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An Introductory Review of a Structural VAR-X Estimation and Applications

  • Sergio Ocampo

    ()

  • Norberto Rodríguez

    ()

This document presents how to estimate and implement a structural VAR-X model under long run and impact identification restrictions. Estimation by bayesian and maximum likelihood methods is presented. Applications of the structural VAR-X for impulse response functions to structural shocks, multiplier analysis of the exogenous variables, forecast error variance decomposition and historical decomposition of the endogenous variables are also described, as well as a method for computing HPD regions in a bayesian context. Some of the concepts are exemplified with an application to US data.

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Paper provided by Banco de la Republica de Colombia in its series Borradores de Economia with number 686.

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Length: 24
Date of creation: Dec 2011
Date of revision:
Handle: RePEc:bdr:borrec:686
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  1. 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.
  2. Kocięcki, Andrzej, 2010. "A Prior for Impulse Responses in Bayesian Structural VAR Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 115-127.
  3. Runkle, David E, 1987. "Vector Autoregressions and Reality: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 454, October.
  4. Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May.
  5. David E. Runkle, 1987. "Vector autoregressions and reality," Staff Report 107, Federal Reserve Bank of Minneapolis.
  6. Fabio Canova & Evi Pappa, 2003. "Price differentials in monetary unions: The role of fiscal shocks," Economics Working Papers 923, Department of Economics and Business, Universitat Pompeu Fabra, revised Jun 2005.
  7. Runkle, David E, 1987. "Vector Autoregressions and Reality," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 437-42, October.
  8. James Morley & Thomas King, 2003. "In Search of the Natural Rate of Unemployment," Computing in Economics and Finance 2003 190, Society for Computational Economics.
  9. Smets, Frank & Wouters, Rafael, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," CEPR Discussion Papers 6112, C.E.P.R. Discussion Papers.
  10. Mountford, A.W. & Uhlig, H.F.H.V.S., 2002. "What are the Effects of Fiscal Policy Shocks?," Discussion Paper 2002-31, Tilburg University, Center for Economic Research.
  11. Christopher A. Sims & Tao Zha, 1995. "Error bands for impulse responses," Working Paper 95-6, Federal Reserve Bank of Atlanta.
  12. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  13. Lutkepohl, Helmut, 1990. "Asymptotic Distributions of Impulse Response Functions and Forecast Error Variance Decompositions of Vector Autoregressive Models," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 116-25, February.
  14. Bauwens, Luc & Lubrano, Michel & Richard, Jean-Francois, 2000. "Bayesian Inference in Dynamic Econometric Models," OUP Catalogue, Oxford University Press, number 9780198773139, March.
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