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Problems related to confidence intervals for impulse responses of autoregressive processes

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Author Info

  • Alexander Benkwitz
  • Michael Neumann
  • Helmut Lutekpohl
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    Abstract

    Confidence intervals for impulse responses computed from autoregressive processes are considered. A detailed analysis of the methods in current use shows that they are not very reliable in some cases. In particular, there are theoretical reasons for them to have actual coverage probabilities which deviate considerably from the nominal level in some situations of practical importance. For a simple case alternative bootstrap methods are proposed which provide correct results asymptotically.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/07474930008800460
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Econometric Reviews.

    Volume (Year): 19 (2000)
    Issue (Month): 1 ()
    Pages: 69-103

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    Handle: RePEc:taf:emetrv:v:19:y:2000:i:1:p:69-103

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    Related research

    Keywords: impulse response; bootstrap; autoregressive process; asymptotic inference; nonparametric inference;

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    Cited by:
    1. Müller, Christian, 2012. "A new interpretation of known facts: The case of two-way causality between trading and volatility," Economic Modelling, Elsevier, vol. 29(3), pages 664-670.
    2. Granger, Clive W. J. & Jeon, Yongil, 2004. "Thick modeling," Economic Modelling, Elsevier, vol. 21(2), pages 323-343, March.
    3. DUFOUR, Jean-Marie, 2005. "Monte Carlo Tests with Nuisance Parameters: A General Approach to Finite-Sample Inference and Nonstandard Asymptotics," Cahiers de recherche 03-2005, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    4. DUFOUR, Jean-Marie & JOUINI, Tarek, 2005. "Finite-Sample Simulation-Based Inference in VAR Models with Applications to Order Selection and Causality Testing," Cahiers de recherche 16-2005, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    5. Müller, Gernot J., 2008. "Understanding the dynamic effects of government spending on foreign trade," Journal of International Money and Finance, Elsevier, vol. 27(3), pages 345-371, April.
    6. Dufour, Jean-Marie & Jouini, Tarek, 2006. "Finite-sample simulation-based inference in VAR models with application to Granger causality testing," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 229-254.
    7. Hess, Martin K., 2004. "Dynamic and asymmetric impacts of macroeconomic fundamentals on an integrated stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(5), pages 455-471, December.
    8. Kilian, Lutz & Kim, Yun Jung, 2009. "Do Local Projections Solve the Bias Problem in Impulse Response Inference?," CEPR Discussion Papers 7266, C.E.P.R. Discussion Papers.
    9. Tuck Cheong Tang, 2006. "Japan's balancing item: do timing errors matter?," Applied Economics Letters, Taylor & Francis Journals, vol. 13(2), pages 81-87.
    10. Brüggemann, Ralf & Lütkepohl, Helmut, 2000. "Lag selection in subset VAR models with an application to a US monetary system," SFB 373 Discussion Papers 2000,37, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    11. Mei-yin Lin & Hui-hua Wang, 2009. "What Causes the Volatility of the Balancing Item?," Economics Bulletin, AccessEcon, vol. 29(4), pages 2738-2748.
    12. Tuck Cheong Tang, 2006. "The influences of economic openness on Japan's balancing item: an empirical note," Applied Economics Letters, Taylor & Francis Journals, vol. 13(1), pages 7-10.

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