We examine global economic dynamics under learning in a New Keynesian model in which the interest-rate rule is subject to the zero lower bound. Under normal monetary and fiscal policy, the intended steady state is locally but not globally stable. Large pessimistic shocks to expectations can lead to deflationary spirals with falling prices and falling output. To avoid this outcome we recommend augmenting normal policies with aggressive monetary and fiscal policy that guarantee a lower bound on inflation. In contrast, policies geared toward ensuring an output lower bound are insufficient for avoiding deflationary spirals.

The bounded rationality literature has studied heterogeneous learning rules under models with a single equilibrium. This paper examines learning with heterogeneous expectations in a simple macroeconomic model with multiple equilibria. Stability properties of this model are determined by the distribution of heterogeneity. These results differ greatly from those which impose homogenous expectations a priori. When the level of heterogeneity is allowed to vary, stability conditions become more restrictive due to the stationarity requirements of the simpler, more parsimonious updating rule. Finally, I find that the two equilibria exchange stability when the MSE of using this simpler updating rule is minimized.

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This paper explores the equilibrium properties of boundedly rational heterogeneous agents under adaptive learning. In a modified cobweb model with a Stackelberg framework, there is an asymmetric information diffusion process from leading to following firms. It turns out that the conditions for at least one learnable equilibrium are similar to those under homogeneous expectations. However, the introduction of information diffusion leads to the possibility of multiple equilibria and can expand the parameter space of potential learnable equilibria. In addition, the inability to correctly interpret expectations will cause a “boomerang effect” on the forecasts and forecast efficiency of the leading firms. The leading firms' mean square forecast error can be larger than that of following firms if the proportion of following firms is sufficiently large.

This paper introduces a general method to study learnability of equilibria resulting from agents using misspecified forecasting models. One can represent the actual and perceived laws of motion (PLM) as seemingly unrelated regressions and then linearly project the actual law of motion into the same class as the PLM. I present an application using the New Keynesian IS-AS model with inertia under several simple Taylor policy rules. It turns out that the results presented in Bullard and Mitra [2002. Learning about monetary policy rules. Journal of Monetary Economics 49, 1105-1129; 2005. Determinacy, Learnability, and Monetary Policy Inertia. Journal of Money, Credit, and Banking, forthcoming] are robust when agents do not include all the state variables in their forecasting models. r 2007 Elsevier B.V. All rights reserved. JEL classification: E4; E5