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Robust small area estimation and oversampling in the estimation of poverty indicators
Stabile Schätzung von Kleinflächen und Oversampling bei der Schätzung von Armutsindikatoren
[journal article]
dc.contributor.author | Giusti, Caterina | de |
dc.contributor.author | Marchetti, Stefano | de |
dc.contributor.author | Pratesi, Monica | de |
dc.contributor.author | Salvati, Nicola | de |
dc.date.accessioned | 2015-08-13T15:27:30Z | |
dc.date.available | 2015-08-13T15:27:30Z | |
dc.date.issued | 2012 | de |
dc.identifier.issn | 1864-3361 | de |
dc.identifier.uri | http://www.ssoar.info/ssoar/handle/document/44234 | |
dc.description.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 the authors 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/ ), they 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, they show how direct estimates computed without the oversample have larger errors as well as larger estimated mean squared errors than corresponding M-quantile estimates." (author's abstract) | en |
dc.language | en | de |
dc.subject.ddc | Sozialwissenschaften, Soziologie | de |
dc.subject.ddc | Social sciences, sociology, anthropology | en |
dc.subject.ddc | Soziale Probleme und Sozialdienste | de |
dc.subject.ddc | Social problems and services | en |
dc.title | Robust small area estimation and oversampling in the estimation of poverty indicators | de |
dc.title.alternative | Stabile Schätzung von Kleinflächen und Oversampling bei der Schätzung von Armutsindikatoren | de |
dc.description.review | begutachtet (peer reviewed) | de |
dc.description.review | peer reviewed | en |
dc.source.journal | Survey Research Methods | |
dc.source.volume | 6 | de |
dc.publisher.country | DEU | |
dc.source.issue | 3 | de |
dc.subject.classoz | Erhebungstechniken und Analysetechniken der Sozialwissenschaften | de |
dc.subject.classoz | Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods | en |
dc.subject.classoz | soziale Probleme | de |
dc.subject.classoz | Social Problems | en |
dc.subject.thesoz | Methode | de |
dc.subject.thesoz | method | en |
dc.subject.thesoz | Messung | de |
dc.subject.thesoz | measurement | en |
dc.subject.thesoz | Armut | de |
dc.subject.thesoz | poverty | en |
dc.subject.thesoz | Indikator | de |
dc.subject.thesoz | indicator | en |
dc.subject.thesoz | Indikatorenforschung | de |
dc.subject.thesoz | indicator research | en |
dc.subject.thesoz | Indikatorenbildung | de |
dc.subject.thesoz | construction of indicators | en |
dc.subject.thesoz | Daten | de |
dc.subject.thesoz | data | en |
dc.subject.thesoz | Datenorganisation | de |
dc.subject.thesoz | data organization | en |
dc.subject.thesoz | Datenqualität | de |
dc.subject.thesoz | data quality | en |
dc.rights.licence | Deposit Licence - Keine Weiterverbreitung, keine Bearbeitung | de |
dc.rights.licence | Deposit Licence - No Redistribution, No Modifications | en |
ssoar.gesis.collection | aDIS | de |
internal.status | formal und inhaltlich fertig erschlossen | de |
internal.identifier.thesoz | 10036452 | |
internal.identifier.thesoz | 10036930 | |
internal.identifier.thesoz | 10036765 | |
internal.identifier.thesoz | 10047129 | |
internal.identifier.thesoz | 10047138 | |
internal.identifier.thesoz | 10047135 | |
internal.identifier.thesoz | 10034708 | |
internal.identifier.thesoz | 10040555 | |
internal.identifier.thesoz | 10055811 | |
dc.type.stock | article | de |
dc.type.document | Zeitschriftenartikel | de |
dc.type.document | journal article | en |
dc.source.pageinfo | 155-163 | de |
internal.identifier.classoz | 10105 | |
internal.identifier.classoz | 20500 | |
internal.identifier.journal | 674 | |
internal.identifier.document | 32 | |
internal.identifier.ddc | 300 | |
internal.identifier.ddc | 360 | |
dc.source.issuetopic | Papers from ITACOSM11 | de |
dc.identifier.doi | https://doi.org/10.18148/srm/2012.v6i3.5131 | de |
dc.description.pubstatus | Veröffentlichungsversion | de |
dc.description.pubstatus | Published Version | en |
internal.identifier.licence | 3 | |
internal.identifier.pubstatus | 1 | |
internal.identifier.review | 1 | |
dc.description.misc | gesis-solis-00590831 | de |
internal.pdf.valid | false | |
internal.pdf.wellformed | false | |
internal.check.abstractlanguageharmonizer | CERTAIN |
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Erhebungstechniken und Analysetechniken der Sozialwissenschaften
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods -
soziale Probleme
Social Problems