Extraneous expert information

When a Bayesian decision maker has to choose among information sources, he should consider the anticipated impact that the information will have on his posterior distribution. In some cases he may determine at the outset that an information source will have no effect on his posterior beliefs, no matter what that source says. Such an information source is called extraneous. In this paper we discuss Bayesian conditions for extraneous information sources, and show a hypothetical example involving experts with overlapping information. Analysis of U.S. weather forecasts demonstrates how this concept can be operationalized to test hypotheses concerning the use of information by forecasters. Copyright © 1985 John Wiley & Sons, Ltd.

Duke Scholars

Author Robert T. Clemen Fuqua School of Business