Developing a Methodology for Identifying Urban Neighborhoods with Severe Housing Deprivation in Iran

AbstractThe aim of this paper is to present a methodology for identifying urban neighborhoods with severe housing deprivation (SHD) in Iran. The study, in addition to the housing physical determinants and overcrowding, considers household ’s socioeconomic characteristics as an integral dimension of SHD. It proposes a methodology that adopts census-based data and data-pooling strategy to map the spatial distribution and clustering of housing deprivation (HD) within five selected cities in Iran. First, a hybrid Factor Analysis and An alytic Network Process (F’ANP) model is used to construct a composite housing deprivation index (HDI) composed of eight HD indicators. The composite HDI is then validated using the leave-one-out cross validation method in discriminant analysis, correlation and regression analyses. Second, the comp osite HDI scores are classified into five categories using standard deviations. Then, spatial data analyses are performed to investigate the presence of spatial autocorrelation. The results confirm that HD in the selected cities is spatially autocorrelated and have a statistically significant patter n of spatial clustering that includes five distinct categories. The neighborhoods that belong to the HD hot spots are considered as the neighborhoods with SHD. The identification and spatial distribution of the neighborhoods characterized by different levels of HD, not only provide a deep knowledge about the existing housing situation, but also can effecti...
Source: Social Indicators Research - Category: International Medicine & Public Health Source Type: research