Empirical justification of the uncertain equivalence method

The uncertain equivalence method (UE) is a newly proposed technique for elicitation of 1-D utilities in the case of monotonic preferences. Previous publications argue that the rationale behind the introduction of this technique is that UE estimates are not influenced by certainty effect, UE elicits points that well describe the curvature of the utility function, which is somewhat closer to the true function than the one of the lottery equivalence method (LE), and there is no increase in the width of the elicited UE uncertainty intervals compared to those of the certainty equivalence method (CE). This paper analyzes these assumptions quantitatively on the basis of empirical data from 104 volunteers who constructed their utility functions over monetary prizes using CE, LE and UE. The data was analyzed with the help of four one-tail statistical tests for paired samples. Results showed that: 1) UE results are not influenced by the certainty effect, unlike CE; 2) the UE utility function is more curved than that of LE, but that might be associated with the better selection of approximation nodes and not with the certainty effect; 3) the length of the UE uncertainty intervals is greater than that of the CE intervals, perhaps because of higher complexity of the method, but the increase is only by 30%.