IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login

Citations for "Likelihood preserving normalization in multiple equation models"

by Waggoner, Daniel F. & Zha, Tao

For a complete description of this item, click here. For a RSS feed for citations of this item, click here.
as in new window

  1. Kociecki, Andrzej, 2013. "Further Results on Identification of Structural VAR Models," MPRA Paper 46536, University Library of Munich, Germany.
  2. John Keating, 2004. "Interpreting Permanent and Transitory Shocks to Output When Aggregate Demand May Not Be Neutral in the Long-run," Econometric Society 2004 North American Summer Meetings 608, Econometric Society.
  3. John W. Keating, 2013. "Interpreting Permanent Shocks to Output When Aggregate Demand May Not Be Neutral in the Long Run," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(4), pages 747-756, 06.
  4. Kociecki, Andrzej, 2013. "Towards Understanding the Normalization in Structural VAR Models," MPRA Paper 47645, University Library of Munich, Germany.
  5. Kociecki, Andrzej, 2012. "Orbital Priors for Time-Series Models," MPRA Paper 42804, University Library of Munich, Germany.
  6. Christopher A. Sims & Tao Zha, 2005. "Were There Regime Switches in U.S. Monetary Policy?," Working Papers 92, Princeton University, Department of Economics, Center for Economic Policy Studies..
  7. Juan F. Rubio-Ram�rez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 665-696.
  8. Leeper, Eric M. & Zha, Tao, 2003. "Modest policy interventions," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1673-1700, November.
  9. Christopher A. Sims & Daniel F. Waggoner & Tao Zha, 2006. "Methods for inference in large multiple-equation Markov-switching models," Working Paper 2006-22, Federal Reserve Bank of Atlanta.
  10. Bognanni, Mark & Herbst, Edward, 2014. "Estimating (Markov-Switching) VAR Models without Gibbs Sampling: A Sequential Monte Carlo Approach," Working Paper 1427, Federal Reserve Bank of Cleveland.
  11. Villani, Mattias & Warne, Anders, 2003. "Monetary policy analysis in a small open economy using Bayesian cointegrated structural VARs," Working Paper Series 0296, European Central Bank.
  12. Arias, Jonas E. & Rubio-Ramirez, Juan F. & Waggoner, Daniel F., 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.).
  13. Keating, John W., 2013. "What do we learn from Blanchard and Quah decompositions of output if aggregate demand may not be long-run neutral?," Journal of Macroeconomics, Elsevier, vol. 38(PB), pages 203-217.
  14. Cyriac Guillaumin, 2008. "(A)symetrie et convergence des chocs macroeconomiques en Asie de l'Est : une analyse dynamique," Economie Internationale, CEPII research center, issue 114, pages 29-68.
  15. James D. Hamilton & Daniel F. Waggoner & Tao Zha, 2007. "Normalization in Econometrics," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 221-252.
  16. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
  17. 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.
  18. Mattias Villani, 2009. "Steady-state priors for vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 630-650.
  19. Voss, G.M. & Willard, L.B., 2009. "Monetary policy and the exchange rate: Evidence from a two-country model," Journal of Macroeconomics, Elsevier, vol. 31(4), pages 708-720, December.
  20. Evans, Charles L. & Marshall, David A., 2007. "Economic determinants of the nominal treasury yield curve," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 1986-2003, October.
  21. Khiabani, Nasser, 2010. "How Important are Oil and Money Shocks in Explaining Housing Market Fluctuations in an Oil-exporting Country?: Evidence from Iran," MPRA Paper 34041, University Library of Munich, Germany, revised 01 Mar 2011.
  22. Del Negro, Marco & Otrok, Christopher, 2007. "99 Luftballons: Monetary policy and the house price boom across U.S. states," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 1962-1985, October.
  23. 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.
  24. Par Osterholm, 2008. "A structural Bayesian VAR for model-based fan charts," Applied Economics, Taylor & Francis Journals, vol. 40(12), pages 1557-1569.
  25. John W. Keating, 2013. "What Do We Learn from Blanchard and Quah Decompositions If Aggregate Demand May Not be Long-Run Neutral?," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201302, University of Kansas, Department of Economics.
  26. Luigi Paciello, 2009. "Does Inflation Adjust Faster to Aggregate Technology Shocks than to Monetary Policy Shocks?," EIEF Working Papers Series 0917, Einaudi Institute for Economics and Finance (EIEF), revised Apr 2011.
  27. Penelope A. Smith & Peter M. Summers, 2004. "Identification and normalization in Markov switching models of "business cycles"," Research Working Paper RWP 04-09, Federal Reserve Bank of Kansas City.
  28. Malin Adolfson & Michael K. Andersson & Jesper Lindé & Mattias Villani & Anders Vredin, 2007. "Modern Forecasting Models in Action: Improving Macroeconomic Analyses at Central Banks," International Journal of Central Banking, International Journal of Central Banking, vol. 3(4), pages 111-144, December.
  29. Andrea Nobili & Stefano Neri, 2006. "The transmission of monetary policy shocks from the US to the euro area," Temi di discussione (Economic working papers) 606, Bank of Italy, Economic Research and International Relations Area.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.