A FIRST STEP TOWARDS A GERMAN SYNLBD: CONSTRUCTING A GERMAN LONGITUDINAL BUSINESS DATABASE
Joerg Drechsler () and
Lars Vilhuber ()
Working Papers from U.S. Census Bureau, Center for Economic Studies
One major criticism against the use of synthetic data has been that the efforts necessary to generate useful synthetic data are so in- tense that many statistical agencies cannot afford them. We argue many lessons in this evolving field have been learned in the early years of synthetic data generation, and can be used in the development of new synthetic data products, considerably reducing the required in- vestments. The final goal of the project described in this paper will be to evaluate whether synthetic data algorithms developed in the U.S. to generate a synthetic version of the Longitudinal Business Database (LBD) can easily be transferred to generate a similar data product for other countries. We construct a German data product with infor- mation comparable to the LBD - the German Longitudinal Business Database (GLBD) - that is generated from different administrative sources at the Institute for Employment Research, Germany. In a fu- ture step, the algorithms developed for the synthesis of the LBD will be applied to the GLBD. Extensive evaluations will illustrate whether the algorithms provide useful synthetic data without further adjustment. The ultimate goal of the project is to provide access to multiple synthetic datasets similar to the SynLBD at Cornell to enable comparative studies between countries. The Synthetic GLBD is a first step towards that goal.
Keywords: confidentiality; comparative studies; German Longitudinal Business Database; synthetic data (search for similar items in EconPapers)
Pages: 18 pages
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Persistent link: https://EconPapers.repec.org/RePEc:cen:wpaper:14-13
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