The Value Spatial Component in the Real Estate Market: the Turin Case Study.

In the study of variables affecting the determination of property prices, the spatial component is playing an increasingly significant role. In order to quantify the property value variability due to its location, it is necessary to resort to spatial statistics. The aim of this paper is twofold. On the one hand, we propose a geostatistical model aimed at identifying the incidence of position on housing asking prices. Starting from a geostatistical model we propose a methodology to empirically measure the incidence of a geographical segmentation on asking prices. The purpose of this paper is to test whether appraisers take account of the location in defining the asking prices, that represent the first signal of houses values. The proposed model is tested on a sample of residential properties, listed on the Turin real estate market. On the other hand, staring from the results of the model, the purpose of the present work is to formulate economic-estimative interpretations of the Turin real estate market dynamics.