Using Partially Synthetic Microdata to Protect Sensitive Cells in Business Statistics

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Abstract
We describe and analyze a method that blends records from both observed and synthetic microdata into public-use tabulations on establishment statistics. The resulting tables use synthetic data only in potentially sensitive cells. We describe different algorithms, and present preliminary results when applied to the Census Bureau's Business Dynamics Statistics and Synthetic Longitudinal Business Database, highlighting accuracy and protection afforded by the method when compared to existing public-use tabulations (with suppressions).
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Sponsorship
Vilhuber acknowledges support through NSF Grants SES-1042181 and BCS-0941226.
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2016
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Statistical Journal of the International Association for Official Statistics
Keywords
synthetic data; statistical disclosure limitation; confidentiality protection; gross job flows; local labor markets; time-series
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Accepted version: Statistical Journal of the International Association for Official Statistics, forthcoming in 2016.
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http://doi.org/10.3233/SJI-160963
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Statistical Journal of the IAOS, vol. 32, no. 1, pp. 69-80, 2016
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CC0 1.0 Universal
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