Optimal Forecasting Groups

• 成果类型: Article
• 署名作者: Lamberson, P. J.; Page, Scott E.
• 署名单位: Northwestern University; Northwestern University; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.1110.1441
• 发表日期: 2012
• 页码: 805-810
• 关键词: combining forecasts; optimal groups; information aggregation

摘要

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.