dc.contributor.author | Mittag, Nikolas | de |
dc.date.accessioned | 2019-04-01T09:30:01Z | |
dc.date.available | 2019-04-01T09:30:01Z | |
dc.date.issued | 2018 | de |
dc.identifier.issn | 1864-3361 | de |
dc.identifier.uri | https://www.ssoar.info/ssoar/handle/document/61946 | |
dc.description.abstract | Many important statistics are known from official records for the entire population, but have to be estimated for subpopulations. I describe two simple data combination methods that reduce the substantial sampling error of the commonly used direct survey estimates for small subpopulations. The first estimator incorporates information from repeated cross-sections, while the second estimator uses the knowledge of the statistic for the overall population to improve accuracy of the estimates for subpopulations. To evaluate the estimators, I compare the estimated number of female and elderly recipients of a government transfer program by county to the "true" number from administrative data on all recipients in New York. I find that even the simple estimators substantially improve survey error. Incorporating the statistic of interest for the overall population yields particularly large error reductions and can reduce non-sampling error. | de |
dc.language | en | de |
dc.subject.ddc | Sozialwissenschaften, Soziologie | de |
dc.subject.ddc | Social sciences, sociology, anthropology | en |
dc.subject.other | survey error; small populations food stamps; government transfers | de |
dc.title | Two Simple Methods to Improve Official Statistics for Small Subpopulations | de |
dc.description.review | begutachtet (peer reviewed) | de |
dc.description.review | peer reviewed | en |
dc.source.journal | Survey Research Methods | |
dc.source.volume | 12 | 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.thesoz | amtliche Statistik | de |
dc.subject.thesoz | official statistics | en |
dc.subject.thesoz | Schätzung | de |
dc.subject.thesoz | estimation | en |
dc.subject.thesoz | Stichprobenfehler | de |
dc.subject.thesoz | sampling error | 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 |
internal.status | formal und inhaltlich fertig erschlossen | de |
internal.identifier.thesoz | 10035431 | |
internal.identifier.thesoz | 10057146 | |
internal.identifier.thesoz | 10059347 | |
internal.identifier.thesoz | 10055811 | |
dc.type.stock | article | de |
dc.type.document | Zeitschriftenartikel | de |
dc.type.document | journal article | en |
dc.source.pageinfo | 181-192 | de |
internal.identifier.classoz | 10105 | |
internal.identifier.journal | 674 | |
internal.identifier.document | 32 | |
internal.identifier.ddc | 300 | |
dc.identifier.doi | https://doi.org/10.18148/srm/2018.v12i3.7309 | de |
dc.description.pubstatus | Veröffentlichungsversion | de |
dc.description.pubstatus | Published Version | en |
internal.identifier.licence | 3 | |
internal.identifier.pubstatus | 1 | |
internal.identifier.review | 1 | |
ssoar.urn.registration | false | de |