Signal perception and belief updating

This paper introduces a theory of signal perception to study how people update their beliefs. By allowing perceived signals to deviate from actual signals, we identify the probability that people miss or misread signals, giving indexes of conservatism and confirmatory bias. In an experiment, we elicited perceived signals from choices and obtained a structural estimation of the indexes. The subjects were conservative and acted as if they missed 43% of the signals they received. Also they exhibited confirmatory bias by misreading 19% of the signals contradicting their prior beliefs.

This seminar is organized by Stefano Palminteri (LNC2/Human reinforcement learning).