Synthetic Data for Small Area Estimation in the American Community Survey

49 Pages Posted: 13 Apr 2013

See all articles by Joseph Sakshaug

Joseph Sakshaug

Government of the Federal Republic of Germany - Institute for Employment Research (IAB)

Trivellore Raghunathan

University of Michigan at Ann Arbor - Survey Research Center, Survey Methodology Program; University of Michigan at Ann Arbor - School of Public Health, Department of Biostatistics

Date Written: April 1, 2013

Abstract

Small area estimates provide a critical source of information used to study local populations. Statistical agencies regularly collect data from small areas but are prevented from releasing detailed geographical identifiers in public-use data sets due to disclosure concerns. Alternative data dissemination methods used in practice include releasing summary/aggregate tables, suppressing detailed geographic information in public-use data sets, and accessing restricted data via Research Data Centers. This research examines an alternative method for disseminating microdata that contains more geographical details than are currently being released in public-use data files. Specifically, the method replaces the observed survey values with imputed, or synthetic, values simulated from a hierarchical Bayesian model. Confidentiality protection is enhanced because no actual values are released. The method is demonstrated using restricted data from the 2005-2009 American Community Survey. The analytic validity of the synthetic data is assessed by comparing small area estimates obtained from the synthetic data with those obtained from the observed data.

Suggested Citation

Sakshaug, Joseph and Raghunathan, Trivellore, Synthetic Data for Small Area Estimation in the American Community Survey (April 1, 2013). US Census Bureau Center for Economic Studies Paper No. CES-WP-13-19. Available at SSRN: https://ssrn.com/abstract=2248881 or http://dx.doi.org/10.2139/ssrn.2248881

Joseph Sakshaug (Contact Author)

Government of the Federal Republic of Germany - Institute for Employment Research (IAB)

Regensburger Str. 104
Nuremberg, 90478
Germany

Trivellore Raghunathan

University of Michigan at Ann Arbor - Survey Research Center, Survey Methodology Program ( email )

426 Thompson Street
Institute for Social Research
Ann Arbor, MI 48106-1248
United States
(734) 647-4619 (Phone)

University of Michigan at Ann Arbor - School of Public Health, Department of Biostatistics ( email )

1415 Washington Heights
Ann Arbor, MI 48109-2029
United States

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