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On Priors for Impulse Responses in Bayesian Structural VAR Models

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  • Andrzej Kociêcki

    (National Bank of Poland)

Abstract

We proposed clear, methodologically sound framework for analyzing SVAR with priors on impulse responses. We showed it poses no difficulties in deriving the posterior which even in case of unidentified SVAR with flat prior on impulse functions (under the appropriate requirement tying number of observations, lags and variables) is necessarily proper. Accordingly, useful factorization of the posterior was given and efficient method for sampling from the posterior was outlined.

Suggested Citation

  • Andrzej Kociêcki, 2003. "On Priors for Impulse Responses in Bayesian Structural VAR Models," Econometrics 0307006, EconWPA.
  • Handle: RePEc:wpa:wuwpem:0307006
    Note: Type of Document - ; prepared on IBM PC - PC-TEX/UNIX Sparc TeX; to print on HP/PostScript/Franciscan monk; pages: 16 ; figures: included/request from author/draw your own. We never published this piece and now we would like to reduce our mailing and xerox cost by posting it.
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    References listed on IDEAS

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    1. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    2. Christopher A. Sims & Tao Zha, 1999. "Error Bands for Impulse Responses," Econometrica, Econometric Society, vol. 67(5), pages 1113-1156, September.
    3. Uhlig, Harald, 1998. "The robustness of identified VAR conclusions about money : A comment," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 245-263, December.
    4. Daniel F. Waggoner & Tao Zha, 1999. "Conditional Forecasts In Dynamic Multivariate Models," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 639-651, November.
    5. Bauwens, L. & Bos, C.S. & van Dijk, H.K. & van Oest, R.D., 2002. "Adaptive polar sampling, a class of flexibel and robust Monte Carlo integration methods," Econometric Institute Research Papers EI 2002-27, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Jon Faust, 1998. "The robustness of identified VAR conclusions about money," International Finance Discussion Papers 610, Board of Governors of the Federal Reserve System (U.S.).
    7. Eric M. Leeper & Christopher A. Sims & Tao Zha, 1996. "What Does Monetary Policy Do?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(2), pages 1-78.
    8. 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.
    9. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 207-244, December.
    10. Luc Bauwens & Charles S. Bos & Herman K. van Dijk & Rutger D. van Oest, 2002. "Adaptive Polar Sampling," Computing in Economics and Finance 2002 307, Society for Computational Economics.
    11. Mark Dwyer, 1998. "Impulse Response Priors for Discriminating Structural Vector Autoregressions," UCLA Economics Working Papers 780, UCLA Department of Economics.
    12. Mark Dwyer, 1998. "Impulse Response Priors for Discriminating Structural Vector Autoregressions," Econometrics 9808001, EconWPA.
    13. Schotman, Peter & van Dijk, Herman K., 1991. "A Bayesian analysis of the unit root in real exchange rates," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 195-238.
    14. Daniel F. Waggoner & Tao Zha, 1997. "Normalization, probability distribution, and impulse responses," FRB Atlanta Working Paper 97-11, Federal Reserve Bank of Atlanta.
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    More about this item

    Keywords

    impulse responses Structural VAR bayesian analysis;

    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

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