A Coregionalized Model to Predict Housing Prices

Abstract

In a uniequational hedonic model, the main source of spatial dependence is found in the explained variable, since the price of a house mainly depends on the housing prices in the neighborhood (although this can also be due to other factors, such as missing covariates and the model of choice). Dependence is one of the primary causes of spatial autocorrelation in disturbances. However, such disturbances may also be spatially correlated with the disturbances of other equations; in this case, they can be considered coregionalized. This paper presents a multi-equational hedonic regression model with coregionalized disturbances and heterotopic data. The model comprises two equations. The first explains housing prices using data from a sample, while the second explains an auxiliary variable, quality of the area, obtained from a different sample. The model is then applied practically to predict housing prices. Key words: Cokriging, housing prices, geostatistics, multi-equational hedonic model, coregionalized.]