Much of the empirical success of Rank-Dependent Expected Utility Theory and Cumulative Prospect Theory is due to the fact that they allow for nonlinearity towards both outcomes (through the utility function) and probabilities (through the probability weighting function). Since risk attitude is jointly determined by the shapes of the two functions, it would be instructive to measure how the degree of risk aversion incorporated in the utility function empirically covaries with its counterpart from the probability weighting function. We conduct a large-scale simulation to assess whether an elicitation procedure based on the trade-off method, which essentially equals that used in recent empirical studies, allows to reliably measure the quantity of interest. We find a strong systematic distortion of measurement, which points at the limitations of the presently available elicitation techniques.
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