Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/46270
Authors: 
Altavilla, Carlo
Ciccarelli, Matteo
Year of Publication: 
2011
Series/Report no.: 
CESifo working paper: Monetary Policy and International Finance 3372
Abstract: 
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 releases. Using standard forecasting and policy models to analyze monetary authorities' reaction functions, we show that this simple method can improve forecasting performance and provide reliable estimates of the policy model coefficients associated with small central bank losses, in particular during periods of high macroeconomic uncertainty.
Subjects: 
monetary policy
Taylor rule
real-time data
great moderation
forecasting
JEL: 
E52
E58
C32
C53
C82
Document Type: 
Working Paper

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