Curvature of the Probability Weighting Function

By George Wu, Richard Gonzalez. 1996

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Implicit Quantile Networks for Distributional Reinforcement Learning (2018, background): “71 found by Wu & Gonzalez (1996) to most closely match human subjects.”
Quantal Response Equilibrium and Overbidding in Private-Value Auctions (2002, unknown): “, [35, 36]).”
Risk Preferences Are Not Time Preferences (2012, background): “…p) may take a variety of forms, it is often argued to be monotonically increasing in the interval [0] [1], with an inverted S-shape, such that low probabilities are up-weighted and high probabilities are down-weighted (Tversky and Fox 1995; Wu and Gonzalez 1996; Prelec 1998; Gonzalez and Wu 1999).”
Prospect Theory and the Brain (2009, result): “This inverseS-shaped weighting function seems to be consistent with a range of empirical findings in laboratory studies (Camerer and Ho, 1994; Tversky and Fox, 1995; Wu and Gonzalez, 1996, 1998; Gonzalez and Wu, 1999; Wakker, 2001).”
Prospect theory for continuous distributions (2008, unknown): “Although CPT is often considered as an improvement over PT because it does not violate stochastic dominance and it can be applied to continuous outcomes, the empirical comparisons of these two theories are still inconclusive: some data fit better with PT [3, 15], some data fit better with CPT [4].”
Expected utility theory and prospect theory: one wedding and a decent funeral (2009, background): “For an example on the PT side, there are a plethora of specifications available for the probability weighting function (e.g., Wu and Gonzalez 1996 and Prelec 1998).”
A Genuine Rank-Dependent Generalization of the Von Neumann-Morgenstern Expected Utility Theorem (2002, methodology): “…is ample evidence that the weighting function in RDU is inverse S-shaped, concave over the first third of the unit interval and convex elsewhere (Tversky and Kahneman (1992); Camerer and Ho (1994); Wu and Gonzalez (1996); Gonzalez ansd Wu (1999); Abdellaoui (2000); Bleichrodt and Pinto (2000)).”
A tractable method to measure utility and loss aversion under prospect theory (2008, background): “Most empirical studies on probability weighting observed inverse S-shaped probability weighting both for gains and for losses (Tversky and Kahneman 1992; Tversky and Fox 1995; Wu and Gonzalez 1996; Gonzalez and Wu 1999; Abdellaoui 2000; Bleichrodt and Pinto 2000).”
Cumulative prospect theory and the St. Petersburg paradox (2006, unknown): “Wu and Gonzalez [18] gains: 0.”
Decision by sampling. (2006, unknown): “…(e.g., Abdellaoui, 2000; Bleichrodt & Pinto, 2000; Gonzalez & Wu, 1999; Kahneman & Tversky, 1979; Prelec, 1998; Tversky & Kahneman, 1992; Wu & Gonzalez, 1996, 1999; but see Hertwig, Barron, Weber, & Erev, 2004, for the opposite pattern for small probabilities when probabilities are…”
Probability Weighting in Choice under Risk: An Empirical Test (2001, background): “Empirical studies have displayed that the probability weighting function w is typically inverse S-shaped (Tversky and Kahneman, 1992; Camerer and Ho, 1994; Tversky and Fox, 1995; Wu and Gonzalez, 1996; Gonzalez and Wu, 1999; Bleichrodt, van Rijn, and Johannesson, 1999; Abdellaoui, 2000; Bleichrodt”