Synthesizing Familial Linkages for Privacy in Microdata

Abstract

As the Census Bureau strives to modernize its disclosure avoidance efforts in all of its outputs, synthetic data has become a successful way to provide external researchers a chance to conduct a wide variety of analyses on microdata while still satisfying the legal objective of protecting privacy of survey respondents. Some of the most useful variables for researchers are some of the trickiest to model: relationships between records. These can be family relationships, household relationships, or employer-employee relationships to name a few. This paper describes a method to match synthetic records together in a way that mimics the covariation between related records in the underlying, protected data.