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  • Statistical matching techniques have been gaining interest for several years among the producers of social statistics. This article presents the outcome from a statistical matching exercise between household income (Statistics on Income and Living Conditions - SILC), household expenditure (Household Budget Survey - HBS) and household wealth (Household Finance and Consumption Survey - HFCS) data in Luxembourg. Methodological aspects are addressed, and three examples of indicators based on the fused dataset are presented: the multidimensional poverty rate based on income, consumption and wealth, the saving rate, and the energy poverty rate. Although statistical matching offers a cheap and convenient solution to yield sophisticated indicators using information available from several databases, these methods are model-based and must yet be used with caution, taking into account the main underlying assumptions. (xsd:string)
?:author
?:comment
  • (SILC) (xsd:string)
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  • EU-SILC-Bibliography (xsd:string)
?:dateModified
  • 2023 (xsd:gyear)
?:datePublished
  • 2023 (xsd:gyear)
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  • 53 (xsd:string)
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  • french (xsd:string)
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  • 1 (xsd:string)
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  • L’appariement statistique des bases de données SILC, HBS et HFCS: aspects méthodologiques et applications à l’étude de la pauvreté et des inégalités (xsd:string)
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  • article (xsd:string)
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  • Bibsonomy (xsd:string)
  • In Statistique et Société, 11(1), 53-64, 2023 (xsd:string)
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  • European Union Statistics on Income and Living Conditions (EU-SILC) (xsd:string)
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  • 2023 (xsd:string)
  • FDZ_GML (xsd:string)
  • LFS_contra (xsd:string)
  • SILC (xsd:string)
  • SILC_input2023 (xsd:string)
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  • article (xsd:string)
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  • 64 (xsd:string)
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  • 11 (xsd:string)