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Principal components at work: the empirical analysis of monetary policy with large data sets
Author(s) -
Favero Carlo A.,
Marcellino Massimiliano,
Neglia Francesca
Publication year - 2005
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.815
Subject(s) - monetary policy , inflation (cosmology) , principal component analysis , dynamic factor , economics , econometrics , principal (computer security) , factor analysis , econometric analysis , econometric model , work (physics) , macroeconomics , computer science , mechanical engineering , physics , artificial intelligence , theoretical physics , engineering , operating system
The empirical analysis of monetary policy requires the construction of instruments for future expected inflation. Dynamic factor models have been applied rather successfully to inflation forecasting. In fact, two competing methods have recently been developed to estimate large‐scale dynamic factor models based, respectively, on static and dynamic principal components. This paper combines the econometric literature on dynamic principal components and the empirical analysis of monetary policy. We assess the two competing methods for extracting factors on the basis of their success in instrumenting future expected inflation in the empirical analysis of monetary policy. We use two large data sets of macroeconomic variables for the USA and for the Euro area. Our results show that estimated factors do provide a useful parsimonious summary of the information used in designing monetary policy. Copyright © 2005 John Wiley & Sons, Ltd.