Magazine article Business Review (Federal Reserve Bank of Philadelphia)

Designing Monetary Policy Rules in an Uncertain Economic Environment

Magazine article Business Review (Federal Reserve Bank of Philadelphia)

Designing Monetary Policy Rules in an Uncertain Economic Environment

Article excerpt

A well-designed monetary policy can help the economy respond efficiently to economic disturbances by limiting the deviation of economic activity from its potential while keeping inflation close to its desired rate. But successful implementation of such strategies must confront significant challenges arising from various forms of economic uncertainty. This article discusses the design of monetary policy rules in an environment in which policymakers face two distinct forms of uncertainty. The first involves the uncertainty surrounding the precise values of key policy variables that often appear as determinants in such rules. These variables are typically measures of resource utilization relative to some concept of potential. This data uncertainty can arise because the relevant conceptual definition of potential may be uncertain and even if it is clearly defined, it may not be observable and thus measurement error becomes an important consideration. The second form of uncertainty we refer to is learning uncertainty, which arises when people have only an incomplete knowledge of the economy itself

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Regarding the first source of uncertainty, it is well documented that the key policy variables mentioned above are measured with considerable error. Thus, the true value of these variables is uncertain at the time policy is made. With respect to the second source of uncertainty, we believe that most people do not possess complete knowledge of the economy and that their behavior is characterized by a continual learning process in which their views about the economy evolve over time. Policymakers must recognize these uncertainties when designing policy. Throughout our discussion, we take as given the desirability of rule-like behavior for policy. (1) It is widely accepted in the economics profession that rule-like behavior is preferable to discretion because more desirable economic outcomes can be obtained with commitment. (2) We will also concentrate on the conduct of monetary policy in normal times and will, therefore, not address the special problems brought about by the zero lower bound on nominal interest rates. (3)

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The basic conclusion from the literature is that when policymakers are trying to achieve the best outcomes in terms of economic welfare, these types of uncertainty make it desirable for the central bank to respond relatively aggressively to deviations of inflation from target and to rely less on measured deviations of either output or unemployment from their natural or potential values. Rather, the central bank should also respond to economic growth irrespective of where economic activity is with regard to potential or trend. (4)

USEFULNESS OF INTERESTS ATE RULES

In analyzing the design of beneficial ways in which to conduct monetary policy under uncertainty, we will concentrate on the use of an interest-rate rule. The types of rules we will discuss are fairly simple ones and ones chat have been shown to be useful for policymaking. These rules are generally designed to stabilize some measure of economic activity and inflation, because doing so leads to more efficient economic performance. Simple interest-rate rules tend to perform well in many different economic models, a fact that suggests they can be useful in practice. Thus, it is no accident that the behavior of most central banks in developed economies can be reasonably approximated by a simple interest-rate rule. (5)

However, the formulation of monetary policy rules must take into account the uncertainty that policymakers face, since rules designed under the assumption of no uncertainty are often disastrous when one explicitly considers uncertainty. In particular, a rule may, in theory, perform quite well when data are measured accurately but be quite bad when data are subject to severe measurement errors. Also, rules that work well under the assumption that individuals fully understand their economic environment may not do so well when individuals are constantly learning about economic circumstances. …

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