The challenges of combining two databases in small-area estimation: an example using spatial microsimulation of child poverty.
Spatial microsimulation techniques have become an increasingly popular way of fulfilling the need for generating small-area data estimates. However, the technique also poses numerous methodological challenges, including the utilisation of two different databases simultaneously to produce estimates o...
| Publicado en: | Environment & Planning A Vol. 45; no. 2; pp. 344 - 362 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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Sage Publications Inc.
Feb2013
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=86431637&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 86431637 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 0308518X EPL jtl: Environment & Planning A issn: 0308518X maglogo: Y pubinfo: dt: Feb2013 vid: 45 iid: 2 pid: 344 pub: Sage Publications Inc. artinfo: ui: 86431637 10.1068/a4511 ppf: 344 ppct: 18 formats: tig: atl: The challenges of combining two databases in small-area estimation: an example using spatial microsimulation of child poverty. aug: au: Vidyattama, Yogi Miranti, Riyana McNamara, Justine Tanton, Robert Harding, Ann affil: National Centre for Social and Economic Modelling (NATSEM), University of Canberra, ACT 2601, Australia su: Australia Poor children Poverty Microsimulation modeling (Statistics) Spatial data structures Databases sug: subj: Poor children Poverty Australia Microsimulation modeling (Statistics) Spatial data structures Databases keyword: inequality microsimulation small-area estimation inequality microsimulation small-area estimation ab: Spatial microsimulation techniques have become an increasingly popular way of fulfilling the need for generating small-area data estimates. However, the technique also poses numerous methodological challenges, including the utilisation of two different databases simultaneously to produce estimates of population characteristics at the local level. An important but neglected question is whether different distributions of key variables within these two databases may affect the validity of the spatial estimation results. This study uses the significant policy issue of small-area estimates of child poverty rates in Australia to examine this question. The different income distributions for families with children in the two databases and the consequent effect on child-poverty estimates are assessed, while the apparent validity of these synthetic small-area poverty rates is gauged. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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