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Large Datasets, Small Models and Monetary Policy in Europe

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  • Favero, Carlo A
  • Marcellino, Massimiliano

Abstract

Nowadays a considerable amount of information on the behaviour of the economy is readily available, in the form of large datasets of macroeconomic variables. Central bankers can be expected to base their decisions on this very large information set. Yet the academic profession has shown a clear preference for using small models to highlight stylized facts and to implement policy simulation exercises. Omitted information is then a potentially relevant problem. Recent time-series techniques for the analysis of large datasets have shown how vast an amount of information can be captured by few factors. In this paper we combine factors extracted from large datasets with more traditional small-scale models to analyse monetary policy in Europe. In particular, we model hundreds of macroeconomic variables with a dynamic factor model, and summarize their informational content with a few estimated factors. These factors are then used as instruments in the estimation of forward-looking Taylor rules, and as additional regressors in structural VARs. The latter are then used to evaluate the effects of unexpected and systematic monetary policy.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 3098.

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Date of creation: Dec 2001
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Handle: RePEc:cpr:ceprdp:3098

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Keywords: dynamic factors; monetary policy; small models;

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Cited by:
  1. Reichlin, Lucrezia, 2002. "Factor Models in Large Cross-Sections of Time Series," CEPR Discussion Papers 3285, C.E.P.R. Discussion Papers.
  2. Giannone, Domenico & Reichlin, Lucrezia & Sala, Luca, 2002. "Tracking Greenspan: Systematic and Unsystematic Monetary Policy Revisited," CEPR Discussion Papers 3550, C.E.P.R. Discussion Papers.
  3. Hilde C. Bjørnland, 2005. "Monetary policy and the illusionary exchange rate puzzle," Working Paper 2005/11, Norges Bank.
  4. Marcellino, Massimiliano, 2006. "Some stylized facts on non-systematic fiscal policy in the Euro area," Journal of Macroeconomics, Elsevier, vol. 28(3), pages 461-479, September.
  5. Marcellino, Massimiliano, 2002. "Forecasting EMU Macroeconomic Variables," CEPR Discussion Papers 3529, C.E.P.R. Discussion Papers.
  6. Francesco Daveri & Andrea Mascotto, . "The IT revolution across the U.S. states," Working Papers 226, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  7. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
  8. Carlo Ambrogio Favero & Massimilano Marcellino & Francesca Neglia, . "Principal components at work: The empirical analysis of monetary policy with large datasets," Working Papers 223, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  9. Fabio Bagliano & Claudio Morana, 2008. "Factor vector autoregressive estimation: a new approach," Journal of Economic Interaction and Coordination, Springer, vol. 3(1), pages 15-23, June.
  10. Bjørnland, Hilde C., 2005. "Monetary policy and exchange rate interactions in a small open economy," Memorandum 31/2005, Oslo University, Department of Economics.
  11. Fabio C. Bagliano & Claudio Morana, 2006. "A New Approach to Factor Vector Autoregressive Estimation with an Application to Large-Scale Macroeconometric Modelling," Carlo Alberto Notebooks 28, Collegio Carlo Alberto.
  12. Mark J. Holmes & Arthur Grimes, 2005. "Is there long-run convergence of regional house prices in the UK?," Working Papers 05_11, Motu Economic and Public Policy Research.
  13. Francesco Belviso & Fabio Milani, 2005. "Structural Factor-Augmented VAR (SFAVAR) and the Effects of Monetary Policy," Macroeconomics 0503023, EconWPA.

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