# Modeling Gain-Loss Asymmetries in Risky Choice: The Critical Role of Probability Weighting

- Thorsten Pachur,
*Max Planck Institute for Human Development, Center for Adaptive Rationality*
- David Kellen,
*University of Freiburg*

## Abstract

A robust empirical regularity in decision making is that the
negative consequences of an option (i.e., losses) often have a stronger impact on
people’s behavior than the positive consequences (i.e., gains). One common
explanation for such a gain-loss asymmetry is loss aversion. To model loss
aversion in risky decisions, prospect theory (Kahneman & Tversky, 1979) assumes a
kinked value function (which translates objective consequences into subjective
utilities), with a steeper curvature for losses than for gains. We highlight,
however, that the prospect theory framework offers many alternative ways to model
gain-loss asymmetries (e.g., via the weighting function, which translates
objective probabilities into subjective decision weights; or via the choice
rule). Our goal is to systematically test these alternative models against each
other. In a reanalysis of data by Glöckner and Pachur (2012), we show that
people’s risky decisions are best accounted for by a version of prospect
theory that has a more elevated weighting function for losses than for gains but
the same value function for both domains. These results contradict the common
assumption that a kinked value function is necessary to model risky choices and
point to the neglected role of people’s differential probability weighting
in the gain and loss domains.

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