Synthetic datasets for the German IAB Establishment Panel

Abstract

"Disseminating microdata to the public that provide a high level of data utility while at the same time guaranteeing the confidentiality of the survey respondent is a difficult task. Generating multiply imputed synthetic datasets is an innovative statistical disclosure limitation technique with the potential of enabling the data disseminating agency to achieve this twofold goal. So far, the approach was successfully implemented only for a limited number of datasets in the U.S. In this paper we present the first successful implementation outside the U.S.: The generation of partially synthetic datasets for a German establishment survey, the IAB Establishment Panel. We will describe the synthesis, present our disclosure risk evaluations and provide some first results on the data utility of the generated datasets." (Author's abstract, IAB-Doku) ((en))

Cite article

Drechsler, J. (2009): Synthetic datasets for the German IAB Establishment Panel. (Joint UNECE/Eurostat Work Session on Statistical Data Confidentiality 2009. Working paper 10), New York, 13 p.