IDEAS home Printed from https://ideas.repec.org/p/fip/fednsr/89474.html
   My bibliography  Save this paper

Monetizing Privacy

Author

Abstract

In a market where consumers choose between payment options and firms compete with products and prices, we show that payment data drives the formation of a market monopoly. A data-sharing policy can successfully restore and maintain a competitive market, but often at the expense of both efficiency and consumer welfare. The introduction of a low-cost anonymous means of electronic payment, or digital cash, preserves the market structure and improves consumers’ welfare by enabling them to monetize their private information. We discuss the potential role of central banks in providing digital cash.

Suggested Citation

  • Rod Garratt & Michael Junho Lee, 2021. "Monetizing Privacy," Staff Reports 958, Federal Reserve Bank of New York.
    • Handle: RePEc:fip:fednsr:89474
    as

    Download full text from publisher

    File URL: https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr958.pdf
    File Function: Full text
    Download Restriction: no
    File URL: https://www.newyorkfed.org/research/staff_reports/sr958.html
    File Function: Summary
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Maryam Farboodi & Roxana Mihet & Thomas Philippon & Laura Veldkamp, 2019. "Big Data and Firm Dynamics," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 38-42, May.
    2. Maria C. Wasastjerna, 2018. "The role of big data and digital privacy in merger review," European Competition Journal, Taylor & Francis Journals, vol. 14(2-3), pages 417-444, September.
    3. Zhuang Liu & Michael Sockin & Wei Xiong, 2020. "Data Privacy and Temptation," NBER Working Papers 27653, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Oliver Falck & Johannes Koenen, 2020. "Rohstoff „Daten“: Volkswirtschaflicher Nutzen von Datenbereitstellung – eine Bestandsaufnahme," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 113, July.
    2. Cujean, Julien & Bustamante, Maria Cecilia & Frésard, Laurent, 2019. "Knowledge Cycles and Corporate Investment," CEPR Discussion Papers 14152, C.E.P.R. Discussion Papers.
    3. Doerr, Sebastian & Frost, Jon & Gambacorta, Leonardo & Shreeti, Vatsala, 2023. "Big techs in finance," CEPR Discussion Papers 18665, C.E.P.R. Discussion Papers.
    4. Daron Acemoglu & Ali Makhdoumi & Azarakhsh Malekian & Asu Ozdaglar, 2022. "Too Much Data: Prices and Inefficiencies in Data Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 14(4), pages 218-256, November.
    5. Zhijun Chen & pch346 & Chongwoo Choe & Jiajia Cong & Noriaki Matsushima, 2020. "Data-Driven Mergers and Personalization," Monash Economics Working Papers 16-20, Monash University, Department of Economics.
    6. Ehsan Valavi & Joel Hestness & Newsha Ardalani & Marco Iansiti, 2022. "Time and the Value of Data," Papers 2203.09118, arXiv.org.
    7. Wang, Li & Wu, Yuhan & Huang, Zeyu & Wang, Yanan, 2024. "Big data application and corporate investment decisions: Evidence from A-share listed companies in China," International Review of Financial Analysis, Elsevier, vol. 94(C).
    8. Jean Tirole, 2023. "Competition and the Industrial Challenge for the Digital Age," Post-Print hal-04464905, HAL.
    9. Martin Beraja & David Y Yang & Noam Yuchtman, 2023. "Data-intensive Innovation and the State: Evidence from AI Firms in China," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(4), pages 1701-1723.
    10. Pehr-Johan Norbäck & Lars Persson, 2024. "Why generative AI can make creative destruction more creative but less destructive," Small Business Economics, Springer, vol. 63(1), pages 349-377, June.
    11. Isaac Baley & Laura Veldkamp, 2021. "Bayesian learning," Economics Working Papers 1797, Department of Economics and Business, Universitat Pompeu Fabra.
    12. He, Zhiguo & Huang, Jing & Zhou, Jidong, 2023. "Open banking: Credit market competition when borrowers own the data," Journal of Financial Economics, Elsevier, vol. 147(2), pages 449-474.
    13. repec:ecb:ecbdps:202220 is not listed on IDEAS
    14. Yannelis, Constantine & Zhang, Anthony Lee, 2023. "Competition and selection in credit markets," Journal of Financial Economics, Elsevier, vol. 150(2).
    15. Naude, Wim, 2019. "The race against the robots and the fallacy of the giant cheesecake: Immediate and imagined impacts of artificial intelligence," MERIT Working Papers 2019-005, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    16. Toni Ahner & Katrin Assenmacher & Peter Hoffmann & Agnese Leonello & Cyril Monnet & Davide Porcellacchia, 2024. "The Economics of Central Bank Digital Currency," International Journal of Central Banking, International Journal of Central Banking, vol. 20(4), pages 221-274, October.
    17. Oliver Falck & Johannes Koenen, 2020. "Resource “Data”: Economic Benefits of Data Provision," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 21(03), pages 31-41, September.
    18. Schaefer, Maximilian & Sapi, Geza, 2023. "Complementarities in learning from data: Insights from general search," Information Economics and Policy, Elsevier, vol. 65(C).
    19. Naudé, Wim, 2020. "Industrialization under Medieval Conditions? Global Development after COVID-19," IZA Discussion Papers 13829, Institute of Labor Economics (IZA).
    20. Lyu, Wenjing & Liu, Jin, 2021. "Soft skills, hard skills: What matters most? Evidence from job postings," Applied Energy, Elsevier, vol. 300(C).

    More about this item

    Keywords

    customer data; privacy; market structure; digital cash; payments;
    All these keywords.

    JEL classification:

    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:fednsr:89474. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Gabriella Bucciarelli (email available below). General contact details of provider: https://edirc.repec.org/data/frbnyus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.