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Optimal Forecasting Groups

Pj Lamberson () and Scott E. Page ()
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Scott E. Page: Center for the Study of Complex Systems, Departments of Economics and Political Science, University of Michigan, Ann Arbor, Michigan 48106

Management Science, 2012, vol. 58, issue 4, 805-810

Abstract: This paper characterizes the optimal composition of a group for making a combined forecast. In the model, individual forecasters have types defined according to a statistical criterion we call type coherence. Members of the same type have identical expected accuracy, and forecasters within a type have higher covariance than forecasters of different types. We derive the optimal group composition as a function of predictive accuracy, between- and within-type covariance, and group size. Group size plays a critical role in determining the optimal group: in small groups the most accurate type should be in the majority, whereas in large groups the type with the least within-type covariance should dominate. This paper was accepted by Peter Wakker, decision analysis.

Keywords: combining forecasts; optimal groups; information aggregation (search for similar items in EconPapers)
Date: 2012
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