Anticipated utility: A measure representation approach

The measure representation: A correction

“…Theorem 2 in [6] and Theorem 9 in [7] prove that under some further conditions, the measure{) is a product measure. These proofs implicitly assume that {) on D is bounded.…”

“…According to this model, the value of a lottery X with a cumulative distribution function F is given by AU(X) = j u(x)df(F(x)) A natural extension of this model is to represent the preference relation � on lotteries by a general (not necessarily product) measure of the lotteries' epigraphs. This functional is suggested and axiomatized in Segal [5,6]. It turns out, however, that there are some mistakes in these papers (see Wakker [9] and Puppe [2] [ 5 ] .…”

“…This leads to the conclusion that the measure representation applies only to subsets of the space of lotteries, although these subsets can become arbitrarily close to the whole space of lotteries. Some additional axioms (Segal [6,7]), implying that the measure is a product measure (and hence anticipated utility), also guarantee that the measure is bounded.…”

Cardinal Extensions of the EU Model Based on the Choquet Integral

“…Variants of this model are due to Yaari (1987), Segal (1987Segal ( , 1993 and Allais (1988). More general axiomatizations can be found in Wakker (1994), Chateauneuf (1999).…”

From Uniform Expected Utility to Uniform Rank-Dependent Utility: An experimental study

“…Several researchers have provided axiomatizations of RDU models [1,11,22,24,27,28,33], and, according to Wakker [34, p. 352], they are said to be the 420 best-performing and most-confirmed empirical models for decision under risk and uncertainty to date. Because of their extensive use, however, numerous empirical violations of these models have been documented as well [e.g., 6, 16, 19, 29, 35].…”