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Using Partially Synthetic Microdata to Protect Sensitive Cells in Business Statistics

Author
Vilhuber, Lars; Miranda, Javier
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).
Sponsorship
Vilhuber acknowledges support through NSF Grants SES-1042181 and BCS-0941226.
Date Issued
2016Publisher
Statistical Journal of the International Association for Official Statistics
Subject
synthetic data; statistical disclosure limitation; confidentiality protection; gross job flows; local labor markets; time-series
Related Version
Accepted version: Statistical Journal of the International Association for Official Statistics, forthcoming in 2016.
Related To:
http://doi.org/10.3233/SJI-160963Previously Published As
Statistical Journal of the IAOS, vol. 32, no. 1, pp. 69-80, 2016
Rights
CC0 1.0 Universal
Type
article
The following license files are associated with this item:
Except where otherwise noted, this item's license is described as CC0 1.0 Universal