Assessing Social and Territorial Vulnerability on Real Estate Submarkets

Abstract

Abstract:The concept of social vulnerability is widely studied in literature in order to identify particularly socially fragile sectors of the population. For this purpose, several studies have adopted indexes to measure the economic and social conditions of the population. The aim of this paper is to investigate the link between social and territorial vulnerability and the real estate market, by means of an exploratory analysis related to the possibility that spatial analyses can help to identify spatial latent components and variables in the process of price determination. A three phase approach is proposed, using the geographical segmentation of Turin and its related submarkets as a case study. After the identification and analysis of a set of three social and territorial vulnerability indicators, a traditional hedonic approach was applied to measure their influence on property listing prices. Subsequently, spatial analyses were investigated to focus on the spatial components of the indicators and property prices; their spatial autocorrelation was measured and the presence of spatial dependence was taken into account by applying a spatial regression. Results demonstrated that two indicators were spatially correlated with property prices and had a significant and negative influence on them. The proposed approach may help not only to identify the most vulnerable urban areas characterized by the lowest property prices, but also to support the future modification to the actual geographical segmentation of Turin.

Monitoring and Analysis of the Real Estate Market in a Social Perspective: Results from the Turin’s (Italy) Experience

“…In Reference [55], spatial analyses are illustrated for calculating the spatial autocorrelation in property prices [23,56,57] and the presence of spatial dependence [18] between social vulnerability indicators and property prices, using a sample of georeferenced data (years 2011-2017). The territorial unit used in the study is the historical territorial segment [9,58].…”

Housing and the City: A Spatial Analysis of Residential Building Activity and the Socio-Demographic Background in a Mediterranean City, 1990–2017

“…Real estate market segmentation may be achieved by applying cluster techniques that allow identification of homogeneous sub-markets based on specific metrics of building activity [40][41][42][43][44]. Due to its inherent limits, complexity and heterogeneity, urban real estate markets can be segmented into sub-markets by analyzing consistent associations among performances (characteristics) and economic attributes [45][46][47].…”

Housing Vulnerability and Property Prices: Spatial Analyses in the Turin Real Estate Market

“…In the last few years, some studies were carried out in order to study the market and territorial segmentation of the city of Turin [10,35,36,38]. One of the most important segmentations of Turin is based on the 40 microzones (submarkets), defined in 1999 by Politecnico di Torino and approved by the Municipal Council in accordance with DPR 138/98 and the Regulation issued by the Ministry of Finance.…”

“…One of the most important segmentations of Turin is based on the 40 microzones (submarkets), defined in 1999 by Politecnico di Torino and approved by the Municipal Council in accordance with DPR 138/98 and the Regulation issued by the Ministry of Finance. A series of studies on the city of Turin analyzed the relation between property prices and microzones [35,36], as well as other different territorial segmentations, such as the 3852 census cells and the 93 historical territorial units based on an urban and historical analysis developed in 2011 by Politecnico di Torino [10,38]. Microzones currently need to be updated in order to take into consideration the most recent transformations that have occurred at the urban level; therefore, with this aim, in this study, a smaller administrative urban segmentation was selected: the 94 statistical zones (SZ), defined by ISTAT as aggregations of census cells.…”

“…Firstly, it aims to study housing vulnerability in relation to the real estate market by identifying three possible indicators and spatially analyzing their influence on property prices. Secondly, it aims to compare the identified housing vulnerability indicators with two social vulnerability indicators, representative of fragile sectors of the population, which a previous study demonstrated to be spatially correlated with property prices and have a significant and negative influence on them [10]. The city of Turin and its territorial segmentation into statistical zones is assumed as a case study, and widely recognized spatial dependence analyses and spatial regression models are performed [11].…”