Multivariate Almost Stochastic Dominance: Transfer Characterizations and Sufficient Conditions Under Dependence Uncertainty

Most often, important decisions involve several unknown attributes. This produces a double challenge in the sense that both assessing the individual multiattribute preferences and assessing the joint distribution of the attributes can be extremely hard. To handle the first challenge, the authors suggest multivariate almost stochastic dominance, a relation based on bounding marginal utilities. The authors provide necessary and sufficient characterizations in terms of simple transfers, which are easily communicated to decision makers and, thus, can be used for preference elicitation. To handle the second challenge, the authors develop sufficient conditions that do not consider the dependence structure and are based on either marginal distributions of the attributes or just their means and variances. The authors apply the theoretical results to a case study of comparing the efficiency of photovoltaic plants.