Information order in monotone decision problems under uncertainty

This paper examines the robustness of Lehmann’s ranking of experiments (Lehmann, 1988) for decisionmakers who are uncertainty-averse à la Cerreia- Vioglio et al. (2011). We show that, assuming commitment, for all uncertaintyaverse indices satisfying some mild assumptions, Lehmann’s informativeness ranking is equivalent to the induced uncertainty-averse value ranking of experiments for all agents with single-crossing vNM utility indices (Theorem 1). Moreover, Lehmann ranking can also be detected by varying the uncertainty-averse indices for a fixed finite collection of vNM utility indices (Theorem 2). Our findings suggest that Lehmann’s ranking can be a useful enrichment of Blackwell’s ranking for monotone decision problems even if ambiguity is present. We apply our results to social aggregation of information preferences and investment decision problems

Information order in monotone decision problems under uncertainty

This paper examines the robustness of Lehmann’s ranking of experiments (Lehmann, 1988) for decisionmakers who are uncertainty-averse à la Cerreia- Vioglio et al. (2011). We show that, assuming commitment, for all uncertaintyaverse indices satisfying some mild assumptions, Lehmann’s informativeness ranking is equivalent to the induced uncertainty-averse value ranking of experiments for all agents with single-crossing vNM utility indices (Theorem 1). Moreover, Lehmann ranking can also be detected by varying the uncertainty-averse indices for a fixed finite collection of vNM utility indices (Theorem 2). Our findings suggest that Lehmann’s ranking can be a useful enrichment of Blackwell’s ranking for monotone decision problems even if ambiguity is present. We apply our results to social aggregation of information preferences and investment decision problems.</p