  When people receive new information, sometimes they revise their beliefs too
much, and sometimes too little. In this paper, we show that a key driver of
whether people overinfer or underinfer is the strength of the information.
Based on a model in which people know which direction to update in, but not
exactly how much to update, we hypothesize that people will overinfer from weak
signals and underinfer from strong signals. We then test this hypothesis across
four different environments: abstract experiments, a naturalistic experiment,
sports betting markets, and financial markets. In each environment, our
consistent and robust finding is overinference from weak signals and
underinference from strong signals. Our framework and findings can help
harmonize apparently contradictory results from the experimental and empirical
literatures.
