Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/27389 
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dc.contributor.authorJenkins, Stephen P.en
dc.contributor.authorBurkhauser, Richard V.en
dc.contributor.authorFeng, Shuaizhangen
dc.contributor.authorLarrimore, Jeffen
dc.date.accessioned2009-03-31-
dc.date.accessioned2009-08-06T13:20:59Z-
dc.date.available2009-08-06T13:20:59Z-
dc.date.issued2009-
dc.identifier.urihttp://hdl.handle.net/10419/27389-
dc.description.abstractTo measure income inequality with right censored (topcoded) data, we propose multiple imputation for censored observations using draws from Generalized Beta of the Second Kind distributions to provide partially synthetic datasets analyzed using complete data methods. Estimation and inference uses Reiter's (Survey Methodology 2003) formulae. Using Current Population Survey (CPS) internal data, we find few statistically significant differences in income inequality for pairs of years between 1995 and 2004. We also show that using CPS public use data with cell mean imputations may lead to incorrect inferences about inequality differences. Multiply-imputed public use data provide an intermediate solution.en
dc.language.isoengen
dc.publisher|aDeutsches Institut für Wirtschaftsforschung (DIW) |cBerlinen
dc.relation.ispartofseries|aDIW Discussion Papers |x866en
dc.subject.jelD31en
dc.subject.jelC46en
dc.subject.jelC81en
dc.subject.ddc330en
dc.subject.keywordIncome inequalityen
dc.subject.keywordtopcodingen
dc.subject.keywordpartially synthetic dataen
dc.subject.keywordCPSen
dc.subject.keywordcurrent population surveyen
dc.subject.keywordgeneralized beta of the second kind distributionen
dc.subject.stwEinkommensverteilungen
dc.subject.stwDisparitätsmaßen
dc.subject.stwTobit-Modellen
dc.subject.stwSchätzungen
dc.subject.stwTheorieen
dc.subject.stwUSAen
dc.titleMeasuring inequality using censored data: a multiple imputation approach-
dc.type|aWorking Paperen
dc.identifier.ppn595255892en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:diw:diwwpp:dp866en

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