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Using Partially Synthetic Microdata to Protect Sensitive Cells in Business Statistics

dc.contributor.authorVilhuber, Lars
dc.contributor.authorMiranda, Javier
dc.date.accessioned2016-02-02T21:23:54Z
dc.date.available2016-02-02T21:23:54Z
dc.date.issued2016
dc.description.abstractWe describe and analyze a method that blends records from both observed and synthetic microdata into public-use tabulations on establishment statistics. The resulting tables use synthetic data only in potentially sensitive cells. We describe different algorithms, and present preliminary results when applied to the Census Bureau's Business Dynamics Statistics and Synthetic Longitudinal Business Database, highlighting accuracy and protection afforded by the method when compared to existing public-use tabulations (with suppressions).en_US
dc.description.sponsorshipVilhuber acknowledges support through NSF Grants SES-1042181 and BCS-0941226.en_US
dc.identifier.citationStatistical Journal of the IAOS, vol. 32, no. 1, pp. 69-80, 2016
dc.identifier.urihttps://hdl.handle.net/1813/42339
dc.language.isoen_USen_US
dc.publisherStatistical Journal of the International Association for Official Statisticsen_US
dc.relation.hasversionAccepted version: Statistical Journal of the International Association for Official Statistics, forthcoming in 2016.en_US
dc.relation.urihttp://doi.org/10.3233/SJI-160963
dc.rightsCC0 1.0 Universal*
dc.rights.urihttps://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectsynthetic dataen_US
dc.subjectstatistical disclosure limitationen_US
dc.subjectconfidentiality protectionen_US
dc.subjectgross job flowsen_US
dc.subjectlocal labor marketsen_US
dc.subjecttime-seriesen_US
dc.titleUsing Partially Synthetic Microdata to Protect Sensitive Cells in Business Statisticsen_US
dc.typearticleen_US

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