Uncertainty is a central issue in monetary policy, as the quote from Alan Greenspan above illustrates. Empirical models, however, rarely take account of this, effectively assuming that policymakers ignore uncertainty. The evident focus of policymakers on uncertainty suggests that this assumption is invalid and therefore that empirical models of monetary policy must account for uncertainty. This article considers the effects of uncertainty about the true state of the economy on monetary policy, estimating a monetary policy rule that allows for this.

Our empirical model combines elements of Svensson’s (1997) model of inflation forecast targeting with models drawn from the theoretical literature on optimal monetary policy when there is uncertainty about the true state of the economy, most prominently Svensson and Woodford (2003, 2004) and Swanson (2004). In existing models of monetary policy under certainty, monetary policy affects inflation and the output gap directly, so it is optimal for policymakers to use these variables in forming monetary policy. This is the basis for the Taylor rule (Taylor 1993) model of monetary policy and its subsequent refinements (e.g., Woodford 2003).

Following the literature on monetary policy under uncertainty, our model assumes instead that monetary policy affects the state of the economy, which in turn affects inflation and the output gap. The optimal monetary policy rule is then a certainty equivalent function of the state of the economy. However, the state of the economy is unobserved, so policymakers must infer this from observations of inflation and the output gap. These latter variables therefore act as indicator variables for monetary policy. The optimal predictor of the true state of the economy is a linear function of inflation and the output gap whose parameters are functions of the variances of these variables, which we assume to be time varying.

The resultant empirical model resembles the familiar Taylor rule but where the coefficients on inflation and the output gap are functions of the variances of these variables. An increase in, for example, the variance of inflation reduces the parameter on inflation and increases the parameter on the output gap in the equation for the expected state of the economy. This leads to a smaller weight on inflation and a larger weight on the output gap in the monetary policy rule. Similarly, an increase in the variance of the output gap reduces the weight on the output gap and increases the weight on inflation in the equation for the expected state of the economy, resulting in a lower weight on the output gap and a corresponding larger weight on inflation. As a result, the model makes two main testable predictions. First, policymakers should respond less vigorously to variables that are more uncertain, so the weight on inflation in the policy rule should be lower when inflation is more uncertain and similarly for the output gap (Peersman and Smets 1999; Rudebusch 2001; Smets 2002; Soderstrom 2002; Srour 2003; Swanson 2004; Walsh 2004). Second, uncertainty about one variable may strengthen the response to the other variable, so the weight on the output gap may be larger when inflation is less certain and vice versa (cf. Peersman and Smets 1999; Swanson 2004). (1)

We estimate a system of equations, comprising a monetary policy rule whose parameters are functions of the variances of inflation and the output gap and equations for inflation and the output gap whose error terms have GARCH processes, from which these variances are derived. We use data since 1983 since this is when the Federal Reserve Bank (Fed) switched to using the interest rate as the tool of monetary policy and since continuity in monetary policy objectives has allowed stable policy rules to be estimated over this period (e.g., Judd and Rudebusch 1998). We find that the behavior of monetary policymakers is consistent with the predictions of the theoretical literature. Monetary policy responds less to inflation and the output gap when these variables are more uncertain. We also find that the response to inflation is stronger when the output gap is more uncertain and vice versa. We quantify the impact of uncertainty by constructing a measure of the counterfactual interest rate, which would have been observed if there had been no uncertainty. We find that the impact of uncertainty was most marked in 1983, when uncertainty increased interest rates by up to 140 basis points, in 1990-1991, when uncertainty reduced interest rates by up to 80 basis points, and in 1996-2001, when uncertainty reduced interest rates by up to 70 basis points over 5 yr.

1. Open Market Operations
2. Discount Rates
3. Reserve Requirements

Since open market operations is the tool used most, we will cover it. Here’s how it works: When the economy is growing too fast and the Fed is worried about the inflation rate, it will sell government securities from its portfolio to the open market. This decreases bank reserves, which means the money supply decreases. When there are less bank and businesses have to pay the bank more in order to borrow. This discourages consumers and businesses from borrowing. Less borrowing means less spending, which slows the economy and eventually can reduce price pressures.

When the economy is growing too slowly and the inflation rate is low the Fed will buy government securities, such as Treasury bills and notes. This increases bank reserves, which increases the money supply and causes short-term interest rates to decrease. Reduced rates induce consumers and businesses to borrow. Consumers will borrow money for items such as automobiles or home loans. Businesses borrow to build their inventories or finance a new factory. As a result, economic growth will accelerate.

The Fed will also leave rates unchanged if the economy is growing at a moderate pace with low inflation or if they feel the economy will slow down by itself. They will even take a wait-and-see approach with regard to how slowly the economy is growing and the rate of inflation, before determining monetary policy.

The bond market plays close attention to the activities of the Federal Reserve, which is why it’s important for us as well.

The Federal Reserve has three goals:

1. Moderate economic growth (not too fast, not too slow)
2. Low unemployment
3. Low inflation

How does the Fed determine whether they are reaching these goals? They watch the same economic indicators as we do. In other words, they monitor the reports that are released by the Labor Department, the segments of our economy.

For instance, the Gross Domestic Product (GDP) consists of four major components: (1) consumption; (2) investment; (3) government; (4) exports. Most of the key economic indicators fall into one of the above categories. For example:

• Retail sales would fall under consumption.
• Business inventories and housing starts would fall under investment.
• Construction Spending would fall under government.
• Trade would fall under exports.

If the key economic indicators continue to come in strong, the GDP will increase. If the indicators come in weak, it will decrease. In other words, Gross Domestic Product measures economic growth.

John Taylor’s rule for setting interest rates provides a framework for studying the global monetary policy generated by individual countries pursing their own policy goals. The study reflects the global nature of monetary policy by modeling an aggregate short-term interest rate as a function of measures of worldwide inflation and the GDP gap. Multiple specifications are estimated to correspond to past studies of the U.S. relationships between these variables. The authors find that Taylor rule is a useful tool for characterizing the global monetary environment as his equation provides a good fit to the data in every specification explored by the authors. However, the international response to inflation is slightly less robust despite claims of inflation targeting by the bulk of the larger economies in the sample. (JEL F33)

Introduction

As each country pursues its monetary agenda, what is the nature of the resulting global monetary policy? Applying John Taylor’s rule for setting interest rates helps to answer this critical policy question. The “Taylor Rule” presents the Federal funds rate as a simple linear function of the inflation rate and the GDP gap [Taylor, 1993]. Researchers have taken his simple rule, which prescribes policy, and used multiple regression techniques to estimate what weights the monetary authorities actually use in setting interest rates. They find that the rule’s recommendations have come very close to the actual policies pursued by the Fed in the recent past [Taylor, 1993; Judd and Rudebusch, 1998]. Earlier monetary regimes followed far different paths [Spencer and Huston, 2002].

The formulation of monetary policy has become increasingly complicated. The relaxation of restrictions on the flow of money among countries has made the monetary policies of individual countries more interdependent. Thus, the three variables in Taylor’s Rule are now less under the control of individual countries. For example, when capital flows are unfettered, interest rates around the world tend to move together [van der Ploeg, 1995]. As a result, efforts to unilaterally change U.S. policy rates become more difficult. Inflation, too, can be a shared experience as monetary expansion in one country spills over into other countries [Hamada, 1985]. (1) The GDP gap is also affected by the policies of other countries. For example, U.S. monetary policy clearly affects the GDP gaps of its major trading partners.

The study presented here reflects the global nature of monetary policy by modeling an aggregate short-term interest rate as a function of measures of worldwide inflation and the GDP gap. The results facilitate judgments about the implicit monetary policies of the world. That is, as each country pursues its own monetary agenda, what is the nature of the aggregate monetary policy that is produced? This is a critical question for monetary policy making. Since a country’s actions have spillover effects for other countries, it is not clear that uncoordinated monetary policies produce optimal worldwide results.

Replicating U.S. studies at the international level demonstrates that the Taylor Rule is a useful tool for characterizing the global monetary environment as his equation provides a good fit to the data in those specifications explored by the authors. At the world level, however, the aggregate of central banks reacts less to inflation than does the Federal Reserve. The inflation target may have become more important to central banks, in total, in the 1990s but the evidence is not strong.