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An Informational Theory of Privacy

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  • Ole Jann
  • Christoph Schottmüller

Abstract

Privacy of consumers or citizens is often seen as an inefficient information asymmetry. We challenge this view by showing that privacy can increase welfare in an informational sense. It can also improve information aggregation and prevent inefficient statistical discrimination. We show how and when the different informational effects of privacy line up to make privacy efficient or even Pareto-optimal. Our theory can be applied to decide who should have which information and how privacy and information disclosure should be regulated. We discuss applications to online privacy, credit decisions and transparency in government.

Suggested Citation

  • Ole Jann & Christoph Schottmüller, 2020. "An Informational Theory of Privacy," The Economic Journal, Royal Economic Society, vol. 130(625), pages 93-124.
    • Handle: RePEc:oup:econjl:v:130:y:2020:i:625:p:93-124.
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    File URL: http://hdl.handle.net/10.1093/ej/uez045
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    Cited by:

    1. Bonatti, Alessandro & Argenziano, Rossella, 2020. "Information Revelation and Privacy Protection," CEPR Discussion Papers 15203, C.E.P.R. Discussion Papers.
    2. Itay P. Fainmesser & Andrea Galeotti & Ruslan Momot, 2023. "Digital Privacy," Management Science, INFORMS, vol. 69(6), pages 3157-3173, June.
    3. Zhuang Liu & Michael Sockin & Wei Xiong, 2021. "Data Privacy and Temptation," Working Papers 2021-77, Princeton University. Economics Department..
    4. Frank Ebbers & Jan Zibuschka & Christian Zimmermann & Oliver Hinz, 2021. "User preferences for privacy features in digital assistants," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 411-426, June.

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