Bayesian identification of structural vector autoregression models
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- Jonas E. Arias & Juan Rubio-Ramirez & Daniel F. Waggoner, 2013.
"Inference Based on SVARs Identied with Sign and Zero Restrictions: Theory and Applications,"
Working Papers
2013-24, FEDEA.
- Juan Rubio-Ramirez & Daniel Waggoner & Jonas Arias, 2016. "Inference Based on SVARs Identified with Sign and Zero Restrictions: Theory and Applications," 2016 Meeting Papers 472, Society for Economic Dynamics.
- Juan Rubio-Ramirez & Daniel Waggoner & Jonas Arias, 2014. "Inference Based on SVARs Identified with Sign and Zero Restrictions: Theory and Applications," 2014 Meeting Papers 1199, Society for Economic Dynamics.
- Arias, Jonas E. & Rubio-Ramírez, Juan F. & Waggoner, Daniel F., 2014. "Inference Based on SVARs Identified with Sign and Zero Restrictions: Theory and Applications," Dynare Working Papers 30, CEPREMAP.
- Rubio-RamÃrez, Juan Francisco & , & Arias, Jonas E., 2014. "Inference Based on SVAR Identified with Sign and Zero Restrictions: Theory and Applications," CEPR Discussion Papers 9796, C.E.P.R. Discussion Papers.
- Jonas E. Arias & Juan F. Rubio-Ramirez & Daniel F. Waggoner, 2014. "Inference Based on SVARs Identified with Sign and Zero Restrictions: Theory and Applications," FRB Atlanta Working Paper 2014-1, Federal Reserve Bank of Atlanta.
- Jonas E. Arias & Juan F. Rubio-Ramirez & Daniel F. Waggoner, 2014. "Inference Based on SVARs Identified with Sign and Zero Restrictions: Theory and Applications," International Finance Discussion Papers 1100, Board of Governors of the Federal Reserve System (U.S.).
- Juan F. Rubio-Ramírez & Jonas E. Arias & Daniel F. Waggoner, 2013. "Inference Based on SVARs Identied with Sign and Zero Restrictions: Theory and Applications," Working Papers 1338, BBVA Bank, Economic Research Department.
- Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010.
"Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference,"
The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
- Juan F. Rubio-Ramirez & Daniel F. Waggoner & Tao Zha, 2008. "Structural vector autoregressions: theory of identification and algorithms for inference," FRB Atlanta Working Paper 2008-18, Federal Reserve Bank of Atlanta.
- Helmut Lütkepohl & Anton Velinov, 2016.
"Structural Vector Autoregressions: Checking Identifying Long-Run Restrictions Via Heteroskedasticity,"
Journal of Economic Surveys, Wiley Blackwell, vol. 30(2), pages 377-392, April.
- Lütkepohl, Helmut & Velinov, Anton, 2016. "Structural Vector Autoregressions : Checking Identifying Long-Run Restrictions via Heteroskedasticity," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 30, pages 377-392.
- Helmut Lütkepohl & Anton Velinov, 2014. "Structural Vector Autoregressions: Checking Identifying Long-run Restrictions via Heteroskedasticity," CESifo Working Paper Series 4651, CESifo.
- Lütkepohl, Helmut & Velinov, Anton, 2014. "Structural vector autoregressions: Checking identifying long-run restrictions via heteroskedasticity," SFB 649 Discussion Papers 2014-009, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Helmut Lütkepohl & Anton Velinov, 2014. "Structural Vector Autoregressions: Checking Identifying Long-Run Restrictions via Heteroskedasticity," Discussion Papers of DIW Berlin 1356, DIW Berlin, German Institute for Economic Research.
- Aldrich, Eric M. & Fernández-Villaverde, Jesús & Ronald Gallant, A. & Rubio-Ramírez, Juan F., 2011.
"Tapping the supercomputer under your desk: Solving dynamic equilibrium models with graphics processors,"
Journal of Economic Dynamics and Control, Elsevier, vol. 35(3), pages 386-393, March.
- Eric M. Aldrich & Jesús Fernández-Villaverde & Ronald Gallant & Juan F. Rubio-RamÃrez, 2010. "Tapping the Supercomputer Under Your Desk: Solving Dynamic Equilibrium Models with Graphics Processors," PIER Working Paper Archive 10-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Eric M. Aldrich & Jesús Fernández-Villaverde & A. Ronald Gallant & Juan F. Rubio-Ramírez, 2010. "Tapping the Supercomputer Under Your Desk: Solving Dynamic Equilibrium Models with Graphics Processors," NBER Working Papers 15909, National Bureau of Economic Research, Inc.
- Eric M. Aldrich & Jesus Fernandez-Villaverde & A. Ronald Gallant & Juan F. Rubio-Ramirez, 2010. "Tapping the Supercomputer Under Your Desk: Solving Dynamic Equilibrium Models with Graphics Processors," Working Papers 10-89, Duke University, Department of Economics.
- 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 949-968, November.
- Christopher A. Sims & Tao Zha, 1996. "Bayesian methods for dynamic multivariate models," FRB Atlanta Working Paper 96-13, Federal Reserve Bank of Atlanta.
- Korobilis, D, 2017.
"Forecasting with many predictors using message passing algorithms,"
Essex Finance Centre Working Papers
19565, University of Essex, Essex Business School.
- Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
- Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
- Christiane Baumeister & James D. Hamilton, 2015.
"Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information,"
Econometrica, Econometric Society, vol. 83(5), pages 1963-1999, September.
- Christiane Baumeister & James D. Hamilton, 2014. "Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information," NBER Working Papers 20741, National Bureau of Economic Research, Inc.
- Matteo Fragetta & Giovanni Melina, 2013.
"Identification of monetary policy in SVAR models: a data-oriented perspective,"
Empirical Economics, Springer, vol. 45(2), pages 831-844, October.
- Matteo Fragetta & Giovanni Melina, 2011. "Identification of Monetary Policy in SVAR Models: A Data-Oriented Perspective," School of Economics Discussion Papers 0811, School of Economics, University of Surrey.
- Alessio Moneta, 2008. "Graphical causal models and VARs: an empirical assessment of the real business cycles hypothesis," Empirical Economics, Springer, vol. 35(2), pages 275-300, September.
- 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.
- Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016.
"Bayesian Graphical Models for STructural Vector Autoregressive Processes,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 357-386, March.
- Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2012. "Bayesian Graphical Models for Structural Vector Autoregressive Processes," Working Papers 2012:36, Department of Economics, University of Venice "Ca' Foscari".
- Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
- Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
- Dimitris Korobilis, 2021.
"High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
- Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
- Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019_07, Business School - Economics, University of Glasgow.
- Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
- Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
- George, Edward I. & Sun, Dongchu & Ni, Shawn, 2008. "Bayesian stochastic search for VAR model restrictions," Journal of Econometrics, Elsevier, vol. 142(1), pages 553-580, January.
- Pearl, Judea, 2015. "Trygve Haavelmo And The Emergence Of Causal Calculus," Econometric Theory, Cambridge University Press, vol. 31(1), pages 152-179, February.
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More about this item
Keywords
SVAR; identification; Bayesian model averaging; Bayesian model selection;All these keywords.
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
Statistics
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