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New Information Response Functions

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Author Info

  • Jardet, C.
  • Monfort, A.
  • Pegoraro, F.

Abstract

We propose a new methodology for the analysis of impulse response functions in VAR or VARMA models. More precisely, we build our results on the non ambiguous notion of innovation of a stochastic process and we consider the impact of any kind of new information at a given date $t$ on the future values of the process. This methodology allows to take into account qualitative or quantitative information, either on the innovation or on the future responses, as well as informations on filters. We show, among other results, that our approach encompasses several standard methodologies found in the literature, such as the orthogonalization of shocks (Sims (1980)), the "structural" identification of shocks (Blanchard and Quah (1989)), the "generalized" impulse responses (Pesaran and Shin (1998)) or the impulse vectors (Uhlig (2005)).

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Bibliographic Info

Paper provided by Banque de France in its series Working papers with number 235.

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Length: 15 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:bfr:banfra:235

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Web page: http://www.banque-france.fr/
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Related research

Keywords: Impulse response functions ; innovation ; new information.;

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References

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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. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1993. "Nonlinear Dynamic Structures," Econometrica, Econometric Society, vol. 61(4), pages 871-907, July.
  3. Jardet, Caroline & Monfort, Alain & Pegoraro, Fulvio, 2013. "No-arbitrage Near-Cointegrated VAR(p) term structure models, term premia and GDP growth," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 389-402.
  4. Juan F. Rubio-Ramírez & Daniel F.Waggoner & Tao Zha, 2008. "Structural vector autoregressions: theory of identification and algorithms for inference," Working Paper 2008-18, Federal Reserve Bank of Atlanta.
  5. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
  6. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
  7. Ben S. Bernanke, 1986. "Alternative Explanations of the Money-Income Correlation," NBER Working Papers 1842, National Bureau of Economic Research, Inc.
  8. Olivier Jean Blanchard & Danny Quah, 1988. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," NBER Working Papers 2737, National Bureau of Economic Research, Inc.
  9. Christian Gourieroux & Joanna Jasiak, 1999. "Nonlinear Innovations and Impulse Response," Working Papers 99-44, Centre de Recherche en Economie et Statistique.
  10. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
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Cited by:
  1. Caroline JARDET & Alain MONFORT & Fulvio PEGORARO, 2011. "No-arbitrage Near-Cointegrated VAR(p) Term Structure Models, Term Premia and GDP Growth," Working Papers 2011-03, Centre de Recherche en Economie et Statistique.

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