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...

We develop and estimate a general equilibrium model to quantitatively assess the effects and welfare implications of central bank transparency. Monetary policy can deviate from active inflation stabilization and agents conduct Bayesian learning about the nature of these deviations. Under...

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 test whether deviations from Nash equilibrium in rent-seeking contests can be explained by the slow convergence of payoff-based learning. We identify and eliminate two sources of noise that slow down learning. The first source of noise is present because each action is evaluated against a...

A policymaker selects a group of citizens—a minipublic—to advise her on the desirability of a policy. Each citizen can discover local evidence about the policy but might prefer not to due to political uncertainty in the policymaker’s adoption threshold. Such uncertainty is detrimental to...

We consider one-to-one matching problems under two modalities of uncertainty that differ in the way types are assigned to agents. Individuals have preferences over the possible types of the agents from the opposite market side and initially know the “name” but not the ”type” of the other...

We consider one-to-one matching problems under two modalities of uncertainty that differ in the way types are assigned to agents. Individuals have preferences over the possible types of the agents from the opposite market side and initially know the "name" but not the "type" of the other...

Quantum decision theory (QDT) is a recently developed theory of decision making based on the mathematics of Hilbert spaces, a framework known in physics for its application to quantum mechanics. This framework formalizes the concept of uncertainty and other effects that are particularly manifest...