Optimal Forecasting Groups

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.

• 저널Management Science · 58(4) · 805–810
• 토픽Forecasting Techniques and Applications · Management Science and Operations Research
• DOI10.1287/mnsc.1110.1441
• 저자P. J. Lamberson, Scott E. Page