This paper develops an adaptive learning formulation of an extension to the Ball, Mankiw, and Reis (2005) sticky information model that incorporates endogenous inattention. We show that, following an exogenous increase in the policymaker’s preferences for price vs. output stability, the...

This paper addresses the output-price volatility puzzle by studying the interaction of optimal monetary policy and agents' beliefs. We assume that agents choose their information acquisition rate by minimizing a loss function that depends on expected forecast errors and information costs....

The development of tractable forward looking models of monetary policy has lead to an explosion of research on the implications of adopting Taylor-type interest rate rules. Indeterminacies have been found to arise for some specifications of the interest rate rule, raising the possibility of...

This paper develops an adaptive learning formulation of an extension to the Ball, Mankiw and Reis (2005) sticky information model that incorporates endogenous inattention. We show that, following an exogenous increase in the policymaker's preferences for price vs. output stability, the learning...

By endowing his agents with simple forecasting models, or <italic>representations</italic>, M. Woodford (“Learning to Believe in Sunspots,” <italic>Econometrica</italic> 58, 277–307, 1990) found that finite state Markov sunspot equilibria may be stable under learning. We show that common factor representations generalize...

Incorporating adaptive learning into macroeconomics requires assumptions about how agents incorporate their forecasts into their decision-making. We develop a theory of bounded rationality that we call finite-horizon learning. This approach generalizes the two existing benchmarks in the...

We reexamine issues of coordination in the standard RBC model. Is the unique rational expectations equilibrium attainable by rational agents who contemplate the possibility of small deviations from equilibrium? Surprisingly, we find that coordination cannot be expected. Even with strong common...

Incorporating adaptive learning into macroeconomics requires assumptions about how agents incorporate their forecasts into their decision-making. We develop a theory of bounded rationality that we call finite-horizon learning. This approach generalizes the two existing benchmarks in the...