Multidimensional housing deprivation indices with application to Spain
The main aim of this article is to define a multidimensional housing deprivation index and identify the main determining characteristics of this phenomenon, using Spain as reference. A latent variable model is used in order to overcome some of the traditional difficulties encountered in multidimensional deprivation studies. The construction of a latent structure model has allowed a set of partial housing deprivation indices to be grouped together under a single index. It has also enabled each individual to be assigned to a different class depending on the level and type of deprivation. Results show that the vector of observed variables (having hot running water, heating, a leaky roof, damp walls or floor, rot in window frames and floors and overcrowding) and the correlations among such variables can be explained by a single latent variable. There are also specific characteristics that differentiate the population affected by housing deprivation.
Volume (Year): 40 (2008)
Issue (Month): 5 ()
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