The Future of Economic Research Under Rising Risks and Costs of Information Disclosure
Saturday, Jan. 5, 2019 2:30 PM - 4:30 PM
- Chair: Ben Casselman, New York Times
Differential Privacy and Census Data: Implications for Social and Economic Research
AbstractThe Census Bureau has announced a new set of standards and methods for disclosure control in public use data products. The new approach, known as differential privacy, represents a radical departure from current practice. In its pure form, differential privacy techniques may make the release of useful microdata impossible and severely limit the utility of tabular small-area data. Adoption of differential privacy will have far-reaching consequences for research. It is possible—even likely—that scientists, planners, and the public will lose the free access we have enjoyed for six decades to reliable public Census Bureau data describing American social and economic change. We believe that the differential privacy approach is inconsistent with the statutory obligations, history, and core mission of the Census Bureau.
Reconciling Access and Privacy: Building a Sustainable Model for the Future
AbstractIn recent decades, social science research has benefited greatly 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 outside data about all of us that increasingly is available in electronic form, however, the risk that information contained in data products released by the federal government could compromise the privacy of data subjects has grown. It seems to me to be 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. The challenge will be how to do this in a way that also enables effective use of the data. Tiered access is likely to be a central element of any new model for data access, with the information needs of many data users satisfied through publicly disseminated tabulations and the capacity to provide necessary behind-the-firewall access to other data users expanded. This same mix of approaches also 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 clear, many important practical questions about its implementation remain to be addressed.
Privacy-Protection for Economics Research in Small Cells
AbstractPublic release of disaggregated statistics holds tremendous value for research and policy but presents challenges for privacy protection. This paper presents a new approach to protecting privacy when publishing statistics from data in small cells. This noise-infusion algorithm draws from ideas in the privacy literature and is straightforward to apply in almost any setting, even for complex statistical models. After describing the details of our approach, we discuss its benefits relative to common privacy-protection procedures, such as count-based suppression
- C4 - Econometric and Statistical Methods: Special Topics