Aiming for the Bull's Eye: Uncertainty and Inertia in Monetary Policy
Maria Demertzis and
Nicola Viegi ()
No 150, Computing in Economics and Finance 2006 from Society for Computational Economics
We study the implications of uncertainty for inflation targeting. We apply multiplicative uncertainty to a standard forward looking model and demonstrate Brainard's attenuation effect. But the result as monetary authorities become naturally more cautious at the same time 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. To do that, we assume that private sector expectations are subject to differentiated information, thereby introducing inertia in the system. 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. 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; Brainard Uncertainty; Two-Step Target; Differential Information (search for similar items in EconPapers)
JEL-codes: E42 E52 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:sce:scecfa:150
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