Estimation of Housing Price Variations Using Spatio-Temporal Data
Jorge Chica-Olmo,
Rafael Cano-Guervos and
Mario Chica-Rivas
Additional contact information
Jorge Chica-Olmo: Department of Quantitative Methods for Economics and Business, University of Granada, 18011 Granada, Spain
Rafael Cano-Guervos: Department of Quantitative Methods for Economics and Business, University of Granada, 18011 Granada, Spain
Mario Chica-Rivas: Department of Mathematical Analysis, University of Granada, 18071 Granada, Spain
Authors registered in the RePEc Author Service: rafael cano guervós, Sr. ()
Sustainability, 2019, vol. 11, issue 6, 1-21
Abstract:
This paper proposes a hedonic regression model to estimate housing prices and the spatial variability of prices over multiple years. Using the model, 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 cokriging with 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.
Keywords: hedonic regression model; cokriging; spatio-temporal; housing price variation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (11)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:6:p:1551-:d:213821
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