Journal of Risk and Uncertainty

, Volume 59, Issue 1, pp 51–83 | Cite as

An experimental test of the predictive power of dynamic ambiguity models

  • Konstantinos GeorgalosEmail author


In this paper we report results from an economic experiment where we investigate the predictive performance of dynamic ambiguity models in the gains domain. Representing ambiguity with the aid of a transparent and non-manipulable device (a Bingo Blower) and using two-stage allocation questions, we gather data that allow us to estimate particular parametric forms of the various functionals and compare their relative performance in terms of out-of-sample fit. Our data show that a dynamic specification of Prospect Theory has the best predictive capacity, closely followed by Choquet Expected Utility, while multiple-prior theories can predict choice only for a very restricted subset of our subjects.


Ambiguity Belief updating Dynamic ambiguity models Non-expected utility Experiment 

JEL Classifications

C91 D81 D83 D90 



I am grateful to Glenn Harrison, John Hey, Ivan Paya, Vitalie Spinu and Mike Tsionas for providing helpful comments. The author would like to thank the Editor of this journal W. Kip Viscusi and a referee for very helpful comments that led to significant improvements in both the analysis and the presentation. This research was funded by a Research and Impact Support Fund awarded by the Department of Economics at the University of York (RIS 39). The financial aid of the Greek Scholarships Foundation (IKY) is gratefully recognised. The usual disclaimer applies.

Supplementary material

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of EconomicsLancaster University Management SchoolLancasterUK

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