How Better Information Can Garble Experts’ Advice∗

We model two experts who must make predictions about whether an event will occur or not. The experts receive private signals about the likelihood of the event occurring, and simultaneously make one of a finite set of possible predictions, corresponding to varying degrees of alarm. The information structure is commonly known among the experts and the recipients of the advice. Each expert’s payoff depends on whether the event occurs, her prediction, and possibly the prediction of the other expert. Our main result shows that when either or both experts receive uniformly more informative signals, their predictions can become unambiguously less informative. We call such information improvements perverse. Suppose a third party wishes to use the experts’ recommendations to decide whether to take some costly preemptive action to mitigate a possible bad event. The third party would then trade off the costs of two kinds of mistakes: (i) failing to take action when the event will occur; and (ii) needlessly taking the action when the event will not occur. Regardless of how this third party trades off the associated costs, he will be worse off after a perverse information improvement. These perverse information improvements can occur when each expert’s payoff is independent of the other expert’s predictions and when the information improvement is due to a transfer of technology between the experts.