SI 2020 Methods Lectures - Differential Privacy for Economists

James M. Poterba, Organizer

July 17, 2020

on Zoom.us

Conference Code of Conduct

Friday, July 17
1:00pm
Differential Privacy for Economists
1:30pm
Daniel Goroff, Alfred P. Sloan Foundation
Differential Privacy: Observations for Economists (background paper) (slides) (video)
1:45pm
Daniel Kifer, Pennsylvania State University
Introduction to Differential Privacy (slides) (video)
2:30pm
Ian Schmutte, University of Georgia
Decisions with Privacy-Protected Data (slides) (background paper) (video)
3:30pm
Daniel Kifer, Pennsylvania State University
Basic Statistics with Differential Privacy (slides) (video)
4:15pm
Ian Schmutte, University of Georgia
Formal Privacy in Census Data (slides) (video)
5:00 pm
Frauke Kreuter, University of Maryland
Implications of Data Privacy Concerns for Empirical Social Science (background paper) (video)
6:00pm
The extent to which individual responses to household surveys are protected from discovery by outside parties depends on the summary information released by the collecting government or firm, and on the broader data environment. Rapid decline in the cost of computation, along with a rising number of publicly available data sets, often from private vendors, have increased the risk that a determined party could combine public and private data resources and identify the survey responses of small groups or even individual respondents. Differential privacy is a tool for assessing the trade-off between releasing more granular information based on survey responses and protecting the privacy of survey respondents. These lectures offer an introduction to differential privacy along with examples of its application in settings that range from the collection of data on a small group to the US census.