Curvature of the Probability Weighting Function

Curvature of the Probability Weighting Function

When individuals choose among risky alternatives, the psychological weight attached to an outcome may not correspond to the probability of that outcome. In rank-dependent utility theories, including prospect theory, the probability weighting function permits probabilities to be weighted nonlinearly....

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Bibliographische Detailangaben
Veröffentlicht in:Management Science. - Institute for Operations Research and the Management Sciences, 1954. - 42(1996), 12, Seite 1676-1690
1. Verfasser: Wu, George (VerfasserIn)
Weitere Verfasser: Gonzalez, Richard
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 1996
Zugriff auf das übergeordnete Werk:Management Science
Schlagworte:Decision Making Expected Utility Nonexpected Utility Theory Prospect Theory Risk Risk Aversion Mathematics Applied sciences Behavioral sciences Economics Information science
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520 |a When individuals choose among risky alternatives, the psychological weight attached to an outcome may not correspond to the probability of that outcome. In rank-dependent utility theories, including prospect theory, the probability weighting function permits probabilities to be weighted nonlinearly. Previous empirical studies of the weighting function have suggested an inverse S-shaped function, first concave and then convex. However, these studies suffer from a methodological shortcoming: estimation procedures have required assumptions about the functional form of the value and/or weighting functions. We propose two preference conditions that are necessary and sufficient for concavity and convexity of the weighting function. Empirical tests of these conditions are independent of the form of the value function. We test these conditions using preference "ladders" (a series of questions that differ only by a common consequence). The concavity-convexity ladders validate previous findings of an S-shaped weighting function, concave up to p < 0.40, and convex beyond that probability. The tests also show significant nonlinearity away from the boundaries, 0 and 1. Finally, we fit the ladder data with weighting functions proposed by Tversky and Kahneman (1992) and Prelec (1995). 
540 |a Copyright 1996 Institute for Operations Research and the Management Sciences 
650 4 |a Decision Making 
650 4 |a Expected Utility 
650 4 |a Nonexpected Utility Theory 
650 4 |a Prospect Theory 
650 4 |a Risk 
650 4 |a Risk Aversion 
650 4 |a Mathematics  |x Mathematical expressions  |x Mathematical functions  |x Weighting functions 
650 4 |a Mathematics  |x Pure mathematics  |x Geometry  |x Geometric properties  |x Concavity 
650 4 |a Mathematics  |x Pure mathematics  |x Geometry  |x Geometric properties  |x Convexity 
650 4 |a Applied sciences  |x Technology  |x Tools  |x Ladders 
650 4 |a Behavioral sciences  |x Leisure studies  |x Recreation  |x Games  |x Gambling  |x Lotteries 
650 4 |a Behavioral sciences  |x Behavioral economics  |x Prospect theory 
650 4 |a Economics  |x Microeconomics  |x Economic utility  |x Expected utility 
650 4 |a Mathematics  |x Pure mathematics  |x Geometry  |x Geometric properties  |x Curvature 
650 4 |a Information science  |x Information search and retrieval  |x Information search  |x Search strategies  |x Term weighting 
650 4 |a Mathematics  |x Applied mathematics  |x Statistics  |x Applied statistics  |x Inferential statistics  |x Statistical estimation  |x Estimation methods 
655 4 |a research-article 
700 1 |a Gonzalez, Richard  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t Management Science  |d Institute for Operations Research and the Management Sciences, 1954  |g 42(1996), 12, Seite 1676-1690  |w (DE-627)320623602  |w (DE-600)2023019-9  |x 15265501  |7 nnns 
773 1 8 |g volume:42  |g year:1996  |g number:12  |g pages:1676-1690 
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