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Suboptimal Provision of Privacy and Statistical Accuracy When They are Public Goods


  • John M. Abowd
  • Ian M. Schmutte
  • William Sexton
  • Lars Vilhuber


With vast databases at their disposal, private tech companies can compete with public statistical agencies to provide population statistics. However, private companies face different incentives to provide high-quality statistics and to protect the privacy of the people whose data are used. When both privacy protection and statistical accuracy are public goods, private providers tend to produce at least one suboptimally, but it is not clear which. We model a firm that publishes statistics under a guarantee of differential privacy. We prove that provision by the private firm results in inefficiently low data quality in this framework.

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  • John M. Abowd & Ian M. Schmutte & William Sexton & Lars Vilhuber, 2019. "Suboptimal Provision of Privacy and Statistical Accuracy When They are Public Goods," Papers 1906.09353,
  • Handle: RePEc:arx:papers:1906.09353

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    References listed on IDEAS

    1. Alessandro Acquisti & Curtis Taylor & Liad Wagman, 2016. "The Economics of Privacy," Journal of Economic Literature, American Economic Association, vol. 54(2), pages 442-492, June.
    2. Dolan Antenucci & Michael Cafarella & Margaret Levenstein & Christopher Ré & Matthew D. Shapiro, 2014. "Using Social Media to Measure Labor Market Flows," NBER Working Papers 20010, National Bureau of Economic Research, Inc.
    3. Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 151-178, Spring.
    4. Goldfarb, Avi & Greenstein, Shane M. & Tucker, Catherine E. (ed.), 2015. "Economic Analysis of the Digital Economy," National Bureau of Economic Research Books, University of Chicago Press, number 9780226206981.
    5. Avi Goldfarb & Shane M. Greenstein & Catherine E. Tucker, 2015. "Introduction to "Economic Analysis of the Digital Economy"," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 1-17, National Bureau of Economic Research, Inc.
    6. Ori Heffetz & Katrina Ligett, 2014. "Privacy and Data-Based Research," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 75-98, Spring.
    7. John M. Abowd & Ian M. Schmutte, 2019. "An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices," American Economic Review, American Economic Association, vol. 109(1), pages 171-202, January.
    8. Avi Goldfarb & Shane M. Greenstein & Catherine E. Tucker, 2015. "Economic Analysis of the Digital Economy," NBER Books, National Bureau of Economic Research, Inc, number gree13-1, May.
    9. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    10. Ghosh, Arpita & Roth, Aaron, 2015. "Selling privacy at auction," Games and Economic Behavior, Elsevier, vol. 91(C), pages 334-346.
    11. A. Michael Spence, 1975. "Monopoly, Quality, and Regulation," Bell Journal of Economics, The RAND Corporation, vol. 6(2), pages 417-429, Autumn.
    12. Wasserman, Larry & Zhou, Shuheng, 2010. "A Statistical Framework for Differential Privacy," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 375-389.
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