IDEAS home Printed from https://ideas.repec.org/a/spr/reecde/v27y2023i2d10.1007_s10058-022-00294-7.html
   My bibliography  Save this article

Seller experimentation and trade

Author

Listed:
  • Peter Wagner

    (University of York)

Abstract

This paper studies the effect of trade opportunities on a seller’s incentive to acquire information through experimentation. I characterize the unique equilibrium outcome and discuss the effects of variations in the information structure on the probability of trade. The main result is that more accurate information for the buyer can reduce social welfare. Efficiency requires that the buyer offers a price that the seller always accepts and that the seller experiments when it is socially optimal to do so. When the buyer receives very informative signals about positive experimentation outcomes, the absence of such a signal can induce the buyer to purchase the good only with low but known quality at a low price. If the buyer receives an informative signal about negative experimentation outcomes, the seller might prefer to not experiment so as to avoid the risk of generating a negative outcome that could trigger the buyer to reduce her offer.

Suggested Citation

  • Peter Wagner, 2023. "Seller experimentation and trade," Review of Economic Design, Springer;Society for Economic Design, vol. 27(2), pages 337-357, June.
    • Handle: RePEc:spr:reecde:v:27:y:2023:i:2:d:10.1007_s10058-022-00294-7
    DOI: 10.1007/s10058-022-00294-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10058-022-00294-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10058-022-00294-7?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Maarten C. W. Janssen & Santanu Roy, 2002. "Dynamic Trading in a Durable Good Market with Asymmetric Information," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(1), pages 257-282, February.
    2. William Fuchs & Andrzej Skrzypacz, 2019. "Costs and benefits of dynamic trading in a lemons market," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 33, pages 105-127, July.
    3. Kim, Kyungmin, 2017. "Information about sellers' past behavior in the market for lemons," Journal of Economic Theory, Elsevier, vol. 169(C), pages 365-399.
    4. Dilmé, Francesc, 2019. "Pre-trade private investments," Games and Economic Behavior, Elsevier, vol. 117(C), pages 98-119.
    5. Levin, Jonathan, 2001. "Information and the Market for Lemons," RAND Journal of Economics, The RAND Corporation, vol. 32(4), pages 657-666, Winter.
    6. Johannes Hörner & Nicolas Vieille, 2009. "Public vs. Private Offers in the Market for Lemons," Econometrica, Econometric Society, vol. 77(1), pages 29-69, January.
    7. Stephan Lauermann & Asher Wolinsky, 2016. "Search With Adverse Selection," Econometrica, Econometric Society, vol. 84, pages 243-315, January.
    8. Brendan Daley & Brett Green, 2012. "Waiting for News in the Market for Lemons," Econometrica, Econometric Society, vol. 80(4), pages 1433-1504, July.
    9. Kessler, Anke S, 2001. "Revisiting the Lemons Market," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(1), pages 25-41, February.
    10. Dang, Tri Vi, 2008. "Bargaining with endogenous information," Journal of Economic Theory, Elsevier, vol. 140(1), pages 339-354, May.
    11. Ayça Kaya & Kyungmin Kim, 2018. "Trading Dynamics with Private Buyer Signals in the Market for Lemons," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(4), pages 2318-2352.
    12. Steven Shavell, 1994. "Acquisition and Disclosure of Information Prior to Sale," RAND Journal of Economics, The RAND Corporation, vol. 25(1), pages 20-36, Spring.
    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. Bilancini, Ennio & Boncinelli, Leonardo, 2016. "Dynamic adverse selection and the supply size," European Economic Review, Elsevier, vol. 83(C), pages 233-242.
    2. Kim, Kyungmin, 2017. "Information about sellers' past behavior in the market for lemons," Journal of Economic Theory, Elsevier, vol. 169(C), pages 365-399.
    3. Dino Gerardi & Lucas Maestri & Ignacio Monzón, 2022. "Bargaining over a Divisible Good in the Market for Lemons," American Economic Review, American Economic Association, vol. 112(5), pages 1591-1620, May.
    4. Hwang, Ilwoo, 2018. "Dynamic trading with developing adverse selection," Journal of Economic Theory, Elsevier, vol. 176(C), pages 761-802.
    5. Barsanetti, Bruno & Camargo, Braz, 2022. "Signaling in dynamic markets with adverse selection," Journal of Economic Theory, Elsevier, vol. 206(C).
    6. Dilmé, Francesc, 2019. "Dynamic quality signaling with hidden actions," Games and Economic Behavior, Elsevier, vol. 113(C), pages 116-136.
    7. Asriyan, Vladimir & Fuchs, William & Green, Brett, 2021. "Aggregation and design of information in asset markets with adverse selection," Journal of Economic Theory, Elsevier, vol. 191(C).
    8. Fuchs, William & Green, Brett & Papanikolaou, Dimitris, 2016. "Adverse selection, slow-moving capital, and misallocation," Journal of Financial Economics, Elsevier, vol. 120(2), pages 286-308.
    9. Vladimir Asriyan, 2017. "Information Aggregation in Dynamic Markets with Adverse Selection," 2017 Meeting Papers 988, Society for Economic Dynamics.
    10. Kaya, Ayça & Roy, Santanu, 2022. "Market screening with limited records," Games and Economic Behavior, Elsevier, vol. 132(C), pages 106-132.
    11. Manuel Adelino & Kristopher Gerardi & Barney Hartman-Glaser, 2016. "Are Lemons Sold First? Dynamic Signaling in the Mortgage Market," FRB Atlanta Working Paper 2016-8, Federal Reserve Bank of Atlanta.
    12. Sarah Auster & Piero Gottardi & Ronald Wolthoff, 2022. "Simultaneous Search and Adverse Selection," Working Papers tecipa-734, University of Toronto, Department of Economics.
    13. Ayça Kaya & Santanu Roy, 2024. "Repeated Trading: Transparency and Market Structure," American Economic Review, American Economic Association, vol. 114(8), pages 2388-2435, August.
    14. Camargo, Braz & Lester, Benjamin, 2014. "Trading dynamics in decentralized markets with adverse selection," Journal of Economic Theory, Elsevier, vol. 153(C), pages 534-568.
    15. Ferreira, Daniel & Nikolowa, Radoslawa, 2023. "Talent discovery and poaching under asymmetric information," LSE Research Online Documents on Economics 116044, London School of Economics and Political Science, LSE Library.
    16. Santanu Roy, 2014. "Dynamic sorting in durable goods markets with buyer heterogeneity," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 47(3), pages 1010-1031, August.
    17. Dilmé, Francesc, 2017. "Noisy signaling in discrete time," Journal of Mathematical Economics, Elsevier, vol. 68(C), pages 13-25.
    18. Brendan Daley & Brett Green, 2012. "Waiting for News in the Market for Lemons," Econometrica, Econometric Society, vol. 80(4), pages 1433-1504, July.
    19. Moreno, Diego & Wooders, John, 2016. "Dynamic markets for lemons: performance, liquidity, and policy intervention," Theoretical Economics, Econometric Society, vol. 11(2), May.
    20. Fuchs, William & Skrzypacz, Andrzej, 2015. "Government interventions in a dynamic market with adverse selection," Journal of Economic Theory, Elsevier, vol. 158(PA), pages 371-406.

    More about this item

    Keywords

    Experimentation; Learning; Trade; Adverse selection; Market for lemons;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    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:spr:reecde:v:27:y:2023:i:2:d:10.1007_s10058-022-00294-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.