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Estimating Overidentified, Nonrecursive Time-Varying Coefficients Structural VARs

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  • Fabio Canova
  • Fernando J. P�rez Forero

Abstract

This paper provides a method to estimate time varying coefficients structural VARs which are non-recursive and potentially overidentified. The procedure allows for linear and non-linear restrictions on the parameters, maintains the multi-move structure of standard algorithms and can be used to estimate structural models with different identification restrictions. We study the transmission of monetary policy shocks and compare the results with those obtained with traditional methods.

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Bibliographic Info

Paper provided by Barcelona Graduate School of Economics in its series Working Papers with number 637.

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Date of creation: May 2012
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Handle: RePEc:bge:wpaper:637

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Keywords: Non-recursive overidentified SVARs; Time-varying coefficient models; Bayesian methods; Monetary transmission mechanism;

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References

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  1. Canova, Fabio & Paustian, Matthias, 2011. "Business cycle measurement with some theory," CEPR Discussion Papers, C.E.P.R. Discussion Papers 8364, C.E.P.R. Discussion Papers.
  2. Luca Gambetti & Evi Pappa & Fabio Canova, 2008. "The Structural Dynamics of U.S. Output and Inflation: What Explains the Changes?," Journal of Money, Credit and Banking, Blackwell Publishing, Blackwell Publishing, vol. 40(2-3), pages 369-388, 03.
  3. Gordon, David B & Leeper, Eric M, 1994. "The Dynamic Impacts of Monetary Policy: An Exercise in Tentative Identification," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 102(6), pages 1228-47, December.
  4. Ben S. Bernanke & Ilian Mihov, 1998. "Measuring Monetary Policy," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 113(3), pages 869-902, August.
  5. Daniel F. Waggoner & Tao Zha, 1998. "Conditional forecasts in dynamic multivariate models," Working Paper, Federal Reserve Bank of Atlanta 98-22, Federal Reserve Bank of Atlanta.
  6. Canova, Fabio & Gambetti, Luca, 2009. "Structural changes in the US economy: Is there a role for monetary policy?," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 33(2), pages 477-490, February.
  7. 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.
  8. John C. Robertson & Ellis W. Tallman, 1999. "Improving forecasts of the federal funds rate in a policy model," Working Paper, Federal Reserve Bank of Atlanta 99-3, Federal Reserve Bank of Atlanta.
  9. Alejandro Justiniano & Giorgio E. Primiceri, 2006. "The Time Varying Volatility of Macroeconomic Fluctuations," NBER Working Papers 12022, National Bureau of Economic Research, Inc.
  10. Fabio Canova & Filippo Ferroni, 2010. "The dynamics of US inflation: Can monetary policy explain the changes?," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra 1241, Department of Economics and Business, Universitat Pompeu Fabra.
  11. Fabio Canova & Matteo Ciccarelli & Eva Ortega, 2009. "Do institutional changes affect business cycles? Evidence from Europe," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra 1158, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 2012.
  12. Bernanke, Ben S & Blinder, Alan S, 1992. "The Federal Funds Rate and the Channels of Monetary Transmission," American Economic Review, American Economic Association, American Economic Association, vol. 82(4), pages 901-21, September.
  13. Christopher A. Sims & Tao Zha, 2005. "Were There Regime Switches in U.S. Monetary Policy?," Working Papers, Princeton University, Department of Economics, Center for Economic Policy Studies. 92, Princeton University, Department of Economics, Center for Economic Policy Studies..
  14. Jean Boivin & Marc P. Giannoni, 2006. "Has Monetary Policy Become More Effective?," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 445-462, August.
  15. Kim, Sangjoon & Shephard, Neil & Chib, Siddhartha, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 65(3), pages 361-93, July.
  16. Markku Lanne, Helmut Luetkepohl, 2006. "Identifying Monetary Policy Shocks via Changes in Volatility," Economics Working Papers, European University Institute ECO2006/23, European University Institute.
  17. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 28(2), pages 349-366, November.
  18. Juan F. Rubio-Ramírez & Daniel F.Waggoner & Tao Zha, 2008. "Structural vector autoregressions: theory of identification and algorithms for inference," Working Paper, Federal Reserve Bank of Atlanta 2008-18, Federal Reserve Bank of Atlanta.
  19. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-68, November.
  20. Geweke, John & Tanizaki, Hisashi, 2001. "Bayesian estimation of state-space models using the Metropolis-Hastings algorithm within Gibbs sampling," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 37(2), pages 151-170, August.
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Cited by:
  1. Canova, Fabio & Ciccarelli, Matteo, 2013. "Panel vector autoregressive models: a survey," Working Paper Series, European Central Bank 1507, European Central Bank.

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