Probability forecasters who are rewarded via a proper scoring rule may care not only about the score, but also about their performance relative to other forecasters. We model this type of preference and show that a competitive forecaster who wants to do better than another forecaster typically should report more extreme probabilities, exaggerating toward zero or one. We consider a competitive forecaster’s best response to truthful reporting and also investigate equilibrium reporting functions in the case where another forecaster also cares about relative performance. We show how a decision maker can revise probabilities of an event after receiving reported probabilities from competitive forecasters and note that the strategy of exaggerating probabilities can make well-calibrated forecasters (and a decision maker who takes their reported probabilities at face value) appear to be overconfident. However, a decision maker who adjusts appropriately for the misrepresentation of probabilit...
Kenneth C. Lichtendahl Jr., Robert L. Winkler