IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v64y2016i1p67-78.html
   My bibliography  Save this article

The Empirical Implications of Privacy-Aware Choice

Author

Listed:
  • Rachel Cummings

    (Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, California 91125)

  • Federico Echenique

    (Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, California 91125)

  • Adam Wierman

    (Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, California 91125)

Abstract

This paper initiates the study of the testable implications of choice data in settings where agents have privacy preferences. We adapt the standard conceptualization of consumer choice theory to a situation where the consumer is aware of, and has preferences over, the information revealed by her choices. The main message of the paper is that little can be inferred about consumers’ preferences once we introduce the possibility that the consumer has concerns about privacy. This holds even when consumers’ privacy preferences are assumed to be monotonic and separable. This motivates the consideration of stronger assumptions and, to that end, we introduce an additive model for privacy preferences that has testable implications.

Suggested Citation

  • Rachel Cummings & Federico Echenique & Adam Wierman, 2016. "The Empirical Implications of Privacy-Aware Choice," Operations Research, INFORMS, vol. 64(1), pages 67-78, February.
    • Handle: RePEc:inm:oropre:v:64:y:2016:i:1:p:67-78
    DOI: 10.1287/opre.2015.1458
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.2015.1458
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.2015.1458?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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. Varian, Hal R, 1982. "The Nonparametric Approach to Demand Analysis," Econometrica, Econometric Society, vol. 50(4), pages 945-973, July.
    3. Curtis R. Taylor, 2004. "Consumer Privacy and the Market for Customer Information," RAND Journal of Economics, The RAND Corporation, vol. 35(4), pages 631-650, Winter.
    4. Ori Heffetz & Katrina Ligett, 2014. "Privacy and Data-Based Research," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 75-98, Spring.
    5. Szenberg, Michael & Ramrattan, Lall & Gottesman, Aron A. (ed.), 2006. "Samuelsonian Economics and the Twenty-First Century," OUP Catalogue, Oxford University Press, number 9780199298839, Decembrie.
    6. Andrew F. Daughety & Jennifer F. Reinganum, 2010. "Public Goods, Social Pressure, and the Choice between Privacy and Publicity," American Economic Journal: Microeconomics, American Economic Association, vol. 2(2), pages 191-221, May.
    7. Geanakoplos, John & Pearce, David & Stacchetti, Ennio, 1989. "Psychological games and sequential rationality," Games and Economic Behavior, Elsevier, vol. 1(1), pages 60-79, March.
    8. Avi Goldfarb & Catherine Tucker, 2012. "Shifts in Privacy Concerns," American Economic Review, American Economic Association, vol. 102(3), pages 349-353, May.
    9. Ariel Rubinstein, 2012. "Lecture Notes in Microeconomic Theory: The Economic Agent Second Edition," Economics Books, Princeton University Press, edition 2, number 9742.
    10. Dekel, Eddie & Lipman, Barton L & Rustichini, Aldo, 2001. "Representing Preferences with a Unique Subjective State Space," Econometrica, Econometric Society, vol. 69(4), pages 891-934, July.
    11. Vincent Conitzer & Curtis R. Taylor & Liad Wagman, 2012. "Hide and Seek: Costly Consumer Privacy in a Market with Repeat Purchases," Marketing Science, INFORMS, vol. 31(2), pages 277-292, March.
    12. Avi Goldfarb & Ryan C. McDevitt & Sampsa Samila & Brian S. Silverman, 2015. "The Effect of Social Interaction on Economic Transactions: Evidence from Changes in Two Retail Formats," Management Science, INFORMS, vol. 61(12), pages 2963-2981, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gradwohl, Ronen & Smorodinsky, Rann, 2017. "Perception games and privacy," Games and Economic Behavior, Elsevier, vol. 104(C), pages 293-308.

    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. Dengler, Sebastian & Prüfer, Jens, 2021. "Consumers' privacy choices in the era of big data," Games and Economic Behavior, Elsevier, vol. 130(C), pages 499-520.
    2. Rodrigo Montes & Wilfried Sand-Zantman & Tommaso Valletti, 2019. "The Value of Personal Information in Online Markets with Endogenous Privacy," Management Science, INFORMS, vol. 65(3), pages 1342-1362, March.
    3. Gradwohl, Ronen & Smorodinsky, Rann, 2017. "Perception games and privacy," Games and Economic Behavior, Elsevier, vol. 104(C), pages 293-308.
    4. Jin, Ginger Zhe & Wagman, Liad, 2021. "Big data at the crossroads of antitrust and consumer protection," Information Economics and Policy, Elsevier, vol. 54(C).
    5. 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.
    6. 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.
    7. Long Chen & Yadong Huang & Shumiao Ouyang & Wei Xiong, 2021. "The Data Privacy Paradox and Digital Demand," Working Papers 2021-47, Princeton University. Economics Department..
    8. 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.
    9. Lagerlöf, Johan N.M., 2023. "Surfing incognito: Welfare effects of anonymous shopping," International Journal of Industrial Organization, Elsevier, vol. 87(C).
    10. Daniel Krähmer & Roland Strausz, 2023. "Optimal Nonlinear Pricing with Data-Sensitive Consumers," American Economic Journal: Microeconomics, American Economic Association, vol. 15(2), pages 80-108, May.
    11. Jin-Hyuk Kim & Liad Wagman, 2015. "Screening incentives and privacy protection in financial markets: a theoretical and empirical analysis," RAND Journal of Economics, RAND Corporation, vol. 46(1), pages 1-22, March.
    12. Avi Goldfarb, 2014. "What is Different About Online Advertising?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 44(2), pages 115-129, March.
    13. Didier Laussel & Ngo Van Long & Joana Resende, 2023. "Profit Effects of Consumers’ Identity Management: A Dynamic Model," Management Science, INFORMS, vol. 69(6), pages 3602-3615, June.
    14. Clavorà Braulin, Francesco, 2021. "The effects of personal information on competition: Consumer privacy and partial price discrimination," ZEW Discussion Papers 21-007, ZEW - Leibniz Centre for European Economic Research.
    15. Jeffrey T. Prince & Scott Wallsten, 2022. "How much is privacy worth around the world and across platforms?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(4), pages 841-861, November.
    16. Chen, Yongmin & Hua, Xinyu & Maskus, Keith E., 2021. "International protection of consumer data," Journal of International Economics, Elsevier, vol. 132(C).
    17. Li, Jianpei & Zhang, Wanzhu, 2024. "The Value of Anonymous Option," MPRA Paper 120010, University Library of Munich, Germany.
    18. Florian Morath & Johannes Münster, 2018. "Online Shopping and Platform Design with Ex Ante Registration Requirements," Management Science, INFORMS, vol. 64(1), pages 360-380, January.
    19. Anna D’Annunzio & Antonio Russo, 2020. "Ad Networks and Consumer Tracking," Management Science, INFORMS, vol. 66(11), pages 5040-5058, November.
    20. Michael R. Baye & David E. M. Sappington, 2020. "Revealing transactions data to third parties: Implications of privacy regimes for welfare in online markets," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 29(2), pages 260-275, April.

    More about this item

    Keywords

    privacy; revealed preference;

    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:inm:oropre:v:64:y:2016:i:1:p:67-78. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.