to predict the spatial
variability of housing prices in multi-years and to obtain isovalue maps of these variations for the city
of Granada, Spain. The research is useful for the fields of urban studies, economics, real estate, real
estate valuations, urban planning, and for scholars.