Abstract: Monetary policy is modeled as governed by a known rule, except for a
time-varying target rate of inflation. The variable target is taken as
representing either discretionary deviations from the rule, or as the
outcome of a policymaking committee that is unable to arrive at a
consensus. Stochastic simulations of FRB/US, the Board of Governors'
large, rational-expectations model of the U.S. economy, are used to
examine the benefits of reducing the variability in the target rate of
inflation. We find that putting credible boundaries on target
variability introduces an important non-linearity in expectations.
This improves policy performance by focusing agents' expectations on
policy objectives. But improvements are limited; it does not generally
pay to reduce target variability to zero. The non-linearity in
expectations can be used to conduct a policy with greater attention to
output stabilization than otherwise. The results provide insights as
to why inflation-targeting countries use bands and why the bands are
narrower than studies suggest they should be. Also, a numerical
technique that approximates to arbitrary precision a non-linear
process with a linear method is also demonstrated. This greatly speeds
the simulations and makes them more robust.
Keywords: Monetary policy, inflation targeting, macroeconomic modeling, computational methods
Full paper (128 KB PDF)
| Full paper (453 KB Postscript)
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