Estimating ambiguity preferences and perceptions in multiple prior models: Evidence from the field.

ABSTRACT: We develop a tractable method to estimate multiple prior models of decision-making under ambiguity. In a representative sample of the U.S. population, we measure ambiguity attitudes in the gain and loss domains. We find that ambiguity aversion is common for uncertain events of moderate to high likelihood involving gains, but ambiguity seeking prevails for low likelihoods and for losses. We show that choices made under ambiguity in the gain domain are best explained by the α-MaxMin model, with one parameter measuring ambiguity aversion (ambiguity preferences) and a second parameter quantifying the perceived degree of ambiguity (perceptions about ambiguity). The ambiguity aversion parameter α is constant and prior probability sets are asymmetric for low and high likelihood events. The data r

SUBMITTER: Dimmock SG 

PROVIDER: S-EPMC4765960 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature