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Skewness-adjusted bootstrap confidence intervals and confidence bands for impulse response functions

Author

Listed:
  • Daniel Grabowski

    (University of Giessen)

  • Anna Staszewska-Bystrova

    (University of Lodz)

  • Peter Winker

    (University of Giessen)

Abstract

Inference on impulse response functions from vector autoregressive models is commonly done using bootstrap methods. These methods can be inaccurate in small samples and for persistent processes. This article investigates the construction of skewness-adjusted confidence intervals and joint confidence bands for impulse responses with improved small sample performance. We suggest to adjust the skewness of the bootstrap distribution of the autoregressive coefficients before the impulse response functions are computed. Using extensive Monte Carlo simulations, the approach is shown to improve the coverage accuracy in small- and medium-sized samples and for unit-root processes.

Suggested Citation

  • Daniel Grabowski & Anna Staszewska-Bystrova & Peter Winker, 2020. "Skewness-adjusted bootstrap confidence intervals and confidence bands for impulse response functions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(1), pages 5-32, March.
    • Handle: RePEc:spr:alstar:v:104:y:2020:i:1:d:10.1007_s10182-018-00347-9
    DOI: 10.1007/s10182-018-00347-9
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    More about this item

    Keywords

    Bootstrap; Confidence intervals; Joint confidence bands; Vector autoregression;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: 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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