Output gap estimates at the current edge are subject to severe revisions. This study analyzes whether monetary aggregates can be used to improve the reliability of early output gap estimates as proposed by several theoretical models. A real-time experiment shows that real M1 can improve output...

Recent work on policy rules under uncertainty have highlighted the impact of output gap measurement errors on economic outcomes and their importance in the formulation of appropriate policy rules. This paper investigates the reliability of current estimates of the output gap in Canada. We begin...

Estimates of the output gap are an important component of policy-makers’ toolkits. Both the theory underlying monetary policy analysis and the empirical models employed by central banks suggest that the output gap is a key variable explaining inflation. In this view, the estimate of the...

Papers estimating the reaction function of the Bundesbank generally find that its monetary policy from the 1970s to 1998 can well be captured by a standard Taylor rule according to which the central bank responds to the output gap and to deviations of inflation from target, but not to monetary...

National accounts data are always revised. Not only recent data, but also figures dating many years back can be revised substantially. This means that there is a danger that an important part of the central bank's information set is flawed for a long period of time. In this paper we present a...

Estimations of simple monetary policy rules are often very rigid. Standard practice requires that a decision is made as to which indicators the central bank is assumed to respond to, ignoring the data-rich environment in which policy-makers typically form their decisions. However, the choice of...

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...

We find that macroeconomic uncertainty plays a significant role in U.S. monetary policy. First, we construct a measure of uncertainty as felt by policymakers at the time of making their rate-setting decisions. This measure is derived from a real-time, Bayesian estimation of a small monetary VAR...

In this paper we use U.S. real-time vintage data and produce combined density nowcasts for quarterly GDP growth from a system of three commonly used model classes. The density nowcasts are combined in two steps. First, a wide selection of individual models within each model class are combined...

In this paper we describe Norges Bank's system for averaging models (SAM) which produces model-based density forecasts for Norwegian Mainland GDP and inflation. We combine the forecasts from three main types of models typically used at central banks: Vector autoregressive models, leading...