This paper provides a general strategy for analyzing monetary policy in real time which accounts for data uncertainty without explicitly modelling the revision process. The strategy makes use of all the data available from a real-time data matrix and averages model estimates across all data...

I propose a methodology for estimating forward-looking Taylor rules in real time when forward-looking real-time central bank data is unavailable. The methodology consists of choosing appropriate models to closely replicate U.S. Greenbook forecasts, and then applying these models to Canada,...

This article compares two types of monetary policy rules - the Taylor-Rule and the Orphanides-Rule - with respect to their forecasting properties for the policy rates of the European Central Bank. In this respect the basic rules, results from estimated models and augmented rules are compared....

This article compares two types of monetary policy rules - the Taylor-Rule and the Orphanides-Rule - with respect to their forecasting properties for the policy rates of the European Central Bank. In this respect the basic rules, results from estimated models and augmented rules are compared....

The prominent role of monetary policy in the U.S. interwar depression has been conventional wisdom since Friedman and Schwartz [1963]. This paper presents evidence on both the surprise and the systematic components of monetary policy between 1929 and 1933. Doubts surrounding GDP estimates for...

The Taylor rule has become the dominant model for academic evaluation of out-of-sample exchange rate predictability. Two versions of the Taylor rule model are the Taylor rule fundamentals model, where the variables that enter the Taylor rule are used to forecast exchange rate changes, and the...

Sign-restricted Structural Vector Autoregressions (SVARs) are increasingly common. However, they usually result in a set of structural parameters that have very different implications in terms of impulse responses, elasticities, historical decomposition and forecast error variance decomposition...