Evidence from the laboratory and the field has uncovered both underreaction and overreaction to new information. We provide new experimental evidence on the underlying mechanisms of under‐ and overreaction by comparing how people make inferences and revise forecasts in the same information environment. Participants underreact to signals when inferring about underlying states, but overreact to the same signals when revising forecasts about future outcomes—a phenomenon we term “the inference‐forecast gap.” We show that this gap is largely driven by different simplifying heuristics used in the two tasks. Additional treatments suggest that the choice of heuristics is affected by the similarity between statistics in the information environment and the statistic elicited by the belief‐updating problem.

We consider a dynamic monetary economy where agents gradually learn about the holding cost of a new asset and coordinate to adopt it as money or abandon it. We provide closed-form solutions for state-contingent asset prices and agents’ adoption decision. The transactional benefits of using money are endogenous and can convexify or concavify the payoff structure. Thus, the arrival of new information can raise or reduce the asset’s price, which is in sharp contrast to standard insights in experimentation models. Full disclosure of the asset type and an increase in the learning speed improve information but have different welfare implications.