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Privacy and Data-Based Research

29 Pages Posted: 15 Sep 2013  

Ori Heffetz

Cornell University - S.C. Johnson Graduate School of Management; Hebrew University of Jerusalem; National Bureau of Economic Research (NBER)

Katrina Ligett

California Institute of Technology - Department of Computing and Mathematical Sciences & Division of Humanities and Social Sciences

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Date Written: September 7, 2013

Abstract

What can we, as users of microdata, formally guarantee to the individuals (or firms) in our dataset, regarding their privacy? We retell a few stories, well-known in data-privacy circles, of failed anonymization attempts in publicly released datasets. We then provide a mostly informal introduction to several ideas from the literature on differential privacy, an active literature in computer science that studies formal approaches to preserving the privacy of individuals in statistical databases. We apply some of its insights to situations routinely faced by applied economists, emphasizing big-data contexts.

Keywords: data privacy, differential privacy, privacy guarantees, big data

JEL Classification: C49, C89, D89, Z00

Suggested Citation

Heffetz, Ori and Ligett, Katrina, Privacy and Data-Based Research (September 7, 2013). Available at SSRN: https://ssrn.com/abstract=2324830 or http://dx.doi.org/10.2139/ssrn.2324830

Ori Heffetz (Contact Author)

Cornell University - S.C. Johnson Graduate School of Management ( email )

324 Sage Hall
Ithaca, NY 14853
United States

Hebrew University of Jerusalem

Mount Scopus
Jerusalem, IL 91905
Israel

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

HOME PAGE: http://www.nber.org/~heffetz

Katrina Ligett

California Institute of Technology - Department of Computing and Mathematical Sciences & Division of Humanities and Social Sciences ( email )

Mail Code 305-16
Pasadena, CA 91125
United States

HOME PAGE: http://users.cms.caltech.edu/~katrina/

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