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Learning Monetary Policy Strategies at the Effective Lower Bound with Sudden Surprises
Central banks around the world have revised their operating frameworks in an attempt to counter the challenges presented by the effective lower bound (ELB) on policy rates. We examine how private sector agents might learn such a new regime and the effect of future shocks on that process. In our model agents use Bayesian updating to learn the parameters of an asymmetric average inflation targeting rule that is adopted while at the ELB. Little can be discovered until the economy improves enough that rates would be near liftoff under the old policy regime; learning then proceeds until either the ...