Full Citation

Title: Finding a Needle in a Haystack: The Theoretical and Empirical Foundations of Assessing Disclosure Risk for Contextualized Microdata

Citation Type: Working Paper

Publication Year: 2008

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Abstract: Contextualized microdata are one way to safely release geographic data without identifying the location of survey respondents. This study informs the design of such datafiles with its needle-in-haystack approach to disclosure and its discussion of associated methodological concerns. Drawing a sample of counties, tracts, and blockgroups, I illustrate how the reidentification of individuals is shaped by aggregating geographies into look-alike sets. I detail the complexity of reidentification patterns by assessing the likelihood that young adult white and black males would be pinpointed within reconstituted haystacks given: (1) the size of the total population of aggregated contexts; (2) the amount of error in population counts; and (3) differential search costs stemming from spatially dispersed contexts.

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Authors: Kristine, Witkowski

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Publication Number: 4

Institution: University of Michigan

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Publisher Location: Michigan

Data Collections: IPUMS USA

Topics: Methodology and Data Collection

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