IDEAS home Printed from https://ideas.repec.org/a/eee/jetheo/v144y2009i2p884-897.html
   My bibliography  Save this article

The role of optimal threats in auction design

Author

Listed:
  • Figueroa, Nicolás
  • Skreta, Vasiliki

Abstract

This paper studies revenue-maximizing auctions when buyers' outside options depend on their private information and are endogenously chosen by the seller. We show that the revenue-maximizing assignment of the object can depend crucially on the outside options that the seller can choose as threats. Depending on the shape of outside options, sometimes an optimal mechanism allocates the object in an ex-post efficient way, and, other times, buyers obtain the object more often than is efficient.

Suggested Citation

  • Figueroa, Nicolás & Skreta, Vasiliki, 2009. "The role of optimal threats in auction design," Journal of Economic Theory, Elsevier, vol. 144(2), pages 884-897, March.
  • Handle: RePEc:eee:jetheo:v:144:y:2009:i:2:p:884-897
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0022-0531(08)00164-6
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Richard Arnott & Joseph E. Stiglitz, 1988. "Randomization with Asymmetric Information," RAND Journal of Economics, The RAND Corporation, vol. 19(3), pages 344-362, Autumn.
    2. Philippe Jehiel & Benny Moldovanu, 2000. "Auctions with Downstream Interaction Among Buyers," RAND Journal of Economics, The RAND Corporation, vol. 31(4), pages 768-791, Winter.
    3. Jehiel, Philippe & Moldovanu, Benny & Stacchetti, Ennio, 1996. "How (Not) to Sell Nuclear Weapons," American Economic Review, American Economic Association, vol. 86(4), pages 814-829, September.
    4. Paul Klemperer, 2004. "Auctions: Theory and Practice," Online economics textbooks, SUNY-Oswego, Department of Economics, number auction1.
    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. Frédéric Koessler & Ariane Lambert-Mogiliansky, 2012. "Optimal Extortion and Political Risk Insurance," PSE Working Papers halshs-00672963, HAL.
    2. Serkan Kucuksenel, 2012. "Interim efficient auctions with interdependent valuations," Journal of Economics, Springer, vol. 106(1), pages 83-93, May.
    3. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2020. "Market for Information and Selling Mechanisms," CESifo Working Paper Series 8307, CESifo.
    4. David Bounie & Antoine Dubus & Patrick Waelbroeck, 2021. "Selling strategic information in digital competitive markets," RAND Journal of Economics, RAND Corporation, vol. 52(2), pages 283-313, June.
    5. Koessler, Frédéric & Lambert-Mogiliansky, Ariane, 2014. "Extortion and political-risk insurance," Journal of Public Economics, Elsevier, vol. 120(C), pages 144-156.
    6. Brocas, Isabelle, 2014. "Countervailing incentives in allocation mechanisms with type-dependent externalities," Journal of Mathematical Economics, Elsevier, vol. 50(C), pages 22-33.
    7. Isabelle Brocas, 2013. "Optimal allocation mechanisms with type-dependent negative externalities," Theory and Decision, Springer, vol. 75(3), pages 359-387, September.
    8. Madhav Aney, 2015. "Inefficiency in the shadow of unobservable reservation payoffs," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 44(4), pages 833-859, April.
    9. Frank Stähler, 2014. "Partial ownership and cross-border mergers," Journal of Economics, Springer, vol. 111(3), pages 209-237, April.
    10. Alexandre Belloni & Changrong Deng & Saša Pekeč, 2017. "Mechanism and Network Design with Private Negative Externalities," Operations Research, INFORMS, vol. 65(3), pages 577-594, June.
    11. Chen, Bo & Potipiti, Tanapong, 2010. "Optimal selling mechanisms with countervailing positive externalities and an application to tradable retaliation in the WTO," Journal of Mathematical Economics, Elsevier, vol. 46(5), pages 825-843, September.
    12. Roberto Sarkisian & Takuro Yamashita, 2024. "Optimal student allocation with peer effects," Review of Economic Design, Springer;Society for Economic Design, vol. 28(3), pages 551-571, September.
    13. Yamashita, Takuro & Sarkisian, Roberto, 2021. "Large mechanism design with moment-based allocation externality," TSE Working Papers 21-1241, Toulouse School of Economics (TSE).
    14. Ying‐Ju Chen, 2021. "Optimal Design of Revenue‐Maximizing Position Auctions with Consumer Search," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 3297-3316, September.

    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. Nicolas Figueroa & Vasiliki Skreta, 2006. "The Role of Outside Options in Auction Design," Levine's Bibliography 321307000000000140, UCLA Department of Economics.
    2. Nicolás Figueroa & Vasiliki Skreta, 2011. "Optimal allocation mechanisms with single-dimensional private information," Review of Economic Design, Springer;Society for Economic Design, vol. 15(3), pages 213-243, September.
    3. Kaplan, Todd R. & Zamir, Shmuel, 2015. "Advances in Auctions," Handbook of Game Theory with Economic Applications,, Elsevier.
    4. Philippe Jehiel & Benny Moldovanu, 2005. "Allocative and Informational Externalities in Auctions and Related Mechanisms," Levine's Bibliography 784828000000000490, UCLA Department of Economics.
    5. Brocas, Isabelle, 2014. "Countervailing incentives in allocation mechanisms with type-dependent externalities," Journal of Mathematical Economics, Elsevier, vol. 50(C), pages 22-33.
    6. Chen, Bo & Potipiti, Tanapong, 2010. "Optimal selling mechanisms with countervailing positive externalities and an application to tradable retaliation in the WTO," Journal of Mathematical Economics, Elsevier, vol. 46(5), pages 825-843, September.
    7. Arozamena, Leandro & Weinschelbaum, Federico, 2011. "On favoritism in auctions with entry," Economics Letters, Elsevier, vol. 110(3), pages 265-267, March.
    8. Onur A. Koska & Ilke Onur & Frank Stähler, 2018. "The scope of auctions in the presence of downstream interactions and information externalities," Journal of Economics, Springer, vol. 125(2), pages 107-136, October.
    9. Loyola, Gino, 2012. "Optimal and efficient takeover contests with toeholds," Journal of Financial Intermediation, Elsevier, vol. 21(2), pages 203-216.
    10. Condorelli, Daniele, 2013. "Market and non-market mechanisms for the optimal allocation of scarce resources," Games and Economic Behavior, Elsevier, vol. 82(C), pages 582-591.
    11. Hu, Youxin & Kagel, John & Xu, Xiaoshu & Ye, Lixin, 2013. "Theoretical and experimental analysis of auctions with negative externalities," Games and Economic Behavior, Elsevier, vol. 82(C), pages 269-291.
    12. Jehiel, Philippe & Meyer-ter-Vehn, Moritz & Moldovanu, Benny, 2007. "Mixed bundling auctions," Journal of Economic Theory, Elsevier, vol. 134(1), pages 494-512, May.
    13. Li, Zhen & Kuo, Ching-Chung, 2011. "Revenue-maximizing Dutch auctions with discrete bid levels," European Journal of Operational Research, Elsevier, vol. 215(3), pages 721-729, December.
    14. Tomoya Kazumura & Debasis Mishra & Shigehiro Serizawa, 2017. "Strategy-proof multi-object auction design: Ex-post revenue maximization with no wastage," ISER Discussion Paper 1001, Institute of Social and Economic Research, Osaka University.
    15. Committee, Nobel Prize, 2020. "Improvements to auction theory and inventions of new auction formats," Nobel Prize in Economics documents 2020-2, Nobel Prize Committee.
    16. Hongjun Zhong, 2002. "postbid market interaction and auction choice," Microeconomics 0210002, University Library of Munich, Germany.
    17. Elbittar, Alexander, 2009. "Impact of valuation ranking information on bidding in first-price auctions: A laboratory study," Journal of Economic Behavior & Organization, Elsevier, vol. 69(1), pages 75-85, January.
    18. Jacob Goeree & Theo Offerman & Randolph Sloof, 2013. "Demand reduction and preemptive bidding in multi-unit license auctions," Experimental Economics, Springer;Economic Science Association, vol. 16(1), pages 52-87, March.
    19. Jung, Kyu-Chul & Kim, Kyoo H., 2005. "Revenue and optimality in unequal-sized share auctions," International Review of Financial Analysis, Elsevier, vol. 14(2), pages 177-190.
    20. Hart, Sergiu & Nisan, Noam, 2017. "Approximate revenue maximization with multiple items," Journal of Economic Theory, Elsevier, vol. 172(C), pages 313-347.

    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:eee:jetheo:v:144:y:2009:i:2:p:884-897. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/622869 .

    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.