Bayesian analysis of recursive SVAR models with overidentifying restrictions
The paper provides a novel Bayesian methodological framework to estimate structural VAR (SVAR) models with recursive identification schemes that allows for the inclusion of over-identifying restrictions. The proposed framework enables the researcher to (i) elicit the prior on the non-zero contemporaneous relations between economic variables and to (ii) derive an analytical expression for the posterior distribution and marginal data density. We illustrate our methodological framework by estimating a backward looking New-Keynesian model taking into account prior beliefs about the contemporaneous coefficients in the Phillips curve and Taylor rule. JEL Classification: C11, C32, E47
|Date of creation:||Nov 2012|
|Date of revision:|
|Contact details of provider:|| Postal: 60640 Frankfurt am Main, Germany|
Phone: +49 69 1344 0
Fax: +49 69 1344 6000
Web page: http://www.ecb.europa.eu/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Christopher A. Sims & Tao Zha, 1996.
"Bayesian methods for dynamic multivariate models,"
FRB Atlanta Working Paper
96-13, Federal Reserve Bank of Atlanta.
- Kadiyala, K Rao & Karlsson, Sune, 1997.
"Numerical Methods for Estimation and Inference in Bayesian VAR-Models,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
- Kadiyala, K. Rao & Karlsson, Sune, 1994. "Numerical Aspects of Bayesian VAR-modeling," SSE/EFI Working Paper Series in Economics and Finance 12, Stockholm School of Economics.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E, 2012.
"Prior Selection for Vector Autoregressions,"
CEPR Discussion Papers
8755, C.E.P.R. Discussion Papers.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2012. "Prior selection for vector autoregressions," Working Paper Series 1494, European Central Bank.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," NBER Working Papers 18467, National Bureau of Economic Research, Inc.
- Domenico Giannone & Michèle Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," Working Papers ECARES ECARES 2012-002, ULB -- Universite Libre de Bruxelles.
- Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010.
"Large Bayesian vector auto regressions,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
- Martha Banbura & Domenico Giannone & Lucrezia Reichlin, 2008. "Large Bayesian VARs," Working Papers ECARES 2008_033, ULB -- Universite Libre de Bruxelles.
- Bańbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Large Bayesian VARs," Working Paper Series 0966, European Central Bank.
- Banbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2007. "Bayesian VARs with Large Panels," CEPR Discussion Papers 6326, C.E.P.R. Discussion Papers.
- Domenico Giannone & Martha Banbura & Lucrezia Reichlin, 2008. "Bayesian VARs with large panels," ULB Institutional Repository 2013/13388, ULB -- Universite Libre de Bruxelles.
- Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
- Athanasios Orphanides, 1998.
"Monetary policy evaluation with noisy information,"
Finance and Economics Discussion Series
1998-50, Board of Governors of the Federal Reserve System (U.S.).
- Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
- John C. Robertson & Ellis W. Tallman, 1999. "Vector autoregressions: forecasting and reality," Economic Review, Federal Reserve Bank of Atlanta, issue Q1, pages 4-18.
When requesting a correction, please mention this item's handle: RePEc:ecb:ecbwps:20121492. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Official Publications)
If references are entirely missing, you can add them using this form.