Affiliations: [a] Center for Economic Studies, US Bureau of the Census,
FB3, Room 1587, Washington, DC 20233, USA
Note: [1] The authors are chief and Economist, respectively, at the Center for Economic
Studies, U.S. Bureau of the Census, Washington, DC 20233, USA. The judgments
and conclusions herein are those of the authors and do not necessarily
reflect those of the Census Bureau. We would like to thank Tom Abbott, Zvi
Griliches, Mark Roberts and Peter Zadrozny for helpful comments, and Jan
Parks for her patient and skillful typing of the manuscript.
Abstract: Official statistical agencies such as the Census Bureau and the Bureau of Labor
Statistics collect enormous quantities of microdata in statistical surveys.
These data are valuable for economic research and market and policy analysis.
However, the data cannot be released to the public because of confidentiality
commitments to individual respondents. These commitments, coupled with the
strong research demand for microdata, have led the agencies to consider various
proposals for releasing public use microdata. Most proposals for public use microdata call for the development of surrogate
data that disguise the original data. Thus, they involve the addition of
measurement errors to the data. In this paper, we examine disclosure issues and
explore alternative masking methods for generating panels of useful economic
microdata which can be released to researchers. While our analysis applies to
all confidential microdata, applications using the Census Bureau's Longitudinal
Research Data Base (LRD) are used for illustrative purposes throughout the
discussion.
Keywords: Longitudinal Research Data Base, Data Transformation, Surrogate Microdata, Disclosure Risk, Econometric Models
