Calibration, sharpness and the weighting of experts in a linear opinion pool

Stephen Hora () and Erim Kardeş ()

Annals of Operations Research, 2015, vol. 229, issue 1, 429-450

Abstract: Linear opinion pools are the most common form of aggregating the probabilistic judgments of multiple experts. Here, the performance of such an aggregation is examined in terms of the calibration and sharpness of the component judgments. The performance is measured through the average quadratic score of the aggregate. Trade-offs between calibration and sharpness are examined and an expression for the optimal weighting of two dependent experts in a linear combination is given. Circumstances where one expert would be disqualified are investigated. Optimal weights for the multiple, dependent experts are found through a concave quadratic program. Copyright Springer Science+Business Media New York 2015

Keywords: Probabilistic expert judgment; Subjective probability; Scoring rules; Subject matter expert; Calibration; Quadratic score; Brier score (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10479-015-1846-0

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