Monetary policy in a model with misspecified, heterogeneous and ever-changing expectations

The applied literature on adaptive learning has mostly focused on small, linear models, with homogenous expectations. In non-linear models heterogeneous expectations prevail and the process through which agents select (and change) a forecasting model becomes a necessary ingredient of the analysis; moreover, the temporary equilibrium of the learning process approaches an asymptotic limit that may be affected by the communication strategies of the monetary policymaker. The objective of this paper is to assess whether in such a model economy the optimal monetary policy exhibits properties that are similar to those found in the literature for small, linear models. The main results are the following: (1) expectations heterogeneity is an intrinsic feature of the economy: no PLM succeeds in ruling out all the other forecasting models; (2) contrary to previous findings, the monetary policymaker has no incentive to adopt highly inflation-averse policies: too strong a reaction to price shocks increases both inflation and output volatility; (3) partial transparency seems to enhance somewhat welfare (but fully transparent policies do not); (4) a higher degree of transparency calls for stronger inflation aversion.