Online Program Home
My Program

Abstract Details

Activity Number: 344 - Expanding Data Utility - Issues in Disclosure and Modeling
Type: Contributed
Date/Time: Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
Sponsor: Government Statistics Section
Abstract #306493 Presentation
Title: Balancing Privacy and Precision: Disclosure Control Methods in Government Surveys
Author(s): Ellen Galantucci*
Companies: Bureau of Labor Statistics
Keywords: Statistical Disclosure Control; Confidentiality; Data Quality

As methods for determining the values of confidential data that are collected and published by federal statistical agencies become more sophisticated, it is important to regularly evaluate disclosure control methods to ensure data are adequately protected. While publishing fewer estimates or adding noise would solve the problem of disclosure protection, it would limit the utility of the data. This presentation reviews the methods currently used in the Office of Compensation and Working Conditions at the Bureau of Labor Statistics and makes recommendations for updated methods that should be implemented to reduce the disclosure risks in our publications while also maximizing utility for our data users. I tested multiple methods of disclosure protection on each survey publication and compared the utility to the protection each provided. My conclusion is that a one-size-fits-all approach to disclosure protection is not appropriate and, depending on the survey type, we must balance our competing goals differently when choosing a method.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2019 program