Smoothing Spline Method for Measuring Prospect Theory Components
Yao Thibaut Kpegli ()
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Yao Thibaut Kpegli: Univ Lyon, Université Lyon 2, GATE UMR 5824, F-69130 Ecully, France
No 2303, Working Papers from Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon
Prospect theory is today the main descriptive model for decision making under risk and uncertainty. Measurement methods of its components are key to many behavioral applications. This paper presents a smoothing spline method for measuring utility function, weighting function and loss aversion. The method is nonparametric and includes a penalty term to control the collinearity between the value and the weighting functions. It is applicable to both risk and uncertainty. We apply the method to individual data of Tversky and Kahneman (1992) and Gonzalez and Wu (1999). In line with original prospect theory, the probability weighting function is not sign-dependent. The value function is S-shaped with a loss aversion coefficient of 1.6.
Keywords: prospect theory; risk attitudes elicitation; smoothing spline (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gat:wpaper:2303
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