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Smoothing Spline Method for Measuring Prospect Theory Components

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  • Yao Thibaut Kpegli

    (Univ Lyon, Université Lyon 2, GATE UMR 5824, F-69130 Ecully, France)

Abstract

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.

Suggested Citation

  • Yao Thibaut Kpegli, 2023. "Smoothing Spline Method for Measuring Prospect Theory Components," Working Papers 2303, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    • Handle: RePEc:gat:wpaper:2303
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    References listed on IDEAS

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    Keywords

    prospect theory; risk attitudes elicitation; smoothing spline;
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