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Small-Sample Confidence Intervals For Impulse Response Functions

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  • Lutz Kilian

Abstract

Bias-corrected bootstrap confidence intervals explicitly account for the bias and skewness of the small-sample distribution of the impulse response estimator, while retaining asymptotic validity in stationary autoregressions. Monte Carlo simulations for a wide range of bivariate models show that in small samples bias-corrected bootstrap intervals tend to be more accurate than delta method intervals, standard bootstrap intervals, and Monte Carlo integration intervals. This conclusion holds for VAR models estimated in levels, as deviations from a linear time trend, and in first differences. It also holds for random walk processes and cointegrated processes estimated in levels. An empirical example shows that bias-corrected bootstrap intervals may imply economic interpretations of the data that are substantively different from standard methods. © 1998 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology

Suggested Citation

  • 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.
  • Handle: RePEc:tpr:restat:v:80:y:1998:i:2:p:218-230
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    6. Helmut Lütkepohl & Anna Staszewska-Bystrova & Peter Winker, 2018. "Estimation of structural impulse responses: short-run versus long-run identifying restrictions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(2), pages 229-244, April.
    7. Max Hanisch, 2017. "US Monetary Policy and the Euro Area," Discussion Papers of DIW Berlin 1701, DIW Berlin, German Institute for Economic Research.
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    9. Rui Manuel Pereira, Alfredo Marvao Pereira and William J. Hausman, 2017. "Railroad Infrastructure Investments and Economic Development in the Antebellum United States," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 42(3), pages 1-16, September.
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    15. Lenard Lieb & Stephan Smeekes, 2017. "Inference for Impulse Responses under Model Uncertainty," Papers 1709.09583, arXiv.org, revised May 2018.
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    17. Burak Eroglu & Kemal Caglar Gogebakan & Mirza Trokic, 2017. "Fractional Seasonal Variance Ratio Unit Root Tests," Working Papers 1707, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
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    20. Ashima Goyal & Abhishek Kumar, 2018. "The effect of oil shocks and cyclicality in hiding Indian twin deficits," Journal of Economic Studies, Emerald Group Publishing, vol. 45(1), pages 27-45, January.
    21. Burak Eroglu & Secil Yildirim-Karaman, 2017. "Responses Of Term Structure Of Interest Rates And Asset Prices To Monetary Policy Shocks: Evidence From Turkey," Working Papers 1705, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.

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