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Probabilistic Opinion Pooling

Dietrich, Franz and List, Christian (2014) Probabilistic Opinion Pooling. [Preprint]

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Abstract

Suppose several individuals (e.g., experts on a panel) each assign probabilities to some events. How can these individual probability assignments be aggregated into a single collective probability assignment? This article reviews several proposed solutions to this problem. We focus on three salient proposals: linear pooling (the weighted or unweighted linear averaging of probabilities), geometric pooling (the weighted or unweighted geometric averaging of probabilities), and multiplicative pooling (where probabilities are multiplied rather than averaged). We present axiomatic characterisations of each class of pooling functions (most of them classic, but one new) and argue that linear pooling can be justified "procedurally" but not "epistemically", while the other two pooling methods can be justified "epistemically". The choice between them, in turn, depends on whether the individuals' probability assignments are based on shared information or on private information. We conclude by mentioning a number of other pooling methods.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Dietrich, Franz
List, Christian
Keywords: Probabilistic opinion pooling, Judgment aggregation, Peer disagreement, Linear, geometric, and multiplicative pooling, Eventwise independence, Unanimity preservation, External Bayesianity
Subjects: General Issues > Decision Theory
Specific Sciences > Economics
Specific Sciences > Probability/Statistics
Depositing User: Christian List
Date Deposited: 01 Mar 2015 01:21
Last Modified: 01 Mar 2015 01:21
Item ID: 11349
Official URL: http://personal.lse.ac.uk/list/PDF-files/OpinionPo...
DOI or Unique Handle: http://personal.lse.ac.uk/list/PDF-files/OpinionPoolingReview.pdf
Subjects: General Issues > Decision Theory
Specific Sciences > Economics
Specific Sciences > Probability/Statistics
Date: October 2014
URI: https://philsci-archive.pitt.edu/id/eprint/11349

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