Applying Data Synthesis for Longitudinal Business Data Across Three Countries

• Autorzy: M. Jahangir Alam , Benoit Dostie , Jörg Drechsler , Lars Vilhuber
• Języki publikacji: EN

Abstrakty

EN

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. (original abstract)

Słowa kluczowe

EN

Information disclosure; Panel data; Microeconometrics

PL

Jawność informacji; Dane panelowe; Mikroekonometria

• Czasopismo: Statistics in Transition
• Rocznik: 2020
• Tom: 21
• Numer: nr 4 Special Issue
• Strony: 212--236

Twórcy

autor

M. Jahangir Alam

• HEC Montréal, Canada; Truman State University, United States

autor

Benoit Dostie

• HEC Montréal, Canada

autor

Jörg Drechsler

• Institute for Employment Research, Germany

autor

Lars Vilhuber

• Cornell University, United States

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Identyfikatory

DOI

10.21307/stattrans-2020-039