We propose a class of multiple-prior representations of preferences under ambiguity where the belief the decision …

the model’s implications for optimal decision-making. This practice ignores model ambiguity, exposes the decision problem … to misspecification, and ultimately leads to post-decision disappointment. Using statistical decision theory, we develop … a framework to explore, evaluate, and optimize robust decision rules that explicitly account for estimation uncertainty …

remedy for these shortcomings by developing a dynamical model of procedurally rational decision making. The basic idea of the … model is a feedback loop between experienced utility, decision utility, and activities. In applications of the model, I show …

financial decision making, i.e. the domain of most applied economic decision making. We find no evidence of asymmetric updating …

field environment of decision making under uncertainty. Furthermore, the degree of loss aversion appears to be persistent …

We test the effects of dual processing differences in both individual traits and decision states on risk taking. In an … emotion or reason, while simultaneously measuring individual decision-making traits. Our results show that decision …

” (Kahneman, 2011, p. 300). It has powerful implications for decision theory and has been fruitfully applied in many subfields of …