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On the relationship between individual and group decisions

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    (Department of Economics, University of California, San Diego)

Abstract

Each member of a group receives a signal about the unknown state of the world and decides upon a utility-maximizing recommendation on the basis of that signal. The individuals have identical preferences. The group makes a decision that maximizes the common utility function assuming perfect pooling of the information in individual signals. An action profile is a group action and a recommendation from each individual. A collection of action profiles is rational if there exists an information structure under which all elements in the collection arise with positive probability. With no restrictions on the information structure, essentially all action profiles are rational. In fact, given any distribution over action profiles it is possible to find an information structure that approximates the distribution. In a monotone environment in which individuals receive conditionally independent signals, essentially any single action profile is rational, although some collections of action profiles are not.

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  • ,, 2014. "On the relationship between individual and group decisions," Theoretical Economics, Econometric Society, vol. 9(1), January.
    • Handle: RePEc:the:publsh:1185
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    Citations

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    Cited by:

    1. Stephan Jagau & Theo Offerman, 2018. "Defaults, normative anchors, and the occurrence of risky and cautious shifts," Journal of Risk and Uncertainty, Springer, vol. 56(3), pages 211-236, June.
    2. Laurent Denant-Boemont & Enrico Diecidue & Olivier l’Haridon, 2017. "Patience and time consistency in collective decisions," Experimental Economics, Springer;Economic Science Association, vol. 20(1), pages 181-208, March.
    3. P. Jean-Jacques Herings & Dominik Karos & Toygar T. Kerman, 2024. "Belief inducibility and informativeness," Theory and Decision, Springer, vol. 96(4), pages 517-553, June.
    4. Levy, Gilat & Razin, Ronny, 2018. "Information diffusion in networks with the Bayesian Peer Influence heuristic," LSE Research Online Documents on Economics 86554, London School of Economics and Political Science, LSE Library.
    5. Bougheas, Spiros & Nieboer, Jeroen & Sefton, Martin, 2015. "Risk taking and information aggregation in groups," Journal of Economic Psychology, Elsevier, vol. 51(C), pages 34-47.
    6. Gilat Levy & Ronny Razin, 2017. "The Coevolution of Segregation, Polarized Beliefs, and Discrimination: The Case of Private versus State Education," American Economic Journal: Microeconomics, American Economic Association, vol. 9(4), pages 141-170, November.
    7. Nicolas Roux & Joel Sobel, 2015. "Group Polarization in a Model of Information Aggregation," American Economic Journal: Microeconomics, American Economic Association, vol. 7(4), pages 202-232, November.
    8. Abhijit Banerjee & Olivier Compte, 2024. "Consensus and Disagreement: Information Aggregation under (Not So) Naive Learning," Journal of Political Economy, University of Chicago Press, vol. 132(8), pages 2790-2829.
    9. Levy, Gilat & Razin, Ronny, 2022. "Combining forecasts in the presence of ambiguity over correlation structures," Journal of Economic Theory, Elsevier, vol. 199(C).
    10. Levy, Gilat & Razin, Ronny, 2015. "Segregation in Education and Labour Market Discrimination: The Role of Peer Beliefs," CEPR Discussion Papers 10394, C.E.P.R. Discussion Papers.
    11. Levy, Gilat & Razin, Ronny, 2018. "Information diffusion in networks with the Bayesian Peer Influence heuristic," Games and Economic Behavior, Elsevier, vol. 109(C), pages 262-270.
    12. Razin, Ronny & Levy, Gilat, 2020. "Combining forecasts in the presence of ambiguity over correlation structures," LSE Research Online Documents on Economics 104641, London School of Economics and Political Science, LSE Library.
    13. David Dillenberger & Colin Raymond, 2016. "Group-Shift and the Consensus Effect, Second Version," PIER Working Paper Archive 16-015, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 30 Sep 2016.
    14. Honryo, Takakazu, 2018. "Risky shifts as multi-sender signaling," Journal of Economic Theory, Elsevier, vol. 174(C), pages 273-287.
    15. Xiu Chen & Fuhai Hong & Xiaojian Zhao, 2020. "Concentration and variability of forecasts in artificial investment games: an online experiment on WeChat," Experimental Economics, Springer;Economic Science Association, vol. 23(3), pages 815-847, September.
    16. Dillenberger, David & Raymond, Collin, 2019. "On the consensus effect," Journal of Economic Theory, Elsevier, vol. 183(C), pages 384-416.

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    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles

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