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Selective Sampling with Information-Storage Constraints

Philippe Jehiel () and Jakub Steiner

CERGE-EI Working Papers from The Center for Economic Research and Graduate Education - Economics Institute, Prague

Abstract: A decision-maker acquires payoff-relevant information until she reaches her storing capacity, at which point she either terminates the decision-making and chooses an action, or discards some information. By conditioning the probability of termination on the information collected, she controls the correlation between the payoff state and her terminal action. We provide an optimality condition for the emerging stochastic choice. The condition highlights the benefits of selective memory applied to the extracted signals. 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 (search for similar items in EconPapers)
JEL-codes: D03 D80 D81 D83 D89 D90 (search for similar items in EconPapers)
Date: 2018-07
New Economics Papers: this item is included in nep-mic and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Selective Sampling with Information-Storage Constraints (2020) Downloads
Working Paper: Selective Sampling with Information-Storage Constraints (2020)
Working Paper: Selective Sampling with Information-Storage Constraints (2020)
Working Paper: Selective Sampling with Information-Storage Constraints (2019) Downloads
Working Paper: Selective Sampling with Information-Storage Constraints (2019) Downloads
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