Bounded Memory and Biases in Information Processing
Before choosing among two actions with state‐dependent payoffs, a Bayesian decision‐maker with a finite memory sees a sequence of informative signals, ending each period with fixed chance. He summarizes information observed with a finite‐state automaton. I characterize the optimal protocol as an equilibrium of a dynamic game of imperfect recall; a new player runs each memory state each period. Players act as if maximizing expected payoffs in a common finite action decision problem. I characterize equilibrium play with many multinomial signals. The optimal protocol rationalizes many behavioral phenomena, like “stickiness,” salience, confirmation bias, and belief polarization.
Year of publication: |
2014
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Authors: | Wilson, Andrea |
Published in: |
Econometrica. - Econometric Society. - Vol. 82.2014, 11, p. 2257-2294
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Publisher: |
Econometric Society |
Saved in:
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