RDP 1999-10: The Implications of Uncertainty for Monetary Policy 1. Introduction

Monetary authorities aim to achieve low and stable inflation while keeping output at capacity. To achieve these goals they manipulate the policy instrument which has an effect on economic activity and prices through one or more transmission mechanisms. Monetary authorities face many difficulties in achieving these goals. The current state of the economy, for example, is not known with certainty. Moreover, the responses of the economy to demand and supply shocks are difficult to quantify and new shocks are arriving all the time. As if these problems are not enough, the transmission channels from the policy instrument to the objectives are complex and imprecisely estimated.

Economic models are useful tools for helping to deal with these uncertainties. By abstracting from less important uncertainties, models provide a framework within which the workings of the economy can be quantified. In doing so, models generally reduce the complexity of the policy decision-making process and go some way towards helping monetary authorities achieve their goals. However, to the extent that models are only an approximation to the ‘true’ economy, there will always be uncertainty about the correct structure and parameters of an economic model.

Blinder (1995), commenting in his capacity as a central banker, observed that model uncertainty can have important implications for policy. In particular, uncertainty about the model may make monetary authorities more conservative in the sense that they determine the appropriate policy response ignoring uncertainty, ‘and then do less’. This conservative approach to policy was first formalised by Brainard (1967). Although Blinder views the Brainard conservatism principle ‘as extremely wise’, he admits that the result is not robust. For practical purposes, this recommendation leaves two questions unanswered. First, how much should policy be adjusted to account for model uncertainty? Second, is conservatism always the appropriate response?

This paper addresses both of these questions by generalising the Brainard model to a multi-period horizon and a multivariate model. A small data-consistent model of the Australian economy is used to illustrate the effect of parameter uncertainty on policy responses. Contrary to Brainard's conservatism result, we show that parameter uncertainty can actually induce greater policy activism following most types of shocks. We argue that this increased activism is primarily a consequence of uncertainty about the persistence of shocks to the economy. This type of uncertainty cannot be incorporated into the static model of Brainard.

The remainder of the paper is structured as follows. In Section 2, we discuss the various sources of forecasting error which lie behind model uncertainty. Section 3 summarises the specification of a small macroeconomic model used in the remainder of the paper. Section 4 shows how sensitive policy responses are to changes in the parameter values when the policy-maker ignores this parameter uncertainty. Section 5 demonstrates how parameter uncertainty can be accommodated in the solution to a monetary authority's optimal policy problem and Section 6 illustrates the difference between naive policy, that ignores parameter uncertainty, and policy that explicitly takes parameter uncertainty into account. Section 7 concludes and summarises the practical implications for monetary policy.