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Decisions with conflicting and imprecise information

Author

Listed:
  • Thibault Gajdos Preuss

    (X-DEP-ECO - Département d'Économie de l'École Polytechnique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris, CERSES - UMR 8137 - Centre de recherche sens, ethique, société - UPD5 - Université Paris Descartes - Paris 5 - CNRS - Centre National de la Recherche Scientifique, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Jean-Christophe Vergnaud

    (CERSES - UMR 8137 - Centre de recherche sens, ethique, société - UPD5 - Université Paris Descartes - Paris 5 - CNRS - Centre National de la Recherche Scientifique, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

The most usual procedure when facing decisions in complex settings consists in consulting experts, aggregating the information they provide, and deciding on the basis of this aggregated information. We argue that such a procedure entails a substantial loss, insofar as it precludes the possibility to take into account simultaneously the decision maker's attitude towards conflict among experts and her attitude towards imprecision of information. We propose to consider directly how a decision maker behaves when using information coming from several sources. We give an axiomatic foundation for a decision criterion that allows to distinguish on a behavioral basis the decision maker's attitude towards imprecision and towards conflict.

Suggested Citation

  • Thibault Gajdos Preuss & Jean-Christophe Vergnaud, 2013. "Decisions with conflicting and imprecise information," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00443075, HAL.
    • Handle: RePEc:hal:cesptp:hal-00443075
    DOI: 10.1007/s00355-012-0691-1
    Note: View the original document on HAL open archive server: https://hal.science/hal-00443075v1
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    Citations

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    Cited by:

    1. ,, 2012. "The ex-ante aggregation of opinions under uncertainty," Theoretical Economics, Econometric Society, vol. 7(3), September.
    2. Eric Danan & Thibault Gajdos & Brian Hill & Jean-Marc Tallon, 2016. "Robust Social Decisions," American Economic Review, American Economic Association, vol. 106(9), pages 2407-2425, September.
    3. Stergios Athanassoglou & Valentina Bosetti, 2015. "Setting Environmental Policy When Experts Disagree," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 61(4), pages 497-516, August.
    4. Brian Hill, 2012. "Unanimity and the aggregation of multiple prior opinions," Working Papers hal-00712015, HAL.
    5. Théodora Dupont-Courtade, 2012. "Insurance demand under ambiguity and conflict for extreme risks : Evidence from a large representative survey," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00718642, HAL.
    6. Marcello Basili, 2018. "Aggregation of experts’ opinions and conditional consensus opinion," Department of Economics University of Siena 780, Department of Economics, University of Siena.
    7. repec:spo:wpmain:info:hdl:2441/eu4vqp9ompqllr09iepso50rh is not listed on IDEAS
    8. Jean Desrochers & J. Francois Outreville, 2013. "Uncertainty, Ambiguity and Risk Taking: an experimental investigation of consumer behavior and demand for insurance," ICER Working Papers 10-2013, ICER - International Centre for Economic Research.
    9. repec:hal:pseose:halshs-01415412 is not listed on IDEAS
    10. Théodora Dupont-Courtade, 2012. "Insurance demand under ambiguity and conflict for extreme risks: Evidence from a large representative survey," Documents de travail du Centre d'Economie de la Sorbonne 12020, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    11. Berger, Loïc & Bosetti, Valentina, 2020. "Characterizing ambiguity attitudes using model uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 621-637.
    12. repec:spo:wpecon:info:hdl:2441/eu4vqp9ompqllr09iepso50rh is not listed on IDEAS
    13. Crès, Hervé & Gilboa, Itzhak & Vieille, Nicolas, 2011. "Aggregation of multiple prior opinions," Journal of Economic Theory, Elsevier, vol. 146(6), pages 2563-2582.
    14. Gayer, Gabrielle & Lehrer, Ehud & Persitz, Dotan, 2024. "Aggregating inconclusive data sets," Games and Economic Behavior, Elsevier, vol. 146(C), pages 77-90.
    15. Xiangyu Qu, 2017. "Separate aggregation of beliefs and values under ambiguity," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 63(2), pages 503-519, February.
    16. Stanca, Lorenzo, 2021. "Smooth aggregation of Bayesian experts," Journal of Economic Theory, Elsevier, vol. 196(C).
    17. Eric Danan, 2021. "Partial utilitarianism," Working Papers hal-03327900, HAL.
    18. Aurélien Baillon & Laure Cabantous & Peter Wakker, 2012. "Aggregating imprecise or conflicting beliefs: An experimental investigation using modern ambiguity theories," Journal of Risk and Uncertainty, Springer, vol. 44(2), pages 115-147, April.
    19. Théodora Dupont-Courtade, 2012. "Insurance demand under ambiguity and conflict for extreme risks : Evidence from a large representative survey," Post-Print halshs-00718642, HAL.
    20. Laure Cabantous & Denis Hilton & Howard Kunreuther & Erwann Michel-Kerjan, 2011. "Is imprecise knowledge better than conflicting expertise? Evidence from insurers’ decisions in the United States," Journal of Risk and Uncertainty, Springer, vol. 42(3), pages 211-232, June.
    21. Pablo Amorós, 2017. "The problem of aggregating experts' opinions to select the winner of a competition," Working Papers 2017-04, Universidad de Málaga, Department of Economic Theory, Málaga Economic Theory Research Center.

    More about this item

    Keywords

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    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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