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Nothing to hide? Gender and age differences in willingness to share data

Author

Listed:
  • Olivier Armantier

    (Chapman University - Economic Science Institute)

  • Sebastian Doerr

    (Bank for International Settlements; Centre for Economic Policy Research (CEPR))

  • Jon Frost

    (Bank for International Settlements (BIS))

  • Andreas Fuster

    (École Polytechnique Fédérale de Lausanne (EPFL); Swiss Finance Institute; Centre for Economic Policy Research (CEPR))

  • Kelly Shue

    (Yale School of Management; National Bureau of Economic Research (NBER))

Abstract

Many digital applications rely on the willingness of users to voluntarily share personal data. Yet some users are more comfortable sharing data than others. To document these differences, we draw on questions to a representative sample of U.S.\ households added to the New York Fed's Survey of Consumer Expectations. We find that women are less willing than men, and older individuals less willing than the young, to share their financial transaction data in exchange for better offers on financial services. Across these groups, there are significant differences in attitudes, such as willingness to take financial risks, concerns that data will become publicly available, and concerns around personal safety. Responses suggest that privacy regulation can increase the willingness to share data, but effects do not differ by gender.

Suggested Citation

  • Olivier Armantier & Sebastian Doerr & Jon Frost & Andreas Fuster & Kelly Shue, 2024. "Nothing to hide? Gender and age differences in willingness to share data," Swiss Finance Institute Research Paper Series 24-99, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp2499
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    File URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4808467
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    Cited by:

    1. Agur, Itai & Ari, Anil & Dell’Ariccia, Giovanni, 2025. "Bank competition and household privacy in a digital payment monopoly," Journal of Financial Economics, Elsevier, vol. 166(C).
    2. Helmut Elsinger & Helmut Stix & Martin Summer, 2025. "Consumer preferences for a digital euro: insights from a discrete choice experiment in Austria," BIS Working Papers 1302, Bank for International Settlements.
    3. Leonardo Gambacorta & Tullio Jappelli & Tommaso Oliviero, 2025. "Exploring household adoption and usage of generative AI: new evidence from Italy," BIS Working Papers 1298, Bank for International Settlements.

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    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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