Unanimity and Compromise Among Probability Forecasters

When two forecasters agree regarding the probability of an uncertain event, should a decision maker adopt that probability as his or her own? A decision maker who does so is said to act in accord with the unanimity principle. We examine a variety of Bayesian consensus models with respect to their conformance (or lack thereof) to the unanimity principle and a more general compromise principle. In an analysis of a large set of probability forecast data from meteorology, we show how well the various models, when fit to the data, reflect the empirical pattern of conformance to these principles.