IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-06c90004.html
   My bibliography  Save this article

Learning in Tournaments with Inter-Generational Advice

Author

Listed:
  • Ananish Chaudhuri

    (University of Auckland)

  • Barry Sopher

    (Rutgers University)

  • Andrew Schotter

    (New York University)

Abstract

We study learning in a simulated tournament using an inter-generational framework. Here a group of subjects are recruited into the lab and play the stage game for 10 rounds. After his participation is over, each player is replaced by another player, his laboratory descendant, who then plays the game for another 10 rounds as a member of a fresh group of subjects. A particular player in generation t+1 can (1) see the history of choices by his generation t predecessor and (2) receive advice from that predecessor via free-form messages that generation t players leave for their generation t+1 successors. We find that the presence of advice makes a difference in that the experimental groups who get advice perform better – their decisions are closer to the Nash equilibrium – compared to a control group of subjects that plays the game with no recourse to such advice.

Suggested Citation

  • Ananish Chaudhuri & Barry Sopher & Andrew Schotter, 2006. "Learning in Tournaments with Inter-Generational Advice," Economics Bulletin, AccessEcon, vol. 3(26), pages 1-16.
    • Handle: RePEc:ebl:ecbull:eb-06c90004
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/pubs/EB/2006/Volume3/EB-06C90004A.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrew Schotter, 2005. "Decision Making with Naïve Advice," Springer Books, in: Amnon Rapoport & Rami Zwick (ed.), Experimental Business Research, chapter 0, pages 223-248, Springer.
    2. Bull, Clive & Schotter, Andrew & Weigelt, Keith, 1987. "Tournaments and Piece Rates: An Experimental Study," Journal of Political Economy, University of Chicago Press, vol. 95(1), pages 1-33, February.
    3. Merlo, Antonio & Schotter, Andrew, 2003. "Learning by not doing: an experimental investigation of observational learning," Games and Economic Behavior, Elsevier, vol. 42(1), pages 116-136, January.
    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. Martin Kocher & Matthias Sutter & Florian Wakolbinger, 2014. "Social Learning in Beauty‐Contest Games," Southern Economic Journal, John Wiley & Sons, vol. 80(3), pages 586-613, January.
    2. David Cooper & John Lightle, 2013. "The gift of advice: communication in a bilateral gift exchange game," Experimental Economics, Springer;Economic Science Association, vol. 16(4), pages 443-477, December.
    3. Ananish Chaudhuri & Tirnud Paichayontvijit & Erwann Sbai, 2016. "The Role of Framing, Inequity and History in a Corruption Game: Some Experimental Evidence," Games, MDPI, vol. 7(2), pages 1-24, June.
    4. Cooper, David J. & Kagel, John H., 2016. "A failure to communicate: an experimental investigation of the effects of advice on strategic play," European Economic Review, Elsevier, vol. 82(C), pages 24-45.
    5. So, Tony & Brown, Paul & Chaudhuri, Ananish & Ryvkin, Dmitry & Cameron, Linda, 2017. "Piece-rates and tournaments: Implications for learning in a cognitively challenging task," Journal of Economic Behavior & Organization, Elsevier, vol. 142(C), pages 11-23.

    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. repec:ebl:ecbull:v:3:y:2006:i:26:p:1-16 is not listed on IDEAS
    2. So, Tony & Brown, Paul & Chaudhuri, Ananish & Ryvkin, Dmitry & Cameron, Linda, 2017. "Piece-rates and tournaments: Implications for learning in a cognitively challenging task," Journal of Economic Behavior & Organization, Elsevier, vol. 142(C), pages 11-23.
    3. Cooper, David J. & Kagel, John H., 2016. "A failure to communicate: an experimental investigation of the effects of advice on strategic play," European Economic Review, Elsevier, vol. 82(C), pages 24-45.
    4. Jinkwon Lee, 2007. "Repetition And Financial Incentives In Economics Experiments," Journal of Economic Surveys, Wiley Blackwell, vol. 21(3), pages 628-681, July.
    5. Christine Harbring & Bernd Irlenbusch, 2005. "Incentives in Tournaments with Endogenous Prize Selection," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 161(4), pages 636-663, December.
    6. Gehrig, Thomas & Güth, Werner & Leví0nský, René & Popova, Vera, 2010. "On the evolution of professional consulting," Journal of Economic Behavior & Organization, Elsevier, vol. 76(1), pages 113-126, October.
    7. Simon Gächter & Lingbo Huang & Martin Sefton, 2016. "Combining “real effort” with induced effort costs: the ball-catching task," Experimental Economics, Springer;Economic Science Association, vol. 19(4), pages 687-712, December.
    8. Zubanov, Nick & Cadsby, Bram & Song, Fei, 2017. "The," IZA Discussion Papers 10542, Institute of Labor Economics (IZA).
    9. Eriksen, Kristoffer W. & Kvaløy, Ola, 2014. "Myopic risk-taking in tournaments," Journal of Economic Behavior & Organization, Elsevier, vol. 97(C), pages 37-46.
    10. Lucas C. Coffman & Alexander Gotthard-Real, 2019. "Moral Perceptions of Advised Actions," Management Science, INFORMS, vol. 65(8), pages 3904-3927, August.
    11. Graff, Frederik & Grund, Christian & Harbring, Christine, 2021. "Competing on the Holodeck - The effect of virtual peers and heterogeneity in dynamic tournaments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).
    12. Jia, Hao & Skaperdas, Stergios & Vaidya, Samarth, 2013. "Contest functions: Theoretical foundations and issues in estimation," International Journal of Industrial Organization, Elsevier, vol. 31(3), pages 211-222.
    13. Bougheas, Spiros & Nieboer, Jeroen & Sefton, Martin, 2013. "Risk-taking in social settings: Group and peer effects," Journal of Economic Behavior & Organization, Elsevier, vol. 92(C), pages 273-283.
    14. Wu, Steven Y. & Roe, Brian E., 2006. "AJAE Appendix: Tournaments, Fairness, and Risk," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 88(3), pages 1-44, August.
    15. Shakun D. Mago & Anya C. Savikhin & Roman M. Sheremeta, 2012. "Facing Your Opponents: Social identification and information feedback in contests," Working Papers 12-15, Chapman University, Economic Science Institute.
    16. Deck, Cary & Sheremeta, Roman M., 2019. "The tug-of-war in the laboratory," European Journal of Political Economy, Elsevier, vol. 60(C).
    17. Vital Anderhub & Simon Gächter & Manfred Königstein, 2002. "Efficient Contracting and Fair Play in a Simple Principal-Agent Experiment," Experimental Economics, Springer;Economic Science Association, vol. 5(1), pages 5-27, June.
    18. Loukas Balafoutas & E. Glenn Dutcher & Florian Lindner & Dmitry Ryvkin, 2017. "The Optimal Allocation Of Prizes In Tournaments Of Heterogeneous Agents," Economic Inquiry, Western Economic Association International, vol. 55(1), pages 461-478, January.
    19. Leuermann, Andrea & Roth, Benjamin, 2012. "Does good advice come cheap? - On the assessment of risk preferences in the lab and the field," Working Papers 0534, University of Heidelberg, Department of Economics.
    20. Fehr, Dietmar & Sutter, Matthias, 2019. "Gossip and the efficiency of interactions," Games and Economic Behavior, Elsevier, vol. 113(C), pages 448-460.
    21. Frimmel, Wolfgang & Horvath, Thomas & Schnalzenberger, Mario & Winter-Ebmer, Rudolf, 2018. "Seniority wages and the role of firms in retirement," Journal of Public Economics, Elsevier, vol. 164(C), pages 19-32.

    More about this item

    Keywords

    Advice;

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory

    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:ebl:ecbull:eb-06c90004. 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: John P. Conley (email available below). General contact details of provider: .

    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.