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dc.contributor.authorVilhuber, Lars
dc.contributor.authorAbowd, John A.
dc.contributor.authorReiter, Jerome P.
dc.date.accessioned2016-02-02T21:26:44Z
dc.date.available2016-02-02T21:26:44Z
dc.date.issued2016
dc.identifier.citationStatistical Journal of the IAOS, vol. 32, no. 1, pp. 65-68, 2016
dc.identifier.urihttps://hdl.handle.net/1813/42340
dc.descriptionPresented at World Statistical Congress 2015 and Joint Statistical Meetings .
dc.description.abstractIn contrast to the many public-use microdata samples available for individual and household data from many statistical agencies around the world, there are virtually no establishment or firm microdata available. In large part, this difficulty in providing access to business micro data is due to the skewed and sparse distributions that characterize business data. Synthetic data are simulated data generated from statistical models. We organized sessions at the 2015 World Statistical Congress and the 2015 Joint Statistical Meetings, highlighting work on synthetic establishment microdata. This overview situates those papers, published in this issue, within the broader literature.en_US
dc.description.sponsorshipAbowd and Vilhuber acknowledge support through NSF Grant SES-1042181. Reiter acknowledges support through NSF grant SES-11-31897.en_US
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-160964
dc.subjectsynthetic dataen_US
dc.subjectdifferential privacyen_US
dc.subjectestablishment microdataen_US
dc.subjectUnited Statesen_US
dc.subjectBrazilen_US
dc.subjectColombiaen_US
dc.titleSynthetic Establishment Microdata Around the Worlden_US
dc.typearticleen_US
dc.description.legacydownloadsDownloads for this item at https://digitalcommons.ilr.cornell.edu/ldi/26/ as of 9/11/2020: 178


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