Fast and Simple Adaptive Elicitations
53 Pages Posted: 5 May 2020 Last revised: 24 Feb 2022
Date Written: June 9, 2021
We propose a new adaptive procedure for the measurement of decision models. Our procedure bounds the function of the decision model, sequentially halves the maximal distance between its bounds, and incrementally restricts the feasible space of associated parameters. It relies on approximating splines that improve tractability and descriptiveness. We apply and illustrate our procedure to elicit the probability weighting function in a simulation study and laboratory experiment. Our procedure faithfully recovers the underlying function and captures empirical regularities in probability weighting. In addition, it reveals systematic distortions introduced by standard parametric forms and sheds new light on the pervasiveness of possibility and certainty effects.
Keywords: elicitations, Expected Utility, Rank-Dependent Utility, probability weighting function
JEL Classification: C1
Suggested Citation: Suggested Citation