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Bayesian VARs: A Survey of the Recent Literature with an Application to the European Monetary System

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Author Info

  • Matteo Ciccarelli
  • Alessandro Rebucci

Abstract

This paper reviews recent advances in the specification and estimation of Bayesian Vector Autoregressive models (BVARs). After describing the Bayesian principle of estimation, we first present the methodology originally developed by Litterman (1986) and Doan et al. (1984) and review alternative priors. We then discuss extensions of the basic model and address issues in forecasting and structural analysis. An application to the estimation of a system of time-varying reaction functions for four European central banks under the European Monetary System (EMS) illustrates how some of the results previously presented may be applied in practice.

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Bibliographic Info

Paper provided by International Monetary Fund in its series IMF Working Papers with number 03/102.

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Length: 44
Date of creation: 01 May 2003
Date of revision:
Handle: RePEc:imf:imfwpa:03/102

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Related research

Keywords: Economic models; European Monetary System;

References

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  1. Kadiyala, K. Rao & Karlsson, Sune, 1994. "Numerical Aspects of Bayesian VAR-modeling," Working Paper Series in Economics and Finance 12, Stockholm School of Economics.
  2. Luis J. Álvarez & Fernando C. Ballabriga, 1994. "BVAR models in the context of cointegration: A Monte Carlo experiment," Banco de Espa�a Working Papers 9405, Banco de Espa�a.
  3. Clarida, Richard & Gali, Jordi & Gertler, Mark, 1998. "Monetary policy rules in practice Some international evidence," European Economic Review, Elsevier, vol. 42(6), pages 1033-1067, June.
  4. Fabio Canova & Matteo Ciccarelli, 1999. "Forecasting and turning point predictions in a Bayesian panel VAR model," Economics Working Papers 443, Department of Economics and Business, Universitat Pompeu Fabra.
  5. Daniel F. Waggoner & Tao Zha, 1998. "Conditional forecasts in dynamic multivariate models," Working Paper 98-22, Federal Reserve Bank of Atlanta.
  6. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
  7. Bernanke, Ben S. & Mihov, Ilian, 1997. "What does the Bundesbank target?," European Economic Review, Elsevier, vol. 41(6), pages 1025-1053, June.
  8. Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
  9. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
  10. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
  11. 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, vol. 39(4), pages 949-68, November.
  12. Matteo Ciccarelli & Alessandro Rebucci, 2001. "The Transmission Mechanism of European Monetary Policy: Is There Heterogeneity? Is It Changing Over Time?," Banco de Espa�a Working Papers 0115, Banco de Espa�a.
  13. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
  14. Sims, Christopher A, 1972. "Money, Income, and Causality," American Economic Review, American Economic Association, vol. 62(4), pages 540-52, September.
  15. repec:cup:cbooks:9780521558839 is not listed on IDEAS
  16. Zha, Tao, 1999. "Block recursion and structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 90(2), pages 291-316, June.
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Cited by:
  1. Caraiani, Petre, 2010. "Forecasting Romanian GDP Using a BVAR Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 76-87, December.

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