Keywords: Optimal monetary policy, parameter uncertainty, loss-function uncertainty, inertial interest rate policy.
Abstract: In this paper, we structurally model uncertainty with a micro-founded model, and investigate
its implications for optimal monetary policy. Uncertainty about deep parameters of the model
implies that the central bank simultaneously faces both uncertainty about the structural
dynamic equations and about the social loss function. Considering both uncertainties with
cross-parameter restrictions based on the micro-foundations of the model, we use Bayesian
methods to determine the optimal monetary policy that minimizes the expected loss. Our
analysis shows how uncertainty can lead the central bank to pursue a more aggressive
monetary policy, overturning Brainard's common wisdom. As the degree of uncertainty
about inflation dynamics increases, the central bank should place much more weight
on price stability, and should respond to shocks more aggressively. In addition, when
the central bank is uncertain about output dynamics, an aggressive policy response can
be justified by the positive correlation between policy multiplier and transmission of
natural rate of interest shock as well as the effect of loss-function uncertainty. We
also show that combining a more aggressive policy response with a highly inertial interest
rate policy reduces Bayesian risk.
Full paper (869 KB PDF)
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Last update: January 20, 2004