Optimal Monetary Policy under Adaptive Learning

This work discusses the issue of optimal monetary policy when there is no assumption of full rationality of private agents when forming their expectations about future macroeconomic variables. In particular, the question is about the optimality of constrained discretionary policy under adaptive learning. One of such policies is the popular nowadays inflation targeting, the relevance of which under adaptive learning is still not confirmed by theoretical models. This work also considers the problem of optimal inflation targeting horizon. Adaptive learning transforms the mechanism of building private expectations that can be a reason of the changing of targeting horizon by Central Banks in practice. The main result of this research is the optimality of inflation targeting as constrained discretionary policy when the adaptivity in private agents’ expectations takes place. In addition, this work demonstrates theoretical reasons of the gradual shorting of targeting horizon by the Central Bank during the learning of private agents.