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Dynamic Privacy Choices

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  • Shota Ichihashi

Abstract

I study a dynamic model of consumer privacy and platform data collection. In each period consumers choose their level of platform activity. Greater activity generates more information about the consumer, thereby increasing platform profits. When the platform can commit to the future privacy policy, it collects information by committing to gradually decreasing the level of privacy protection. In the long run consumers lose privacy and receive low payoffs but choose high activity levels. In contrast, the platform with weaker commitment power may attain the commitment outcome or fail to collect any data depending on consumer expectations regarding future privacy protection.

Suggested Citation

  • Shota Ichihashi, 2023. "Dynamic Privacy Choices," American Economic Journal: Microeconomics, American Economic Association, vol. 15(2), pages 1-40, May.
    • Handle: RePEc:aea:aejmic:v:15:y:2023:i:2:p:1-40
    DOI: 10.1257/mic.20210100
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    References listed on IDEAS

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    1. Michael Kummer & Patrick Schulte, 2019. "When Private Information Settles the Bill: Money and Privacy in Google’s Market for Smartphone Applications," Management Science, INFORMS, vol. 65(8), pages 3470-3494, August.
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    6. Bonatti, Alessandro & Argenziano, Rossella, 2020. "Information Revelation and Privacy Protection," CEPR Discussion Papers 15203, C.E.P.R. Discussion Papers.
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    Citations

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    Cited by:

    1. Itay P. Fainmesser & Andrea Galeotti & Ruslan Momot, 2023. "Digital Privacy," Management Science, INFORMS, vol. 69(6), pages 3157-3173, June.
    2. Jiadong Gu, 2024. "Data Trade and Consumer Privacy," Papers 2406.12457, arXiv.org, revised Jul 2024.
    3. Charlson, G., 2022. "Digital Gold? Pricing, Inequality and Participation in Data Markets," Janeway Institute Working Papers 2225, Faculty of Economics, University of Cambridge.
    4. Charlson, G., 2022. "Digital gold? Pricing, inequality and participation in data markets," Cambridge Working Papers in Economics 2258, Faculty of Economics, University of Cambridge.
    5. Jeanine Miklós-Thal & Avi Goldfarb & Avery Haviv & Catherine Tucker, 2024. "Frontiers: Digital Hermits," Marketing Science, INFORMS, vol. 43(4), pages 697-708, July.
    6. Yosuke Uno & Akira Sonoda & Masaki Bessho, 2021. "The Economics of Privacy: A Primer Especially for Policymakers," Bank of Japan Working Paper Series 21-E-11, Bank of Japan.
    7. Shuaicheng Liu, 2024. "Privacy regulation in asymmetric environments," Journal of Regulatory Economics, Springer, vol. 66(2), pages 157-173, December.

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    More about this item

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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