The Distribution of Ambiguity Attitudes

Abstract

This paper analyses the stability and distribution of ambiguity attitudes using a broad population sample. We employ four waves of data from a survey instrument with high-powered incentives. Structural estimation of random utility models yields three individual-level parameters: Ambiguity aversion, likelihood insensitivity or perceived level of ambiguity, and the variance of decision errors. We demonstrate that these parameters are very heterogeneous but fairly stable over time and across domains. These contexts span financial markets—our main application—and climate change. The ambiguity parameters are interdependent in their interpretation and the precision of their estimates depends on decision errors. To describe heterogeneity in these three dimensions, we adopt a discrete classification approach. A third of our sample comes rather close to the behaviour of expected utility maximisers. Half of the sample is characterized by a high likelihood insensitivity, with thirty per cent ambiguity-averse and twenty per cent making ambiguity-seeking choices for most events. For the remaining eighteen per cent, we estimate sizeable error parameters, which implies that no robust conclusions about their ambiguity attitudes are possible. Predicting group membership with a large number of observed characteristics shows reasonable patterns.