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Structural Factor-Augmented VAR (SFAVAR) and the Effects of Monetary Policy

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Author Info

  • Francesco Belviso

    (Princeton University & University of Chicago)

  • Fabio Milani

    (Princeton University)

Abstract

Factor-augmented VARs (FAVARs) have combined standard VARs with factor analysis to exploit large data sets in the study of monetary policy. FAVARs enjoy a number of advantages over VARs: they allow a better identification of the monetary policy shock; they can avoid the use of a single variable to proxy theoretical constructs, such as the output gap; they allow researchers to compute impulse responses for hundreds of variables. Their shortcoming, however, is that the factors are not identified and, therefore, lack any economic interpretation. This paper seeks to provide an interpretation to the factors. We propose a novel Structural Factor-Augmented VAR (SFAVAR) model, where the factors have a clear meaning: 'Real Activity' factor, 'Price Pressures' factor, 'Financial Market' factor, 'Credit Conditions' factor, 'Expectations' factor, etc. The paper employs a Bayesian approach to extract the factors and jointly estimate the model. This framework is then suited to study the effects on a wide range of macroeconomic variables of monetary policy and non-policy shocks.

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Bibliographic Info

Paper provided by EconWPA in its series Macroeconomics with number 0503023.

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Length: 48 pages
Date of creation: 30 Mar 2005
Date of revision:
Handle: RePEc:wpa:wuwpma:0503023

Note: Type of Document - pdf; pages: 48
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Web page: http://128.118.178.162

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Keywords: VAR; Dynamic Factors; Monetary Policy; Structural FAVAR.;

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  1. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
  2. Marvin J. Barth III & Valerie A. Ramey, 2002. "The Cost Channel of Monetary Transmission," NBER Chapters, in: NBER Macroeconomics Annual 2001, Volume 16, pages 199-256 National Bureau of Economic Research, Inc.
  3. Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," NBER Chapters, in: NBER Macroeconomics Annual 2004, Volume 19, pages 161-224 National Bureau of Economic Research, Inc.
  4. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
  5. Mario Forni & Domenico Giannone & Marco Lippi & Lucrezia Reichlin, 2007. "Opening the Black Box: Structural Factor Models with Large Cross-Sections," Center for Economic Research (RECent) 008, University of Modena and Reggio E., Dept. of Economics.
  6. Ben S. Bernanke & Mark Gertler, 2001. "Should Central Banks Respond to Movements in Asset Prices?," American Economic Review, American Economic Association, vol. 91(2), pages 253-257, May.
  7. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148 Elsevier.
  8. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," NBER Working Papers 10220, National Bureau of Economic Research, Inc.
  9. Forni, Mario & Lippi, Marco & Reichlin, Lucrezia, 2003. "Opening the Black Box: Structural Factor Models versus Structural VARs," CEPR Discussion Papers 4133, C.E.P.R. Discussion Papers.
  10. Alejandro Justiniano, 2004. "Sources and Propagation Mechanims of Foreign Disturbances in Small Open Economies: A Dynamic Factor Analysis," Econometric Society 2004 Latin American Meetings 148, Econometric Society.
  11. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
  12. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
  13. Christopher A. Sims, 2002. "The Role of Models and Probabilities in the Monetary Policy Process," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2), pages 1-62.
  14. Eric M. Leeper & Christopher A. Sims & Tao Zha, 1996. "What Does Monetary Policy Do?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(2), pages 1-78.
  15. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  16. Favero, Carlo A & Marcellino, Massimiliano, 2001. "Large Datasets, Small Models and Monetary Policy in Europe," CEPR Discussion Papers 3098, C.E.P.R. Discussion Papers.
  17. 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.
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