Full Citation
Title: Reconciling Data Access and Privacy: Building a Sustainable Model for the Future
Citation Type: Journal Article
Publication Year: 2019
ISBN:
ISSN: 2574-0768
DOI: 10.1257/pandp.20191108
NSFID:
PMCID:
PMID:
Abstract: Social science researchers have benefited enormously from access to survey and census data collected and disseminated by the federal statistical agencies. The research made possible by this access has generated invaluable insights. An important factor in the government’s ability to collect data from individuals and businesses is the promise it gives to data subjects that their information will be kept private. The statistical agencies are vigilant in their efforts to honor this promise. Given the explosion of data from numerous sources that increasingly are available in electronic form, however, the risk that information contained in data products released by federal agencies could compromise the privacy of data subjects has grown. I view it as an unavoidable conclusion that, in order to honor the promises of privacy made to data subjects, current modes for disseminating information based on survey and census data will need to be rethought. Tiered access seems certain to be a central feature of any new model for data access, with the needs of many data users met through tabulations or other data products that safely can be made public and behind-the-firewall access to more sensitive information provided to the smaller number of data users who truly require it. A similar mix of approaches can be used to increase access to administrative records for research purposes. While the broad outlines of what a new system will look like seem relatively clear, important practical questions about its implementation will need to be addressed.
Url: https://doi.org/10.1257/pandp.20191108
Url: https://pubs.aeaweb.org/doi/10.1257/pandp.20191108
User Submitted?: No
Authors: Abraham, Katharine G
Periodical (Full): AEA Papers and Proceedings
Issue:
Volume: 109
Pages: 409-413
Data Collections: IPUMS USA
Topics: Population Data Science
Countries: United States