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?:abstract
  • There has been rising interest in research on poverty mapping over the last decade, with the European Union proposing a core of statistical indicators on poverty commonly known as Laeken Indicators. They include the incidence and the intensity of poverty for a set of domains (e.g. young people, unemployed people). The EU-SILC (European Union-Statistics on Income and Living Conditions) survey represents the most important source of information to estimate these poverty indicators at national or regional level (NUTS 1-2 level). However, local policy makers also require statistics on poverty and living conditions at lower geographical/domain levels, but estimating poverty indicators directly from EU-SILC for these domains often leads to inaccurate estimates. To overcome this problem there are two main strategies: i. increasing the sample size of EU-SILC so that direct estimates become reliable and ii. resort to small area estimation techniques. In this paper we compare these two alternatives: with the availability of an oversampling of the EU-SILC survey for the province of Pisa, obtained as a side result of the SAMPLE project (Small Area Methods for Poverty and Living Conditions, http://www.sample-project.eu/), we can compute reliable direct estimates that can be compared to small area estimates computed under the M-quantile approach. Results show that the M-quantile small area estimates are comparable in terms of efficiency and precision to direct estimates using oversample data. Moreover, considering the oversample estimates as a benchmark, we show how direct estimates computed without the oversample have larger errors as well as larger estimated mean squared errors than corresponding M-quantile estimates. (xsd:string)
?:author
?:comment
  • (SILC) (xsd:string)
?:dataSource
  • EU-SILC-Bibliography (xsd:string)
?:dateModified
  • 2012 (xsd:gyear)
?:datePublished
  • 2012 (xsd:gyear)
?:doi
  • 10.18148/srm/2012.v6i3.5131 ()
?:duplicate
?:fromPage
  • 155 (xsd:string)
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?:inLanguage
  • english (xsd:string)
?:isPartOf
?:issn
  • 1864-3361 ()
?:issueNumber
  • 3 (xsd:string)
is ?:mainEntity of
?:name
  • Robust Small Area Estimation and Oversampling in the Estimation of Poverty Indicators (xsd:string)
?:publicationType
  • article (xsd:string)
?:sourceInfo
  • Bibsonomy (xsd:string)
  • In Survey Research Methods, 6(3), 155-163, 2012 (xsd:string)
?:studyGroup
  • European Union Statistics on Income and Living Conditions (EU-SILC) (xsd:string)
?:tags
  • 2012 (xsd:string)
  • FDZ_GML (xsd:string)
  • SCOPUSindexed (xsd:string)
  • SILC (xsd:string)
  • SILC_input2020 (xsd:string)
  • SILC_pro (xsd:string)
  • SSCIindexed (xsd:string)
  • article (xsd:string)
  • checked (xsd:string)
  • imported (xsd:string)
  • indexproved (xsd:string)
  • jak (xsd:string)
  • reviewed (xsd:string)
?:toPage
  • 163 (xsd:string)
rdf:type
?:url
?:volumeNumber
  • 6 (xsd:string)