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dc.contributor.authorAbowd, John
dc.contributor.authorSchmutte, Ian M.
dc.date.accessioned2017-10-12T14:32:55Z
dc.date.available2015-01-31T21:07:58Z
dc.date.available2017-10-12T14:32:55Z
dc.date.issued2017-04-17
dc.identifier.urihttps://hdl.handle.net/1813/39081
dc.descriptionA complete archive of the data and programs used in this paper is available via http://doi.org/10.5281/zenodo.345385.
dc.description.abstractWe consider the problem of the public release of statistical information about a population–explicitly accounting for the public-good properties of both data accuracy and privacy loss. We first consider the implications of adding the public-good component to recently published models of private data publication under differential privacy guarantees using a Vickery-Clark-Groves mechanism and a Lindahl mechanism. We show that data quality will be inefficiently under-supplied. Next, we develop a standard social planner’s problem using the technology set implied by (ε, δ)-differential privacy with (α, β)-accuracy for the Private Multiplicative Weights query release mechanism to study the properties of optimal provision of data accuracy and privacy loss when both are public goods. Using the production possibilities frontier implied by this technology, explicitly parameterized interdependent preferences, and the social welfare function, we display properties of the solution to the social planner’s problem. Our results directly quantify the optimal choice of data accuracy and privacy loss as functions of the technology and preference parameters. Some of these properties can be quantified using population statistics on marginal preferences and correlations between income, data accuracy preferences, and privacy loss preferences that are available from survey data. Our results show that government data custodians should publish more accurate statistics with weaker privacy guarantees than would occur with purely private data publishing. Our statistical results using the General Social Survey and the Cornell National Social Survey indicate that the welfare losses from under-providing data accuracy while over-providing privacy protection can be substantial.en_US
dc.description.sponsorshipAbowd and Schmutte acknowledge the support of Alfred P. Sloan Foundation Grant G-2015-13903 and NSF Grant SES-1131848. Abowd acknowledges direct support from the U.S. Census Bureau (before and during his appointment as Associate Director) and from NSF Grants BCS- 0941226, TC-1012593. Some of the research for this paper was conducted using the resources of the Social Science Gateway, which was partially supported by NSF grant SES-0922005.
dc.language.isoen_USen_US
dc.relation.replaceshttp://hdl.handle.net/1813/39081.1
dc.relation.urihttps://ideas.repec.org/p/cen/wpaper/17-37.html
dc.relation.urihttp://digitalcommons.ilr.cornell.edu/ldi/37/
dc.subjectDemand for public statisticsen_US
dc.subjectTechnology for statistical agenciesen_US
dc.subjectOptimal data accuracyen_US
dc.subjectOptimal confidentiality protectionen_US
dc.titleRevisiting the Economics of Privacy: Population Statistics and Confidentiality Protection as Public Goodsen_US
dc.typearticleen_US


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