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Confidence, Consensus and Aggregation

Author

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  • Hill, Brian

    (HEC Paris)

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

  • Hill, Brian, 2023. "Confidence, Consensus and Aggregation," HEC Research Papers Series 1472, HEC Paris.
    • Handle: RePEc:ebg:heccah:1472
    DOI: 10.2139/ssrn.4387641
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    More about this item

    Keywords

    Belief aggregation; confidence in beliefs; Pareto principle; linear pooling; spurious unanimity; expertise; consensus; model averaging; model misspecification.;
    All these keywords.

    JEL classification:

    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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