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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

This article investigates the construction of skewness-adjusted confidence intervals and joint confidence bands for impulse response functions from vector autoregressive models. Three different implementations of the skewness adjustment are investigated. The methods are based on a bootstrap algorithm that adjusts mean and skewness of the bootstrap distribution of the autoregressive coefficients before the impulse response functions are computed. Using extensive Monte Carlo simulations, the methods are shown to improve the coverage accuracy in small and medium sized samples and for unit root processes for both known and unknown lag orders.

Suggested Citation

  • Daniel Grabowski & Anna Staszewska-Bystrova & Peter Winker, 2018. "Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions," MAGKS Papers on Economics 201810, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    • Handle: RePEc:mar:magkse:201810
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    References listed on IDEAS

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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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