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Dynamic Effects of Credit Shocks in a Data-Rich Environment

  • Jean Boivin
  • Marc P. Giannoni
  • Dalibor Stevanovic

We examine the dynamic effects of credit shocks using a large data set of U.S. economic and financial indicators in a structural factor model. The identified credit shocks, interpreted as unexpected deteriorations of credit market conditions, immediately increase credit spreads, decrease rates on Treasury securities, and cause large and persistent downturns in the activity of many economic sectors. Such shocks are found to have important effects on real activity measures, aggregate prices, leading indicators, and credit spreads. Our identification procedure does not require any timing restrictions between the financial and macroeconomic factors, and yields interpretable estimated factors.

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File URL: http://www.cirano.qc.ca/files/publications/2013s-11.pdf
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Paper provided by CIRANO in its series CIRANO Working Papers with number 2013s-11.

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Length: 56 pages
Date of creation: 01 May 2013
Date of revision:
Handle: RePEc:cir:cirwor:2013s-11
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  1. Marc P. Giannoni & Jean Boivin, 2005. "DSGE Models in a Data-Rich Environment," Computing in Economics and Finance 2005 431, Society for Computational Economics.
  2. Ben S. Bernanke & Mark Gertler, 1995. "Inside the Black Box: The Credit Channel of Monetary Policy Transmission," NBER Working Papers 5146, National Bureau of Economic Research, Inc.
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  4. Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," Working Papers 284, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    • 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.
  5. Forni, Mario & Giannone, Domenico & Lippi, Marco & Reichlin, Lucrezia, 2007. "Opening the black box: structural factor models with large cross-sections," Working Paper Series 0712, European Central Bank.
  6. Vladimir Yankov & Egon Zakrajsek & Simon Gilchrist, 2009. "Credit Market Shocks and Economic Fluctuations: Evidence from Corporate Bond and Stock Markets," 2009 Meeting Papers 514, Society for Economic Dynamics.
  7. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
  8. Ben Bernanke & Jean Boivin & Piotr S. Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, MIT Press, vol. 120(1), pages 387-422, January.
  9. Lawrence J. Christiano & Martin Eichenbaum & Charles Evans, 2001. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," NBER Working Papers 8403, National Bureau of Economic Research, Inc.
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  14. Lawrence Christiano & Roberto Motto & Massimo Rostagno, 2013. "Risk Shocks," NBER Working Papers 18682, National Bureau of Economic Research, Inc.
  15. Mark Gertler & Cara S. Lown, 2000. "The Information in the High Yield Bond Spread for the Business Cycle: Evidence and Some Implications," NBER Working Papers 7549, National Bureau of Economic Research, Inc.
  16. Borus Jungbacker & Siem Jan Koopman, 2008. "Likelihood-based Analysis for Dynamic Factor Models," Tinbergen Institute Discussion Papers 08-007/4, Tinbergen Institute, revised 20 Mar 2014.
  17. 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.
  18. Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May.
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