 Principal components at work: The empirical analysis of monetary policy with large datasetsCarlo Favero (), Massimiliano Marcellino and Francesca Neglia No 223, Working Papers from IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University Abstract: Two competing methods have been recently developed to estimate large-scale dynamic factor models based, respectively, on static and dynamic principal components. In this paper we use two large datasets of macroeconomic variables for the US and for the Euro area to evaluate in practice the relative performance of the two approaches to factor model estimation. The comparison is based both on the relative goodness of fit of the models, and on the usefulness of the factors when used in the estimation of forward looking Taylor rules, and as additional regressors in monetary VARs. It turns out that dynamic principal components provide a more parsimonious summary of the information, but the overall performance of the two methods is very similar, in particular when a common information set is adopted. Moreover, the information extracted from the large datasets turns out to be quite useful for the empirical analysis of monetary policy. New Economics Papers: this item is included in nep-cba, nep-fin and nep-mon Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:igi:igierp:223 Ordering information: This working paper can be ordered from Access Statistics for this paper More papers in Working Papers from IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University via Rontgen, 1 - 20136 Milano (Italy). |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.