Abstract #301748

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JSM 2003 Abstract #301748
Activity Number: 285
Type: Topic Contributed
Date/Time: Tuesday, August 5, 2003 : 2:00 PM to 3:50 PM
Sponsor: Section on Government Statistics
Abstract - #301748
Title: Disclosure Risks in Cross-Section Regression Models
Author(s): Arnold P. Reznek*+
Companies: U.S. Census Bureau
Address: 6205 Seminole Place, Berwyn Heights, MD, 20740-2348,
Keywords: confidentiality ; disclosure risks ; regression ; restricted access ; research data centers
Abstract:

The U.S. Census Bureau's Center for Economic Studies (CES) may grant researchers restricted access to nonpublic microdata files for research purposes that benefit the Census Bureau's programs. The Census Bureau must approve research proposals for this work. For more details on the CES research program, see the CES web site, www.ces.census.gov. Typically, the researchers describe relationships in these data by estimating regression-type models. These models generally pose much smaller disclosure risks than detailed cross-tabulations or frequencies, but they are completely not risk-free. This paper discusses disclosure risks in cross-section regression models, for example, ordinary least squares, discrete dependent variable (e.g., logit and probit), and count models (e.g., Poisson regressions). The paper considers situations involving categorical or "dummy" variables) in which models really produce tables and also considers whether "dominance" of a model by a small number of observations presents disclosure risks.

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