We study the classic implementation problem under the behavioral assumption that agents myopically adjust their actions in the direction of better-responses within a given institution. We offer results both under complete and incomplete information. First, we show that a necessary condition for...

We study the classic implementation problem under the behavioral assumption that agents myopically adjust their actions in the direction of better-responses within a given institution. We offer results both under complete and incomplete information. First, we show that a necessary condition for...

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...

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....

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...

Many models of monetary policy predict a trade-off between inflation and output variance despite compelling evidence that the Federal Reserve has become more aggressive in fighting inflation and there has been a resulting decline in both inflation and output variance. We address this apparent...