Second-best probability weighting

Florian Herold and Nick Netzer

Games and Economic Behavior, 2023, vol. 138, issue C, 112-125

Abstract: Non-linear probability weighting is an integral part of descriptive theories of choice under risk such as prospect theory. But why do these objective errors in information processing exist? Should we try to help individuals overcome their mistake of overweighting small and underweighting large probabilities? In this paper, we argue that probability weighting can be seen as a compensation for preexisting biases in evaluating payoffs. In particular, inverse S-shaped probability weighting is a flipside of S-shaped payoff valuation. Probability distortions may thus have survived as a second-best solution to a fitness maximization problem, and it can be counter-productive to correct them while keeping the value function unchanged.

Keywords: Probability weighting; Prospect theory; Evolution of preferences (search for similar items in EconPapers)
JEL-codes: D01 D03 D81 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:gamebe:v:138:y:2023:i:c:p:112-125

DOI: 10.1016/j.geb.2022.12.005

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