The standard Bayesian model implies that information can never have a negative value. We put this implication to the proof. Our paper provides the first test of the value (positive or negative) of information under uncertainty. We show that the "Bayesian implication" stands in conflict with the...

We propose and axiomatize a decision model of social preferences under risk that captures motivated reasoning in social assessments. Our model considers a setup with a decision maker (DM) and one other individual. It highlights how the presence of risk enables the DM to egoistically exploit the...