Working Paper: CEPR ID: DP12546
Authors: Philippe Jehiel; Jakub Steiner
Abstract: A proposed model of information processing generates a prediction about the constrained-optimal stochastic choice that is robust to details of the feasible information structures. A decision-maker processes payoff-relevant information until she reaches her cognitive constraint, at which point she either terminates the decision-making and chooses an action, or restarts the process. By conditioning the probability of termination on the information collected, she controls the correlation between the payoff state and her terminal action. The constrained-optimal choice rule exhibits (i) confirmation bias, (ii) speed-accuracy complementarity, (iii) overweighting of rare events, and (iv) salience effect.
Keywords: bounded rationality; cognitive constraints; information processing; stochastic choice; confirmation bias; speed-accuracy complementarity; probability weighting; salience
JEL Codes: D03; D80; D81; D83; D89; D90
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| cognitive constraints (D91) | processing payoff-relevant information (G35) |
| processing payoff-relevant information (G35) | cognitive limit (D91) |
| cognitive limit (D91) | terminate decision-making or restart information acquisition (D87) |
| confirmation bias (D91) | informed posteriors (Y50) |
| longer response times (C41) | decreased accuracy (C83) |
| overweighting of rare events (C46) | beliefs about infrequent events (D80) |
| distinct states (H73) | attract attention more than indistinct ones (D80) |
| selective rerunning of decision process (D79) | optimal under certain conditions (C61) |