IDEAS home Printed from https://ideas.repec.org/a/bpj/germec/v17y2016i3p284-297.html
   My bibliography  Save this article

Impulse Response Dynamics in Weakest Link Games

Author

Listed:
  • Goerg Sebastian J.

    (Florida State University,Tallahassee, United States of America)

  • Sadrieh Abdolkarim

    (University of Magdeburg,Magdeburg, Germany)

  • Neugebauer Tibor

    (University of Luxembourg,Esch-sur-Alzette, Luxemburg)

Abstract

In a recent paper, Croson et al. (2015) experimentally study three weakest link games with multiple symmetric equilibria. They demonstrate that static concepts based on the Nash equilibrium (including multiple Nash equilibria, quantal response equilibria, and equilibrium selection by risk and payoff dominance) cannot successfully capture the observed treatment differences. Using Reinhard Selten’s impulse response dynamics, we derive a proposition that provides a theoretical ranking of contribution levels in the weakest link games. We show that the predicted ranking of treatment outcomes is fully consistent with the observed data. In addition, we demonstrate that the impulse response dynamics perform well in tracking average contributions over time. We conclude that Reinhard Selten’s impulse response dynamics provide an extremely valuable behavioral approach that is not only capable of resolving the indecisiveness of static approaches in games with many equilibria, but that can also be used to track the development of choices over time in games with repeated interaction.

Suggested Citation

  • Goerg Sebastian J. & Sadrieh Abdolkarim & Neugebauer Tibor, 2016. "Impulse Response Dynamics in Weakest Link Games," German Economic Review, De Gruyter, vol. 17(3), pages 284-297, August.
    • Handle: RePEc:bpj:germec:v:17:y:2016:i:3:p:284-297
    DOI: 10.1111/geer.12100
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/geer.12100
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1111/geer.12100?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. John C. Harsanyi & Reinhard Selten, 1988. "A General Theory of Equilibrium Selection in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262582384, April.
    2. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    3. Neugebauer, Tibor & Selten, Reinhard, 2006. "Individual behavior of first-price auctions: The importance of information feedback in computerized experimental markets," Games and Economic Behavior, Elsevier, vol. 54(1), pages 183-204, January.
    4. Sebastian Goerg & Reinhard Selten, 2009. "Experimental investigation of stationary concepts in cyclic duopoly games," Experimental Economics, Springer;Economic Science Association, vol. 12(3), pages 253-271, September.
    5. Chmura, Thorsten & Goerg, Sebastian J. & Selten, Reinhard, 2014. "Generalized Impulse Balance: An Experimental Test for a Class of 3 × 3 Games," Review of Behavioral Economics, now publishers, vol. 1(1-2), pages 27-53, January.
    6. Enrique Fatas & Tibor Neugebauer & Javier Perote, 2006. "Within‐Team Competition In The Minimum Effort Coordination Game," Pacific Economic Review, Wiley Blackwell, vol. 11(2), pages 247-266, June.
    7. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    8. Reinhard Selten & Klaus Abbink & Ricarda Cox, 2005. "Learning Direction Theory and the Winner’s Curse," Experimental Economics, Springer;Economic Science Association, vol. 8(1), pages 5-20, April.
    9. Croson, Rachel & Fatas, Enrique & Neugebauer, Tibor & Morales, Antonio J., 2015. "Excludability: A laboratory study on forced ranking in team production," Journal of Economic Behavior & Organization, Elsevier, vol. 114(C), pages 13-26.
    10. Chmura, Thorsten & Goerg, Sebastian J. & Selten, Reinhard, 2012. "Learning in experimental 2×2 games," Games and Economic Behavior, Elsevier, vol. 76(1), pages 44-73.
    11. Ho, Teck H. & Camerer, Colin F. & Chong, Juin-Kuan, 2007. "Self-tuning experience weighted attraction learning in games," Journal of Economic Theory, Elsevier, vol. 133(1), pages 177-198, March.
    12. Jieyao Ding & Andreas Nicklisch, 2013. "On the Impulse in Impulse Learning," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2013_02, Max Planck Institute for Research on Collective Goods.
    13. Selten, Reinhard & Stoecker, Rolf, 1986. "End behavior in sequences of finite Prisoner's Dilemma supergames A learning theory approach," Journal of Economic Behavior & Organization, Elsevier, vol. 7(1), pages 47-70, March.
    14. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    15. Reinhard Selten & Thorsten Chmura, 2008. "Stationary Concepts for Experimental 2x2-Games," American Economic Review, American Economic Association, vol. 98(3), pages 938-966, June.
    16. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    17. Ockenfels, Axel & Selten, Reinhard, 2014. "Impulse balance in the newsvendor game," Games and Economic Behavior, Elsevier, vol. 86(C), pages 237-247.
    18. Ding, Jieyao & Nicklisch, Andreas, 2013. "On the impulse in impulse learning," Economics Letters, Elsevier, vol. 121(2), pages 294-297.
    19. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    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. Edward Cartwright & Anna Stepanova & Lian Xue, 2019. "Impulse balance and framing effects in threshold public good games," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 21(5), pages 903-922, October.
    2. Federica Alberti & Anna Cartwright & Edward Cartwright, 2021. "Predicting Efficiency in Threshold Public Good Games: A Learning Direction Theory Approach," Working Papers in Economics & Finance 2021-01, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    3. Selten, Reinhard & Neugebauer, Tibor, 2019. "Experimental stock market dynamics: Excess bids, directional learning, and adaptive style-investing in a call-auction with multiple multi-period lived assets," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 209-224.
    4. Edward Cartwright & Anna Stepanova, 2017. "Efficiency in a forced contribution threshold public good game," International Journal of Game Theory, Springer;Game Theory Society, vol. 46(4), pages 1163-1191, November.
    5. Edward Cartwright, 2018. "The Optimal Strategy in the Minimum Effort Game," Games, MDPI, vol. 9(3), pages 1-11, June.
    6. Keser Claudia & Gaudeul Alexia, 2016. "Foreword: Special Issue in Honor of Reinhard Selten’s 85th Birthday," German Economic Review, De Gruyter, vol. 17(3), pages 277-283, August.

    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. Edward Cartwright & Anna Stepanova, 2017. "Efficiency in a forced contribution threshold public good game," International Journal of Game Theory, Springer;Game Theory Society, vol. 46(4), pages 1163-1191, November.
    2. Chmura, Thorsten & Goerg, Sebastian J. & Selten, Reinhard, 2012. "Learning in experimental 2×2 games," Games and Economic Behavior, Elsevier, vol. 76(1), pages 44-73.
    3. Erhao Xie, 2019. "Monetary Payoff and Utility Function in Adaptive Learning Models," Staff Working Papers 19-50, Bank of Canada.
    4. Thorsten Chmura & Werner Güth, 2011. "The Minority of Three-Game: An Experimental and Theoretical Analysis," Games, MDPI, vol. 2(3), pages 1-22, September.
    5. Nicklisch, Andreas & Köke, Sonja & Lange, Andreas, 2016. "Is Adversity a School of Wisdom? Experimental Evidence on Cooperative Protection Against Stochastic Losses," VfS Annual Conference 2016 (Augsburg): Demographic Change 145716, Verein für Socialpolitik / German Economic Association.
    6. Jieyao Ding & Andreas Nicklisch, 2013. "On the Impulse in Impulse Learning," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2013_02, Max Planck Institute for Research on Collective Goods.
    7. Edward Cartwright & Anna Stepanova & Lian Xue, 2019. "Impulse balance and framing effects in threshold public good games," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 21(5), pages 903-922, October.
    8. Köke, Sonja & Lange, Andreas & Nicklisch, Andreas, 2015. "Adversity is a school of wisdomː Experimental evidence on cooperative protection against stochastic losses," WiSo-HH Working Paper Series 22, University of Hamburg, Faculty of Business, Economics and Social Sciences, WISO Research Laboratory.
    9. Ding, Jieyao & Nicklisch, Andreas, 2013. "On the impulse in impulse learning," Economics Letters, Elsevier, vol. 121(2), pages 294-297.
    10. Chernov, G. & Susin, I., 2019. "Models of learning in games: An overview," Journal of the New Economic Association, New Economic Association, vol. 44(4), pages 77-125.
    11. V. P. Crawford, 2014. "Boundedly rational versus optimization-based models of strategic thinking and learning in games," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 5.
    12. Wilfred Amaldoss & Teck-Hua Ho & Aradhna Krishna & Kay-Yut Chen & Preyas Desai & Ganesh Iyer & Sanjay Jain & Noah Lim & John Morgan & Ryan Oprea & Joydeep Srivasatava, 2008. "Experiments on strategic choices and markets," Marketing Letters, Springer, vol. 19(3), pages 417-429, December.
    13. Heggedal, Tom-Reiel & Helland, Leif, 2014. "Platform selection in the lab," Journal of Economic Behavior & Organization, Elsevier, vol. 99(C), pages 168-177.
    14. Marco LiCalzi & Roland Mühlenbernd, 2022. "Feature-weighted categorized play across symmetric games," Experimental Economics, Springer;Economic Science Association, vol. 25(3), pages 1052-1078, June.
    15. Rick, Scott & Weber, Roberto A., 2010. "Meaningful learning and transfer of learning in games played repeatedly without feedback," Games and Economic Behavior, Elsevier, vol. 68(2), pages 716-730, March.
    16. Mohlin, Erik & Östling, Robert & Wang, Joseph Tao-yi, 2020. "Learning by similarity-weighted imitation in winner-takes-all games," Games and Economic Behavior, Elsevier, vol. 120(C), pages 225-245.
    17. Xie, Erhao, 2021. "Empirical properties and identification of adaptive learning models in behavioral game theory," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 798-821.
    18. Zhang, Yang & Du, Xiaomin, 2017. "Network effects on strategic interactions: A laboratory approach," Journal of Economic Behavior & Organization, Elsevier, vol. 143(C), pages 133-146.
    19. Crawford, VP, 2014. "Boundedly rational versus optimization-based models of strategic thinking and learning in games," University of California at San Diego, Economics Working Paper Series qt04h694rz, Department of Economics, UC San Diego.
    20. Yoella Bereby-Meyer & Alvin E. Roth, 2006. "The Speed of Learning in Noisy Games: Partial Reinforcement and the Sustainability of Cooperation," American Economic Review, American Economic Association, vol. 96(4), pages 1029-1042, September.

    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:bpj:germec:v:17:y:2016:i:3:p:284-297. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.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.