We show how low-frequency boom and bust cycles in asset prices can emerge from Bayesian learning by investors. Investors rationally maximize infinite horizon utility but hold subjective priors about the asset return process that we allow to differ infinitesimally from the rational expectations...

We present a decision theoretic framework in which agents are learning about market behavior and that provides microfoundations for models of adaptive learning. Agents are 'internally rational', i.e., maximize discounted expected utility under uncertainty given dynamically consistent subjective...

When is it optimal for a government to default on its legal repayment obligations? We answer this question for a small open economy with domestic production risk in which contracting frictions make it optimal for the government to finance itself by issuing non-contingent debt. We show that...

We document the presence of sizable distributional effects from unexpected price level movements in the Euro Area (EA) using sectoral accounts and newly available data from the Household Finance and Consumption Survey. The EA\ as a whole is a net winner of unexpected price level increases, with...

We study adaptive learning in a monetary overlapping generations model with sticky prices and monopolistic competition for the case where learning agents observe current endogenous variables. Observability of current variables is essential for informational consistency of the learning setup with...

We study optimal nominal demand policy in an economy with monopolistic competition and flexible prices when firms have imperfect common knowledge about the shocks hitting the economy. Parametrizing firms' information imperfections by a (Shannon) capacity parameter that constrains the amount of...

This paper considers a sticky price model with a cash-in-advance constraint where agents forecast inflation rates with the help of econometric models. Agents use least squares learning to estimate two competing models of which one is consistent with rational expectations once learning is...

We determine optimal monetary policy under commitment in a forwardlooking New Keynesian model when nominal interest rates are bounded below by zero. The lower bound represents an occasionally binding constraint that causes the model and optimal policy to be nonlinear. A calibration to the U.S....

This paper compares Bayesian decision theory with robust decision theory where the decision maker optimizes with respect to the worst state realization. For a class of robust decision problems there exists a sequence of Bayesian decision problems whose solution converges towards the robust...

Ignoring the existence of the zero lower bound on nominal interest rates one considerably understates the value of monetary commitment in New Keynesian models. A stochastic forward-looking model with lower bound, calibrated to the U.S. economy, suggests that low values for the natural rate of...