What is the “best” way to measure the relative location variables in the market value assessment? An econometric method applied to an Italian case study

Abstract

The present research is dedicated to investigating the explanatory power of relative location variables in assessing and forecasting market values. Here, relative location refers to the spatial position (geographical context) of a building or property in relation to a given Point Of Interest (POI). Specifically, a methodological approach is proposed for identifying the most suitable quantification modality based on statistical performance and consistency with the market mechanisms of the specific reference context. For a case study in Northern Italy, we collected data on 615 residential properties and 2673 POIs, including cultural facilities, school and education institutions, commercial services, sports, entertainment, and leisure facilities, health and care services, public transport systems, urban parks, and green areas. The relative location between the collected properties and the POIs is assessed using an automated calculation procedure developed in the Python programming language, in conjunction with Geographic Information Software (GIS). This automatism allows the assessment of relative location in terms of different Units Of Measure (UOM), such as straight-line distance, travel time by car, travel time on foot, travel time by public transport, and the number of POIs in a 400 m/1 km ring buffer. Since 615 residential buildings and 2673 POIs were analysed, with their relative locations measured using six different UOMs, a database of 9'865'215 data was produced. Furthermore, for each category of POI, a feature importance analysis guides the selection of the best UOM, i.e., the most statistically significant one. Considering the chosen UOM, an optimised econometric technique is finally implemented to analyse the functional relationships between the market values of residential properties and the set of identified relative location variables.