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Confidence, consensus and aggregation

Author

Listed:
  • Brian Hill

    (HEC Paris - Recherche - Hors Laboratoire - HEC Paris - Ecole des Hautes Etudes Commerciales, CNRS - Centre National de la Recherche Scientifique, GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper develops and defends a new approach to belief aggregation, involving confidence in beliefs. It is characterised by a variant of the Pareto condition that enjoins respecting consensuses borne of compromise. Confidence aggregation recoups standard probability aggregation rules, such as linear pooling, as special cases, whilst avoiding the spurious unanimity issues that have plagued such rules. Moreover, it generates a new family of probability aggregation rules that can faithfully accommodate within-person expertise diversity, hence resolving a longstanding challenge. Confidence aggregation also outperforms linear aggregation: the group beliefs it provides are closer to the truth, in expectation. Finally, confidence aggregation is dynamically rational: it commutes with update.

Suggested Citation

  • Brian Hill, 2023. "Confidence, consensus and aggregation," Working Papers hal-04381136, HAL.
    • Handle: RePEc:hal:wpaper:hal-04381136
    DOI: 10.2139/ssrn.4387641
    as

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