IDEAS home Printed from https://ideas.repec.org/p/gms/wpaper/1066.html
   My bibliography  Save this paper

Collective Experimentation: A Laboratory Study

Author

Listed:
  • Mikhail Freer

    (Department of Economics, University of Leuven (KU Leuven).)

  • Cesar Martinelli

    (Interdisciplinary Center for Economic Science and Department of Economics, George Mason University)

  • Siyu Wang

    (For Motor Company)

Abstract

We develop a simple model of collective experimentation and take it to the lab. In equilibrium, as in the recent work of Strulovici (2010), majority rule has a bias toward under experimentation, as good news for a minority of voters may lead a majority of voters to abandon a policy when each of them thinks it is likely that the policy will be passed by a future majority excluding them. We compare the behavior in the lab of groups under majority rule and under the optimal voting rule, which precludes voting in intermediate stages of the policy experiment. Surprisingly, performs better than the (theoretically) optimal voting rule. Majority rule seems to be more robust than other forms of voting when players make mistakes.

Suggested Citation

  • Mikhail Freer & Cesar Martinelli & Siyu Wang, 2018. "Collective Experimentation: A Laboratory Study," Working Papers 1066, George Mason University, Interdisciplinary Center for Economic Science.
  • Handle: RePEc:gms:wpaper:1066
    as

    Download full text from publisher

    File URL: http://www.gmu.edu/schools/chss/economics/icesworkingpapers.gmu.edu/pdf/1066.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ernst Fehr & Klaus M. Schmidt, 1999. "A Theory of Fairness, Competition, and Cooperation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(3), pages 817-868.
    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. Richard Mckelvey & Thomas Palfrey, 1998. "Quantal Response Equilibria for Extensive Form Games," Experimental Economics, Springer;Economic Science Association, vol. 1(1), pages 9-41, June.
    4. McKelvey Richard D. & Palfrey Thomas R., 1995. "Quantal Response Equilibria for Normal Form Games," Games and Economic Behavior, Elsevier, vol. 10(1), pages 6-38, July.
    5. Steven Callander & Patrick Hummel, 2014. "Preemptive Policy Experimentation," Econometrica, Econometric Society, vol. 82(4), pages 1509-1528, July.
    6. Axel Ockenfels & Gary E. Bolton, 2000. "ERC: A Theory of Equity, Reciprocity, and Competition," American Economic Review, American Economic Association, vol. 90(1), pages 166-193, March.
    7. Albrecht, James & Anderson, Axel & Vroman, Susan, 2010. "Search by committee," Journal of Economic Theory, Elsevier, vol. 145(4), pages 1386-1407, July.
    8. Messner, Matthias & Polborn, Mattias K., 2012. "The option to wait in collective decisions and optimal majority rules," Journal of Public Economics, Elsevier, vol. 96(5), pages 524-540.
    9. Bruno Strulovici, 2010. "Learning While Voting: Determinants of Collective Experimentation," Econometrica, Econometric Society, vol. 78(3), pages 933-971, May.
    10. Chen, Daniel L. & Schonger, Martin & Wickens, Chris, 2016. "oTree—An open-source platform for laboratory, online, and field experiments," Journal of Behavioral and Experimental Finance, Elsevier, vol. 9(C), pages 88-97.
    11. Jimmy Chan & Alessandro Lizzeri & Wing Suen & Leeat Yariv, 2018. "Deliberating Collective Decisions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(2), pages 929-963.
    12. Fernandez, Raquel & Rodrik, Dani, 1991. "Resistance to Reform: Status Quo Bias in the Presence of Individual-Specific Uncertainty," American Economic Review, American Economic Association, vol. 81(5), pages 1146-1155, December.
    13. , & ,, 2013. "Specialization and partisanship in committee search," Theoretical Economics, Econometric Society, vol. 8(3), September.
    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. Bowen, Renee & Hwang, Ilwoo & Krasa, Stefan, 2022. "Personal power dynamics in bargaining," Journal of Economic Theory, Elsevier, vol. 205(C).
    2. Vincent Anesi & Mikhail Safronov, 2021. "Cloturing Deliberation," DEM Discussion Paper Series 21-03, Department of Economics at the University of Luxembourg.
    3. Vincent Anesi & Mikhail Safronov, 2023. "Deciding When To Decide: Collective Deliberation And Obstruction," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(2), pages 757-781, May.
    4. Gersbach, Hans & Wickramage, Kamali, 2021. "Balanced voting," Mathematical Social Sciences, Elsevier, vol. 113(C), pages 203-229.
    5. Bowen, T. Renee & Krasa, Stefan & Hwang, Ilwoo, 2020. "Agenda-Setter Power Dynamics: Learning in Multi-Issue Bargaining," CEPR Discussion Papers 15406, C.E.P.R. Discussion Papers.
    6. DeAngelo, Gregory & Houser, Daniel & Romaniuc, Rustam, 2020. "Experimental public choice: An introduction to the special issue," Journal of Economic Behavior & Organization, Elsevier, vol. 175(C), pages 278-280.
    7. Bowen, T. Renee & Anesi, Vincent, 2018. "Policy Experimentation, Redistribution and Voting Rules," CEPR Discussion Papers 12797, C.E.P.R. Discussion Papers.
    8. Ginzburg, Boris & Guerra, José-Alberto, 2019. "When collective ignorance is bliss: Theory and experiment on voting for learning," Journal of Public Economics, Elsevier, vol. 169(C), pages 52-64.
    9. Ginzburg, Boris, 2022. "Collective Learning and Distributive Uncertainty," MPRA Paper 112780, University Library of Munich, Germany.

    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. Moldovanu, Benny & Rosar, Frank, 2021. "Brexit: A comparison of dynamic voting games with irreversible options," Games and Economic Behavior, Elsevier, vol. 130(C), pages 85-108.
    2. Jacob K. Goeree & Charles A. Holt, 2001. "Ten Little Treasures of Game Theory and Ten Intuitive Contradictions," American Economic Review, American Economic Association, vol. 91(5), pages 1402-1422, December.
    3. Simon P. Anderson & Jacob K. Goeree & Charles A. Holt, 2002. "The Logit Equilibrium: A Perspective on Intuitive Behavioral Anomalies," Southern Economic Journal, John Wiley & Sons, vol. 69(1), pages 21-47, July.
    4. Ginzburg, Boris & Guerra, José-Alberto, 2019. "When collective ignorance is bliss: Theory and experiment on voting for learning," Journal of Public Economics, Elsevier, vol. 169(C), pages 52-64.
    5. Ginzburg, Boris, 2022. "Collective Learning and Distributive Uncertainty," MPRA Paper 112780, University Library of Munich, Germany.
    6. moldovanu, benny & Rosar, Frank, 2019. "Brexit: Dynamic Voting with an Irreversible Option," CEPR Discussion Papers 14101, C.E.P.R. Discussion Papers.
    7. Camerer, Colin F. & Ho, Teck-Hua, 2015. "Behavioral Game Theory Experiments and Modeling," Handbook of Game Theory with Economic Applications,, Elsevier.
    8. Inukai, Keigo & Kawata, Keisuke & Sasaki, Masaru, 2017. "Committee Search with Ex-ante Heterogeneous Agents: Theory and Experimental Evidence," IZA Discussion Papers 10760, Institute of Labor Economics (IZA).
    9. Dieter Balkenborg & Rosemarie Nagel, 2016. "An Experiment on Forward vs. Backward Induction: How Fairness and Level k Reasoning Matter," German Economic Review, Verein für Socialpolitik, vol. 17(3), pages 378-408, August.
    10. Quement, Mark T. Le & Marcin, Isabel, 2020. "Communication and voting in heterogeneous committees: An experimental study," Journal of Economic Behavior & Organization, Elsevier, vol. 174(C), pages 449-468.
    11. Stefan Kohler & European University Institute, 2006. "Inequality Aversion and Stochastic Decision-making: Experimental Evidence from Zimbabwean Villages after Land Reform," Economics Series Working Papers GPRG-WPS-061, University of Oxford, Department of Economics.
    12. Yi, Kang-Oh, 2005. "Quantal-response equilibrium models of the ultimatum bargaining game," Games and Economic Behavior, Elsevier, vol. 51(2), pages 324-348, May.
    13. Cason, Timothy N. & Mui, Vai-Lam, 2002. "Fairness and sharing in innovation games: a laboratory investigation," Journal of Economic Behavior & Organization, Elsevier, vol. 48(3), pages 243-264, July.
    14. Olivier Armantier, 2006. "Do Wealth Differences Affect Fairness Considerations?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 391-429, May.
    15. Breitmoser, Yves & Tan, Jonathan H.W., 2020. "Why should majority voting be unfair?," Journal of Economic Behavior & Organization, Elsevier, vol. 175(C), pages 281-295.
    16. Cooper, David J. & Van Huyck, John B., 2003. "Evidence on the equivalence of the strategic and extensive form representation of games," Journal of Economic Theory, Elsevier, vol. 110(2), pages 290-308, June.
    17. Klempt Charlotte & Pull Kerstin & Stadler Manfred, 2019. "Asymmetric Information in Simple Bargaining Games: An Experimental Study," German Economic Review, De Gruyter, vol. 20(1), pages 29-51, February.
    18. Mark T. Le Quement & Isabel Marcin, 2016. "Communication and voting in heterogeneous committees: An experimental study," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2016_05, Max Planck Institute for Research on Collective Goods, revised Oct 2016.
    19. Tavoni, Alessandro, 2009. "Incorporating Fairness Motives into the Impulse Balance Equilibrium and Quantal Response Equilibrium Concepts: An Application to 2x2 Games," Sustainable Development Papers 50740, Fondazione Eni Enrico Mattei (FEEM).
    20. Nick Feltovich, 2000. "Reinforcement-Based vs. Belief-Based Learning Models in Experimental Asymmetric-Information," Econometrica, Econometric Society, vol. 68(3), pages 605-642, May.

    More about this item

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:gms:wpaper:1066. 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: Shams Bahabib (email available below). General contact details of provider: https://edirc.repec.org/data/icgmuus.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.