Aiming for the Bull's Eye: Inflation Targeting Under Uncertainty

Abstract

We study the implications of uncertainty for inflation targeting. We apply Brainard's static framework which assumes multiplicative uncertainty in the monetary transmission. Brainard's main result is that in the presence of uncertainty, monetary authorities become naturally more cautious. But this also implies that monetary objectives are seldom achieved. We therefore attempt to find a monetary rule that reaches the objectives set more often and improves the welfare of the Central Bank. Such a rule is the result of a new algorithm that we put forward, in which the inflation target is state contingent. The Central Bank sets therefore (as an auxiliary step), a variable inflation target that depends on both the degree of uncertainty as well as the shocks that occur each time. If the benefits of reaching the inflation target are properly accounted for in the loss function, we show that such an optimisation procedure helps the CB attain its objectives more often, thereby reducing the losses incurred. Moreover, and as a corollary to such an approach, the rule derived is ex ante neutral to the degree of uncertainty.

Keywords: Inflation Targeting, Parameter Uncertainty, Brainard, Two-step targeting

JEL Classification: E42, E52