A Bayesian agent evaluates a stream of information over a finite period before deciding on which of two alternatives to adopt. At any point, the agent is free to convert information into an informative, binary signal. When information arrives at a roughly constant rate, an agent who frequently...

When do groups and societies choose to be uninformed? We study a committee that needs to vote on a reform which will give every member a private state- dependent payoff. The committee can vote to learn the state at no cost. We show that the committee decides not to learn the state when...

The paper proves that the Bayesian approach to learning and expectations formation implies no propositions that could conceivably be refuted by observation. For a (non-expanding) universe infinite in time but finite at any point of time, it is shown that by a suitable choice of priors, any...

This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors' information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the...

We examine the effects of estimation risk and Bayesian learning on equilibrium asset prices when there is uncertainty about both the first and second moments of consumption and dividend growth rates. For the 1891-2007 period, our model generates a sizable average annual equity premium,...

We examine the effects of parameter uncertainty and Bayesian learning on equilibrium asset prices when all the structural parameters of the aggregate consumption and dividend growth rate processes are unknown. With realistic calibration of a parsimonious set of prior parameters, the model...

In the face of demand uncertainty, a monopolist can observe sales as a controlled reaction to its price and advertising so as to improve the choice of this marketing mix in the future. Furthermore, to upgrade its knowledge about demand the firm has the option to invest in external market...

We develop a behavioral theory of real options that relaxes the informational and behavioral assumptions underlying applications of financial options theory to real assets. To do so, we augment real option theory's focus on uncertain future asset values (prospective uncertainty) with feedback...

In standard models of rational learning from experience, prior uncertainties and disagreements recede smoothly as common evidence accumulates. However, this presumes that the underlying risks are relatively stable. Otherwise, rational learners need to sift random noise for signs that the trend...

A new methodology is presented to solve an important model of dynamic decision-making with a continuous unknown parameter (or state). The methodology centers on the concepts of “continuation-value function” (which gives the expected value-to-go as a function of the parameter under a feasible...