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Some have argued that ambiguity aversion implies information aversion (refusing free information) and is therefore irrational (see, e.g., Al-Najjar and Weinstein 2009 and Fleurbaey 2018). However, using a simple model involving climate policy, this paper shows that such supposed information avoidance merely demonstrates a perfectly reasonable preference for time-consistency and/or cost-avoidance.

AbstractWe design and implement lab experiments to evaluate the normative appeal of behavior arising from models of ambiguity-averse preferences. We report two main empirical findings. First, we demonstrate that behavior reflects an incomplete understanding of the problem, providing evidence that subjects do not act on the basis of preferences alone. Second, additional clarification of the decision making environment pushes subjects' choices in the direction of ambiguity aversion models, regardless of whether or not the choices are also consistent with subjective expected utility, supporting the position that subjects find such behavior normatively appealing.

AbstractWe 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.

Abstract
Consumers generally prefer precise probabilities or outcomes over imprecise ranges with the same expected value, a bias known as "ambiguity aversion." We argue that two elementary principles of numerical cognition explain great heterogeneity in this bias, affecting consumer choices in many domains where options are characterized by varying levels of uncertainty (e.g., lotteries, discounts, investment products, vaccines, etc.). The first principle, the "compression effect," stipulates that consumers' mental number lines are increasingly compressed at greater number magnitudes. This alone suffices to predict ambiguity aversion as it causes a midpoint (e.g., $40) to be perceived as closer to the upper bound of a range (e.g., $60) compared to its lower bound (e.g., $20). Furthermore, as the compression effect distorts the mental number line especially at lower numbers, it follows that ambiguity aversion should decrease around greater numbers. The second principle, the "left-digit effect" causes a range's relative attractiveness to decrease (increase) disproportionately with every left-digit transition in its lower (upper) bound, thus increasing (decreasing) ambiguity aversion. Due to the overall compression effect, the impact of the left-digit effect increases at greater numbers. We present 34 experiments (N = 10,634) to support the theory's predictions and wide applicability.