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  • The main aim of this paper is to defining a multidimensional housing deprivation index and identifying 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. (xsd:string)
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?:dateModified
  • 2008 (xsd:gyear)
?:datePublished
  • 2008 (xsd:gyear)
?:doi
  • 10.1080/00036840600722323 ()
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  • true (xsd:boolean)
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  • en (xsd:string)
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?:issueNumber
  • 5 (xsd:string)
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?:name
  • Multidimensional housing deprivation indices with application to Spain (xsd:string)
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?:publicationType
  • Zeitschriftenartikel (xsd:string)
  • journal_article (en)
?:reference
?:sourceInfo
  • GESIS-SSOAR (xsd:string)
  • In: Applied Economics, 40, 2008, 5, 597-611 (xsd:string)
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?:url
?:urn
  • urn:nbn:de:0168-ssoar-240315 ()
?:volumeNumber
  • 40 (xsd:string)