All at Once! A Comprehensive and Tractable Semi-Parametric Method to Elicit Prospect Theory Components

Yao Kpegli, Brice Corgnet and Adam Zylbersztejn ()
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Adam Zylbersztejn: GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique

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Abstract: Eliciting all the components of prospect theory-curvature of the utility function, weighting function and loss aversion-remains an open empirical challenge. We develop a semi-parametric method that keeps the tractability of parametric methods while providing more precise estimates. Using the data of Tversky and Kahneman (1992), we revisit their main parametric results. We reject the convexity of the utility function in the loss domain, find lower probability weighting, and confirm loss aversion. We also report that the probability weighting function does not exhibit duality and equality across domains, in line with cumulative prospect theory and in contrast with original prospect and rank dependent utility theories.

Keywords: Prospect theory; semi-parametric estimation; risk attitudes; weighting function; loss aversion (search for similar items in EconPapers)
Date: 2020-11-20
New Economics Papers: this item is included in nep-upt
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-03016517v1
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Journal Article: All at once! A comprehensive and tractable semi-parametric method to elicit prospect theory components (2023)
Working Paper: All at Once! A Comprehensive and Tractable Semi-Parametric Method to Elicit Prospect Theory Components (2020)
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