The Current Stage of the Microdata Analysis System at the U.S. Census Bureau
Jason Lucero, Laura Zayatz, Lisa Singh, Jiashen You, Michael DePersio, Michael Freiman
Center for Disclosure Avoidance Research, U.S. Census Bureau, Washington, DC, United States

The U.S. Census Bureau collects its survey and census data under Title 13 of the U.S. code, which promises to protect the confidentiality of all survey respondents. Additionally, the Census Bureau has the responsibility to release high quality data products while maintaining confidentiality. This paper discusses the current stage of a Microdata Analysis System (MAS) that is under development at the Census Bureau. We discuss the reason for developing the MAS, address some FAQs about the MAS, and give a brief overview of the system's analysis capabilities before covering the rules enforced to maintain confidentiality of data. Finally, we given an overview of the evaluation of a universe subsampling routine in the MAS known as the Drop q Rule and conclude with some remarks on future research.

Keywords: Data confidentiality; Remote access servers; Universe subsampling; Schur-convexity

Biography: Laura Zayatz has been working on disclosure avoidance for over 20 years at the U.S. Census Bureau. She is the Chief of the Center for Disclosure Avoidance Research at the Census Bureau as well as the Chair of the Disclosure Review Board. She is one of two founders of the Confidentiality and Data Access Committee under the U.S. Office of Management and Budget and a Fellow of the American Statistical Association.