Ambiguity aversion and the degree of ambiguity

Abstract

We empirically show that sample information not only moderates prospects’ outcome ambiguity but also decision makers’ revealed aversion of them. Since most natural prospects permit at least some sample inference, accounting for their degree of ambiguity improves prediction of aversion. The special case of full ambiguity, as in Ellsberg-type designs, is typically averted—yet many decision makers systematically like low degrees of ambiguity while disliking higher degrees. Ambiguity attitudes might thus usefully be characterized by not only their sensitivity to degrees of ambiguity but also such ambiguity thresholds. Just as people like some risks but not others, they have ambiguity attitudes that depend on how much ambiguity there is. We thus show how attitudes towards a degree of ambiguity are systematic, enabling prediction across sources of ambiguity.