Optimal Disinflation Under Learning

We model transitional dynamics that emerge after the adoption of a new monetary-policy rule. We assume that private agents learn about the new policy via Bayesian updating, and we study how learning affects the nature of the transition and choice of a new rule. The model endogenously generates time-varying volatility during the transition. Managing this volatility is the central bank's main challenge. The optimal policy depends on subtle features of the private sector's prior. Nevertheless, two robust conclusions emerge from our examples. First, the central bank can adjust target inflation freely without triggering high volatility. Second, none of our examples rationalizes a gradual reduction in inflation. On the contrary, inflation falls sharply at impact, overshoots the new target, and converges from below.