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 analyze a bias in transaction-based price indexes due to the presence of seller reservation prices. We develop a model in which the ratio of sellers' reservation prices to the market value affects trading volume and biases of observed transaction prices: when trading volume decreases (increases), index returns are estimated with an upward (downward) bias. We propose a new econometric procedure to mitigate the bias, and use simulations to demonstrate the effectiveness of the procedure. We construct a reserve-conditional unbiased index for the Los Angeles housing market, which substantially differs from a traditional repeat sale index.