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Impulse response confidence intervals for persistent data: What have we learned?

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  • Pesavento, Elena
  • Rossi, Barbara

Abstract

This paper is a comprehensive comparison of existing methods for constructing confidence bands for univariate impulse response functions in the presence of high persistence. Monte Carlo results show that Kilian (1998a), Wright (2000), Gospodinov (2004) and Pesavento and Rossi (2005) have favorable coverage properties, although they differ in terms of robustness at various horizons, median unbiasedness, and reliability in the possible presence of a unit or mildly explosive root. On the other hand, methods like Runkle’s (1987) bootstrap, Andrews and Chen (1994), and regressions in levels or first differences (even when based on pre-tests) may not have accurate coverage properties. The paper makes recommendations as to the appropriateness of each method in empirical work.
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  • Pesavento, Elena & Rossi, Barbara, 2007. "Impulse response confidence intervals for persistent data: What have we learned?," Journal of Economic Dynamics and Control, Elsevier, vol. 31(7), pages 2398-2412, July.
  • Handle: RePEc:eee:dyncon:v:31:y:2007:i:7:p:2398-2412
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    Cited by:

    1. K. Azim Ozdemir, 2015. "Interest Rate Surprises and Transmission Mechanism in Turkey: Evidence from Impulse Response Analysis," Working Papers 1504, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    2. Neil Kellard & Denise Osborn & Jerry Coakley & Simone D. Grose & Gael M. Martin & Donald S. Poskitt, 2015. "Bias Correction of Persistence Measures in Fractionally Integrated Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 721-740, September.
    3. Lenard Lieb & Stephan Smeekes, 2017. "Inference for Impulse Responses under Model Uncertainty," Papers 1709.09583, arXiv.org, revised May 2018.
    4. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, Elsevier.
    5. 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.

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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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