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...

We develop a theoretical framework for studying the effects of interaction on the quaJity of decision-making by monetary policy committees. We show that interaction, i.e. increasing one's expertise through an exchange of views, is most likely not to result in interdependent voting...

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...

Parliamentary institutions and partisan norms are complex, and new members of parliament are unlikely to possess an innate awareness of optimal behavior. This paper examines how new legislators adopt the behavioral patterns of incumbent members in the 6th European Parliament. The 6th EP provides...

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 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 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...

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...