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Applying data synthesis for longitudinal business data across three countries

Jahangir Alam M. (), Benoit Dostie, Drechsler Jörg () and Lars Vilhuber
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Jahangir Alam M.: Department of Applied Economics, HEC Montréal, Canada & Department of Economics, Truman State University, ; Truman, ; United States
Drechsler Jörg: Institute for Employment Research, ; Berlin;, ; Germany

Statistics in Transition New Series, 2020, vol. 21, issue 4, 212-236

Abstract: Data on businesses collected by statistical agencies are challenging to protect. Many businesses have unique characteristics, and distributions of employment, sales, and profits are highly skewed. Attackers wishing to conduct identification attacks often have access to much more information than for any individual. As a consequence, most disclosure avoidance mechanisms fail to strike an acceptable balance between usefulness and confidentiality protection. Detailed aggregate statistics by geography or detailed industry classes are rare, public-use microdata on businesses are virtually inexistant, and access to confidential microdata can be burdensome. Synthetic microdata have been proposed as a secure mechanism to publish microdata, as part of a broader discussion of how to provide broader access to such data sets to researchers. In this article, we document an experiment to create analytically valid synthetic data, using the exact same model and methods previously employed for the United States, for data from two different countries: Canada (Longitudinal Employment Analysis Program (LEAP)) and Germany (Establishment History Panel (BHP)). We assess utility and protection, and provide an assessment of the feasibility of extending such an approach in a cost-effective way to other data.

Keywords: business data; confidentiality; LBD; LEAP; BHP; synthetic. (search for similar items in EconPapers)
Date: 2020
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https://doi.org/10.21307/stattrans-2020-039 (text/html)

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Journal Article: Applying data synthesis for longitudinal business data across three countries (2020) Downloads
Working Paper: Applying Data Synthesis for Longitudinal Business Data across Three Countries (2020) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:21:y:2020:i:4:p:212-236:n:19

DOI: 10.21307/stattrans-2020-039

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