IDEAS home Printed from https://ideas.repec.org/a/aea/aejmic/v14y2022i1p186-215.html
   My bibliography  Save this article

How Bayesian Persuasion Can Help Reduce Illegal Parking and Other Socially Undesirable Behavior

Author

Listed:
  • Penélope Hernández
  • Zvika Neeman

Abstract

We consider the question of how best to allocate enforcement resources across different locations with the goal of deterring unwanted behavior. We rely on "Bayesian persuasion" to improve deterrence. We focus on the case where agents care only about the expected amount of enforcement resources given messages received. Optimization in the space of induced mean posterior beliefs involves a partial convexification of the objective function. We describe interpretable conditions under which it is possible to explicitly solve the problem with only two messages: "high enforcement" and "enforcement as usual." We also provide a tight upper bound on the total number of messages needed to achieve the optimal solution in the general case as well as a general example that attains this bound.

Suggested Citation

  • Penélope Hernández & Zvika Neeman, 2022. "How Bayesian Persuasion Can Help Reduce Illegal Parking and Other Socially Undesirable Behavior," American Economic Journal: Microeconomics, American Economic Association, vol. 14(1), pages 186-215, February.
  • Handle: RePEc:aea:aejmic:v:14:y:2022:i:1:p:186-215
    DOI: 10.1257/mic.20190295
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/doi/10.1257/mic.20190295
    Download Restriction: no

    File URL: https://www.aeaweb.org/doi/10.1257/mic.20190295.ds
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.

    File URL: https://libkey.io/10.1257/mic.20190295?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
    ---><---

    Citations

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


    Cited by:

    1. Makoto Shimoji, 2023. "Setting an exam as an information design problem," International Journal of Economic Theory, The International Society for Economic Theory, vol. 19(3), pages 559-579, September.
    2. Tan, Teck Yong, 2023. "Optimal transparency of monitoring capability," Journal of Economic Theory, Elsevier, vol. 209(C).
    3. Maennig, Wolfgang & Wilhelm, Stefan, 2023. "News and noise in crime politics: The role of announcements and risk attitudes," Economic Modelling, Elsevier, vol. 129(C).

    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

    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:aea:aejmic:v:14:y:2022:i:1:p:186-215. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.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.