Work

Disclosure Avoidance for the 2020 Census Demographic and Housing Characteristics File

Year: 2025

Type: article

Abstract: Abowd et al. (2022) describe the concepts and methods used by the Disclosure Avoidance System (DAS) to produce formally private output in support of the 2020 Census statistical data product releases, with a particular focus on the DAS implementation that was used to create the 2020 Census Redistricting Data (P.L. 94-171) Summary File. In this paper we describe the updates to the DAS that were required to release the Demographic and Housing Characteristics (DHC) File, which provides more granular tables than other statistical data products, such as the Redistricting Data Summary File. We also describe the final configuration parameters used for the 2020 production DHC DAS implementation, error metrics for these production statistical data products, and plans for future experimental data products that provide confidence intervals for confidential 2020 Census tabulations.

Source: Harvard Data Science Review

DOI: 10.1162/99608f92.f1065159

Authors: Ryan Cumings-Menon, Robert Ashmead, Daniel Kifer, Philip Leclerc, Matthew Spence, Pavel Zhuravlev, John M. Abowd

Institutions: United States Census Bureau, University of Chicago, National Opinion Research Center, Pennsylvania State University, Cornell University

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4410230419

FWCI: 1.243

Cites: 3

Cited by: 8

Related to: 10