Selective Sampling with Information-Storage Constraints

Philippe Jehiel () and Jakub Steiner

Working Papers from HAL

Abstract: A memoryless agent can acquire arbitrarily many signals. After each signal observation, she either terminates and chooses an action, or she discards her observation and draws a new signal. By conditioning the probability of termination on the information collected, she controls the correlation between the payo_ state and her terminal action. We provide an optimality condition for the emerging stochastic choice. The condition highlights the bene_ts of selective memory applied to the extracted signals. Implications|obtained in a simple class of binary problems| include (i) confirmation bias, (ii) speed-accuracy complementarity, (iii) overweighting of rare events, and (iv) salience effect.

Keywords: bounded rationality; information processing; stochastic choice; confirmation bias; speed-accuracy complementarity; probability weighting; salience (search for similar items in EconPapers)
Date: 2019-07
New Economics Papers: this item is included in nep-mic
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-02183450v1
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Citations: View citations in EconPapers (3)

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Related works:
Journal Article: Selective Sampling with Information-Storage Constraints (2020)
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)
Working Paper: Selective Sampling with Information-Storage Constraints (2018)
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