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In recent years, simple policy rules have received attention as a means to a more transparent and effective monetary policy. Often, however, the analysis is based on unrealistic assumptions about the timeliness of data availability. This permits rule specifications that are not operational and ignore difficulties associated with data revisions. This paper examines the magnitude of these informational problems using Taylor's rule as an example. First, I construct a database of current quarter estimates/forecasts of the quantities required by the rule based only on information available in real time. Using this data I reconstruct the policy recommendations which would have been obtained in real time. I demonstrate that the real-time policy recommendations differ considerably from those obtained with the ex post revised data. Within-year revisions in the policy recommendations are also quite large with a standard deviation exceeding that of the quarterly change of the federal funds rate. Further, I show that estimated policy reaction functions obtained using the ex post revised data can yield misleading descriptions of historical policy. Using Federal Reserve sta forecasts I show that in the 1987-1992 period simple forward-looking specifications describe policy better than comparable Taylor-type specifications, a fact that is largely obscured when the analysis is based on the ex post revised data.

Policy rules that are consistent with ination targeting are examined in a small macroeconometric model of the US economy. We compare the properties and outcomes of explicit instrument rules as well as targeting rules. The latter, which imply implicit instrument rules, may be closer to actual operating procedures of inflation-targeting central banks. We find that ination forecasts are central for good policy rules under inflation targeting. Some simple instrument and targeting rules do remarkably well relative to the optimal rule; others, including some that are often used as representing inflation targeting, do less well.

The purpose of this paper is to survey and discuss inflation targeting in the context of monetary policy rules, to clarify the essential characteristics of in‡ation targeting, to compare inflation targeting to other monetary policy rules, and to draw some conclusions for the monetary policy of

The central puzzle in international business cycles is that real exchange rates are volatile and persistent. The most popular story for real exchange rate fluctuations is that they are generated by monetary shocks interacting with sticky goods prices. We quantify this story and find that it can account for some of the observed properties of real exchange rates. When prices are held fixed for at least one year, risk aversion is high and preferences are separable in leisure, the model generates real exchange rates that are as volatile as in the data. The model also generates real exchange rates that are persistent, but less so than in the data. If monetary shocks are correlated across countries, then the comovements in aggregates across countries are broadly consistent with those in the data. Making asset markets incomplete or introducing sticky wages does not measurably change the results.

Numerous studies have used quarterly data to estimate monetary policy rules or reaction functions that appear to exhibit a very slow partial adjustment of the policy interest rate. The conventional wisdom asserts that this gradual adjustment reflects a policy inertia or interest rate smoothing behavior by central banks. However, such quarterly monetary policy inertia would imply a large amount of forecastable variation in interest rates at horizons of more than three months, which is contradicted by evidence from the term structure of interest rates. The illusion of monetary policy inertia evident in the estimated policy rules likely reflects the persistent shocks that central banks face.

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Because asset prices are forward-looking, they constitute a class of potentially useful predictors of inflation and output growth. The premise that interest rates and asset

The New-Keynesian Phillips curve has recently become an important ingredient in mon-etary policy models. However, using limited information methods, the empirical support for the New-Keynesian Phillips curve appear to be mixed. This paper argues, by means of Monte Carlo simulations with a simple New-Keynesian sticky price model, that single equations methods, e.g. GMM, are likely to produce imprecise and biased estimates. Then, it is ar-gued that estimating the model with full information maximum likelihood (FIML) is a useful way of obtaining better estimates. Finally, a version of the model used in the Monte Carlo simulations is estimated on U.S. data with FIML and although the pure forward-looking New-Keynesian Phillips curve is rejected, a version with both forward- and backward-looking components provides a reasonable approximation of U.S. inflation dynamics.