We study orders of risk and model uncertainty aversion in the smooth ambiguity model proposed by Klibanoff, Marinacci, and Mukerji (2005). We consider a quadratic approximation of their model and we show that both risk and model uncertainty attitudes have at most a second order effect....

We derive the analogue of the classic Arrow-Pratt approximation of the certainty equivalent under model uncertainty as defined by the smooth model of decision making under ambiguity of Klibanoff, Marinacci and Mukerji (2005). We study its scope via a portfolio allocation exercise that delivers a...

We propose a portfolio selection model based on a class of monotone preferences that coincide with mean-variance preferences on their domain of monotonicity, but differ where mean-variance preferences fail to be monotone and are therefore not economically meaningful. The functional associated to...

We use decision theory to confront uncertainty that is sufficiently broad to incorporate “models as approximations.” We presume the existence of a featured collection of what we call “structured models” that have explicit substantive motivations. The decision maker confronts uncertainty...

We establish an Ergodic Theorem for lower probabilities, a generalization of standard probabilities widely used in applications. As an application, we provide a version for lower probabilities of the Strong Law of Large Numbers.

This chapter reviews developments in the theory of decision making under risk and uncertainty, focusing on models that, over the last 40 years, dominated the theoretical discussions. It also surveys some implications of the departures from the “linearity in the probabilities†aspect of...